2 research outputs found
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An indicator‐based decision framework for the northern California red abalone fishery
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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Use of management strategy evaluation to understand the value of citizen science in managing an iconic California recreational fishery
Data-limited fisheries present significant challenges to fisheries management around the world. Landings data represent the simplest and most common source of fishery information, but length data of harvested species can offer particularly useful insight into the strength of fishing pressure and the status of stocks. However, unbiased length data can be difficult and costly to collect, which highlights a need for understanding the utility of non-conventional data collection programs, such as those generated by community members and citizen science programs to improve management decision-making. In this study, our objective was to understand the value of citizen science for management using the iconic California recreational red abalone (Haliotis rufescens) dive fishery. To accomplish this, we employed management strategy evaluation (MSE) to simulate this benthic invertebrate fishery that was sampled by two different fishery independent survey protocols: a community science survey program led by trained volunteers and a professional science survey program led by a state agency. We subjected the data to a range of uncertainties, by including time-varying life history parameters, environmental variability, and effective sample size scenarios, to understand the management level consequences of each survey methodology. Our results show that community science program data collection can serve as a high-quality data source, can be linked directly to fisheries management decisions via a Harvest Control Rule (HCR), and can be a useful information source even in the absence of conventional data sources. Our results are specific to the California red abalone fishery, but they also highlight the potential broader value of community science data collection programs for improving information content of small-scale and recreational fisheries.•Accelerating stressors to marine ecosystems elevate the need for new data sources that allow timely management decisions.•Our study represents a quantitative evaluation of citizen/community science in meeting fisheries management objectives.•We demonstrate that community science data collection programs can be explicitly linked to fisheries harvest control rules.•Citizen science data can supplement conventional data sources, and can even stand alone to inform decisions that meet management objectives.•Linking data collection to management decisions can illuminate previously ignored data sources and elevate the value of citizen science