Scientific tools to support the practical implementation of ecosystem-based fisheries management

Smith, Anthony D. M.; Fulton, Elizabeth A.; Hobday, AJ; Smith, David C.; Shoulder, P.

doi:10.1093/icesjms/fsm041

Cited by 330 publications

(231 citation statements)

References 12 publications

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“…Specifically, an HCR could act on both P obj and the related P x indicator(s) (Figure 10) to adjust catches up or down. However, a full examination of P x -based HCRs requires a management strategy evaluation (MSE; Smith 1994a; Sainsbury et al 2000;Smith et al 2007) and is hence beyond the scope of this study. Using Froese's (2004) P x values to interpret catchbased length compositions in the context of status determination remains less than ideal in several ways.…”

Section: Length-based Reference Points and Harvest Control Rulesmentioning

confidence: 99%

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Length‐Based Reference Points for Data‐Limited Situations: Applications and Restrictions

2009

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Current fisheries management policies generally require an assessment of stock status, which is a difficult task when population and fisheries data are limited. Three simple metrics based on catch length compositions (i.e., that reflect exclusive take of mature individuals, P mat; that consist primarily of fish of optimal size, the size at which the highest yield from a cohort occurs, P opt; and that demonstrate the conservation of large, mature individuals, P mega) can be used to monitor population status relative to exploitation. The metrics (collectively referred to as Px) were intended to avoid growth and recruitment overfishing, but there was no quantitative linkage to stock status and calculation of future sustainable catches. We attempt to make this connection by exploring the relationship of Px measures to fishing mortality and spawning biomass (SB). The relationships are compared specifically to the current target reference point (0.4 times the virgin, or unfished, SB [SB0]) and limit reference point (0.25SB0) used for the U.S. West Coast groundfish fishery by using simulations based on a deterministic age‐structured population dynamics model. Sensitivity to fishery selectivity, life history traits, and recruitment compensation (steepness) is explored. Each Px measure showed a wide range of possible values depending on fishery selectivity, steepness, and the ratio of the length at maturity (L mat) to the optimal fishing length (L opt). Although the values of Px may be compatible with sustainable fishing, these values are not always sufficient to ensure stock protection from overfishing. Moreover, values for Px cannot be interpreted adequately without knowledge of the selectivity pattern. A new measure, P obj (the sum of P mat, P opt, and P mega), is introduced to distinguish selectivity patterns and construct a decision tree for development of stock status indicators. Heuristic indicator values are presented to demonstrate the utility of this approach. Although several caveats remain, this approach builds on the recommendations of previous literature by giving further guidance related to interpreting catch length composition data under variable fishery conditions without collecting additional information. It also provides a link to developing harvest control rules that inform proactive fisheries management under data‐limited conditions.

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Section: Length-based Reference Points and Harvest Control Rulesmentioning

confidence: 99%

“…Such approaches strive to apply transparent protocols to simple or limited data. However, the ability to validate these methods and use them to inform future catches remains a formidable task (Rochet and Trenkel 2003;Jennings and Dulvy 2005;Smith et al 2007). …”

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confidence: 99%

Length‐Based Reference Points for Data‐Limited Situations: Applications and Restrictions

2009

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“…Tett et al (2013) In a socio-economic context "The restoration, and improvement where appropriate, A function of exposure and effect which is more appropriate when an assessment of on-going (current) pressure is needed (Smith et al, 2007).…”

Section: Recoverymentioning

confidence: 99%

Cumulative effects assessment: proof of concept marine mammals

Piet¹,

Boon²,

Jongbloed³

et al. 2017

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Piet, G.J 1 ., Boon, A 2 . Jongbloed, R 1 ., van der Meulen, M 2 ., Tamis, J 1 . van der Wal, J.T 1 .Teal ,L SummaryThis development of the framework and approach for a Cumulative Effects Assessment (CEA) is based on a literature review. From this we adopted several definitions that guided this development.• A CEA is understood as "a systematic procedure for identifying and evaluating the significance of effects from multiple sources/activities and for providing an estimate on the overall expected impact to inform management measures. The analysis of the causes (source of pressures and effects), pathways and consequences of these effects on receptors is an essential and integral part of the process".• Cumulative effects are "the incremental impact of the action when added to the other past, present and reasonably foreseeable actions". In this approach we only consider a (cumulative) effect significant if it has an impact on a relevant ecosystem component.Therefore our framework and approach for a CEA is based on all human activities that may have a potential impact on any relevant (from a policy perspective) ecosystem component at an appropriate spatio-temporal scale.The literature also identified some key challenges that need to be addressed for CEA to evolve into a consistent, appropriate tool to assist decision-making. These challenges included• A clear distinction of the receptor-led CEA from the dominating stressor-led Environmental Impact Assessment (EIA) approaches and• Enabling CEA to provide ecosystem-relevant information at an appropriate regional scale.Therefore this CEA is explicitly developed to be a receptor-led and fully integrated framework, i.e.involving multiple occurrences of multiple pressures (from single and/or different sources) on multiple receptors, as opposed to other existing approaches dealing with only a subset of those pressures or receptors, hence our use of the phrase iCEA for integrated CEA. As a proof of concept for this iCEA we selected one receptor, the ecosystem component marine mammals.From the literature review we adopted (and slightly modified) a risk-based framework for defining and undertaking cumulative effects assessments which is aligned to the work in the OSPAR IntersessionalCorrespondence Group on Cumulative (ICG-C) Effects and the ICES Working Group on IntegratedAssessments of the North Sea (WGINOSE), thereby ascertaining this framework and approach is wellplaced within ongoing international North Sea initiatives. Furthermore, the CEA framework in this study should contribute to national North Sea policymaking, with a specific focus on the Marine Strategy framework Directive (MSFD). This literature review is presented in Chapter 1.Our iCEA framework consists of four phases each corresponding to a chapter in this report:1. Conception. This is where purpose and scope are defined (see Chapter 2). 3. Execution (importance). Here we establish the relative importance of each impact chain using a risk-based approach that calculates "Impact Risk", i.e. the contribution of...

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“…These ecosystems all support unique fauna and flora (Butler et al 2010). Australia is well prepared in terms of its current modelling capability and approaches for both inland aquatic ecosystems (Tomlinson and Davis 2010) and coastalmarine ecosystems (McDonald et al 2006;Smith et al 2007a). The current toolbox of modelling approaches includes applications for modelling the impacts of climate change from a social CSIRO PUBLISHING Marine and Freshwater Research, 2011, 62, 1132-1147 www.publish.csiro.au/journals/mfr and economic perspective (e.g.…”

Section: Introductionmentioning

confidence: 99%

Modelling climate-change effects on Australian and Pacific aquatic ecosystems: a review of analytical tools and management implications

Plagányi

Bell

Bustamante

et al. 2011

Mar. Freshwater Res.

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Climate change presents significant challenges to modelling and managing aquatic resources. Equilibrium assumptions common in many modelling approaches need to be replaced by formulations that allow for changing baselines and integration of ongoing changes and adaptations by species, ecosystems and humans. As ecosystems change, so will the ways humans use, monitor and manage them. Consequently, adaptive management loops and supporting tools deserve more prominence in the management toolbox. Models are critical tools for providing an early understanding of the challenges to be faced by integrating observations and examining possible solutions. We review modelling tools currently available to incorporate the effect of climate change on marine and freshwater ecosystems, and the implications for management of natural resources. System non-linearity can confound interpretations and hence adaptive management responses are needed that are robust to unexpected outcomes. An improvement in the ability to model the effects of climate change from a social and economic perspective is necessary. The outputs from ‘end-to-end’ and socio-ecological models can potentially inform planning, in both Australia and the Pacific region, about how best to build resilience to climate change. In this context, the importance of well directed data-collection programs is also emphasised. Lessons from this region, which is advanced with regard to modelling approaches, can guide increased use of models to test options for managing aquatic resources worldwide.

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Scientific tools to support the practical implementation of ecosystem-based fisheries management

Cited by 330 publications

References 12 publications

Length‐Based Reference Points for Data‐Limited Situations: Applications and Restrictions

Length‐Based Reference Points for Data‐Limited Situations: Applications and Restrictions

Cumulative effects assessment: proof of concept marine mammals

Modelling climate-change effects on Australian and Pacific aquatic ecosystems: a review of analytical tools and management implications

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