microbial, enzymatic, and soil nutrient dynamics - repositories

Microbial, enzymatic, and soil nutrient dynamics associated with debris dam

revegetation efforts of low degraded tobosa grasslands in the Chihuahuan Desert at

Big Bend National Park

By Apolinar Ortiz Jr, B.S.

A Thesis

in

Microbiology

Submitted to the Graduate Faculty

of Texas Tech University in

the Requirements for

the Degree of

MASTER OF SCIENCE

Approved

Dr. John C. Zak

Chair of Committee

Dr. Veronica Acosta-Martinez

Dr. Randall Jeter

Dr. Peggy Miller,

Interim Dean of the Graduate School

August, 2011

Copyright, 2011

Apolinar Ortiz Jr

Texas Tech University, Apolinar Ortiz Jr, August 2011

ii

Acknowledgments

I would like to thank Dr. John Zak without whom, I would not have been able to

experience research and pursue my degree. I have been very fortunate to have such a

knowledgeable person guide me through my Masters. I would also like to thank Dr.

Acosta-Martinez and Dr. Jeter for all their time, patience and guidance in my pursuits for

a higher education. I would like to give a big thanks to all the lab helpers at the USDA,

and John Cotton for aiding me in my experiments. I would like to thank the

undergraduates and graduates in Dr. Zak lab for all their knowledge, patience and time

they have given me during my research, without which I would have never experienced

what real lab work was. Finally I would like to thank my friends and family for their

support. My wife Michelle for always being there when I needed her, my mother Maria

for teaching me so many important values growing up, my Sister Lorena for making fun

of me for enjoying science, my Aunt Jacinta for showing me to appreciate what I have

and work hard. My Uncle Camilo and cousins for helping me enjoy life, and my

grandmother Emilia for teaching me to be tough. My son Dacien Ortiz for reminding me

to be a good example for him and show him that learning can be fun.


iii

Table of Contents

Acknowledgments……………………………………………………………………..….ii

Abstract…………………………………………………………………………………...iv

List of Figures………………………………………………………………………….....vi

I. Introduction …………………………………………………………………………….1

Desert Systems………………………………………………………………...…1

Restoration ……………………………………………………………………...3

References ……………………………………………………………………....5

II. Relating re-vegetation efforts in a degraded low-elevation grassland at Big Bend

National Park, Chihuahuan Desert to microbial community structure and

nutrient dynamics …………………………………………………………………8

Introduction…………………………………………………………….….…..…..8

Methods…………………………………………………………………..……....10

Results…………………………………………………………………………....14

Discussion………………………………………………………………………..24

References………………………………………………………………………..37

III. Restoring microbial functionality as a prerequisite to successful restoration effort

of low-elevation grassland in the Chihuahuan Desert in Big Bend

National Park……………………………………………………………….……40

Introduction……………………………………………….……………………..40

Methods………………………………………………….……………………....43

Results…………………………………………………………………………...45

Discussion……………………………………………………………………….49

References……………………………………………………………………….57


iv

Abstract

With the increase of temperature and the amount of land lost to desertification,

scientists must learn to monitor, control, and reestablish the land for future generations.

This study, conducted in the northern part of Big Bend National Park, Chihuahuan Desert

examined the ability of the debris dam approach to reestablish critical soil microbial

activity and community structure and activity in conjunction with revegetation efforts of

low-elevation arid grasslands. Debris dams previously established by resource managers

at Big Bend National Park in 2006 were sampled in January, May, August and October

2010 and January 2011 along with bare soil and an adjacent intact tabosa grassland. For

all locations, a 7-cm diameter by 15-cm long bucket auger was used to take soil samples

at 15-cm increments to a depth of 45 cm total (3 increments per core). At each sample

date microbial biomass carbon and fatty acid methyl ester (FAME) analyses were

conducted to ascertain microbial community structure. Functional characteristics of the

soil bacteria and fungi were evaluated using BIOLOG and FUNGILOG procedures and

key microbial enzyme activities of soil nutrient cycling (phosphodiesterase, β-

glucosidase, and phenol oxidase). Soil nutrient and edaphic properties were also obtained

for each sample date. The debris dam approach did reestablish important microbial

activity in these degraded low desert grasslands. Microbial biomass carbon had increased

substantially as compared with the bare soils and were even higher than the natural

grassland. Microbial community structure was similar between the natural vegetation and

the debris dams after 4 years. Although fungi dominated all three locations, Gram-

negative bacteria and Actinomycetes dominated the bare soil while Gram-positive


v

Bacteria dominated the natural vegetation and debris dam soils. Soil nutrient dynamics

were similar between the debris dams and natural vegetation areas as important microbial

and plant linkages were reestablished. Importantly, the high levels of extractable NO3-

that characterize the bare soils in this region of Big Bend National Park with the loss of

vegetation were reduced under the debris dams as nitrogen becomes immobilized in the

vegetation and with greater microbial biomass. All microbial enzyme activities were

higher under the natural vegetation with the debris dams intermediate in activity levels

between the natural vegetation and the bare soil. Microbial carbon use was also similar in

that microbial functional capabilities were intermediate between the natural vegetation

and the bare soil. The microbial and nutrient data indicates that debris dams can be

effective in restoring plant cover to formally bare regions in the Chihuahuan Desert

without the need for supplemental water. Once plants are reestablished, regardless of

species, important microbial dynamics and associated ecosystem processes are increased

above levels that had been occurring in the bare or disturbed soils. Moreover the

trajectory of the microbial and soil nutrients suggests that these vegetated bands are

sustainable as critical aspects of nutrient mineralization coupled with increased microbial

activity have been promoted. In addition from a practical standpoint, the debris dams will

be more effective than the intensive investment of planting drought-tolerant plants that

can become invasive and threatening to the naturally occurring plants within Big Bend

National Park.


vi

List of Figures

2.1 Seasonal patterns of microbial biomass carbon by depth associated with a

restoration effort at a low-elevation degraded tabosa grassland in the

Chihuahuan Desert at Big Bend National Park…………………………………..29

2.2 Seasonal patterns of Fatty acid methyl esters (FAME) by depth associated with a



2.3 Seasonal patterns of nitrate (NO3-) by depth associated with a



2.4 Seasonal patterns of ammonium (NH4+) by depth associated with a



2.5 Seasonal patterns of pH by depth associated with a


Chihuahuan Desert at Big Bend National Park…………………………………33

2.6 Seasonal patterns of available phosphorus by depth associated with a


Chihuahuan Desert at Big Bend National Park………………………………….34

2.7 Seasonal patterns of potassium by depth associated with a



2.8 Seasonal patterns of Soil Organic Matter (SOM) by depth associated with a



3.1 Seasonal patterns of Biolog GN-2 microtiter plate activity by depth associated

with a restoration effort at a low-elevation degraded tabosa grassland in the


3.2 Seasonal patterns of Fungilog SFN-2 microtiter plate activity by depth

associated with a restoration effort at a low-elevation degraded tabosa grassland

in the Chihuahuan Desert at Big Bend National Park……………………………53


vii

3.3 Seasonal patterns of phosphodiesterase activities by depth associated with a



3.4 Seasonal patterns of β-glucosidase activities by depth associated with a



3.5 Seasonal patterns of phenol oxidase values by depth associated with a


Chihuahuan Desert at Big Bend National Park…………………………………56


1

Chapter I

Introduction

Desert System

“With the desert fathers you have the characteristic of a clean break with a

conventional, accepted social context in order to swim for one’s life into an apparently

irrational void.”

Thomas Merton

Desertification occurs in arid and semi-arid environments, as these areas are

primarily limited by the amount of rainfall available for soil microbial activity and plant

growth (Weltzin et al. 2003). A secondary factor limiting ecosystem processes in arid

ecosystems is the high temperatures that occur during the day and the drastic drop in

temperatures at night. These two factors restrict ecosystem function over much of the

year leading to reduced soil microbial activity and primary production. If arid systems are

secondarily impacted by human activity, ecosystem process can further decline leading to

desertification. Lovich and Bainbridge (1999) have noted that many areas around the

world are becoming converted to dry lands and deserts due to overgrazing, firewood

harvesting, poor farming, and off-road recreation along with business operations,

introduction of exotic animals and plants, and more recently due to climate change. Once

arid landscapes are damaged they are very difficult but not impossible to repair (Lovich

and Bainbridge 1999). Tolba (1984) compared desertification to a skin disease and


2

suggested as with any disease, treating the symptoms is secondary to tackling the cause.

If we look at desertification at a landscape level disease we must look at the abiotic and

biotic constraints as they influence system dynamics to help restore health with proper

management and treatments.

Deserts have limited biological potential and activity due to adverse abiotic

factors that limit diversity and activity except during intermittent ephemeral periods of

time (Goodall 1976; Whitford, 2002). Across seasons, water availability is the major

abiotic constraint to all biotic structure and activity (e.g., Weltzin et al. 2003). For most

arid ecosystems precipitation events occur primarily as small scattered rain events that

are usually less than two millimeters (Collins et al. 2008; Robertson et al 2009). Whitford

(2002) also reported for desert ecosystems moisture lost from evaporation and

transpiration in desert systems was greater than the moisture gained during that period for

when plant productivity is the highest. With limited water availability, the desert growing

season can be short with plants showing the stress of water deficit. Patrick et al. (2007)

showed that in mid-elevation grassland in the Chihuahuan Desert at Big Bend National

Park, during the winter months, the levels of evaporation and transpiration are much

lower than the summer months due to lower levels of solar radiation, lower precipitation

and decreased plant activity. This evaporation and transpiration combined with limited

precipitation can account for the pulse patterns in biological activity that has been

documented for soil processes as well as with plant activity. Gallo et al. (2006) and

Collins et al. (2008) showed how these stress periods cause the accumulation of nutrients

due to suppressed microbial activity and lack of degradation of organic materials. As


3

ecosystem processes in arid ecosystems are tightly linked to moisture availability and

subsequent microbial activity, any perturbation that disrupts these plant-soil linkages

either through direct or indirect results of human activity will likely lead to desertification

and system degradation.

With the stress from high temperature, microbial activity slows down and even

causes microbes to die off, leaving pockets of nutrients that become available when

moisture is present (Belnap et al. 2005). With large precipitation events and low plant

uptake, nutrients can be lost due to leaching or runoff further decreasing ecosystem

productivity. With limited vegetation, movement of nutrients in desert systems to deeper

soil or to adjacent areas can be attributed to the soil topography and soil texture (Collins

et al. 2008). Some plant roots can access these pockets of nutrients and with available

moisture, primary productivity can continue even when the soil moisture levels do not

remain at optimum levels (Robertson et al. 2009). However, loss of nutrients and the

aggregation of nutrients into patches is a hallmark of desertification (Whitford 2002).

Restoration

Natural recovery of desertified ecosystems in arid regions is limited due to

extreme temperatures, high winds, low levels of moisture, and loss of fertility within the

soil even if the disturbance has halted (Bainbridge 2007). Favorable conditions for plant

establishment occur infrequently in desert systems and could take hundreds of years to

recover without human involvement. Bainbridge (2007) showed that arid systems that

have had human activity beyond a simply hunter-gatherer level of existence are in need


4

of restoration. Restoration efforts globally have been noted to start in the early 1900s for

many dry lands (Griffiths 1901; Cox et al. 1982). Progress was limited due to lack of

scientific testing, controlled experiments, and a way to distribute findings. Hall (2001)

said that another limiting factor was the lack of understanding of arid and semi-arid

ecosystems because most of the research was collected from areas that had humid

environments and had natural recovery of vegetation. Natural vegetation restoration can

be minimal or large scale; some projects are short term or long term, each project is

designed for the affected area, and with positive results it can be established in other

similar areas such as soil type, cover type or location.


5

References

1. Belnap, J., Welter, J.R., Grimm, N.B., Barger, N., and Ludwig, J.A., 2005.

Linkages between Microbial and Hydrologic Processes in Arid and Semiarid

watersheds. Ecology 86, 298-307.

2. Bainbridge, D.A., 2007. A Guide to Desert and Dryland Restoration. Island Press.

Washington, DC.

3. Collins, S.L., Sinsabaugh, R.L., Cresnshaw, C., Green, L., Porras-Alfaro, A.,

Stursova, M., and Zeglin L.H., 2008. Pulse dynamics and microbial processes in

arid lands ecosystems, Journal of Ecology 96, 413-420.

4. Cox, J.R., H.L., Morton, T.N., Johnson, G.L., Jordan, S.C., Martin, and L.C.,

Fierro. 1982. Vegetation Restoration in the Chihuahuan and Sonoran Deserts of

North America. Agriculture Reviews and Manuals #28. USDA Agricultural

Research Service, Tucson, AZ.

5. Gallo, M.E., Sinsabaugh, R.L., and Cabaniss, S.E., 2006. The role of ultraviolet

radiation in litter decomposition in arid ecosystems. Applied Soil Ecoogy 34, 8-

91.

6. Goodall, D.W., 1976. Evolution of desert biota. University of Texas Press,

Austin, TX.

7. Griffiths, D., 1901. Range improvements in Arizona. USDA Bureau of Plant

Industry Bulletin #4. Washington, DC.


6

8. Hall, M., 2001. Repairing mountains: Restoration ecology and wilderness in 20th

century. Utah. Environmental history 6,574-601.

9. Lovich, J.E., D. Bainbridge. 1999. Anthropgenic degradation of the Southern

California desert ecosystem and prospects for natural recovery and restoration.

Environmental Management 24,309-326.

10. Mostafa K. Tolba 1984. A Harvest of Dust? Envrironmental Conservation 11,1-2.

11. Patrick, L., Cable, J., Potts, D., Ignace, D., Barron-Grafford, G., Griffith, A.,

Alpert, H., van Gestel, N., Robertson, T., Huxman, T.E., Zak, J., Loik, M.E., and

Tissue, D., 2007. Effects of a decrease in summer precipitation on leaf, soil an

ecosystem fluxes of CO2 and H2O in a sotol grassland in Big Bend National Park,

Texas. Oecologia 151,704-718.

12. Robertson, T.R., Bell, C.W., Zak, J.C., and Tissue, D.T., 2009. Precipitation

timing and magnitude differentially affect aboveground annual net primary

productivity in three perennial species in Chihuahuan Desert grassland. New

Phytologist 181, 230-242.

13. Whitford, W.G., 2002. Ecology of Desert Systems, Academic Press, London, UK


7

14. Weltzin, J.F., Loik, M.E., Schwinnings, S., Williams, D.G., Fay, P.A., Haddad,

B.M., Harte, J., Huxman, T.E., Knapp, A.K., Lin, G., Pockman, W.T., Shaw,

M.R., Small, E.E., Smith, M.D., Smith, S.D., Tissue, D.T., and Zak, J.C., 2003.

Assessing the response of terrestrial ecosystems to potential changes in

precipitation. BioScience 53,941-952.


8

Chapter II

Relating re-vegetation efforts in a degrade low-elevation grassland at Big Bend

National Park, Chihuahuan Desert to microbial community structure and nutrient

dynamics

Introduction

The low-elevation grasslands in the Chihuahuan Desert in Big Bend National

Park (BBNP) are a patchwork of bunchgrasses, shrubs, and succulents (Alex 2006,

Fenstermacher et al. 2006). These grasslands are important for maintaining the

hydrologic and ecological processes, nutrient cycling, and preserving biodiversity across

large areas of the Chihuahuan Desert. Unfortunately, these low elevation grasslands in

BBNP have changed since the park was established in the early 1940s due to overgrazing

in the early 19th

century combined with periods of drought. As a consequence, these low-

elevation grasslands have experienced the greatest change in vegetation cover and

structure within the National Park and have been modified to bare areas, shrubs lands or

banded grasslands (Rinas 2007).

Restoration of arid region grasslands is hindered by the amount of precipitation

they receive (e.g., Weltzin et al. 2003), the high evaporation rates from bare soil surfaces

and the changes in soil temperatures on a daily basis that occur within these soils

throughout the year. Hadley (1970) reported that soil surface temperatures in a

creosotebush in the Sonoran Desert exhibited daily fluctuations of 45 C during the

summer. Once vegetation is removed from a site that experiences these high soil


9

temperatures, the links between plant productivity and microbial dynamics decline,

increasing plant loss and subsequent soil erosion. Consequently, areas that have

experienced a reduction in vegetation cover lose moisture faster than they gain resulting

in exaggerated periods of dry days that occur between critical moisture pulses (Huxman

et al. 2002, 2004).

Under typical conditions in desert systems, nutrient dynamics, microbial activity

and plant growth are tightly linked with moisture pulses and the amount and timing of

these pulses (Whitford 2002). However, due to increased moisture stress in bare areas

combined with high soil temperature, many soil microbes die from desiccation thus

decreasing subsequent microbial activity when moisture does become available (Orchard

& Cook 2002) In addition, a negative feedback loop can be established, whereby the

amount of microbial death that has occurred results in the occurrence of moderate to

high soil nutrient levels that can subsequently be transported off-site following a large

rain event furthering the decline of the ecosystem (e.g. Belnap et al. 2005).

One approach that has shown promise in reducing erosion and promoting plant

establishment in arid ecosystems is establishing buffer strips using coarse woody debris

on highly erodible low-elevation grassland soils at BBNP (Rinas 2007). The approach

involves the building of debris dams that are perpendicular to the flow of water across the

landscape. These structures can help in the reallocation of nutrients and water to provide

sufficient moisture for the reestablishment of grasses. Debris dams have been shown to

collect nutrients from bare areas in grasslands (Marino 2004) and redistribute these

resources to vegetated areas. The goal is to restore these degraded areas back to their


10

previous state, having the same microbial diversity and dynamics to help sustain

ecosystem processes critical for that system (Allen 1988). Restoration or rehabilitation is

designed to reestablish critical paths of energy flow, nutrient water filtration and linkages

between the plant and microbial subsystem throughout the ecosystem (Allen 1988, 1989).

Our goals for this investigation are to evaluate the success of the “debris dam” approach

to ameliorate the adverse effects of bare soil on soil microbial and nutrient dynamics as a

precursor to effective low-elevation grasslands restorations in Big Bend National Park.

Methods

The restoration efforts for this project were initiated at North Rosillos site on the

former Harte ranch beginning in May 2006. As restoration managers at Big Bend

National Park were aware that soil temperatures and water infiltration issues were a

major concern in establishing vegetation on former low-elevation tobosa (Pleuraphis

mutica) grasslands, a new approach using a combination of erosion control blankets,

hydro-seeding and coarse woody debris obtained from management efforts within the

National Park was attempted (Rinas 2007). Revegetation strips for this site are 1-1.2

meters wide (three to four feet) and about 9 meters (thirty feet) long and placed along

contours to decrease water runoff and increase infiltration. Strips were also formed to

mimic the natural patterns of the shrubs and grasses in this low-elevation grassland

(Rinas 2007). A disk plow was used to break-up the soil to a depth of 15 cm to increase

infiltration. After plowing, a seed mixture consisting of native and range grass and forb,

mulch and a glue substance that had been used in road revegetation was sprayed on the

soil of each debris dam strip. Following seeding, erosion control blankets were placed on


11

top of the hydro mulch and the strips were covered with brush obtained from trail

management to a depth of 1 m. Plant growth was initiated with the onset of the summer

rains for the area. The debris dams established at the North Rosillos location are part of a

larger restoration project on the Hart Ranch where 77.3 hectares (191 acres) of low-

elevation grasslands are considered for restoration.

Soil at the North Rosillos Site is a deep silty loam originally classified as Tornillo

(fine-silty, mixed, superactive, thermic Fluventic Haplocambids) and recently reclassified

as Chalkdraw. Mean elevation at the North Rosillos site is 835 masl with site aspect of

0.6%. Total annual precipitation for the region has averaged approximately 268 mm since

1982 with mean monthly rainfall ranging between 8.8 mm (March) and 41.1 mm

(September). Mean daily high temperatures range from 17.59 °C (December) to 36.20 °C

(June), while daily lows range from 1.10 °C (January) to 22.32 °C (July). Of note, surface

temperatures recorded in situ at the North Rosillos location rank among the highest

recorded in BBNP.

Three debris dames, three bare areas and three locations in an intact tobosa

grassland adjacent to the reclaimed areas were sampled during each designated period.

Two samples were taken at each location, the bare and debris dams were sampled relative

to each other with the bare areas above and below the debris dam sampled, while the

vegetated areas were sampled west of the debris dams. For all locations a 7-cm diameter

by 15-cm long bucket auger was used to take soil samples at 15-cm increments to a depth

of 45 cm total (3 increments per core). Approximately 250 g of soil were obtained per

depth increment per sample. Soils were transported in a cooler and stored at 4ºC at Texas


12

Tech University for no longer than one week after collection. Soil moisture and nutrient

analyses were conducted immediately after returning from the field.

Soil microbial biomass carbon was evaluated using the chloroform fumigation

procedure described by Vance et al. (1987). Two 10-g dry weight equivalent subsamples

from each sample were fumigated with chloroform for 48 hours under vacuum. A second

set of 10-g subsamples was processed without chloroform fumigation as controls. After

the fumigation, samples were extracted using a 5M K2SO4 solution and filtered through

Whatman 43 filter paper. Filtered samples were transferred to a cuvette and absorbance

measured for biomass estimates at 280 nm on a spectrophotometer (Nunan et al. 1997).

The amount of microbial biomass carbon obtained in the controls was subtracted from the

amount of carbon obtained in the fumigated samples to obtain the amount of carbon

present as microbial biomass carbon using the correction factors provided in Nunan et al.

(1997).

Fatty Acid Methyl Ester amounts and compositions from soil samples collected in

the natural vegetation, bare soil, and debris dams at each sample period were obtained

using procedures for the MIDI system as established by Acosta-Martinez et al. (2003).

The microbial fatty acid subsamples obtained from each sample period were compared

and identified with the fatty acid recognition software 6890 GC series II. This program

will use a Microbial Identification system to profile microbial community structure based


13

upon FAME signatures were classified as:

1. saprophytic fungi: 18:1ω9c, 18:2ω6.9, 18:3ω3c, 18:3ω6c, and 20:5ω3;

2. arbuscular-mycorrhizal fungi: 16:1ω5c, 20:1ω9c, 20:2ω6c and 22:1ω9c;

3. Gram-positive bacteria: 14:0 iso, 15:0 iso. 15:0 anteiso, 16: iso, 17:0 iso and

17:0 anteiso markers;

4. Gram-negative bacteria: 16:1ω9c, 16:1ω7c, 16:1ω7t, cyclo17:0, 18:1ω7c,

18:1ω7t, 18:1ω5c and cyclo19:0;

5. Actinomycetes: 10 methyl 16:0, 10 methyl 17:0 and 10 methyl 18:0 fungi

(Madan et al., 2001; Olsson et al. 1999).

A 100-g subsample of soil from each sample was sent within 24 hours to Waters

Agriculture Laboratories Inc. (city, state) to obtain levels of extractable NH4+, and NO3

-,

soil pH, percentage soil organic matter and a suite of minor nutrients including levels of

extractable phosphorus.

Statistical Analyses

Data Analysis was conducted using SPSS 19 at three levels of analysis. A

Levene’s test was used on all parameters to ensure the variance of each group are

homogenous. Tukey Post hoc tests were run when ANOVAs were significant to

determine the source of the significance. For the level one assessment, ANOVAs of

depth by location with seasons combined and location by season with depths combined


14

were conducted for all data. For the level two assessments a repeated measures ANOVA

using time as the repeated measure was run for depth by location with seasons combined.

The level three analyses also employed a one-way ANOVA for each depth if the location

and season interaction was significant in the previous level two assessments.

Results

Microbial Community Structure

Microbial Biomass Carbon

Across all sample dates and depths combined, Microbial Biomass Carbon (MBC)

values were significantly highest under the debris dams (p<0.001) than in either the

natural grassland or bare soils for a full year of sampling (Figure 2.1A, B, C). MBC

values from the natural grasslands were significantly higher than values obtained from

the bare soil (p<0.001) across all depths and seasons. Across all sample times there was

no effect of depth on levels of microbial biomass for all locations combined. However,

within sample times there were significant effects of depth on MBC. For 0-15-cm depth

the highest MBC levels occurred in October, this event happened in both 15-30 and 30-

45 depths as well Figure (2.1). These values were significantly (p<0.001) different than

for any other sample month. However there were no significant (p=0.167) differences

among any location for MBC values for the other three sample dates for 0-15-cm depth.

In the analysis of location by sample date there were significant differences by

season (between subject effects) with the highest values of MBC in all locations


15

occurring in October (Figure 2.1). The repeated measures analysis showed that the

highest MBC values were associated with the debris dams (wilks lambda p=.001) and

there was no significant interaction of sample date and location (wilks lambda p=0.327).

The lowest values of MBC were observed in January 2010 for all locations. Though

MBC differed among depths by location the seasonal effects were consistent within each

of the three depths.

FAME

Actinomycetes

Across all sample times, location is significant (p<0.001) with the highest

percentage FAME values for actinomycetes occurring under the bare soil and the lowest

values under the natural vegetation (Figure 2.2). Values for the debris dam restoration

approach were intermediate and similar to the natural vegetation. Across all sample times

there was a significant (p=0.031) effect on actinomycetes percentages by depth (15-30

cm) in all locations (Figure 2.2B). For 15-30-cm depth the highest actinomycetes

percentages occurred in August 2010. These values were significantly (p<0.001) different

than January 2010 and 2011; however there were no significant (0.658) difference among

any location for actinomycetes percentage for the other three sample dates.


season (between subject effects) with the highest values of actinomycetes in all locations

occurring in August 2010 (Figure 2.2). The repeated measures analysis showed that the

highest actinomycetes percentages were associated with the bare soils (wilks lambda


16

p<0.001) and there was no significant interaction of sample date and location (wilks

lambda p=0.826). The lowest values of actinomycetes percentages were observed in

January 2011. Although actinomycetes percentages differed among depth by location, the

seasonal effect was consistent at each of the three depths.

Fungi

Across all sample times, location was significant (p< 0.001) with the highest

values of fungi percentage FAME levels occurring under the natural vegetation and the

lowest value under the bare soil, and the values associated with the debris dams were

intermediate and similar to the natural vegetation (Figure 2.2). Across all sample times

there was not a significant (p= 0.343) effect on fungal FAME levels by depth for all

locations combined (Figure 2.2). Also within sample times there was not a significant

effect on depths. For the 15-30-cm depth the highest fungal FAME levels occurred in

October 2010. The fungal FAME values were not significantly (p= 0.401) different

among any location for the other three sample months. In the analysis of location by

sample date there was not a significant difference by season effect (between subject

effects) as the percentages of fungal FAME levels were very similar across sample dates

(Figure 2.2). The repeated measures analysis showed that the highest fungal FAME

percentages were associated with the natural vegetation (wilks lambda p<0.001). There

was no significant interaction of sample date and location (wilks lambda p=0.616). The

lowest values of fungal FAME levels were observed in January 2010. Although Fungal

FAME levels differed among depth by location, the seasonal effect was also not

consistent at each of the three depths.


17

Gram-Negative Bacteria

Across all sample times, location was significant (p< 0.001) with the highest

levels of Gram-negative FAME occurring under the bare soil and the lowest values under

the debris dams (Figure 2.2). Gram-negative FAME levels in natural vegetation were

intermediate and similar to the debris dams. Across all sample times there was a

significant (p< 0.001) effect on Gramnegative FAME percentages by depth (0-15 cm) in

all locations (Figures2.2). For 0-15cm depth the highest Gram-negative percentage

occurred October 2010 these values were significantly (p<0.001) different than January

2010; however there were no significant (p= 0.700) differences among any location for

Gram-negative percentages for the other three sample dates.

In the analysis of location by sample date, there were significant differences by

season (between subject effects) with the highest values occurring in October 2010. The

repeated measures analysis showed that the highest Gram-negative percentages were

associated with bare soils (wilks lambda p<0.001) and there was no significant

interaction of sample date and location (wilks lambda p= 0.373). The lowest levels of

Gram-negative FAME were observed in January 2010. Although Gram-negative

percentages differed among depth by location, the seasonal effects were consistent at

each of the three depths (Figure 2.2).

Gram-Positive Bacteria

Across all sample times location was significant (p< 0.001) with the highest

values for Gram-positive percentages occurring under the bare soil and the lowest values


18

under the natural vegetation (Figure 2.2), and the levels associated with the debris dams

were intermediate and similar to levels from the bare soil. Across all sample times there

was not a significant (p= 0.081) effect of depth on Gram-positive FAME levels by depth

for all locations combined. For 15-30-cm depth (Figure 2.2) the highest Gram-positive

percentages occurred in August 2010 (p<0.001). Gram-positive FAME levels were not

significantly (p= 0.261) different among any location for the other three sampled months.

In the analysis of location by sample date there were not significant differences by

season (between subject effects) Figure 2.2 for Gram-positive FAME levels for any

location. The repeated measures analysis also showed that the highest Gram-positive

percentages were associated with the bare soil (wilks lambda < 0.001) and that there was

no significant interaction of sample date and location (wilks lambda p=0.453). The lowest

values of Gram-positive FAME levels were observed in January 2011. Though Gram-

positive percentages differed among depth by location the seasonal effect was also not

consistent for 0-15 cm and 30-45 cm (Figure 2.2 A, C).

Soil Nutrient Dynamics

Extractable NO3-

Across all sample times, location was significant (p<0.001) with the highest

values of extractable nitrate under bare soils reaching levels of 250 parts per million

(Figure 2.3) and the lowest values under the natural vegetation, and values associated

with the debris dams were intermediate and similar to the levels under the natural

vegetation. Across all sample times there was a significant (p<0.001) effect of depth for


19

all locations combined (Figure 2.3). Within sample times there were also significant

effects of depth on levels of extractable NO3-. For the 0-15-cm depth the highest nitrate

levels occurred in October 2010. These values were significantly (p=0.024) higher than

August 2010; however there was a significant (p=0.024) difference among location for

nitrate values where January 2010 differed from August 2010 and January 2011.


season (between subject effects) with the highest values of nitrate in all locations

occurring in January 2010. The repeated measures analysis showed that the highest

nitrate values were associated with the bare soil (wilks lambda p<0.001). There was no

significant interaction of sample date and location (wilks lambda p=0.166). The lowest

values of nitrate were observed August 2010. Though nitrate levels were similar among

depth by location the seasonal effects were consistent at each of the three depths as well.

Ammonium NH4+


values of extractable ammonium under natural vegetation and the lowest values under

bare soil, and the levels associated with the debris dams were intermediate and similar to

the natural vegetation. Across all sample times there was no effect of depth on levels of

ammonium for all locations combined. Within sample times there was also no significant

effect on depths across all locations. For 0-15-cm depth the highest extractable

ammonium levels occurred in August 2010 as these values were significantly (p<0.001)


20

different than any other sampled month. However there were no significant (p=0.144)

differences among any locations for ammonium values for the other three sample dates.


season (between subject effects) with the highest values of ammonium occurring in

August 2010. The repeated measures analysis showed that the highest ammonium values

were associated with natural vegetation (wilks lambda p<0.001). There was no significant

interaction of sample date and location (wilks lambda p=0.065). The lowest values of

ammonium were observed in January 2011. Though extractable ammonium values

differed among depth by location the seasonal effects were consistent at each of the three

depths.

pH


values of pH occurring under the natural vegetation and the lowest values under the bare

soil. Soil pH values under the debris dams were intermediate and similar to the natural

vegetation. Across all sample times there was not a significant (p=0.665) effect on pH

values by depth for all locations combined. However, within sample times there was a

significant effect of depth. For 0-15-cm depth the highest pH values occurred in August

2010. These values were significantly (p<0.001) different than any other sampled month;

however there were no significant (p=0.291) differences among any locations for pH

values for the other three sampled dates.


21


season (between subject effects) with the highest values of pH in all locations occurring

in August 2010. The repeated measures analysis showed that the highest pH values were

associated with the natural vegetation (wilks lambda p<0.001) and that there was no

significant interaction of sample date and location (wilks lambda p=0.479). The lowest

pH values were observed in January 2011.

Phosphorus


values of available phosphorus occurring under the bare soil and the lowest values under

the natural vegetation, and the levels associated with the debris dams were intermediate

and similar to the bare soil. Across all sample times there was a significant (p<0.001)

effect on phosphorus levels by depth for all locations combined. Within sample times

there was also a significant effect of depth on levels of available soil phosphorus. For 0-

15-cm depth the highest phosphorus values occurred in January 2011. These values were

significantly (p<0.001) different than October 2010; however there were no significant

(p=0.754) differences among any locations for phosphorus for the other three sample

dates.


season (between subject effects) with the highest values of phosphorus in all locations


values of available phosphorus were associated with the bare soils (wilks lambda


22

p<0.001) and there was significant interaction of sample date and location (wilks lambda

p=0.022). The lowest values of phosphorus were observed in October 2010. Though

phosphorus levels were similar among depth by location the seasonal effects were

consistent at each of the three depths as well.

Potassium

Across all sample times location was significant (p<0.001) with the highest values

of potassium occurring under bare soil and the lowest values under natural vegetation,

and the values associated with the debris dams were intermediate and similar to the bare

soil. Across all sample times there was a significant (p<0.001) effect on potassium by

depth (0-15 cm) for all locations combined. Within sample times there were significant

effects on depths. For 0-15-cm depth the highest potassium values occurred in January

2010. These values were significantly different than any other sampled month; however,

there was no significant (p=0.795) difference among any location for potassium values

for the other three sample dates.


season (between subject effects) with the highest values of potassium in all locations


potassium values were associated with the bare soil (wilks lambda p<0.001) and there

was no significant interaction of sample date and location (wilks lambda p=0.227). The

lowest values of potassium were observed in October 2010. Although potassium values


23

were similar among depth by location, the seasonal effects were consistent at each of the

three depths as well.

Soil Organic Matter (SOM)


values of SOM occurring under the natural vegetation and the lowest values under the

bare soil. SOM levels for the debris dams were intermediate and similar to the bare soil.

Across all sample times there was a significant (p=0.006) effect on SOM values with

depth (0-15 cm) in all locations. Within sample times there were also significant effects

on depths. For 0-15-cm depth the highest SOM values occurred in October 2010. These

values were significantly different than any other sampled month; however there were no

significant (p=0.593) differences among any locations for SOM values for the other three

sample dates.


season (between subject effects) with the highest values of SOM in all locations

occurring in October 2010. The repeated measures analysis showed that the highest SOM

values were associated with the natural vegetation (wilks lambda p<0.001) and there was

no significant interaction of sample date and location (wilks lamda p=0.242). The lowest

values of SOM were observed in January 2011. Though SOM values were similar among

depth by location the seasonal effects were consistent at each of the three depths as well.


24

Discussion

Results from this one-year study indicate that a debris dam approach does

reestablish important microbial activity on degraded low desert grasslands. After debris

dams were in place for four years, microbial biomass carbon levels had increased

substantially as compared with the bare soils and were even higher than the natural

grassland possibly due to initial inputs of carbon from the hydroseeding and different

vegetation composition. Soil nutrient dynamics were also becoming similar between the

debris dams and natural vegetation areas as important microbial and plant linkages are

reestablished. Importantly, the high levels of extractable NO3

- that characterize the bare

soils in this region of Big Bend National Park with the loss of vegetation (Haralson 2010)

are reduced under the debris dams as nitrogen becomes immobilized in the vegetation

and greater microbial biomass. For arid grasslands, increases in soil nitrogen levels have

been implicated in the conversion of grasslands to shrub lands as nitrogen becomes

concentrated at high levels (Whitford 2002).

The debris dam approach was found to be more effective than other procedures

that have been used at Big Bend to reestablish vegetation, such as developing water

reservoir holes and planting of drought tolerant plants at the North Rosillos location

(Rinas 2007). While the water reservoirs holes could allow for water to get deeper into

the soil, this restoration approach was unable to distribute the water over a large enough

area and did not reduce evaporation of the collected water nor reduce the high soil

temperatures that prevent seedling establishment. The debris dams capture and reduce

soil evaporation as soil moisture levels were higher under the debris dams as compared


25

with the bare soil. The debris dams were designed to capture run-off from adjacent bare

areas, and to increase infiltration. Moreover, shading from the coarse woody debris that is

piled up to a meter high on top of the erosion control blankets reduces soil temperatures,

aiding in moisture retention while reducing temperatures stress on soil microbes (Rinas

2007).

Seasonal patterns of microbial activity under the debris dam after 4 years did

approach levels and follow the trends from the tabosa grasslands that are characteristic of

this low desert in the Chihuahuan Desert. However, for some aspects of microbial

community structure and soil nutrient dynamics the debris dams had higher activity or

levels than found under the natural tabosa grasslands. The high levels of microbial

biomass under the debris dams can reflect the lower soil temperatures and greater

moisture retention provided by the hydroseeding and debris (Rinas 2007). The similarity

in microbial activity with depth under the debris dams and the natural vegetation

underscores the importance of plant cover in regulating soil microbial and nutrient

dynamics and edaphic constraints. Holden and Fierer (2005) showed that MBC is

influenced with depth by plant uptake dynamics and seasonal patterns in soil moisture

and temperature. Belnap et al. (2005) discussed the effect of plant cover type on MBC in

arid systems with the highest values occurring in the vegetated areas.

The debris dam treatment has substantially altered microbial community structure

in this highly disturbed former low-elevation grassland site. Moreover the length of time

for recovery of microbial community structure was quick as these former bare and eroded

sites now mimic that of the natural grasses. In all depths the pattern of high levels of


26

fungi, followed by Gram-negative bacteria, actinomycetes, and finally low levels of

Gram-positive bacteria is seen in both dams and natural grasses. The high levels of fungi

under the vegetated locations are supported by Ibekwe and Kenndy (1999). While

saprophytic fungi were detected in all locations the lowest levels occurred in the bare

soil. For Gram-negative bacteria the highest levels were seen in the bare soil and almost

nonexistent in the other two treatments. This could be a result of the high levels of soil

nitrate as the genus Pseudomonas is an important denitrifier.

Halving et al. (2005) stated that nitrate is one of the most readily available forms

of nitrogen for plants. This can be attributed to its ability to move in the soil solution and

is readily used by plants and soil microbes, which can contribute to the varying levels of

nitrate across season and moisture patterns (Havlin et al. 2005). The high levels of nitrate

in the bare soil can be attributed to the lack of vegetation cover at the levels that occur at

the site (Marrett et al. 1990). The debris dams, which started off as a bare soil, did show

slightly higher levels of extractable nitrate than the natural vegetation at all three depths

but these levels were significantly lower than the levels under bare soil. The higher levels

of extractable ammonium under the natural vegetation followed by levels associated with

the debris dams suggest that critical aspects of organic matter decomposition and

mineralization are occurring that is not associated with the bare soils. The increase of

organic matter and mineralization under the debris dams could account for the levels

occurring in the areas with plant availability compared to bare soils (McLain and Martens

2005). As ammonium levels under the debris dams did not reach levels seen in the natural

vegetation during any portion of the year, the rates of mineralization can be inferred to be


27

lower than for functional low-elevation grasslands. Moreover, this study did not evaluate

the rate of dentrification that could be occurring under the debris dams or the level of

nitrogen fixation that occurs in desert grasslands from cyanobacterial crusts (Whitford

2002).

Soil pH showed how the debris dams are still similar to the bare soil but were

developing characteristics of the soil under the natural vegetation. Moreover nutrient

availability can be influenced by pH, in particular higher pH (Havlin et al. 2005). The

higher pH under the debris dams did not diminish phosphorus availability. The higher

level of phosphorus under the debris dams as compared to natural vegetation suggests

that this nutrient is highly immobilized in the plant and microbial biomass. The higher

levels of SOM at all depths in the natural vegetated sites could account for differences in

phosphorus levels between the natural vegetation and the debris dams (Thompson et al.

2006). As phosphorus is not fixed from the atmosphere, the lower levels in the natural

vegetation suggest that previous erosion could have reduced phosphorus levels and that

arbuscular mycorrhizae will be needed to compensate for the loss of phosphorus.

Patterns of phosphorus and potassium with depth are similar to previous reports (e.g.,

Jobbagy and Jackson 2001).

The microbial and nutrient data indicate that debris dams can be effective in

restoring plant cover to formerly bare regions in the Chihuahuan Desert without the need

for supplemental water. Once plants are reestablished, regardless of species, important

microbial dynamics and associated ecosystem processes are increased above levels that

had been occurring in the bare or disturbed soils. Moreover the trajectory of the microbial


28

and soil nutrients suggests that these vegetated bands are sustainable as critical aspects of

nutrient mineralization coupled with increased microbial activity have been promoted. In

addition, from a practical standpoint the debris dams will be more effective than the

intensive investment of planting drought-tolerant plants that can become invasive and

threaten the naturally occurring plants within Big Bend National Park.


29

References

1. Acosta-Martinez, V., Zobeck, T.M., et al. 2003. Enzyme activities and microbial

community structure in semi-arid agricultural soils. Biol Fertil Soils 38, 216-227

2. Acosta-Martinez, V., Upchurch D.R., et al. 2004. Early impacts of cotton and

peanut cropping systems on selected soil chemical, physical, microbiological and

biochemical properties. Bio Fertil Soils 40, 44-54

3. Alex, B.L., Leavitt, A., Timmer, J., and Sirotnak, J., 2006. Final report on the

sensitive plant project, Big Bend National Park, Texas, Field Seasons: June 2003–

April 2006. Science & Resource Management, Big Bend National Park, Texas.

Unpublished report to the National Biological Infrastructure Inventory, U.S.

Geological Survey, Washington, D.C.

4. Allen, E. B., 1988. The reconstruction of disturbed arid lands. Westview Press,:

9, 267

5. Allen, M. F. 1989. Mycorrhizae and rehabilitation of disturbed arid soils:

processes and practices. Arid soil Research and Rehabilitation 3, 229-241.

6. Belnap, J., Welter, J.R., Grimm, N.B., Barger, N., and Ludwig, J.A., 2005.

Linkages Between Microbial and Hydrologic Processes in Arid and Semiarid

Watersheds. Ecology 86, 298-307


30

7. Fenstermacher, J., Sirotnak, J., Michael P.A., Terry, M., 2006. Annotated vascular

flora of the DEAD HORSE MOUTAINS, Big Bend National Park, Texas, with

notes on local vegetation communities and regional floristic relationships.

National Park Service Big Bend National Park

8. Hadley, N., 1970. Water relations of the desert. Ecology 53, 547-548.

9. Huxman, T.E., Cable, J.M., Ignace, D.D, Eilts, J.A., English, N.B., Weltzin, J,

Williams, D.G., 2002. Response of net ecosystem gas exchange to a simulated

precipitation pulse in a semi-arid grassland: the role of native versus non-naïve

grasses and soil texture, Oecologia 141, 295-30

10. Huxman, T.E., Snyder, K.A., Tissue, D., Leffler, A.J., Ogle, K., Pockman, W.T.,

Sandquist, D.R., Potts, D.L., and Schwinning, S., 2004. Precipitation pulses and

carbon fluxes in semi-arid and arid ecosystems. Oecologia 141, 254-268

11. Huxman, T.E., Smith, M.D., Fay, P.A., Knapp, A.K., Shaw, M.R., Loik, M.E.,

Smith, S.D., Tissue, D.T., Zak, J.C., Weltzin, J.F., Pockman, W.T., Sala, O.E.,

Haddad B.M., Harte, J., Koch, G.W., Schwinning, S., Small, E.E., and Williams,

D.G., 2004. Convergence across biomes to a common rain-use efficiency. Nature

429, 651-654

12. Marino, A. P., 2004. Stream community structure and the role of allochthonous

inputs in quebrada moquina at Montverde

13. Nunan, N., M. A. Morgan, et al. 1998. Ultraviolet absorbance (280 nm) of

compounds released from soil during chloroform fumigation as an estimate of the

microbial biomass. Soil Biol. and Biochem. 30, 1599-1603.


31

14. Orchard, V. A., and Cook, F.J., 2002. Relationship between soil respiration and

soil moisture. Soil Biology and Biochemistry 15, 447-453.

15. Rinas, C., 2007. Grasslands not badlands: Arid grassland restoration in Big Bend

National Park. Nature science 1-10.

16. Vance, E.D., et al., 1987. An extraction method for measuring soil microbial

biomass C. Soil Biol. and Biochem. 19, 703-707

17. Whitford, W.G., 2002. Ecology of Desert Systems. Academic Press, London, UK

18. Weltzin, J.F., Loik, M.E., Schwinnings, S., Williams, D.G., Fay, P.A., Haddad

B.M, Harte. J., Huxman, T.E., Knapp, A.K., Lin, G., Pockman, W.T., Shaw, M.R.

Small, E.E., Smith, M.D., Smith, S.D., Tissue, D.T., and Zak, J.C, 2003.

Assessing the response of terrestrial ecosystems to potential changes in

precipitation. BioScience 53, 941-952


32

Figure 2.1 Seasonal patterns of microbial biomass carbon by depth 0-15(A), 15-30 (B),

and 30-45 cm (C) associated with a restoration effort at a low-elevation degraded tabosa

grassland in the Chihuahuan Desert at Big Bend National Park. Values are means ± SE.

n= 6. Dam = vegetation associated with debris dams, veg = natural tobosa grassland, and

bare = areas with no vegetation cover.

0

1000

2000

3000

4000

5000

Jan-10 Aug Oct Jan-11

µg/

g d

ry w

t o

f so

il

A.

0

1000

2000

3000

4000

5000


µg/

g d

ry w

t o

f so

il

B.

0

1000

2000

3000

4000

5000


µg/

g d

ry w

t o

f so

il

Sample Date

Dam

Veg

Bare

C.


33

Figure 2.2 Seasonal patterns of Fatty acid methyl esters (FAME) by depth 0-15(A), 15-30

(B), and 30-45 cm (C) associated with a restoration effort at a low-elevation degraded

tabosa grassland in the Chihuahuan Desert at Big Bend National Park. Values are means

± SE. n= 6. Dam = vegetation associated with debris dams, veg = natural tobosa

grassland, and bare = areas with no vegetation cover.

0%

20%

40%

60%

80%

100%

Jan

-10

Au

g

Oct

Jan

-11

Jan

-10

Au

g

Oct

Jan

-11

Jan

-10

Au

g

Oct

Jan

-11

Dam Dam Dam Dam Veg Veg Veg Veg Bare Bare Bare Bare

Pe

rce

nta

ge

0%

20%

40%

60%

80%

100%

Jan

-10

Au

g

Oct

Jan

-11

Jan

-10

Au

g

Oct

Jan

-11

Jan

-10

Au

g

Oct

Jan

-11


Pe

rce

nta

ge

0%20%40%60%80%

100%

Jan

-10

Au

g

Oct

Jan

-11

Jan

-10

Au

g

Oct

Jan

-11

Jan

-10

Au

g

Oct

Jan

-11


Pe

rce

nta

ge

Treatment by Date

Actinomycetes

Fungi

Gram -

Gram +

C.

A.

B.


34

Figure 2.3 Seasonal patterns of nitrate (NO3-) by depth 0-15(A), 15-30 (B), and 30-45 cm

(C) associated with a restoration effort at a low-elevation degraded tabosa grassland in

the Chihuahuan Desert at Big Bend National Park. Values are means ± SE. n= 6. Dam

= vegetation associated with debris dams, veg = natural tobosa grassland, and bare =

areas with no vegetation cover.

0

10

20

30

40

50

60


mg/

kg d

ry s

oil

A.

0

50

100

150

200

250

300


mg/

kg d

ry s

oil

B.

0

20

40

60

80

100

120


mg/

kg d

ry s

oil

Sample Date

Dam

Veg

Bare

C.


35

Figure 2.4 Seasonal patterns of ammonium (NH4+) by depth 0-15(A), 15-30 (B), and 30-

45 cm (C) associated with a restoration effort at a low-elevation degraded tabosa




0

0.5

1

1.5

2

2.5

3

3.5


mg/

kg d

ry s

oil

A.

0

0.5

1

1.5

2

2.5

3

3.5


mg/

kg d

ry s

oil

B.

0

0.5

1

1.5

2

2.5

3

3.5


mg/

kg d

ry s

oil

Sample Date

Dam

Veg

Bare

C.


36

Figure 2.5 Seasonal patterns of pH by depth 0-15(A), 15-30 (B), and 30-45 cm (C)

associated with a restoration effort at a low-elevation degraded tabosa grassland in the

Chihuahuan Desert at Big Bend National Park. Values are means ± SE. n= 6. Dam =

vegetation associated with debris dams, veg = natural tobosa grassland, and bare = areas

with no vegetation cover.

7

7.2

7.4

7.6

7.8

8

8.2

8.4

8.6

8.8


pH

A.

7

7.2

7.4

7.6

7.8

8

8.2

8.4

8.6

8.8


pH

B.

77.27.47.67.8

88.28.48.68.8


pH

Sample Date

Dam

Veg

Bare

C.


37

Figure 2.6 Seasonal patterns of available phosphorus by depth 0-15(A), 15-30 (B), and

30-45 cm (C) associated with a restoration effort at a low-elevation degraded tabosa




0

20

40

60

80

100


mg/

kg d

ry s

oil

A.

0

20

40

60

80

100


mg/

kg d

ry s

oil

B.

0

20

40

60

80

100


mg/

kg d

ry s

oil

Sample Date

Dam

Veg

Bare

C.


38

Figure 2.7 Seasonal patterns of potassium by depth 0-15(A), 15-30 (B), and 30-45 cm (C)

associated with a restoration effort at a low-elevation degraded tabosa grassland in the

Chihuahuan Desert at Big Bend National Park. Values are means ± SE. n= 6. Dam =

vegetation associated with debris dams, veg = natural tobosa grassland, and bare = areas

with no vegetation cover.

0

5

10

15

20


mg/

kg d

ry s

oil

A.

0

5

10

15

20


mg/

kg d

ry s

oil

B.

0

5

10

15

20


mg/

kg d

ry s

oil

Sample Date

Dam

Veg

Bare

C.


39

Figure 2.8 Seasonal patterns of Soil Organic Matter (SOM) by depth 0-15(A), 15-30 (B),





0

0.5

1

1.5

2

2.5


Soil

Org

anic

Mat

ter

(%)

A.

0

0.5

1

1.5

2

2.5


Soil

Org

anic

Mat

ter

(%)

B.

0

0.5

1

1.5

2

2.5


Soil

Org

anic

Mat

ter

(%)

Sample Date

Dam

Veg

Bare

C.


40

Chapter 3

Restoring microbial functionality as a prerequisite to successful restoration efforts

of low elevation grassland in the Chihuahuan Desert in Big Bend National Park

Introduction

Cattle grazing and sequent drought during the early 1900’s, prior to the creation

of Big Bend National Park, caused subsequent degradation of once extensive grasslands

across much of the Park (Maxwell 1985). While rangeland improvement was evident at

higher elevations during the 1930’s with an increase in rainfall (Maxwell 1985), much of

the former lowland grasslands did not recover. Once the Park was established in 1945 the

National Park Service in cooperation with the Soil Conservation Service began a

reseeding project (Maxwell 1985) involving pitting of the soil surface, shallow pit

development and the construction of low, net-wire spreader dams across washes and

sheet-wash overflow areas to trap moisture and debris. All of these efforts had limited or

no long-term success (Rinas 2007). Once disturbances occurred within these lowland

grassland sites, changes in soil microbial dynamics quickly follow leading to declines in

soil nutrient cycling and critical plant-microbe interactions. These negative biotic

changes are in addition to the higher soil temperatures and decreased infiltration of

rainfall that follow with the loss of vegetation in desert areas (Whitford 2002).

Recent discussions concerning the need to reduce sediment loading within the Rio

Grande (Rinas 2007) has refocused attention on degraded low-elevation grasslands within

the national park and across the region as a critical component in this problem. Analysis


41

of the landscape by park managers has shown that efforts have to be taken to reestablish

low-elevation grasslands as one countermeasure to decrease sediment loading along the

Rio Grande in the Big Bend region. Initial attempts in early 2000 to reestablish

vegetation on bare sites that contribute to sediment deposition into the Rio Grande

included micro-pits to stop overland flow and to retain and increase rain fall infiltration.

These efforts were unsuccessful as they could not overcome the harsh abiotic conditions

of these sites with little vegetation (Rinas 2007). Current attempts at reestablishing

vegetation cover on bare locations has focused on building debris dams to help “jump

start” plant growth in bare soil sites by providing seedling shade within the debris dams,

to help capture water moving across the site as sheet flow and to provide lower soil

temperatures thereby increasing microbial activity. The debris dams are placed in a

staggered pattern mimicking the natural vegetation structure and contour lines (Rinas

2007). Debris dams have been shown to collect nutrients from bare areas in grasslands

(Marino 2004) and redistribute these resources to vegetated areas. Shading from the

coarse woody debris should also reduce soil temperature and increase soil moisture for

longer periods following rainfall events as these structures will increase water infiltration

rates by decreasing surface flow across the debris dams. With increased soil moisture,

decreased temperature and increased carbon input from established vegetation, microbial

activity and functionality should also aid in the reestablishment of critical ecosystem

process of decomposition and nutrient recycling.

The goal of this investigation is to determine the degree to which the “debris dams”

approach can ameliorate the harsh abiotic conditions associated with bare areas in these


42

low-elevation grassland and restore necessary microbial functions comparable with

microbial functional activity associated with undisturbed low-elevation grasslands in this

region of the Chihuahuan Desert.

Site Description

The current restoration efforts for this project were initiated at North Rosillos site

on the former Harte ranch beginning in May 2006. As restoration managers at Big Bend

National Park were aware that soil temperatures and infiltration issues were a major

concern in establishing vegetation on former low-elevation tobosa grasslands, a new

approach using a combination of erosion control blankets, hydro-seeding and coarse

woody debris obtained from management efforts to modify soil temperatures was

employed (Rinas 2007). Mean elevation at the North Rosillos site is 835 masl with site

aspect of 0.6%. Total annual precipitation for the region has averaged approximately 268

mm since 1982 with mean bimonthly rainfall ranging between 8.8 mm (March) and 41.1

mm (September). Mean daily high temperatures range from 17.59 °C (December) to

36.20 °C (June), while daily lows range from 1.10 °C (January) to 22.32 °C (July). Of

note, surface temperatures recorded at the North Rosillos location rank among the highest

recorded in BBNP. The debris dams established at the North Rosillos location are part of

a larger restoration project on the Harte Ranch where 77.3 hectares (191 acres) are to be

restored to low-elevation grasslands. Additional information on the site can be found in

Chapter 2. Soil at the North Rosillos site is deep silty loam originally classified as


43

Tornillo (fine-silty, mixed, superactive, thermic Fluventic Haplocambids) and now

reclassified as Chalkdraw.

Methods

Microbial Enzyme Analysis

Microbial enzymatic activity was evaluated to determine the degree to which the

“debris dam” approach to grassland restoration in an arid environment could reestablish

important soil microbial processes that are critical for decomposition and nutrient cycling

(Acosta-Martinez et al. 2004) after being in place for four years. The activity of a suite of

microbial exoenzymes was assessed over a year (January 2010 through January 2011)

within the debris dams, in undisturbed tobosa grassland and in association with highly

disturbed non-vegetated soil. Soil samples from each location were collected in January,

August, October 2010 and January 2011. Sampling details are provided in Chapter 2.

Phenol oxidase was used to determine how the microbial community can utilize lignin

using the protocol described by Sinsabaugh et al. (2003). Briefly, 0.5 grams of soil from

each site was mixed with 62.5 ml of acetate buffer and homogenized for 1 minute,

filtered using Whatman 43 filter paper, dispensed in 100-µl aliquots into Costar

microtiter plates and read after 18 hrs at 650 nm. The substrate L-3,4-

dihydroxyphenylalanine (DOPA) produces the color change needed to observe the

reaction. DOPA alone was loaded into the blank wells, and a DOPA and sample soil

solution was placed in the complete-assay wells for analysis.


44

The overall activity of the microbial community within the three different habitats

was evaluated by assaying for β-glucosidase activity. The assay is a good indicator of

cellular degradation and soil quality. Three replicates of 0.5 grams from each sample soil

were used for this enzyme assay (Eivazi and Tabatabai 1988). p-Nitrophenyl-b-D-

glucopyranoside will give an absorbance reading of the reaction at 560nm.

To evaluate soil microbial contributions to phosphorus availability in response to

seasons and debris dam influences, phosphodiesterase activity was measured.

Phosphodiesterase activity determines the degree to which nucleic acids in the soil are

being degraded and were used to monitor the P dynamics in the soil as influenced by

grassland restoration efforts. The phosphodiesterase assays were conducted as described

by Browman and Tabatabai (1978) and (Acosta-Martinez et al. 2003).

Microbial Carbon Use

The BIOLOG procedure (Zak et al. 1994) was used to determine the effects of

debris dams on reestablishment of bacterial functional diversity across season and with

depth compared with bacterial functional diversity from the intact tabosa grassland.

Biolog plates were read at 590 nm after incubation for 72 hrs and 120 hrs using a 10-4

dilution. The evaluation of fungal functional ability on carbon substrates from each of the

three locations was conducted using the FungiLog procedure as described by Sobek and

Zak (2003) at a 120-hr incubation time. Microplates were placed into Ziploc storage bags

to conserve moisture, incubated at 25° C and read at 590 nm at 72 hrs and 120 hrs (Sobek

and Zak 2003). From each microtiter plate from the 120-hr incubation time, substrate


45

activity and substrate richness were obtained. Substrate activity is the sum of the

absorbance values for each plate, and substrate richness is the number of carbon

substrates that are utilized at each sample period and depth (Sobek and Zak 2003).

Nutrient Analysis

Soil nutrient data are presented in Chapter 2.

Data Analysis

Data analysis was conducted as described in Chapter 2 using the microbial carbon

use and enzyme data.

Results

Bacterial Functional Activity

Across all sample times location is significant (p<0.004) with the highest values

of Biolog activity occurring under the natural vegetation and the lowest values under the

bare soil, and the values associated with the debris dams were intermediate and similar to

the natural vegetation. Across all sample times there was not a significant (p=0.065)

effect on Biolog activity with depth for all locations combined. Within sample times there

was a significant effect of depth. For 0-15-cm depth the highest Biolog activity occurred

in October 2010. These values were significantly different than any other sampled month;

however there were no significant difference among any location for Biolog activity for

the other three sampled dates.


46


season (between subject effects) with the highest values of Biolog activity in all locations

occurring in October 2010. The repeated measures analysis showed that the highest

Biolog activity was found associated with the natural vegetation (wilks lambda p<0.001)

and there was a significant interaction of sample date and location (wilks lambda

p=0.004). The lowest values of Biolog Activity were observed in January 2010. Although

Biolog activity differed among depth by location, the seasonal effects were consistent at

each of the three depths.

Fungal Functional Activity


of Fungilog Activity occurring under the debris dams and the lowest values under the

bare soil, and the values associated with natural vegetation were intermediate and similar

to the debris dams. Across all sample times there was not a significant (p=0.859) effect

on Fungilog activity by depth for all locations combined. For 0-15-cm depth the highest

Fungilog activity occurred in August 2010. These values were significantly different than

October 2010; however there were no significant differences among any location for

Fungilog activity for the other three sampled dates.


season (between subject effects) with the highest values of Fungilog activity in all

locations occurring in August 2010. The repeated measures analysis showed that the

highest Fungilog activity was associated with the debris dams (wilks lambda p<0.001)


47

and there was a significant interaction of sample date and location (wilks lambda

p<0.001). The lowest values of Fungilog Activity were observed in October 2010.

Although Fungilog activity differed among depth by location, the seasonal effects were

consistent at each of the three depths.

Phosphodiesterase

Across all sample times location was significant (p<0.001) with the highest values

of phosphodiesterase activity occurring under the natural vegetation and the lowest

values under the bare soil, and the value associated with the debris dams were

intermediate and similar to the bare soil. Across all sample times there was a significant

(p=0.001) effect on phosphodiesterase activity by depth for all locations combined. Also,

within sample times there were significant effects of depths. For the 0-15cm depth, the

highest phosphodiesterase activity occurred in January 2010. These values were

significantly different than any other sampled month; however there were no significant

differences among any location for Fungilog activity for the other three sampled dates.


season (between subject effects) with the highest values of phosphodiesterase activity in

all locations occurring in August 2010. The repeated measures analysis showed that the

highest Fungilog activity was associated with the natural vegetation (wilks lambda p-

0.012) and there was a significant interaction of sample date and location (wilks lambda

p<0.001). The lowest values of phosphodiesterase activity were observed in January


48

2011. Although phosphodiesterase activity differed among depth by location, the

seasonal effects were consistent at each of the three depths.

β-Glucosidase Activity


of β-glucosidase activity occurring under the natural vegetation and the lowest values

under the bare soil, and values associated with the debris dams were intermediate and

similar to the natural vegetation. Across all sample times there was not a significant

(p=0.253) effect on β-glucosidase activity by depth for all locations combined. For 0-15-

cm depth the highest β-glucosidase activity occurred in January 2010. These values were

significantly different than any other sampled month; however there were no significant

differences among any location for β-glucosidase activity for the other three sampled

dates.


season (between subject effects) with the highest values of β-glucosidase activity in all

locations occurring in August 2010. The repeated measures analysis showed that the

highest β-glucosidase activity was associated with the natural vegetation (wilks lambda

p<0.001) and there was a significant interaction of sample date and location (wilks

lambda p<0.001). The lowest values of β-glucosidase Activity were observed in October

2010. Although β-glucosidase activity differed among depth by location the seasonal

effects were consistent at each of the three depths.


49

Phenol Oxidase Activity


values of phenol oxidase activity occurring under the natural vegetation and the lowest

values under the bare soil, and values associated with the debris dams were intermediate

and similar to the natural vegetation. Across all sample times there was not a significant

(p=0.176) affect on phenol oxidase activity by depth for locations combined. For the 0-

15-cm depth the highest phenol oxidase activity occurred in January 2010. These values

were significantly different than any other sampled month; however there were no

significant differences among any location for phenol oxidase activity for the other three

sampled dates.

In the analysis of location by sample date there were significant differences by season

(between subject effects) with the highest values of phenol oxidase activity in all

locations occurring in January 2010. The repeated measures analysis showed that the

highest phenol oxidase activity was found associated with the natural vegetation (wilks

lambda p<0.001) and there was a significant interaction of sample date and location

(wilks lambda p<0.001). The lowest values of phenol oxidase activity were observed in

October 2010.

Discussion

The low levels of bacterial substrate activity associated with the debris dams

suggest that bacterial carbon dynamics have not reestablished to the level expressed

under the natural vegetation. The idea of restoring what took centuries to achieve in a few


50

years is possible as there has been the reestablishment of vegetation in areas that had

none four years ago. As with all restoration efforts recovery will take time (Rinas 2007).

As bacterial substrate activity was not significantly different under the debris dams in

comparison with the bare soils except for October 2010, when the site received

substantial rainfall, the length of time needed to establish the full extent of soil microbial

activity is certainly longer than the five years since initial establishment of the debris

dams. Although FAME levels (Chapter 2) were similar for Gram-positive bacteria under

the debris dams and the natural vegetation, differences in carbon substrate use could

reflect major taxonomic differences or physiological differences.

The debris dams did have an increase in fungal substrate diversity as compared

with the bare soils suggesting that the increase in microbial biomass reflects changes in

fungal abundances. The increase in Soil Organic Matter (SOM) from primary production

over the four years coupled with the carbon input from the coarse woody debris can be a

reason why the debris dams had similar fungal substrate activity levels compared to the

natural vegetation. The pattern in fungal substrate activity by depth under the natural

vegetation and debris dams also reflects the impact of the vegetation on reducing the

nitrate levels that build up under bare soil.

The influences of a few factors such as temperature, increased microbial activity,

and pH, all of which can have an impact on the rate of breaking down carbon sources,

can account for the high levels of bacterial and fungal activity under the natural

vegetation and debris dams (Eivazi and Tabatabai 1990). The debris dams aid in retaining

moisture and increase infiltration helping to prevent further soil erosion and reestablish


51

microbial activity by supplying material for decomposition (Rinas 2007). Fontaine et al.

(2003) showed how the addition of SOM to areas with plant cover and a similar

environment, temperature, pH and microbial activity can have a major impact on soil

enzymes.

The increase in SOM under the debris dams, coupled with lower soil temperatures

and increased soil moisture, could account for changes in soil enzyme activity (Rinas

2007). Importantly, as the vegetation continues to establish and provide carbon input to

the system, critical linkages through decomposition and mineralization are established.

The high levels of phenol oxidase in soils with vegetation emphasizes that the debris dam

approach can reestablish critically important soil microbial activity levels. Excess

nitrogen can have a negative effect on the activity of phenol oxidase and other lignin-

degrading enzymes (Carreiro 2000 and DeForest 2004). The lower levels of phenol

oxidase under the bare soil could be attributed to high soil nitrate levels in addition to

lower levels of SOM.

The addition of nitrogen should have no influence on β-glucosidase activity and

its role in hydrolysis of glycosidic molecules that release glucose for energy for the

microbial flora (Dick 1997). While β-glucosidase levels under the debris dams have not

reached those seen in the natural vegetation, they have increased under the debris dams.

With β-glucosidase not being affected by high nitrogen, it is one of the few soil enzymes

that is not affected by the changes in C:N ratios within the soil (Sinsabaugh et al. 2005).

As β-glucosidase does contribute to the carbon dynamics, it does have influence on other

soil enzymes.


52

References

1. Acosta-Martinez, V., T.M. Zobeck, et al. 2003, Enzyme activities and microbial

community structure in semi-arid agricultural soils. Biol Fertil. Soils 38, 216-227

2. Acosta-Martinez, V., D.R. Upchurch, et al. 2004, Early impacts of cotton and

peanut cropping systems on selected soil chemical, physical, microbiological and

biochemical properties. Bio Fertil. Soils 40, 44-54

3. Browman, M.G., Tabatabai, M.A., 1978. Phophodiesterase activity of soils. Soil

Sci. Am. J. 42, 284-290

4. Eivazi and Tabatabai, 1977 F., Phosphatases in soils, Soil Biol. Biochem. 9, 167–

172

5. Ekenler, M. and Tabatabai, M.A., 2002. β-Glucosaminidase activity of soils:

effect of cropping systems and its relationship to nitrogen mineralization. Biol

Fertil. Soils. 36, 367-376.

6. Maxwell, R.A., 1985. Big Bend History: A History of Big Bend National Park.

Big Bend National History Association, Big Bend National Park, Texas. 88

7. Rinas, C., 2007, Grasslands not badlands: Arid grassland restoration in Big Bend

National Park. Nature science 1-10.

8. Shaw. J.L., and Burns. G. R., 2006, Enzyme activity profiles and soil quality,

Microbiological methods for assessing soil quality 158-170


53

9. Sinsabaugh, R.L., Saiya-Cork, K, Long, T, Osgood, M.P, Neher, D.A., Zak, D.R.,

and Norby, R.J. 2003, Soil microbial activity in a Liquidambar plantation

unresponsive to CO2-driven increases in primary production. Appl. Soil Ecol. 24,

263-271.

10. Sobek, E., and J. Zak. 2003. A microtiter plate method for evaluating soil

fungal functional diversity. Mycologia 95, 590-602.

11. Whitford, W.G., 2002. Ecology of Desert Systems. Academic Press, London, UK

12. Zak, J. C., Willig, M.R., Moorhead, D.L., Wildman, H.G., 1994. Functional

diversity of bacterial communities: a quantitative approach. Soil Biol. Biochem.

26, 1101-1108.


54

Figure 3.1 Seasonal patterns of Biolog GN-2 microtiter plate activity by depth 0-15(A),

15-30 (B), and 30-45 cm (C) associated with a restoration effort at a low-elevation

degraded tabosa grassland in the Chihuahuan Desert at Big Bend National Park. Values

are means ± SE. n= 6. Dam = vegetation associated with debris dams, veg = natural

tobosa grassland, and bare = areas with no vegetation cover.

0

2

4

6

8

10


Ave

rage

SA

0

1

2

3

4

5

6

7

8

9


Ave

rage

SA

0123456789

Bio Bio Bio Bio


Ave

rage

SA

Sample Date

Dam

Veg

Bare

C.


55

Figure 3.2 Seasonal patterns of Fungilog SFN-2 microtiter plate activity by depth 0-

15(A), 15-30 (B), and 30-45 cm (C) associated with a restoration effort at a low-elevation

degraded tabosa grassland in the Chihuahuan Desert at Big Bend National Park. Values

are means ± SE. n= 6. Dam = vegetation associated with debris dams, veg = natural

tobosa grassland, and bare = areas with no vegetation cover.

0

10

20

30

40

50

60

70

80


Ave

rage

SA

0

10

20

30

40

50

60

70

80


Ave

rage

SA

0

20

40

60

80

100


Ave

rage

SA

Sample Date

Dam

Veg

Bare


56

Figure 3.3 Seasonal patterns of phosphodiesterase values by depth 0-15(A), 15-30 (B),





0

100

200

300

400

500

600


Ph

osp

ho

sdie

ste

ras

Act

ivit

ym

gPn

Kg-1

soil

h-1

0

100

200

300

400

500


Ph

osp

ho

sdie

ste

ras

Act

ivit

ym

gPn

Kg-1

soil

h-1

0

100

200

300

400

500

Jan-10 Aug Oct Jan-11Ph

osp

ho

sdie

ste

ras

Act

ivit

ym

gPn

Kg-1

soil

h-1

Sample Date

Dam

Veg

Bare


57

Figure 3.4 Seasonal patterns of β-glucosidase values by depth 0-15(A), 15-30 (B), and





0

100

200

300

400

500

600


β-G

luco

sid

ase

mg

pn

kg-1

soil-1

0

100

200

300

400

500

600

700


β-G

luco

sid

ase

mg

pn

kg-1

soil-1

0

100

200

300

400

500

600


β-G

luco

sid

ase

mg

pn

kg-1

soil-1

Sample Date

Dam

Veg

Bare


58

Figure 3.5 Seasonal patterns of phenol oxidase values by depth 0-15(A), 15-30 (B), and





0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45


Ph

en

ol O

xid

ase

Act

ivit

yµ

mo

l h-1

g-1

0

0.1

0.2

0.3

0.4

0.5

0.6


Ph

en

ol O

xid

ase

Act

ivit

yµ

mo

l h-1

g-1

0

0.1

0.2

0.3

0.4

0.5

0.6


Ph

en

ol O

xid

ase

Act

ivit

yµ

mo

l h-1

g-1

Sample Date

Dam

Veg

Bare

microbial, enzymatic, and soil nutrient dynamics - repositories

Documents