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"Strengthening Fisheries Management in ACP
Countries"
Annex 5 - Guidelines for stock assessment on dams
Fish Stock Assessment in Major Dams in Botswana
Project ref. N° SA-3.2- B15
Region: Southern Africa Country: Botswana
October 2012
Assignment by:
Fish Stock Assessment in Major Dams in Botswana
Project Funded by the European Union A project implemented by Landell Mills pg. 2
Fish Stock Assessment in Major Dams in Botswana
Guidelines for stock assessment on dams
Project ref. N° SA-3.2- B15
Name of individual consultant
Professor Ian Cowx
Contents amendment record
This report has been issued and amended as follows:
Revision Description Date Signed
1 First draft 24/06/2012
2 Report 22/11/2012
Designed and produced at Landell Mills Ltd
Task management & quality assurance by Charlotte Howell
This report has been prepared with the financial support of the European Union. The contents of this
publication are the sole responsibility of Landell Mills and can in no way be taken to reflect the views of the
European Union.
Fish Stock Assessment in Major Dams in Botswana
Project Funded by the European Union A project implemented by Landell Mills pg. 3
Contents
LIST OF ACRONYMS ...................................................................................................................................... 5
1 INTRODUCTION ...................................................................................................................................... 6
2. BACKGROUND INFORMATION ON MAJOR DAMS ....................................................................... 7
3 STOCK ASSESSMENT PROTOCOL FOR MAJOR DAMS AND SMALL WATER BODIES .... 10
3.1 INTRODUCTION ................................................................................................................................... 10
3.2 OVERALL OBJECTIVE .......................................................................................................................... 11
3.3 DAMS SAMPLING STRATEGY ............................................................................................................... 12
4 OPERATING PROCEDURES FOR SAMPLING AND MONITORING GEARS ........................... 14
4.1 INTRODUCTION TO GEARS ................................................................................................................... 14
4.2 OPERATING PROCEDURE FOR GILL NETS ............................................................................................. 15
4.2.1 Objectives and outputs of gillnet surveys............................................................................. 16
4.2.2 Survey planning ................................................................................................................... 17
4.2.3 Sampling design ................................................................................................................... 17
4.2.4 Setting of nets....................................................................................................................... 17
4.2.5 Catch handling and recording ............................................................................................. 18
4.3 OPERATING PROCEDURE FOR SAMPLING ARTISANAL CATCH FOR BIOLOGICAL DATA .......................... 19
4.4 OPERATING PROCEDURE FOR SEINE NETS ........................................................................................... 20
4.5 OPERATING PROCEDURES FOR DATA MANAGEMENT AND ANALYSIS (FOR ALL GEARS) ....................... 20
4.5.1 Data recording .................................................................................................................... 20
4.5.2 Biological data collection and analysis ............................................................................... 21
4.5.3 Species identification ........................................................................................................... 21
4.5.4 Sample sizes ......................................................................................................................... 22
4.5.5 Sampling and preservation of specimens for biological studies .......................................... 22
4.5.6 Biometric data collection ..................................................................................................... 22
4.6 DATA ANALYSIS FOR ALL SPECIES ...................................................................................................... 23
4.6.1 Species composition and relative abundance ...................................................................... 23
4.6.2 Catch rates ........................................................................................................................... 25
4.6.3 Population structure ............................................................................................................ 25
4.6.4 Population parameters ........................................................................................................ 25
4.6.5 Food and feeding habits ...................................................................................................... 27
4.6.6 Reproductive biology ........................................................................................................... 28
4.6.7 Parasitic infection ................................................................................................................ 29
Fish Stock Assessment in Major Dams in Botswana
Project Funded by the European Union A project implemented by Landell Mills pg. 4
REFERENCES ................................................................................................................................................. 30
ANNEX 1 – INTERVIEW FORMS ................................................................................................................ 32
ANNEX 2 DATA RECORDING FORMS ...................................................................................................... 37
Fish Stock Assessment in Major Dams in Botswana
Project Funded by the European Union A project implemented by Landell Mills pg. 5
LIST OF ACRONYMS
ACP African, Caribbean and Pacific Group of States
ADSB Aquaculture for Development Strategy for Botswana
ALCOM Local Community Development Programme
CBNRM Community Based Natural Resources Management
CEDA Citizen Enterprise Development Agency
DWNP Department of Wildlife and National Parks
FAO United Nation Food and Agriculture Organization
FISAT FAO-ICLARM Stock Assessment Tool
FD Fisheries Division
FMPOD Fisheries Management Plan of the Okavango Delta
NDP9 National Development Programme 9
SADC Southern African Development Community
ToR Terms of Reference
TNA Training Needs Assessment
WUC Water Utilities Corporation
Fish Stock Assessment in Major Dams in Botswana
Project Funded by the European Union A project implemented by Landell Mills pg. 6
1 Introduction
The fisheries sector in Botswana is composed of inland fisheries and aquaculture. While the contribution of
the fisheries sector to the national economy is insignificant (0.002% of GDP), the sector is an important
provider of income, employment and food security in some rural areas. The majority of the national fish
production (averaged about 238t per year in the last 10 years based on Food and Agriculture Organization
[FAO] statistics) is from the Okavango aquatic system where conflict between commercial fishers and
recreational fishing promoters is a real concern. Therefore other fishing and fisheries opportunities need to
be developed to relieve the current pressure on the existing fisheries whilst creating employment,
generating income and also providing a diverse, good quality diet for the rural communities and the
population in general.
One possible opportunity is to exploit the fish stocks in dams and reservoirs, but their fishing potential are
not yet properly known. In the 1980s and 1990s an initiative was undertaken through the Aquaculture for
Local Community Development Programme (ALCOM) led by the FAO to conduct preliminary surveys for
assessing the potential for developing fisheries in small water bodies in the southern part of Botswana.
However, the methodologies were unsustainable since there was no appropriate involvement of local
communities and not much was done with regard to capacity building. The aim of this document is to
provide guidelines for carrying out stock assessment in the major dams in the country and to set up a
monitoring system for the FD/research institutes. It should be read in conjunction with the Fisheries
Science Training manual.
Fish Stock Assessment in Major Dams in Botswana
Project Funded by the European Union A project implemented by Landell Mills pg. 7
2. Background information on major dams
Five major dams were originally considered under this programme (see Table 1, Figures 1 & 2), but
following visits to various large dams in Botswana, it was recommended that the newly flooded
Dikgathong dam be included in the assessment and smaller irrigation reservoirs that could potentially be
sources of fish for local communities. The potential yield of the reservoirs has been estimated using the
Morphoedaphic Index environmental correlation method to be betwen120 and 200 kg/ha/yr for the dams
(Table 2), which represents a significant contribution to the supply of fish to the region.
Table 1. Baseline information on large dams in Botswana (source Mmopelwa 2000)
Area
km2
Catchment
area km2
Depth
max m
Depth
mean
(m)
Conductivity
uS
No of
species
Licensed
fishers
Average
CPUE (kg/net)
Gaborone 19 4300 18 6 263 15 4 0.41
Shashe 17 3650 10 3.3 245 19 4 12.32
Letsibogo 18 30 10 297 6 3
Bokaa 6.6 3570 6.5 2.2 248 5 1 6.3
Nnywane 0.55 238 12 4 281 0 Not exploited
Figure 1. The Limpopo catchment with locations of existing and new reservoirs or dams in Botswana portion of the
catchment.
Gaborone
Dam
Bokaa
Dam Nnywane
Dam
Ntimbale Dam
Shashe Dam
Fish Stock Assessment in Major Dams in Botswana
Project Funded by the European Union A project implemented by Landell Mills pg. 8
Table 2. Baseline information (source Mmopelwa 2000) and predicted potential yield from major dams in
Botswana using environmental correlation methods (MEI morphoedaphic index)
Area km2 Conductivity
uS
Depth
mean (m)
MEI MEI Estimated
production (kg/ha/yr)
Gaborone 19 263 6 43.8 126.1
Shashe 17 245 3.3 74.2 159.6
Letsibogo 18 297 10 29.7 106.0
Bokaa 6.6 248 2.2 112.7 192.4
Nnywane 0.55 281 4 70.3 155.8
Figure 2. Google earth images of major dams in Botswana.
Fish Stock Assessment in Major Dams in Botswana
Project Funded by the European Union A project implemented by Landell Mills pg. 9
The key issues from reviewing available information (Figure 3) is inadequate to make an assessment of the
status or potential yield in the short term because there are no longer term data series and it is impossible to
carry out catch assessment surveys because there are insufficient fisheries exploiting the dams to adopt a
classic catch assessment strategy.
0
2000
4000
6000
8000
10000
12000
1996 1997 1998 1999 2000 2001 2002
Fish
yie
ld (k
g)
Year
Gaborone
Shashe
Figure 3. Trends in fisheries production from major dams in Botswana (source Mmopelwa 2000 and FD
Annual report 2002/3).
Consequently there is a need to develop a strategy that uses fisheries independent methods (experimental
approaches) as well a strategy that links to the management objectives of the reservoirs. In this context it
must be recognised that commercial fisheries is only one user amongst several resource users of the dams,
as highlighted in Figure 3.
Fish
stocks
Commercial
licensed
fisheries
Subsistence
fisheries
dried fresh
Recreational
fisheries
Domestic
consumption
Domestic
consumption
Wildlife
Water supply
Irrigation
Water level
management
Illegal
fishing
Cattle
watering
Recreation
and Tourism
Urban
development
Birds + other
piscivores
Dying
in mud
Drinking
Drinking &
Trampling
Defecation &
nutrient loading
Litter, noise
etc
Yacht
club
Aquaculture
Figure 3. Interaction between resource users at major dams in Botswana.
Fish Stock Assessment in Major Dams in Botswana
Project Funded by the European Union A project implemented by Landell Mills pg. 10
3 Stock assessment protocol for major dams and small water
bodies
3.1 Introduction
As elaborated in the previous section, little is known about the status of the fish stocks in the major dams
or community dams and the contribution they could potentially make to meeting demand for fish in
Botswana. There is thus a need to establish a sampling protocol to build knowledge of the status of the fish
stocks and fisheries to underpin management decisions about their sustainable exploitation and
conservation.
Traditionally stock assessment is based on data collected from the fisheries sector directly (fisheries
dependent catch assessment surveys linked to frame surveys) and indirectly by targeted experimental
surveys (fisheries independent surveys). The latter are often linked with limnological, hydrological and
socio-economic information to provide an understanding of the factors driving the fishery production and
yield. The major problem that exists with carrying out fisheries dependent surveys for the major dams and
community dams in Botswana is that there is little if no commercial exploitation (maximum four licensed
fishers on any one reservoir – see Table 1), Consequently alternative stock assessment strategies coupled
with surveys of the fishing communities are required to understand the status of the stocks in the reservoirs,
This calls for applied fisheries biological surveys using standardised techniques. This document offers a
sampling protocol and provides guidelines on the sampling techniques and data analysis required to meet
the requirements for understanding the status of the fish stocks in reservoirs.
The protocol follows a structure approach (Figure 4) to attempt to match the data to management and
policy objectives. The protocols are based on the currently limited fisheries exploitation but focusing of the
policy objectives of optimising the fisheries potential of each system, whether for commercial or
recreational purposes. The protocol also highlights the data analysis procedures but also stresses the
importance of data storage and reporting. Storage of data in an accessible and useable format is currently a
problem in Botswana, as there is no central database or data backup and security system. Indeed it appears
that considerable data are held on individual laptop computers that are not accessible to the FD or on
desktop computers that are poorly maintained. Data should be backed up systematically because there is
evidence that data have been lost because of computer virus problems.
Fish Stock Assessment in Major Dams in Botswana
Project Funded by the European Union A project implemented by Landell Mills pg. 11
General policy decisions
Data collection objectives
Fishery indicators
Data variables
Data collection methods
Analytical
methods
Logistics and
resources
Validation of data
collection programme
Strategy for estimating
variables
Data management
Storage and processing
WHY
Planning and
implementation
System appraisal
and Feedback
WHAT
HOW
Figure 4. Protocol for fish stock assessment in major dams in Botswana
3.2 Overall objective
The overall objectives of this report are to provide biological and ecological information on fish species
present in the dams to support management and conservation strategies. Specifically:
To monitor trends in the biological parameters of fish stocks and examine factors influencing these
trends; and
To predict responses in fish populations to human interventions (fishing and non-fishing) and
natural environmental change.
The key questions associated with these objectives that need to be answered for as many fish species and
fisheries as possible are:
What are the key species in the dam (species richness and diversity)?
What are the key fish population production parameters (growth, recruitment, mortality) and how
are these changing?
What are the key fish condition parameters (e.g. Lm50, sex ratio, fecundity, condition factor, food
and feeding) and how are these changing?
Fish Stock Assessment in Major Dams in Botswana
Project Funded by the European Union A project implemented by Landell Mills pg. 12
What is the status of biodiversity indicators across the dam?
What are the best indicators of population status and environmental change?
3.3 Dams sampling strategy
Following the review of existing information, the data sampling regime tested during the project period and
the stock assessment criteria the following sampling strategy (Table 3) is recommended at minimum for
each reservoir. The programme should be integrated into the work programme of the FD staff at Gaborone
and Mmadinare.
The above recommendations are the minimum monitoring requirements to understand the status of the fish
stocks in the major dams. Where possible, monthly gill net sampling should be undertaken in the early
formative stages of the stock assessment programme. This will give a better indication of variation in catch
rates at different times of the year, understanding of the reproductive cycles of the important fish species
present and composition of the stocks present in terms of abundance and size of structure.
It was originally recommended that seine netting should be carried out at Gaborone, Bokaa and Letsibogo
dams to compliment gill net data, but this was not possible because of problems accessing the water’s edge
because of low water levels and thick mud. It is therefore recommended that seine netting is carried out as
a supplementary activity where possible to get an indication of inshore fish stocks and possibly
recruitment.
In addition, full use should be made of the logbook returns of licensed fishers. Under the new arrangement
for applying for a fishing license from the FD fishers will be obliged to complete daily catch records forms
on monthly basis. These should be compiled and validated on a regular basis and trend analyses in catches
explored.
Fish Stock Assessment in Major Dams in Botswana
Project Funded by the European Union A project implemented by Landell Mills pg. 13
Table 3. Sampling strategy for large dams in Botswana.
Reservoir Gill netting Catch assessment
Gaborone Seasonal (3 times/year) fleet set over night in 3
locations. Dam area, shallow littoral zone and around
rocks or tree stumps
Collect log book data from
WUC
Interview fishers about catches
and trends
Bokaa Seasonal (3 times/year) fleet set over night in 2
locations. Dam area, shallow littoral zone
Collect log book data from
WUC
Nnywane Seasonal (3 times/year) fleet set over night in 2
locations. Dam area, shallow littoral zone
Letsibogo Monthly fleet set over night in 3 locations. Dam area,
shallow littoral zone and around rocks or tree stumps
Collect log book data from
WUC
Interview fishers about catches
and trends
Shashe Seasonal (3 times/year) fleet set over night in 3
locations. Dam area, shallow littoral zone and around
rocks or tree stumps
Collect log book data from
WUC
Interview fishers about catches
and trends
Dikgathong Seasonal (3 times/year) fleet set over night in 3
locations, Important to start immediately to monitor
colonisation process
Ntimbale Seasonal (3 times/year) fleet set over night in 3
locations. Dam area, shallow littoral zone and around
rocks or tree stumps
Community
dams
Select 6-10 dams with varying flood regimes and
stocking regimes and sample once annually - fleet
initially set only once overnight but increase sample
size by duplicating sampling and increasing number
of reservoirs sampled.
The new arrangement is that the fisherfolk apply for a fishing license from the FD and through this
arrangement they will be obliged to complete daily catch records forms on a monthly basis. WUC had no
log books in place hence the new arrangement.
Fish Stock Assessment in Major Dams in Botswana
Project Funded by the European Union A project implemented by Landell Mills pg. 14
4 Operating procedures for sampling and monitoring gears
4.1 Introduction to gears
Inland fisheries stock assessment is traditionally problematic because of the range of species and fishing
methods used, and the influence of external environmental factors that drive the stock structure and
replenishment. Consequently, the methods used should reflect those in the fishery and also provide as
comprehensive coverage of the fishery activities and stock structure to understand the processes that drive
the stock’s dynamics and its current state, ideally in relation to agreed-upon reference points and
performance metrics that, when violated, will initiate some harvest control rule or other management
response. To this end, information about fishing effort and mortality, including illegal fishing is needed,
although in the absence of such information, managers should adopt a precautionary approach until such
information gathering becomes possible.
To obtain the necessary information, a range of methods are available to the FD in Botswana. These
include catch assessment survey methods (based on direct interviews or log book returns to the WUC),
gillnet surveys and seine net surveys, although other opportunities such as electric fishing, traps, larval net
surveys and local knowledge can be explored. The advantages and disadvantages of the various methods
are reviewed in Table 4. The conclusion from the preliminary field assessment exercise was that gill net
surveys and catch assessment surveys –direct interviews and or logbooks (including those collated by
WUC) – were the most appropriate gears, and that other methods should be used to supplement
information if the opportunities arise.
The following sections provide a summary of the standard operating procedures that are recommended for
sampling the dams.
Fish Stock Assessment in Major Dams in Botswana
Project Funded by the European Union A project implemented by Landell Mills pg. 15
Table 4. Advantages and disadvantages of various sampling methods for collecting biological data.
Method Advantages Disadvantages
Artisanal fishery
catches
Species presence and absence data
Size distribution of fish in catch
Limited to species and meshes used by
fishery
Gill nets Species presence and absence
Length based data through length frequency
analysis
Some information of species distribution and
movements
Reproductive state; trophic behaviour;
Selective
Do not give biomass data
Difficult to use in heavy vegetation or
branches
Net shyness
Seine nets Species presence and absence
Length based data
Reproductive state; trophic behaviour;
Limited to beaches with no physical
obstructions such as rocks, tree stumps and
vegetation
Electric fishing Enables fishing in difficult habitats not
accessible to other gears, rocky shores,
submerged woodland and vegetation
Information of species presence and abundance
Can give general biomass estimates
Differential responses of fish
Needs specialised handling
Egg and larval
surveys
Distribution, timing and relative abundance of
eggs and larvae
Taxonomic
classification
Essential to understanding of species presence
and absence and biodiversity trends
Information often not available
4.2 Operating procedure for gill nets
Gillnets are one of the most widely used gears for sampling fish. They are particularly useful for sampling
in relatively shallow waters where other sampling gears are limited. They are the most commonly used
fishing gear on the dams. The low cost of purchase, ready availability, and ease of use means that even the
poorest can enter the fishery.
It is a passive gear, relying on the movements of the fish to enmesh themselves and for this reason fish are
often driven into the net by beating the water as a commercial practice, even though this is illegal.
Gillnetting is a very flexible technique consisting of either setting static nets in a variety of ways that are
often difficult to access for other types of gear, or as drifting nets in the open waters. Gillnets can be
difficult to use in certain circumstances, for example, where there is a large amount of submerged snags,
under floating and submerged vegetation, or in areas of high current. They are, however, liable to
disturbance by crocodiles and hippopotamus and to poaching or theft.
Fish Stock Assessment in Major Dams in Botswana
Project Funded by the European Union A project implemented by Landell Mills pg. 16
Gillnet selectivity is widely used as a management and monitoring tool to limit the sizes of the fish that can
be caught. Because of this, it is important to understand the performance of the gear so that appropriate
advice can be provided for fisheries management.
4.2.1 Objectives and outputs of gillnet surveys
The general objective of gill net surveys is to provide information for the management of the dam fishery
resources. Specifically, however, gillnets can be used to gather a range of information about the fishery and
the fish, principally:
To advise managers on the performance of gillnets to support their management in the fishery
through the application of inter alia mesh size restrictions;
To provide information on the basic parameters of fish species as inputs to dynamic models;
To provide information on biological and ecological characteristics of the various species; and
To provide information on biodiversity status and trends.
Gillnet surveys provide information to:
Determine the composition, relative abundance, population structure and distribution of the fishes;
Determine catch rate, catchability coefficient and selectivity by mesh size of gill nets; information
that can be used for setting regulations on mesh sizes;
Determine and monitor biological, ecological and population parameters (food and feeding habits,
reproductive biology, growth parameters) of the fishes;
Establish breeding seasons and recruitment patterns especially of the major commercial fish
species; information that can be used to determine closed seasons;
Determine and map critical habitats for fish survival and for biodiversity conservation including
breeding and nursery grounds of the fishes; information that can be used to identify protected
areas.
The ultimate aim of an assessment survey is to estimate the absolute abundance of fish in the area
surveyed. This requires information on the affected area and the catching efficiency of the gear. For highly
mobile species like finfish, being caught by a static, passive gear like a gillnet, it is extremely difficult to
estimate the size of the affected area in practice. In most cases, no attempt is made to raise gillnet survey
results to absolute abundance (Hovgård and Lassen (2000)
Catch per Unit Effort (CPUE) of gillnets set under controlled and standardized (to the extent possible)
conditions will, however, provide a valuable relative index of abundance that can be related to the stock
abundance (N) by the proportionality: CPUE = q N, where q is the survey catchability. In fish stock
assessments, the fish size effects are often accounted for by expressing CPUE by age: CPUEage = qage Nage
Fish Stock Assessment in Major Dams in Botswana
Project Funded by the European Union A project implemented by Landell Mills pg. 17
The calculation of qage is a central part of stock assessment modelling, for example in the use of CPUE as
an index of recruitment or adult population size for tuning a catch at age or Virtual Population Analysis
model.
Standardized catch rates can also be derived from the analysis of commercial catch data collected through
the catch assessment survey, although this approach can be problematic, depending on the extent and
reliability of the data. The results obtained from a fishery-independent gillnet survey will provide a
valuable comparison with the results of the analysis of the data from gillnets fished commercially.
Unfortunately, the major dams in Botswana are not heavily exploited (with a 4 maximum of licensed
fishers on any one dam), thus data from this source will probably provide little additional information.
4.2.2 Survey planning
There are essentially two kinds of surveys using gillnets:
Regular monitoring of fish populations employing standard protocols over a long period of time.
Gillnets are particularly useful for this due to their relative ease of use and relatively low cost.
Gillnets can be used across a range of depths and can be used in shallow water where most other
sampling gears cannot be used. Regular monitoring programmes are used to gain information as to
trends in abundance, composition and characteristics of the fish and performance of the gear.
Ad-hoc sampling for specific studies, responding to information needs for specific questions such
as effect of lake level rises or pollution incidents. The methods used during these surveys may vary
from the standard procedures, but any variation must be well documented and justified.
4.2.3 Sampling design
Several meshes of nets are required to monitor and collect data on different elements of the fish
populations (e.g. biodiversity for small fish species, feeding guilds). Each of these will need to be specified
separately, but the basic criteria are as follows:
The gillnets consist of graded fleets of mesh sizes set as follows: 11 panels ranging from 12 mm - 150 mm
(12, 16, 22, 35, 45, 57, 73, 93 115 118, 150) connected at random. Each gillnet will be 2 m deep and 5
metres long and will be mounted at a hanging ratio of 50%
4.2.4 Setting of nets
In the major dams, the standard fleet of mesh sizes will be used on all occasions. The different mesh panels
should be connected prior to deployment from the boat and where possible should be joined so there is no
gap between panels, It is recommended to use quick release cable ties to link the panels.
Surveys should be conducted at minimum once every three months to cover the main seasons of the year
and phases of the moon. Different habitat types including sandy areas, rocky areas, areas with marginal
macrophytes or submerged wood, and different depths should be surveyed where possible. To achieve this
Fish Stock Assessment in Major Dams in Botswana
Project Funded by the European Union A project implemented by Landell Mills pg. 18
it may be necessary to set nets over 2-3 days if insufficient fleets of nets are available. Whatever the
sampling schedule, the nets should be set at the same location on each sampling occasion. To cover these
requirements:
The nets will be set as random graded fleets
Preferably two graded fleets constitute one sampling set is used - one fleet will be set parallel to
the shore and one will be set perpendicular to the shore
The nets will normally be set 30 m from the shore in water of less than 5 m depths to determine the
distribution of fish near-shore. Adjustments to this procedure may be necessary according to local
conditions, but must be recorded and explained, Where only one fleet is available this is preferably
set at an angle to shore to sample fish moving along the shoreline and those moving to deeper
water
The nets will be set in the evening and retrieved the following morning
Where possible, nets should be set at the surface and on the bottom to target different species. The
weights and floats should be adjusted depending on the depth of setting, although it is recognised
the dams are mostly shallow so such operations may not be necessary.
4.2.5 Catch handling and recording
Net retrieval: prior to removing the fish, note the position of fish in the net (top, bottom or mid),
distribution of fish in the net (e.g. clumped, random etc.), the direction of fish (off-shore or onshore for
parallel sets; left or right for perpendicular sets), and whether entangled or gilled, where possible by
species.
Catches from each net should be kept separate and labelled.
When recording catch processes, care should be given to classify such catches by the primary catch
process. The following classification of the mode of capture is provided by Hovgård & Lassen (2000). This
information is particularly important for selectivity experiments (see also Figure 5).
Gilled: The fish is meshed immediately behind the gill cover.
Wedged: The fish is meshed around the body somewhere behind the gill cover. Wedging is hardly
distinguishable from gilling when the maximal girth is found at a position close to the gill cover.
Snagged: The fish is attached to the netting at the head region. This catch process is most common for
species with protruding maxilla or preopercula.
Entangled: The fish is wrapped into the netting, held by pockets of netting or attached to the net by
teeth, fins, spines or other projections. Fish that are already caught by other catch processes may
subsequently be wrapped into the netting while struggling to free themselves.
Fish Stock Assessment in Major Dams in Botswana
Project Funded by the European Union A project implemented by Landell Mills pg. 19
Figure 5. Relation between fish size and catch process. For the smaller fish (top) the girth at the gills
(indicated by the bar) matches the mesh-size and this fish is likely to be gilled. For the larger individual
(bottom) the girth at the head region matches the mesh -size and this fish is therefore potentially snagged
(Hovgård & Lassen 2000).
The following data shall be recorded for each mesh size and each set:
Date and time of capture (season, diurnal light cycle)
Species composition
Total weight of catch
Numbers of specimens per species
Length frequency data (sub-sampling where necessary)
Physical and biological parameters (see procedure on biological sampling).
Note that various selectivity experiments will have to be carried out using length frequency distributions
and catches (numbers and weight) from different mesh sizes if a full assessment of the stock abundance is
to be possible, This will require considerable data of high quality for each species and the full size range of
fish to be caught in the different nets. It is not considered practical in the short term with the small sizes of
nets available and dedicated studies may have to be carried out for this to be feasible.
Data from gill net surveys should be combined with the results of other surveys for biological studies and
formulation of fisheries policies.
4.3 Operating procedure for sampling artisanal catch for biological data
The use of classic catch assessment surveys linked to frame surveys is limited at the various dams because
the number of licensed fisher is small – maximum 4 fishers at any one site (although considerably more
persons fish at the dams illegally and sport fishing is also prevalent at several dams). Nevertheless, use
should be made of data from the commercial (artisanal) and recreational fisheries where possible, It is
recommended the data are collected in several ways.
Fish Stock Assessment in Major Dams in Botswana
Project Funded by the European Union A project implemented by Landell Mills pg. 20
Commercial fishers are required to complete a log of catch under the license agreement. These data
are held by the regional WUC office where the fisher is registered. These data should be collated
and interrogated.
To support assessment of accuracy, the fisheries should be checked periodically and their catches
monitored, These data can be used to audit the reported data and improve reporting, Biological
data on the fishes will also be collected from samples caught by artisanal fisheries during this
assessment.
Undertake semi-structured interviews with the commercial fishers and explore their experiences on
fish catches and trends. Questions relating the catch, trends, species and market value of catch can
be asked as well as what problems the fishers encounter. The same can be done with the
recreational fishers to report their catches and the whether they release the fish or take them home
for consumption, An example of a semi-structure questionnaire is provided in Appendix 1.
The advantage of conducting surveys on artisanal catches is involvement of the local communities and the
opportunity it presents to understand their concerns over the status of the stocks, and interaction with other
stakeholders, to support rational management decisions, Such involvement of fisherfolk in the data
collection may be seen as a first step in preparing the communities to take up their role in a community-
based approach to the management of the fisheries resources.
4.4 Operating procedure for seine nets
Seine nets can be used to collect samples from near-shore. Different mesh sizes of nets can be used for
different age groups e.g. larval fish. A standard net 50 m long and 2 m deep should be set in a rectangle
parallel to the bank from a boat. The net should be fished to the bank in the usual manner for a beach seine,
i.e. the net is hauled from both ends and the lead line held to the bottom at all times during hauling to
ensure it does not rise when pulled. Two sweeps of the net were made at each sample site. The technique is
quantitative because a known area of water is swept by the net.
All captured fishes should be transferred to large water-filled containers prior to analysis. When
excessively large numbers of fishes were caught, a random sub-sample of known percentage of the total
catch should be processed.
4.5 Operating procedures for data management and analysis (for all gears)
4.5.1 Data recording
At each site, each individual will be identified where possible to species and measured for length
(Total length TL, nearest mm) and weight, with the remainder of the fish counted. Data should be
Fish Stock Assessment in Major Dams in Botswana
Project Funded by the European Union A project implemented by Landell Mills pg. 21
recorded on standard data sheets (Annex 2). The following field and identification data will be
recorded with each set of samples:
Survey number
Dam
Locality
GPS coordinates of latitude and longitude
Collector
Collection date
Collection time
Collection method
Capture depth
Water depth
Water temperature
Conductivity
Bottom type
In addition, digital photos were taken of the site at the time of sampling and collated by the FD.
The FD should ensure that all data from surveys of the major dams and community dams are uploaded in
the PASGEAR or DWNP Oracle database for analysis. It is imperative that all data collected are backed up
and held on independent hard drives as computer viruses are a major threat.
4.5.2 Biological data collection and analysis
Biological sampling and analysis of resulting data provides information on fish species present in the
reservoir and their habitats to support management and conservation strategies. There is a need to monitor
trends in the biological parameters of fish stocks and examine factors influencing these trends, and to
predict responses in fish populations to human interventions (fishing and non-fishing) and natural
environmental change.
Biological studies are the fundamental way of understanding the dynamics of the species in the reservoir,
the relationships between species and between species and the environment in which they live. Biological
information can be “absolute” in that it defines the characteristics of the species and “relative” in that
changes in these characteristics are indicators of something happening in the reservoir either man made
(pollution, water level fluctuations, overfishing) or natural (climatic; global warming).
4.5.3 Species identification
These guidance notes assume that the catch has been removed from the sampling gear and sorted into
species. The number and weight of each species is measured in situ. An important aspect of this
assumption is that species are correctly identified. This is relatively straightforward for the main
commercial species (breams and barbels) but the large variety of cichlids and cyprinids are much harder to
distinguish and use of a detailed field guide and input from experienced field scientists will be important
(e.g. Skelton 2001).
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Project Funded by the European Union A project implemented by Landell Mills pg. 22
4.5.4 Sample sizes
Normally, the entire catch should be weighed and counted by species. In exceptional circumstances (e.g.
large catches of small fish), it may be necessary to sub-sample the catch for estimating catch composition
by number, however, it should invariably be possible to get a total weight for each species in the catch. The
catch may be sub-sampled to enable collection of biometric data for different length classes depending on
the size of the catch. For those length classes with a few specimens (the large specimens), all the specimens
will be examined. Where many specimens are caught, about 30 fish will be examined for each 10-cm
length class.
4.5.5 Sampling and preservation of specimens for biological studies
To the extent possible, biometric data on individual specimens are recorded on the spot in the field. In
some cases, whole or parts of fish may be preserved in formalin or frozen and examined in laboratory.
However, note that the weight of the fish will change due to preservation treatment and therefore these fish
cannot be used for collecting length weight data.
Gut contents
Fecundity
Genetics - samples need to be taken using specific sampling and handling techniques depending on
the type of laboratory analyses being undertaken.
4.5.6 Biometric data collection
The data on individual specimens are recorded on the spot in the field but that of small fish that cannot be
weighed in the field are preserved in formalin and examined in laboratory. Biometric data are recorded in
the Biometric Data Sheet Form B (Annex 2). Each specimen is given a Serial Number, The Location, Time
of Capture, gear Types and Size are recorded. The biometric data recorded for each fish specimen include:
Total Length (TL); Standard Length (SL); Weight (WT), Sex, Gonad State, Gonad weight, Stomach
fullness, Weight of food in the stomach (where possible), the types and size of food, and any parasites
present. The total length (TL) is measured from the anterior end of the lower jaw with the mouth closed to
the distal end of the caudal fin while standard length (SL) is measured only up to the last caudal vertebrae.
The fish is opened, sexed and the gonads assigned to a maturity state using the key adopted from Nikolsky
1963 (Table 5). The gonads should be weighed (nearest 0.1 g). The gonads of ripe females should be
preserved in Gilsons fluid/5% formalin for fecundity studies. Gilson’s is preferred because the gonads go
hard in formalin and eggs cannot easily be separated.
Prior to opening, the fish are weighed using either a mechanical, spring or electronic balance depending on
availability. The accuracy and/or sensitivity of the balance should be appropriate to the size of the fish
and/or sample being weighed.
For further examination, the fish is opened using a sharp knife or scalpel along its ventral axis to enable
visual examination of the internal organs (Figure 6). Be careful not to cut the gut or ovary during this initial
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Project Funded by the European Union A project implemented by Landell Mills pg. 23
incision, so that they can be assessed for size and fullness prior to removal, if required. Sex is identified
and the gonads are assigned a maturity state using the keys set out in Table 5.
Figure 6. Position of the gonads and other viscera in the body cavity of a male tilapiine cichlid:
1= liver; 2 = stomach; 3 = gonads; 4 =intestine; 5 = spleen; 6 = swim bladder.
4.6 Data analysis for all species
4.6.1 Species composition and relative abundance
Data should be analysed to investigate fish community structure and relative abundance in each dam.
Catches are used to calculate the relative abundance of each fish species in each sample. The relative
abundance of a species is defined as the percentage of total catches (numbers) comprised by the given
species. The relative abundance (%Ai) of species i is described as:
100%
t
i
i
S
SA
where Si is the sample content (number) composed by species i, and St is the total content of all species
(Hynes, 1950).
For each survey, a Bray-Curtis similarity matrix (Bray & Curtis, 1957) should be calculated and presented
as a dendrogram using hierarchical agglomerative clustering (group average) to investigate similarities in
fish community structure between sites or dams using the Primer software package. The Bray-Curtis
similarity index (Cz) represents the overall similarity between each pair of samples, taking the abundance
of all species into consideration, and is calculated as:
Fish Stock Assessment in Major Dams in Botswana
Project Funded by the European Union A project implemented by Landell Mills pg. 24
)(
2
ba
WCz
where W is the sum of the lesser percent abundance value of each species common to two samples
(including tied values), and a and b are the sums of the percent abundances of species in samples a and b,
respectively. The index ranges from 0 (no species in common) to 1 (identical samples), and a similarity
profile test (SIMPROF) can be used to ascertain whether clusters of sites were significantly similar with
one another (Anderson et al. 2008). SIMPROF is a permutation test of the null hypothesis that a specified
set of samples, which are not a priori divided into groups, do not differ from each other in multivariate
structure. In this process, tests are performed at every node of the completed dendrogram to provide
objective stopping rules and identify whether groups being sub-divided have significant internal structure
(i.e. that samples in each group show evidence of multivariate pattern).
Multi-dimensional scaling (MDS) is used to establish any relationships between species abundance at the
different sites and identify key differences between dams or sites in terms of contribution to the fish fauna.
Nested groupings of similar sites are created using the cluster overlap function within the PRIMER
statistical package. MDS can also be used to identify similarities between catches in the samples.
Various types of measures of diversity are available. The simplest measure of species diversity is species
richness – i.e. the total number of species per unit area or volume (i.e. in a sample). Simpsons Index [D =
1-∑(n/N)2 where n is the number of individuals of a particular species and N is the total number of
individuals] incorporates additional information on the number of individuals of each species. The number
of animals representing each species is divided by the total number of animals in the sample and this value
is then squared. D is 1 minus the total sum of these values for each species.
The Shannon-Wiener (H’) diversity index and Margalef’s index (d), Pielou’s measure of evenness (J) can
be applied to investigate spatial or temporal variations in diversity and evenness of fish catches. H’ and J
are calculated as:
H’ = - ∑pi ln pi ......................................................................................................(4)
d = (S – 1) / log N……………………………………………...……………………….(5)
where S is the species number, N the total number of individuals and pi is the proportion of the total count
arising from the ith species. These indices are different in that the Shannon Weiner index is a measure of
the proportional representation of each species and the Margalef index a measure of the number of species
present for a given number of individuals
Canonical Correspondence Analysis (CCA) can be used to investigate the influence of environmental
variables on the relative abundance and community composition of fish species in each dam (Clarke &
Warwick, 2001; Zuur et al., 2007).
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Project Funded by the European Union A project implemented by Landell Mills pg. 25
4.6.2 Catch rates
Data can be analysed in Excel or PASGEAR to determine
mean catch rates for each taxa;
compare the mean catch rates for the different dams, seasons, zones and depths
compare mean catch rates between different mesh sizes of gill nets.
Appropriate statistical methods (Principal Component Analysis – within the PRIMER software ) can be
used to investigate trends and to relate catch rates to changes in environmental conditions.
4.6.3 Population structure
To compare length distributions for a given species from location to location and from time to time, it is
necessary to calculate the combined distributions for each species on each occasion in each reservoir.
These distributions should be plotted on the same scales, and simply laid next to each other in
chronological order and look for differences in characteristics such as modal lengths and minimum and
maximum lengths. The analysis can be performed in either PASGEAR or Excel. Such an examination can
reveal much about the way fish are growing over time (shown by shifts in modal lengths over time), or any
progressive loss of larger fish or lack of recruitment. This type of visual examination will also show the
potential for analysing the modes in the length distributions to estimate growth parameters. In essence, if
the length distributions do not show reasonably obvious and consistent modes, then an analysis of length
frequency distributions will be highly subjective and is unlikely to be successful. It is also useful to
compare mean lengths of different samples using a standard test such as Student’s t test. Differences
between length distributions can be examined using the Kolmogorov-Smirnov Goodness-of-Fit Test, but
for samples with large numbers of fish this tends to be overly sensitive, indicating differences between
distributions that are not really indicative of genuine differences in biological processes.
Note that before such an analysis of growth and population characteristics can be fully assessed, due
account must be taken of selective of the gear, especially the selectivity of different mesh panels of gill
nets, The data collected from the gillnets should be input into software such as SELECT or PASGEAR to
adjust for selectivity before establish growth parameters using length-based methods.
4.6.4 Population parameters
Population parameters viz, growth coefficient (K), asymptotic length (L), total mortality (Z), fishing
mortality (F), natural mortality (M), exploitation rate(E), growth performance index (’), recruitment
pattern, maximum yield (Lopt), maximum length, length at 50% entry or length at recruitment to the fishery,
are estimated using appropriate computer packages such as PASGEAR or FISAT.
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Growth parameters
The estimation of the growth parameters is based on the Von Bertalanffy Growth equation (VBGF)
expressed by the form: Lt = L (1-exp (-K*(t- to)
)) (Sparre and Venema 1998), where: Lt is the predicted
length at age, L is the asymptotic length, or the mean length the fish of a give stock would reach if they
were to grow indefinitely; K is a growth constant also called “ stress factors” by Pauly (1980) and to is the
age the fish would have been at zero length.
The growth parameters are estimated by length-frequency analysis (Pauly et al. 1984; Sparre and Venema
1998). Various methods of analysis are available, and have been incorporated into sophisticated computer
software packages. For example, the FAO-ICLARM Stock Assessment Tool (FISAT) (Gayanilo et al.
1996) incorporates the Electron Length Frequency Analysis (ELEFAN I and II) method. An alternative is
Length Frequency Distribution Analysis (LFDA) from the FMSP website (www.fmsp.org.uk). This
package includes implementations of ELEFAN, SLCA and PROJMAT. The package used should be
standardized.
Growth performance index (’)
Growth performance is used to compare different populations of the same species. Differences in the index
between different reservoirs may reflect different local conditions and be indicative of different stochastic
events in the reservoirs. The growth performance index is computed according to Pauly and Munro (1984)
formula, ’ = log10 K + 2 log10 L, where K is expressed on an annual basis and L in cm.
Life span
The life span is the approximate maximum (tmax) that fishes of a given population would reach. It is
calculated as the age at 95 % of L, using the parameters of von Bertalanffy growth function as estimated
above tmax = t0 + 3/K.
Mortality
Various methods are available for estimating total mortality Z. The method described by Beverton and Holt
(1956) for estimation of the instantaneous rate of total mortality Z from length frequency samples is one
such method. It assumes that growth is deterministic, non-seasonal and is described by the von Bertalanffy
growth curve. The overall population should be in steady state, with constant mortality over the range of
lengths in the sample, and it is assumed that recruitment is continuous and constant throughout the year.
Under these assumptions, Beverton and Holt (1956) showed that if Lc is the length at which fish are first
fully recruited, and L is the mean length of fish longer than Lc, then an estimate of Z is given by Z =
K[(Linf – L)/(L-Lt)].
The Beverton and Holt estimate of the total mortality rate can be quite reliable if the assumptions behind
the method are met, and if the length at first capture is well-estimated. However, these assumptions are not
always met and in those circumstances estimates of Z can be obtained from the slope of the upper limb of
the length-converted catch curve.
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Suppose the i-th length class in a length frequency distribution includes fish with lengths in the range Li to
Li+1. The relative age of a fish of length L (calculated assuming t0=0) is t = - ln (1 - L/L ) / K, so that the
time taken to grow through length class i is ti = - ln (( L - Li) / (L - Li+1)) and the relative age at the middle
of length class i is ti = - ln (1 - ½(Li + Li+1)/L ) / K. The curve relating ln(Ni /ti ) to it is called the length
converted catch curve, and the slope of the right hand limb of this catch curve is - Z.
Various methods are available for estimating M (see Sparre and Venema 1998).
Length-weight relationships
The length-weight relationship is determined according to W = aLb where, W = weight, L = length, a an
intercept and b the slope.
When satisfactory length-weight relationships have been established for a species, it is not necessary to
include further data unless there is reason to suspect that a significant change has occurred, These data can
also be used to estimate weight of the fish at a given length to avoid weighing individual fish, although
care must be taken to ensure seasonal and sex specific variations are accounted for.
Condition factor
The condition factor (CF) is an index used to quantify the state of well-being of fish, The condition factor
is determined according to CF = W*a/Lb (Le Cren 1951); where W = weight of the fish, L = length a and b
are constants of length weight relationship. This will be calculated for male/female, different reservoirs and
seasons. The condition factor is compared for different sizes of fish, sexes and locations and in time and
space.
4.6.5 Food and feeding habits
In the first instance the fullness of the stomach is assessed. An index of fullness of the stomach is estimated
as follows: Stomach completely empty - 0; ¼ - very little food present, stomach fills to less than a quarter
when pressed from anterior to distal end; ½ - half full, stomach fills to about one half when pressed from
anterior to distal end; ¾ - Stomach nearly full but wall not bulging, food fills to about three quarters when
stomach is pressed from anterior to distal end; and Stomach fully distended with food from anterior to
distal end,
For analysis of diet composition, stomachs with some food are removed from the fish, weighed separately
and then preserved in 5% formalin solution to be examined in the laboratory. The importance of food in the
stomach is estimated according to Hynes (1950) using the index of fullness, A full stomach is given 16
points, ¾ stomach is 8 points, ½ stomach is 4 points, ¼ stomach is 2 points and empty stomach scores zero
point, The importance of a food item in the stomach is estimated by multiplying its percentage contribution
by the points allocated to the index of fullness. Spearman rank correlation or diversity indices such as Bray
Curtis can be used to test for significance of differences in diet within and between years, seasons and
locations. Plot overall percentage contribution per taxa in stacked bar charts according to fish species
season, length class or location.
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Project Funded by the European Union A project implemented by Landell Mills pg. 28
4.6.6 Reproductive biology
Size at first maturity
The size at first maturity is the size at which 50% of the fish are mature. The maturity status of the gonads
is assessed using Nikolski (1963) as described in Table 5. Maturity is estimated for males and females
separately by determining the proportion of mature fish in different length classes of fish (Bagenal &
Braum 1978, Ricker 1971, Nikolsky 1963). The proportions of mature and immature fish are determined
for length classes of 2 cm or less depending on the size of the fish.
Sex ratio
Sex ratio is the proportion of males to females in the population, It is estimated by determining the number
of males to females in different length classes of the fish. It is also useful to determine the proportion of
mature males to mature female in the population and in different dams to get an idea of the reproductive
capacity and the breeding areas and seasons. Use chi square to test for differences.
Table 5. Generic classification of maturity stages
Males Females
I: Immature: Testis appear a pair of long
thin transparent strands running
longitudinally long the dorsal wall of the
body cavity;.
I: Immature: Gonads appear as a pair of short and thin
transparent strands running long the dorsal wall of the
body cavity;
II: Immature - Early developing: Strands
start to thicken; testis are whitish- yellow
II: Immature - Early developing: Ovaries recognized by
small whitish dots (eggs); caudal part of the ovaries more
thickened than rostral part.
III: Developing: Testis are pinkish-
reddish and sideways flattened; often
vascularised.
III: Developing or recovering: Eggs developing inside the
ovaries unequal in size:
IV. Early ripening: Testis thick and
straight, increasing in volume. When cut
and squeezed milt comes out.
IV: Early ripening: Ovary greatly increased in size; eggs
visible but not fully grown; all coloured yellow.
V: Ripe: Testis thick and straight and
copious waterish-white milt comes out
freely when cut or pressed.
V: Ripe: Ovary has reached maximum weight. Eggs large
nearly of uniform size and visible through the tunica.
Application of light pressure to peritoneum leads to
extrusion of eggs from the genital opening.
VI: Late ripe/Spent: Testis thick and often
curled or lobed, white in colour. When
cut some milt comes out.
VI Spent: Eggs of juveniles in the buccal cavity; ovaries
recovering, thin and reddish; eggs unequal in size, often
including a few residual stage V eggs. Ovaries are loose,
flabby, curled or lobed with a few left over eggs. After
spawning the testis and ovary return to stage III.
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Project Funded by the European Union A project implemented by Landell Mills pg. 29
Reproductive state – gonad analysis
In the laboratory, the preserved ovary is washed in tap water and most of the adhering moisture removed
with blotting paper, The ova are then examined under a binocular microscope, Only those ovaries whose
ova have developed to uniform size are used in fecundity estimates, Samples of about 0.1 g are taken from
different parts of the ovary and the numbers of ova in at least five replicate sub-samples are counted under
a binocular microscope. The mean number of ova from the sub-samples is used to estimate the total
number of ova. For small gonads, total counts of eggs in all the ovaries are counted.
Absolute and relative fecundity
The relationship between fecundity and length of the fish described by : F = aLb; where F = fecundity, L =
length, a is a constant and b an exponent. The relationship between fecundity and weight of the fish is
normally linear and is of the form: F = a+bW; where W is weight of the fish.
Relative fecundity is fecundity per unit weight or per unit length of the fish, It is used for comparing
fecundity data in time and space and between dams, The average relative fecundity of the fish is calculated
and the mean compared between the different period and between different habitats. When satisfactory
length-fecundity relationships have been established for a species, it is not necessary to collect and re-
analyse data unless there is reason to suspect that a significant change has occurred. Also, it should be
noted that mouthbrooders such as tilapiines are limited by the capacity of the mouth, thus the ovarian
fecundity is only a potential, and not necessarily actual measure of reproductive output (Welcomme 1967).
Gonad somatic Index (GSI) and Breeding Season
Gonadosomatic Index (GSI) is calculated as the weight of the gonad divided by the weight of the fish and
expressed as a percentage. A plot of the mean gonadosomatic index against time of the year for mature fish
can provide an indication of the breeding season. The breeding season occurs just after peak GSI.
4.6.7 Parasitic infection
Prior to cutting the body wall, the external features should be examined for parasites or lesions and fungal
infestations. On cutting open the body wall, the internal organs should be inspected for presence of internal
parasites. When examining the guts for food contents, they should be inspected for Cestode and
Acanthocephalan parasites. The gill arches should also be removed and inspected for parasites. When
present the parasites will be removed, identified and counted and measured.
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References
Anderson, M.J., Gorley, R.N. & Clarke, K.R. (2008). Permaonova+ for Primer: User Manual/Tutorial.
Primer-e, Plymouth.
Beverton, R.J.H. & Holt, S.J. (1956). A review of methods for estimating mortality rates in exploited fish
populations, with special reference to sources of bias in catch sampling. Rapp. P.-v. Reun.
Commn. int. Explor. Mer 140 (1), pp. 67-83.
Bray, J.R. & Curtis, J.T. (1957). An ordination of the upland forest communities of Southern Wisconsin.
Ecological Monographs 27, 325-349.
Clarke, K.R. & Warwick, R.M. (2001). Change in Marine Communities: an Approach to Statistical
Analysis and Interpretation. Second Edition. PRIMER-E, Plymouth.
Hamley. J.M. (1975). Review of gillnet selectivity. J. Fish. Res. Board Can. 32(11), 1944-1965.
Hilborn, R. & Walters, C.J. (1992). Quantitative fisheries stock assessment. Choice, dynamics and
uncertainty. Chapman and Hall, London, New York. 570 pp.
Hovgård, H. & Lassen, H. (2000). Manual on estimation of selectivity for gillnet and longline gears in
abundance surveys. Fish. Tech. Pap. No. 397. Rome, FAO. 2000. 84 pp.
Le Cren, E.D. (1951). The length-weight relationship and seasonal cycle in gonad weight and condition in
the perch (Perca fluviatilis). J. Anim. Ecol. 20 (2), 201-219.
Mann M.J. (1969). A resume of the evolution of the Tilapia fisheries of Lake Victoria up to the year 1960.
EAFFRO Ann. Rep. 1969: 21-27.
Millar, R.B. & Holst, R. (1997). Estimation of gillnet and hook selectivity. ICES Journal of Marine
Science 54, 471 - 477.
Millar, R.B. (1992). Estimating size selectivity of fishing gear by conditioning total catch. Journal Amer.
Stat. Assoc. 87(420), 962 - 968.
Nikolsky, G.V. (1963). The ecology of fishes. Academic Press, London and New York, 352pp.
Pauly D. & Munro, J.L. (1984). Once more on the comparison of growth in fish and invertebrates.
ICLARM fishbyte 2 (1), 21.
Pauly, D. (1980). On the interrelationships between natural mortality, growth parameters, and mean
environmental temperature in 175 fish stocks. J. Cons. CIEM 39 (2), 175-192.
Regier, H.A. & Robson, D.S. (1966). Selectivity of gillnets, especially to Lake Whitefish. J. Fish. Res. Bd.
Canada 23 (3), 423-454.
Regier, H.A. (1969). Fish parameters useful in estimating gill-net selectivity. Prog. Fish. Cult. 31, 57 – 59.
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Ricker, W.E. (Ed.) (1971). Methods for assessment of fish production in fresh waters. IBP Handbook 3
(2nd edition). International Biological Program. Blackwell Scientific Publications, UK. 348 pp.
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Fisheries Technical Paper. No. 306.1, Rev 2. Rome, FAO, 1998. 407p.
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Fish Stock Assessment in Major Dams in Botswana
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Annex 1 – Interview forms
SEMI STRUCTURED INTERVIEWS FOR BOTSWANA DAMS
Non fisheries stakeholders 1
When was the dam constructed and first filled?
What the full size of the reservoir?
Area Volume
Is the reservoir perennial or season?
What is the catchment area of the reservoir?
What is the land use in the catchment area?
What is the nearest large urban area?
Ownership and management
Who is the owner of the dam?
What is the primary and secondary use of the reservoir?
What management regime exists for the reservoir?
Water resources
Other activities
Fisheries
Is there any integrated resource management / co-management arrangement?
What fisheries exist on the reservoir?
Species
Commercial fishing
How many licences and what is the exploitation
Subsistence fishing licences
How many fishers and what gears
Recreational fishing
Is there any stocking?
Are there any access problems for fishing?
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SEMI STRUCTURED INTERVIEWS FOR BOTSWANA DAMS
Non fisheries stakeholders 2
Issues with reservoir use
Water levels
Water quality
Sedimentation
Poaching
Alien species
Algal blooms/ eutrophication
Conflicts between users
Commercial fisheries v subsistence fisheries v recreational fisheries
Fisheries and wildlife
Options for development
Fisheries
Recreation
Other uses
Who should manage development?
What sources of investment are available?
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SEMI STRUCTURED INTERVIEWS FOR BOTSWANA DAMS
Fisheries stakeholders 1
Demography
Age of fisher Sex
Family dependents
Fishing operations
How long have you been fishing?
How long on this reservoir?
What gears to you use?
Type, number and mesh size
What is your target species?
Full time or Part-time
What is the contribution of fisheries to livelihood [proportion of income]?
What is the contribution of fisheries to food security [proportion of animal protein]?
What other livelihood do you operate?
Income during closed season
Catch
Species caught
Is there seasonal variation?
Describe trends in catches
Seasonal
Long-term annual
Size of catch
Size of fish caught
What is your understanding of fishing regulations?
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SEMI STRUCTURED INTERVIEWS FOR BOTSWANA DAMS
Fisheries stakeholders 2
What are the management arrangements for fisheries?
Explain co-management arrangements if any
Markets
Where do you sell your fish?
Household consumption
Bartering
Local markets
Traders
How much do you consume?
How much do you barter?
What are the issues with fisheries and fishing?
Declining catches
Catch in species composition
Competition and poaching
Other resource users
Water levels
Access
What options for development
Management of fisheries
Open access
Stocking
Species change
Fish Stock Assessment in Major Dams in Botswana
Project Funded by the European Union A project implemented by Landell Mills pg. 36
Aquaculture development
Open up markets
Recreational fishing
Fish Stock Assessment in Major Dams in Botswana
Project Funded by the European Union A project implemented by Landell Mills pg. 37
Annex 2 Data recording forms
Fish Stock Assessment in Major Dams in Botswana
38
Form 1.1 Catch Composition Data Sheet Sheet No
Date ; DAM ; Catch; Habitat Type ;
GPS Ref, __________ Weather [R/D], [WD/CA], [CD/CL]; Lunar Cycle [FQ] [FM] [LQ]; Time [Start] ___ Time [End]_____
Site
De
pth
(m
)
Ge
ar
Type
Op
era
tio
n A
ct
/
Pa
ss
Me
sh S
ize
No
. n
ets
Species / Taxa
No
. o
f fish
Tot. W
t. (g
)
Total / Fork Length of individual specimens (cm)
Weather, R=rainy, D=dry, WD=windy, CA=calm, CD=cloudy, CL=clear; Lunar Cycle, FQ=full moon, FM=full moon, LQ=last quarter.
Fish Stock Assessment in Major Dams in Botswana
39
Form 1.2 Catch Composition Data Sheet Sheet No
Date ; DAM ; Catch; Habitat Type ;
GPS Ref, __________ Weather [R/D], [WD/CA], [CD/CL]; Lunar Cycle [FQ] [FM] [LQ];
Se
rial N
o
Site
Tim
e [
D] [N
]
Ge
ar
Type
Ge
ar
Siz
e
TL/F
L (
cm
)
SL
(cm
)
WT
(g)
Fat
Co
nt.
Se
x
Go
n. S
tate
Go
n. W
t (g
)
Sto
m.
Full
Wt. F
oo
d (
g)
Pre
y 1
Dig
Sta
te
% W
t
Len
gth
(cm
)
Pre
y 2
Dig
Sta
te
% W
t
Len
gth
(cm
)
Pa
rasite
Weather, R=rainy, D=dry, WD=windy, CA=calm, CD=cloundy, CL=clear; Lunar Cycle, FQ=full moon, FM=full moon, LQ=last quarter.
Fish Stock Assessment in Major Dams in Botswana
Project Funded by the European Union A project implemented by Landell Mills pg. 40
Form 1.3. Length Frequency Distribution Form [General] Sheet No
Date ; DAM ; Catch; Habitat Type ;
GPS Ref, __________ Weather [R/D], [WD/CA], [CD/CL]; Lunar Cycle [FQ] [FM] [LQ]; Time [Start] ___ Time [End]_____
TL Frequency
Tot TL Frequency Tot TL Frequency Tot TL Frequency Tot
1 26 51 76
2 27 52 77
3 28 53 78
4 29 54 79
5 30 55 80
6 31 56 81
7 32 57 82
8 33 58 83
9 34 59 84
10 35 60 85
11 36 61 86
12 37 62 87
13 38 63 88
14 39 64 89
15 40 65 90
16 41 66 91
17 42 67 92
18 43 68 93
19 44 69 94
20 45 70 95
21 46 71 96
22 47 72 97
23 48 73 98
24 49 74 99
25 50 75 100
Weather, R=rainy, D=dry, WD=windy, CA=calm, CD=cloudy, CL=clear; Lunar Cycle, FQ=full moon, FM=full moon, LQ=last quarter.