Introduction to the model of the Guinea-Bissau Continental Shelf Ecosystem and an exercise on simulating the effects of

fishing

Patrícia Amorim1, Gregório Duarte2, Miriam Guerra1,

Telmo Morato3 and Kim A. Stobberup1

1: IPIMAR: Instituto de Investigação das Pescas e do Mar (Portugal)

2: CIPA: Centro de Investigação Pesqueira Aplicada (Guiné-Bissau)

3: DOP: Departamento de Oceanografia e Pescas (Portugal)

Presented at the Symposium on “Marine fisheries, ecosystems, and societies in West Africa: half a century of change”, 24-28 June 2002, Dakar, Senegal.

Parameter estimation

Production/BiomassProduction/Biomass (P/B) and Consumption/Biomass (Q/B)

• Based on empirical equations

• Information from fisbase and surveys

• Information from other models

Diet matrix

Fish Groups:Fish Groups: Published data and Fishbase information

Non Fish Groups:Non Fish Groups: Other models with a similar division of functional groups(Opitz, 1993 and Arreguín-Sanchez et al, 1993)

Model construction

Improvements on the “first” preliminary model:

incorporation of more reliable estimates on artisanal catches (D. Thiam, 1993)

- artisanal catches were increased from 17000 to 46000 tons, which is almost a triplication in relation to the first version of the model (mainly mullets and Ethmalosa catches).

biomass estimates for benthos groups were included, giving a better definition of lower trophic level.

These modifications lead to problems in balancing the model, particulary in relation to B and P/B

parameters for demersal fish groups.

31 ecological groups:

- Marine mammals

- Turtles

- Seabirds

- Fish groups (15)

- Squid

- Benthos groups (7)

- Zooplankton

- Primary producers (2)

- Detritus (2)

Guinea Bissau Ecopath Model

Area covered by the model• Extends along Guinea-Bissau shore, including

the Bijagós Archipelago and the continental shelf down to a depth of 200 meters

• Inner waters such as the Geba River were not considered

• The total area considered was 40816 km2.

Reference period• The reference period of the model is from

1990 to 1993, because of the availability of fisheries statistics and biomass estimates from trawl and acoustics surveys.

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CIPA-IPIMAR surveys: trawl stations

Surveys covered the same area

138 stations

Fish groups (including 166 species)

- Biomass estimates

CIPA-IPIMAR trawl surveys

average of 1990 and 1991

Billfish and Marlins*

Tuna*

Pelagic sharks*

Pelagic predatores

Benthic predatores*

Demersal sharks

Groupers/Snappers*

Rays*

Benthos/Fish feeders

Sparids

Flatfish*

Benthic feeders

Small pelagics

Phytoplanktivores

Mullets

* Biomass estimated by model

Estimates of total biomass

Survey 1990 63 000 Ton

Survey 1991 37 000 Ton

Great inter-annual variability of the total catch

Problems found:

Groups poorly sampled by trawl surveys

Published data

Low values of biomass estimated from surveys data were in conflict with high

catch estimates

Biomass estimated by model

• Benthic predatores

• Groupers/Snappers

• Rays

• Flatfish

• Small pelagics

• Pelagic predatores

• Phytoplanktivores

• Mullets

Fish Groups

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CIPA-IPIMAR surveys: Benthic grab samples

91 stations

Benthos groups Cephalopods*

Gastropods/Bivalves

Shrimps*

Crabs

Small crustaceans

Annelids

Equinoderms

- Biomass estimates

Survey 1990 40 t/km2

Survey 1991 59 t/km2

Dominant groups:

Annelids: B=21.7 t/km2

Gastropods/Bivalves: B=16.1 t/km2

Crabs: B= 9.1 t/km2

These groups constitute an important part of the diet of many fish groups

* Biomass estimated by model

Other Groups

Biomass estimates were not available for these groups.

Thus, biomass was estimated by model except for:

- Zooplankton and Phytoplankton (Longhurst, 1983)

Marine mammals

Seabirds

Turtles

Squid

Zooplankton

Phytoplankton

Benthic algae

Discards

Detritus

Fisheries Data

Fisheries in Guinea-Bissau can be divided into three major categories:

Industrial, Artisanal and Tuna.

Guinea Bissau statistics present some problems of coverage and species identification.

Therefore, it was necessary to estimate catch for some groups of species.

Catches by Fleet

Artisanal fishing dominated in terms of total catches

Total catch estimate 46000 ton. (D. Thiam 1993 )

Industrial fishing: Total catch estimate 45000 ton. (CIPA,1996)

- Shrimp trawlers are the most important component of the industrial fleet

Tuna fishery: catches estimated for EEZ of Guinea Bissau based on ICCAT data (1991).

Total catch estimate 4800 ton

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Catch species composition

Artisanal Fishery: mullets and phytoplanktivores (Ethmalosa fimbriata)

Trawl: multispecific fishery

Purse seine: small pelagics

Tuna Fishery: tuna

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Shrimps

Gastropods/Bivalves

Cephalopods

Mullets

Phytoplanktivores

Squid

Small pelagics

Benthic feeders

Flatfish

Sparids

Benthos/Fish feeders

Rays

Groupers/Snappers

Demersal sharks

Benthic predatores

Pelagic predatores

Pelagic sharks

Tuna

Billfish and marlins

Box Diagram

Results

Mixed trophic impacts

Phytoplankton positive impact on almost all groups

Artisanal fishery negative impact on mullets (intensive fishing)

Shrimp and Fish trawl negative impact on Pelagic sharks and Benthic predatores (competition for prey)

Small pelagics/Squid, Marine mammals/Tuna and Marine mammals/Pelagic sharks form opposing groups in competition for main prey

ECOSIM: simulating the effects of fishingPossible scenario of fishing in Guinea Bissau during the

decade of the 90´s.

Combined gears

Combined gears

Principal species affected (Biomass)

- Benthic/fish feeders (+42%)

- Cephalopods (+19%)

- Sparids (+17%)

- Mullets (-19%)

- Rays (-21%)

- Groupers/Snappers (-25%)

- Pelagic sharks (-27%)

End of simulation (End of 1999)

ECOSPACE: spatial representation

Fishing effort by fleet

Fishing rate=1.5

Final considerations:

Better estimates of landings and discards are needed in order to simulate the effect of fishing on the ecosystem.

The re-establisment of the statistical collection system in Guinea Bissau, which is in course, will lead to improved statistics.

Spatial dynamics are known to be important and it would be desirable to develop a spatial model considering the distribution of species by zone and depth.

Regular surveys, covering seasonal changes, would lead to a better understanding of variability in the system.