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      Predicting how many animals will be where: How to build, calibrate and evaluate individual-based models

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      Ecological Modelling
      Elsevier BV

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          Approximate Bayesian Computation in Evolution and Ecology

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            Ecological implications of behavioural syndromes.

            Interspecific trait variation has long served as a conceptual foundation for our understanding of ecological patterns and dynamics. In particular, ecologists recognise the important role that animal behaviour plays in shaping ecological processes. An emerging area of interest in animal behaviour, the study of behavioural syndromes (animal personalities) considers how limited behavioural plasticity, as well as behavioural correlations affects an individual's fitness in diverse ecological contexts. In this article we explore how insights from the concept and study of behavioural syndromes provide fresh understanding of major issues in population ecology. We identify several general mechanisms for how population ecology phenomena can be influenced by a species or population's average behavioural type, by within-species variation in behavioural type, or by behavioural correlations across time or across ecological contexts. We note, in particular, the importance of behavioural type-dependent dispersal in spatial ecology. We then review recent literature and provide new syntheses for how these general mechanisms produce novel insights on five major issues in population ecology: (1) limits to species' distribution and abundance; (2) species interactions; (3) population dynamics; (4) relative responses to human-induced rapid environmental change; and (5) ecological invasions. © 2012 Blackwell Publishing Ltd/CNRS.
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              abc: an R package for approximate Bayesian computation (ABC)

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                Author and article information

                Journal
                Ecological Modelling
                Ecological Modelling
                Elsevier BV
                03043800
                April 2016
                April 2016
                : 326
                :
                : 113-123
                Article
                10.1016/j.ecolmodel.2015.08.012
                10400136-97fd-4c0b-8f8c-da720d5c6808
                © 2016
                History

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