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Species Distribution Models for Management of Fisheries and MPAs: Innovative Approaches to Cost-Effective Data Collection

Award Period: 

Monday, February 1, 2016 to Wednesday, January 31, 2018

Award Amount: 

$220 887

Agency Name: 

UC Sea Grant

Award Number: 

R/HCME-25A

PI First Name: 

Jenn

PI last name: 

Caselle

MSI Person: 

Area/s of Research: 

Abstract: 

Project summary - As marine resource managers continue to adopt ecosystem-based approaches, there is a growing need to acquire reliable spatial information on species distributions (Fielding and Bell 1997, Manel et al. 1999, Costello et al. 2010). A landscape (seascape) approach that (i) identifies habitat and environmental features with which species associate, (ii) quantifies the numerical relationships of species with those habitats, and (iii) identifies the geographic distribution of habitats across a species range, is central to advancing our understanding of how and why marine populations are distributed throughout their environment and, as a result, can better inform a variety of management applications (Sala et al. 2002, Friedlander et al. 2006, Robinson et al. 2011). California has invested heavily in monitoring of coastal waters and as the baseline period of MPA monitoring comes to a close, future investment in long-term monitoring will require cost-effective, statistically robust methods.  Here we propose to develop and apply advanced species distribution models (SDMs) while simultaneously testing new monitoring methods for coastal waters in southern California. Using state-of-the-art methods in spatial analysis, we will create highly resolved maps of geomorphic, biotic, geographic and oceanographic variables. The maps will be coupled with in situ survey data of ecologically and commercially important marine organisms using statistical models such as generalized linear models (GLMs) and generalized additive models (GAMs), which allow for typically nonlinear relationships between species and habitat and have, therefore, become widely used in modeling the distribution and abundance of species (Guisan and Zimmermann 2000). In situ survey data will be collected using established methods in conjunction with new methods. Newly designed stereo drop camera surveys will be explicitly compared to SCUBA surveys to evaluate the level of correspondence between the two methods as well as cost effectiveness and the potential for citizen science application.