97th ESA Annual Meeting (August 5 -- 10, 2012)

COS 2-5 - Spatiotemporal trends in marine biodiversity in the Northeast Pacific: Linking patterns to climate and fisheries management

Monday, August 6, 2012: 2:50 PM
B112, Oregon Convention Center
Susan E. Hilber1, Allison K. Barner2, Cassandra E. Benkwitt3, Kate S. Boersma4, Elizabeth B. Cerny-Chipman2, Kurt E. Ingeman2, Tye L. Kindinger2, Jonathan D. Lee5, Amy J. Lindsley1, Jessica N. Reimer3, Jennifer C. Rowe1, Chenchen Shen2, Kevin A. Thompson1, Lindsey L. Thurman1 and Selina S. Heppell1, (1)Fisheries and Wildlife, Oregon State University, Corvallis, OR, (2)Integrative Biology, Oregon State University, Corvallis, OR, (3)Zoology, Oregon State University, Corvallis, OR, (4)Biology, University of San Diego, San Diego, CA, (5)Geographic Information Science, Oregon State University, Corvallis, OR
Background/Question/Methods

Patterns of biodiversity vary in space and time and are strongly influenced by human activities and climate conditions. Increasing human pressures on marine ecosystems and emphasis on ecosystem-based management (EBM) requires an evaluation of the drivers of biodiversity over large spatial scales.  Specifically, we ask the questions:  how does the diversity of fishes and macroinvertebrates change spatio-temporally, and how are these changes in biodiversity related to climate trends and fisheries management, particularly trawl effort and marine protected areas?   

We used the NOAA West Coast Groundfish Bottom Trawl Survey (WCGBT), from 2003-2010, to map the biodiversity of demersal fishes and macroinvertebrates captured on the continental shelf and slope between depths of 55-1,280m. Species abundance was standardized as biomass over area swept (kg/ha).  We mapped spatio-temporal diversity patterns using species richness and Shannon diversity index, and assessed sampling effort using species accumulation curves.  We used a variety of tools to determine the degree of spatial and temporal autocorrelation and correlations between diversity metrics and predictor variables.  To infer which predictors are most influential, we are employing multivariate tools, including hierarchical partitioning and non-parametric multiplicative regression.

Results/Conclusions

The WCGBT encountered 233 fishes and 310 invertebrates.  At the largest scales, shallow areas south of Cape Mendocino consistently had the highest richness and diversity overall.  In contrast, moderate inter-annual variability was evident at smaller scales in more northern latitudes.  Biodiversity demonstrated low but positive spatial auto-correlation up to a scale of 50-75km.  Invertebrate richness showed a positive relationship with depth; conversely fish richness decreased at increasing depths.  In fish, richness was inversely related to latitude across the entire coastline.  However at the regional scale, fish richness increased with latitude south of Point Conception and decreased northward of Point Conception.

This study is one of the first to map biodiversity across the continental shelf of the western US.  Results from this study will elucidate the drivers of marine biodiversity in the Northeast Pacific as a consequence of natural and human-induced processes.  While fishing effort is regulated, the stochastic effects of climate change are much less predictable; both are powerful explanatory variables of spatio-temporal trends in marine biodiversity in this region.  Gaining insight into how these drivers influence patterns of diversity is a first step in the direction of broadening fisheries conservation goals and ultimately informing EBM decisions.