the ecological sustainability of short fallow shifting cultivation in upland systems
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F A C U L T Y O F S C I E N C E
U N I V E R S I T Y O F C O P E N H A G E N
Master’s Thesis
Catherine M Hepp
The Ecological Sustainability of Short Fallow Shifting
Cultivation in Upland Systems A Study in Northern Lao PDR, Southeast Asia
Academic Advisor: Thilde Bech Bruun, Assistant Professor
Department of Plant and Environmental Sciences
University of Copenhagen
Submitted: 31/07/13
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Photograph Credits: Catherine M. Hepp
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Name of department: Department of Plant and Environmental Sciences
Author: Catherine M Hepp
Title / Subtitle: The Ecological Sustainability of Short Fallow Shifting Cultivation in Upland Systems / A study in Northern Lao PDR in Southeast Asia
Subject description: The impact of shorter fallow lengths on the ecological sustainability of shifting cultivation in Lao PDR, specifically in terms of soil quality and upland rice yields. The drivers of the decreasing fallow length are also discussed and how such changes will affect the livelihood strategies of upland populations.
Academic advisor: Thilde Bech Bruun, Assistant Professor
Submitted: 31. July, 2013
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ǁ Abstract
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Abstract The Ecological Sustainability of Short Fallow Shifting Cultivation in Upland Systems A Study in Northern Lao PDR, Southeast Asia
C. M. Hepp Dept. of Plant and Envrionmental Sciences, Faculty of Science, University of Copenhagen, Denmark
Shifting cultivation in Southeast Asia is rapidly transforming due to increased land pressure, governmental policies and improved access to infrastructure and markets. The forced use of shortened fallow lengths questions its ecological sustainability, a concern as the livelihoods of resource-poor farmers may be affected. The objective of the study was to assess the ecological sustainability of short fallow shifting cultivation systems in Lao PDR; specifically, how fallow length and topography influence soil quality and upland rice yields. Upland fields of 2-, 3-, 5-, 10- and 11-year fallows of similar topography, parent soil and land use history were selected; the 5-year fields were used to assess topographical influence. Soil organic carbon and permanganate oxidisable carbon were identified as key indicators of soil quality as they were positively correlated to the soil nutrients, N, P and K, and led to higher upland rice yields. Although fields of longer fallows were associated with higher yields, no such correlations were found with soil quality; the positive association between fallow length and upland rice yields may rather reflect weed suppression, less pest or disease infestation or a combination. The results indicate that a length of five years for fallow will give the greatest return to the soil; the increase in upland rice yields when fallowed for longer than five years will depend on the technical skill and management practices of the farmer. Soil quality or upland rice yields were not significantly influenced by slope position, thus erosion is not a major constraint; nitrogen and potassium show an accumulation at the bottom of the slope possibly due to leaching effects and the downward movement of ash. It appears the use of appropriate scales in such studies whereby soil quality and yields are both measured from marked plots will improve accuracy. The impact of fallow length on soil quality and upland rice yields remains ambiguous; more future studies at the plot level are required as such findings will have implications for governmental policy reforms and the livelihoods of the rural poor.
Key Words: Lao PDR, shifting cultivation,ecological sustainability, upland rice, soil quality, fallow length, slope position, Pox C, SOC
Preface ǁ
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Preface
This thesis is for the completion of a M.Sc. in Agricultural Development from the Faculty of Science
at the University of Copenhagen, Denmark. The study was partially funded by the University of
Copenhagen. It is written from an agricultural development perspective with the intention of
assessing the ecological impacts of intensification on traditional upland systems.
Mandatory field work in a developing country was carried out in Northern Lao PDR from September
to the end of November 2012. The host institution was the National University of Lao PDR. Field
sites were located in the Ban Navene area, a relatively remote village located in the Viengkham
District of the Louangphabang province. The duration of field work was spent in Ban Navene and
thus exposure to and involvement in everyday life activities occurred. Data was collected with the
help of a translator who spoke both Lao and Khamu.
Soil analysis was completed at three different institutions: the Pox C analysis was done at the
Department of Soil and Environmental Resources of the Faculty of Agricultural Production at Maejo
University in Chiang Mai, Thailand; soil samples were sent to the Soils and Fertilizers Research
Institute (SFRI) in Hanoi, Vietnam for textural and chemical analysis; and finally, pH and carbon and
nitrogen content measurements were completed at the Dept of Plant and Environmental Sciences,
Faculty of Science of the University of Copenhagen.
ǁ Acknowledgements
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Acknowledgements
This thesis would not have been possible without the support and assistance of numerous people
and institutions. I would first like to express my sincere gratitude to my academic advisor, Thilde
Bech Bruun, for her support and guidance throughout the study. Her invaluable insight, experience
and knowledge were a continuous source of encouragement and what led me to undertake this
study in the first place. Furthermore I would like to extend my appreciation for the Agricultural
Development programme (Faculty of Science, University of Copenhagen) and its programme
director, Andreas de Neergaard, for the supportive academic environment. Additionally, I would like
to thank the staff and peers from the Dept of Plant and Environmental Sciences for their assistance
with numerous aspects of the soil analysis and final stages of the study.
I would like to thank Ms. Somvilay Chanthalounnavong at the Faculty of Forestry of the National
University of Laos as her guidance made my stay in Lao PDR possible. Special thanks go out to Ms.
Supathida Aumtong, Assist. Prof., and the Department of Soil and Environmental Resources (Faculty
of Agricultural Production, Maejo University, Thailand) for generously making their facilities and
expertise available to me. I would furthermore like to extend my gratitude to Mr. Kronpech Srisoy
and his fellow peers for hosting me during the week and making my stay at Maejo truly enjoyable.
My sincere thanks go to Mr. Phaeng Xaphokhame, my interpreter, and DAFO (Viengkham district,
Lao PDR). Without Mr. Xaphokhame’s guidance and valuable knowledge, the study and data
collection would not have been attainable.
Last but not least, I would like to express my eternal gratitude to the Headman, Thong Phouy, his
family and the people of Ban Navene who graciously welcomed me into their community for the
duration of my field work. I feel privileged to have been given such an honour and opportunity as to
share in their daily life activities and Khamu culture. My stay is an experience I will truly treasure and
I hold the memories dear to my heart.
Catherine M. Hepp
July 31, 2013
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Table of Contents
Abstract ............................................................................................................................................... v
The Ecological Sustainability of Short Fallow Shifting Cultivation in Upland Systems .......... v
A Study in Northern Lao PDR, Southeast Asia ....................................................................................... v
Preface ............................................................................................................................................... vi
Acknowledgements ...................................................................................................................... vii
List of Tables ................................................................................................................................... xii
List of Figures ................................................................................................................................ xiii
Appendices .................................................................................................................................... xiv
1 Introduction ............................................................................................................................. 1
1.1 Research Objective ............................................................................................................................... 1
2 Theoretical Background ...................................................................................................... 3
2.1 Soil Quality: Indicators and their Significance ........................................................................... 3
2.1.1 Inherent Physical Properties .................................................................................................................. 3
2.1.2 Dynamic Properties .................................................................................................................................... 3
2.2 Shifting Cultivation: a description .................................................................................................. 5
2.2.1 The Role of Burning .................................................................................................................................... 6
2.2.2 The Importance of Fallow Length ......................................................................................................... 6
2.2.3 The Impact of Shortened Fallows ......................................................................................................... 7
2.2.4 Topography: Does it have an Influencing Role?.............................................................................. 8
2.3 The Drivers of Decreasing Fallow Lengths .................................................................................. 8
2.3.1 Demographical Change ............................................................................................................................. 8
2.3.2 Political Influence ........................................................................................................................................ 9
2.3.3 The Development and Expansion of Commercial Agriculture.................................................. 9
2.4 Livelihood Strategy Implications .................................................................................................. 10
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3 Methodology ........................................................................................................................... 11
3.1 Study Site Description ....................................................................................................................... 11
3.2 Identification of Fields ...................................................................................................................... 13
3.3 General Plot Layout ............................................................................................................................ 13
3.3.1 Soil Sampling and Analysis ................................................................................................................... 14
3.3.2 Yield Assessments .................................................................................................................................... 15
3.4 Calculations and Statistical Analysis ............................................................................................ 15
3.5 Constraints of Upland Rice Production ....................................................................................... 17
3.6 Farmers’ Perception .......................................................................................................................... 17
3.7 Future Perspectives ........................................................................................................................... 18
4 Results ...................................................................................................................................... 19
4.1 Soil Quality Analysis ........................................................................................................................... 19
4.1.1 General Soil Description ........................................................................................................................ 19
4.1.2 Soil Parameter Interactions ................................................................................................................. 20
4.2 Implications of the Soil Quality on the Yield of Upland Rice ............................................... 27
4.2.1 Soil Parameter Influences on Yield ................................................................................................... 27
4.2.2 Stock Values and Yield ............................................................................................................................ 31
4.3 System Influences ............................................................................................................................... 32
4.3.1 Topographical Influence ........................................................................................................................ 32
4.3.2 Fallow Length Impact ............................................................................................................................. 34
4.3.3 Alternative Measures of Land Use Intensity ................................................................................. 39
4.4 From the Farmers’ Perspective ...................................................................................................... 40
4.4.1 Historical and Socioeconomic Context for Ban Navene ............................................................ 40
4.4.2 The Establishment of the NEPL NPA ................................................................................................ 42
4.4.3 The Constraints of Upland Rice Production .................................................................................. 42
5 Discussion ............................................................................................................................... 45
5.1 Ban Navene- a village in transition ............................................................................................... 45
5.2 The Ecological Sustainability .......................................................................................................... 45
5.2.1 Soil Quality: the Parameters and Their Interactions ................................................................. 46
5.2.2 The Link between Soil Quality and Upland Rice Yield .............................................................. 49
5.2.3 System Influence: the topography of a field .................................................................................. 51
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5.2.4 System Influence: the fallow length .................................................................................................. 52
5.2.5 Quantitative Experimental Design: a reflection ........................................................................... 56
5.3 What is Driving the Decrease of Fallow Lengths in Ban Navene? ...................................... 58
5.3.1 Demographical Changes ........................................................................................................................ 58
5.3.2 Political influences ................................................................................................................................... 59
5.3.3 The Development and Expansion of Commercial Agriculture............................................... 61
5.4 The Implications for Upland Rice Productivity: From the Farmers’ Perspective ........ 62
5.4.1 The Constraints to Upland Rice Production .................................................................................. 62
5.5 The Implications for Livelihood Strategies ............................................................................... 64
5.5.1 Livelihood Security .................................................................................................................................. 64
5.6 Future Prospects for Ban Navene .................................................................................................. 66
6 Conclusion ............................................................................................................................... 67
7 Personal Reflection .............................................................................................................. 69
8 References .............................................................................................................................. 71
9 Appendices ............................................................................................................................. 75
List of Tables ǁ
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List of Tables
Table 1: The range and correlations of soil parameters at the soil surface of fields ............................ 21
Table 2: The range and correlations of soil parameters at a 10 cm depth of fields ............................. 22
Table 3: The range in soil parameters at depths of thirty cm of fields ................................................. 23
Table 4: Multiple stepwise regression results for the dependent factor, yield, for the soil surface at a confidence level of 99% (p<0.05). ............................................................................................ 30
Table 5 The clay and carbon content (0-5 cm) at the top, middle and bottom of a continuous slope. .................................................................................................................................................. 32
Table 6:The nutrient stocks at the soil surface and at a depth of 10 cm according to the topographical positions within a slope: top, middle and bottom. .......................................... 33
Table 7: The yield in upland rice assessed directly from plots placed at the top, middle and bottom of a continuous slope. .............................................................................................................. 34
Table 8: The carbon concentrations of fields grouped according to the duration of the preceding fallow¹ ....................................................................................................................................... 35
Table 9: The C:N and SOC:Pox C ratios of fields grouped according to the duration of the preceding fallow¹ ....................................................................................................................................... 35
Table 10: The stocks of Pox C, N, P Avail and K Exch of the upper 10 cm in an eqv mass according to fallow lenght............................................................................................................................. 37
Table 11: The major pre-determined constraints to upland rice production for shifting cultivators in Ban Navenea ............................................................................................................................. 43
ǁ List of Figures
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List of Figures
Figure 1: The nutrient availability as a function of soil pH. .................................................................... 3
Figure 2: Landscape typical for shifting cultivation ................................................................................ 5
Figure 3: Theoretical illustration of the relationship between fallow length (x-axis) and soil productivity (y-axis) ................................................................................................................. 6
Figure 4: The location map of Lao PDR and approximate location of the study site ........................... 11
Figure 5 : A schematic drawing representing Ban Navene and its surrounding area. ......................... 12
Figure 6: (a) Diagram depicting the plot design and (b) layout ............................................................ 14
Figure 7: The flashcards used for the pairwise ranking method .......................................................... 17
Figure 8: Sheang’s father, a key informant .......................................................................................... 17
Figure 9: The participants of the group meeting held at the Ban Navene School ................................ 18
Figure 10: Soil profile of the ultisol typical for the Ban Navene area ................................................... 19
Figure 11: Relationship between carbon and nitrogen soil content depicted by SOC % and N%. ....... 24
Figure 12: Relationship between SOC % and a) P Avail and b) K Exch .................................................. 25
Figure 13: The relationship between SOC % and Pox C ....................................................................... 26
Figure 14: Relationship between Pox C and N% ................................................................................... 27
Figure 15: The relationship between upland rice yield and pH ........................................................... 28
Figure 16: The relationship between upland rice yield and Pox C ....................................................... 28
Figure 17: The relationship between upland rice yield, Pox C and a) N% and b) C:N .......................... 29
Figure 18: The relationship between upland rice yield (kg·ha¯¹) and the upper 10 cm quantities, in equivalent masses of soil, 81 kg, of a) SOC, b) N, c) P Avail and d) K Exch. ........................... 31
Figure 19: The relationship between SOC stocks of the upper 10 cm in an equivalent mass of soil, 88.24 kg, and fallow length ................................................................................................... 36
Figure 20: The yield (kg · ha-1) in upland rice after a preceding fallow of 2, 3, 5, 10 or 11 years ......... 37
Figure 21: Relationship between SOC stock and Stock N ..................................................................... 38
Figure 22: The relationship between yield (kg · ha-1) in upland rice and alternative land use intensity measures ............................................................................................................................... 39
Figure 23: The historical timeline of Ban Navene from its establishment in 1910 to the present date, 2012 ....................................................................................................................................... 40
Figure 24: The population growth of Ban Navene from 1985 - 2012 .................................................. 41
Figure 25: Rice with a dead panicle of unfilled grains, termed ‘whitehead’ and indicative of stem borer infestation or rice blast (IRRI, 2009). ........................................................................... 42
Figure 26: The impressed tortoise (M. impressa), a vulnerable species found in the NEPL NPA illegally trapped .................................................................................................................................. 60
Figure 27: Thong La, the maize company, husking the stored maize, 11/12 ...................................... 61
Appendices ǁ
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Appendices
1 Methodolgy ................................................................................................................. 75
1.1 Survey for Field Identification ................................................................................................................ 75
1.2 Visual Observations/ Characteristics for Field ........................................................................................ 76
1.4 Protocol for Pox C .................................................................................................................................. 77
1.5 Standard Curve of Pox C Analysis ........................................................................................................... 78
1.6 Guiding Questions for In-Depth Farmer Interviews................................................................................ 79
1.7 Guiding Questions for NEPL NPA Land loss Effects ................................................................................. 81
1.8 Guiding Questions for Group Interview ................................................................................................. 82
2 Field Record Sheet ..................................................................................................... 83
3 Map of Field Locations Depicting Area (ha) ............................................................. 84
4 Soil Data Summaries.................................................................................................. 85
4.1 Physical and Chemical Parameters at the Surface, 10 cm and 30 cm of the Fallow Length Study ........... 85
4.2 The Carbon and Nitrogen Parameters of the Fallow Length Study ......................................................... 86
4.3 The Carbon and Nutrient Upper 10 cm Stocks (kg m-2
) using a fixed depth or mass equivalent approach of the Fallow Length Study .................................................................................................................... 87
4.4 Pox C levels (mg kg-1
) at the Soil Surface and 10 cm depth of the Fallow Length Study .......................... 87
4.5 Physical and Chemical Parameters at the Surface, 10 cm and 30 cm of the Topographical Study .......... 88
4.6 The Carbon and Nitrogen Parameters of the Topographical Study ........................................................ 89
4.7 The Carbon and Nutrient Upper 10 cm Stocks (kg m-2
) using a fixed depth or mass equivalent approach of the Topographical Study .................................................................................................................... 90
4.8 Pox C levels (mg kg-1
) at the Soil Surface and 10 cm depth of the Topographical Study ......................... 91
5 Results ........................................................................................................................ 92
5.1 Interactions between Soil Quality and Upland Rice Yield ....................................................................... 92
5.2 System Influence: Topographical Influence on Upland Rice Yield .......................................................... 93
6 List of Interviewees and Informants ......................................................................... 94
7 Ranking of the Constraints to Upland Rice Production .......................................... 95
Research Objective ǁ Introduction
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1 Introduction
Agricultural systems in developing regions are shifting from subsistence farming to more specialised
and commercialised types, a goal of many national policies as this is often seen as a necessary step
for economic growth and development. The process is a step-wise transition where traditional
shifting cultivation, a once widespread form of subsistence farming in the upland areas of Southeast
Asia (Ziegler et al., 2011), is slowly replaced by permanent cropping systems, commonly with cash
crops such as maize, oil palm or rubber (Cramb et al., 2009; Ziegler et al., 2011).
The replacement of traditional shifting cultivation as a livelihood strategy, where upland rice is
commonly the dominant crop, is accelerated by demographical changes, governmental policies and
reform, the development and improved access to markets and sociocultural trends (Cramb et al.,
2009; Roder, 1997; Ziegler et al., 2011). The consequences on livelihood strategies are poorly
understood and will depend greatly on the resource endowment of the affected rural villages, often
of ethnic minority (Roder, 1997). A livelihood strategy change, in turn, will affect food security and
will have repercussions for the ecological sustainability (Cramb et al., 2009).
Where shifting cultivation is retained, intensification will lead to the implementation of shorter
fallows, a trend that has been widely observed in Southeast Asia (Schmidt-vogt et al., 2009); shorter
fallows are often the only viable intensification strategy as the adoption of alternatives, such as
permanent cropping, is difficult in upland areas as they are steep, exposed to high precipitation
levels and have generally poor soils (Cramb et al., 2009). The decline in fallow length, the central
ecological principal through which soil fertility is restored (Bruun et al., 2009), is thought to lower
upland rice yields, increase weeds, degrade soil and result in a lower return to labour (Bruun et al.,
2006; Mertz, 2002; Mertz et al., 2013); this is often termed the ‘downward spiral’ of shifting
cultivation and has negatively influenced the policies of developing countries as it is thought as
unsustainable (Cramb et al., 2009; Lestrelin & Giordano, 2007).
However, a direct causal link between the decline in fallow length and the assumed downward spiral
has been difficult to prove and the effects remain somewhat ambiguous. As shifting cultivation
supports the livelihoods of the majority of the poor upland populations in Southeast Asia, a clearer
understanding of the full impacts of the intensification is preeminent.
1.1 Research Objective
Considering this lack of understanding, the main objective of the study is to investigate the impact
short-fallow shifting cultivation, an intensification strategy, will have on the livelihoods of upland
populations, specifically from an ecological perspective. Emphasis is placed on the consequence of
short fallow lengths on upland rice yields and soil quality, both intricately-linked to the ecological
sustainability of the system and, in a broader sense, to food security.
The assessment is made difficult as there are numerous parameters that will play an influencing role;
upland rice yields are a product of both socioeconomic, i.e. land use history and fertilizer inputs, and
Introduction ǁ Research Objective
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ecological parameters, i.e. inherent soil properties or the burn quality. Past studies are not
consistent in which parameters have been controlled hence it is difficult to isolate the actual impacts
caused by shorter fallow lengths and to compare results. A major challenge for past studies has
been to find areas where external inputs such as fertilizers are not used and how to account for their
effect on soil quality.
Any circumstance therefore in which the parameters can be better controlled would facilitate the
study. This was a strong point for why a relatively isolated village in Northern Lao PDR was the
selected study location; it is a country with a high proportion of its population dependent on shifting
cultivation thus systems of various intensities can be found and, furthermore, farmers lack the
resources for external soil inputs. This helps lower the possibility that any ecological impact
observed is a mere consequence of an unrelated parameter.
The objective will be achieved through the following research question:
How does the fallow length affect the soil quality and upland rice yield in a shifting cultivation
system of Northeastern Lao PDR?
i. How have the fallow lengths changed in Ban Navene, a village of Khamu ethnicity
since 1985, and what are the drivers?
ii. What are the major constraints to upland rice production? Have the farmers
perceived a change in soil quality and upland rice yields?
iii. How do the soil’s properties, specifically the total carbon and nitrogen content,
plant-available minerals and nutrients, pH and cation exchange capacity, interact to
give an overall impression of soil quality? How are soil quality and upland rice yield
linked?
iv. How does the topography of a cultivated field affect the soil quality and upland rice
yield?
v. Is the fallow length correlated to soil quality, specifically the total carbon and
nitrogen content, plant-available minerals and nutrients, pH and cation exchange
capacity?
vi. What impact does the fallow length have on the yield of hill rice, without the
addition of chemical or organic fertilizers?
Soil Quality: Indicators and their Significance ǁ Theoretical Background
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2 Theoretical Background
2.1 Soil Quality: Indicators and their Significance
Soil quality in this context is defined as the ability of the soil to support and maintain crop
production and incorporates physical, chemical and biological parameters (Bruun et al., 2009; Brady
and Weil, 1999). Management practices will influence soil parameters of varying sensitivities (Brady
and Weil, 1999); it is thus important that suitable soil parameters are chosen as indicators of soil
quality to determine the extent of soil degradation, if any. The parameters selected to explore soil
quality are the inherent physical properties (CEC and clay content), bulk density, soil organic carbon
(SOC) and permanganate oxidisable carbon (Pox C) content, and the nutrient levels of total nitrogen
(N), available phosphorus (P Avail) and exchangeable potassium (K Exch). Additional calculations
using the listed parameters can give further insight into soil quality levels; i.e. C:N ratio, SOC:Pox C
ratio and carbon and nutrient stocks.
2.1.1 Inherent Physical Properties
One of the defining characteristics of a highly weathered tropical
soil is its acidity and the consequential implications (Brady and Weil,
1999). At low pH, soil colloids will preferentially adsorb soluble iron
and aluminum ions; when hydrolysed, the adsorbed iron and
aluminum ions will produce hydrogen ions thereby contributing to
the acidity (Brady and Weil, 1999). The implication of pH on the soil
quality is considerable as it is strongly tied to nutrient availability
and will thus influence crop yield levels (Figure 1).
The clay content of a soil will have considerable implications for the
soil quality; clay colloids are influential determinants of the
chemical properties of a soil due to their unbalanced negative
charges (Weil and Brady, 1999).
2.1.2 Dynamic Properties
The dynamic properties of a soil are insightful as they will react to
agricultural management practices however in varying degrees of sensitivity. Nevertheless, the
sustainability of a shift in management practices can be assessed through such parameters.
2.1.2.1 Soil Organic Carbon Content
SOC, in primary association with soil organic matter (58%), is a commonly measured soil parameter
because of its key role in the global carbon cycle and its response to anthropogenic activities. The
SOC content of a soil has significant implications for soil quality; it is an important source of plant
nutrients (N,P,K) and CEC, acts as a buffer against acidity and Al- toxicity, improves soil aggregation
Figure 1: The nutrient availability as a function of soil pH Source: University of Minnesota (2009)
Theoretical Background ǁ Soil Quality: Indicators and their Significance
4
and stability, and it enhances the water holding capacity and infiltration (Bruun et al., 2009). Hence
it is intricately-linked to the other investigated parameters.
Bulk density is defined as the mass per unit volume of dry soil whereby the volume includes the
solids and pores (Brady and Weil, 1999); a greater proportion of pore space will correlate to a lower
bulk density. Bulk density is a function of both soil organic matter and the clay content of a soil due
to their positive influence on pores between and within the soil granules (Brady and Weil, 1999). A
fine-textured soil, characterized by higher clay content, will have aggregates of porous granules and
hence, the total pore volume be greater. This translates to a lower bulk density and indicates
favourable physical conditions for crop growth.
Funakawa et al. (1997) found soil organic matter to be a determinant of plant-available nitrogen.
The mineralization of nitrogen by soil microbes is the main source for plant uptake and is heavily
reliant on the C:N ratio. Nitrogen immobilization, i.e. its incorporation into the cells of
microorganisms, will be determined by the C:N ratio and will occur if it is greater than 25 (Brady and
Weil, 1999).
Likewise, P Avail and K Exch levels are influenced by the SOC. The mineralization of organic
phosphorus to its inorganic plant-available form is important as the added phosphorus will become
quickly fixed by the Al- and Fe-oxides (Brady and Weil, 1999). SOC degradation supplies K Exch as it
is largely determined by the plant and animal residues that are returned to the soil; K Exch will
quickly leach through a soil and can be a limiting factor in production (Brady and Weil, 1999).
2.1.2.2 Permanganate Oxidisable Carbon
Studies suggest that SOC levels of a soil are too insensitive to land use changes to be of any use in
detecting soil degradation (Aumtong et al., 2009). As a result, a magnitude of varying methods have
been proposed of which target different fractions of the SOC pool higher in sensitivity, one of which
is the Pox C method (Aumtong et al., 2009).
The use of Pox C as a sensitive indicator of the effects land use changes may have on the soil quality
has been proposed by several studies (Aumtong et al., 2009; Culman et al., 2012); however the
exact fraction of the carbon pool it reflects is not well understood (Aumtong et al., 2009; Culman et
al., 2012; Tirol-Padre & Ladha, 2004). It is commonly said to represent the most readily oxidisable
carbon such as plant litter, microbial biomass and non-humic substances that are not bound to
minerals (Tirol-Padre & Ladha, 2004; Weil et al., 2003). The Pox C content of a soil will influence soil
quality considerably and in a similar matter to that of SOC; as soil microbes readily degrade the labile
carbon, nutrients will be converted to plant-available forms with obvious implications for crop yields.
It is important to assess the changes in the various carbon pools as their sensitivities towards change
and activity levels are different; a greater change in the labile carbon pool will have larger
implications for soil fertility when compared to non-labile carbon (Blair et al., 2001). This has led to
the development of a carbon management index (CMI) by Blair et al. (2001) in which the changes in
the various carbon pools, relative to one another, can be compared to reference levels; the index
will give a clearer picture of the full impacts of management practices seen sooner than if only SOC
Shifting Cultivation: a description ǁ Theoretical Background
5
content was measured. Alternatively, if no reference soil is available, the similar parameter, SOC:Pox
C, may reflect the respective carbon pool changes.
2.2 Shifting Cultivation: a description
The definition of shifting cultivation is debated but the majority agree that it refers to a smallholder
agricultural system that implores the use of fallow as a means to restore productivity, usually with
no addition of external inputs such as fertilizers (Lestrelin et al., 2012; Mertz, 2002; Mertz et al.,
2009). The farmers will rotate between their upland fields usually in a cyclic manner (Cramb et al.,
2009). Commonly, local varieties of upland rice are the main crop of shifting cultivation produced
for subsistence needs; upland rice may be sold or exchanged for labour, market food, goods such as
clothes or fuel, or when health supplements or services are required (Seidenberg et al., 2003).
The fallow phase, the central ecological
principle, works to repress weeds and restores
soil quality (Bruun et al., 2006; Mertz, 2002;
Mertz et al., 2008). The regenerating fallow
vegetation will absorb nutrients and return
them to the soil surface as litter or, when cut
and burned, in a biologically active form
(Bruun, et. al., 2009). Essentially it counteracts
the tendency for the decline in nutrient
availability caused by crop export, leaching and
volatilisation of nitrogen and sulphur during the
burning (Bruun et al., 2006; Mertz, 2002).
Furthermore, the biodiversity of the fallow
vegetation is an important source of NTFPs and
account for 40 – 60% of the income of rural
households (Moore et al., 2011)
Shifting cultivation is often the main land use strategy of ethnic minorities who live in remote upland
areas with poor soil and who contend with a limited access to markets, socioeconomic benefits and
communication (Figure 2; Roder, 1997). The system is often the only available livelihood strategy
and is thus seen as environmentally and economically sound for such populations, especially when
compared to other intensified and commercialised systems (Nielsen et al., 2006; Roder, 1997; Vien
et al., 2006).
Figure 2: Landscape typical for shifting cultivation where a mosaic of upland rice plots and regenerating fallow of variable age are seen. Taken in the upland area of Northern Lao PDR.
Theoretical Background ǁ Shifting Cultivation: a description
6
2.2.1 The Role of Burning
The slash-and-burning of fallow vegetation is meant to resupply the soil with nutrients lost to crop
uptake. The amount of nutrients returned to the soil is highly dependent on the ash, directly linked
to the burn success of a field, and hence should be taken into account when considering the soil
quality (Andriesse & Schelhaas, 1987). The burn quality, in terms of moisture and fuel content, the
nutrient content of the fallow vegetation and the temperature thresholds of the respective nutrient
will determine the mineral nutrient content found in the ash (Andriesse & Schelhaas, 1987).
The levels of nitrogen in a soil are important when considering soil quality as it is commonly a
limiting factor in upland rice production (Roder et al., 1995) as the volatilisation losses during the
burning of fallow vegetation are high due to its low temperature threshold (Bruun et al., 2006). The
microbial biomass is a source of soil nitrogen both in regards to the mortality that occurs during the
burn and the enhanced microbial activity after burning, a consequence of the warm temperature
and increased carbon and nutrient content (Bruun et al., 2006).
Though the ash will contain some phosphorus due to its relatively high temperature threshold, the
mineralization is still important as any additional supply is beneficial since phosphorus will be quickly
fixed by the Al- and Fe-oxides (Andriesse & Koopmans, 1984; Brady & Weil, 1999). Phosphorus
content of the soil in a shifting cultivation system is thus determined in a similar manner to that of
nitrogen: by the soil organic matter concentration, the microbial mortality during burning and the
enhanced microbial activity thereafter (Bruun et al., 2006). Potassium availability for plant uptake is
dependent on the amount stored in the aboveground fallow vegetation, which will be transferred to
the soil via ash deposit (Bruun et al., 2006).
2.2.2 The Importance of Fallow Length
The length of fallow will impact the nutrients returned
to the soil as it influences the species composition and
biomass of the fallow vegetation (Bruun et al., 2009).
In the tropics, the biomass accumulation rate of the
secondary vegetation will be the greatest during the
first ten years and will then start to slow (Jepsen,
2006).
These factors, as discussed, will in turn affect the
levels of nutrients returned to the soil during burning.
Some suggest a minimum fallow length requirement
to maintain crop and soil productivity (Cramb et al.,
2009; Mertz, 2002; Mertz et al., 2009; Nielsen et al.,
2006); however the exact length is difficult to
pinpoint. Studies have found different lengths
necessary, as depicted in Figure 3 (Mertz, 2002), and
will vary according to climate and management
Figure 3: Theoretical illustration of the relationship
between fallow length (x-axis) and soil productivity (y-axis); a and b both represent sustainable systems. From
Mertz, 2002.
Shifting Cultivation: a description ǁ Theoretical Background
7
(Bruun et al., 2009); in some areas, fallow lengths of 8-20 years with two or three years of successive
cropping are adequate in maintaining soil quality however it is largely dependent on the initial
condition of the soil (Mertz, 2002). Furthermore, the number of cultivation cycles, length of
cropping periods or field size will reduce biomass accumulation and, thus, the nutrients available to
the subsequent crop (Bruun, et. al., 2009).
2.2.3 The Impact of Shortened Fallows
Although the impacts still remain ambiguous, the general theory that shortened fallow lengths will
lead to a system breakdown has been widely accepted and taken for granted (Mertz et al., 2009).
With no external inputs, it is thought that shorter fallow lengths will lead to lower yield levels
because of a decline in nutrient availability, higher rates of weed infestation and poorer soil physical
properties (Mertz, 2002).
The difficulty lies in that ‘real life’ situations are diverse. To accurately assess if fallow length affects
soil quality and upland rice yields, the investigated parameters must be kept identical across study
sites; this is difficult due to variations in the physical and spatial environment, inherent soil
properties and farmers’ land use decisions and management practices as they contribute to the
productivity of the system (Aumtong et al., 2009; Mertz et al., 2008; Roder et al., 1995).
The effect of fallow length on soil quality has been difficult to quantify and results from studies have
been inconsistent as to which parameters are significantly affected. Roder et al. (1995) found a
weak positive association between SOC content and fallow length, while Bruun et al. (2006) found
plant available nitrogen to be positively correlated with fallow length instead. SOC content does
appear to be an important indicator of soil quality in general as it does respond to different land use
strategies and is influenced by a soil’s clay content and CEC (Aumtong et al., 2009).
The theoretical relationship between fallow length and upland rice yields has been difficult to prove.
Bruun et al. (2006) found fallow length to be an indicator of upland rice yield levels in Sarawak
Malaysia; however the rice density and degree of intercropping were not considered and
management practices were assumed to be constant, weaknesses of the study.
Whether fallow length has a larger function in restoring soil fertility or suppressing weed populations
also remains ambiguous; studies that have found accurate links between fallow length and weed
density are lacking. A study by Roder et al. (1995) found no links between fallow length and weed
density in Northern Lao PDR. However suggestions have been made stating that the higher yields
observed are rather a function of the fallow length’s influence on weed density and not on soil
quality (Mertz, 2002).
Theoretical Background ǁ The Drivers of Decreasing Fallow Lengths
8
2.2.4 Topography: Does it have an Influencing Role?
Many studies refer to the hilly topography characteristic of upland areas as a major limitation to
production(Bruun et al., 2009; Mertz et al., 2008; Roder, 1997; van Vliet et al., 2012) and will
accelerate land degradation especially in light of the decreasing fallow lengths; however the
influence of topography remains ambiguous as there are few studies. Of these studies, the majority
have investigated the degree of erosion through the measurements of sediment runoff; fewer still
have looked at soil quality in relation to slope position or its implications for upland rice yields.
It appears erosion is not as limiting as theoretically expected when measuring sediment runoff in Lao
PDR (Lestrelin et al., 2012). This is reflected in the finding by Roder et al. (1995) where erosion was
not identified as a major constraint to upland rice production.
The general soil quality does not appear to be significantly influenced by slope position (Aumtong et
al., 2009; de Neergaard et al., 2008). Aumtong et al. (2009) found carbon stocks to be unaffected by
slope position in Northern Thailand. The same result was found in Sarawak Malaysia by de
Neergaard et al. (2008) however there does appear to be an accumulation of base cations at the
slope bottoms. It was suggested that this pattern is not due to erosion per se but rather to the
downward movement of ash by wind and water and leaching (de Neergaard et al., 2008).
2.3 The Drivers of Decreasing Fallow Lengths
Cramb, et al. (2009) have defined three main causes for the trend of intensification: demographical
change, the development and expansion of markets for commercial agriculture, i.e. cash crop
integration, and policy reform. Each will increase pressure on the traditional shifting cultivation
system whereby a reduction in fallow lengths will occur (Cramb et al., 2009); in remote upland areas
with poor soils, a reduction in fallow length is often the only viable option as no alternative
livelihood strategy is available (Roder, 1997).
2.3.1 Demographical Change
Boserup’s (1965) model for agrarian change stipulates that the main driver of the change from
shifting cultivation to permanent cropping systems is population pressure; an increase in population
will add strain to the traditional system whereby the principle change is an increase in intensification
either through a decrease in fallow length or the cultivation of permanent crops. Population growth
will cause additional changes in land use strategies, agricultural technology, village locations and
land tenure systems (Boserup, 1965).
The Drivers of Decreasing Fallow Lengths ǁ Theoretical Background
9
The out-migration of younger generations to urban areas is a widespread trend in Southeast Asia,
one that will further promote the intensification of shifting cultivation (Cramb et al., 2009; Hansen &
Mertz, 2006; Ziegler et al, 2011). This trend will place added pressure on the labour availability; if
labour supply is limited, upland fields in close proximity to villages will be more intensively cropped
and long fallows will no longer be favoured due to the high labour requirement of falling large trees
(Nielsen, et. al., 2006; Roder, 1997).
2.3.2 Political Influence
The general notion that the system is ‘backwards’ and must be replaced if modern development is to
occur has been pushed by governmental representatives and has hastened the demise of shifting
cultivation (Cramb et al., 2009). Governmental policy reform and programmes have strained
extensive shifting cultivation as they have involved land use classification, resettlement of villages
and land privatization (Fox et al., 2009). The regulations are often restrictive in nature and thus
discourage shifting cultivation as a suitable land use form (Cramb et al., 2009). Shifting cultivation
has been mandated to specific land classes, meaning that it has been restricted to certain areas
outside defined forest reserves, protected areas and community forests (Cramb et al., 2009; Fox et
al., 2009). It is hoped that this will ultimately lead to the discouragement of shifting cultivation as
the required intensification will be deemed unsustainable (Moore et al., 2011).
2.3.3 The Development and Expansion of Commercial Agriculture
Often the commercialisation of agriculture will include the integration of cash crop cultivation and
livestock; both trends are seen in Southeast Asia and lower the reliance on shifting cultivation. Cash
crops such as the oil palm, maize, pepper and rubber are increasingly integrated with the upland
agricultural systems (Cramb et al., 2009; Ziegler et al., 2011). The livelihoods of the farmers can be
improved however they will also become more exposed to market vulnerability as the prices of such
crops are known to fluctuate (Roder, 1997). Not do they only become more vulnerable but their
continuous cropping will accelerate land degradation (Cramb et al., 2009). Furthermore, the
cultivation of permanent cash crops removes land from the cyclic rotation of shifting traditional and
thereby reduces the fallow length.
Livestock may be of benefit to villages in the upland areas as they have a high market value per unit
weight and are somewhat mobile, an important trait if road facilities are lacking (Roder, 1997). A
study found that there are cases whereby villages with poor market access built successful networks
by walking for as long as three days to bring their livestock to markets (Vien et al., 2006).
Furthermore, they can act as an insurance of some type, sold during times of illnesses or food
shortages. However livestock integration requires a basic fundamental level of infrastructure
development to avoid conflict with crops and humans, i.e. fences.
Theoretical Background ǁ Livelihood Strategy Implications
10
2.4 Livelihood Strategy Implications
Where the transformation of shifting cultivation has occurred, the process has involved multiple
steps and system variations. The progressive integration of padi rice in response to intensification
occurs if suitable areas, i.e. flat valley bottoms, are available (Roder, 1997); Rambo (2006) coined the
term ‘composite swidden agriculture (CSA)’ for such systems and claims it has a higher sustainability
than traditional shifting cultivation. Cramb, et al. (2009) further defines a ‘partial swiddening’
system where the inclusion of cash crops increases gradually at the expense of subsistence crops.
The cultivation of maize for the livestock feed sector is becoming widespread in Southeast Asia
where upland farmers sign contract agreements with maize companies who offer support services in
varying degrees. Published studies of this trend are scarce and farmer benefits will be dependent on
the contract conditions and the extension services provided.
On the other hand, traditional shifting cultivation is still maintained in some upland areas despite the
aforementioned drivers and challenges; it has been suggested that its maintenance as a livelihood
strategy is due to the lack of feasible alternatives (Hansen and Mertz, 2006). Governmental polices
thus have been criticised as only placing extra strain on the livelihoods of the rural poor and
accelerating land degradation.
The intensification of shifting cultivation by means of decreasing fallow length will have implications
for livelihood strategies. Food security of the upland communities is expected to be negatively
influenced as a consequence of lower rice yields and availability of NTFPs (Rerkasem et al., 2009).
Furthermore, the environmental and socioeconomic constraints in the cultivation of upland rice will
increasingly become more prominent. Roder et al. (1995) found farmers in Northern Lao PDR
identified weeds, rodents and insufficient rainfall as the three most limiting constraints to upland
rice production; the other constraints found were land availability (which included the short fallow
constraint), insects, labour, soil suitability, erosion, domestic animals, wild animals and disease and
were ranked by the farmers in this order (Roder et al., 1995).
Study Site Description ǁ Methodology
11
3 Methodology
To investigate the study objective, a methodology with a mix of qualitative and quantitative
methods was employed. This allowed for triangulation and a better understanding of the overall
agricultural management practices as socio-economic influences are often lost in strictly quantitative
studies. Living within the community as an active participant gave deeper insight and was an
enriching experience. Interviews were communicated through the help of a translator.
3.1 Study Site Description
The study was carried out in Lao PDR (Figure 4), a
developing country where shifting cultivation is the
main land use strategy of the rural villages in the
upland areas (Roder, 1997). Lao PDR has the greatest
extent of shifting cultivation than any other country in
Southeast Asia where an estimated 6.5 million
hectares of upland area is used (Schmidt-vogt et al.,
2009).
Fieldwork was conducted in Ban Navene, a remote
village located in the northern province of
Louangphabang (20°22’48”N, 103°10’85”E; Figure 4).
Ban Navene consists of 76 ethnic Khamu households
that are characterised by subsistence farming (Figure
5). Both upland and padi rice are cultivated in the area
and are the principal components in their diets; 27
households exclusively rely on upland rice cultivation
while the remaining rely on a combination of the two.
Each household additionally cultivates a small
vegetable garden to supplement food products found in the surrounding forest. Maize cultivation
as a cash crop is gaining momentum among the farmers; at the time of fieldwork, 45 households
were under a contract agreement with the maize company, Thong La, to whom they exclusively sold
to.
Figure 4: The location map of Lao PDR indicating approximate location of the study site (red square) and Ban Navene, a village in the Viengkham district of the northern province of Louangphabang (shaded pink). Adapted from Hett et al. (2012)
Methodology ǁ Study Site Description
12
Figure 5 : A schematic drawing representing Ban Navene and its surrounding fields and crop types. Original land use map was drawn at the introductory meeting with the Headman, Assistant Headman and key village elders (20/09/2012). Past DAFO boundary maps were used as references. The locations of the upland rice fields used in the study are labeled.
There are a total of 60 ha of padi rice in Ban Navene, a quality that sets the village apart from its
equally-impoverished neighbours and is the major driving force for the influx of new families. Water
is supplied to a proportion of the fields by a large-scale irrigation system built by the District
Agricultural and Forestry Office (DAFO) in compensation for the land lost with the establishment of
the Nam Et – Phou Louey National Protected Area (NEPL NPA) in 2001. In addition to the irrigation
system, a dirt road from Nam Xoy was built, fish ponds were established and families were given
‘replacement’ fields if any were lost to the NEPL NPA. Policy changes were invoked to restrict or
minimise resource extraction from the NEPL NPA; hunting and cultivation within the boundary is
illegal and non-timber forest products can only be collected within specified months.
Shifting cultivation is still practiced by the villagers whereby one cropping of upland rice is cultivated
after the area is slashed-and-burned and then left for fallow. There are numerous local varieties of
upland rice grown in the area and all are of the ‘middle-season’ harvest type. Additional crops, such
as local varieties of squash, sesame, green bean, Job’s tears (Coix lacryma-jobi), pigeon pea (Cajanus
cajan) and ‘man pao (Pachyrhizus erosis)’ are scattered amid the upland rice. In the 1980s, fallow
lengths were of longer durations of those employed now; lengths were upwards of 15 years but
many are now in the range of two to eight years. This trend is largely due to the Lao government
policy whereby a family is restricted to three or four upland fields, shortening the possible length of
the entire cycle.
Identification of Fields ǁ Methodology
13
3.2 Identification of Fields
Prior to field selection, an introductory meeting was held with the Headman, Thong Phouy, and
village elders to obtain a general overview of the area, farming strategies and trends. Furthermore, a
land use village map was drawn (Figure 5); this map was used as a basis to where suitable fields may
be located and to ensure the fields were spatially distributed. An exception is the five-year fallow
fields wherein two are situated in close proximity of one another due to time constraint and low
field numbers. The fallow categories defined were based from the discussion which also helped to
ensure all three parties, meaning the village members, the translator and the researcher had the
same definition of the term ‘fallow length.’
Upland rice fields with various lengths of preceding fallow were needed to investigate the effects on
soil quality and rice yield; three fields for each fallow category (two to three years, five years and ten
to eleven years) were identified by conducting short surveys with households using convenience
sampling; respondents were selected on the basis of whether they were present in the village, had
the time and owned upland rice fields (Appendix 1.1).
The purpose of the short survey was not only to identify the fallow lengths of the field but also to
collect data on variables such as family size (linked to available labour), land use history and the
general economic standing of the farmer (i.e. what other crops they grow as this will affect the
available labour and time). The short survey also ensured that all the fields used had a good quality
burn. If there was some degree of uncertainty in the ownership and the length of the preceding
fallow, it was then excluded. The slope gradient and base soil type were assessed of potential fields
to ensure similarity before selection; the altitudes ranged between 600 – 843 m ± 5 m with slope
gradients between 51 – 93% and were of the ultisol soil order. In total, nine fields were identified: a
two-year fallow (2F3), 2 three-year fallows (3F1 and 3F2), 3 five-year fallows (5F1, 5F2 and 5F3), 2
ten-year fallows (10F2 and 10F3) and an eleven-year fallow (11F1). Please refer to Appendix 2 for a
full field record of characteristics and harvest data and Appendix 3 for a field area map.
3.3 General Plot Layout
A visual survey was completed for each field where details such as aspect, topography, indications of
erosion and weed coverage were noted (Appendix 1.1). In each of the fields, a 15 m by 15 m plot
was established in the middle of the slope from which soil samples were collected. The five year
fallow fields had two additional plots made at the top and bottom to investigate the influence of
topography on soil quality and yield. The distance between the plots, however, could not be fulfilled
as depicted in Figure 6 (b); the five-year fallow fields had a length of approximately 70 meters thus
restricting the distance between the plots to only 5 meters, a weakness in the design.
Methodology ǁ General Plot Layout
14
a) b)
Figure 6: (a) Diagram depicting the plot design; red circles represent full soil pit sampling sites (down to 50 cm) whereas the ‘x’ represents the micro sampling sites (to 10 cm). Numbering scheme is from left to right with ‘1’ at the top left and ‘9’ at the bottom right. For the five year fallows, three plots were placed down the slope and plot yields were also assessed, as depicted in (b).
3.3.1 Soil Sampling and Analysis
Soil samples were collected at the soil surface, 10 cm and, for the pit profiles, also at 30cm with 100
cmᶟ cores. Pit profile descriptions (i.e. colour according to the 7.5 YR Munsell Colour Chart, texture
via the feel method as described by the FAO Soil Description Guidelines, 2006, and descriptive
remarks) were recorded. Sampling depths were adjusted if a horizon boundary transected at the
desired depth and occurrences were noted. Samples were dried, weighed and crushed. If a sample
contained more than 5% of its weight in stones, they were then weighed separately and bulk density
was corrected using a value of 2.6 g cm¯ᶟ for the stones.
The pit samples were analysed for a total of seven parameters: pH, cation exchange capacity (CEC),
total carbon, total nitrogen, plant-available phosphorus (P Avail), exchangeable potassium (K Exch)
and permanganate oxidisable carbon (Pox C). Clay content (%) and texture were measured for only
one complete pit profile in each plot. The micro samples were analysed for pH, total carbon, total
nitrogen and Pox C.
The dried crushed pit samples were forwarded to the Soils and Fertilizers Research Institute (SFRI) in
Hanoi, Vietnam for analysis: the ammonium acetate method (at a pH of 7) was used to find CEC, P
Avail was detected by the Bray II method and K Exch was found by extracting with 1M ammonium
acetate and measured by flame photometry (pers. comm. Tran Tien 15/03/13). The texture of one
pit profile from each plot was also characterised.
The analyses for Pox C and pH were carried out at the Department of Soil and Environmental
Resources of the Faculty of Agricultural Production at Maejo University in Chiang Mai, Thailand1. pH
was determined in a 1:2.5 soil:water solution. Pox C concentrations of the surface and 10 cm
samples were determined by using the method as described by Weil et al. (2003): 2.5 g of crushed
soil was weighed in a 50 ml Falcon tube, to which 18 ml of milli Q water and 2 ml of 0.2 M KMnO₄
11 With the exception of the 30 cm samples where pH was measured in a 1:2.5 soil:water solution at the
Dept of Plant and Environmental Sciences in the Faculty of Science at the University of Copenhagen.
Calculations and Statistical Analysis ǁ Methodology
15
were added. Due to previous observations, shaking time was doubled from two to four minutes.
After a settling time of 10 minutes, 1 mL of the supernatant was transferred to a new Falcon tube
with 19 ml of milli Q water. Absorbance was measured at 550 nm by spectrophotometry. Samples
were analysed in batches of five to maintain consistency. Please refer to Appendix 1.3 for full
protocol and Appendix 1.4 for the standard curve found for the reduction of KMnO4.
The total carbon and nitrogen content of all samples were determined using the Isotope Ratio Mass
Spectrometer at the Department of Agriculture and Ecology in the Faculty of Science at the
University of Copenhagen.
3.3.2 Yield Assessments
Upland rice yield was assessed directly from the 15 m by 15 m plots of the three five-year fallows (a
total of nine plots) in order to investigate if there is an influence from slope position. The plots were
harvested and weighed separately. Other yield assessments were based on the entire harvest where
the number of bags and average weight of a bag, based on three bags, were recorded in the field.
Plot-specific yield measurement was not done for these fields as it was deemed unnecessary as
separate harvesting did result in a certain degree of crop destruction; the three farmers of the five-
year fallows were compensated with two bags of rice each. The field perimeters, defined by the
farmers themselves, were tracked with a Garmin GPS to determine the area with Google Earth Pro
7.0. In order to determine the yield in terms of processed rice, 1 kg subsamples were dried in the
sun, milled and weighed.
3.4 Calculations and Statistical Analysis
The upland rice yield (kg ha¯¹) was calculated by:
[(No. of Bags x Weight (kg))-(No. of Bags x Weight of casing (kg))] / Area (ha)
Processed rice yields were found by multiplying the above equation with the weight of the milled
subsample.
The stock concentrations were calculated by multiplying the elemental concentration, bulk density
and the soil depth. As analysis was not done according to soil horizons, the surface stocks were
extrapolated to a depth of 5 cm and the 10 cm stocks from 5 – 10 cm.
An equivalent mass approach was used to calculate the stocks of the upper 10 cm using the
following formula as described by Ellert (2001):
Upper 10 cm X = (BDSurface x ConcentrationSurface x 0.05 m) + (BD10 cm x Concentration10 cm x T add(depth))
Where T add is the new depth if all samples are an equivalent mass, i.e. the average mass of the
upper 10 cm for the entire data set:
Methodology ǁ Calculations and Statistical Analysis
16
T add = [ Avg Mass 10 cm – ((BDSurface x 0.05 m) + (BD 10 cm x 0.05 m)) / BD 10 cm ]
A standard curve for the KMnO₄ reaction was first plotted using initial concentrations of 0.02M, 0.01
M and 0.005 M and was used to determine the final concentrations of MnO₄ in all of the reactions
(Appendix 1.4). To determine the concentration of Pox C, the following formula was then used:
Pox C (mg kg¯¹) = (0.02 mol l¯¹ - [MnO₄ Final]) x 9000 mg C mol-1
x (0.02 l solution / 0.0025 kg soil)
Where 0.02 mol l-1 is the initial concentration of the MnO4, [MnO4 Final] is the final concentration
interpolated from the standard curve and 9000 mg in the amount of Carbon (mg) that is oxidized by
1 mol of MnO4.
The data set generated from the fallow length study was used to investigate the interactions
between parameters, the influence of fallow length on soil quality and yield levels. The
topographical study provided the data set used to analyse the effect soil quality has on yield levels,
as the specific plots were harvested, and the influence of slope position on soil quality and yield
levels. Statistical analyses were conducted using SPSS 16.0 for Windows. One-way ANOVAs, with
the Levene’s test for equality, were performed to assess for any differences in the measured soil
parameters. Least Significant Difference (LSD) post hoc tests, or Games-Howell Tests if homogeneity
in variance was not observed, revealed where the significant differences lied, if any. Independent t-
tests were used to assess differences in yields between the fallows due to the group size (there was
only one site for both the 2 and 11 year fallow). Multiple regression analyses were performed to
identify the factors affecting yield, where all parameter but the stock values were included as
independent factors. Pearson’s correlation tests were also applied.
Using the land use history obtained from the short survey, it was possible to calculate an adapted
Ruthenberg Index (R Index), a measure of land use intensity developed by Ruthenberg (1971), via
the following equation:
[Years cultivated / (Years cultivated + Years fallow)] x 100
In this adapted R Index, (Years cultivated + Years fallow) always equaled ten years as this history was
available for all fields. The fields were then assessed as above but according to their R Index, which
meant that two 3-year fallows increased in their level of intensity to match those of the 5-year while
one 5-year fallow decreased to an intensity equal of the 2-year fallow.
The Accumulated Cropping index (ACi), a second measure of land use intensity, was adapted from
the Accumulated Farming Index developed by Birch-Thomsen et al.( 2007). Here each year was
assigned a value, i.e. the present year would be assigned a value of 10, the preceding year a value of
9 and so on, which would only be included in the calculated sum if it was a year of cropping. In this
way, more recent years have a bigger influence over the land use intensity. To clarify, the equation
is:
ACi = [Value cultivation yrs (10 present + 7if 2 year fallow+…)]
Constraints of Upland Rice Production ǁ Methodology
17
3.5 Constraints of Upland Rice Production
Roder (1995) has identified constraints of upland rice
production and, of these, ten were picked based on initial
findings to which would be of relevance to Ban Navene
(domestic livestock was not included, for example, as the
majority of farmers did not own grazing livestock): weeds,
pests (insects), disease, wild animals (i.e. wild boar), land
availability (includes shortened fallow length), rainfall, soil
suitability, labour availability, soil erosion and rodents.
Pair-wise ranking was conducted with twenty villagers at
random to investigate which identified factor was most
limiting in upland rice production in Ban Navene.
To alleviate miscommunication, flashcards for each factor
were made with a representational image and translated
both in Lao and Khamu (Figure 7). Flashcards were
presented two at a time whereupon the informant was
asked to identify which was the most constraining.
Responses were recorded in a matrix from which total
scores for each factor were calculated by summing up the
individual scores.
3.6 Farmers’ Perception
To gain a deeper insight into management practices and for
triangulation purposes, in-depth interviews were conducted with
the farmers of the nine chosen fields. Questions pertaining to
cycle management, assets (labour, financial), challenges and their
perspective on any changes in yields or soil quality were asked
(full guideline in Appendix 1.5). Their outlook on the soil quality
of their own fields and the attributes that make them suitable for
upland rice production led to a better understanding of the soil
and yield results. Overall, the interviews allowed for a holistic
perspective of the links within an agricultural system and how an
individual’s unique life story will shape management practices. To
understand the consequences of land allocation for conservation
projects, interviews were conducted with three families who
had lost land to NEPL NPA establishment (Appendix 1.6 for
question guideline).
Figure 8: Sheang’s father, a key informant for what characteristics, physical and biological, are indicative of a field with high quality for upland rice production
Figure 7: The flashcards used for the pairwise ranking method to assess which factors constrain upland rice production
Methodology ǁ Future Perspectives
18
A field walk with a key informant, Sheang’s father, was carried out with focus placed on what singles
out a field of higher quality (Figure 8). Sheang’s father was chosen as a key informant because he
appeared to have extensive knowledge on this topic from a prior informal discussion. The walk was
through the surrounding upland fields of Ban Navene during which Sheang’s father identified fields
with fertile soil, indicated by the presence of specific plants and soil characteristics (i.e. colour), and
the general physical properties that reflect suitability for upland rice (i.e. slope gradient).
As mentioned, every day discussions and observations enhanced results by allowing for a better
understanding of how such developing villages respond to change, be it in policy or the
environment. General discussions were had with many informants; some of which are the
Headman, Thong Phouy, a volunteer forest officer, and an officer from DAFO, Phaeng Xaphokhame
(who also acted as a translator).
3.7 Future Perspectives
Thong Phouy, the Headman, was a valuable resource
in understanding how the villagers of Ban Navene
perceive their future. He was involved in the
introductory meeting, where the community map was
drawn, the timeline exercise and the group meeting.
General discussions with him touched upon many
subjects of which include but are not restricted to
policy changes, future endeavors, maize production
and community forest management.
A group meeting was held with Thong Phouy, the
assistant headman, Siphet, the women’s group head,
Von Shaeng, and the nine selected farmers to discuss
two main topics: the decreasing trend in labour supply in Ban Navene and governmental policies,
specifically the restriction of three to four upland fields per family and the 2020 policy in which the
Lao Government hopes to stop all slash-and-burn activity (Figure 9). These two topics very much
touched upon the future of Ban Navene and how the challenges may be overcome. Additionally, the
participants were asked what they feel is required for Ban Navene to develop further and what
social programmes would help in reaching their goals. Please refer to Appendix 1.7. for guiding
questions of the group interview.
Figure 9: The participants of the group meeting held at the Ban Navene School; some attendees are missing from the picture
Soil Quality Analysis ǁ Results
19
4 Results
4.1 Soil Quality Analysis
There are two sets of quantitative data:
1. Soil and yield data from nine fields of fallow lengths from 2-11 years.
2. Soil and yield data from three 5-year fallow fields whereby each had three sampling plots,
giving a total of nine plots.
The first set of data is used to investigate the interactions between soil parameters and the overall
influence of fallow length. The second set of data better represents the links between yield and soil
parameters as yield measurements are taken directly from the marked plots, hence it is used to
identify the influence of the soil quality on yield. Additionally, topographical influence on soil quality
and yield is also explored using this set. Refer to 3.3 General Plot Layout in the Methodology section
for full details of experimental set-up, collection and assessment.
Please refer to Appendix 2 for an inventory of the field codes and their characteristics, i.e. area,
slope gradient. For the map of the areas of each field site, please refer to Appendix 3. The soil
parameter averages are organised in tables according to the two studies, fallow length and
topographical, and can be found in Appendix 4.
4.1.1 General Soil Description
The ranges found for the soil parameters are typical of a tropical ultisol
with kandic horizons (Table 1, 2 and 3) and fall within those found by
Roder et al (1995) in a study also conducted in Northern Lao P.D.R.
Ultisols are extensively found in humid forested areas (Weil and Brady,
1999).
The soils in the Ban Navene area are quite acidic (4.60 – 5.05), clay or
clay loam in texture and with clay in the upper 10 cm ranging between
363 – 487 g ∙ kg¯¹. The topsoil is thin, fine and is either a deep
brown/black colour or bleached (Figure 10). The accumulation of Fe-
and Al-oxides, characteristic of kandic horizons (Weil and Brady, 1999),
is evident by the red colour of the subsurface horizons (Figure 10). The
soils contain charcoal and quartz fragments (Figure 10).
Conventionally, ultisols can be quite productive with adequate fertilizer
and liming (Weil and Brady, 1999); however, the farmers in Ban
Navene do not use any fertilizer or lime, removing chemical additives
as a possible influencing factor. Figure 10: Soil profile of the ultisol typical for the Ban Navene area
Results ǁ Soil Quality Analysis
20
4.1.2 Soil Parameter Interactions
The Pearson’s correlation coefficient test revealed the linear relationships between the parameters
and how they may interact. Results involving the physical soil parameters are presented first
followed by those involving SOC. It should be noted that CEC and pH display minimal or no
correlations with the investigated soil parameters, a surprising result as they are known to
theoretically influence the nutrient availability (i.e. K Exch, P Avail) in a soil. Only two significant
correlations were found: pH and stock K Exch show a positive medium-strength correlation
(r=0.578**) at the surface, and pH and bulk density exhibit a weak positive correlation at the surface
and at 30 cm (Table 1 and 3).
The results may not be fully indicative of the true links between the soil parameters as relationships
may not be linear and, thus, would be deemed insignificant. In general, it must be kept in mind that
the overall sample size is quite small, especially when interpreting the correlations found involving
clay.
4.1.2.1 Interactions of Physical Soil Parameters
Many of the correlations at 10 cm parallel those found at the soil surface though to a lesser degree
as the soil will be less exposed to environmental and management effects. Therefore, the soil
parameters are influenced by soil depth: they decrease with soil depth except for bulk density, clay
content and SOC:Pox C depicted by Table 1 (soil surface), 2(10 cm) and 3(30 cm).
The soil physical parameters, bulk density and clay content, show a significant correlation to each
other and to those pertaining to carbon and nitrogen content (Table 1, 2 and3). Bulk density and
clay are positively correlated (Table 1 and 2). Both show an inverse relationship with carbon (SOC %
and Pox C) and nitrogen (N %) content (Table 1 and 2). At 10 cm, however, clay content is only
negatively correlated to N % (Table 2). Only bulk density interacts with potassium and phosphorus;
at the surface, P Avail shows a weak negative correlation (Table 1), while at 10 cm, K Exch has a
strong negative correlation to bulk density (Table 2).
Significant correlations between the soil parameters at 30 cm are few, evident from Table 3 where
all significant correlations are shown. Bulk density is positively correlated with pH and negatively
correlated with both SOC % and N % (Table 3). Clay content is correlated to SOC% (Table 3), N% (r=-
0.575**) and stock N (r=-0.498**).
Soil Quality Analysis ǁ Results
21
Table 1: The range and correlations of soil parameters at the soil surface of fields under shifting cultivation management and after one harvest of upland rice; based on nine
fields with fallow lengths from two to eleven years.
Correlation Coefficient (r)¹
Soil Parameter Range Clay Bulk Density CEC pH SOC % SOC Stock Pox C SOC: Pox C N % Stock N SOC : N P Avail K Exch
Clay (g·kg¯1) 367 - 450
Bulk Density (g∙m¯ᶟ) 558 - 934 0.716**
CEC (cmol(+) kg¯¹) 11.5 - 14.0 ns ns
pH 4.64 - 5.05 ns 0.445* ns -
SOC % 3.00 - 4.59 -0.631** -0.627** ns ns
SOC Stock (kg · m¯²) 1.27 - 1.79 ns 0.330** ns ns 0.490**
Pox C (mg·kg soil¯¹) 808 - 1143 -0.595** -0.728** ns ns 0.792** ns
SOC : Pox C 36.6 - 41.5 ns ns ns ns 0.683** 0.618** ns
N % 0.28 - 0.39 -0.687** -0.592** ns ns 0.835** 0.424** 0.779** 0.502**
Stock N (g · m¯²) 105 - 160 ns 0.523** ns ns ns 0.851** ns 0.347** 0.353**
SOC : N 10.8 - 12.1 ns -0.331** ns ns 0.677** 0.331** 0.383** 0.557** ns ns
P Avail (mg·100g soil¯¹)
0.409 - 3.38 ns -0.433* ns ns 0.389* ns 0.540** ns 0.443* ns ns
K Exch (mg·100g soil¯¹) 12.6 - 32.1 ns ns ns ns ns ns 0.415* ns ns ns 0.516** ns
¹Analysed by the Pearson’s Correlation Test via SPSS 16.0 at a confidence level of 95%,(*) or of 99% (**). n = 81 for bulk density, Pox C, SOC %, N%, SOC : Pox C, SOC Stock, SOC:N, Stock
N and pH; n = 27 for CEC, P Avail, K Exch; n = 9 for clay
Results ǁ Soil Quality Analysis
22
Table 2: The range and correlations of soil parameters at a 10 cm depth of fields under shifting cultivation management and after one harvest of upland rice; based on nine
fields with fallow lengths from two to eleven years.
Correlation Coefficient (r)¹
Soil Parameter Range Clay Bulk Density CEC pH SOC % SOC Stock Pox C SOC : Pox C N % Stock N SOC : N P Avail K Exch
Clay (g·kg¯1) 363 – 521
Bulk Density (g∙m¯ᶟ) 818 - 1102 0.532**
CEC (cmol(+) kg¯¹) 11.5 – 15.5 ns ns
pH 4.60 – 4.86 ns ns ns -
SOC % 2.07 – 3.58 ns -0.680** ns ns
SOC Stock(kg · m¯²) 1.12 – 1.46 ns ns ns ns 0.732**
Pox C (mg·kg soil¯¹) 556 - 770 ns -0.363** -0.461** ns 0.830** 0.592**
SOC : Pox C 37.6 – 47.6 ns -0.321** ns ns 0.422** 0.325** ns
N % 0.22 – 0.31 -0.539** -0.696** ns ns 0.907** 0.646** 0.743** 0.439**
Stock N (g · m¯²) 119 - 141 ns 0.258* ns ns 0.345** 0.793** 0.248* 0.235** 0.494**
SOC : N 9.25 – 11.39 ns -0.390** ns ns 0.758** 0.604** 0.656** 0.230* 0.423** ns
P Avail (mg· 100g soil¯¹)
0.201 -0.376 ns ns ns ns 0.420* ns ns ns ns ns ns
K Exch (mg·100g soil¯¹) 6.42 – 15.3 ns -0.640** ns ns 0.439* ns 0.431* ns 0.420* ns ns ns
¹Analysed by the Pearson’s Correlation Test via SPSS 16.0 at a confidence level of 95%,(*) or of 99% (**). n = 81 for bulk density, Pox C, SOC %, N%, SOC STOCK : Pox C, SOC Stock,
SOC:N, Stock N and pH; n = 27 for CEC, P Avail, K Exch; n = 9 for clay
Soil Quality Analysisǁ Results
23
Table 3: The range in soil parameters at depths of thirty cm of fields under shifting cultivation management and after one harvest of upland rice; based on nine fields with fallow lengths from two to eleven years
Correlation Coefficient (r)¹
Soil Parameter Range Bulk Density SOC %
Clay (g·kg¯¹)² 333 - 526 ⁿ⁼7
ns -0.512**
pH 4.77 - 4.95 0.427* ns
CEC (cmol(+) kg¯¹) 11.4 - 13.7 ns ns
P Avail (mg·100g soil¯¹) 0.06 - 0.22 ns ns
K Exch (mg·100g soil¯¹) 3.67 - 6.90 ns ns
Bulk Density (g∙m¯ᶟ) 990 - 1192 - -
SOC % 1.24 - 1.93 -0.488** -
N % 0.16 - 0.29 -0.556** 0.843**
¹Analysed by the Pearsons Correlation Test via SPSS 16.0 at a confidence level of 95% (*) or of 99% (**). n = 81 for bulk density, SOC %, N%, pH; n = 27 for CEC, P Avail, K Exch; n = 9 for clay, ²Range in clay content for surface and 10 cm samples; 3F1 was 237 & 11F1 was 184, both excluded
4.1.2.2 SOC Influence on Soil Parameters
The Pearson’s correlation coefficient test revealed that SOC is correlated with the majority of the soil
parameters investigated at both the soil surface and at a 10 cm depth (Table 1 and 2). This indicates
the high degree of influence SOC has on soil quality and thus will be discussed as a key variable. SOC
is negatively correlated with the physical properties of a soil (i.e. bulk density and clay content) while
showing no correlation with CEC and pH (Table 1 and 2).
SOC is correlated with the nutrient levels (N, P, K) found in soil (Table 1 and 2). SOC % and N%
appear to be covariates, evident from their strong correlation at all three depths and a mirroring in
their general interactions to the other soil parameters (Table 1 and 2, Figure 11). The average C:N
ratio at the surface is 11.4, slightly higher than that of 10 cm but is still generally quite low (Figure
11). SOC % has a weak positive correlation with P Avail and K Exch; P Avail is correlated at both soil
depths while K Exch is only at 10 cm (Table 1, Figure 12). Figure 12 points to possible outliers:
1. The P Avail outlier depicted in 12a is a sample from 11F3, a low-yielding field,
and was re-tested.
2. 12b indicates three K Exch outliers: two are from 2F3 and one is from 11F3, both
low-yield fields. Unfortunately re-tests were not done as decisions were based
on whether the results followed the general observed pattern (or ratio, when
compared to P Avail for instance) and cost.
Results ǁ Soil Quality Analysis
24
.
Figure 11: Relationship between carbon and nitrogen soil content at the surface and at a depth of 10 cm, depicted by SOC % and N%. Individual points colour-coded according to fallow length and yield level (kg∙ha¯¹): blue is 2, 3 or 11-year fallow and below 1000, red/pink is 5 or 10-year fallow and above 1000 and green is 10F3, a 10-year fallow with the highest yield, 1552; lighter colours represent data points corresponding to levels at 10 cm. Soil samples were taken after the harvest of one cropping of upland rice. Analysed using the Pearson’s correlation coefficient test at a confidence level of 99% (**). n=81
11.4
9.94
0,00
0,10
0,20
0,30
0,40
0,50
0,60
0,00 1,00 2,00 3,00 4,00 5,00 6,00 7,00 8,00
N %
SOC %
Surface
10 cm
Surface C:N
10 cm C:N
r S = 0.835**
r 10
= 0.907**
Soil Quality Analysisǁ Results
25
Figure 12: Relationship between SOC % and a) P Avail and b) K Exch at the soil surface and at a depth of 10 cm. Individual points colour-coded according to fallow length and yield level (kg∙ha¯¹): blue is 2, 3 or 11-year fallow and below 1000, red/pink is 5 or 10-year fallow and above 1000 and green is 10F3, a 10-year fallow with the highest yield, 1552; lighter colours represent data points corresponding to levels at 10 cm. Soil samples were taken after the harvest of one cropping of upland rice from fields. Analysed using the Pearson’s correlation coefficient test at a confidence level of 95%. n = 27
0,00
1,00
2,00
3,00
4,00
5,00
6,00
7,00
0,00 1,00 2,00 3,00 4,00 5,00 6,00
P A
vail
(mg
· 10
0 g
so
il¯¹)
SOC %
r S = 0.389*
r 10
= 0.420*
a)
b)
0,00
10,00
20,00
30,00
40,00
50,00
60,00
0,00 1,00 2,00 3,00 4,00 5,00 6,00
K E
xch
(m
g ·1
00
g s
oil¯
¹)
SOC %
Surface
10 cm
Surface
10 cm
r 10
= 0.439*
Results ǁ Soil Quality Analysis
26
4.1.2.3 A Closer Look at Pox C
At 10 cm CEC shows an inverse relationship with Pox C levels (Table 2). Pox C has a strong positive
correlation with SOC % at both depths; the correlation is stronger at a depth of 10 cm than at the
soil surface (Table 1 and 2, Figure 13). The ratio between SOC and Pox C is 39.6 at the soil surface
and 44.0 at 10 cm, indicating the relative pool sizes (Figure 13).
Pox C displays similar correlations with soil nutrients (i.e. N%, P Avail and K Exch) as SOC % (Table 1
and 2, Figure 14). Pox C is stronlgy positively correlated with N % at both depths (Figure 14). It has
a weak relationship with the SOC:N ratio (Table 1 and2).
At the soil surface P Avail has a stronger positive correlation to Pox C than to SOC%; however this
relationship disappears at 10 cm (Table 1 and 2). K Exch displays positive correlations with Pox C at
both depths; a trend which SOC% does not follow as it displays no significant relationship with K
Exch at the soil surface (Table 1 and 2).
39.6
44.0
0
200
400
600
800
1.000
1.200
1.400
1.600
0,00 1,00 2,00 3,00 4,00 5,00 6,00 7,00 8,00
Po
x C
(m
g · k
g so
il¯¹)
SOC %
Surface
10 cm
Surface SOC:Pox C
10 cm SOC:Pox C
Figure 13: The relationship between SOC % and Pox C at the soil surface and at a depth of 10 cm. Individual points colour-coded according to fallow length and yield level (kg∙ha¯¹): blue is 2, 3 or 11-year fallow and below 1000, red is 5 or 10-year fallow and above 1000 and green is 10F3, a 10-year fallow with the highest yield, 1552; lighter colours represent data points corresponding to levels at 10 cm. Soil samples were taken after the harvest of one cropping of upland rice. Analysed by the Pearson’s correlation test at a confidence level of 99% (**), n = 81
r S = 0.792**
r 10
= 0.830**
Implications of the Soil Quality on the Yield of Upland Riceǁ Results
27
4.2 Implications of the Soil Quality on the Yield of Upland Rice
The yield in the local, mid-season varieties of upland rice ranged from 517.35 – 1552.22 kg · ha¯¹.
The processing of rice grains resulted in a loss of 40% in weight, i.e. 1 kg of un-milled and un-
threshed grain gave approximately 600 g of finished rice.
4.2.1 Soil Parameter Influences on Yield
Statistical analysis, via Pearson’s correlation coefficient test, revealed links between soil parameters
and yield, indicating that the overall soil quality does influence upland rice yield. Soil parameters
that are directly correlated to yield are pH, bulk density, SOC %, Pox C and N%.
There is a strong negative correlation between both yield and pH, depicted by Figure 15, and yield
and bulk density.
0,00
0,05
0,10
0,15
0,20
0,25
0,30
0,35
0,40
0,45
0,50
0 200 400 600 800 1000 1200 1400 1600
N %
Pox C (mg ∙ kg soil¯¹)
Surface
10 cm
Surface
10 cm
r S = 0.779**
r 10
= 0.743**
Figure 14: Relationship between Pox C and N% at the soil surface and at a depth of 10 cm. Individual points colour-coded according to fallow length and yield levels (kg∙ha¯¹): blue is 2, 3 and 11-year fallow and below 1000, red/pink is 5 or 10-year fallow and above 1000 and green is 10F3, a 10-year fallow with the highest yield, 1552; lighter colours represent data points corresponding to levels at 10 cm. Soil samples were taken after the harvest of one cropping of upland rice from fields. Analysed using the Pearson’s correlation test at a confidence level of 95%. n = 81
Results ǁ Implications of the Soil Quality on the Yield of Upland Rice
28
The significant correlations between Pox C and yield will be of focus as it has a stronger correlation to yield than SOC% (Pox C rSurface = 0.517** and r10 = 0.554**, SOC % rSurface = 0.497** and r 10 = 436*) (Figure 16).
Figure 16: The relationship between upland rice yield and Pox C at the soil surface and at depth of 10cm of fields with five-year preceding fallows. Soil samples were taken after the harvest of one cropping of upland rice. Analysed by the Pearson’s Correlation Coefficient test at a confidence level of 99% (**), n=27
0
200
400
600
800
1.000
1.200
1.400
1.600
3,50 3,70 3,90 4,10 4,30 4,50 4,70 4,90 5,10 5,30
Yie
ld (
kg ·
ha¯
¹)
pH
Surface
10 cm
30 cm
rS= -0.635**
r10= -0.716**
r30= -0.515**
0
200
400
600
800
1000
1200
1400
1600
1800
0 250 500 750 1000 1250 1500
Yie
ld (
kg ∙
ha¯
¹)
Pox C (mg · kg¯¹)
Surface
10 cm
Surface
10 cm
rS = 0.517**
r10 = 0.554**
Figure 15: The relationship between upland rice yield and pH at the soil surface and at depths of 10cm and 30 cm of fields with five-year preceding fallows. Soil samples were taken after the harvest of one cropping of upland rice. Analysed by the Pearson’s Correlation Coefficient test at a confidence level of 99% (**), n=27
Implications of the Soil Quality on the Yield of Upland Riceǁ Results
29
Pox C and N % have a strong positive correlation at both depths. When paired with yield data, it appears that a Pox C level above 1000 mg ∙ kg soil¯¹ with a N % above 0.35% leads to a higher yield in upland rice; the majority of the data points from the field with the highest yield are above 1000 mg Pox C ∙ kg soil¯¹ and all have at least 0.35% N (Figure 17a, red outline). The C:N ratio appears to also influence yield to some degree; a C:N ratio of 11 will result in a higher yield of upland rice (Figure 17b, red line).
The links between upland rice yield, Pox C and P Avail are not clear (Appendix 5.1, Fig. B (a)) though
Pox C and P Avail do have a strong positive correlation. The same pattern is observed with K Exch
Figure 17: The relationship between upland rice yield, Pox C and a) N% and b) C:N at the soil surface and at a depth of 10cm of fields with five-year preceding fallows. Soil samples were taken after the harvest of one cropping of upland rice. Individual points are colour coded according to yield levels (kg ∙ ha¯¹): below 1000 is depicted with blue, above 1000 is red/pink and the highest yield (1432) is coded green; lighter colours represent data points corresponding to levels at 10 cm. Analysed by the Pearson’s Correlation coefficient test at a confidence level of 99% (**), n=81
0,00
0,05
0,10
0,15
0,20
0,25
0,30
0,35
0,40
0,45
0,50
0 200 400 600 800 1.000 1.200 1.400 1.600
N %
Pox C (mg · kg soil¯¹)
r10
= 0.870**
r N%-yield
= 0.549**
rS= 0.698**
0,0
2,0
4,0
6,0
8,0
10,0
12,0
14,0
16,0
18,0
0 200 400 600 800 1.000 1.200 1.400 1.600
SOC
: N
Pox C (mg ∙ kg soil¯¹)
Surface
10 cm
Surface
10 cm
rS= 0.508**
r10
= 0.594**
a)
b)
Results ǁ Implications of the Soil Quality on the Yield of Upland Rice
30
(Appendix 5.1, Fig. B (b)). There is a larger degree of variation in the data points whereby some high-
yielding fields have low P Avail or K Exch levels. It does appear, however, that once again a level
above 1000 mg Pox C ∙ kg soil¯¹ will translate to a higher yield (Appendix 5.1, Fig. B).
4.2.1.1 Regression Analysis
Table 4: Multiple stepwise regression results for the dependent factor, yield, at the soil surface at a confidence level of 99% (p<0.05). Independent factors included: bulk density, pH, Pox C, SOC:N, N% and SOC %.
Variable Model 1 Model 2
pH -0.635 -0.515
Pox C
0.329
R² 0.403 0.497
R² Adjusted 0.379 0.456
n 27 27
Significant parameters found via the Pearson’s correlation coefficient test were then applied to a
multiple stepwise regression analysis to investigate which were explanatory factors for yield
variance. Two possible models explain the variance found in the yield of upland rice when using the
soil surface data (Table 4). In both, pH is a significant contributor. 40.3% (37.9% if adjusted) of the
variance observed is due to pH alone and, when coupled with Pox C, 49.7% of the variance (adjusted
45.6%) is accounted for (Table 4). The equations are: for Model 1, y =-610(pH) +3985, and for Model
2, y = 0.487(PoxC) – 495(pH) +2996.
Multiple stepwise regression analysis with the 10 cm data indicates that pH is the sole contribute to
the variance observed in yield, where R²= 0.513 (Adjusted R²=0.494, p= 0.000). Independent
variables included were: bulk density, pH, Pox C, C:N, N% and SOC %. There were no significant
models found at 30 cm. The equation for the model is y = -702 (pH) + 4347.
Implications of the Soil Quality on the Yield of Upland Riceǁ Results
31
4.2.2 Stock Values and Yield
A mass equivalent approach was used to calculate the upper 10 cm quantities of carbon and the
nutrients (N,P Avail and K Exch) due to the variation in bulk density; furthermore, Pearson’s
correlation coefficient test revealed stronger significant differences when the mass equivalent values
were used.
The mass equivalent (81 kg) in carbon stocks of the upper 10 cm was positively correlated with yield
(r=0.560, p<0.005) (Figure 18a). The strongest correlation was found between yield and nitrogen
stocks of the upper 10 cm (mass equivalent) where r=0.587 (p<0.005) (Figure 18b). No significant
relationship was found between yield and P Avail or K Exch; results appear to indicate there may be
a negative tendency between yield and P Avail (Figure 18c, d).
0
200
400
600
800
1000
1200
1400
1600
0,00 1,00 2,00 3,00 4,00 5,00
SOC (kg ∙ m¯²)
0
200
400
600
800
1000
1200
1400
1600
1800
0,00 0,10 0,20 0,30 0,40
N (kg ∙ m¯²)
0,00 0,20 0,40 0,60 0,80 1,00 1,20
P Avail (g ∙ m¯²)
0,00 5,00 10,00 15,00
K Exch (g ∙ m¯²)
Yie
ld (
kg ∙
ha¯
¹)
a) c)
b) d)
r = 0.587**
r = 0.560**
Figure 18: The relationship between upland rice yield (kg·ha¯¹) and the upper 10 cm quantities, in equivalent masses of soil, 81 kg, of a) SOC, b) N, c) P Avail and d) K Exch. Soil samples and yield measurements were taken after the harvest of one cropping of upland rice from fields with a preceding fallow length of 5 years. Analysed by Pearson’s correlation coefficient test at a confidence level of 95%. SOC and N, n=81; P Avail and K Exch, n=27
Results ǁ System Influences
32
4.3 System Influences
4.3.1 Topographical Influence
Distances between the plots on the same slope were restricted to approximately 5 meters due to
total slope lengths of approximately 70 meters- a weakness mentioned in the plot layout design
(Refer to Methodology, 3.3 General Plot Layout). It was thought that the plots were placed too
closely to accurately reflect the relationship between the soil parameters and slope position. The
soil parameters in question were SOC, N and Pox C as the sampling spanned across three rows
within each plot; in other words, sampling was done at least every 5 meters down the slope (Refer
to Methodology, 3.3 General Plot Layout for sampling sites). However, this does not appear to have
skewed the soil results as ANOVA whereby each individual row was compared found no
contradicting results.
4.3.1.1 Impact on Soil Parameters
To investigate the influence slope position, or indirectly erosion, may have on soil quality, focus was
placed on the following parameters as it is thought they would be most likely affected: clay stock,
SOC stock, Pox C, N stock, P Avail stock and K Exch stock. Of those soil parameters, the clay content,
SOC stocks, N stocks and P Avail stocks were significantly influenced by slope position (Table 5 and
6).
Table 5 The clay and carbon content (0-5 cm) at the top, middle and bottom of a continuous slope. Samples are from three fields with five-year preceding fallows and taken after the harvest of one cropping of upland rice
Slope Position
Soil Parameter Top Middle Bottom
Clay (kg ∙ m¯²) 23.8 ± 2.0ᵃ 15.7 ± 2.5ᵇ 20.4 ± 1.6ᶜ
SOC Stock (kg · m¯²) 1.50 ± 0.32ᵃ 1.43 ± 0.20ᵃᵇ 1.30 ± 0.25ᵇ
Pox C (mg·kg soil¯¹) 938 ± 192 978 ± 151 1004 ± 240
*Different letters within parameter categories indicate a significant difference, analysed by ANOVA at a confidence level of 95%
Clay content displays a negative relationship with slope position; this specific dataset indicates that
the middle of a slope will have the least clay (Table 5). This pattern is reflected in bulk density as
samples with lower clay content appear to have lower bulk densities, although this result was not
significant.
The results indicate that carbon content is significantly affected by slope position as a negative
correlation was found; the top of a slope will have the largest SOC stock (Table 5). Pox C, although
not statistically significant due to the large standard deviation, interestingly depicts the opposite
trend with slope position (Table 5).
System Influencesǁ Results
33
N stocks are greatest at the bottom of a slope (Table 6); the opposite trends displayed by SOC stocks
and N stocks may explain the significant decrease in the C:N ratio with slope position. A general
decreasing trend is observed between P Avail stocks and slope position; however, statistical
significance is found only at the soil surface and between the middle and bottom slope positions
(Table 6). The K Exch stocks appear to not be affected by slope position (Table 6) although
significant differences in K Exch levels were found at 10 cm, where levels increased from the top to
the middle slope positions.
Table 6: The nutrient stocks at the soil surface and at a depth of 10 cm according to the topographical positions within a slope: top, middle and bottom. Samples were taken from fields with five-year preceding fallows and after the harvest of one cropping of upland rice.
Slope Position
Soil Parameter Depth Top Middle Bottom
Stock N (g · m¯²)
0-5 cm 130 ± 23 123 ± 16 120 ± 22
5-10 cm 113 ± 17ᵃ 121 ± 16ᵃᵇ 125 ± 18ᵇ
Stock P Avail (g·m¯²)
0-5cm 0.323 ± 0.19ᵃᵇ 0.425 ± 0.18ᵃ 0.252± 0.11ᵇ
5-10 cm 0.101 ± 0.05 0.152 ± 0.11 0.089 ± 0.05
Stock K Exch (g·m¯²)
0-5 cm 5.07 ± 2.8 5.70 ± 2.2 5.68 ± 2.0
5-10 cm 2.82 ± 1.0 3.70 ± 0.80 3.48 ± 0.94
*Different letters within parameter categories indicate a significant difference, analysed by ANOVA at a confidence level of 95%
Results ǁ System Influences
34
4.3.1.2. Influence on the Yield of Upland Rice
ANOVA indicates no significant differences exist between yield and slope position. Multivariate
stepwise regression analysis of the yield variance did not identify slope position as an explanatory
parameter. There does appear to be an increasing trend in yield as one moves down a slope
(Appendix 5.2. Fig. C), however the differences are small and show a large variation (Table 7).
Table 7: The yield in upland rice assessed directly from plots placed at the top, middle and bottom of a continuous slope from fields with five-year preceding fallow lengths.
Slope Position Yield (kg · ha¯¹)
Top 1017.62 ± 124.85
Middle 1116.15 ± 359.62
Bottom 1173.93 ± 287.45
4.3.2 Fallow Length Impact
In general, it must be kept in mind that the overall sample size is quite small making it plausible that the values do not reflect actual levels and, as such, the influences that fallow length will have. It is important for one must consider the field history as past land use cycles will have long-term effects on the soil. Furthermore, the 2-year fallow field appears to have exceptionally high values in comparison to other fields hence, as the sample size is only one, may skew results (Table 8 and 9).
4.3.2.1 Impact on the Soil Parameters
The impact of fallow length on the soil parameters does not follow what is theoretically expected.
pH and CEC show no relationship with fallow length. Bulk density has conflicting correlations with
fallow length depending on depth; at the surface it has a weak positive correlation (r=0.282*) while
at 10 cm it has a stronger negative correlation (r=-0.287**). Clay content is positively correlated to
fallow length as a significant correlation is found at 10 cm (r=0.424*).
SOC% has the strongest correlation with fallow length, although negative (Table 8). Pox C reflects
the same trend as SOC% though the correlation is much weaker (Table 8). Of the nutrients, N % is
the single parameter to show a correlation with fallow length; at the soil surface it has a weak
negative correlation (r = -0.268*) whereby it is slightly stronger at 10 cm (r=-0.328**).
System Influencesǁ Results
35
Table 8: The carbon concentrations at the surface and ten cm depth of fields grouped according to the duration of the preceding fallow¹
Fallow Length (Years) SOC % Pox C (mg · kg¯¹)
Surface 10 cm Surface 10 cm
2 4.59 ± 0.71ᵃ 3.58 ± 0.60ᵃ 1143 ± 83ᵃ 770 ± 179ᵃ
3 3.95 ± 0.59ᵃ 2.42 ± 0.48ᵇᶜ 959 ± 130ᵇ 558 ± 124ᵇ
5 4.05 ± 0.75ᵃ 2.93 ± 0.76ᵃᶜ 978 ± 151ᵇ 618 ± 150ᵇ
10 3.00 ± 1.2ᵇ 2.07 ± 0.47ᵇ 808 ± 174ᶜ 556 ± 107ᵇ
11 4.20 ± 0.52ᵃ 2.79 ± 0.52ᵃᶜ 1087 ± 148ᵃ 590 ± 119ᵇ
Correlation Coefficient (r)¹
-0.334** -0.330** -0.267* ns
¹ Samples taken after the harvest of one cropping of upland rice. Different letters within categories represent a
significant difference (Analysed by ANOVA, LSD test (equal variance) or Games-Howell test (variance unequal) at a confidence level of 95%) 2 yr n= 9, 3 yr n= 18, 5 yr n=27, 10 yr n=18, 11 yr n=9 ²Pearson’s correlation coefficient test at a confidence of 95% (*) or of 99% (**)
Both the C:N and SOC:Pox C ratios show a weak negative correlation with fallow length (Table 9). ANOVA analysis indicates the majority of the significant differences are between those involving the 10-year fallow category (Table 9).
Table 9: The C:N and SOC:Pox C ratios at the surface and ten cm depth of fields grouped according to the duration of the preceding fallow¹
Fallow Length (Years) C:N SOC:Pox C
Surface 10 cm Surface 10 cm
2 12.1 ± 1.4ᵃ 11.4 ± 1.2ᵃ 40.1 ± 4.7ab
47.4 ± 5.2cd
3 11.2 ± 0.64ᵃᵇ 9.25 ± 0.82ᵇ 41.5 ± 5.5a 43.7 ± 3.5
c
5 11.7 ± 0.77ᵃᵇ 10.2 ± 1.2ᶜ 41.4 ± 4.9a 48.0 ± 8.6
c
10 10.8 ± 2.9ᵇ 9.52 ± 1.2ᵇ 36.6 ± 8.8b 37.6 ± 6.8
b
11 10.8 ± 0.56ᵃᵇ 9.82 ± 0.76ᵇᶜ 38.9 ± 3.7ab
47.6 ± 5.9cd
Correlation Coefficient (r¹)
-0.222* ns -0.255* -0.262*
¹ Samples taken after the harvest of one cropping of upland rice. Different letters within categories represent a
significant difference (Analysed by ANOVA, LSD test (equal variance) or Games-Howell test (variance unequal) at a confidence level of 95%) 2 yr n= 9, 3 yr n= 18, 5 yr n=27, 10 yr n=18, 11 yr n=9 ²Pearson’s correlation coefficient test at a confidence of 95% (*) or of 99% (**)
Results ǁ System Influences
36
4.3.2.2 Impact on the Stock Levels
Figure 19: The relationship between SOC stocks of the upper 10 cm in an equivalent mass of soil, 88.24 kg, and fallow length. Soil samples were taken after one harvest of upland rice. Different letters within categories represent a significant difference (Analysed by ANOVA, LSD test (equal variance) or Games-Howell test (variance unequal) at a confidence level of 95%). 2 yr n= 9, 3 yr n= 18,
5 yr n=27, 10 yr n=18, 11 yr n=9
The average mass of the soil of the upper 10 cm is 88.24 kg; therefore, all stocks of the upper 10 cm
are calculated in terms of quantities in 88.24 kg of soil (via the mass equivalence approach. Refer to
Methodology, 3.4 Calculations and Statistical Analysis). While SOC% is negatively affected by
increasing fallow lengths, its stock levels do not reflect the same (Figure 19). On the contrary, SOC
stocks of the upper 10 cm will generally increase with fallow length; significant differences were
observed between 2- and 3-, 5- and 11-year fallows (Figure 19). The 10-year fallow however is an
exception as the SOC stock level is similar to that of the 2-year fallow (Figure 19). However, the
Pearson’s correlation coefficient test revealed no significant correlation.
Pox C stocks of the upper 10 cm still show a consistent negative correlation with fallow length (r=-
0.285**). ANOVA results show significant differences when the Pox C stocks of the 2-yr fallow are
compared with the other fallow lengths (Table 10).
Fallow length negatively, albeit weakly, affects the N stocks of the upper 10 cm as the Pearson’s
correlation coefficient test revealed an r value of -0.336**. ANOVA results show a significant
difference between the N stock of the 2- and 10-yr fallow (Table 10); while the 10-year fallow
average is low for all the nutrient stocks the average yield level, 1325 ± 322 kg · ha¯¹, is highest.
Furthermore, the 10-year fallow category includes the most productive field, 10F3.
Stocks of P Avail and K Exch of the upper 10 cm are not influenced by fallow length (Table 10).
ᵃ
ᵇ ᵇ
ᵃ
ᵇ
0,00
0,50
1,00
1,50
2,00
2,50
3,00
3,50
4,00
0 2 4 6 8 10 12
SOC
Sto
ck (
kg·m
¯²)
Fallow Length (Years)
System Influencesǁ Results
37
Table 10: The stocks of Pox C, N, P Avail and K Exch of the upper 10 cm in an equivalent mass of soil of fields grouped according to the duration of the preceding fallow¹
Fallow Length (Years)
Pox C stock of Upper 10 cm (g· m¯²)
N stock of Upper 10 cm (kg · m¯²)
P Avail stock of Upper 10 cm (g · m¯²)
K Exch stock of Upper 10 cm (g · m¯²)
2 78.3 ± 11a 0.295 ± 0.02ᵃ 0.475 ± 0.16ᵃ 17.6 ± 6.7ᵃ
3 67.2 ± 8.5bd 0.274 ± 0.03ᵃ 0.412 ± 0.14ᵃ 8.27 ± 2.4ᵃ
5 67.6 ± 9.3bd 0.273 ± 0.03ᵃ 0.629 ± 0.31ᵃ 10.2 ± 2.2ᵃ
10 59.7 ± 8.2c 0.220 ± 0.05ᵇ 0.271 ± 0.09ᵃ 9.77 ± 4.6ᵃ
11 71.3 ± 9.6ad 0.292 ± 0.03ᵃ 1.33 ± 0.81ᵃ 15.0 ± 2.3ᵃ
¹ Samples taken after the harvest of one cropping of upland rice. Different letters within categories represent a significant
difference (Analysed by ANOVA, LSD test (equal variance) or Games-Howell test (variance unequal) at a confidence level of 95%) Pox C and N : 2 yr n= 9, 3 yr n= 18, 5 yr n=27, 10 yr n=18, 11 yr n=9; P Avail & K Exch: 2 yr n=3, 3 yr n = 6, 5 yr n=9, 10 yr n = 6, 11 yr n=3
4.3.2.3 Influence on the Yield of Upland Rice
Figure 20: The yield (kg · ha
-1) in upland rice after a preceding fallow of 2, 3, 5, 10 or 11 years. Blue data
point at 11 years is excluded from the trendline. (1)
is if the data point from 11 years is excluded at a confidence level of 95% for Pearson’s correlation coefficient test (2) is the Spearman’s rank correlation coefficient at a confidence level of 95% if the data point from 11 years is excluded
0
200
400
600
800
1000
1200
1400
1600
1800
0 2 4 6 8 10 12
Yie
ld (
kg ∙
ha¯
¹)
Fallow Lenth (Years)
r(1)= 0.709* r(2)= 0.778*
Results ǁ System Influences
38
Figure 20 illustrates the relationship between fallow length and upland rice yield; it suggests a
positive relationship as the Pearson’s correlation coefficient test revealed an r value of 0.709.
However the data point from 11F1, an 11-year fallow, does not follow the predicted trend as it is
much lower than expected (Figure 20). Independent student t-tests revealed significance lies
between upland rice yields from fields of 3-year and 5-year fallows (p=0.029). The yield data for the
2- and 11-year fallows was not included in the Independent student t-tests as sample sizes were only
one and, thus, were not defined.
4.3.2.4 Links Between Soil Quality, Fallow Length and Yield
In general, many of the relationships between soil parameters and yield disappear when fallow
length is taken into consideration; such correlations should have been re-enforced as data suggests
yield increases with fallow length (Figure 20). The relationships between fallow length and the
chemical soil parameters will be presented; the 11-yr fallow field continues to display discrepancies
as it does not follow the general trends.
Figure 11 depicts the relationship between SOC % and N% with data points colour-coded according
to yield levels; the figure suggests that the higher- yielding fields are correlated to lower levels of
SOC and N (Figure 11). In respect to fallow length, as mentioned, the longer fallow lengths (i.e. 5-
and 10-yr) have higher yields and, thus, lower SOC and N levels (Figure 11). The C:N ratio is lowest
for 10F3, the 10-yr high-yielding field, validating the negative weak correlations found between
fallow length and both SOC % and C:N (Figure 11, Table 8 and 9). The same general trend is depicted
in Figure 21, where SOC and N stocks appear to be inversely related to yield levels and fallow length.
11.4
9.94
0
50
100
150
200
250
0,00 0,50 1,00 1,50 2,00 2,50 3,00
Sto
ck N
(g
· m¯²
)
SOC Stock (kg · m¯²)
Surface
10 cm
SOC:N Surface
SOC:N 10 cm
Figure 21: Relationship between SOC stock and Stock N at the soil surface and at a depth of 10 cm. Individual points colour-coded according to fallow length and yield levels (kg∙ha¯¹): blue is 2, 3 and 11-year fallow and below 1000, red/pink is 5 or 10-year fallow and above 1000 and green is 10F3, a 10-year fallow with the highest yield, 1552. Soil samples were taken after the harvest of one cropping of upland rice from fields. Analysed using the Pearson’s correlation coefficient test at a confidence level of 95%. n = 81
r S = 0.851**
r 10
= 0.793**
System Influencesǁ Results
39
Figure 12 illustrates the relationship between SOC % and a) P Avail, and b) K Exch and the link to
both yield and fallow length; there appear to be no obvious trends although the highest-yielding
field has the lowest levels of both nutrients (Figure 12a and b).
Similar trends are observed when looking at Pox C, the labile fraction of SOC. The SOC:Pox C ratio
and its link to fallow length and yield, depicted by Figure 13, reveals that again the highest-yielding
field has a lower ratio. A lower SOC:Pox C ratio corresponds to a larger Pox C pool, relative to SOC.
Again, the same pattern is observed in Figure 14 whereby lower Pox C and N% levels are linked to
the longer fallow lengths with higher yields.
4.3.3 Alternative Measures of Land Use Intensity
Alternative methods of measuring land use intensity consider the cropping cycles in a specific
preceding length of time, in this case, 10 years. Analysis with the two alternative land use intensity
measures, ACi and R Index, did not reveal any additional or different trends.
Multiple stepwise regression analysis did not reveal land use intensity as a significant explanatory
factor to the yield variance observed. A linear relationship between R index and yield is suggested
by Figure 22a, although insignificant (r=-0.527, p=0.179, if blue data point excluded). The negative
correlation between ACi and yield is moderately strong (Figure 22b, if the blue data point is
excluded, p<0.05). Spearman’s rank correlation analysis revealed insignificant results. In both cases,
as land use intensity increases, yield will tend to decrease (Figure 22a andb). The trends, however,
are with the 11F1 data point excluded as it appears to be an outlier as it may have been influenced
by socio-economic factors.
Figure 22: The relationship between yield (kg · ha-1
) in upland rice and land use intensity, measured via two different methods: the R Index and ACi. The trendlines are representative of the data with the blue data point (11F1) excluded.
0
400
800
1200
1600
2000
0 5 10 15 20 25
Yie
ld (
kg ∙
ha¯
¹)
ACi
0
400
800
1200
1600
2000
0 10 20 30 40
Yie
ld (
kg ·
ha¯
¹)
R Index (%) a) b)
r= -0.796*
Results ǁ From the Farmers’ Perspective
40
- NEPL NPA
-geographically defined
-Clearly mapped
-Farmers compensated
-Signs posted
-Policy change
1910
Establishment of Ban Navene
2001
-Road built
-Large-scale irrigation(11 ha)
2010
- Maize contract-farming initiated (32 households)
- Primary school built
2012
(present)
2004
- Volunteer health clinic
- Veterinarian services
-Land tenureship defined
1985
-Khamu ethnicity
-Current headman, Thong Phouy, emigrated
1993
Establishment of NEPL NPA
1990
-Small-scale irrigation (8ha)
1995
-Buffalo increase
4.4 From the Farmers’ Perspective
Qualitative data was collected to shed light on
what changes have occurred and how the
farmers’ perceive soil quality and system
productivity (Refer to Methodology, Sections
3.5 -3.7). The data will be used in conjunction
with the quantitative data throughout the
discussion. A list of interviewees can be found
in Appendix 6.
4.4.1 Historical and Socioeconomic
Context for Ban Navene
The current socio-economic status of Ban
Navene is the product of past historical events,
depicted by the timeline in Figure 23. Ban
Navene was first established in 1910 as a Moy
ethnic village and later became Khamu-
dominated in 1985, comprised of a total of 35
households (Figure 23 and 24). In 1990, the
first irrigation system was built where it
covered 8 ha and benefited 15 families (Figure
23). The dominant livelihood strategy was
shifting cultivation where livestock, such as
pigs and buffalo, were integrated; in 1995
there was a boom in the buffalo numbers as
villagers were given access to credit (Figure
23). In 2000 there was a spike in population
to a total of 46 households (Figure 24); people
from the Pakxeng district were encouraged to
migrate to Ban Navene by the Lao Government
due to the extensive paddy and upland area.
The development led to the construction of a
road to Nam Xoy, the village along the highway
between Sam Nuea and Luang Prabang, and
the construction of a large-scale irrigation
system funded by DAFO (Figure 23).
Figure 23: The historical timeline of Ban Navene from its establishment in 1910 to the present date, 2012. Data collected during the introductory meeting, with the headman Thong Phouy as a key informant.
2003
2005
2007
2008
From the Farmers’ Perspectiveǁ Results
41
In 2003, again coinciding with a population spike to 60 households (Figure 24), land tenureship was
defined by DAFO where the land surrounding Ban Navene was mapped and divided among the
households according to the following five criteria:
1. Who used the land previously
2. If a household had a paddy field, then they were entitled to three upland fields
3. If a household did not have a paddy field, then they were given five upland fields
4. Any unused land was appropriated for the community forest or conservation
a. Land from the community forest is given to new or in-need families
5. Every household was ensured enough land for two vegetable gardens
In 2008 the policy was adjusted in where a restriction of three to four upland fields per household
has been imposed (Figure 23).
Contract-farming with Thong La, a maize company, was initiated in 2010 by 32 households who
approached DAFO to ask for assistance with contract dealings (Figure 23). Currently (2012), there
are 45 households cultivating maize in Ban Navene. The contract is binding until 2014 and includes
the following contingencies:
- Input requirements and services are provided by Thong La at the following prices:
o Seed: 15 000 kip/kg seed or 30 kg maize/kg seed
o Transport: 200 kip/kg maize transported out
- Ban Navene farmers are required to sell all their maize harvest to Thong La at market price
(decided by Thong La)
- Road upkeep is the responsibility of Thong La.
In the middle of November of 2012, Thong La finally arrived to dehusk and collect the maize at a
price of 1 000 kip/kg maize; the farmers expressed disappointment in the allocated price.
In 2012, 43 households cultivated paddy rice on 46 ha, of which less than half is irrigated. There are
26 or 27 households (key informant was unsure) that do not cultivate upland rice but still own three
upland fields.
0
10
20
30
40
50
60
70
80
1980 1985 1990 1995 2000 2005 2010 2015
Ho
use
ho
lds
Year
Figure 24: The population growth, represented by the number of households, of Ban Navene from 1985 - 2012
Results ǁ From the Farmers’ Perspective
42
4.4.2 The Establishment of the NEPL NPA
The NEPL NPA was first established in 1993 but it was not until 2003 that the NPA boundary was
geographically mapped in conjunction with the LUP-LA programme. Policies were introduced in
2005 that restricted entry to and cultivation within the NEPL NPA (Figure 23). However, in 2008 the
policies were adjusted as officials found them too restrictive and difficult to enforce whereby:
- NTFPs can be collected within specific seasons, i.e. bamboo cannot be collected from
May-Aug while medicinal herbs have no restrictions
- No hunting
- No cultivation (DAFO official, pers. comm., 10/2012).
Thirteen families in Ban Navene were affected by the establishment of the NPA as their upland fields
were within the boundary. As compensation, they were given fields closer to the village but were
rarely of equivalent size or quality.
4.4.3 The Constraints of Upland Rice Production
The top three constraints to upland rice production were
identified as, in order, disease, labour supply and rodents by 20
farmers in Ban Navene (Table 11). Ranking did result in duplicate
scorings for some constraints, thus the percentage does not total
to 100%. When strictly regarding the frequency a constraint was
ranked as the most limiting (i.e. a score of 1), labour supply
ranked as the greatest constraint to upland rice production by 30
% of the respondents (Table 11). However, the overall scores of
the constraints paint a slightly different picture where disease is
ranked first, followed by labour supply and then rodents (Table
11). Soil suitability and land availability are ranked as the fourth
and fifth most limiting, respectively (Table 11). Please refer to
Appendix 7 for full ranking results.
Figure 25: Rice with a dead panicle of unfilled grains, termed ‘whitehead’ and indicative of stem borer infestation or rice blast (IRRI, 2009).
From the Farmers’ Perspectiveǁ Results
43
Table 11: The major pre-determined constraints to upland rice production ranked in order, from 1 being the most limiting, by shifting cultivators in Ban Navene
a
Constraint Rank % as No. 1
b
Disease 1 20
Labour Supply 2 30
Rodents 3 20
Soil Suitability1 4 20
Land Availability
2 5 15
Insects 6 15
Wild Animals 7 0
Rainfall3
8 10
Weeds 9 0
Erosion 9 5 a Sample size is 20 households
b Percentage of respondents that ranked constraint as 1
1 Soil suitability according to its ability to support rice
2Included shortened fallow length
3Miscommunication: original constraint was ‘insufficient
rainfall’ but was translated as ‘water availability’
Many respondents identified 2012 as an unfavourable year weather-wise; at the time of seeding
(June) there was minimal rain while the latter part of the season was quite wet (pers. comm. Thong
Phuoy, 09/12). Rodents, insects and rice disease were said to be prevalent, supported by first-hand
observations of root grubs, wild boar damage, disease and field rats (Figure 25).
The number of adults in a household appears to influence whether or not land availability is seen as
a limitation to upland rice production; households composed of at least 7 adults ranked land
availability as one of the top three constraints. Alternatively, households comprised of three adults
or less identified labour supply as a major constraint to upland rice production; of the 15 households
with three adults or less, 13 ranked labour supply as a ‘top three’ constraint.
Results ǁ From the Farmers’ Perspective
44
Ban Navene- a village in transitionǁ Discussion
45
5 Discussion
5.1 Ban Navene- a village in transition
Ban Navene has not been isolated from the widespread transformation of agricultural systems
occurring in Southeast Asia. There has been a decline in the number of households actively engaged
in traditional long fallow shifting cultivation; 34 % of households no longer cultivate upland rice and
29% are engaged in a composite form of cultivation, i.e. CSA. This transition has of course been
facilitated by the development of Ban Navene’s paddy area where a large-scale irrigation system was
introduced. Furthermore, 59% of households now practice partial swiddening meaning they have
included maize cultivation into their upland rotation; this is a substantial proportion considering
maize was introduced only in 2010 (Refer to Results, 4.4.1). However, due to this recent
introduction, the full implication of cash crop inclusion on the livelihood strategies cannot be
assessed. This step away from upland rice dependency has been advocated by the government and
some NGOs (Moore, et. al., 2011).
Households that have maintained upland rice cultivation have adopted the intensification strategy of
shortening fallow lengths. Roder (1997) suggests poor infrastructure, low support and minimal
access to markets will accelerate this process hence land degradation may be prominent in Ban
Navene. According to the headman, Thon Phouy, fallow lengths today are commonly between two
to five years whereas they were once upwards of ten years (pers. comm., 09.12); the claim is
supported by comments made during in depth interviews and it appears declining fallow lengths is
indeed a dominating trend. Furthermore, there is a pattern where fields located farther away are
less intensively used, as suggested by Nielsen et al. (2006) and Cramb et al. (2009) to occur; at the
time of the field study, farmers were forced to move their further away from the village, a decision
made collectively to allow the fields in close proximity time to recover.
The setting of Ban Navene may lead to an intensification that is environmentally and socio-
economically unsustainable with outcomes that are not clearly understood.
5.2 The Ecological Sustainability
For Ban Navene, declining fallow length may have enormous implications on the ecological
sustainability of shifting cultivation as they are resource poor thus are entirely dependent on the
fallow period to maintain productivity.
The soil quality will affect the yield levels of upland rice. The links between parameters, combined
with corresponding yield levels, will determine what criteria are important for sustainable rice
productivity. The soil quality and upland rice yield will then be discussed separately as a function of
two system influences: the topography of a field and the fallow length.
Discussion ǁ The Ecological Sustainability
46
It is important to note the discussion of the interactions between parameters and the influence of
fallow length is based on results from the fallow length study, while those from the topographical
study provide the base for the discussion of the effect soil quality has on yield levels and the
influence of slope position. It is thought that, as yield was assessed directly from the plots, the
topographical study would better represent the soil quality effects on upland rice yields.
5.2.1 Soil Quality: the Parameters and Their Interactions
The amount of nutrients returned to the soil is highly dependent on the burn of a field and hence
should be taken into account when considering soil quality (Bruun et al., 2006). Farmers of the
sampled fields were asked of the timing and quality of the respective burn; all were burned between
the end of April and beginning of May 2012 and rated as either ‘good’ or ‘excellent.’ Furthermore,
as a precaution, statistical analysis according to the ratings was done and revealed no significant
differences in parameters. Thus, the links between the soil parameters and comparisons between
plots are not due to variability in the burn timing and quality.
Farmers are highly aware of characteristics indicative of good quality fields. Their own perceptions
of soil quality relate to its colour, moisture, temperature and texture. Common descriptors of soil
quality were ‘dark’, ‘moist’, ‘cool’, ‘soft’ and ‘no stones’. A relatively flat field in close proximity to a
water source was the general criteria of a good quality field and was highly sought after.
Furthermore, certain plant species serve as indicators of suitable soil for upland rice production.
When asked if the soil quality has changed, interviewees had mixed responses where some claimed
that soil quality has decreased while others were insistent that it has remained the same. Studies
should take into account the perceptions of the farmers as their management practices can be field-
specific, i.e. studies have suggested that fields of poor quality will be left fallow for longer periods of
time (Aumtong et al., 2009; Bruun et al., 2006; Roder et al., 1995). Such insight will give a better
interpretation of the data found.
The values found for the soil parameters are similar to those of Roder et al. (1995), a study also done
in Lao PDR. Notable differences however are in the SOC % where Roder et al.’s (1995) values are
considerably lower (assuming 58% of the soil organic matter is carbon), and of higher CEC values.
The differences may be due to the soils’ inherent physical properties, but this is hard to say as Roder
et al. (1995) do not mention the clay content of their field sites. Of important note is that shifting
cultivation is a no-till system and the farmers of Ban Navene do not add external inputs such as
fertilizer; both would affect the soil fertility and a soil’s metabolic processes.
The Ecological Sustainabilityǁ Discussion
47
The results indicated SOC and Pox C are associated with the majority of the investigated soil
parameters, i.e. bulk density and nutrient levels. Hence the two will be discussed as possible key
indicators of soil quality.
5.2.1.1 SOC: a Key Indicator
The quantitative results suggest SOC is a key indicator of soil quality as it is correlated to many of the
parameters investigated; it was found to influence all parameters but CEC and pH (Refer to Results,
4.1.2, Table 1 and 2). This finding agrees with the farmers’ perception of soil quality as the
descriptors used are commonly affiliated with organic carbon; i.e. a dark soil colour will indicate a
humus layer, a fraction of the total SOC.
The strong correlations found between the soil parameters and SOC are of no surprise due to the
significant functions of organic carbon in a soil (Bruun et al., 2009). The importance of SOC is more
prominent in soils that are nutrient poor and to which no external inputs are added (Bruun et al.,
2009) as is the case in this study.
The physical parameters of a soil, i.e. bulk density and clay content, were both negatively correlated
to the SOC content (Results 4.1.2, Table 1, 2 and 3). Theoretically, as SOC determines soil
aggregation, the higher the SOC content, the lower the bulk density (Brady and Weil, 1999). This will
also explain the positive trend of bulk density with soil depth as the deeper soil layers will have a
lower SOC content and pore volume. Discrepancy lies however in the relationship found between
SOC and clay content of a soil as it is counterintuitive and opposite to what the study by Aumtong et
al. (2009) found. It is expected a higher clay content in soils of similar clay mineralogy will better
stabilize SOC by chemical mechanisms (Bruun et al., 2010; Feller and Beare, 1997). The conflicting
data is more likely due to the small sample size since the texture for only one full soil profile from
each plot was analysed.
The correlations between the nutrient levels and SOC again suggest its significant role as a nutrient
source, especially in regards to N% (Results 4.1.2, Figure 11). The result is similar to the finding by
Funakawa et al. (1997), where soil organic matter was a determinant of plant-available nitrogen;
although total N % was measured similar patterns are expected. The soils of Ban Navene have low
C:N ratios, the average being 9.94 at the surface. This is surprising as nitrogen is often the limiting
factor in production. The low ratio indicates a high level of microbial activity (Tanaka et al., 1998)
and thus, when combined with the relatively high SOC%, suggests the soils in the Ban Navene area
are not degraded. The correlation between C:N ratio and K Exch is interesting as it implies that
potassium availability within the soil will promote microbial activity.
Weak positive correlations were found between SOC % and both P Avail and K Exch (Results 4.1.2,
Figure 12) which again reflects the role of soil organic matter as a source of nutrients. The study by
Roder et al. (1995) found both K Exch and P Avail levels will increase with ash deposits. The ash
content will influence the K Exch levels in the soil to a greater degree (Bruun et al., 2006); however
Discussion ǁ The Ecological Sustainability
48
this is not reflected in the results where a correlation between P Avail and SOC % at the soil surface
was found while no such correlation with K Exch was. The correlation was however found at the ten
cm depth, possibly reflecting the high mobility of potassium within the soil profile although this is
speculative as the lack of correlation at the soil surface may also be explained by the large variation
found.
5.2.1.2 A Closer Look at Pox C and its Potential
The low sensitivity of SOC to land use changes is a disadvantage if it is to be used as a suitable
indicator of soil quality and degradation (Aumtong et al., 2009). The results indicate that the
sensitivity of SOC and Pox C as indicators is comparable; the patterns are similar however
correlations with Pox C are slightly weaker. Furthermore, the lower SOC:Pox C ratio at the surface of
a soil illustrates the carbon decay process whereby the surface layer will have a higher content of
fresh plant and animal residues (Brady and Weil, 1999) thus greater Pox C levels.
An advantage of the use of Pox C may be in detecting changes in nutrient levels as the labile carbon
pool is a greater source; P Avail displayed stronger correlations with Pox C than with SOC %, and Pox
C correlations to K Exch were consistent at both soil depths. The stronger correlation between P
Avail and Pox C may highlight its role as a supply of organic phosphorous, the main source of P Avail
for plants in an acidic soil with high concentrations of Al- and Fe-oxides.
The inverse correlation between Pox C and CEC endorses the Pox C method as a sensitive tool in
assessing soil quality since no such correlation was found between SOC and CEC (Results 4.1.2, Table
1 and 2); however it is not easily explained. The low CEC values (11.5 – 14.0) of the soil in the Ban
Navene area indicate that the clay minerals are of the low-activity kaolinitic type; thereby the CEC
will be largely dependent on the pH of the soil (Brady and Weil, 1999). The pH-dependent charges
will also be closely affiliated with the SOC and, under such acidic conditions, will be positive. Hence
the low CEC values found. The lack of a correlation between SOC and CEC is thus surprising.
Furthermore, the correlation between Pox C and CEC is difficult to explain as it is not expected to be
an active contributor to CEC but instead a direct source of hydrogen ions. Speculatively, the
hydrogen ions may push the CEC lower; however for this rationale to hold bearing, both an inverse
correlation between Pox C and pH and a positive correlation between pH and CEC would have to
have been found. The uncertainties are more likely to do with the narrow range in CEC values that
was found and the ambiguous representation of Pox C.
Though the overall impression of soil quality is similar when using SOC % or Pox C as the key
indicators, the ease and low cost of the Pox C method may give it an advantage. The method can be
carried out in the field, requires little equipment and is relatively quick. All are important factors
when field work is conducted in isolated areas. Furthermore, the modification of doubling the
shaking time proportionally increased the measured Pox C levels; this did improve the sensitivity of
The Ecological Sustainabilityǁ Discussion
49
the method and, as few studies have been done under tropical conditions, may be a modification to
consider.
5.2.1.3 Additional and Surprising Finds
The positive correlations between the nutrients themselves indicates their interactions will influence
the availability of one another; it has been suggested by Bruun et al. (2006) that the availability of
phosphorus for instance will be a limiting factor in nitrogen mineralization.
The lack of correlations found between pH or CEC and SOC content or nutrient levels was
unexpected as they are known to chemically influence soils; they will also interact closely as high pH
will increase CEC via the soil’s pH-dependent charges (Brady and Weil, 1999). In general, the lack of
correlations involving CEC may be due to the narrow range in values found; the soils appear to all be
of kaolinitic clay mineralogy. The maximum pH found for the soil surface was a reading of 5.05,
indicating iron, aluminum, manganese and zinc are dominant (Refer to 2.1, Figure 1). A negative
impact on the plant availability of the measured nutrients, i.e. K Exch, P Avail and N, is expected as
pH decreases however no such correlations were found. Again, this may be due to the narrow range
found in pH values.
5.2.2 The Link between Soil Quality and Upland Rice Yield
It is difficult to isolate the direct influence soil quality has on upland rice yield as there are numerous
additional socioeconomic factors that may play a role, i.e. labour input, environmental conditions.
Thus studies show ambiguous results as to how soil quality is linked to yield levels. The inconsistency
in results is also due to environmental impacts. For instance the weak association found by Roder et
al. (1995) between SOC and yield levels in Lao PDR may be more related to the low moisture levels
as any increase in SOC will improve yields by a greater extent than in areas with sufficient moisture
(Bruun et al., 2006).
The results from the multiple regression analysis identify pH and Pox C as parameters responsible for
the yield variation observed; if both variables are included in a single model, 49.7% of the yield
variance is accounted for (Refer to Results 4.2, Table 4). However results also indicated upland rice
yield is correlated to SOC %, total N%, bulk density and the nutrient stock levels and thus will also be
discussed.
5.2.2.1 Upland Rice Yield and pH: plant uptake
The role of pH may be accentuated as the soils under cultivation are inherently acidic; this is
reflected in the results where alone it accounts for 40% of the yield variation observed. It is
Discussion ǁ The Ecological Sustainability
50
expected a higher pH would positively influence yield levels as nutrients are more readily available
to the crop. Nevertheless, the inverse relationship was found (Results 4.2, Figure 15).
The timing of soil sampling likely explains the conflicting pattern. Soil samples were collected after
harvest of the upland rice therefore the trend reflects the secondary effects of plant uptake; plants
will exude hydrogen ions through their roots to aid in the uptake of base cations and hence the
decrease in pH. Base cation uptake will have occurred to a greater extent in the higher-yielding
fields and thus will have lower pH values.
5.2.2.2 Upland Rice Yield and Pox C: a key relationship
In addition to it being an explanatory factor, Pox C had a stronger correlation to yield levels than
SOC% (Results 4.2, Figure 16). This suggests again that Pox C is a key indicator of soil quality and an
accurate tool in assessing the ecological sustainability of management practices. Studies however
on the effect of Pox C on yield levels in tropical systems are limited; Weil et al. (2003) did find Pox C
to positively influence yield levels of maize in Honduras. To understand the full implications, more
studies are needed.
As discussed, Pox C will promote microbial activity as it is easily degradable and thus will significantly
influence nutrient availability for plant uptake (Culman et al., 2012). The results may reflect this
relationship as it appears Pox C and total N% have a compounding effect on yield levels; a total N %
of 0.35% and a Pox C level above 1000 mg· kg¯¹ appears to correlate to a higher yield (Results 4.2.1,
Figure 17). This may indicate that to ensure a sufficient supply of plant available nitrogen, the soil
should contain a minimum level of 1000 mg ·kg-1of Pox C. When this threshold level is combined
with a C:N ratio above 11.0, the same pattern of higher yields is reflected (Results 4.2.1, Figure 17).
The positive influence a higher C:N ratio appears to have is counterintuitive however again it may
reflect the crop uptake of nitrogen.
5.2.2.3 Upland Rice Yield and Soil Carbon and Nutrient Stocks
The SOC, Pox C and total N stocks are positively correlated with yield, again suggesting the
importance of carbon and nitrogen in low external-input systems. This supports the suggestion that
the carbon content of soils will have greater implications for systems of areas that are drought prone
(Roder et al.,1995; Bruun et al., 2006), though 2012 was said to be a wet year in Lao PDR. Pox C
stock levels are weakly correlated to upland rice yields, surprising as their concentration levels are so
strongly correlated; however this may be due to the fact that Pox C is highly concentrated at the
surface and, consequently, when the upper ten cm is taken into account the strong correlation
becomes weaker.
The stocks of P Avail and K Exch are not significantly correlated to yield levels; however one could
speculate rice yields may be negatively correlated with P Avail stocks while positively with K Exch
stocks (Results 4.2.2, Figure 18). The P Avail stock is the only parameter that shows any kind of
The Ecological Sustainabilityǁ Discussion
51
negative correlation with upland rice yields, thus it may be suggested that phosphorus is the limiting
factor in system productivity.
5.2.3 System Influence: the topography of a field
There is concern that an intensification of shifting cultivation will lead to significant ecological
impacts due to increased risk of soil erosion; this has had implications on the agricultural
development policies in Lao PDR where reforestation and conservation projects have been
promoted in place of agriculture in the upland areas (Lestrelin et al., 2012).
The influence of slope position on soil quality will first be discussed and will lead to the implications
this has on upland rice yields. There are discrepancies between the topographical and fallow length
data sets in the interaction between clay content and SOC and the links between nutrient levels and
upland rice yield. This will be discussed further in Section 5.2.5: Quantitative Experimental Design.
5.2.3.1 Soil Quality as a Function of Slope Position
Farmers in Ban Navene did prefer level fields close to water sources as they had better soil quality
and were productive under short fallow management. Although slope position does appear to
somewhat influence the soil parameters, no clear association to the overall soil quality was found
(Results 4.3.1). Clay content appears to be lower downslope and validates the decreasing trend
found in the SOC stock; lower clay content will correspond to a smaller SOC stock. However, it is
surprising to find an accumulation of carbon at the top of a slope as this indicates no downward
movement of carbon occurs. Interestingly, the opposite pattern between Pox C and slope position
suggests the downslope accumulation is due to the downward movement of ash, as found by de
Neergaard et al. (2008); a study by Skjemstad et al. (2006) found the Pox C method sensitive to
charcoal content and, as samples were not screened, those at the bottom of the slope may have had
a higher content due to the ash movement. Hence Pox C levels would increase down a slope.
The nutrient stocks are not indicative of a distinct trend. The significant increase in the nitrogen
stock from the top of a slope downward in the five to ten cm interval suggests leaching may be more
prominent than erosion as no such relationship occurs at the surface. The same leaching effect may
explain the accumulation of potassium, a base cation, downslope and supports the finding by de
Neergaard et al. (2008); the differences however are not significant due to the high variability in the
levels. The phosphorus stock levels significantly decrease down a slope, an unexpected trend;
phosphorus however is quickly immobilised within the soil thus it will not be highly influenced by
leaching. Hence the stock levels may just reflect field variability.
The lack of correlations found between the soil parameters and slope position may indicate the
system is still at a sustainable intensity; the fallow length, in this case five years, with no successive
cropping is sufficient to control erosion. Furthermore, in general, the fields have a high SOC content
Discussion ǁ The Ecological Sustainability
52
if compared to Roder et al. (1995), thus promoting stable soil aggregates and reducing the risk of
erosion (Feller and Beare, 1997). It would be interesting to compare the influence of slope position
on fields of varying fallow lengths.
5.2.3.2 The Implication on Upland Rice Yield
Slope position does not influence the yield of upland rice as no correlations were found; although
the data was insignificant, it may suggest that there is a positive tendency of upland rice yield to
increase downslope (Appendix 5.2, Fig. C). A weakness of the study is the small sample size of three
fields; one field, 5F1, did not follow the increasing trend in that the top and middle plots had much
lower yield levels. Furthermore, the farmer from 5F1 began to harvest the two plots in question
alone and, although the intended process was followed, there is room for error in the labeling of the
harvested bags. No significant difference was seen in the grain size in regards to whether they
were harvested from the top, middle or bottom of a slope.
5.2.4 System Influence: the fallow length
The central ecological principle of shifting cultivation is the restoration of soil fertility and nutrient
levels through the use of fallow; this is preeminent in areas where farmers are resource-poor and
hence cannot restore soil fertility through the use of external inputs (Bruun et al., 2009).
According to the farmers interviewed, fallow length is a major influencing factor; a fallow length of
at least five years was the farmers’ preference as they will have ‘bigger trees, more water running
from the cut trees and more nutrients (5F2, pers. comm., 10/2012)’. Strategies to increase fallow
lengths, constrained by the LUP-LA programme, have been adopted whereby fields are commonly
divided or borrowed from households who only cultivate paddy rice. A key informant, however,
voiced a different opinion where 2- or 3-year fallows are the most productive as they will have
younger bamboo, tree seedlings and herbs; the opinion may be strongly linked to labour availability
as longer fallows will require intensive input for clearing and the burning must be of better quality if
the older vegetation is to be sufficiently reduced to ash.
5.2.4.1 Fallow Length Impact on Soil Quality
The soil quality of a field can be improved with fallow length; according to the farmers, if a field is
sloped or has red dry soil it should be left fallow for longer. The argument that fields of low soil
quality are managed under longer fallows is certainly valid (Aumtong et al., 2009; Roder et al., 1995);
however, as the farmers of the specific fields analysed all stated they were of ‘good’ soil quality, land
use according to inherent soil properties should be accounted for.
The Ecological Sustainabilityǁ Discussion
53
Although the quantitative results do allude to fallow length as being an influential factor of soil
quality, the links to specific soil parameters remain unclear. There are discrepancies between the soil
parameters that do not follow what is theoretically expected:
- Bulk density has conflicting correlations dependent on soil depth; at the surface, bulk
density is positively correlated with fallow length while at a 10 cm depth it is negatively
correlated. One would expect longer-fallowed fields to have a higher SOC content thus
lower bulk densities, as is seen at a depth of 10 cm. The soil surface may reflect the
opposite as it is more exposed to environmental conditions and management practices; the
circumstances would thus be plot-specific, dependent on debris accumulation, erosion, and
the farmers’ technical skills.
- The lack of correlation between fallow length and CEC is unexpected; theoretically, there
should be a positive correlation due to the indirect effects of higher SOC accumulation in soil
of longer-fallowed fields (Funakawa et al., 1997). Furthermore, the positive correlation
found between fallow length and clay content should also promote CEC.
Explanations for the observed discrepancies are difficult to pinpoint; actual correlations may be
clouded by the small sample size, especially in regards to the clay content. The timing of soil
sampling may be a factor and will be discussed later in conjunction with the other parameters.
5.2.4.1.1 Influence of Fallow Length on Soil Quality: SOC
SOC %, discussed before as a key indicator of soil quality, surprisingly decreased with fallow length.
Studies have been inconsistent; Roder et al. (1995) and Funakawa et al. (1997) found weak positive
correlations between soil organic matter and fallow length while Bruun et al. (2006) found no
correlation. The SOC stocks however did depict a weak positive correlation. The finding is consistent
with the thought that biomass will accumulate linearly during the first ten years of fallow (Bruun et
al., 2009) thus the longer fallows will have the largest SOC stocks. It further highlights the role of
clay content, also positively correlated to fallow length, in carbon sequestration.
The fact that the positive correlation was found between SOC stocks and not SOC % reflects the
importance of including bulk density, in this case, through stock calculations and using a mass
equivalent approach, when comparing different land use intensities (Bruun et al., 2013).
The weak negative correlation found between fallow length and the C:N ratio agrees with the study
by Funakawa et al. (1997) where the microbial C:N ratios were inversely related to fallow length.
This implies that nitrogen is more limiting in soils managed under shorter fallow lengths. Reasons
for lower nitrogen levels of shorter fallows are a lower biomass accumulation and lower
mineralization rates after burning (Funakawa et al., 1997). Furthermore, the lower C:N ratio of the
longer-fallowed fields indicates that the soil microbes are more active and a larger microbial biomass
is thus implied (Tanaka et al., 2001).
5.2.4.1.2 Influence of Fallow Length and Soil Quality: Pox C
Though the correlations are weak, the concentration and stocks of Pox C both decrease with fallow
length. Studies still dispute which fraction of the SOC Pox C actually represents; Aumtong et al.
Discussion ǁ The Ecological Sustainability
54
(2009) and Tirol-Padre and Ladhe (2004) observe that Pox C more likely represents a larger fraction
of the SOC pool than originally thought (Weil et al., 2000). The counterintuitive result lends to the
uncertainty. However, one could speculate the result reflects the greater mineralization rates of
longer-fallowed fields as Pox C content was depleted faster during the cropping season (Funakawa et
al., 1997).
Alternatively, the result may likely be due to experimental error; the visual charcoal content was
noted for each soil sample and ANOVA revealed that the shorter-fallowed fields contained higher
charcoal content, a random error. Although large charcoal fragments were removed, the soil
samples were not sifted. This may explain the hither readings since it has been shown that the Pox C
method can be sensitive to charcoal content (Skjemstad et al., 2006).
Though it was not possible to calculate the CMI described by Blair et al. (1995) due to the absence of
a reference soil the concept was adapted and is here represented by the SOC:Pox C ratio. The
SOC:Pox C ratio decreases with fallow length indicating that, in spite of the decreasing Pox C
content, the size of the pool actually increases in comparison to the total SOC content. This trend
supports theoretical knowledge that longer-fallowed fields will have higher biomass accumulation
and thus greater returns of decomposable plant material. A larger pool of Pox C is linked to greater
microbial activity, mineralization rates and, in the end, soil quality (Blair et al., 1995). The result also
highlights the importance of the use of an early indicator for SOC changes to detect the ecological
impacts of management practices.
The effect of fallow length on nutrient levels will be discussed in conjunction with upland rice yields
as the results are thought again to be a reflection of plant uptake.
5.2.4.2 Upland Rice Yields and the Influence of Fallow Length
Interviewees were asked how much rice they need annually to meet their household’s needs; it was
then calculated that approximately 454 kg of rice per capita is required per year to meet the
subsistence needs , if children are equivalent to 0.5 of an adult. Of the nine farmers, only two had
harvested enough rice for the entire year; 3 farmers were unsure as it was dependent on whether
they re-paid their debts, which are commonly made with rice.
Farmers did express a common opinion that higher upland rice yields were obtained when fields
were managed under longer fallow periods. Studies are highly ambiguous in whether fallow length
does indeed influence yield; the link becomes even more obscure since socioeconomic factors, i.e.
land use decisions and labour input, were included making it difficult to compare studies as methods
were not consistent.
The results do indicate that upland rice yield is moderately correlated with fallow length and
supports the findings of the study by Bruun et al. (2006); the study is one of few that have been able
to link higher upland rice yields to longer fallow lengths.
The Ecological Sustainabilityǁ Discussion
55
As discussed, soil quality is positively influenced by longer fallows thus they will have higher
productivity. Interestingly, the nutrient levels, total N, P Avail and K Exch, were inversely correlated
with fallow length and yields. However the trends likely reflect plant uptake.
The trend indicates upland rice yield will be significantly influenced by fallow lengths of up to five
years after which yield levels appear to fluctuate and the association becomes less apparent (Results
4.3.2, Figure 20). This suggests that the positive effects of fallow length alone on the soil quality will
stagnate. Assuming fallow length is influencing the yield levels, there may be several explanations
for the diminishing strength in correlation:
- A biomass accumulation model developed by Jepsen (2006) found it to peak after six years in
Sarawak, Malaysia. The trend found implies stagnation of biomass accumulation may occur
similarly at approximately five years; meaning the added benefits of using longer fallows is
reduced after five years. This is echoed by the farmers’ preferred fallow length of five years.
- The fluctuating yield levels after a fallow length of five years suggests that any increase in
yield is due to management practices. Technical skill, knowledge and labour inputs may have
a greater influencing role when longer fallows are implemented. This explains why the 11-
year fallow field appeared to be an outlier; the field 11F1, represented by the blue data point
in the yield figures (Results 4.3.2, Figure 20), was omitted from statistical analysis as its yield
level was considerably lower. The in-depth interview revealed the farmer was not
accustomed to cultivating upland rice; he had not cultivated upland rice in the last ten years
and when he had it was with his parents. The upland field in question was cultivated out of
necessity as the irrigation for his paddy field was not functioning. Hence, the degree of
knowledge and technical skill would not be at the same level as of the other farmers.
- Studies do point to burn quality as an influential parameter in the restoration of soil fertility
(Bruun et al., 2006, 2009) and thus may contribute to the diminishing link between yield and
fallow length. Fallows composed of a higher proportion of woody species will require a better
burn quality, in terms of burn length and temperature, to reduce the biomass to ash.
Although all farmers did state the year’s burn was of good quality, ash deposition in the
longer-fallowed fields may be irregular, introducing variability in the soil restoration levels
whereby patches of concentrated nutrients within the fields may exist; this would reflect the
uncertain and fluctuating yield levels.
Shortened fallows will lead to an increase in weed pressure (Mertz, 2002) or pest and disease
infestation (Roder et al., 1995) and may be more of a constraint for upland rice yield cultivation than
soil quality. When asked of the role of fallow, farmers did mention its importance in controlling
weed populations. Increased weed pressure will require more frequent weeding, thus labour input.
This will place further strain on the available labour supply. Similar effects on the labour supply will
be observed with an increase in pest or disease pressure. If sufficient labour is available, the farmer
can counteract the negative influences the pressures will have on rice yield; however, if labour is
limited, yield levels will decline.
As these influences were not considered, their role as limiting factors and the effect of fallow length
cannot be assessed. Therefore, the positive association between upland rice yields and fallow length
Discussion ǁ The Ecological Sustainability
56
may not be a function of improved soil quality but rather of lower weed pressure, less pest or
disease infestation or a combination. Interviewees identified two major weed species: Mimosa
invisa and Chromolaena odorata.
In general, it appears that a minimum fallow length of five years will improve yields and may avoid
the assumed system breakdown of shifting cultivation. Unfortunately, ambiguity still remains as:
multiple regression analysis did not identify fallow length as an explanatory factor and parameters
such as weed density and degree of intercropping were not assessed.
5.2.4.3 Alternative measures of land use intensity
Studies have used different methods to measure land use intensity. Logistically, the easiest and
most straightforward method is to take only the preceding fallow length into account as many
studies do (Bruun et al., 2006; Funakawa et al., 1997; Roder et al., 1995). The need of including the
past cultivation cycles is increasingly important; a field now managed under a 3-year fallow length
would not have been so ten years ago. Therefore if land use history is not considered, the added
benefits of previous fallow cycles, likely of longer lengths, will not be accounted for.
The number and length of previous cultivation cycles will influence the biomass and nutrient
accumulation (Bruun et al., 2009); repeated cycles of shorter fallow length will reduce the diversity
and the regeneration of certain species whereby grasses of low biomass productivity will dominate
(Rerkasem et al., 2009). The R Index (Ruthenberg, 1971) and ACi (Birch-Thomsen et al., 2007) do
account for such impacts as the land use history is taken into account; this study however used
adapted versions of the two indexes due to data limitations i.e. data for the past ten years was
available. The main disadvantage of the alternatives is the high dependency on the ability of
farmers’ to recall from memory.
Both land use intensity measurements reflected the same negative trend with upland rice yield as
when measured by preceding fallow lengths. It appears that ACi is a more accurate measurement
for land use intensity as its correlation with yield levels was significant whereas the R Index was not.
The fact that different weightings are given to the cultivated years, i.e. those closer to the time of
assessment bear more weight, may give the ACi the added accuracy and, consequently, may be the
better approach.
5.2.5 Quantitative Experimental Design: a reflection
Discrepancies in the correlations between the soil parameters and yield levels of the two different
data sets, where one relates parameters to yield at a plot level (i.e. the topographical study) while
the other is at the entire field-level(i.e. the fallow length study), infers that the scale used in
The Ecological Sustainabilityǁ Discussion
57
experimental designs is important and must be considered. The scale used by other studies is
inconsistent and may explain the ambiguous results; Bruun et al. (2006) analysed soil parameters
and yield levels from test plots while comparisons by Roder et al. (1995) used yield levels obtained
from the entire field. The correlations between the soil parameters, specifically the nutrient levels,
and upland rice yield were clear and supported by theoretical knowledge when the data set derived
from the test plots was used. Why plant nutrient uptake appears to be reflected in the field data
and not in the test plot data set is unknown.
The inclusion of additional parameters would improve the accuracy and understanding of the
implications fallow length will have on soil quality and upland rice yields. As mentioned,
socioeconomic factors such as labour input would help assess as to whether or not fields managed
under shorter fallows do indeed require more weeding (Mertz, 2002) or whether farmers are more
likely to invest more labour in longer fallows due to the initial high investment required for clearing
(Bruun et al., 2006); both will influence the upland rice yields obtained.
Furthermore, an important factor to consider is the species richness and diversity of the fallow
vegetation (Rerkasem et al., 2009); unfortunately, this was never assessed due to the time
constraints and late arrival to the field. Additional ecological parameters to include would be weed
density and the extent of intercropping.
A greater variation in fallow length and of regular intervals, i.e. repetitive intervals of three years,
would give a more accurate representation and a better indication of overall soil fertility restoration.
However difficulty arises in not only finding fields of longer-fallows but also in obtaining accurate
land use history as it is entirely dependent on memory recall, an essential requirement if the ACi is
to be used as a measure of land use intensity.
A major weakness of the experimental design is the timing of the soil sampling; as it was done after
the harvest of upland rice, plant uptake and season conditions will influence the soil parameters. It
would be interesting to collect soil samples throughout the cycle: before burning, after burning, half
way during the rice crop season and after harvest for instance. Soil sampling after burning would
capture the direct effects of fallow length on the soil parameters more accurately. Furthermore, a
larger sample size would improve the validity of the results however this would require more time in
the field. The assessment of the influence of topographical position on soil quality and upland rice
yields could be improved if fields with longer slope lengths were used.
Discussion ǁ What is Driving the Decrease of Fallow Lengths in Ban Navene?
58
5.3 What is Driving the Decrease of Fallow Lengths in Ban Navene?
It appears the quantitative results do indicate that the decrease in fallow length will have influence
on the ecological sustainability of shifting cultivation which in turn will implement the livelihood
strategies of Ban Navene. It is thus important to identify the drivers of the trend in decreasing fallow
lengths in order to grasp an understanding. Three drivers are thought to be driving the decrease in
fallow lengths in Ban Navene: demographical change, policy reforms regarding land use and
allocation and the inclusion of maize as a cash crop.
5.3.1 Demographical Changes
Ban Navene has experienced a population growth especially in the last ten years; the influx of
households was government-sponsored due to the developed paddy area and sufficient upland
fields. There has been some degree of out-migration as younger people have left Ban Navene in
favour of permanent off-farm employment in cities like Vientiane or in pursuit of secondary
education; however not to as great of an extent as found by several other studies in Southeast Asia
(Cramb et al., 2009; Hansen and Mertz, 2006; Ziegler et al., 2011).
At a household-level, out migration will decrease the labour available and the demand for shifting
cultivation, i.e. less rice is required for subsistence needs. It will also increase the average age of the
households and the risk of illness; this may be the cause of the increasing gradient of fallow age with
field distance from the village however this theory cannot be verified as an assessment of age
distribution was not made. At the group interview, held November 2012, concern was voiced over
the loss of the younger generation. Furthermore, labour supply was a major limiting factor in the
production of upland rice (Results 4.4.2, Table 11). On a purely observational basis, however, it does
appear that the proportion of older to younger generations may be slightly more. This trend will
most likely gain more momentum when the infrastructure, i.e. road access, in the area is improved
and thus the exposure to ‘urban lifestyles’ increases.
Currently, while it appears population density does play an influential role in the intensification of
shifting cultivation, it is not the single determinant; the total land available does not appear to be
exhausted as fields of longer fallows can still be found and the practice of successive cropping on the
same field was not observed, an indicator of land constraint (Lestrelin et al., 2012). The decline in
fallow length is then due to a combination of population growth and other drivers of intensification.
What is Driving the Decrease of Fallow Lengths in Ban Navene?ǁ Discussion
59
5.3.2 Political influences
The government of Lao has placed considerable emphasis on the need to restrict shifting cultivation
because of the desire to protect the country’s natural resources, seen as necessary for development
and poverty reduction (Lestrelin and Giordano, 2007). Many implemented policies have discouraged
shifting cultivation and thus have played an influential role in both the system decline and
intensification.
The DAFO of the Viengkham district implements the policies dictated by the provincial offices of
Louangphabang. Ban Navene has been subjected to two influential regulatory developments: the
implementation of the Land Use Planning and Land Allocation (LUP-LA) programme in 2003 and the
establishment of the NEPL NPA, first in 1993 but geographically defined in 2003 (Refer to Results,
4.4.1). The implementation of each and the reactions of the farmers will be discussed in the
following sections.
5.3.2.1 The LUP-LA programme
The LUP-LA programme led to two developments: i) areas are now designated for specific land uses,
i.e. community forests, vegetable gardens, and ii) fields, both paddy and upland, were re-distributed
among farmers in an equally-intended manner (Moore et al., 2011). Land tenureship, a result of the
LUP-LA programme, was identified by Rasul and Thapa (2003) as necessary if governments are to
successfully eradicate shifting cultivation. Please refer to Results, 4.4.1 for specific criteria used.
In general, the programme has reduced the possible fallow length as farmers are now restricted to
three or four upland fields; the restriction in field number equates to a maximum fallow length of
three years, reflected in the findings from Lestrelin et al. (2012) where average fallow age in Laotian
upland systems was said to be 3.8 years in 2003. Farmers however have adopted new strategies to
curtail the forced short fallow lengths:
- Many upland rice fields are borrowed from farmers who no longer cultivate upland rice.
These fields are usually of longer fallow as they have not been as intensively cultivated.
- Upland fields are split to increase the number of fields included in the cyclic rotation, thus
prolonging the time duration between cultivations. A limitation is that the area cultivated is
considerably less and translates to a lower yield. However, Cramb et al. (2009) suggests that
a decrease in field size also allows the area to be farmed more intensively and will offset
yield declines. Some farmers will also split fields as a coping strategy of low labour supply.
Furthermore, the quantitative data suggests no significant differences in yield levels when
compared according to field size.
- At least one interviewed farmer withheld the true number of upland fields that they owned,
suggesting that there may be additional such cases.
Furthermore, it appears there is a miscommunication between DAFO and Ban Navene in how the
future agricultural system will function. This was made evident during the group interview where it
became apparent that the interpretation of policies by the farmers did not match that of the
Discussion ǁ What is Driving the Decrease of Fallow Lengths in Ban Navene?
60
government. Farmers have interpreted the paradigm shift, in which slash-and-burn activity is
restricted by 2020, as pertaining specifically only to the cultivation of upland rice and not to the
cultivation of alternative crops such as maize, manioc and chili. Their outlook for Ban Navene in
2020 consists of an agricultural system where trade will occur between households cultivating rice
on the paddy fields and those cultivating alternative crops on the upland fields, with no mention of
the discontinuance of burning. Meanwhile DAFO is determined to reduce, if not prohibit, the slash-
and-burn activity (DAFO official, pers. comm., 10/2012).
The apparent conflict between the regional government and rural villages is a direct consequence of
broad policies that are implemented improperly by local offices who do not have the institutional
capacities required (Moore et al., 2011). Unless communication and cooperation is improved
between the two parties, the conflicts will only become more prominent; a concern as the livelihood
strategies of the rural poor will be heavily affected and proper caution should be utilised.
5.3.2.2 The establishment of NEPL NPA in 1993
The establishment of the NEPL NPA exacerbated land pressure caused by the LUP-LA programme as
the land designated for cultivation now had to be equally divided among a greater number of
households. The restrictive use of forest resources (policy outlined in Results, 4.4.1) places
additional strain on the livelihood strategies of households and the environment; this was
highlighted by the comment of one interviewee where they mention that “every family uses the
forest” in Ban Navene.
Thirteen households in Ban Navene were affected by the establishment of the NPA as their upland
fields were within the boundary. As compensation, they were given fields closer to the village but
were rarely of equivalent size or quality. Three
households were interviewed to gain a perspective on
the effect of such conservation projects.
It has been criticised that boundaries are often not
defined in a participatory manner (Moore et al., 2011);
this was reflected in the responses from the
interviewees whereby, although they were
participants of the 2003 land allocation meeting, the
relinquishment of their fields was nonnegotiable. One
interviewee explicitly stated that they did not agree
with the decision. Though the lost fields were far from
Ban Navene, the farmers still had the opinion that they
were of high-quality. The interviewees reasoned that
the pressures from the widespread poverty of Ban Navene, combined with the year’s low rice yield,
could have been alleviated by the high quality land found within the NEPL NPA; it was suggested that
approximately 20 households are illegally cultivating within NPA boundaries.
Figure 26: The impressed tortoise (M. impressa), a vulnerable species found in the NEPL NPA illegally trapped
What is Driving the Decrease of Fallow Lengths in Ban Navene?ǁ Discussion
61
There were numerous field observations of illegal hunting and possession of firearms. Furthermore,
village diets did include the civet (status: protected), hornbill (Aceros nipalensis, status: vulnerable)
and the impressed tortoise (Manouria impressa, status: vulnerable, Figure 26). Additionally, to
offset the shortcomings in rice yields, households will turn to the extraction of NTFPs as a coping
strategy, whether legal or not; as described by one interviewee, the earnings could amount to
400,000 kip,or US $ 51.31 (3F2, pers comm., 12/11/12).
The extent of illegal behaviour can indirectly suggest the degree of pressure placed on the livelihood
strategies of the households in Ban Navene by land availability and resource constraints. In the
absence of alternative livelihood options or resources, forest conservation projects will only
promote such illegal activity.
Policies, especially when combined with the government-sponsored immigration, have played an
influential role in the decrease of fallow length; a sentiment reflected by Rasul and Thapa (2003)
where they state that the transformation of shifting cultivation to more sedentary practices occurs
when population growth is accentuated by additional drivers.
5.3.3 The Development and Expansion of Commercial Agriculture
The inclusion of both cash crop cultivation and livestock has been heavily promoted by the Lao
Government (Moore et al., 2011; DAFO Official, pers. comm., 09/2012) and is reflected by the 59%
of farmers who now practice partial swiddening.
Farmers have a desire to cultivate maize due to the
lower labour requirements when compared to upland
rice cultivation. In 2012, the price Thong La paid for the
maize was 1 000 kip/kg, the equivalent of 0.13 USD/kg
(Figure 27). This equates to an income of 1.33 million
kip or 172 USD if two tonnes are harvested and nine kg
of seed is used; of the interviewees who cultivated
maize, two tonnes was the most common estimate of
harvest.
The cultivation of maize is a new development and
many farmers expressed their uncertainty of its
profitability. One interviewee suggested that a better
use of the maize would be as feed for their own
livestock, which is of greater market value and thus a
better return to investment.
Furthermore, the pressure placed on the soil by maize cultivation is also ambiguous as farmers
cannot afford external inputs, i.e. fertilizers. Its cultivation will accelerate the land degradation that
Figure 27: Thong La, the maize company,
husking the stored maize, 11/12
Discussion ǁ The Implications for Upland Rice Productivity: From the Farmers’ Perspective
62
is said to be caused by shifting cultivation. As upland rice production increasingly becomes more
difficult, an objective of the LUP-LA programme, the shift towards maize cultivation will gain
momentum.
Maize and livestock integration has reduced the land available for upland rice cultivation.
Households who are engaged in traditional shifting cultivation, i.e. not CSA, do not cultivate maize or
own large livestock suggesting a certain level of resources is required for the shift towards partial
swiddening. This indicates that, instead, the inclusion of cash crops and livestock has promoted
inequality between the households of Ban Navene.
5.4 The Implications for Upland Rice Productivity: From the Farmers’ Perspective
Upland rice yields do tend to fluctuate and, as Roder et al. (1995) points out, there was never
incentive to produce excess rice as grain damage and loss during storage was too high. The
expressed desire to produce surplus rice may reflect the changing attitude of the community where
luxury items, i.e. television, clothing and motorcycles, are gaining popularity. Many farmers
however did state yields were generally higher in the past; it appears from the interviews that yield
levels declined approximately five years ago, i.e. 2007, four years after the LUP-LA programme came
into effect. In the past, rice was more ‘beautiful,’ the fallows longer and the weather better. One
farmer claims that yields have declined by as much as 50% and points to problems with birds,
rodents and bad seed quality (11F1, pers. comm., 11/2012). Also mentioned were smaller field sizes
and less available seed. The statement that rice grains are no longer ‘beautiful’ may relate to the
high prevalence of rice disease and insect infestation seen in 2012 and one can question if this is
becoming a general trend due to changing environmental conditions further aggravated by the
shorter fallow lengths.
However, farmers were also quick to point to socioeconomic reasons for the general decline in yield
and appeared to be more influential in spite of the repetitive referrals made to fallow length and
soil; though quality soil and long fallow lengths were said to be a necessity for high yields,
interviewees did not directly identify them as constraints or causes of the decline in productivity.
The assessment of which constraints are more limiting to upland rice productivity will indicate the
overall influence that fallow lengths do have from the perspective of the farmers; it will also give an
understanding as to how the system intensification may affect the productivity in the future.
5.4.1 The Constraints to Upland Rice Production
Rice disease, labour supply and rodents were identified as the most important constraints to upland
rice production (Results 4.4.2, Table 11). Observations, both general and in the field, agree with the
finding; symptoms of rice disease (i.e. rice blast, Figure 25) were frequently observed and rodents
were numerous as they were commonly included in the daily diet. Labour supply was a concern for
The Implications for Upland Rice Productivity: From the Farmers’ Perspectiveǁ Discussion
63
many households as members emigrate or grow older; furthermore, it is directly linked to other
constraints (i.e. rodents, weeds) and thus will greatly influence upland rice production.
The study by Roder et al. (1997) found different results whereby weeds, rodents and insufficient
rainfall were identified as the three most challenging constraints to upland rice production.
However, it is important to consider the conditions of the preceding year as these will be the
reference points for farmers as they are easiest to recall. In general, 2012 was a very wet year which
could explain the high disease rates and the low ranking of rainfall. Furthermore, the rainfall
constraint was also communicated incorrectly; the initial intention was to assess the constraint of
moisture availability for crops (i.e. or the frequency of ‘drought’ incidences) but it was instead
communicated in a more ambiguous way meaning it could be interpreted as too much or too little
rainfall.
It is surprising that weeds was not a major constraint, as found by Roder et al. (1995). A function of
the fallow period is to decrease weed pressure (Cramb et al., 2009; Roder et al., 1995; Roder, 1997);
weed pressure will increase as fallow length decreases and, thus, more labour is required for
removal. However, weeds are a direct constraint on labour input and not yield as weeding practices
remain consistent (Roder, 1997); Farmers acknowledged the problem of weeds however the
negative impact was minimized or negligent if the workforce was of proper size. Roder (1997) found
that the weeding requirement doubled between 1950 and 1997 as the fallow length decreased from
an average of 40 years to five years; weeding accounted for 40 – 50% of the total labour input.
Farmers are restricted in the number of upland fields, however as discussed, they will borrow longer
fallowed fields from households who no longer cultivate upland rice; the lower ranking of land
availability, soil suitability and weed pressure as constraints may reflect this strategy. Upland fields
with longer fallows are still found in the area hence the full negative effects of the constraints have
not yet been realized. When the supply of long-fallowed upland fields is exhausted, the negative
influence of the constraints on upland rice production may become stronger.
A function of fallow length is it serves as a control for insects and plant diseases. This would explain
the high ranking of plant disease as a major constraint to upland rice production and the problem
will only become more widespread. Insect damage was frequently observed in the field but was
given a low ranking of 6th (Results, 4.4.3). This unexpected result could be a simple case of
misidentification as both plant disease and pest attack can manifest the same symptoms: whitehead,
weak stems, unfilled grains (IRRI, 2009; Figure 25). One farmer in particular identified the root grub
as a major pest for upland rice production; however, he had no knowledge on possible control
measures (5F1, pers. comm., 09/2012), an interesting entry point for any future workshop or
project.
Labour supply is a prominent concern. The fact that Roder et al. (1995) did not find this may
highlight the changing challenges that rural villages face as the world becomes more globalised. The
issue of labour shortage was a central topic at the group meeting (Refer to Methodology, 3.7 Future
Perspectives) whereby the possible causes and solutions were discussed. The general trend of
decreasing numbers of children per family, due to shortage in food supply and increasing expenses,
have led to households with more elders who are unable to work in the upland rice fields.
Confounded by the facts that there is no employment in Ban Navene and unsustainable crop yields,
many of the young people emigrate to other villages or to Vientiane to find work in manufacturing.
Discussion ǁ The Implications for Livelihood Strategies
64
Furthermore, this trend will be accentuated as younger people become more exposed to education
and urban lifestyles, as discussed. At the time of the group meeting, held November 2012, eleven
young people had left to work on the Xayaburi Dam on the Mekong River, a highly publicised
project.
Two solutions were suggested to encourage the younger generation to stay in Ban Navene:
1. To improve agriculture through governmental support programs, improved yields and
access to markets, livestock introduction and the sale of locally processed raw goods,
2. To educate the younger generation in traditional Khamu handicrafts that could be sold at
markets, i.e. weaving fabric and baskets.
5.5 The Implications for Livelihood Strategies
Agricultural and land use policies, conservation projects and population growth appear to be the
main drivers of the transformation of shifting cultivation whereby fallow length has indeed
decreased. Land availability is not a constraint for Ban Navene at the village level; however, the land
available per household has certainly declined and strained the traditional system. Furthermore, the
labour supply, per household and for work parties, has been reduced. Both are major outcomes of
the aforementioned drivers. Furthermore, constraints such as pests, diseases, soil suitability and
weeds will increasingly become evident and limit the productivity of upland rice under short fallow
management.
Livelihood strategies have been influenced by these factors and will continue to be; the shift towards
intensified systems will only accelerate which, in turn, will change the livelihood security of upland
communities at a rapid rate.
5.5.1 Livelihood Security
Food security will be negatively influenced by the decline in shifting cultivation as Ban Navene faces
mandated restrictions without the provision of alternative livelihood options; a trend found by
Cramb et al. (2009) and Vien et al. (2006). The two common coping strategies for upland loss
suggested by Cramb et al. (2009) are observed in Ban Navene:
1. Paddy cultivation in the river valley area next to Ban Navene was expanded and fitted
with an irrigation system; however, less than half of the fields are irrigated thus
upgrades are necessary. As already mentioned, some households have completely
abandoned the cultivation of upland rice while some have adopted the ‘composite
swiddening’ strategy. In Ban Navene, animal power has been replaced with machines
and the use of mechanic de-husking was also observed; although many farmers stated
The Implications for Livelihood Strategiesǁ Discussion
65
that the innovations have deterred some households from adopting paddy rice
cultivation as they require more capital investment.
2. Upland rice cultivation has intensified, using the strategy of decreasing fallow lengths
since the land available per household is constrained.
Paddy rice cultivation does appear to improve the food security; the influence of maize production is
ambiguous as it has been only recently introduced. However the positive effects are not seen equal
across households as the two coping strategies have led to the marginalization of households and
segregation in Ban Navene, a change that will affect also the social norms. The intention was for the
land to be allocated equally among the farmers of Ban Navene and provisions were included in the
policy criteria in which households owning paddy fields were then granted less upland fields (Results
4.4.1). While the total cultivable area in a given year may be somewhat equal, the productivity of
the two rice systems is not. Statements of the interviewed farmers did reflect this finding; there was
a strong desire for paddy field ownership. The households who owned paddy fields were in a better
position to meet their subsistence needs while those that entirely relied on upland rice production
were forced into a cycle of debt.
The implications for Ban Navene of the inclusion of maize and livestock are ambiguous but most
likely will only strengthen the marginalization of resource-poor households. DAFO encourages the
adoption of maize cultivation and livestock rearing as it feels it will improve the food security of Ban
Navene (DAFO Official, pers. comm., 10/2012); however there does not appear to be sufficient
support or the extension services required for such a transition.
Food security in Ban Navene will not improve with the transformation of shifting cultivation to a
permanent cropping system; in depth interviews have shown that food security has declined in the
last five years. This will place added strain on the environment because the population will turn to
natural resources, i.e. NTFPs, to supplement the shortcomings.
With no alternate sustainable livelihood options available, the rural populations in villages like Ban
Navene will maintain shifting cultivation out of necessity; a trend found by Hansen and Mertz (2006)
where the system is maintained due to the high investment required for permanent cropping and
the low infrastructure and external support. Projects initiated by the Governmental agencies and
NGOs should emphasize such development if the desired phase out of shifting cultivation is to be
reached instead of restricting land access. Furthermore, the inclusion of cash crops and livestock
and the development of the paddy area have led to household inequality and stratification whereby
some have access to more luxuries, i.e. power, television, motorcycles.
Discussion ǁ Future Prospects for Ban Navene
66
5.6 Future Prospects for Ban Navene
The farmers appear to want to shift away from the cultivation of upland rice, evident by the
comments during the group meeting where it was said that the labour input is not proportionally
rewarded in upland rice yields. They point to the need for Ban Navene to develop in terms of
market access if the young generation is to stay. Furthermore households would like more
governmentally-sponsored agricultural projects, i.e. irrigation development for the remaining paddy
fields, improvement to infrastructure necessary for livestock integration and more assistance for
when dealing with the maize companies.
ǁ Conclusion
67
6 Conclusion
The farmers are quite aware of the physical indicators of soil quality, its impact on upland rice yields
and the importance of both field topography and fallow length. The quantitative results indicate
that both SOC and Pox C are key indicators of soil quality whereby greater levels will improve
nutrient availability to the crop. Surprising results were the lack of correlation between SOC and pH
or CEC; Pox C however was negatively correlated to CEC suggesting it is a source of hydrogen ions.
Soil quality is an indicator of upland rice yield levels where pH and Pox C are the two identified
explanatory variables.
Erosion does not appear to be a major constraint to the productivity of the system nor is there
considerable variation in the soil quality in accordance to slope position. SOC content is greatest at
the top of the slope and may coincide with high clay content. The accumulation of Pox C downslope
may be because of the downward transport of charcoal; the Pox C method cannot distinguish
between charcoal and bioactive molecules thus results may be skewed. Leaching may have a bigger
influence as both nitrogen and potassium accumulate downslope in the 5-10 cm soil layer;
potassium stock differences however are statistically insignificant due to large standard deviations.
Phosphorus does reveal a tendency to decrease downslope however there is an absence of a
consistent pattern. Hence the differences may simply be due to its low mobility, confounded by
field variation.
Upland rice yields appear to be positively influenced by fallow lengths of up to five years, after which
the added benefits become dependent on the management practices and knowledge of the farmer.
It remains ambiguous as to whether the increase in yield is a result of the positive influence fallow
length will have on soil quality, weed suppression, pest and disease control or a combination of all.
Biomass accumulation is greater when long fallows are used, reflected in the larger SOC stocks, and
will have higher microbial activity, i.e. a lower C:N ratio. Pox C levels decrease with fallow length
however this is more likely a consequence of the observation that the soil samples from the longer
fallowed fields had higher charcoal content; the SOC:Pox C ratio indicates that the Pox C fraction will
increase in size, relative to the SOC pool, when fallow lengths are increased. The effect on the
nutrient levels is counterintuitive as they decrease with fallow length but this likely reflects crop
uptake.
Specific to Pox C, much remains unknown as in regards to its sensitivity to land use changes and the
exact fraction of the SOC pool it represents. The suggested skew of the results caused by charcoal
content in soil samples is a major limitation to using the Pox C method in the assessments of shifting
cultivation systems though this could be avoided with proper sample preparation, i.e. sifting. This
requirement however would lower its efficiency as a field method.
The use of the ACi as an alternative measure of land use intensity appears to be promising as it did
show similar correlations with upland rice yield levels. The main advantage is that it incorporates
past cultivation cycles with more weight given to those more recent. A disadvantage of the index
however is the need for a detailed field history; it is difficult to recall past cycles and some error in
memory may result.
Conclusion ǁ
68
The drivers of the trend in decreasing fallow lengths are demographical changes, land use and
allocation policies and the integration of cash crop cultivation, i.e. maize. Ecologically, shortened
fallow lengths, i.e. of two or three years, will eventually degrade the soil quality and result in lower
upland rice yields. However it appears that the level of land use intensity in the Ban Navene area is
sustainable at the moment as there is no indication of soil degradation. Furthermore, policies
restricting fallow length to two or three years have only been in place for the last ten years; longer-
fallowed land can still be found in the area.
Thus the full implications of short fallow shifting cultivation are not clearly understood. The general
decrease in upland rice yields will progressively have greater negative impacts on the livelihood
security of Ban Navene especially as alternative livelihood strategies are absent. The integration of
maize and livestock may show promise however the necessary infrastructure and support are not in
place; instead the integration seems to promote household inequality.
This study highlights the imminent need for a greater understanding of shifting cultivation and the
consequences of shortened fallow lengths on its ecological sustainability as the livelihoods of upland
populations in Southeast Asia will be influenced. Many developing countries, where shifting
cultivation is still practiced, have the desire to economically develop and see the agricultural sector
as key to development and poverty reduction. However, the discouragement of shifting cultivation
without viable alternative livelihood options and sufficient support is not a suitable strategy, as
exemplified by Ban Navene.
ǁ Personal Reflection
69
7 Personal Reflection
This study does not give a clear indication of the ecological sustainability of short fallow shifting
cultivation systems; the soil quality and yield results remain far too ambiguous. I do believe,
however, that the length of fallow required to restore soil fertility may not be as long as commonly
thought; this study did point to a fallow length of five years as sufficient for recovering productivity
without added external inputs or changes in management practices. Fallow length does not have a
single role in shifting cultivation; it will influence numerous aspects such as weed pressure, pest and
disease infestation and soil quality thus it is difficult to identify how it influences upland rice yields.
Further studies are obviously still required where weed density, intercropping, disease and pest
infestation, soil quality and system inputs, i.e. labour, are taken into consideration at plot-levels and
in terms of ACi; a large and daunting task.
It is my opinion that the livelihoods of upland populations are being negatively influenced not by the
decrease in fallow length but by the negative view projected by various governments and agencies
on shifting cultivation. Furthermore, upland populations seem to be marginalised although the
younger generation increasingly wants to integrate with their ‘urban’ counterparts. The traditional
upland culture in Lao PDR is rapidly transforming, confounded by government-sponsored village re-
locations and the pushed integration of livestock or maize cultivation. Such policies and
programmes are only increasing stratification and inequality between villages but households as
well. It is as if the policies are always two steps ahead of the upland villages, who are struggling to
keep up. I believe more support, i.e. infrastructure and health services, is needed if the livelihoods
of upland populations are to be improved. For instance, in my opinion, CSA may be a good option;
however, paddy fields fitted with irrigation must be allocated to all of the households not to only a
certain proportion.
The vast amount I learned, both academically and personally, during the duration of this thesis
project in unquantifiable. Academically, it has helped me develop my skills in experimental design,
data collection and statistical analysis. I have also improved my understanding of agricultural upland
systems and soil science. Furthermore it reaffirmed for me the importance of ethical responsibility
as findings can and will have livelihood implications. Personally, the exposure to the struggle
between traditional and modern lifestyles highlighted the enormous challenges that the future will
hold. The experience was eye-opening and one that I would never change or want to replace.
Personal Reflection ǁ
70
ǁ References
71
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Mertz, Ole, Padoch, C., Fox, J., Cramb, R. A., Leisz, S. J., Jefferson, P., & Christine, O. M. 2009. Swidden Change in Southeast Asia : Understanding Causes and Consequences. Human Ecology, 37: 259–264. doi:10.1007/s
Mertz, Ole, Wadley, R. L., Nielsen, U., Bruun, T. B., Colfer, C. J. P., de Neergaard, A.,Jepsen, M.R., Martinussen, T., Zhao,Q., Noweg, G.T., Magid, J. 2008. A fresh look at shifting cultivation: Fallow length an uncertain indicator of productivity. Agricultural Systems, 96(1-3), 75–84. doi:10.1016/j.agsy.2007.06.002
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Moore, C., Ferrand, J., & Khiewvongphachan, X. 2011. Investigation of the Drivers of Deforestation and Forest Degradation in Nam Phui National Protected Area, Lao PDR. Climate Protection through Avoided Deforestation Programme (CliPAD), (April). Retrieved from www.giz.de
Nielsen, U., Mertz, O., & Noweg, G. T. 2006. The Rationality of Shifting Cultivation Systems : Labor Productivity Revisited. Human Ecology, 34: 201–218.
Rasul, G. & Thapa, G. 2003. Shifting Cultivation in the mountains of South and Souteast Asia: regional patterns and factors influencing the change. Land Degradation and Development 14: 495- 508.
Rerkasem, K., Lawrence, D., Padoch, C., Schmidt-vogt, D., Ziegler, A. D., Bruun, T. B., & Dietrich, P. 2009. Consequences of Swidden Transitions for Crop and Fallow Biodiversity in Southeast Asia. Human Ecology, 37: 347–360. doi:10.1007/s
Roder, W. 1997. SLASH-AND-BURN SYSTEMS IN TRANSITION : CHALLENGES FOR AGRICULTURAL DEVELOPMENT IN THE HILLS OF NORTHERN LAOS. Mountain Research and Development, 17: 1–10.
Roder, W., Phengchanh, S., & Keoboulapha, B. 1995. Relationships between soil , fallow period , weeds and rice yield in slash-and-burn systems of Laos *. Plant and Soil: 27–36.
Ruthenberg, H. 1971. Farming Systems in the Tropics. Oxford: Clarendon Press.
Schmidt-vogt, A. D., Leisz, S. J., Mertz, O., Heinimann, A., Messerli, P., Epprecht, M., Cu, P.V., Chi, V.K, Hardiano, M., Dao,T.U., Leisz, O., Mertz, A., Vogt, S., Vu,K.,Peter, M. 2009. An Assessment of Trends in the Extent of Swidden in Southeast Asia. Human Ecology, 37. doi:10.1007/sl0745-009-9239-0
Seidenberg, C., Mertz, O. and Kias, M.B.2003. Fallow, Labour and Livelihood in Shifting Cultivation: implications for deforestation in Northern Lao PDR. Danish Journal of Geography 103: 71-80.
Tanaka, S., Ando, T., Funakawa, S., Sukhrun, C., Kaewkhongkha, T., & Sakurai, K. 2001. Effect of burning on soil organic matter content and N mineralization under shifting cultivation system of Karen people in Northern Thailand. Soil Science and Plant Nutrition, 47: 547–558. doi:10.1080/00380768.2001.10408418
Tirol-Padre, A., & Ladha, J. K. 2004. Division S-8—nutrient management & soil & plant analysis. Soil Science Society of America Journal 68: 969–978.
Van Vliet, N., Mertz, O., Heinimann, A., Langanke, T., Pascual, U., Schmook, B., Pascual, U., Adams, C., Schmidt-vogt, D., Messerli, P., Leisz, S., Castella, J.C., Jorgensen, L., Birch-Thomsen, T., Hett., C., Bech-Bruun, T., Ickowitz, A., Vu, K.C. Yasuyuki, K., Fox, J, Padoch, C, Dressler W., Ziegler, A. D. 2012. Trends, drivers and impacts of changes in swidden cultivation in tropical forest-agriculture frontiers: A global assessment. Global Environmental Change, 22: 418–429. doi:10.1016/j.gloenvcha.2011.10.009
Vien, T. D., Leisz, S. J., Lam, N. T., & Rambo, T. 2006. Using Traditional Swidden Agriculture to Enhance Rural Livelihoods in Vietnam’s Uplands. Mountain Research and Development, 26: 192–196. doi:10.1659/0276-4741(2006)26[192:UTSATE]2.0.CO;2
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Weil, R. R., Islam, K. R., Stine, M. A., Gruver, J. B., & Samson-liebig, S. E. 2000. Estimating active carbon for soil quality assessment : A simplifi ed method for laboratory and fi eld use.
Ziegler, A. D., Fox, J. M., Webb, E. L., Padoch, C., Leisz, S. J., Cramb, R., Mertz,O., Bruun, T.B., Vien, T.D. 2011. Recognizing contemporary roles of swidden agriculture in transforming landscapes of southeast Asia. Conservation biology : the journal of the Society for Conservation Biology, 25: 846–8. doi:10.1111/j.1523-1739.2011.01664.x
Figures
Hett, C., Castella, J-C., Heinimann, A., Messerli, J-L.P. 2012. Figure 4: Locational map of Lao PDR from: A landscape mosaics approach to characterizing swidden systems from a REDD+ perspective. Applied Geography 32: 608-618.
Mertz, O. 2002. Figure 3: Theoretical relationship between fallow length and soil productivity from: The relationship between length of fallow and crop yields in shifting cultivation : a rethinking. Agroforestry Systems 55: 149–159.
University of Minnesota. 2009. Figure 1: The nutrient availability as a function of soil pH from: Unit 12 Soil pH. Retrieved from http://www.swac.umn.edu/classes/soil2125/doc/s12ch5.htm
Survey for Field Identificationǁ Appendices
75
9 Appendices
1 Methodolgy
1.1 Survey for Field Identification
Date:
Interviewer: Interpreter:
Farmer:
Timeline of field use: fallow, upland rice, any other crops? Cycles? Harvest date?
Are any fertilizers or pesticides used?
What proportion of their daily activities relates to farming? i.e. Subsistence vs. off-farm work
When was the field burned?
Rate: poor good (avg) very good
Family size: Adults __ Children (<12 yrs) __
Methodolgy ǁ Visual Observations/ Characteristics for Field
76
1.2 Visual Observations/ Characteristics for Field
Field & Owner:
Fallow Length:
Coordinates:
Slope:
Aspect:
Parameter tracked? Area:
Hill Rice Yield: Bags
Weight
kg/m2
Date of Harvest:
General Observations:
Topography-
Signs of Erosion-
Weeds-
Other Remarks- Pests/Diseases?
Protocol for Pox Cǁ Methodolgy
77
1.4 Protocol for Pox C
Note: specific protocol adapted from T.B. Bruun (10/13) but based on Weil et al. (2003)
Preparation of stock solution of KMnO4 (0.2M in 0.1M CaCl2 at pH 7.2)
1. Weigh 147 g CaCl2*2H2O and add to a 1000 ml flask half filled with miliQ water. Shake
2. Weigh 31,608 g of KMnO4 and add to a 2l glass beaker that is half filled with the 1 M CaCl2
solution. Shake. Fill the same beaker now to 90% with the 1M CaCl2 solution. Adjust pH to 7.2 using NaOH or HCl while stirring. Add 1 M CaCl2 to the 2l mark and shake. Transfer solution to a capped bottle wrapped in aluminum foil. Store bottle in the dark.
Preparations of Standards (0.005, 0.01, 0.02)
Add 1.25 ml,2.5 ml and 5.0 ml of the 0.2M KMnO4 stock solution to centrifuge tubes and dilute to the 50 ml mark with miliQ water.
Analysis
Fill a clean cuvette with distilled water, wipe the outside with a tissue and place it is the spectrophotometer **make sure it is set at 550 nm. Measure absorbance.
Standard Curve:
Add 1 ml of the 0.005M KMnO4 standard to a Falcon tube and add 19ml of distilled water. Pour about 15 ml of this standard into a 20 ml cuvette, wipe with a tissue, and measure the absorbance at 550nm. Repeat with the 0.01 and 0.02 M solutions. Construct a standard curve with absorbance on the x axis and concentration on the y-axis.
Samples:
Weigh 2,5 g of crushed soil in a Falcon tube, add 18 ml of miliQ water and 2 ml of the 0.2M KMnO4 stock solution. Shake for 4 minutes. Leave to settle for 10 minutes. Using an electronic pipette, transfer 1.00 ml supernatant to a clean Falcon tube with 19 ml of distilled water. Measure the absorbance at 550 nm.
Calculation
Pox C (mg/kg) = [0.02 mol/l – (a+b*absorbance)1]*(9000 mg C/mol)*(0.02l/0.0025 kg soil)2
1 linear equation found from the standard curve
2 Assuming 1 mol MnO4 is consumed in the oxidation of 0.75 mol (9000mg) of C
Methodolgy ǁ Standard Curve of Pox C Analysis
78
1.5 Standard Curve of Pox C Analysis
Figure BB: The standard curve derived from the spectrophotometry analysis of the standard KMnO4 solutions:0.005 M, 0.01 M and 0.02 M. The linear equation was then used to calculate the concentration of Mn
+4 (M) in the soil samples collected whereby the concentration of Pox C could be then calculated.
y = 0,0105x - 0,0004
0
0,005
0,01
0,015
0,02
0,025
0 0,2 0,4 0,6 0,8 1 1,2 1,4 1,6 1,8 2
Co
nce
ntr
atio
n (
M)
Absorbance at 550 nm
Standard Curve for KMnO₄ Reduction
Guiding Questions for In-Depth Farmer Interviewsǁ Methodolgy
79
1.6 Guiding Questions for In-Depth Farmer Interviews
Farmer Specific Interview Date: Interviewer: Catherine
IMPORTANT DATES:
Interpreter: Phaeng
2010 - corn cultivation began
2003 - land use planning & NEPL NPA boundary defined
1993 - NEPL NPA established
INTRODUCTION 1. Field & Farmer: 2. Family Size: Adults ______ Children (≤12 yrs) _____ 3. Have been a resident of B. Navene since ______
a. Reason they moved to B. Navene?
ECONOMIC 1. Fields: Upland Rice ____ Approximate Harvest ___________
Fallow ____
Padi (Lowland) Rice ____ Approximate Harvest ___________
Corn* ____ Approximate Harvest ___________
* Expenses ___________
* Income ____________
Other ? ______________
Livestock: 2. In what year were they given or buy the identified fields above? If given, by who and why?
a. Do they own land titles to them?
3. Have they sold, lost or gave away any of the fields? Y / N
a. Which and how much (land) ? b. Reason? How has this affected them?
SOCIAL/ NEEDS 1. Does the family have enough to eat from their annual rice harvest? Y / N
a. How much is it that they need for a year? i. If they cultivate padi (lowland) rice, what proportion is upland rice vs
lowland rice (Refer to Economic question #1)? b. If no, how do they compensate for the shortage? (Relatives, loans)
2. Has the average rice harvest changed? What was it like before?
a. Was it easier to meet their family’s needs or is it easier now? Why?
Methodolgy ǁ Guiding Questions for In-Depth Farmer Interviews
80
AGRICULTURAL 1. What is the rotation/cycle like between the fields?
a. Padi rice- planted every year? b. Corn- planted every year? Rotated? c. Upland rice- rotation between how many fields? Average fallow length?
2. Has their management of the rotation/cycle changed? Y / N a. How? b. Why (Causes)?
Upland Rice 1. What factors are important and they look for in a field to determine its suitability for rice
production? a. Slope? b. Soil quality? (i.e. colour) c. The presence of specific plants? Which ones? d. The size of the trees?
Soil 1. Do they believe their soil is fertile? How productive is it?
a. Has this changed? b. What makes a soil ‘good’? (feel, smell, colour..)
GENERAL 1. Any other challenges or problems? What improvements would they like to see? Do they
desire any assistance from government or sponsored programs?
Guiding Questions for NEPL NPA Land loss Effectsǁ Methodolgy
81
1.7 Guiding Questions for NEPL NPA Land loss Effects
Land loss Interview
Date: Interviewer: Catherine
INTRODUCTION Interpreter: Phaeng
1. Farmer:
2. Family Size: Adults ______ Children (<12 yrs) _____
3. Have been a resident of B. Naven since ______
a. Reason they moved to B. Naven?
ECONOMIC
4. Fields: Upland Rice ____ Approximate Harvest ___________
Padi (Lowland) Rice ____ Approximate Harvest ___________
Corn* ____ Approximate Harvest ___________
* Expenses ___________
* Income ____________
Other ? ______________
SOCIO-ECONOMIC
5. How many fields did they lose to NEPL NPA? What did they grow on them?
6. Were they compensated? Y / N
a. If yes, how? What were they given?
7. How has the loss of land affected their family?
a. Are they able to survive on their annual rice harvest?
i. Were they able to survive before they lost their land?
b. If they did receive compensation in fields, are the fields of equal, lesser or greater
quality than the fields they lost
Methodolgy ǁ Guiding Questions for Group Interview
82
1.8 Guiding Questions for Group Interview
Focus: Labour supply and 2020 policy (slash & burning /3-4 fields per family restriction)
Labour Supply:
Reasons for Problem:
General Trend:
Solutions:
Policy Reform:
Their Interpretation:
What do they think of it? i.e. problems? Good? Bad?
How do you think Ban Navene will look like in the future?
What would you like?
Open Floor:
Any questions/comments/concerns
Guiding Questions for Group Interviewǁ Field Record Sheet
83
2 Field Record Sheet
Code Long Lat Owner Fallow Slope Harvest Date Area (ha) Yield (kg·ha¯¹)
5F1 103°09'84" 20°21'86" Somdii 5 37˚ [ T 38˚(13m), M 43˚, B 42˚] Start: 23/09 Plots: 29/09 2.31 1321
5F2 103°11'15" 20°24'79" Buon Phone 5 38˚ [T 35˚, M 37˚, B 36˚] Start: 26/09 Plots: 5/10 1.29 1112
5F3 103°10'86" 20°22'51" Am Phai 5 33˚ [ T 32˚, M 31˚, B 34˚] Start: 26/09 Plots:6/10 0.69 1265
3F1 103°09'98" 20°22'11" Ka 3 28˚ 21/09 0.28 976
3F2 103°09'97" 20°24'74" Somsak 3 32˚ 20/09, finished 13/10 2.00 819
2F3 103°10'98" 20°23'88" Buon Phang 2 40˚ Finished 15/10 2.11 517
11F1 103°09'83" 20°22'06" Monsii 11 38˚ 4/10 1.35 757
10F2 103°09'80" 20°24'78" Sivone 10 27˚ Finished mid 10 1.96 1097
10F3 103°12'02" 20°24'69" Vilaisone 10 36˚ Finished mid 10 3.65 1552
Topographical Yields (kg·ha¯¹)
5F1 Top 886 5F2 Top 988 5F3 Top 1179
Middle 637
Middle 1360
Middle 1352
Bottom 780
Bottom 1290
Bottom 1432
Map of Field Locations Depicting Area (ha) ǁ Guiding Questions for Group Interview
84
3 Map of Field Locations Depicting Area (ha)
Figure CC: Map of the field locations depicting field area in hectares, colour-coded by fallow length: Blue = 2 or 3 year fallow, red = 5 year fallow and green = 10 or 11 year fallow. The dark green star represents Ban Navene.
Physical and Chemical Parameters at the Surface, 10 cm and 30 cm of the Fallow Length Study ǁ Soil Data Summaries
85
4 Soil Data Summaries
4.1 Physical and Chemical Parameters at the Surface, 10 cm and 30 cm of the Fallow Length Study
Fallow Length Bulk Density (g m¯ᶟ)** Clay (kg m¯²)* pH CEC (cmol(+) kg¯¹)
Surface 10 cm 30 cm
Surface 10 cm 30 cm
Surface 10 cm 30 cm
Surface 10 cm 30 cm
2 (n=3)
557.778 ± 60.782ᵃ
817.778 ± 161.383ᵃ
990 ± 105.830ᵃ 11.01ᵃ 15.43ᵃ
18.43ᵃᶜ
4.64 ±
0.305
4.61 ±
0.085
4.94 ±
0.295
11.487 ±
1.675
11.473 ±
0.942ᵃ
11.367 ±
1.547
3 (n=6)
903.889 ±
149.672ᵇ
1091.833 ±
140.090ᵇ 1183.333 ± 62.183ᵇ
16.65 ±
1.91ᵇ
20.30 ±
1.57ᵇ
16.38 ±
2.35ᵃ
5.02 ±
0.305
4.71 ±
0.141
4.91 ±
0.161
13.463 ±
3.024
14.533 ±
1.935ᵃᵇ
13.010 ±
1.337
5 (n=9)
726.667 ±
146.445ᶜ 866.667 ± 135.021ᵃ
1012.222 ±
113.663ᵃ
15.69 ±
2.55ᵇ
20.86 ±
1.75ᵇ
20.21 ±
2.08ᵃ
4.71 ±
0.301
4.60 ±
0.298
4.77 ±
0.222
12.204 ±
3.431
15.516 ±
2.634ᵇ
13.738 ±
4.010
10 (n=6)
933.889 ±
180.495ᵇ
1102.223 ±
113.664ᵇ 1191.667± 85.654ᵇ
17.98 ±
3.89ᵇ
23.34 ±
6.18ᵃᵇ
28.10 ±
4.40ᵇ
4.96 ±
0.353
4.70 ±
0.170
4.95 ±
0.065
14.093 ±
1.387
13.163 ±
2.364ᵃᵇ
12.980 ±
2.217
11 (n=3)
776.667 ± 91.788ᶜ
952.576 ± 77.170ᶜ
1020.000 ±
138.924ᵃ 13.71ᵃ
ᵇ 20.8ᵃᵇ 8.57ᶜ
5.05 ±
0.373
4.86 ±
0.385
4.87 ±
0.231
12.993 ±
1.505
12.960 ±
3.108ᵃᵇ
12.793 ±
3.090
P Avail (mg 100 g¯¹) Stock P Avail (g m¯²) K Exch (mg 100 g¯¹) Stock K Exch (g m¯²)
Surface 10 cm 30 cm Surface 10 cm 30 cm Surface 10 cm 30 cm Surfac
e 10 cm 30 cm
1.114 ± 0.623ᵃᵇ
0.293 ±
0.061
0.110 ±
0.039 0.296 ± 0.160ᵃᵇ
0.111 ±
0.021
0.054 ±
0.019 32.111 ± 1.956
15.338 ± 3.452ᵃ
6.904 ±
4.468
8.524 ±
5.052 5.872 ± 1.624ᵃ
3.43 ± 2.360
0.730 ± 0.524ᵃᵇ
0.261 ±
0.084
0.078 ±
0.050 0.297 ± 0.133ᵃᵇ
0.138 ±
0.040
0.047 ±
0.033 12.587 ± 4.565
6.419 ± 2.676ᵇ
3.668 ±
1.295
5.472 ±
1.617
3.466 ±1.596
ᵇ
2.150 ±
0.713
1.240 ± 0.632ᵃ
0.376 ±
0.349
0.217 ±
0.192 0.425 ± 0.177ᵃ
0.152 ±
0.111
0.107 ±
0.090 15.737 ± 5.361
8.669 ± 2.332ᵇ
4.446 ±
1.332
5.698 ±
2.179 3.695 ± 0.798ᵇ
2.251 ±
0.712
0.409 ± 0.159ᵇ
0.201 ±
0.097
0.063 ±
0.024 0.186 ± 0.073ᵇ
0.108 ±
0.048
0.038 ±
0.014 14.322 ± 8.277
6.851 ± 1.822ᵇ
4.182 ±
0.779
6.946 ±
4.412 3.854 ± 1.251ᵇ
2.500 ±
0.534
3.379 ± 2.419ᵃᵇ
0.318 ±
0.059 0.105 ± 0.38
1.165 ± 0.789ᵃᵇ
0.153 ±
0.024
0.052 ±
0.014 20.506 ± 1.448
14.873 ± 5.089ᵃ
6.837 ±
2.312
7.142 ±
4.950 7.136 ± 2.290ᵃ
3.431 ±
0.933
Samples were taken after one cropping of upland rice. Different letters within the categories represent a significant difference (Analysed by ANOVA, LSD test (if equal variance) or Games Howell test (if variance unequal) at a confidence level of 95%).
* 2 year (n=1), 3 year (n=2), 5 year (n=3), 10 year (n=2), 11 year (n=1); ** Surface & 10 cm: 2 year (n = 9), 3 year (n = 18), 5 year (n = 27), 10 year (n = 18), 11 year (n = 9)
Soil Data Summaries ǁ The Carbon and Nitrogen Parameters of the Fallow Length Study
86
4.2 The Carbon and Nitrogen Parameters of the Fallow Length Study
Fallow Length (years)
N % Total N (g m¯²) C %
Surface 10 cm 30 cm Surface 10 cm 30 cm Surfac
e 10 cm 30 cm
2 (n = 9) 0.38 ± 0.028ᵃ
0.31 ± 0.029ᵃ
0.20 ± 0.008ᵃ
104.976 ± 11.412ᵃ
127.522 ± 24.037ᵃᵇᶜᵈ
100.611 ± 9.781
4.59 ± 0.71ᵃ
3.58 ± 0.60ᵃ
1.64 ± 0.104ᵃᶜ
3 (n = 18) 0.35 ± 0.042ᵃ
0.26 ± 0.040ᶜᵈ
0.29 ± 0.075ᵇ
159.534 ± 31.624ᵇ
140.813 ± 15.922ᵃᶜ
99.956 ± 5.452
3.95 ± 0.59ᵃ
2.42 ± 0.48ᵇᶜ
1.26 ± 0.220ᵇᵈ
5 (n = 27) 0.35 ± 0.050ᵃ
0.28 ± 0.044ᵃᶜ
0.19 ± 0.021ᵃᵇ
122.908 ± 15.756ᶜ
120.625 ± 15.666ᵇᵈ
94.149 ± 14.860
4.05 ± 0.75ᵃ
2.93 ± 0.76ᵃᶜ
1.49 ± 0.263ᵃᵈ
10 (n = 18) 0.28 ± 0.078ᵇ
0.22 ± 0.055ᵇᵈ
0.16 ± 0.035ᵃᵇ
124.959 ± 24.544ᵃᶜ
118.801 ± 20.359ᵇ
92.177 ± 18.542
3.00 ± 1.2ᵇ
2.07 ± 0.47ᵇ
1.24 ± 0.160ᵇ
11 (n = 9) 0.39 ± 0.043ᵃ
0.28 ± 0.041ᵃᶜ
0.21 ± 0.018ᵃᵇ
150.281 ± 23.767ᵇᶜ
134.757 ± 24.343ᶜᵈ
106.223 ± 8.152
4.20 ± 0.52ᵃ
2.79 ± 0.52ᵃᶜ
1.93 ± 0.185ᶜ
SOC (kg m¯²) C:N SOC:Pox C
Surface 10 cm 30 cm Surface 10 cm 30 cm Surface 10 cm
1.267 ± 0.139ᵃ
1.456 ± 0.336ᵃ
0.812 ± 0.091ᵃᵇ
12.13± 1.367ᵃ
11.39 ± 1.226ᵃ
8.06 ± 0.232ᵃᵇ
40.06 ± 4.728ᵃᵇ
47.36 ± 5.193ᵃᶜ
1.794 ± 0.415ᵇ
1.306 ± 0.211ᵃᶜ
0.747 ± 0.139ᵃ
11.19 ± 0.635ᵃᵇ
9.25 ± 0.821ᵇ 7.44 ± 1.19ᵃ
41.50 ± 5.542ᵃ
43.70 ± 3.458ᵃ
1.430 ± 0.197ᵃᶜ
1.240 ± 0.250ᵇᶜ
0.754 ± 0.160ᵃ
11.65 ± 0.766ᵃᵇ
10.23 ± 1.211ᶜ
7.96 ± 0.623ᵃ
41.44 ± 4.870ᵃ
48.03 ± 8.583ᶜ
1.324 ± 0.316ᵃᶜ
1.122 ± 0.177ᵇ
0.731 ± 0.062ᵃ
10.78 ± 2.913ᵇ
9.52 ± 1.149ᵇ
8.09 ± 0.936ᵃᵇ
36.55 ± 8.755ᵇ
37.61 ± 6.811ᵇ
1.627 ± 0.254ᵇᶜ
1.333 ± 0.309ᵃᶜ
0.977 ± 0.051ᵇ
10.84 ± 0.563ᵃᵇ
9.82 ± 0.761ᵇᶜ
9.21 ± 0.234ᵇ
38.87 ± 3.737ᵃᵇ
47.59 ± 5.945ᵃᶜ
Samples were taken after one cropping of upland rice. Different letters within the categories represent a significant difference (Analysed by ANOVA, LSD test (if equal variance) or Games Howell test (if variance unequal) at a confidence level of 95%).
The Carbon and Nutrient Upper 10 cm Stocks (kg m-2) using a fixed depth or mass equivalent approach of the Fallow Length Study ǁ Soil Data Summaries
87
4.3 The Carbon and Nutrient Upper 10 cm Stocks (kg m-2) using a fixed depth or mass equivalent approach of the Fallow Length Study
Fallow Length
Upper 10 cm C (kg m¯²)
Mass Eqv. C (kg m ¯²)
Upper 10 cm N (kg m¯²)
Mass Eqv. N (kg m ¯²)
Upper 10 cm P (g m¯²)*
Mass Eqv. P (g m ¯²)*
Upper 10 cm K (g m¯²)*
Mass Eqv. K (g m ¯²)*
2 (n = 9)
2.418 ± 0.528ᵃ
2.087 ± 0.462ᵃ
0.232 ± 0.027ᵃ
0.295 ± 0.021ᵃ
0.406 ± 0.168ᵃᵇ
0.475 ± 0.162ᵃ
14.397 ± 6.501ᵃ
17.590 ± 6.672ᵃ
3 (n = 18)
3.100 ± 0.545ᵇ
2.855 ± 0.394ᵇᶜ
0.300 ± 0.038ᵇ
0.274 ± 0.026ᵃ
0.436 ± 0.121ᵃᵇ
0.412 ± 0.138ᵃ
8.939 ± 2.958ᵃ
8.271 ± 2.400ᵃ
5 (n = 27)
2.670 ± 0.319ᵃᶜ
2.999 ± 0.543ᵇ
0.244 ± 0.024ᵃ
0.273 ± 0.033ᵃ
0.578 ± 0.230ᵃ
0.629 ± 0.312ᵃ
9.393 ± 2.370ᵃ
10.228 ± 2.180ᵃ
10 (n = 18)
2.446 ± 0.404ᵃ
2.207 ± 0.503ᵃ
0.244 ± 0.043ᵃᶜ
0.220 ± 0.054ᵇ
0.294 ± 0.098ᵇ
0.271 ± 0.089ᵃ
10.800 ± 5.372ᵃ
9.773 ± 4.615ᵃ
11 (n = 9)
2.960 ± 0.416ᵇᶜ
3.030 ± 0.412ᵇᶜ
0.285 ± 0.034ᵇᶜ
0.292 ± 0.032ᵃ
1.318 ± 0.806ᵃᵇ
1.334 ± 0.809ᵃ
14.277 ± 2.661ᵃ
15.042 ± 2.298ᵃ
Values calculated by using both the fixed depth and mass equivalent approach. Different letters within categories represent significant differences (ANOVA analysis followed by LSD or Games-Howell post hoc tests, dependent on Levene's homogeneity test, at a confidence level of 95%).
* 2 n = 3, 3 n = 6, 5 n = 9, 10 n = 6, 11 n = 3
4.4 Pox C levels (mg kg-1) at the Soil Surface and 10 cm depth of the Fallow Length Study
Fallow Length Surface 10 cm
2 (n=9) 1143.20 ± 83.02ᵃ 769.75 ± 178.53ᵃ
3 (n=18) 958.54 ± 130.08ᵇ 557.86 ± 124.14ᵇ
5 (n=27) 977.96 ± 150.69ᵇ 618.47 ± 149.95ᵇ
10 (n=18) 807.76 ± 174.04ᶜ 556.01 ± 107.26ᵇ
11 (n=9) 1086.50 ± 148.10ᵃ 590.33 ± 118.92ᵇ
The Pox C (mg kg¯¹) at soil surface and at a depth of 10 cm of fields grouped according to the duration of the preceding fallow. Samples were taken after one cropping of upland rice. Different letters within the categories represent a significant difference (Analysed by ANOVA, LSD test (if equal variance) or Games Howell test (if variance unequal) at a confidence level of 95%)
Soil Data Summaries ǁ Physical and Chemical Parameters at the Surface, 10 cm and 30 cm of the Topographical Study
88
4.5 Physical and Chemical Parameters at the Surface, 10 cm and 30 cm of the Topographical Study
Slope position
Bulk Density (g m¯ᶟ)** Clay (kg m¯²)* pH
Surface 10 cm 30 cm Surface 10 cm 30 cm Surface 10 cm 30 cm
Top (n=9)
778.519 ± 184.196
874.336 ± 171.747
990.000 ± 93.274
23.75 ± 2.035ᵃ
22.46 ± 1.507ᵃ
22.50 ± 4.828
4.70 ± 0.312
4.64 ± 0.254
4.74 ± 0.206
Middle (n=9)
726.667 ± 146.445
866.667± 135.021
1012.222 ± 113.664
15.69 ± 2.547ᵇ
20.19 ± 2.325ᵃᵇ
20.21 ± 2.082
4.71 ± 3.431
4.60 ± 0.298
4.77 ± 0.221
Bottom (n=9)
785.846 ± 197.723
907.407 ± 148.857
998.889 ± 158.386
20.42 ± 1.632ᶜ
20.96 ± 1.586ᵇ
22.35 ± 2.219
4.77 ± 0.262
4.63 ± 0.314
4.82 ± 0.227
CEC (cmol(+) kg¯¹) P Avail (mg 100 g¯¹) Stock P Avail (g m¯²) K Exch (mg 100 g¯¹) Stock K Exch (g m¯²)
Surface
10 cm
30 cm
Surface
10 cm
30 cm
Surface
10 cm
30 cm
Surface
10 cm
30 cm
Surface
10 cm
30 cm
14.216 ± 1.71
3
13.122 ± 2.94
0
15.218 ± 3.41
2
0.839 ±
0.505ᵃᵇ
0.265 ±
0.087
0.190 ±
0.131
0.323 ±
0.186ᵃᵇ
0.101 ±
0.050
0.093 ±
0.061
13.181 ± 7.10
7
6.368 ±
1.741ᵃ
4.357 ±
1.982
5.067 ±
2.841
2.802 ±
1.023
2.160 ±
0.950
12.204 ± 3.43
1
15.516 ± 2.63
4
13.738 ± 4.01
0
1.240 ±
0.632ᵃ
0.376 ±
0.349
0.217 ±
0.192
0.425 ±
0.177ᵃ
0.152 ±
0.111
0.107 ±
0.090
15.737 ± 5.36
1
8.669 ±
2.332ᵇ
4.446 ±
1.332
5.698 ±
2.179
3.695 ±
0.798
2.251 ±
0.712
13.742 ± 2.59
2
15.589 ± 2.34
5
13.560 ± 4.24
7
0.554 ±
0.232ᵇ
0.089 ±
0.053
0.064 ±
0.035
0.252 ±
0.113ᵇ
0.089 ±
0.053
0.064 ±
0.035
13.015 ± 5.10
5
7.859 ±
2.352ᵃᵇ
4.046 ±
0.835
5.682 ±
2.000
3.483 ±
0.938
2.007 ±
0.432
Samples were taken after one cropping of upland rice. Different letters within the categories represent a significant difference (Analysed by ANOVA, LSD test (if equal variance) or Games Howell test (if variance unequal) at a confidence level of 95%)
* n = 3, ** n = 27
The Carbon and Nitrogen Parameters of the Topographical Study ǁ Soil Data Summaries
89
4.6 The Carbon and Nitrogen Parameters of the Topographical Study
Slope position
C % SOC (kg m¯²) SOC : Pox C N %
Surface 10 cm 30 cm Surface 10 cm 30 cm Surface 10 cm
Surface 10 cm 30 cm
Top 4.02 ± 1.07ᵃ
2.77 ± 0.77
1.66 ± 0.34
1.501 ± 0.320ᵃ
1.666 ± 0.250
0.817 ± 0.154
42.51 ± 5.60ᵃ
45.19 ± 6.57
0.35 ± 0.06
0.27 ± 0.05
0.20 ± 0.03
Middle 4.05± 0.75ᵃ
2.93 ± 0.75
1.49 ± 0.26
1.430 ± 0.197ᵃᵇ
1.240 ± 0.250
0.754 ± 0.160
41.44 ± 4.87ᵃ
48.03 ± 8.59
0.35 ± 0.05
0.28 ± 0.04
0.19 ± 0.02
Bottom 3.47 ± 0.93ᵇ
2.96 ± 0.95
1.72 ± 0.27
1.301 ± 0.249ᵇ
1.292 ± 0.277
0.851 ± 0.148
34.93 ± 6.323ᵇ
45.73 ± 6.21
0.32 ± 0.07
0.28 ± 0.06
0.20 ± 0.03
Total N (g m¯²) SOC : N
Surface 10 cm 30 cm Surface 10 cm 30 cm
130.511 ± 23.047 113.171 ± 16.535ᵃ 95.606 ± 12.065 11.52 ± 1.640ᵃᵇ 10.32 ± 1.769 8.54 ± 1.063
122.908 ± 15.756 120.625 ± 15.666ᵃᵇ 94.149 ± 14.860 11.65 ± 0.77ᵃ 10.23 ± 1.21 7.96 ± 0.62
120.233 ± 22.098 125.434 ± 17.880ᵇ 100.250 ± 21.702 10.84 ± 0.95ᵇ 10.27 ± 1.49 8.58 ± 0.90
Samples were taken after one cropping of upland rice. Different letters within the categories represent a significant difference (Analysed by ANOVA, LSD test (if equal variance) or Games Howell test (if variance unequal) at a confidence level of 95%).
* n = 3, ** n = 27
Soil Data Summaries ǁ The Carbon and Nutrient Upper 10 cm Stocks (kg m-2) using a fixed depth or mass equivalent approach of the Topographical Study
90
4.7 The Carbon and Nutrient Upper 10 cm Stocks (kg m-2) using a fixed depth or mass equivalent approach of the Topographical Study
Top
Field Upper 10 cm C (kg m¯²)
Mass Eqv. C (kg m ¯²)
Upper 10 cm N (kg m¯²)
Mass Eqv. N (kg m ¯²)
Upper 10 cm P (g m¯²)*
Mass Eqv. P (g m ¯²)*
Upper 10 cm K (g m¯²)*
Mass Eqv. K (g m ¯²)*
1 2.418 ± 0.528 2.087 ± 0.462 0.253 ± 0.040
0.215 ± 0.038 0.600 ± 0.132
0.554 ± 0.145
10.140 ± 4.219
8.953 ± 4.557
2 2.452 ± 0.323 2.998 ± 0.389 0.225 ± 0.034
0.274 ± 0.027 0.284 ± 0.060
0.312 ± 0.103 5.159 ± 1.397
6.080 ± 2.645
3 3.128 ± 0.276 3.183 ± 0.352 0.253 ± 0.026
0.256 ± 0.028 0.433 ± 0.190
0.418 ± 0.202 8.311 ± 3.265
8.010 ± 3.297
Average: 2.666 ± 0.503
2.753 ± 0.622 0.244 ± 0.035
0.248 ± 0.038
0.439 ± 0.180ᵃᵇ
0.428 ± 0.171ᵃᵇ 7.870 ± 3.516
7.681 ± 3.355
Middle
Field Upper 10 cm C (kg m¯²)
Mass Eqv. C (kg m ¯²)
Upper 10 cm N (kg m¯²)
Mass Eqv. N (kg m ¯²)
Upper 10 cm P (g m¯²)*
Mass Eqv. P (g m ¯²)*
Upper 10 cm K (g m¯²)*
Mass Eqv. K (g m ¯²)*
1 2.623 ± 0.254 2.380 ± 0.209 0.255 ± 0.023
0.227 ± 0.016 0.652 ± 0.267
0.607 ± 0.258
11.756 ± 0.550
10.743 ± 0.636
2 2.520 ± 0.277 2.940 ± 0.550 0.227 ± 0.018
0.265 ± 0.032 0.532 ± 0.300
0.646 ± 0.425 8.385 ± 1.437
10.034 ± 1.880
3 2.866 ± 0.345 3.125 ± 0.352 0.249 ± 0.022
0.272 ± 0.019 0.549 ± 0.194
0.576 ± 0.205 8.038 ± 2.730
9.153 ± 1.534
Average: 2.670 ± 0.319
2.815 ± 0.499 0.244 ± 0.024
0.255 ± 0.030
0.578 ± 0.230ᵃ
0.610 ± 0.271ᵃ 9.393 ± 2.370
9.977 ± 1.431
Bottom
Field Upper 10 cm C (kg m¯²)
Mass Eqv. C (kg m ¯²)
Upper 10 cm N (kg m¯²)
Mass Eqv. N (kg m ¯²)
Upper 10 cm P (g m¯²)*
Mass Eqv. P (g m ¯²)*
Upper 10 cm K (g m¯²)*
Mass Eqv. K (g m ¯²)*
1 2.321 ± 0.356 1.946 ± 0.301 0.230 ± 0.029
0.191 ± 0.017 0.418 ± 0.068
0.360 ± 0.065 9.493 ± 2.892
7.910 ± 2.763
2 2.695 ± 0.310 3.076 ± 0.614 0.241 ± 0.018
0.275 ± 0.044 0.401 ± 0.160
0.406 ± 0.162 8.620 ± 3.600
8.821 ± 3.590
3 2.762 ± 0.280 2.873 ± 0.471 0.266 ± 0.023
0.275 ± 0.022 0.202 ± 0.082
0.206 ± 0.095 9.384 ± 1.303
10.303 ± 3.369
Average: 2.593 ± 0.363
2.632 ± 0.681 0.246 ± 0.028
0.247 ± 0.049
0.340 ± 0.142ᵇ
0.324 ± 0.134ᵇ 9.165 ± 2.434
9.011 ± 3.010
Pox C levels (mg kg-1) at the Soil Surface and 10 cm depth of the Topographical Study ǁ Soil Data Summaries
91
4.8 Pox C levels (mg kg-1) at the Soil Surface and 10 cm depth of the Topographical Study
Row (n = 9)
Total (n=27)
1 2 3
Slope Position Surface 10 cm Surface 10 cm Surface 10 cm Surface 10 cm
Top 899.61 ±
199.18 572.85 ±
186.14 904.57 ±
207.85 597.72 ±
134.42 1011.08 ± 167.36
672.65 ± 110.13
938.42 ± 192.00
614.41 ± 147.72
Middle 982.18 ± 141.93
636.52 ± 103.38
946.66 ± 182.23
566.39 ± 173.93
1005.03 ± 135.99
652.49 ± 165.57
977.96 ± 150.69
618.47 ± 149.95
Bottom 1056.36 ± 278.42
688.36 ± 199.95
897.01 ± 181.46
570.67 ± 132.81
1057.95 ± 241.19
674.83 ± 196.34
1003.78 ± 240.42
644.620 ± 180.17
Samples were taken within a 15 m by 15 m plot across three rows from three fields with a five year preceding fallow length and one cropping of upland rice. Different letters within the categories represent a significant difference (Analysed by ANOVA, LSD test (if equal variance) or Games Howell test (if variance unequal) at a confidence level of 95%)
Results ǁ Interactions between Soil Quality and Upland Rice Yield
92
5 Results
5.1 Interactions between Soil Quality and Upland Rice Yield
0,00
0,50
1,00
1,50
2,00
2,50
0 200 400 600 800 1000 1200 1400
P A
vail
(mg∙
10
0 g
so
il¯¹)
Pox C (mg·kg soil¯¹)
0,0
5,0
10,0
15,0
20,0
25,0
0 200 400 600 800 1000 1200 1400
K E
xch
(m
g ·1
00
g so
il¯¹)
Pox C (mg·kg soil¯¹
Surface
10 cm
Surface
10 cm
a)
b)
rS= 0.602**
rS= 0.534**
Figure B: The relationship between upland rice yield, Pox C and a) P Avail and b) K Exch at the soil surface and at a depth of 10cm of fields with five-year preceding fallows. Soil samples were taken after the harvest of one cropping of upland rice. Individual points are colour coded according to yield levels (kg ∙ ha¯¹): below 1000 is depicted with blue, above 1000 is red/pink and the highest yield (1432) is coded green. Analysed by the Pearson’s Correlation test at a confidence level of 99% (**), n=27
System Influence: Topographical Influence on Upland Rice Yield ǁ Results
93
5.2 System Influence: Topographical Influence on Upland Rice Yield
0
200
400
600
800
1000
1200
1400
1600Y
ield
(kg
∙ha¯
¹)
Slope Position
5F1
5F2
5F3
Top Middle Bottom
Figure C: The relationship between upland rice yield and slope position. The solid trendline represents the association if 5F1 is excluded; the dotted trendline includes all data points. No significance found.
List of Interviewees and Informants ǁ System Influence: Topographical Influence on Upland Rice Yield
94
6 List of Interviewees and Informants
In Depth Interviews: Farmers
2 and 3 Year Fallow 5 Year Fallow 10 or 11 Year Fallow
Buon Thong Somdii Vilaisone
Ka Buon Phone Sivone
Somsak Am Phai Monsii
NEPL NPA Land loss Interviews:
Thong dee
Som Thong
Phuangsone (aka Little Father)
**Families who lost land:
Phaeng Phone Chanty Somthong
Bin’s Father Chan Phet Boua thong
Sivone Thong Phouy Kham La
Vilaisone Kham Lay
Siphone Xieng Phan
Group Interview:
Thong Phouy (Headman) Buon Phone
Siphet (2nd Headman) Am Phai (+ wife)
Von Shaeng (Women’s Rep) Jaem (Somdii’s wife)
Ka Monsii (+wife)
Buon Thong
Somsak
System Influence: Topographical Influence on Upland Rice Yield ǁ Ranking of the Constraints to Upland Rice Production
95
7 Ranking of the Constraints to Upland Rice Production
Participant
Constraint A B C D E F G H I J K L M N O P Q R S T Score
Rank
Weeds 6 4 7 5 9 5 7 7 6 5 5 7 5 4 6 6 5 6 7 4 116 9
Rodents 9 9 7 7 8 9 10
10 4 7 7 9 9
10 9 9
10 7 7 7 164 3
Rainfall 5 5 10 6
10 6 7 8 7 9 9 6 1 4 5 4 6 5 4 3 120 8
Land Availability 7 7
10 3 7 8 6 7 6 6
10 9 6 5 5 6 4 7
10 6 135 5
Insects 6 5 7 4 4 7 7 9 3 10 6
10 7 7
10 7 5 6 8 5 133 6
Soil Suitability 8 8 8 5 9 5 5 8 6 4
10 7 4 8 9
10 8
10 8
10 150 4
Erosion 4 3 7 10 5 6 3 5 8 9 9 5 2 6 6 4 5 6 5 8 116 9
Wild Animals 6 8 6 6 6 8 4 6 5 5 5 8 3 9 7 5 8 8 6 6 125 7
Disease 7 6 9 8 10
10 9
10 9 8 8 7 8 8
10 8 9 9 9 9 171 1
Labour Supply
10
10 8 9 8 5 8 9
10 3 7
10
10 9 8 9 7
10 9 8 167 2
Disease 1
Labour Supply 2
Rodents 3
Soil Suitability 4
Land Availability 5
Insects 6
Wild Animals 7
Rainfall 8
Weeds & Erosion 9