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Title: 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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Award ID(s):
1909303 1435473 1734999
NSF-PAR ID:
10360474
Author(s) / Creator(s):
 ;  ;  ;  ;  ;  ;  ;  
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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