Management strategy evaluation of a multi-indicator adaptive framework for data-limited fisheries management

Harford, William J.; Gedamke, Todd; Babcock, Elizabeth A.; Carcamo, Ramon; McDonald, Gavin; Wilson, Jono R.

doi:10.5343/bms.2016.1025

Cited by 23 publications

(15 citation statements)

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“…As it was applied here, MSE provided guidance on decision tree design, and in doing so, illustrated how pragmatism will be required in implementing an indicator-based approach. Pragmatism was reflected in our attempt to design a management strategy that reconciled capacity for achieving fishery objectives against practical impediments of data availability and data quality (Cadrin and Pastoors 2008, Dowling et al 2015b, Harford et al 2016. We also demonstrated that data-limited methods should be examined cautiously and be subjected to simulation testing.…”

Section: Discussionmentioning

confidence: 91%

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An indicator‐based decision framework for the northern California red abalone fishery

Harford

Dowling

Prince³

et al. 2019

Ecosphere

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Among abalone species that were once harvested along the California coastline, red abalone (Haliotis rufescens) supports the remaining recreational fishery. To support development of a red abalone fishery management plan, non-governmental organizations have initiated expanded data collection and developed fishery management strategies. The latter is the subject of this study, as we present a management strategy evaluation (MSE) of a multi-indicator decision tree. The decision tree relies on landings from each of 56 fishing sites and length frequency information collected during fishery-independent diver surveys at a subset of sites. The decision tree was designed to cope with existing data limitations and to ensure that localized meta-population dynamics were adequately considered in decision-making. It was also necessary to balance the potential for localized abundance changes with the practical issue of implementing fishery regulations at larger spatial scales. The MSE demonstrated that undesirably low stock sizes could be avoided while also continuing to maintain a viable fishery, even under environmental conditions that are detrimental to abalone populations. Under less-severe environmental conditions, stock size was maintained, on average, above the biomass associated with production of maximum sustainable yield. Our discussion centers on steps that were taken to refine the decision tree and to incorporate feedback from scientists and stakeholders and to facilitate transparent evaluation of management options.

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Section: Discussionmentioning

confidence: 91%

“…, Harford et al. ). We also demonstrated that data‐limited methods should be examined cautiously and be subjected to simulation testing.…”

Section: Discussionmentioning

confidence: 99%

An indicator‐based decision framework for the northern California red abalone fishery

Harford

Dowling

Prince³

et al. 2019

Ecosphere

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“…In this situation, the Multi‐indicator approach would be suited to balancing performance metrics while also achieving management objectives (Harford et al. ), as evident by slightly higher long‐term and short‐term yield when compared with the other candidate DLMs.…”

Section: Discussionmentioning

confidence: 99%

“…; Caddy ; Harford et al. ). Alternatively, decision trees can be used to parse information from each indicator into a sequence of decision‐making steps, which allows management responses to reflect a variety of different circumstances (Dowling et al.…”

Section: Discussionmentioning

confidence: 99%

“…For example, if Puerto Rico Yellowtail Snapper were more severely depleted (i.e., current biomass between 5% and 20% unfished biomass) than initially parameterized (36−59%), CPUE Target assuming a near optimum stock condition during the reference period would no longer meet the performance criteria. In this situation, the Multi-indicator approach would be suited to balancing performance metrics while also achieving management objectives (Harford et al 2016), as evident by slightly higher long-term and short-term yield when compared with the other candidate DLMs.…”

Section: Data-limited Fisheries Stock Evaluationsmentioning

confidence: 99%

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Working Towards a Framework for Stock Evaluations in Data‐Limited Fisheries

Sagarese

Rios

Cass-Calay

et al. 2018

N American J Fish Manag

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Data‐limited approaches to managing fisheries are widespread in regions where insufficient data prevent traditional stock assessments from determining stock status with sufficient certainty to be useful for management. Where severe data limitations persist, a catch‐only approach is commonly employed, such as in the U.S. Caribbean region. This approach, however, has not received the level of scrutiny required to determine the potential long‐term risks (e.g., probability of overfishing) to fish stocks. In this study, we present a framework for comparison and implementation of data‐limited methods, including the static Status Quo approach, which uses average catch landings. Candidate species for stock evaluation were identified through a data triage and included Yellowtail Snapper Ocyurus chrysurus (Puerto Rico), Queen Triggerfish Balistes vetula (St. Thomas and St. John), and Stoplight Parrotfish Sparisoma viride (St. Croix). Feasible data‐limited methods, based on data availability and quality, included empirical indicator approaches using relative abundance (i.e., catch per unit effort) or mean length. Results from the management strategy evaluation support the use of adaptive data‐limited methods, which incorporate feedback in contrast to the static Status Quo approach. The proposed framework can help guide the development of catch advice for dynamic fisheries management in data‐limited regions.

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