Assessing the ecosystem impacts of fishing in the South Catalan Sea by developing dynamic...

Assessing the ecosystem impacts of fishing in the South

Catalan Sea by developing dynamic simulations

on fishing effort and target species

Marta Coll, Isabel Palomera, Sergi Tudela and Francesc Sardà

Institut de Ciències del Mar (ICM-CSIC)

Barcelona, Spain

1. The South Catalan Sea ecosystem model (SCMEE 2004)

2. The SCS model calibrated with time series of data

3. Temporal dynamic simulations of 5 fishing scenarios

1. The South Catalan Sea ecosystem model

Mass balance model of trophic interactions

Ecopath with Ecosim software version 5.1

40 functional groups from primary producers to main top predators

Includes trawling, purse seining, long lining and troll bait fisheries

6 fishing harbours: Tarragona to Les Cases d’Alcanar

Area modelled of 4300 km2

50-400 m depth: continental shelf and upper slope

Represents the ecosystem in 1994

Coll et al., accepted to Journal of Marine Systems

Tarragona

Sant Carles de la Ràpita

Ebro River Delta

Les Cases d’Alcanar

Cambrils

L’Ametlla

L’Ampolla

Catala

nSea

Western Mediterranean

Study area

Ecopath mass balance modelling

Basic parameters required per compartment (i): B: BiomassP/B: Production per unit of biomassQ/B: Consumption per unit of biomassEE: Ecotrophic efficiency (production used within the ecosystem)1-EE: Other mortalityDCij: Fraction of (i) in the diet of (j)Y: Catches; E: Net migration; BA: Biomass accumulation

Expressed on an annual basis per unit surface area and WW (t·km-2·yr-1)

www.ecopath.org. Pauly et al., 2000. ICES J. Mar. Sci., 57: 697-706; Christensen and Walters. 2004. Ecol. Model., 172(2-4): 109-139.

j

iiiiijjji )EE(1 i·BP

·BBAEY·DCBQ

·BBP

·B ii

1. The South Catalan Sea model

Production = Predation + Yield + Net Migration + Biomass accumulation + Other mortality

(i) food tedUnassimila(i) nRespiratio(i) Production(i) nConsumptio

Overview of trophic flows and ecosystem structure


Pelagic Demersal Benthic

Large pelagics

Bonito

Zooplankton

Phytoplankton

Discards By catch

Detritus

Suprabenthos

Macrozooplankton

Various small pelagics

Squids

Fin whale

Dolphins

Anchovy

Jellyfish

Sardine

Marine turtles

Seabirds

Adult hake

Benthopelagic fishes Juvenile hakeAudouin

gull

Shrimps

Blue whiting

Demersal fishes(2)

Poor cod

Demersal fishes(3)

Demersal sharks

Anglerfish

Conger eel

Demersal fishes(1)

Flatfishes Mullets Octopuses

Crabs Norway lobster

PolychaetesBenthic

invertebrates

TL

V

IV

III

II

I

TrawlPurse seine

Troll baitLong line

Horse mackerel

Mackerel

Wide and intense fishing impact

Target species, predators and by-catch

Target species, preys and by-catch

Low TLcLow OI

High PPR


1. Trawling fleet-1.0

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2. Purse seine-1.0

-0.5

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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 T P L Tb

3. Longline-1.0

-0.5

0.0

0.5

1.0

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 T P L Tb

4. Troll bait -1.0

-0.5

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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 T P L Tb

Fishing feetLandings

t·km-2·y-1

Discards

t·km-2·y-1 TLc OI %PPR (pp) %PPR (pp+det)

Trawling 2.17 0.23 3.16 0.13 15.95 23.21Purse seining 2.61 0.14 3.01 0.01 13.78 10.43Longlining 0.17 0.01 4.04 0.06 5.47 6.98Troll bait fishery 0.03 0.00 4.16 0.06 1.50 1.36Total 4.98 0.37 3.12 0.10 36.70 41.99

Impact of fishing activities


The mass balance modelling is a good tool to summarize and integrate the available information in a coherent way, identifying critical gaps and describing the ecosystem structure and functioning:

* Quantification of trophic flows, globally or by components * Estimation of TLs, OI, Mortalities: M2, M0, F* Indices related with network and information analysis * Quantification of fishing impact through the MTI, PPR, TLc, GE…

The starting point from where to develop dynamic simulations with the temporal dynamic module Ecosim:

* Assessing the impact of fishing trough time by changing fishing mortalities or

fishing effort by gear (from an initial value of Ecopath)

* Fitting the model to available data, searching for trophic interactions parameters

and environmental anomaly

* Applying optimization routines to include economic and social data

Walters et al. 1997. Rev. Fish Biol. and Fish., 7: 139-172, Christensen and Walters. 2004. Ecol. Model., 172(2-4): 109-139.

In summary…

2. Temporal dynamic modelling and calibration process

Ecosim takes the Ecopath master equation and sets up a series of differential equations of biomass dynamics to calculate changes of each group over time:

dBi/dt: growth rate during time dt of group (i) in terms of its biomassP/Q: net gross efficiencyMOi: other non-predation natural mortalityFi: fishing mortalityIi: immigration rate; ei: emigration rate; Ii-ei·Bi: net migration rate

j

Qji Total consumption by group i

j

Qij Total consumption on group i by all predators j

jj

ei)·BiFi(MOiIiQijQjii·QP

dtdBi


Qs are calculated based on the Foraging arena where Bi is divided into vulnerable and non-vulnerable components and the transfer rate vij determines the flow control: top-down, bottom-up or intermediate

·Sij·Tj/Djaij·Mij·Bjvij·Ti·MijvijSij·Mij/Dj·Bj·Ti·Tj·vij·aij·Bi

Qij


* vij is expressing the rate with which B move between being vulnerable and not vulnerable* Bi is prey biomass; Bj is predator biomass* aij is the effective search rate for i by j* Ti and Tj is relative feeding time for prey and predator * Dj represents effects of handling time as a limit to consumption rate* Sij are seasonal or long term forcing effects* Mij are mediation forcing effects

2. Dynamic modeling and calibration process

Fitting the model to data …

EwE now includes an iterative process to fit the model and calibrate it with empirical data

To explore how changes in functional groups can be attributed * to internal ecosystem factors: feeding interactions and population factors * to external ecosystem factors: fishing activity and environmental forcing

- From an ecosystem model of a past situation

- Using to force the model changes in: * fishing effort, fishing mortality, total mortality

- Using available information on biomasses and catches to modify model variables (mainly vulnerability factor vij) based on the reduction of the goodness of fit measure that it is the summed-squared residuals (SS) of a predicted from an observed value



South Catalan Sea calibrated ecosystem model: from 1978-2003

We developed an ecosystem model representing 1978-1979

We used changes in fishing mortality and nominal fishing effort of trawling, purse seining and longline fishery ► best fit: Cv > TRB > nº boats > days fishing

Absolute and relative biomasses to fit the model

Corrected catches from 1978-2003 to compare results

Change vulnerabilities of most sensible interactions (vij) and prediction of an environmental anomaly


0

5

10

15

20

25

1975 1980 1985 1990 1995 2000 2005

Year

Bio

ma

ss

(t·

km

-2)

Anchovy biomass

Sardine biomass


* Trophic flow control for the most sensible prey-predator interactions: e.g. sardine

* Anomaly function linked with primary production correlated with NAO indexes (annual and winter values) and time series of temperature

* Identification of compensation in recruitment of hake when adult stock is low (commonly defined in many stocks, Myers and Cadigan, 1993)

Predicted and empirical biomasses and catches1

1. Relative and absolute values (y) over time (x); Myers and Cadigan, 1993. Can. J. Fish. Aquat. Sci., 50: 1576-1590.

Fitting summary results SS values Contribution (%)

Total 215.22Fishing 194.48 9.64Vulnerabilities 57.75/95.68 63.53-45.91Environmental annomaly* 98.27/108.67 3.57-11.32Combined 50.07/71.30 76.74-66.87* Probability occuring by chance: 0.001


1. Trophic interactions play a key role in explaining the variability2. Fishing dynamics: adult hake, sardine, anchovy and demersal sharks3. Environmental forcing paying its role in the pelagic compartment

The model predicts important changes in the ecosystem structure and functioning, highlyexploited from 1978 and overexploited in 2003

Functional groups B2003/B1978 C2003/C1978

Jellyfish 1.28Shrimps 0.83 1.44Crabs 0.58 1.02Norway lobster 0.47 0.81Benthic cephalopods 0.60 1.12Benthopelagic cephalopods 0.47 0.84Mullets 0.24 0.57Conger eel 1.54 3.50Anglerfish 0.76 1.32Flatfishes 0.58 1.79Juvenile hake 0.63 1.08Adult hake 0.08 1.65Demersal fishes (1) 0.59 1.27Demersal fishes (2) 1.48 2.99Demersal fishes (3) 1.20 2.22Demersal sharks 0.06 0.15Benthopelagic fishes 4.28 7.30European anchovy 0.72 0.55European pilchard 0.19 0.79Other small pelagic fishes 0.87 1.39Horse mackerel 0.64 1.41Mackerel 0.55 1.28Total 0.78 1.61

* Biomass decrease of top predators like adult hake and demersal sharks

* Biomass decrease of target low TL organism: like small pelagics and juv. hake

* Increase of benthopelagic fishes, jellyfish, conger eel and small demersal fishes: preys and competitors

* Lower biomass of sardine than anchovy in 2003

* Lowest levels of anchovy in the late 1990s and showing modest recovering…

Summary: what seems to have happened in these 26 years?

3. Development of dynamic simulations of fishing options

* Changing the fishing mortality (F) by group or fishing effort by fleet * Assuming constant the predicted environmental anomaly* Making simulations of 20 years from 2003

* Assessing the impact of changing fishing activity * Comparing predicted values of Bf/Bi and Cf/Ci (1978-2003-2023)

5 Simulations

- If nothing changes… - If global fishing effort decreases 20% (≈ one fishing day) - If demersal fishery or purse seine fishing effort decreases 20% - How to recover high levels of hake, anchovy and sardine

3. Dynamic simulations

Simulation 1: If nothing changes….


* Low biomasses of adult hake, sardine

* Decreasing biomass of juv. hake and several demersal species

* High biomasses of benthopelagic fishes, conger eel, other small pelagics (mainly round sardinella), jellyfish, shrimps and horse mackerel

* Anchovy shows a recovery trend

* Biomasses are maintained and catches don’t increase

1978 2003 2023

01

10

3.4

6.717

28

20

1418 1

Functional groups B2023/B1978 C2023/C1978

1 Jellyfish 1.622 Shrimps 1.35 2.343 Crabs 0.66 1.164 Norway lobster 0.56 0.965 Benthic cephalopods 0.86 1.606 Benthopelagic cephalopods 0.82 1.487 Mullets 0.94 2.188 Conger eel 3.25 7.409 Anglerfish 0.68 1.18

10 Flatfishes 0.85 2.6611 Juvenile hake 0.77 1.3412 Adult hake 0.09 2.0213 Demersal fishes (1) 0.93 1.9914 Demersal fishes (2) 1.68 3.4015 Demersal fishes (3) 0.63 1.1716 Demersal sharks 0.00 0.0117 Benthopelagic fishes 8.61 14.7318 European anchovy 1.49 1.1419 European pilchard 0.05 0.2220 Other small pelagic fishes 2.66 4.2521 Horse mackerel 1.11 2.4422 Mackerel 0.74 1.73

Total 1.05 0.89

Simulation 2: If fishing effort is globally reduced by 20%


1978 2023

01

10

3.4

6.717

2

8

20

1418 1

* Some partial recovery on biomass of demersal and pelagic depleted species

* Still high biomasses of benthopelagic fishes, conger eel, other small pelagics, jellyfish

* Increasing catches of anglerfish, conger eel, demersal fishes, sardine, horse mackerel

* Global biomass maintained, non clear recovery of global catches

Functional groups B2023/B1978If nothing changes…

C2023/C1978If nothing changes…

1 Jellyfish 1.62 ►2 Shrimps 1.01 ▼ 1.79 ▼3 Crabs 1.30 ▲ 1.08 ▼4 Norway lobster 0.76 ▲ 0.63 ▼5 Benthic ceph. 1.05 ▲ 1.57 ▼6 Benthop. ceph. 0.80 ▼ 1.16 ▼7 Mullets 0.96 ▲ 1.78 ▼8 Conger eel 4.17 ▲ 7.59 ▲9 Anglerfish 1.09 ▲ 1.50 ▲

10 Flatfishes 0.96 ▲ 2.40 ▼11 Juvenile hake 0.80 ▲ 1.11 ▼12 Adult hake 0.10 ▲ 1.67 ▼13 Demersal fishes (1) 0.97 ▲ 1.66 ▼14 Demersal fishes (2) 1.68 ▲ 2.73 ▼15 Demersal fishes (3) 1.19 ▲ 1.77 ▲16 Demersal sharks 0.03 ▲ 0.06 ▲17 Benthopelagic fishes 8.38 ▼ 11.45 ▼18 European anchovy 1.47 ▼ 0.90 ▼19 European pilchard 0.07 ▲ 0.23 ▲20 Other small pel. fishes 2.41 ▼ 3.09 ▼21 Horse mackerel 1.08 ▼ 1.91 ▲22 Mackerel 0.74 ▲ 1.39 ▼

Total 1.05 ► 0.76 ▼

2003

Simulation 3: If fishing effort is reduced by 20% for purse seine


Simulation 4: If fishing effort is reduced by 20% for the demersal fishery

* Some recovery on biomass of pelagic depleted species


* Increasing catches of sardine and some demersal fishes

* General recovery on biomass of demersal depleted species


* Increasing catches of some demersal fishes



1 Jellyfish 1.61 ▼2 Shrimps 1.02 ▼ 2.33 ▼3 Crabs 1.35 ▲ 1.16 ►4 Norway lobster 0.66 ▲ 0.96 ►5 Benthic cephalopods 0.86 ► 1.60 ►6 Benthop. ceph. 0.84 ▲ 1.52 ▲7 Mullets 0.93 ▼ 2.17 ▼8 Conger eel 3.25 ► 7.38 ▼9 Anglerfish 0.68 ► 1.18 ►

10 Flatfishes 0.85 ► 2.66 ►11 Juvenile hake 0.77 ► 1.33 ▼12 Adult hake 0.09 ► 2.01 ▼13 Demersal fishes (1) 0.93 ► 1.98 ▼14 Demersal fishes (2) 1.67 ▼ 3.37 ▼15 Demersal fishes (3) 0.70 ▲ 1.30 ▲16 Demersal sharks 0.004 ► 0.01 ►17 Benthopelagic fishes 8.55 ▼ 14.24 ▼18 European anchovy 1.51 ▲ 0.92 ▼19 European pilchard 0.07 ▲ 0.24 ▲20 Other small pel. fishes 2.69 ▲ 3.54 ▼21 Horse mackerel 1.10 ▼ 2.28 ▼22 Mackerel 0.74 ► 1.61 ▼

Total 1.05 ► 0.83 ▼



1 Jellyfish 1.63 ▲2 Shrimps 1.01 ▼ 1.79 ▼3 Crabs 1.30 ▲ 1.08 ▼4 Norway lobster 0.76 ▲ 0.63 ▼5 Benthic ceph. 1.06 ▲ 1.58 ▼6 Benthop. ceph. 0.78 ▼ 1.13 ▼7 Mullets 0.96 ▲ 1.78 ▼8 Conger eel 4.18 ▲ 7.60 ▲9 Anglerfish 1.08 ▲ 1.50 ▲

10 Flatfishes 0.96 ▲ 2.40 ▼11 Juvenile hake 0.81 ▲ 1.11 ▼12 Adult hake 0.10 ▲ 1.67 ▼13 Demersal fishes (1) 0.98 ▲ 1.67 ▼14 Demersal fishes (2) 1.69 ▲ 2.75 ▼15 Demersal fishes (3) 1.09 ▲ 1.62 ▲16 Demersal sharks 0.029 ▲ 0.06 ▲17 Benthopelagic fishes 8.43 ▼ 11.87 ▼18 European anchovy 1.45 ▼ 1.11 ▼19 European pilchard 0.05 ► 0.22 ►20 Other small pel. fishes 2.41 ▼ 3.77 ▼21 Horse mackerel 1.09 ▼ 2.07 ▼22 Mackerel 0.75 ▲ 1.51 ▼

Total 1.04 ▼ 0.82 ▼

Simulation 5: how to recover high levels of hake, anchovy and sardine


If we reduce the fishing rate of adult hake to F/Z <0.81; eliminating fishing on juv. hake < 25cm (immature ones) to 80%, reducing F/Z for sardine <0.52 and maintaining F/Z for anchovy <0.5

0

1

2.7

5.3

8

1978 2003 2023

172

11 19 20 12

* Recovery of biomasses of adult and juv. hake, sardine and other benthic and pelagic species

* Lower levels for anchovy comparing 1978 but higher ones respect 2003 (25%)

* Lower biomasses of benthopelagic fishes, jellyfish, conger and other pelagic fishes

* Higher levels of caches for target demersal and pelagic species

* Global increase of biomasses and catches

Functional groups B2023/B1978In nothing changes…

B2023/B2003 C2023/C1978In nothing changes…

C2023/C2003

1 Jellyfish 1.00 ▼▼ 0.782 Shrimps 1.11 ▼ 1.41 2.43 ▲ 1.693 Crabs 1.41 ▲ 1.47 1.49 ▲ 1.474 Norway lobster 0.84 ▲ 1.67 1.35 ▲ 1.675 Benthic cephalopods 0.94 ▲ 1.57 1.76 ▲ 1.576 Benthop. cephal. 1.35 ▲ 2.89 2.43 ▲ 2.897 Mullets 1.01 ▲ 4.14 2.35 ▲ 4.148 Conger eel 0.10 ▼▼ 0.07 0.24 ▼ 0.079 Anglerfish 0.47 ▼ 0.62 0.82 ▼ 0.62

10 Flatfishes 0.73 ▼ 1.27 2.28 ▼ 1.2711 Juvenile hake 1.40 ▲▲ 2.24 0.48 ▼ 0.4412 Adult hake 1.15 ▲▲ 15.13 2.01 ▲ 1.2213 Demersal fishes (1) 0.91 ▼ 1.53 1.94 ▼ 1.5314 Demersal fishes (2) 1.08 ▼ 0.73 2.20 ▼ 0.7315 Demersal fishes (3) 0.65 ▲ 0.54 1.20 ▲ 0.5416 Demersal sharks 0.001 ▲ 0.01 0.002 ▼ 0.0117 Benthopelagic fishes 2.37 ▼▼ 0.55 4.04 ▼ 0.5518 European anchovy 0.90 ▼ 1.25 0.69 ▼ 1.2519 European pilchard 1.65 ▲▲ 8.67 1.31 ▲ 1.6520 Other small pelagic fishes 1.38 ▼ 1.58 2.20 ▼ 1.5821 Horse mackerel 0.82 ▼ 1.28 1.81 ▼ 1.2822 Mackerel 0.88 ▲ 1.61 2.06 ▲ 1.61

Total 1.10 ▲ 1.41 1.24 ▲ 1.60

1. As recommended for ground fished stocks: Mertz and Myersl, 1998. Can. J. Fish. Aquat. Sci., 55: 478-484; 2. As recommended for small pelagic fishes: Patterson. 1992. Rev. Fish Biol. Fish, 2: 321-338.

Conclusions

Simulation examples are showing interesting results:

* Target species are driven by fishing activity and we need to lower fishing impact to recover them, probably preventing as well the proliferation of other species (jellyfishes and benthopelagic fishes: trophic cascades)

* A reduction of 20% of effort would imply some improvement of the ecosystem respect the actual state

* To recover the system we need an intervention in both pelagic and demersal fisheries to increase top predator biomasses and relax the impact on target small pelagic fishes, while increasing the predation on preys of top predators and competitors of low TL target species

Ecological modeling in the Mediterranean context is shown as an appropriated tool to investigate fishing management options

To answer important ecological questions, to pose new ones and to assess the ecosystem effects of fishing

This is especially relevant in the Mediterranean because it take into account the multispecific nature of ecosystem and fisheries: essential under the EAF

Conclusions

The ecosystem modeling approach is a tool to improve the strategic nature of the management: where we are, where we are going?

Complementing the tactical management from stock assessment and evaluation tools

This can contribute to evolve the reactive management of fishing resources into a more adaptive and strategic one, in line with recommendations of GFCM

Ecological modeling is nourished by conventional assessment methods, information that we already have and we organize into an ecosystem context

We need: to continue collecting this essential information to increase it: some critical gaps (diet of key specie, ontogeny) to collect new data to monitor model predictions (validate or refuse)

Are benthopelagic fishes increasing in Mediterranean exploited ecosystems?

Models are always under construction in the sense that when new data or new ideas are available, they can be improved

Conclusions

1. Libralato et al., Submitted to Journal of Applied Ecology; 2. Granzotto et al., 2004. Chemistry and Ecology, 20(1): 435-449; 3. Walters et al., 1999. Ecosystems, 2: 539-554.

EwE Ecological modeling shows an essential improvement with the ability to fit models to data:

* From calibrated models we can derive ecosystem indicators like L index (presented by S. Libralato and collaborators1)

* They can be used to derive classical indicators as fishing mortalities (F), predator mortalities (M2), maximum sustainable catches (MSY) from an ecosystem context

* They can also include socioeconomic data to assess the optimum equilibrium of different fishing options taking into account social, economic and ecological criteria (example in Venice lagoon 2)

* They are the baseline from where to develop spatial simulations3

We suggest to the Sub-Committee of Stock Assessment:To foment the ecosystem modeling application in the Mediterranean

by implementing EwE and other toolsby implementing them to different scales

We are also working in the Adriatic Sea (1970s to 2000s): This will enable us to have another example to compare observed patterns and different model scales

THANKS!

Assessing the ecosystem impacts of fishing in the South Catalan Sea by developing dynamic...

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