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ICES CM 2008/O:22

IndiSeas: A Global Comparison of ecosystem indicators across fished marine

ecosystems

Alida Bundy1, Yunne-Jai Shin2, Lynne Shannon3, Marie-Joëlle Rochet4, Marta Coll5,

Philippe Cury2.

Abstract

There has been a strong global move towards the Ecosystem Approach to Fisheries (EAF).

To make progress towards implementing the EAF, carefully selected and appropriate

indicators are required to translate ecosystem impacts and changes into management and

policy measures that can be assessed for their effectiveness. The scientific community

grappling with the EAF is challenged to provide a generic set of synthetic indicators to

accurately reflect the effects of fisheries on marine ecosystems, to facilitate effective

communication of these effects and to promote sound management practices. Building on

the work of SCOR/IOC Working Group on “Quantitative Ecosystem Indicators” (2004), a

working group was established under the auspices of the EUROCEANS European NoE

(Network of Excellence), to look at “EAF Indicators: a comparative approach across

ecosystems”. A suite of ecosystem indicators were chosen after careful consideration of

several criteria, including ecological meaning, availability and cost of data, sensitivity to

fishing pressure and comprehension to the general public. These indicators were assembled

for 22 fished ecosystems, representing tropical, temperate, high latitude and upwelling

systems. The results of comparative analyses were synthesized to inform the public and

fisheries managers of relative states and recent trends in the world’s fished marine

ecosystems. Using the comparative approach, a web-based “dashboard” comprised of these

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ecosystem indicators has been developed, reporting results of various statistical and

analytical techniques employed to evaluate the exploitation status of marine ecosystems in a

comparative framework and to guide fisheries management in each ecosystem.

Key words: ecosystem indicators, comparative trends, ecosystem approach to fisheries

Contact author: Alida Bundy, Fisheries and Oceans, Canada, Bedford Institute of Oceanography, PO Box 1006, Dartmouth, NS B2Y 4A2, Canada. Tel: + 902 426 8353, Fax:+902 426 1506; Email: [email protected]

2, 6 - Institut de Recherche pour le Développement (IRD), CRHMT-Thetis Avenue Jean Monnet, BP 171, 34203 Sète Cedex, France 3 - Marine and Costal Management (MCM), Department of Environmental Affairs and Tourism , Private Bag X2, Rogge Bay, 8012, South Africa 4 Dalhousie University, Biology Department, 1355 Oxford Street, Halifax, Nova Scotia B3H4J1, Canada. 5 Département EMH (Ecologie et Modèles pour l'Halieutique), IFREMER, B.P. 21105, 44311 Nantes Cedex 03, France.

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mailto:[email protected]


Introduction It has long been recognized that single-species based fisheries management approaches,

although often all that is available, practical or achievable, have their limitations and

should be informed by ecosystem-based approaches that place the species being managed

in the broader context of the ecosystem (environmental, ecological and socio-economic).

Since the FAO Reykjavik Declaration of 2001 and the World Summit on Sustainable

Development held in Johannesburg in 2002, there has been a strong move worldwide

towards the Ecosystem Approach to Fisheries (EAF). Nations are required to develop and

start implementing an EAF for reconciling conservation and exploitation objectives by the

year 2010. They are further required to restore depleted fish stocks by 2015. To fulfill

these objectives, a strategy based on innovative and integrated science is urgently needed

to translate the complexity of marine ecosystems into comprehensible signals and to

propose operational management frameworks (e.g. FAO 2003, Link 2005). The scientific

community is therefore challenged to provide a generic set of integrated ecological

indicators to accurately reflect the effects of fisheries on marine ecosystems, to facilitate

effective communication of these effects and to promote sound management practices.

To further the work achieved that was completed in 2004 by the SCOR/IOC Working

Group on “Quantitative Ecosystem Indicators”, the IndiSeas working group was

established, under the auspices of the EUROCEANS European Network of Excellence, to

look at “EAF Indicators : a comparative approach across ecosystems”. The goal of this

working group is to gather and share indicators expertise across marine ecosystems and

member institutions, in order to (i) develop a set of synthetic ecological indicators, (ii)

build a generic dashboard using a common set of interpretation and visualisation methods,

(iii) evaluate the exploitation status of marine ecosystems in a comparative framework.

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In this paper, we describe the process through which the working group set about

achieving these goals, including (i) development of a common protocol for interpreting,

representing and communicating a carefully selected suite of indicators for a wide range of

ecosystems; (ii) graphical synthesis of the suite of indicators in order to present a simple

but adequate diagnosis of the status of exploited marine ecosystems (iii) the adoption of

common methods within the experts group for standardising indicators, interpreting

combined sets of indicators, interpreting the trends in indicators over time, and

transforming quantitative information into semi-quantitative and visual information. The

main deliverable of this Working Group is the creation of a website to inform fisheries

scientists, managers, policy makers and the public at large of the state of world’s marine

ecosystems as a result of fisheries exploitation.

Why a comparative approach across world marine ecosystems?

Assessing the status of fish stocks can be difficult and full of uncertainty; the task of

assessing an ecosystem is far more challenging since we often know little of their pristine

states, there are no, or few, reference points at an ecosystem level, ecosystems are non-

linear systems which can be difficult to predict, we are still learning how whole

ecosystems respond to the effects of fishing in combination with environmental effects,

and the status of an ecosystem is elaborated on a highly multi-criteria basis.

One way to help facilitate ecosystem assessments and the implementation of EAF is

through comparative ecosystem studies, either focusing on single species (e.g., Brander

1994, 1995), whole ecosystems (e.g., Shannon Jarre-Teichmann 1999; Hunt and Megrey,

2005; Moloney et al., 2005;.Bundy et al in press) or ecosystem indicators. Comparisons of

similar ecosystems can serve as ad hoc replicates, mimicking an experimental set-up where

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common, unique and fundamental features, as well as important responses to fishing, can

be explored. With the difficulty in establishing baseline levels and reference points for

most ecosystem indicators, the comparative approach across ecosystems will at the very

least provide a range of reference values (min, max) against which each ecosystem could

be assessed. These comparative analyses allow the opportunity for taking a broader

ecosystem perspective, help to avoid repeating the same fisheries management mistakes as

may have been the case in some ecosystems in the set considered (i.e. provide early

warning signals), and permit the ability to draw generalizations important to successful

implementation of EAF.

The comparative approach will also help in selecting robust ecological indicators that

would be meaningful and measurable over a set of diverse and contrasted situations, and in

specifying their conditions of use. The comparative approach between ecosystems and its

communication to the public at large is also aimed at creating an incentive for politics to

considering their management options with full responsibility with regard to the ecological

quality of marine world ecosystems.

A selection of indicators for evaluating and communicating ecosystem status

The abundance of ecosystem indicators under consideration has increased substantially

over the last decade (see contributions in Cury and Christensen 2005). The challenge of the

IndiSeas Working Group was not to develop new indicators, but rather to use specific

selection critieria to choose the most representative and practically achievable and

meaningful set of indicators from existing ones.

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Selection criteria

As noted in the introduction, the intent of IndiSeas was to build on the work already

achieved by the SCOR/IOC Working Group on “Quantitative Ecosystem Indicators”, and

specifically on the results of Rice and Rochet (2005) who outline some specific practical

criteria for the selection of ecosystem indicators which were adopted by the SCOR-IOC

Working Group:

• ecological significance (i.e. are the underlying processes essential to the

understanding of the functioning and the structure of marine and aquatic

ecosystems?)

• measurability: availability of the data required for calculating the indicators

• sensitivity to fishing pressure

• awareness of the general public

The last of these criteria was of particular importance to the aims of the IndiSeas WG, that

is the awareness of the general public concerning the meaning (what information is

communicated) of each indicator. For example, among potential size-based indicators, we

preferred to select mean length rather than the slope of the size spectrum since this would

be more difficult to communicate to the general public.

In addition to these practical selection criteria, the indicators were selected to address four

specific management objectives: Conservation of Biodiversity (CB), ecosystem Stability

and Resistance to perturbations (SR), Ecosystem structure and Functioning (EF) and

Resource Potential (RP).

The most constraining criterion in the comparative framework was that of the availability

of the data (from observations or models). The indicators needed to be comparable across

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ecosystems and not too costly (the list of indicators must be concise), so as to be easily

estimated and gathered for each ecosystem considered. In some ecosystems, the data

required for calculating the selected indicators have not been collected yet or are not

readily available. However, the working group found that it is important in those cases, to

set up sampling or modelling programs to fill the gaps. Therefore, the minimal list is not

strictly the lowest common denominator of all the ecosystems represented within the

group.

Ecological categories of indicators

In the review of existing ecosystem indicators, several categories of indicators were

distinguished (Cury and Christensen 2005): size-based, species-based, and trophodynamic

indicators. The eight indicators outlined in Table 1 were selected based on the above

criteria, and are proposed as a minimum set of indicators for diagnosing the status of an

ecosystem. Six of the indicators were used to measure the state (S) of the ecosystem and

six were used to measure trends (T) over time. Data for the indictors are derived primarily

from fisheries independent surveys and commercial fisheries data, with auxiliary

information where indicated.

In addition to the full indicator name, a shorter “headline label” was attributed to each of

the indicators (Table 1) to make them more readily comprehensible (a sound bite).

Furthermore, the indicators are all formulated positively so that a low value of an indicator

means a high impact of fishing and a high value a low impact of fishing. Similarly, an

increase of the indicator means an improving state, whereas a decrease means a

deteriorating state.

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The indicators

Total biomass of surveyed species - total biomass is a conservative property of an

ecosystem; as species are fished and their biomass reduced, other species increase

in abundance and “replace” these species in the foodweb. With the removal of top

predators lower trophic levels can be expected to increase. Thus changes in total

biomass can be reflective of changes in ecosystem productivity. “Biomass” is used

here as a measure of “resource potential (Table 2). “Biomass” was not used to

characterise the ecosystem state since survey data does not provide absolute

estimates of biomass and thus is not comparable between species or ecosystems

(due to differences in species catchability and surveys). Instead, “biomass” was

used to compare biomass trends over time.

1/(landings /biomass) measures the level of exploitation or total fishing pressure on the

ecosystem. This indicator varies in the opposite direction to the other indicators in

the selected suite, as it increases when fishing pressure increases. Thus, it expressed

here as the “inverse fishing pressure”, where a decrease is considered negative and

is a measure of “resource potential” (Table 2). As for total biomass, this indicator is

only used for comparison of trends since absolute estimates of biomass are

generally not available.

Mean length of fish in the community is an indicator of the impact of fishing on an

ecosystem, that is, the reduction of mean length of fish in the community (Shin et

al. 2005), From a single species perspective, the removal of larger fish, which are

more fecund and produce more viable eggs than smaller fish (Longhurst 1999),

compromises productivity. From an ecosystem perspective, the removal of larger

species changes the size structure of the community and potentially ecosystem

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functioning. “Fish size” is thus a measure of ecosystem structure and functioning

(Table 2) and is used to measure state and trend.

Trophic level of landings measures the average trophic level of species exploited by the

fishery, and is expected to decrease in response to fishing, since fisheries tend to

target higher trophic level species (Pauly 1998). A decrease in trophic level of

landings and total catch indicates “fishing down the food web” (Pauly 1998), and a

change in the structure of the community and potentially ecosystem functioning.

“Trophic level” is a measure of ecosystem structure and functioning (Table 2) and

is used to measure state and trend. Trophic level of individual species is either

estimated through modelling, or taken from global database such as Fishbase.

Proportion of predatory fish is a measure of the diversity of fish in the community.

Predatory fish are all surveyed fish species that are piscivorous, or feeds on

invertebrates that are larger than 2 cm. “% predators” is a measure of conservation

of biodiversity (Table 2) and is used to measure state and trend.

Proportion of under and moderately exploited stocks represents the success (or not) of

fisheries management. Ideally, in a precautionary world, all stocks should be

moderately exploited to ensure sustained biodiversity and sustainable ecosystems.

“% of sustainable stocks” is a measure of conservation of biodiversity (Table 2).

The FAO classification of stocks as underexploited, moderately exploited, fully

exploited etc (http://www.fao.org/docrep/009/y5852e/Y5852E10.htm#tbl) was used

to define these categories for the stocks in each ecosystem under consideration in

the current time period. Thus this indicator is used to compare the state of

ecosystems.

Mean life span is a proxy for mean turnover rate of species and communities, and is meant

to reflect the buffering capacity of a system. The life span or longevity is a fixed

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http://www.fao.org/docrep/009/y5852e/Y5852E10.htm#tbl


parameter per species, and therefore the mean life span of a community will reflect

the relative abundances of species with differential turnover rates. Fishing affects

the longevity of a given species (direct effect of fishing and genotype selection), but

the purpose here is to track changes in species composition (same principle as for

mean TL of catch). “Life span” is thus a measure of ecosystem stability and

resistance to perturbations (Table 2) and is used to measure state and trend.

1/Coefficient of variation of total biomass measures the stability of the ecosystem, and is

measured as the COV over the last 10 years. As with “fishing pressure”, it is

expressed as an inverse to make it conform with the directionality of the other

indicators. Thus a low 1/COV indicates low “biomass stability”, low ecosystem

Stability and Resistance to perturbations. Since this indicator is measured over a 10

year time period, it is only used to measure state.

Synthesis of the Indicators

Images help us make sense of who we are, what we do and how we relate to others and to

things around us (Jentoft et al. 2008). They help us to describe, explain and to synthesis

information. As such, they are ideal tools for conveying and synthesising the information

from a suite of ecosystem indicators such as those described here. We have developed a

“generic dashboard” to present the ecosystem indicators describing the state of ecosystems

and the trends within them, using kite diagrams and simple bar plots. The advantage of

such a representation lies in providing a multivariate view of the ecosystem.

Kite diagrams (Figure 1) were used to present the results of the state analysis where state

indicator values (Table 1) were averaged over 2003-2005 to represent the current state of

the ecosystem and over 1993-1995 to represent and earlier time period. Each axis of the

kite diagram corresponds to a selected indicator. On this axis, the indicator is scaled

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between a minimum value (centre of the diagram) and a maximum value which represents

an optimum or a target value. These values are constant across all the ecosystems

considered in the generic dashboard and are determined by the minimum and maximum

values observed in the set of ecosystems. The purpose of the boundaries is to scale the

indicators for graphical representation. This approach highlights the importance of an

inclusive set of case study ecosystems.

Short to medium terms trends were calculated over a 10 year period, 1996-2005 for the

suite of six standardized trend indicators (Table 1). Bar plots were used to represent the

trends which were significant (Figure 2), green indicating and increase, and red a decrease.

This generic dashboard provides (i) set of common indicators, (ii) common methods for

estimating the indicators, (iii) common methods for evaluating ecosystems’ status and

trends, (iv) common methods for representing ecosystems’ status and trends and (v)

provides a platform for comparing a broad range of ecosystems.

A pilot study with 20 marine ecosystems

The IndiSeas WG has assembled the data for this suite of ecosystem indicators for 20

ecosystems around the globe (Table 2). This represents the beginning of a global

comparative analysis and diagnosis of ecosystem status, the results of which will be readily

available to the scientific and general public through the dashboard developed for the

IndiSeas website (see below). The ecosystems in this analysis include temperate,

upwelling, brackish and high latitude ecosystems, with varying ecosystem structure, and a

range of exploitation histories, data quality, sampling programs, and length of time series

of data available. Detailed descriptions of each ecosystem will be available on the IndiSeas

website.

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Reaching the public at large – the IndiSeas Website

In conjunction with the selection of indicators, development of graphical images for data

presentation and synthesis, and data assemblage and compilation, a prototype IndiSeas

website has been developed as a platform to disseminate the results of this analysis to the

scientific and general public (Figure 3). In its first inception, the website consists of (i) the

front page, then (ii) a choice between (a) the results for a specific ecosystem and (b) a

comparison of ecosystem indicators across ecosystems (Figure 1 and 2). With (a), options

include: a detailed description of the ecosystem; a list of description of the key species,

such as target species, habitat-linked species, charismatic species, vulnerable species, top

predator species and forage species; the results of the state indicators and the trend

indicators; and a set of figures which show the short to medium trends for 1996-2005

together with the longer term trends over the whole time series (Figure 4). With (b), the

user can select the ecosystems for comparison.

Further information on the website will include diagnoses of the state of a given ecosystem

and various expert reports, including future publications from this project (see below).

Lessons learned?

Although the full results of this work are not yet available, some lessons have already bee

identified. For example, during the selection stage, sets of indicators were identified that

may be useful to combine for establishing a diagnosis of the state of exploited ecosystems:

The monitoring of a priori redundant indicators may be useful to consolidate the

diagnosis (e.g. mean length and mean TL).

Sets of indicators that are considered to be complementary because they reflect

different processes so that their response to fishing can be different.

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For monitoring exploited populations and ecosystems, ecological indicators can be

calculated from survey data or from catch data. Both sources of information can be

complementary because they do not necessarily include the same components:

catch data concern recruit stages for population indicators, and target species at the

community level.

In some ecosystems, only target species are monitored. This can be detrimental to the

analyses because indirect effects of fishing are essential to understand the responses of the

ecosystem to fishing. In those cases, it is important to identify the gaps and provide

arguments for initiating new surveys. In the meantime, discrepancies need to be taken into

account in the comparative analyses.

It is crucial to determine whether the sampling data include pre-recruits or not. For most

population and ecosystem indicators, the interpretation of their trends will differ according

to the life stages considered, so that the diagnosis may be sometimes biased. For example,

when mean size decreases, it can be either due to decreasing numbers of large fish, and/or

to a good recruitment. Specific surveys conducted for sampling eggs, larval and juvenile

stages should not be considered in the calculation of indicators.

Future research

The goals of this working group were to gather and share indicator expertise across marine

ecosystems and member institutions, in order to (i) develop a set of synthetic ecological

indicators, (ii) build a generic dashboard using a common set of interpretation and

visualisation methods, (iii) evaluate the exploitation status of marine ecosystems in a

comparative framework. Much of this has been achieved, and the IndiSeas WG is currently

taking a broad approach to address the third goal (see also Coll et al, this volume). This

will take the form of a suite of papers which includes interpretations of combined sets of

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indicators representing ecosystem states, interpreting the trends in indicators , and

transforming quantitative information into semi-quantitative and qualitative information

for comparative and managerial purposes. Capturing signals from environmental

variability and how they combine with fishing effects is also addressed through empirical

and modelling approaches.

Additional indicators

The set of indicators examined by the IndiSeas Working Group is viewed in the context of

several other indicators of interest, which are not necessarily available in every ecosystem,

for example discards, as well as model-derived indicators for groups of ecosystems (e.g.

EwE indicators for upwelling systems (Coll et al. 2006, Shannon et al. in prep.) and model-

estimated indicators of fishing pressure C/B). The ratio catch/biomass could be used for

assessing the exploitation state of ecosystems if we had a reliable estimate of B in each

ecosystem (and not only a B index). An estimate of total biomass could, for example, be

estimated by applying Ecopath models in the regions of concern. It should include all

trophic compartments of an Ecopath model except plankton, marine mammals, birds and

detritus. The catch should include all retained species (including unassessed species).

When estimated in this way, fishing pressure (catch/biomass) would measure fishing

pressure at the ecosystem level. Currently, it measure the exploitation rate of retained

species, not all the potentially fished species (Bundy et al. 2005).

Testing the performance of ecosystem indicators in fisheries management

How do we know how well an indicator indicates and guides management decisions? This

is a crucial question in the development of indicators and is often ignored. Performance

testing is a formal procedure to assess whether an indicator and accompanying decision

rule actually guides decision-makers to make the “right” decision, in hindsight.

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Performance testing scores the ratio of “right” decisions to “wrong” decisions. The suite of

indicators collected under the EUR-OCEANS initiative provides a unique opportunity to

test these indicators across a range of ecosystem types. Conclusions should be very robust.

Developing reference points for indicators

Establishing reference points for ecosystem indicators has proven to be a major challenge

to implementing EAF, due to the complexity of ecosystems and their response to fishing in

a changing environment. A key benefit of the comparative approach is that it provides

empirical data on ecosystem indicator behaviour across a range of ecosystem types and

states. These data will be used to explore whether, at the very least, limit thresholds can be

identified, and whether possible target reference points can be proposed. Ecosystem

models can also be used for identifying baseline levels and threshold reference levels.

Building bridges with other scientific fields:

The usefulness of the set of selected ecological indicators needs to be assessed and the

ecosystem diagnosis needs to be strengthened by providing additional non-ecological

indicators in order to provide a more integrative evaluation of ecosystems states to support

an ecosystem-based fisheries management. Three specific tasks have been identified for

the near future:

Studies of the joint effects of climate and fishing changes on the selected indicators.

Time-series analyses of fishing effort and regional climate indices are needed.

Ecosystem models can also be used to assess the specificity of ecosystem indicators

to fishing effects versus climate effects (e.g. EwE, Osmose and Atlantis models).

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Integration of conservation and biodiversity issues in the diagnosis of ecosystem

states.

Biodiversity is a key ingredient for resilient, robust ecosystems. All too often

however, species, habitats or even whole ecosystems are negatively affected by

fishing and mitigation approaches are necessary in addition to avoiding damage

through wise management. A set of indicators that will quantify the biodiversity and

conservation risks in ecosystems should be considered in the future.

Iintegration of socio-economic issues.

EAF has many facets, and one which is too often ignored is the realm of socio-

economic indicators of the effects of fishing on ecosystems. As yet, the development

of socio-economic indicators lags that of ecological indicators, and thus there is less

to work with. However, future studies should aim to review existing socio-economic

indicators and subsequently apply the criteria outlined above to select a subset of

socio-economic indicators for inclusion in the generic dashboard of indicators.

Acknowledgements

EUR-OCEANS for original funding of “EAF Indicators : a comparative approach across

ecosystems” under WP 6. All members of the IndiSeas Working Group.

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Table 1: Minimal list of ecosystem indicators for establishing the generic dashboard with corresponding management objectives (L: length (cm), i: individual, s: species, N: abundance, B: biomass, Y: catch (tons), D=decline over time, RP = Resource Potential, EF = Ecosystem structure and Functioning, CB=Conservation of Biodiversity, SR = Ecosystem Stability and Resistance to Perturbations.

Indicators Headline label

Calculation, notations, units

Used for state (S), trend (T)

Expected Trend

Manage-ment Objectives

Management Direction

Total biomass of surveyed species

biomass B (tons) T D RP

Reduction of overall fishing effort and quotas

1/(landings /biomass)

inverse fishing pressure

B/Y retained species T D RP

Reduction of overall fishing effort and quotas

Mean length of fish in the community

fish size

(cm)

S, T D EF

Reduction of overall fishing effort. Decrease fishing effort on large fish species

TL landings trophic level

S, T D EF

Decrease fishing effort on predator fish species

Proportion of under and moderately exploited stocks

% sustainable stocks

number (under+moderately exploited species)/total no. of stocks considered

S D CB

Decrease fishing effort on overexploited fish species. Diversify resource composition

Proportion of predatory fish

% predators

prop predatory fish= B predatory fish/B surveyed

S, T D CB

Decrease fishing effort on predator fish species

Mean life span life span

(years)

S, T D SR

Decrease fishing effort on long-living species

1/Coefficient of variation of total biomass

biomass stability

mean(total B for the last 10 years) /sd(total B for the last 10 years)

S D SR

N

LL i

i∑=

Y

YTLLT s

ss

la n d

∑=

∑∑

=

SS

SS

B

Bage )( max

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DEFINITIONS Species considered in the calculation of indicators Surveyed species These are species sampled by researchers during routine surveys (as opposed to species sampled in catches by fishing vessels), and should include species of demersal and pelagic fish (bony and cartilaginous, small and large), as well as commercially important invertebrates (squids, crabs, shrimps…). Intertidal and subtidal crustaceans and molluscs such as abalones and mussels, mammalian and avian top predators, and turtles, should be excluded. Surveyed species are those that are considered by default in the calculation of all survey-based indicators. Retained species (landed) These are species caught in fishing operations, although not necessarily targeted by a fishery (i.e. include by-catch species), and which are retained because they are of commercial interest, i.e. not discarded once caught, although this does not imply that sometimes certain size classes of that species may be discarded. A non-retained species is considered to be one that would never be retained for consumptive purposes. Intertidal and subtidal crustaceans and molluscs such as abalones and mussels are to be excluded. Retained species are those that are considered by default in the calculation of all catch-based indicators. Predatory fish species Predatory fish are considered to be all surveyed fish species that are not largely planktivorous (i.e. phytoplankton and zooplankton feeders should be excluded). A fish species is classified as predatory if it is piscivorous, or if it feeds on invertebrates that are larger than the macrozooplankton category (> 2cm). Detritivores should not be classified as predatory fish.

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Table 2: Ecosystems considered in the comparative approach and corresponding FAO fishing zones (http://www.fao.org/fi/website/FISearch.do?dom=area) MFA= FAO Major Fishing Area, Div= FAO Division

Coastal ecosystem

Geographical area

Type of ecosystem

Surrounding countries

Large Marine Ecosystem

FAO fishing zones

Southern Benguela

SE Atlantic Upwelling South Africa Benguela current

MFA: 47, Div: 1.6, 2.1

Bay of Biscay NE Atlantic Temperate Shelf

France Iberian Coastal MFA: 27, Div: VIIIa, b

Sahara Coastal

E Central Atlantic

Upwelling Morocco Canary Current MFA: 34, Div: 1.3

Senegalese ZEE

E. Central Atlantic

Upwelling Senegal Canary Current MFA: 34, Div: 3.12

Guinean ZEE E Central Atlantic

Upwelling Guinea Guinea current MFA: 34, Div: 3.13

Southern Humboldt

SE Pacific Upwelling Chile Humboldt current

MFA 87; Div:

Northern Humboldt

SE Pacific Upwelling Peru Humboldt current

MFA: 87, Div: 1.1, 1.2

Eastern Scotian shelf

NW Atlantic Temperate Shelf

Canada Scotian Shelf MFA: 21, Div: 4V, 4W

North East US

NW Atlantic Temperate Shelf

US NEUS continental shelf

MFA 21; Div 5Y, 5Y, 6A,B,C

North Sea NE Atlantic Temperate UK, Norway, Denmark, Germany, Netherlands, Belgium

North Sea MFA: 27, Div: IVa,b,c, IIIa

Barents sea NE Atlantic High Latitude Norway Barents Sea MFA: 27, Div: I, IIb

Irish Sea NE Atlantic Temperate Ireland, UK Celtic-Biscay Shelf

MFA: 27, Div: VIIa

North Central Adriatic Sea

Central Mediterranean

Temperate Italy, Slovenia, Croatia, Bosnia-Herzegovina, Montenegro

Mediterranean MFA: 37, Div: 2.1

Southern Catalan Sea

NW Mediterranean

Temperate Spain Mediterranean MFA: 37, Div: 1.1

Korea NW Pacific Temperate, semi-enclosed sea

Korea Sea of Japan MFA 61

Portuguese NE Atlantic Upwelling Portugal Iberian Coastal MFA: 27,

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http://www.fao.org/fi/website/FISearch.do?dom=area


ZEE Div: IXa

Central Baltic Sea

NE Atlantic Brackish Temperate

Germany, Estonia, Sweden, Poland, Russia, Lithuania, Latvia, Finland, Denmark

Baltic Sea MFA: 27, Div: IIId 25 to 29

Bering Sea, Aleutian Islands

NE Pacific High Latitude Alaska, US East Bering Sea MFA: 67

West coast Canada

NE Pacific Seasonal Upwelling

Canada Gulf of laska MFA 67

Mauritania E. Central Atlantic

Upwelling Mauritania Canary Current MFA: 34, Div: 3.12

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Figures

Figure 1. Example of kite diagrams,comparing the current state of four of the 20 ecosystems represented in the IndiSeas project. Each arm of the kite represents one indicator, minimum and maximum values are the same for all figures. (note there is an additional indicator, “stability catch” included in these kite diagrams is no longer used and safe species = % sustainable stocks).

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FFigure 2. Example of bar plots comparing the short to medium term trends (1996-2005) of four of the 20 ecosystems represented in the IndiSeas project. Green indicates a significant increase; orange-red indicates a significant decrease. FS=fish size, TL=trophic level, B=biomass, C=catch, P=% predators, LS=lifespan, FP=fishing pressure. (note there is an additional indicator, “stability catch” included in these kite diagrams which is no longer used).

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Figure 3. Front page of the prototype IndiSeas Website.

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Figure 4. Detailed results for the eastern Scotian Shelf, Canada. The significant short to medium term trends (1996-2005) are given in the bar plot at the top. In the lower four plots, the original data is shown (red squares, non-standardised), with a regression line (blue line) through all years and the regression line for 1996-2005 (red line). Note that the negative gradient of the regression line through the whole data set is much steeper than the gradient of the regression line through the recent data, which in the case of trophic level, has reversed and increased. These data indicate that the eastern Scotian Shelf ecosystem may have improved in recent years, perhaps the results of a severe reduction in fishing pressure since the collapse of groundfish in the early 1990s (Bundy 2005).

Documents

IndiSeas: A Global Comparison of ecosystem indicators across … Doccuments/CM-2008/O/O2208.pdf · ecosystem indicators has been developed, reporting results of various statistical