Towards novel approaches to modelling biotic interactions in multispecies assemblages at large spatial extents

Journal of Biogeography - Tập 39 Số 12 - Trang 2163-2178 - 2012
W. Daniel Kissling1, Carsten F. Dormann2,3, Jürgen Groeneveld4,5, Thomas Hickler6, Ingolf Kühn7, Greg McInerny8, José M. Montoya9, Christine Römermann10,11, Katja Schiffers12, Frank M. Schurr10,13, Alexander Singer4, Jens‐Christian Svenning1, Niklaus E. Zimmermann14, Robert B. O’Hara6
1Ecoinformatics & Biodiversity Group, Department of Bioscience, Aarhus University, DK-8000 Aarhus C, Denmark
2Biometry and Environmental System Analysis, Faculty of Forest and Environmental Sciences, University of Freiburg, 79106 Freiburg, Germany
3Helmholtz Centre for Environmental Research – UFZ, Department of Computational Landscape Ecology, 04318 Leipzig, Germany
4Helmholtz Centre for Environmental Research – UFZ, Department of Ecological Modelling, 04318 Leipzig, Germany
5School of Environment, The University of Auckland, Auckland, New Zealand
6Biodiversity and Climate Research Centre (BiK-F), 60325 Frankfurt am Main, Germany
7Helmholtz Centre for Environmental Research – UFZ, Department of Community Ecology, 06120 Halle, Germany
8Computational Ecology and Environmental Science Group, Computational Science Laboratory, Microsoft Research, Cambridge CB3 0FB, UK
9Instituto de Ciencias del Mar, Consejo Superior de Investigaciones Científicas, E-08003 Barcelona, Spain
10Institute for Physical Geography, Goethe University Frankfurt, 60438 Frankfurt am Main, Germany
11Theoretical Ecology, Faculty of Biology and Preclinical Medicine, University of Regensburg, 93040 Regensburg, Germany
12Laboratoire d’Ecologie Alpine, UMR-CNRS 5553, Université J. Fourier, 38041 Grenoble Cedex 9, France
13Plant Ecology and Nature Conservation, Institute of Biochemistry and Biology, University of Potsdam, 14469 Potsdam, Germany
14Landscape Dynamics, Swiss Federal Research Institute WSL, CH-8903 Birmensdorf, Switzerland

Tóm tắt

AbstractAim  Biotic interactions – within guilds or across trophic levels – have widely been ignored in species distribution models (SDMs). This synthesis outlines the development of ‘species interaction distribution models’ (SIDMs), which aim to incorporate multispecies interactions at large spatial extents using interaction matrices.Location  Local to global.Methods  We review recent approaches for extending classical SDMs to incorporate biotic interactions, and identify some methodological and conceptual limitations. To illustrate possible directions for conceptual advancement we explore three principal ways of modelling multispecies interactions using interaction matrices: simple qualitative linkages between species, quantitative interaction coefficients reflecting interaction strengths, and interactions mediated by interaction currencies. We explain methodological advancements for static interaction data and multispecies time series, and outline methods to reduce complexity when modelling multispecies interactions.Results  Classical SDMs ignore biotic interactions and recent SDM extensions only include the unidirectional influence of one or a few species. However, novel methods using error matrices in multivariate regression models allow interactions between multiple species to be modelled explicitly with spatial co‐occurrence data. If time series are available, multivariate versions of population dynamic models can be applied that account for the effects and relative importance of species interactions and environmental drivers. These methods need to be extended by incorporating the non‐stationarity in interaction coefficients across space and time, and are challenged by the limited empirical knowledge on spatio‐temporal variation in the existence and strength of species interactions. Model complexity may be reduced by: (1) using prior ecological knowledge to set a subset of interaction coefficients to zero, (2) modelling guilds and functional groups rather than individual species, and (3) modelling interaction currencies and species’ effect and response traits.Main conclusions  There is great potential for developing novel approaches that incorporate multispecies interactions into the projection of species distributions and community structure at large spatial extents. Progress can be made by: (1) developing statistical models with interaction matrices for multispecies co‐occurrence datasets across large‐scale environmental gradients, (2) testing the potential and limitations of methods for complexity reduction, and (3) sampling and monitoring comprehensive spatio‐temporal data on biotic interactions in multispecies communities.

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Journal of Biogeography

Tập 39 Số 12

2163-2178

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