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Characterising and predicting benthic biodiversity for conservation planning in deepwater environments.

ABSTRACT: Understanding patterns of biodiversity in deep sea systems is increasingly important because human activities are extending further into these areas. However, obtaining data is difficult, limiting the ability of science to inform management decisions. We have used three different methods of quantifying biodiversity to describe patterns of biodiversity in an area that includes two marine reserves in deep water off southern Australia. We used biological data collected during a recent survey, combined with extensive physical data to model, predict and map three different attributes of biodiversity: distributions of common species, beta diversity and rank abundance distributions (RAD). The distribution of each of eight common species was unique, although all the species respond to a depth-correlated physical gradient. Changes in composition (beta diversity) were large, even between sites with very similar environmental conditions. Composition at any one site was highly uncertain, and the suite of species changed dramatically both across and down slope. In contrast, the distributions of the RAD components of biodiversity (community abundance, richness, and evenness) were relatively smooth across the study area, suggesting that assemblage structure (i.e. the distribution of abundances of species) is limited, irrespective of species composition. Seamounts had similar biodiversity based on metrics of species presence, beta diversity, total abundance, richness and evenness to the adjacent continental slope in the same depth ranges. These analyses suggest that conservation objectives need to clearly identify which aspects of biodiversity are valued, and employ an appropriate suite of methods to address these aspects, to ensure that conservation goals are met.

SUBMITTER: Dunstan PK

PROVIDER: S-EPMC3350518 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Characterising and predicting benthic biodiversity for conservation planning in deepwater environments.

Dunstan Piers K PK Althaus Franziska F Williams Alan A Bax Nicholas J NJ

PloS one 20120511 5

Understanding patterns of biodiversity in deep sea systems is increasingly important because human activities are extending further into these areas. However, obtaining data is difficult, limiting the ability of science to inform management decisions. We have used three different methods of quantifying biodiversity to describe patterns of biodiversity in an area that includes two marine reserves in deep water off southern Australia. We used biological data collected during a recent survey, combi ...[more]

PMID: 22606271

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Project description:Marine classification schemes based on abiotic surrogates often inform regional marine conservation planning in lieu of detailed biological data. However, these schemes may poorly represent ecologically relevant biological patterns required for effective design and management strategies. We used a community-level modeling approach to characterize and delineate representative mesoscale (tens to thousands of kilometers) assemblages of demersal fish and benthic invertebrates in the Northwest Atlantic. Hierarchical clustering of species occurrence data from four regional annual multispecies trawl surveys revealed three to six groupings (predominant assemblage types) in each survey region, broadly associated with geomorphic and oceanographic features. Indicator analyses identified 3-34 emblematic taxa of each assemblage type. Random forest classifications accurately predicted assemblage distributions from environmental covariates (AUC > 0.95) and identified thermal limits (annual minimum and maximum bottom temperatures) as important predictors of distribution in each region. Using forecasted oceanographic conditions for the year 2075 and a regional classification model, we projected assemblage distributions in the southernmost bioregion (Scotian Shelf-Bay of Fundy) under a high emissions climate scenario (RCP 8.5). Range expansions to the northeast are projected for assemblages associated with warmer and shallower waters of the Western Scotian Shelf over the 21st century as thermal habitat on the relatively cooler Eastern Scotian Shelf becomes more favorable. Community-level modeling provides a biotic-informed approach for identifying broadscale ecological structure required for the design and management of ecologically coherent, representative, well-connected networks of Marine Protected Areas. When combined with oceanographic forecasts, this modeling approach provides a spatial tool for assessing sensitivity and resilience to climate change, which can improve conservation planning, monitoring, and adaptive management.

Dataset Information

Characterising and predicting benthic biodiversity for conservation planning in deepwater environments.

Publications

Characterising and predicting benthic biodiversity for conservation planning in deepwater environments.

Similar Datasets

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