Ecological applications : a publication of the Ecological Society of America | 2019

Setting expected timelines of fished population recovery for the adaptive management of a marine protected area network.

 
 
 
 
 
 
 

Abstract


Adaptive management of marine protected areas (MPAs) requires developing methods to evaluate whether monitoring data indicate that they are performing as expected. Modeling the expected responses of targeted species to a MPA network, with a clear timeline for those expectations, can aid in the development of a monitoring program that efficiently evaluates expectations over appropriate time frames. Here we describe the expected trajectories in abundance and biomass following MPA implementation for populations of 19 nearshore fishery species in California. To capture the process of filling in the age structure truncated by fishing, we used age-structured population models with stochastic larval recruitment to predict responses to MPA implementation. We implemented both demographically open (high larval immigration) and closed (high self-recruitment) populations to model the range of possible trajectories as they depend on recruitment dynamics. From these simulations, we quantified the time scales over which anticipated increases in abundance and biomass inside MPAs would become statistically detectable. Predicted population biomass responses range from little change, for species with low fishing rates, to increasing by a factor of nearly seven, for species with high fishing rates before MPA establishment. Increases in biomass following MPA implementation are usually greater in both magnitude and statistical detectability than increases in abundance. For most species, increases in abundance would not begin to become detectable for at least ten years after implementation. Overall, these results inform potential indicator metrics (biomass), potential indicator species (those with a high fishing:natural mortality ratio), and time frame (>10 years) for MPA monitoring assessment as part of the adaptive management process. This article is protected by copyright. All rights reserved.

Volume None
Pages \n e01949\n
DOI 10.1002/eap.1949
Language English
Journal Ecological applications : a publication of the Ecological Society of America

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