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"Strengthening Fisheries Management in ACP

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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:


Project Funded by the European Union A project implemented by Landell Mills pg. 2


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.



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



REFERENCES ................................................................................................................................................. 30

ANNEX 1 – INTERVIEW FORMS ................................................................................................................ 32

ANNEX 2 DATA RECORDING FORMS ...................................................................................................... 37



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



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.



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



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.



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.



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.



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?



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.



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


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


WUC


and trends

Shashe Seasonal (3 times/year) fleet set over night in 3




WUC


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



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.



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.



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.



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



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



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.



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.



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



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).



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



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:



)(

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).



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.



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.



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.



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.



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.



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.



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.

Sparre, P. & Venema, S.C. (1998). Introduction to tropical fish stock assessment. Part 1. Manual. FAO

Fisheries Technical Paper. No. 306.1, Rev 2. Rome, FAO, 1998. 407p.

Skelton, P.H. (2001). A Complete Guide to the Freshwater Fishes of Southern Africa. Struik Publishers.

Welcomme, R.L. (1967). The relationship between fecundity and fertility in the mouth-brooding cichlid

fish Tilapia leucosticta. J.Zool.Lond. 151, 453-468.

Zuur, A.F., Leno, E.N. & Smith, G.M. (2007). Analysing Ecological Data. Springer, New York.



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?




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?




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?




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



Aquaculture development

Open up markets

Recreational fishing



Annex 2 Data recording forms


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.


39

Form 1.2 Catch Composition Data Sheet Sheet No


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.



Form 1.3. Length Frequency Distribution Form [General] Sheet No


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.

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