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      Among-site variability in the stochastic dynamics of East African coral reefs

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          Abstract

          Coral reefs are dynamic systems whose composition is highly influenced by unpredictable biotic and abiotic factors. Understanding the spatial scale at which long-term predictions of reef composition can be made will be crucial for guiding conservation efforts. Using a 22-year time series of benthic composition data from 20 reefs on the Kenyan and Tanzanian coast, we developed Bayesian vector autoregressive state-space models for reef dynamics, incorporating among-site variability, and quantified their long-term behaviour. We estimated that if there were no among-site variability, the total long-term variability would be approximately one-third of its current value. Thus, our results showed that among-site variability contributes more to long-term variability in reef composition than does temporal variability. Individual sites were more predictable than previously thought, and predictions based on current snapshots are informative about long-term properties. Our approach allowed us to identify a subset of possible climate refugia sites with high conservation value, where the long-term probability of coral cover ≤0.1 (as a proportion of benthic cover of hard substrate) was very low. Analytical results show that this probability is most strongly influenced by among-site variability and by interactions among benthic components within sites. These findings suggest that conservation initiatives might be successful at the site scale as well as the regional scale.

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          Evaluating life-history strategies of reef corals from species traits.

          Classifying the biological traits of organisms can test conceptual frameworks of life-history strategies and allow for predictions of how different species may respond to environmental disturbances. We apply a trait-based classification approach to a complex and threatened group of species, scleractinian corals. Using hierarchical clustering and random forests analyses, we identify up to four life-history strategies that appear globally consistent across 143 species of reef corals: competitive, weedy, stress-tolerant and generalist taxa, which are primarily separated by colony morphology, growth rate and reproductive mode. Documented shifts towards stress-tolerant, generalist and weedy species in coral reef communities are consistent with the expected responses of these life-history strategies. Our quantitative trait-based approach to classifying life-history strategies is objective, applicable to any taxa and a powerful tool that can be used to evaluate theories of community ecology and predict the impact of environmental and anthropogenic stressors on species assemblages. © 2012 Blackwell Publishing Ltd/CNRS.
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            A 30-YEAR STUDY OF CORAL ABUNDANCE, RECRUITMENT, AND DISTURBANCE AT SEVERAL SCALES IN SPACE AND TIME

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              ESTIMATING COMMUNITY STABILITY AND ECOLOGICAL INTERACTIONS FROM TIME-SERIES DATA

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                Author and article information

                Contributors
                Journal
                PeerJ
                PeerJ
                peerj
                peerj
                PeerJ
                PeerJ Inc. (San Francisco, USA )
                2167-8359
                17 May 2017
                2017
                : 5
                : e3290
                Affiliations
                [1 ]School of Environmental Sciences, University of Liverpool , Liverpool, United Kingdom
                [2 ]Institute of Integrative Biology, University of Liverpool , Liverpool, United Kingdom
                [3 ]Department of Biology, University of North Carolina at Chapel Hill , Chapel Hill, NC, United States of America
                [4 ]School of Mathematical and Computer Sciences, Actuarial Mathematics and Statistics, Heriot-Watt University , Edinburgh, United Kingdom
                [5 ]Wildlife Conservation Society , NY, United States of America
                [6 ]Department of Mathematical Sciences, University of Liverpool , Liverpool, United Kingdom
                Article
                3290
                10.7717/peerj.3290
                5437857
                28533955
                2ec58b21-11fc-4dd5-9ae7-cb978f9a9411
                ©2017 Allen et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.

                History
                : 3 January 2017
                : 10 April 2017
                Funding
                Funded by: NERC
                Award ID: NE/K00297X/1
                This work was supported by NERC grant NE/K00297X/1. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Ecology
                Marine Biology
                Mathematical Biology

                vector autoregressive model,state-space model,stochastic dynamics,community composition,spatial variability,temporal variability,coral reef,bayesian statistics

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