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Abstract The number of protected areas that restrict or prohibit harvest of wild populations is growing. In general, protected areas are expected to increase the abundance of previously‐harvested species. Whether a protected area achieves this expectation is typically evaluated by assessing trends in abundance after implementation. However, the underlying assumption that harvest has actually ceased is rarely tested directly. Determining whether illegal harvest (poaching) has continued in a protected area is important to planning enforcement and adaptive management. Here, we estimated harvest rates for four kelp forest fish species inside marine protected areas (MPAs) and non‐MPA reference sites in the California Channel Islands, from 2003 (when MPAs were implemented) to 2017. We estimated harvest by fitting a size‐structured population model to survey data. Overall, harvest rates were effectively zero in MPAs but much higher in non‐MPA sites. This indicates successful adherence to MPA regulations, and possible displacement of fishing effort to reference sites. However, some poaching was detected in two MPA sites, highlighting the importance of assessing this quantity. This modeling approach could provide a tool to complement the long‐term management of MPA networks, particularly given the difficulty of acquiring harvest rate data at the spatial scale of individual MPAs.
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Setting ecological expectations for adaptive management of marine protected areas
Abstract Marine Protected Areas (MPAs) are being implemented worldwide, yet there are few cases where managers make specific predictions of the response of previously harvested populations to MPA implementation.Such predictions are needed to evaluate whether MPAs are working as expected, and if not, why. This evaluation is necessary to perform adaptive management, identifying whether and when adjustments to management might be necessary to achieve MPA goals.Using monitoring data and population models, we quantified expected responses of targeted species to MPA implementation and compared them to monitoring data.The model required two factors to explain observed responses in MPAs: (a) pre‐MPA harvest rates, which can vary at local spatial scales, and (b) recruitment variability before and after MPA establishment. Low recruitment years before MPA establishment in our study system drove deviations from expected equilibrium population size distributions and introduced an additional time lag to response detectability.Synthesis and applications. We combined monitoring data and population models to show how (a) harvest rates prior to Marine Protected Area (MPA) implementation, (b) variability in recruitment, and (c) initial population size structure determine whether a response to MPA establishment is detectable. Pre‐MPA harvest rates across MPAs plays a large role in MPA response detectability, demonstrating the importance of measuring this poorly known parameter. While an intuitive expectation is for response detectability to depend on recruitment variability and stochasticity in population trajectories after MPA establishment, we address the overlooked role of recruitment variability before MPA establishment, which alters the size structure at the time of MPA establishment. These factors provide MPA practitioners with reasons whether or not MPAs may lead to responses of targeted species. Our overall approach provides a framework for a critical step of adaptive management.
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- PAR ID:
- 10360474
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Journal of Applied Ecology
- Volume:
- 56
- Issue:
- 10
- ISSN:
- 0021-8901
- Page Range / eLocation ID:
- p. 2376-2385
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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