An ecosystem-based fisheries assessment approach for Korean fisheries

Fisheries Research 100 (2009) 26–41

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An ecosystem-based fisheries assessment approach for Korean fisheries Chang Ik Zhang a,∗ , Suam Kim a , Donald Gunderson a , Richard Marasco b , Jae Bong Lee c , Hee Won Park a , Jong Hee Lee a a

Pukyong National University, Busan 608-737, Republic of Korea 18217 NE, 191st Street, Woodinville, WA 98077, USA c National Fisheries Research and Development Institute, Busan 619-902, Republic of Korea b

a r t i c l e

i n f o

Article history: Received 15 January 2008 Received in revised form 5 November 2008 Accepted 1 December 2008 Keywords: Ecosystem-based approach Fisheries assessment Two-tier analytical method Ecosystem indicators Risk index Risk assessment diagram Korean fisheries

a b s t r a c t Concern is growing over how ecosystems are being affected by fishing. A comprehensive ecosystem-based approach is required to holistically assess and manage fisheries resources and their associated habitats by considering ecological interactions of target species with predators, competitors, and prey species, interactions between fishes and their habitats, and the effects of fishing on these processes. A pragmatic ecosystem-based approach was developed for the assessment of fisheries resources in Korean waters involving three management objectives: sustainability, biodiversity, and habitat quality. A two-tier analytical method was employed. Tier 1 was designed for situations where sufficient information is available to allow for a quantitative evaluation of the status of the system, while Tier 2 was designed for situations where available information necessitated a semi-quantitative or qualitative assessment. A total of 20 Tier 1 indicators and 24 Tier 2 indicators were developed for assessment of ecosystem status. Both target and limit reference points were chosen for each indicator to assess the status of species, fisheries and ecosystems. Nested risk indices, such as objectives risk index (ORI), species risk index (SRI), fishery risk index (FRI), and ecosystem risk index (ERI), were developed to assess the ecosystem status at the management unit level. A risk assessment diagram was developed and found to be useful in quickly displaying results. A management status index (MSI) was also developed to evaluate the level of management improvement in species, fisheries, or ecosystems among different time periods or different areas. The method was demonstrated by applying it to the Tongyeong marine ranch and the Korean large purse seine fishery. It was found that this approach can be used to compare the status of species, fisheries and ecosystems spatially and temporally using an ecosystem perspective. © 2008 Elsevier B.V. All rights reserved.

1. Introduction As the twenty-first century unfolds, the world faces unprecidented challenges. The ongoing struggle over fisheries resources is a microcosm of a much larger struggle in which diverse interests compete for the use of the world’s oceans for fishing, industrial needs, waste disposal, recreation, and transport. Concern is growing over how ecosystems are being affected by fishing. Fisheries are managed within a setting that lacks full information on, for example, fish population dynamics, interactions among species, effects of environmental factors, and the effects of human activity on fish and their ecosystem (Zhang and Marasco, 2003). Recognition of uncertainty and its potential consequences led to the adoption of the precautionary approach in the United Nations Conference on the Environment and Development Rio Dec-

∗ Corresponding author. Tel.: +82 51 629 5892; fax: +82 51 629 5886. E-mail address: [email protected] (C.I. Zhang). 0165-7836/$ – see front matter © 2008 Elsevier B.V. All rights reserved. doi:10.1016/j.fishres.2008.12.002

laration (Principle 15), the 1995 United Nations (UN) Agreement on Straddling and Highly Migratory Fish Stocks, and the 1995 Food and Agriculture Organization (FAO) Code of Conduct for Responsible Fisheries (FAO, 1995). The precautionary approach focuses on reducing the likelihood of fisheries having adverse impacts on marine resources and host ecosystems (FAO, 1995). In 2002 the World Summit on Sustainable Development recommended implementation of the ecosytem approach by 2010 (UN, 2002). Three basic and interrelated problems characterize modern day fisheries: (1) the threat of over-exploiting fish stocks, (2) overcapitalization or over-expansion of fishing fleets, and (3) the negative consequences of fisheries on ecosystems and associated habitats. Enitities responsible for managing fisheries have made considerable progress in addressing the first and second problems. For example, the North Pacific Fishery Management Council has adopted overfishing definitions for major species that fall under its jurisdiction (NPFMC, 2007). It has also implemented management measures to control entry into several of its major fisheries (NPFMC, 2004). Due to lack of consensus and the complexity of the issue, progress on the third problem has been slow. The diverse, dynamic,

C.I. Zhang et al. / Fisheries Research 100 (2009) 26–41

and complex nature of fishery management problems necessitates the development of an assessment and management process that allows for the involvement of stakeholders and the expansion of human interactions. Resource managers, researchers, user groups and other interested parties must be involved in the process to minimize conflict and maximize commitment to sustainable management (Zhang and Marasco, 2003). Movement has occurred towards ecosystem-based fisheries management as a common theme in fishery policy and management discussions worldwide (NMFS, 1999; FAO, 2003; Garcia et al., 2003; Anonymous, 2006a; FAO, 2007). The International Council for the Exploration of the Sea (ICES) outlined how it plans to introduce an ecosystem approach (Anonymous, 2004a) and had a special meeting in 2006 to develop a blueprint for the new science and advisory structures that will be required within ICES to service the demands of the ecosystem approach (Anonymous, 2006b). The North Pacific Marine Science Organization (PICES) started discussing ecosystem-based management by establishing a PICES study group in 2003 (Jamieson and Zhang, 2005). Further, a working group on ecosystem-based management science and its application in North Pacific countries was created in 2005. Many counties, such as Australia, Canada and USA, are contemplating how to implement marine fisheries management concepts considering ecosystems (Anonymous, 2004b, 2005; CSIRO, 2005). There have been numerous workshops and conferences that have

27

addressed what ecosystem-based fisheries management is and how it should be implemented (NRC, 1999; Witherell, 2004). Marasco et al. (2007) suggested some approaches useful for planning, implementing, and evaluating ecosystem-based fisheries management. In Korea several studies stressed the importance of implementing an ecosystem-based approach to fisheries (Zhang, 2002; Huh and Zhang, 2005; Zhang, 2006). The Korean government recently defined a “Vision for Korean Fisheries”. Stated in the vision statement was the desire to maintain abundant and healthy marine ecosystems and prosperous fishing villages (MOMAF, 2006). Four major goals were identified for Korean fisheries. The first was rebuilding fishery resources based on an ecosystem approach. The other goals were: modifying the structure of fishery production, preventing harmful and illegal fishing activities, and improving marine environmental quality. This vision statement builds upon the “Act on the Conservation and Management of Marine Ecosystems” that came into force in April 2007. It focused on the sustainable utilization of marine biological resources, protection of marine ecosystems and conservation of marine biodiversity. The purpose of this study is to develop a pragmatic ecosystembased fisheries assessment approach that integrates ecosystem considerations into the fishery assessment process, with the intent being to facilitate the realization of the Korean government’s desire to improve management of its fishery resources. This approach is

Fig. 1. Identification of objectives (circles) and attributes (bulleted list) for the ecosystem-based fisheries assessment approach.

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C.I. Zhang et al. / Fisheries Research 100 (2009) 26–41

Table 1 Attributes and indicators for the sustainability objectives used in the ecosystem-based fisheries assessment approach in Korea. Tier 1 assessment uses quantitative analysis of rich scientific data, whereas Tier 2 assessment involves qualitative or semi-quantitative analysis of data-poor situations. The number of asterisks (*) reflects the subjective relative importance of the indicator, and is used to calculate objective risk indices. Attribute

Indicator Tier 1

Weight

Tier 2

Weight

Biomass

Biomass or CPUE

*** **

CPUEa

***

Fishing intensity

Fishing mortality or catch

** **

Restricted access Fishery monitoring and sampling Fishing method Precautionary approach and quality of stock assessment

*** ** ** **

Size at first capture

Age at first capture

*

Size at entry

***

Habitat size

Habitat size

*

n/a

Community structure

FIB indexb

*

n/a

indexc

*

n/a

*

n/a

Reproductive potential

FRP

Productivity

Total production of ecosystemd

Life history characteristics

n/a

Maximum age or age at maturity Adult and juvenile habitat overlap

** *

n/a

Management plan for fishery Management of IUUe fishery

** *

Management Recovery

n/a

Genetic structure

No. of spawning populations

*

Recovery plan and period for depleted stocks

*

Documentation of population structure

*

n/a denotes not applicable. a CPUE: catch per unit effort. b FIB index (fishery in balance): FIB = log(Y (1/TE)TLi ) − log(Y (1/TE)TL0 ) (Pauly et al., 2000). 0 i c FRP index (fish reproduction potential): FRP = log(Y MR /qf ) − log(Y MR /qf ) (Lee et al., 2007). 0 0 0 i i i d Total production of the ecosystem (unit: mt/km2 /year) (Christensen and Pauly, 1992). e IUU: illegal, unregulated and unreported fishing.

accomplished by defining management objectives, developing indicators, and identifying reference points for assessment. Recently, the topic of the identification of appropriate management indicators has received considerable attention (Cury and Christensen, 2005; Daan, 2005). Further, numerous studies on ecosystem indicators have been carried out (Fulton et al., 2004; Degnobol and Jarre, 2004; Jennings, 2005; Link, 2005; Kruse et al., 2006). Nevertheless, few case studies exist where information on indicators has been synthesized to obtain an integrated ecosystem-based assessment (e.g., Ecological Risk Assessment of Australian Fisheries Management Authority) (CSIRO, 2005). The focus of this study is on the development of nested risk indices that can be used to assess the status of a management unit (i.e., species, fishery or ecosystem).

2. An ecosystem-based fisheries assessment approach using indicators When considering the structure of a fishery management system that allows for the integration of ecosystem considerations into decisions, we believe that the following principles should apply: (1) the approach should be evolutionary rather than revolutionary, (2) it should be capable of being applied with available information, (3) it should be precautionary and environmentally sound, and (4) it should be simple and pragmatic. Larkin (1996) indicated that there are three primary elements in ecosystem management: sustainability of yields, maintenance of biodiversity, and protection from the effects of pollution and habitat degradation. Gislason et al. (2000) proposed six ecosystem characteristics that need to

Table 2 Attributes and indicators for the biodiversity objectives used in the ecosystem-based fisheries assessment approach in Korea. Tier 1 assessment uses quantitative analysis of rich scientific data, whereas Tier 2 assessment involves qualitative or semi-quantitative analysis of data-poor situations. The number of asterisks (*) reflects the subjective relative importance of the indicator, and is used to calculate objective risk indices. Attribute

Indicator

Total bycatch Total discards Trophic level Diversity Integrity of functional groups Gear restrictions and avoidance tactics

Tier 1

Weight

Tier 2

Weight

Bycatch rate Discard rate Mean trophic level of the communitya Diversity indexb Invasive/traditional species in catch n/a

** ** * * *

Bycatch Discard n/a No. of species Changes in ratio of functional groups in catch Gear restrictions and avoidance tactics for non-target species

** **

n/a denotes not applicable. a Mean trophic level from research surveys (Pauly et al., 1998). b

N 

Diversity index: DI = −

j=1

Pj ln Pj (modified from Shannon and Wiener (1963)), where N is the total number of individuals, Pj is proportion of each species.

** * **

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Table 3 Attributes and indicators for the habitat quality objectives used in the ecosystem-based fisheries assessment approach in Korea. Tier 1 assessment uses quantitative analysis of rich scientific data, whereas Tier 2 assessment involves qualitative or semi-quantitative analysis of data-poor situations. The number of asterisks (*) reflects the subjective relative importance of the indicator, and is used to calculate objective risk indices. Attribute

Indicator Tier 1

Weight

Tier 2

Weight

Habitat damage

Critical habitat damage rate Pollution rate of spawning and nursery grounds Lost fishing gear

** * *

Influence of fishing gear on benthic habitat Pollution of habitat Lost fishing gear

*** ** **

Discarded wastes

Discarded wastes

*

Discarded wastes

*

Habitat protection

Areas of prohibited fishing

*

Gear restrictions or habitat closure

***

Habitat recovery

No. of artificial reefs Area of artificial seaweed bed

* *

Recovery of physically damaged habitat Recovery of biologically damaged habitat

* *

be considered: (1) ecosystem diversity, (2) species diversity, (3) genetic variability within species, (4) directly impacted species, (5) ecologically dependent species, and (6) trophic level balance. Insights concerning ecosystem characteristics provided by Larkin

and Gislason are helpful to identify management objectives. Further, key to understanding the status of fisheries and associated ecosystems is the identification of objectives and their associated attributes.

Table 4 Objectives, indicators, and status of indicator relative to target and limit reference points for Tier 1 ecosystem-based fisheries assessment approach. Objective

Attribute

Indicator

Sustainability

Biomass

Biomass (B) or CPUEa Fishing mortality (F) or catch (C) Age at first capture (t) Habitat size (H) FIB indexe FRP indexf Total production of ecosystemg (P) No. of spawning populations (SP) Bycatch rate (BC/C)h Discard rate (D/C)i Mean trophic levelj (TL) Diversity indexk (DI) Invasive/traditional species in catch (I/T)l Critical habitat damage rate (DH/H)m Pollution rate of spawning and nursery ground (PG/G)n Lost fishing gear (frequency, FR) Discarded wastes (DW) Prohibited area from fishing (PA) No. of artificial reefs (N) Area of artificial seaweed bed (A)

Fishing intensity Size at first capture Habitat size Community structure Reproductive potential Productivity Genetic structure Biodiversity

Total bycatch Total discards Trophic level Diversity Integrity of functional group

Habitat

Habitat damage

Discarded wastes Habitat protection Habitat recovery

Indicator status Better than target

Between target and limit

Beyond limit

B ≥ B40% CPUE ≥ CPUEABC b F ≤ F40% C ≤ ABC t ≥ ttarget d H ≥ Htarget FIB ≥ FIBtarget FRP ≥ FRPtarget P ≥ Ptarget

B40% > B ≥ B35% CPUEABC > CPUE ≥ CPUEMSY c F40% < F ≤ FMSY ABC < C ≤ MSY ttarget > t ≥ 0.9ttarget Htarget > H ≥ 0.8Htarget FIBtarget > FIB ≥ FIBlimit FRPtarget > FRP ≥ 0.9FRPtarget Ptarget > P ≥ 0.9Ptarget

B < B35% CPUE < CPUEMSY F < FMSY C > MSY t < 0.9ttarget H < 0.8Htarget FIB < FIBlimit FRP < 0.9FRPtarget P < 0.9Ptarget

SP ≥ SPtarget

SPtarget > SP ≥ 0.9SPtarget

SP < 0.9SPtarget

(BC/C) ≤ (BC/C)target (D/C) ≤ (D/C)target TL ≥ TLtarget DI ≥ DItarget ı(I/T) ≤ 0.05(I/T)target

(BC/C)target < (BC/C) ≤ 1.05(BC/C)target (D/C)target < (D/C) ≤ 1.05(D/C)target TLtaget > TL ≥ TLlimit DItarget > DI ≥ 0.9DItarget 0.05(I/T)target < ı(I/T) ≤ 0.10(I/T)target

(BC/C) > 1.05(BC/C)target (D/C) > 1.05(D/C)target TL < 0.9TLlimit DI < 0.9DItarget ı(I/T) > 0.10(I/T)target

(DH/H) ≤ (DH/H)target

(DH/H)target < (DH/H) ≤ 1.1(DH/H)target

(DH/H) > 1.1(DH/H)target

(PG/G) ≤ (PG/G)target

(PG/G)target < (PG/G) ≤ 1.1(PG/G)target

(PG/G)) > 1.1(PG/G)target

FR ≤ FRtarget

FRtarget < FR ≤ 1.1FRtarget

FR) > 1.1FRtarget

DW ≤ DWtarget PA ≥ PAtarget

DWtarget < DW ≤ 1.1DWtarget PAtarget > PA ≥ 0.9PAtarget

DW) > 1.1DWtarget PA < 0.9PAtarget

|N − Ntarget | ≤ 0.05Ntarget |A − Atarget | ≤ 0.05Atarget

0.05Ntarget < |N − Ntarget | ≤ 0.10Ntarget 0.05Atarget < |A − Atarget | ≤ 0.10Atarget

|N − Ntarget | > 0.10Ntarget |A − Atarget | > 0.10Atarget

n/a denotes not applicable. a CPUE: catch per unit effort. b ABC: acceptable biological catch. c MSY: maximum sustainable yield. d t target : optimum age at first capture from Beverton and Holt yield-per-recruit analysis. e FIB index (fishery in balance): FIB = log(Y (1/TE)TLi ) − log(Y (1/TE)TL0 ) (Pauly et al., 2000). 0 i f FRP index (fish reproduction potential): FRP = log(Y MR /qf ) − log(Y MR /qf ) (Lee et al., 2007). 0 0 0 i i i g Total production of ecosystem (unit: mt/km2 /year) (Christensen and Pauly, 1992). h BC is bycatch and C is total catch. i D is discards and C is total catch. j Mean trophic level from research surveys (Pauly et al., 1998). k

N 

Diversity index: DI = −

Pj ln Pj (modified from Shannon and Wiener (1963)), where N is the total number of individuals, Pj is proportion of each species.

j=1 l m n

I is catch of invasive species and T is catch of traditional species. DH is damaged critical habitat area and H is total habitat area. PG is polluted spawning and nursery ground and G is total spawning and nursery ground.

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Table 5 Objectives, indicators, and status of indicator relative to target and limit reference points for Tier 2 ecosystem-based fisheries assessment approach. Objective

Sustainability

Attribute

Indicator

Indicator status Between target and limit

Beyond limit

Biomass

CPUEa

CPUE data are available and not declining

CPUE data are available, but declining

CPUE data are not available

Fishing intensity

Restricted access

Fixed access, little latent effort exists (≤30% of licenses inactive) Observer program in place, sampling for all fishery data All fishing methods and patterns are evaluated and changes monitored

New entrants can be licensed >30% latent effort in fishery Monitoring and sampling for a limited number of fisheries Fishing methods and patterns are evaluated for main methods and some geographical areas Inadequate stock assessment is provided, but precautionary approach is adopted

Open access

Fishery monitoring and sampling Fishing method

Main fishing methods and patterns are not evaluated

Size at first capture

Size at entry

≥Size at maturity


Greater than 20% of the catch immature or size at maturity unknown

Life history characteristics

Maximum age or age at maturity

Low risk (<10, <5, respectively)

Medium risk (10–25, 5–10, respectively)

High risk (>25, >10, respectively)

Adult habitat overlap with juvenile

Low

Medium

High or no data

Management plan for fishery

Management plan is operational and reviewed annually All fisheries are legal and regulated

Management plan is operational, but irregularly reviewed Some illegal fisheries exist

Management plan is not operational

Recovery plan and period are operational and annually reviewed Number of spawning populations known and constant

Recovery plan and period are operational, but irregularly reviewed Number of spawning populations known and declining

Bycatches are being monitored and controlled for all fisheries Discards are being monitored and controlled for all fisheries Decreases in the number of species have not occurred

Bycatches are being monitored and controlled for some fisheries Discards are being monitored and controlled for some fisheries Decreases in the number of species have occurred in some communities

Little monitoring or control of bycatches

IUUb

fishery

Inadequate stock assessment, and precautionary approach is not adopted

Little regulation exists

Recovery

Recovery plan and period for depleted stocks

Genetic structure

Population structure

Total bycatch

Bycatch

Total discards

Discard

Diversity

No. of species

Integrity of functional group

Changes in ratio of functional groups in catch

Minor change in relative abundance of species in community

Ecosystem function altered measurably and some important species missing locally

Ecosystem function drastically altered with significant loss of important species

Gear restrictions and avoidance tactics

Gear restrictions and avoidance tactics for non-target species

Gear restrictions and avoidance tactics operational

Development of gear restrictions and avoidance tactics in progress

Few gear restrictions or avoidance tactics

Habitat damage

Impact of fishing gear on benthic habitat

Negligible impact (mid-water, surface fishing gears) Monitored, and unpolluted

Identifiable impact (bottom fishing gear)

Serious impact (dredges)

Sufficient knowledge of type, quantity and location of gear types lost and management plan in place No waste discarded

Polluted, but monitoring or recovery plan in place Type, quantity and location of gear lost during fishing operations are recorded and management plan in place Some waste retained

Polluted, but no monitoring or recovery plan in place Little information and no management plan

Pollution of habitat Lost fishing gear

Recovery plan and period are not operational Number of spawning populations unknown or sharply declining

Little monitoring or control of discards Decreases in the number of species have occurred in several communities

Discarded wastes

Discarded wastes

Habitat protection

Gear restrictions or habitat closure

Gear restrictions or closures that avoid damage to critical habitat

Habitat avoidance gear in development or habitat closures planned

No gear restrictions or critical habitat protection

Habitat recovery

Recovery of physically damaged habitat

Artificial reefs have recovered damaged habitat Seaweed beds have recovered damaged habitat

Artificial reefs have partially recovered damaged habitat Seaweed beds have partially recovered damaged habitat

No recovery

Recovery of biologically damaged habitat a

CPUE: catch per unit effort.

b

IUU: illegal, unregulated and unreported fishing.

Little or unknown quantity of waste retained

No recovery

C.I. Zhang et al. / Fisheries Research 100 (2009) 26–41

Adequate stock assessment is provided and precautionary approach is adopted

Management of

Habitat

Negligible monitoring or sampling

Precautionary approach and sensitivity of stock assessment

Management

Biodiversity

Better than target

C.I. Zhang et al. / Fisheries Research 100 (2009) 26–41

Management objectives for this study were determined by reviewing fishery policy actions recently taken by the Korean government. The “Vision for Korean Fisheries” recommends maintaining system sustainability and biodiversity consistent with natural processes, as well as protecting and restoring habitats of fish and associated species. Given these three objectives, i.e., maintenance of sustainability, biodiversity and habitat quality, attributes were identified that characterize the current status of the fishery relative to the corresponding objectives (Fig. 1). The next step in the process was identification of indicators for each attribute. The following four considerations were used in the selection process: (1) ease of understanding by users, (2) susceptibility to influence through management of human activities, and (3) measurability using existing data or currently monitored information. Candidate indicators were obtained from FAO (1999, 2000, 2003), Marine Stewardship Council (http://www.msc.org/html/content 1248.htm), and Ecological Risk Assessment (CSIRO, 2005) for Australia. Indicators were identified for both data-rich (Tier 1) and data-poor (Tier 2) situations (Tables 1–3). Relative weights for each indicator were obtained by conducting a series of expert workshops, considering: (1) the importance for achieving the objectives, (2) scientific basis for estimating indicators and reference points, and (3) availability of data and information. Each weight is represented by one to three asterisks. For instance, ‘Biomass’ was given a weight of three asterisks, and ‘Genetic structure’ one asterisk under the sustainability objectives (Table 1). Then, the number of asterisks was coded with a numerical value: ‘1’ for one asterisk, ‘2’ for two asterisks, and ‘3’ for three asterisks. The same indicators across Tier 1 and Tier 2 assessments can be weighted differently, depending on the scientific situation. Both target and limit reference points for each indicator were established as shown in Fig. 2. The target reference point in this application corresponds to a state of each indicator that is considered desirable, while the limit reference point is defined as the limit beyond which the state of each indicator is not considered desirable (Tables 4 and 5). Species were assigned a status for each indicator to denote risk. If the state of the indicator was between the virgin state and the target reference point, then a score of “0” was assigned (Tables 4 and 5). When it was between the target and limit reference point, the risk score is calculated for each indicator as, Itarget − Ii RSi = RSmax ( ) Itarget − Ilimit

(1)

where RSi is the risk score for indicator i that ranges from 0 to 2. RSmax is the maximum risk score “2”, Ii , Itraget , and Ilimit are estimated, target and limit values for indicator i, respectively (Table 4). If it was beyond the limit reference point, then a score of “2” was assigned. Using the steps described above, information was produced that allowed for the construction of four different but nested indices

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Fig. 3. Nested structure of risk indices used in the ecosystem-based fisheries assessment approach. ORI denotes objectives risk index, SRI, species risk index, FRI, fishery risk index, ERI, ecosystem risk index, and MSI, management status index.

useful for characterizing the status of the system (Fig. 3). These indices are the objectives risk index (ORI), species risk index (SRI), fishery risk index (FRI), and ecosystem risk index (ERI). The objectives risk index was defined as, n 

ORI =

RSi Wi

i=0 n



(2) Wi

i=1

where “RSi ” is the risk score for indicator “i” (Tables 1–3), given the associated reference points (Tables 4 and 5). “Wi ” is the weighting factor for indicator “i”, which is represented by the number of asterisks, and “n” is the number of indicators. For each species, objectives risk indices are calculated for each objective, i.e., ORIS for sustainability, ORIB for biodiversity, ORIH for habitat quality. An overall species risk index was calculated for each species and defined as the weighted sum of the objectives risk indices, SRI = S ORIS + B ORIB + H ORIH

(3)

where “i ” is the weighting factor for the ith ORI. The sum of “i s” is 1.0. “i ” can vary with target species and was determined from the local experts’ opinions based on behavioral, ecological and other fishery-related factors for the given ecosystem. The fishery risk index is the weighted average risk index for exploited species in each fishery, Fig. 2. Reference point (RP) and risk score for the ecosystem-based fisheries assessment approach.

 Bi SRIi FRI =  Bi

(4)

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C.I. Zhang et al. / Fisheries Research 100 (2009) 26–41

three zones represent the degree of risk in the ecosystem. Any risk indicator falling into the red zone is considered to be in need of special attention. Changes in the status of any of the indices can be identified by examining the following management status indices (MSI). MSIO =

ORIt − ORIt  ORIt

(6a)

MSIS =

SRIt − SRIt  SRIt

(6b)

MSIF =

FRIt − FRIt  FRIt

(6c)

MSIE =

ERIt − ERIt  ERIt

(6d)

where MSIO , MSIS MSIF , and MSIE measure changes in objectives, species, fishery and ecosystem management status indices, respectively. The t and t represent the initial and subsequent time periods being compared, respectively. Differences in risk indices can be statistically examined by a Wilcoxon paired-sample nonparametric test (Zar, 1999).

Fig. 4. Risk assessment diagram for ORI (objectives risk index) and SRI (species risk index) for the ecosystem-based fisheries assessment approach. Biodiversity–sustainability plane at upper right, sustainability–habitat quality plane at upper left, habitat quality–biodiversity plane at lower left. The SRI scale is on the diagonal at lower right.

where Bi is the biomass or biomass index such as catch per unit of effort for species i, which ever is the best available index for the species being considered. The ecosystem risk index is defined as the weighted average of the fishery risk indices in an ecosystem,

 Ci FRIi ERI =  Ci

(5)

where Ci is the catch of ith fishery. Insights concerning the success of management actions and the status of fishery resources, fisheries and ecosystems can be obtained by examining the indices discussed above. For example, ORIs can be examined to determine the effectiveness of management in promoting sustainability, biodiversity and habitat quality. A risk assessment diagram (Fig. 4) was created to facilitate consideration of the constructed indices. The four axes of the square represent each ORI (i.e., biodiversity, sustainability, habitat quality and again biodiversity). The additional axis for biodiversity is designed to create three planes, namely, the sustainability–biodiversity plane (S–B plane) in the upper right quadrant, the habitat quality–sustainability plane (H–S plane) in the upper left quadrant, and the biodiversity–habitat quality plane (B–H plane) in the lower left quadrant. Further, a diagonal bisecting line in the lower right quadrant allows the plotting of the SRI value for each species. Therefore, four coordinates per species are labeled on the diagram in Fig. 4. Each ORI’s score is specified to fall in the range 0–2. Each zone is given exactly the same area, with boundary values of 1.16 and 1.63. The probability of any random point falling anywhere within each zone of the square is the same. Color codes are given to each square zone to facilitate the evaluation process. The green (inner) zone is defined to range from 0 to 1.16, the yellow (middle) zone from 1.16 to 1.63, and the red (outer) zone from 1.63 to 2.00. So, three points are plotted in the upper right, upper left, and lower left quadrants for each species, corresponding to the three coordinate pairs. If any one of the ORI scores for any of the three two-component pairs falls into the outer red zone, the resulting coordinate of the pair is assigned to the red zone (Fig. 4). The

3. Application of an ecosystem-based fisheries assessment approach: two examples 3.1. Overview There are more than 250 exploited species in Korean waters, and they are harvested by about 80,000 fishing vessels using 37 gear types (Zhang and Marasco, 2003). Several commercially valuable species, such as small yellow croaker (Larimichthys polyactis), white croaker (Argyrosomus argentatus), red seabream (Pagellus bogaraveo), sharp-toothed eel (Muraenesox cinereus) and some other demersal fish species, are considered to be heavily exploited or depleted (Zhang et al., 1992, 1998; Zhang and Kim, 1999; Zhang et al., 1999; Lee, 1999). Some stocks have been depleted by excessive fishing intensity exerted by over-capitalized fishing fleets. However, land reclamation and coastal pollution, which destroy spawning and nursery grounds along the coastal regions, have contributed to the depressed status of some stocks. A declining pattern in mean trophic levels in Korean marine ecosystems is consistent with overfishing (Zhang and Lee, 2004). To date, Korea has relied on traditional control devices to manage its fisheries. Measures employed include mesh size restrictions, minimum size limits for fish, closed areas/seasons, boat licenses, and gear limitations. After ratifying the UN Convention on the Law of the Sea (UNCLOS) in 1996, the Korean government adopted a total allowable catch (TAC)-based fisheries management system, which was implemented in 1999 (MOMAF, 2000). A number of difficulties have been experienced in employing many of these management measures. For example, mesh and minimum landing size regulations were adopted to avoid the dangers of harvesting fish before they reach full maturity. Such measures alone, however, did not prevent fishing effort from increasing, because the number and fishing power of vessels entering were not limited (MOMAF, 2007a). In addition, regulations to increase the minimum mesh size further were not introduced because of fishermen resistance. Immediate economic pressures stemming from short-term losses resulted in the discounting of future benefits likely to be realized from the introduction of such measures. Closed areas were implemented to allow stocks to reproduce and grow undisturbed by reducing fishing mortality in selected areas, but adequate funds for monitoring were not available. The TAC-based management system also encountered technical problems in the estimation of acceptable biological catch, monitoring and enforcement. Further, the system relies on assessments of fisheries resources based on

C.I. Zhang et al. / Fisheries Research 100 (2009) 26–41

traditional single-species approaches, rather than ecosystem-based approaches. To improve the status of its marine resources, the Korean government in 1998 started a pilot marine ranching program to enhance marine fisheries resources, and to protect and recover marine environments and fish habitats in the Tongyeong marine ranch (20 km2 ), which is located on the southern coast of Korea. Intensive scientific studies on various activities such as: creating artificial reefs, constructing seaweed beds to restore fish habitat, and releasing jacopever rockfish (Sebastes schlegeli) larvae and juveniles were undertaken (MOMAF, 2004). The Tongyeong Marine Ranch Management Council, which is composed of various stakeholders including representatives of local fishermen, central and local government officials, scientists, and NGOs, was given the authority to manage the fishery and other activities. The creation of this marine ranching area provides an opportunity to test the utility of the proposed ecosystem-based fisheries assessment approach and to evaluate impacts on the ecosystem. The large purse seine fishery is one of Korea’s major fisheries. With an annual catch of about 20,000 metric tons, it accounts for more than 20% of total catch of the Korean coastal and offshore fishery. The main fishing ground is around Jeju and Tsushima Islands. Major species taken by the fishery include common mackerel (Scomber japonicus), jack mackerel (Trachurus japonicus), common squid (Todarodes pacificus), hairtail (Trichiurus lepturus), Spanish mackerel (Scomberomorus niphonicus) and yellowtail (Seriola quinqueradiata). Common mackerel accounts for more than 90% of the total catch (Cha et al., 2004; Choi et al., 2004). Since 1999, this fishery has been managed on the basis of annual TACs for common mackerel, jack mackerel and Pacific sardine. Annual TACs are determined by the TAC Management Committee, which is composed of officials from central and regional governments, scientists, representatives of fishermen and NGOs. Because the Tongyeong marine ranch and the large purse seine fishery have been extensively studied, yielding relatively good scientific data, the proposed ecosystem-based fisheries assessment

33

approach was applied to these two cases. One represents a typical commercial fishery and the other is a special fisheries enhancement case. In both cases, the main commercial species were selected to be assessed by the Tier 1 analysis, and the other species were assessed by the Tier 2 analysis. In the Tongyeong marine ranch case, the assessment analysis was conducted for each species before (1998) and after (2006) initiation of marine ranching activities. The assessment for the Korean large purse seine fishery was structured to allow comparison before (1990) and after (2004) the adoption of the TAC system. 3.2. Tongyeong marine ranch At Tongyeong marine ranch, the target species is jacopever rockfish, which is taken in a pole and line fishery. This species was assessed by a Tier 1 analysis, since more scientific data are available and quantitative stock assessment has been conducted for this species. A Tier 2 analysis was conducted for species taken as bycatch: black rockfish (Sebastes inermis), red sea bream (Pagrus major), common sea bass (Lateolabrax japonicas), yellowtail (S. quinqueradiata), and rock bream (Oplegnathus fasciatus), since quantitative data or information were not available for those species. Indicator scores for these species are presented in Appendix Table A1. Because scoring plays an important role in the proposed assessment system, a few examples will help to understand the process. For example, a target prohibited fishing area of 20 km2 was used in evaluating habitat states for jacopever rockfish. Because the area of prohibited fishing was not established in 1998, a score was given the value two. For 2006, a value of 1.22 is assigned because the area is determined to be within the range between the target and limit reference point (Table 4 and Appendix Table A1). As an example of a Tier 2 assessment for black rockfish, a ‘fishing method’ score of two was assigned for the year 1998, because fishing methods and patterns were not evaluated at that time. All fishing methods and patterns were evaluated and changes monitored in 2006, resulting in a score of zero (Table 5 and Appendix Table A1). Detailed meth-

Table 6 Objective risk index (ORI), species risk index (SRI), fishery risk index (FRI), and management status index (MSI) for the Tongyeong marine ranch using the ecosystem-based Tier 1 and Tier 2 fisheries assessment approach. Statistically significant differences between initial and subsequent MSI indices are denoted by *, ** and ***, corresponding to ˛ = 0.05, 0.01 and 0.001 levels, respectively: NS denotes non-significance. Tier

1

Species

Objective

Jacopever rockfish

Black rockfish

Red seabream

Common seabass 2 Black seabream

Yellowtail

Rock bream

FRI

ORI

MSIO

Significance

1998

2006

Sustainability Biodiversity Habitat

1.328 0.768 0.750

0.253 0.364 0.153

80.99 52.59 79.60

** NS **

Sustainability Biodiversity Habitat Sustainability Biodiversity Habitat Sustainability Biodiversity Habitat Sustainability Biodiversity Habitat Sustainability Biodiversity Habitat Sustainability Biodiversity Habitat

1.391 1.667 1.538 1.522 1.667 1.538 1.478 1.778 1.769 1.391 1.556 1.769 1.435 1.889 1.769 1.522 1.889 1.769

0.217 0.444 0.385 0.522 0.667 0.846 0.522 0.444 0.923 0.696 0.667 0.692 0.652 0.667 0.692 0.478 0.667 0.538

84.38 73.33 75.00 65.71 60.00 45.00 64.71 75.00 47.83 50.00 57.14 60.87 54.55 64.71 60.87 68.57 64.71 69.57

*** ** *** *** ** *** *** ** *** *** ** *** *** ** *** *** ** ***

1998 1.101

2006 0.381

SRI

MSIS

Significance

0.256

72.96

***

1.531

0.348

77.23

***

1.574

0.678

56.96

***

1.673

0.629

62.40

***

1.570

0.684

56.43

***

1.696

0.670

60.51

***

1.725

0.561

67.50

***

1998

2006

0.948

MSIF 64.99

Biomass indices used to calculate FRIs are 5.33 in 1998 and 4.12 in 2006 for jacopever rockfish, 0.38 in 1998 and 0.91 in 2006 for black rockfish, 0.80 in 1998 and 0.41 in 2006 for red seabream, 0.18 in 1998 and 0.43 in 2006 for common seabass, 0.08 in 1998 and 0.03 in 2006 for black seabream, 0.18 in 1998 and 1.06 in 2006 for yellowtail, and 0.04 in 1998 and 0.09 in 2006 for rock bream.

34

C.I. Zhang et al. / Fisheries Research 100 (2009) 26–41

Fig. 5. Diagram showing objectives risk indices and species risk indices for the Tongyeong marine ranching area using ecosystem-based Tier 1 and Tier 2 fisheries assessment in (a) 1998 and (b) 2006. A denotes jacopever rockfish, B, black rockfish, C, red seabream, D, common seabass, E, black seabream, F, yellowtail, and G, rock bream. SRIs for A, B, C, D, E, F, and G are 0.948, 1.531, 1.574, 1.673,1.570, 1.696 and 1.725 in 1998, and 0.256, 0.348, 0.678, 0.629, 0.684, 0.670, and 0.561 in 2006, respectively.

ods and data used for scoring other Tier 1 and Tier 2 indicators are explained in MOMAF (2007b). Once scores were assigned to all of the indicators, ORIs were calculated for each of the objectives. ORIs for jacopever rockfish ranged from 0.750 to 1.328 in 1998 (Table 6 and Fig. 5) and from 0.153 to 0.364 in 2006. SRI values were calculated using Eq. (3) with all i s assumed to be equal (0.33). The estimated SRI values for jacopever rockfish are 0.948 for 1998 and 0.256 for 2006, indicating a reduction in the risk level for this species between the two reference years. A Wilcoxon paired-sample nonparametric test was performed to determine the significance of the difference in ORIs and SRIs (Table 6) (Zar, 1999). Differences in all risk indices were statistically significant between the two reference years, with the exception of the ORI associated with the biodiversity objectives for jacopever rockfish. Fig. 5 shows a shift for this Tier 1 species from the yellow zone in 1998 to the green zone in 2006. The diagram for Tier 2 species also shows shifts of all species from the red or yellow zones in 1998 to the green zone in 2006. The ORI and SRI values for all species in this group were lower for 2006 than for 1998 (Table 6). FRI values calculated using Eq. (4) are 1.101 for 1998 and 0.381 for 2006, indicating a 65.0% reduction in the risk level for the fishery between the two reference years. The pattern of ERI values is the same as those for FRI values in the Tongyeong marine ranch, because the pole and line fishery is the only one operating.

3.3. Korean large purse seine fishery Common mackerel was selected for a Tier 1 analysis, because of its importance in the catch (Table 7; Appendix Table A2). Because quantitative data were not available for species taken as bycatch and an endangered species (finless porpoise, Neophocaena phocaenoides), they were assigned to Tier 2. Results reported in Table 7 indicate a reduction in the level of risks for both Tier 1 and 2 species between 1990 and 2004. However, four out of the fourteen reductions in ORI for biodiversity and habitat quality were not significantly different between the reference years, while all changes in ORI for sustainability were significantly different (Table 7). Because this fishery operates in the offshore area, the biodiversity and habitat quality components are relatively less important than the sustainability component. Therefore, SRI values were calculated using Eq. (3), where  for the sustainability is 0.4, while s for both biodiversity and habitat quality are 0.3. The Tier 1 species (common mackerel) shifted from the yellow and red zones in 1990 to the green zone in 2004 (Fig. 6). Likewise, Tier 2 species shifted from the red or yellow zones in 1990 to the yellow or green zones in 2004. FRI values calculated using Eq. (4) were 1.226 for 1990 and 0.457 for 2004, suggesting a 62.7% reduction in the risk level for the fishery between the two reference years. ERI values for the Korean large purse seine ecosystem were not estimated, since there were other

C.I. Zhang et al. / Fisheries Research 100 (2009) 26–41

35

Table 7 Objective risk index (ORI), species risk index (SRI), fishery risk index (FRI), and management status index (MSI) for the Korean large purse seine fishery using the ecosystembased Tier 1 and Tier 2 fisheries assessment approach. Statistically significant differences between initial and subsequent MSI indices are denoted by *, ** and ***, corresponding to ˛ = 0.05, 0.01 and 0.001 levels, respectively: NS denotes non-significance. Tier

1

Species

Common mackerel

Finless porpoise

Horse mackerel

Common squid 2 Hairtail

Spanish mackerel

Yellowtail

FRI

Objective

ORI

MSIO

Significance

1990

2004

Sustainability Biodiversity Habitat

1.585 1.449 0.222

0.406 0.324 0.218

74.38 77.64 1.80

* NS NS

Sustainability Biodiversity Habitat Sustainability Biodiversity Habitat Sustainability Biodiversity Habitat Sustainability Biodiversity Habitat Sustainability Biodiversity Habitat Sustainability Biodiversity Habitat

1.522 1.889 1.727 1.261 1.444 1.727 1.478 1.556 1.000 1.435 1.444 2.000 1.522 1.444 1.455 1.522 1.444 1.455

0.565 1.333 1.091 0.826 1.000 0.818 0.870 1.222 1.000 1.130 1.222 1.636 1.217 1.222 1.091 1.304 1.222 1.091

62.88 29.43 36.83 34.50 30.75 52.63 41.14 21.47 0.00 21.25 15.37 18.20 20.04 15.37 25.02 14.32 15.37 25.02

*** NS ** * ** *** *** ** NS *** ** ** *** ** ** *** ** **

1990 1.226

2004 0.457

SRI

MSIS

Significance

0.325

71.37

*

1.694

0.953

43.74

***

1.456

0.876

39.84

***

1.358

1.014

25.33

***

1.607

1.310

18.48

***

1.478

1.181

20.09

***

1.478

1.216

17.73

***

1990

2004

1.135

MSIF 62.72

Biomass indices used to calculate FRIs are 5.22 in 1990 and 5.67 in 2004 for common mackerel, 0.05 in 1990 and 0.06 in 2004 for finless porpoise, 0.70 in 1990 and 0.55 in 2004 for horse mackerel, 0.05 in 1990 and 0.31 in 2004 for common squid, 0.31 in 1990 and 0.15 in 2004 for hairtail, 0.56 in 1990 and 0.18 in 2004 for Spanish mackerel, and 0.11 in 1990 and 0.08 in 2004 for yellowtail.

fisheries such as the large trawl fishery and the Danish seine fishery, that were not evaluated. Preferably, FRI values for all fisheries should be estimated simultaneously to calculate an ERI value, if possible. 4. Discussion Ecosystem objectives in fisheries management usually begin with high-level national polices or strategies and international agreements. Consequently, they are often broadly stated and hence are difficult to incorporate directly into management assessments. Nevertheless, identification of clearly specified and realistic objectives is critical to the successful integration of ecosystem considerations in fisheries management. A major challenge in incorporating ecosystem objectives within fisheries management is the definition of measurable indicators and cost-effective monitoring programs that relate to ecosystem objectives, as well as the reference points that trigger management actions (Gislason et al., 2000). There are many types of indicators which reflect physical, ecological and socio-economic conditions. Ultimately, the number of indicators depend on the number of objectives identified for the management focus. As Degnobol (2005) observed, “Indicators represent the link between objectives and action in management”. This linkage is perhaps responsible for the interest in indicators that has characterized ecosystem-based fishery management discussions. Kruse et al. (2006) recognized a distinction between ‘contextual’ and ‘management’ indicators. Contextual indicators are used to understand background conditions, which are not controlled by human activities, while management indicators are controlled by management actions. A stepwise process has been suggested by Rice and Rochet (2005) to help facilitate the selection of appropriate indicators for any given situation. First, user needs must be identified. Next, a list of candidate indicators should be developed, and screening criteria identified. Candidate indicators should then be scored

against the screening criteria and scoring results summarized. Finally, the number of indicators should be determined, and the final selection made. While this procedure will facilitate the selection process, in reality, the selection in most cases will be neither easy nor non-controversial. Marine ecosystems have many dimensions, therefore, there are many candidate indicators and suites of indicators that can be employed as operational indicators. A complicating factor is that community or ecosystem-level attributes are difficult to measure directly and the range of their natural variability is not well known. Therefore, the process used to select indicators and set reference points, should fully consider the views of all important stakeholders. In addition, they should be specific to the application. Indicators and reference points selected for use in this study are examples of two Korean cases and their associated species. For other fisheries, indicators and reference points could be established differently (Pauly et al., 1998; Rice and Gislason, 1996; Murawski, 2000). To summarize, we have proposed an assessment method involving the following steps. The selection of the target management unit, i.e., ecosystem, fishery, or species, represents the first step. Once the management unit is selected, stakeholders and experts select ecosystem indicators for each management objective, and determine target and limit reference points. As part of the process, all available data must be identified, evaluated and a decision made as to whether a Tier 1 or Tier 2 analysis is appropriate. Having completed this, the assessment of the system can progress by computing risk indices and evaluating the status for each component, i.e., management objectives, species, fishery and ecosystem. Upon completion of the assessment, the identification and implementation of appropriate management measures can begin. It will be useful to trace thorough the nested system to find the subject or subjects, which resulted in a high risk score. Once this process is completed, necessary corrective actions and enforcement measures can be identified and implemented. In each step the involvement of stakeholders is desirable to achieve consensus. Therefore, it will be

36

C.I. Zhang et al. / Fisheries Research 100 (2009) 26–41

Fig. 6. Diagram showing objectives risk indices and species risk indices for the Korean large purse seine fishery using the ecosystem-based Tier 1 and Tier 2 fisheries assessment approach in (a) 1990 and (b) 2004. A denotes common mackerel, B, finless porpoise, C, horse mackerel, D, common squid, E, hairtail, F, Spanish mackerel, and G, yellowtail. SRIs for A, B, C, D, E, F, and G are 1.135, 1.694, 1.456, 1.358, 1.607, 1.478, and 1.478 in 1990, and 0.325, 0.953, 0.876, 1.014, 1.310, 1.181, and 1.216 in 2004, respectively.

useful to establish a local fisheries management body to facilitate an efficient assessment and to achieve more effective ecosystembased fisheries management. We believe that this proposed method is useful, based on our application to the Tongyeong marine ranch and the Korean large purse seine fishery. These two management units were selected because they have been thoroughly studied and the data are relatively good. Results of the calculations indicated that in both cases most risk indices were reduced significantly between the two reference years. Improvements identified in the various indices were due to a number of factors, which are listed below for each case study. Tongyeong marine ranch:

- more science-based management using intensive stock assessment results improved sustainability, - a local management body (Tongyeong Marine Ranch Management Council) was formed and fishermen actively participated, causing self-regulation that reduced the use of illegal fishing gear and decreased illegal fishing operations in prohibited areas, which improved sustainability and biodiversity, - reduced waste dumping and the implementation of debris removal program improved habitat quality,

- releasing of larvae and juveniles of some species improved sustainability, - creating artificial reefs and artificial seaweed beds improved habitat quality, and - restricted fishing gear regulations improved biodiversity and improved sustainability. Large purse seine fishery: - TAC-based quota management improved sustainability, - representatives of fishermen were appointed as members of the Central TAC Management Committee, improving fishermen’s recognition of the importance of reducing waste dumping, and improving habitat quality, - observer monitoring and reinforcement coupled with fishermen’s self-monitoring against illegal fishing, improved sustainability and biodiversity, and - assignment of landing places, improved sustainability and biodiversity. Our proposed assessment approach has several advantages. First, it is an integrated, holistic approach using a number of management indicators to get single collective indices for objec-

C.I. Zhang et al. / Fisheries Research 100 (2009) 26–41

tives, species, fishery, or ecosystem, unlike other approaches which mostly use individual indicators. Second, the approach is easy to apply. This approach can be applied to any situation even when scientific data are limited. Third, it is possible to evaluate the impact of management practices such as stock rebuilding programs, habitat recovery programs, or alternative management policies. Fourth, it is possible to compare the status of species, fisheries or ecosystems relative to several management objectives, both spatially and temporally, using the management status index. Finally, results lend themselves to graphical analysis, which aids in interpretation by scientists, managers, and stakeholders alike. The major weakness of this approach is the difficulty of selecting appropriate indicators and reference points. Because some indicators are not fully studied, complicating the identification of reasonable reference points, more comprehensive studies on indicators and reference points are necessary. Continued research into ecosystem processes will enhance our ability to link management actions, indicators and ecosystem responses. An additional weakness is the lack of explicit treatment of socio-economic considerations. Once a causal element has been identified, there is not always a process for automatically determining the appropriate management response that will result in reduced risk. However, awareness of a problem does stimulate a discussion as to how that risk might be reduced. Finally, whereas some indicators reflect an ecosystem response (e.g., fish biomass, fishery in balance (FIB) index), others (e.g., habitat protection measures, gear loss) are management actions lacking quantification of realized ecosystem benefits. The analytical method discussed in this paper resembles the ecological risk assessment for the effects of fishing (ERAEF) model developed for Australia (CSIRO, 2005) in some respects. ERAEF evaluates five ecological components similar to sustainability, biodiversity and habitat quality objectives in this study: species type (target species; byproduct and bycatch; and threatened, endangered or protected), habitats, and ecological communities. However, the ERAEF framework involves a hierarchical approach that begins with a qualitative analysis of risk at Level 1. Where risks are detected, ERAEF moves to a semi-quantitative approach at Level 2, and finally to a fully quantitative ‘model-based’ approach at Level 3. The Level 3 quantitative analysis as envisioned in ERAEF is classical population dynamics and ecosystem-level modeling. In contrast, the approach proposed in this study incorporates quantitative analysis throughout the process, provided that the data are available (Tier 1). Qualitative or semi-quantitative anal-

37

ysis is employed only if quantitative data are unavailable (Tier 2). 5. Conclusion An ecosystem-based management strategy for marine fisheries is one that reduces potential fishing impacts while at the same time allowing the extraction of fish resources at levels sustainable for the ecosystem. Predicting the results of any management action is difficult because the dynamics of ecosystems are complex and poorly understood. Methods to design and evaluate operational management strategies have advanced considerably during the last decade (Livingston et al., 2005; Sainsbury et al., 2000; CSIRO, 2005). While substantial progress has been made recently, large gaps in the information needed to support ecosystem-based management still exist. In addition, attention needs to be given to the identification and selection of appropriate objectives and indicators for ecosystems. Ecosystem-based management is an important complement to existing fisheries management approaches. Implementation of an ecosystem-based assessment approach, such as proposed in this paper, should proceed despite current uncertainties regarding ecosystems and their responses to human actions, because the potential benefits of implementation are as large as or greater than the potential risks of inaction (Pikitch et al., 2004). When fishery managers understand the complex ecological and socio-economic environments in which fish and fisheries exist, they will be better able to anticipate the effects that fishery management will have on the ecosystem, as well as the effects that ecosystem change will have on fisheries. Acknowledgments The authors would like to thank Dr. Gordon Kruse and two anonymous reviewers for their useful comments. This work was supported by the Pukyong National University Research Abroad Fund in 2007 (PS-2007-031). This paper was first presented at the Topic Session on “Ecosystem approach to fisheries: Improvements on traditional management for declining and depleted stocks” held at the 2007 PICES Annual Meeting in Victoria, Canada. Appendix A See Tables A1 and A2.

Table A1 Assessment results for the Tongyeong marine ranching area using the ecosystem-based Tier 1 and Tier 2 fisheries assessment approach. (A) Tier 1 (jacopever rockfish) Objective

Attribute

Indicator

Jacopever rockfish 1998

2006

Sustainability

Biomass Fishing intensity Size at first capture Habitat size Community structure Reproductive potential Productivity

Biomass Catch Age at first capture Habitat size FIB indexa FRP indexb Total production of ecosystemc

2 0 2 1.27 1.92 2 0.09

0 0 2 0 0 0 0.53

Biodiversity

Total bycatch Total discards Trophic level Diversity Integrity of functional groups

Bycatch rate Discard rate Mean trophic leveld Diversity indexe Invasive/traditional species in catch

0 2 0.29 1.09 0

0 0 2 0 0.55

38

C.I. Zhang et al. / Fisheries Research 100 (2009) 26–41

Table A1 (Continued ) (A) Tier 1 (jacopever rockfish) Objective

Attribute

Indicator

Habitat damage

Discarded wastes Habitat protection Habitat recovery

Habitat

Jacopever rockfish

Critical habitat damage rate Pollution rate of spawning and nursery ground Lost fishing gear Discarded wastes Prohibited area from fishing No. of artificial reefs Area of artificial seaweed bed

1998

2006

0 0 0 0 2 2 2

0 0 0 0 1.22 0 0

(B) Tier 2 (1998) Objective

Attribute

Indicator

Black rockfish

Red seabream

Common seabass

Black seabream

Yellowtail

Rock bream

Biomass Fishing intensity

CPUEf Restricted access Fishery monitoring and sampling Fishing method Precautionary approach and sensitivity of stock assessment Size at entry Maximum age or age at maturity Adult habitat overlap with juvenile Management plan for fishery Management of IUUg fishery Recovery plan and period for depleted stocks Population structure

1 1 1

2 1 2

2 1 2

2 1 1

1 2 1

2 1 1

2 2

2 2

2 2

2 2

1 2

2 2

2 0

2 0

1 0

2 0

2 0

2 0

1

1

0

1

0

1

2

1

2

1

2

2

1

1

2

1

2

1

2

2

2

1

2

2

2

2

2

2

2

2

2 2 1 1

2 2 1 1

2 2 2 2

1 2 2 2

2 2 2 1

2 2 2 1

2

2

1

1

2

2

0

0

1

1

1

1

2 2 2 2

2 2 2 2

2 2 2 2

2 2 2 2

2 2 2 2

2 2 2 2

2

2

2

2

2

2

2

2

2

2

2

2

Sustainability Size at first capture Life history characteristics

Management

Recovery Genetic structure Total bycatch Total discards Diversity Integrity of functional group Gear restrictions and avoidance tactics

Biodiversity

Habitat damage

Habitat Discarded wastes Habitat protection Habitat recovery

Bycatch Discard No. of species Functional group composition Gear restrictions and avoidance tactics for non-target species Influence of benthic habitat of fishing gear Pollution of habitat Lost fishing gear Discarded wastes Gear restrictions for critical habitat Recovery of physical habitat Recovery of biological habitat

(B) Tier 2 (2006) Objective

Attribute

Indicator

Black rockfish

Red seabream

Common seabass

Black seabream

Yellowtail

Rock bream

Biomass Fishing intensity

CPUEf Restricted access Fishery monitoring and sampling Fishing method Precautionary approach and sensitivity of stock assessment Size at entry Maximum age or age at maturity Adult habitat overlap with juvenile Management plan for fishery Management of IUUg fishery

1 0 0

1 0 1

1 0 1

1 0 1

1 0 1

1 0 1

0 0

0 1

0 1

0 1

0 1

0 0

0 0

0 0

0 0

1 0

1 0

2 0

0

0

0

1

0

0

0

1

1

1

1

0

0

0

0

0

0

0

Sustainability Size at first capture Life history characteristics

Management

C.I. Zhang et al. / Fisheries Research 100 (2009) 26–41

39

Table A1 (Continued ) (B) Tier 2 (2006) Objective

Attribute

Indicator

Black rockfish

Red seabream

Common seabass

Black seabream

Yellowtail

Rock bream

Recovery

Recovery plan and period for depleted stocks Population structure

0

1

1

1

1

0

2

2

2

2

2

0

Genetic structure

Biodiversity

Total bycatch Total discards Diversity Integrity of functional group Gear restrictions and avoidance tactics

Bycatch Discard No. of species Functional group composition Gear restrictions and avoidance tactics for non-target species

0 2 0 0

1 2 0 0

0 2 0 0

1 2 0 0

1 2 0 0

1 2 0 0

0

0

0

0

0

0

Habitat damage

Influence of benthic habitat of fishing gear Pollution of habitat Lost fishing gear Discarded wastes Gear restrictions for critical habitat Recovery of physical habitat Recovery of biological habitat

0

0

0

0

0

0

1 1 1 0

1 2 2 1

1 2 2 1

1 2 1 0

1 2 1 0

1 2 1 0

0

0

1

1

1

0

0

0

0

1

1

0

Habitat Discarded wastes Habitat protection Habitat recovery

a b c d

e

TL

TL

FIB index (fishery in balance): FIB = log(Yi (1/TE) i ) − log(Y0 (1/TE) 0 ) (Pauly et al., 2000). FRP index (fish reproduction potential): FRP = log(Yi MRi /qfi ) − log(Y0 MR0 /qf0 ) (Lee et al., 2007). Total production of the ecosystem (unit: mt/km2 /year) (Christensen and Pauly, 1992). Mean trophic level from research surveys (Pauly et al., 1998). N 

Diversity index: DI = −

Pj ln Pj (modified from Shannon and Wiener (1963)), where N is the total number of individuals, Pj is proportion of each species.

j=1 f g

CPUE: catch per unit effort. IUU: illegal, unregulated and unreported fishing.

Table A2 Assessment results for the Korean large purse seine fishery using the ecosystem-based Tier 1 and Tier 2 fisheries assessment approach. (A) Tier 1 (common mackerel) Objective

Attribute

Indicator

Common mackerel 1990 2004

Sustainability

Biomass Fishing intensity Size at first capture Habitat size Community structure Reproductive potential

CPUEa Catch Age at first capture Habitat size FIB indexb FRP indexc

2 2 2 0.68 0 2

0 0 1.83 0.56 0.86 0

Biodiversity

Total bycatch Total discards Trophic level Diversity Integrity of functional groups

Bycatch rate Discard rate Mean trophic leveld Diversity indexe Invasive/traditional species in catch

2 2 0.78 0 1.36

0 0 0.18 2 0.09

Habitat damage

Critical habitat damage rate Pollution rate of spawning and nursery ground Lost fishing gear Discarded wastes Prohibited area from fishing

0 0.83 0 0.50 0

0 0.68 0 0.63 0

Habitat Discarded wastes Habitat protection (B) Tier 2 (1990) Objective

Attribute

Indicator

Finless porpoise

Horse mackerel

Common squid

Hairtail

Spanish mackerel

Yellowtail

Biomass Fishing intensity

CPUEf Restricted access Fishery monitoring and sampling Fishing method Precautionary approach and sensitivity of stock assessment Size at entry Maximum age or age at maturity

2 0 1

1 2 2

1 2 2

1 2 2

1 2 2

1 2 2

2 2

2 1

1 1

1 1

1 2

1 2

2 1

1 0

2 0

2 0

2 0

2 0

Sustainability Size at first capture Life history characteristics

40

C.I. Zhang et al. / Fisheries Research 100 (2009) 26–41

Table A2 (Continued ) (B) Tier 2 (1990) Objective

Attribute

Indicator

Finless porpoise

Horse mackerel

Common squid

Hairtail

Spanish mackerel

Adult habitat overlap with juvenile Management

2

1

1

0

0

0

Management plan for fishery Management of IUUg fishery Recovery plan and period for depleted stocks Population structure

2 1 2

1 0 2

2 2 2

2 2 2

2 2 2

2 2 2

2

2

2

2

2

2

Total bycatch Total discards Diversity Integrity of functional Group Gear restrictions and avoidance tactics

Bycatch Discard No. of species Functional group composition

2 2 2 1

2 2 1 1

2 2 1 2

2 2 1 1

2 2 1 1

2 2 1 1

Gear restrictions and avoidance tactics for non-target species

2

1

1

1

1

1

Habitat damage

Influence of benthic habitat of fishing gear Pollution of habitat Lost fishing gear Discarded wastes Gear restrictions for critical habitat

1

1

0

2

0

0

2 2 2 2

2 2 2 2

1 2 2 1

2 2 2 2

2 2 2 2

2 2 2 2

Recovery Genetic structure

Biodiversity

Habitat Discarded wastes Habitat protection

Yellowtail

(B) Tier 2 (2004) Objective

Attribute

Indicator

Finless porpoise

Horse mackerel

Common squid

Hairtail

Spanish mackerel

Yellowtail

Biomass Fishing intensity

CPUEf Restricted access Fishery monitoring and sampling Fishing method Precautionary approach and sensitivity of stock assessment Size at entry Maximum age or age at maturity Adult habitat overlap with juvenile Management plan for fishery Management of IUUg fishery Recovery plan and period for depleted stocks Population structure

1 0 1

1 1 1

1 1 1

1 1 2

1 1 2

1 1 2

0 0

0 0

0 0

0 1

0 1

1 2

0 1

2 0

2 0

2 0

2 0

2 0

1

0

0

0

0

0

0 1 2

0 1 2

0 2 2

1 2 2

2 2 2

1 2 2

2

2

2

2

2

2

Bycatch Discard No. of species Functional group composition

1 1 1 2

1 2 0 1

2 2 0 1

2 2 0 1

2 2 0 1

2 2 0 1

Gear restrictions and avoidance tactics for non-target species

2

1

1

1

1

1

Influence of benthic habitat of fishing gear Pollution of habitat Lost fishing gear Discarded wastes Gear restrictions for critical habitat

0

0

0

2

0

0

2 0 2 2

2 0 2 1

2 1 2 1

2 0 2 2

2 0 2 2

2 0 2 2

Sustainability Size at first capture Life history characteristics

Management Recovery Genetic structure

Biodiversity

Total bycatch Total discards Diversity Integrity of functional group Gear restrictions and avoidance tactics Habitat damage

Habitat Discarded wastes Habitat protection a b c d

e

CPUE: catch per unit effort. TL TL FIB index (fishery in balance): FIB = log(Yi (1/TE) i ) − log(Y0 (1/TE) 0 ) (Pauly et al., 2000). FRP index (fish reproduction potential): FRP = log(Yi MRi /qfi ) − log(Y0 MR0 /qf0 ) (Lee et al., 2007). Mean trophic level from research surveys (Pauly et al., 1998). N 

Diversity index: DI = −

Pj ln Pj (modified from Shannon and Wiener (1963)), where N is the total number of individuals, Pj is proportion of each species.

j=1 f g

CPUE: catch per unit effort. IUU: illegal, unregulated and unreported fishing.

C.I. Zhang et al. / Fisheries Research 100 (2009) 26–41

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