Resources

Here we review [assessment] methods...gleaned from the literature, for establishing reference points for data-poor situations. We present a new framework to help managers and stakeholders consider and choose appropriate analytical methods and alternative management approaches, based on available data (type, quantity, and quality) and feasibility constraints (scale, value and implementation costs). We highlight limitations and considerations for each method and illustrate the use of our framework by presenting case-study examples.

Our General Resilience Attributes Checklist draws on lists from The Stockholm Resilience Center; The Resilience Alliance + Transition Movement; and a recent examination of specific climate-resilience criteria for fisheries. Use this list of system resilience attributes to guide your research and examination of your fishery system. Seek to understand if each item is present, partially present, or absent in your system, and then consider ways you might work to fill the gaps where possible.

Worksheet to help fishery managers and stakeholders walk through the goal-setting process, which should be done together. Worksheet should be considered a rough framework only. If specific goals and objectives important to your fishery do not seem to fit into any of the categories herein, they should be included anyway. They key is to identify where stakeholders in your system want your fishery to be in the short-, medium- and long-term future, determine if there are tradeoffs between any of those objectives, and then define a finalized list of goals that everyone can agree on. It will also be critical to identify which goals can be worked on now, given current capacity, and what will need to be tackled later on in the adaptive management process.

This document was designed to walk fishery managers and stakeholders through steps 7 and 8 of the FISHE process: Performance Indicators (PIs), Reference Points (RPs), and Harvest Control Rules (HCRs). Us it in combination with the Excel worksheets (PI-RP-HCR Worksheet) to identify PIs that can help to track fishery progress towards management goals, to select appropriate RPs for each PI, and to define effective and appropriate HCRs that will dictate actions taken in response to the results of the detailed stock assessments conducted at FISHE Step 9.

A management strategy evaluation (based on five species in the California, USA, nearshore fishery) of control rules that reduce relative fishing effort as a function of the ratio of fish density outside versus inside no-take marine reserves (as a measure of depletion) showed that although the control rules allowed effort to increase at first, in the long term, they were effective at maintaining spawning stock biomass and yield for all simulated species, including depleted ones.

Peer-reviewed study that evaluates the potential for ensemble averages and superensemble models (ensemble methods) to improve estimates of population status and trend for fisheries.

An assessment of methods to improve fisheries data collection and monitoring efforts to inform stock assessment and management.

Using length-frequency of the catch, three simple and easily understood indicators are estimated to assess the status and trends of the fishery.

Excel workbook containing worksheets to aid in the application of the Catch Curve, MPA Catch Curve, LBAR, and Length-Based SPR assessment methods. See accompanying Length Based Methods Primer for more information. The Downloadable Workbook also contains a version of this workbook filled in with examples, and an example data set to use when learning this method.

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, Pmat; that consist primarily of fish of optimal size, the size at which the highest yield from a cohort occurs, Popt; and that demonstrate the conservation of large, mature individuals, Pmega) can be used to monitor population status relative to exploitation.