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Correlation and process in species distribution models: bridging a dichotomy

  • Within the field of species distribution modelling an apparent dichotomy exists between process-based and correlative approaches, where the processes are explicit in the former and implicit in the latter. However, these intuitive distinctions can become blurred when comparing species distribution modelling approaches in more detail. In this review article, we contrast the extremes of the correlativeprocess spectrum of species distribution models with respect to core assumptions, model building and selection strategies, validation, uncertainties, common errors and the questions they are most suited to answer. The extremes of such approaches differ clearly in many aspects, such as model building approaches, parameter estimation strategies and transferability. However, they also share strengths and weaknesses. We show that claims of one approach being intrinsically superior to the other are misguided and that they ignore the processcorrelation continuum as well as the domains of questions that each approach is addressing. Nonetheless,Within the field of species distribution modelling an apparent dichotomy exists between process-based and correlative approaches, where the processes are explicit in the former and implicit in the latter. However, these intuitive distinctions can become blurred when comparing species distribution modelling approaches in more detail. In this review article, we contrast the extremes of the correlativeprocess spectrum of species distribution models with respect to core assumptions, model building and selection strategies, validation, uncertainties, common errors and the questions they are most suited to answer. The extremes of such approaches differ clearly in many aspects, such as model building approaches, parameter estimation strategies and transferability. However, they also share strengths and weaknesses. We show that claims of one approach being intrinsically superior to the other are misguided and that they ignore the processcorrelation continuum as well as the domains of questions that each approach is addressing. Nonetheless, the application of process-based approaches to species distribution modelling lags far behind more correlative (process-implicit) methods and more research is required to explore their potential benefits. Critical issues for the employment of species distribution modelling approaches are given, together with a guideline for appropriate usage. We close with challenges for future development of process-explicit species distribution models and how they may complement current approaches to study species distributions.zeige mehrzeige weniger

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Metadaten
Verfasserangaben:Carsten F. Dormann, Stanislaus J. Schymanski, Juliano Sarmento CabralORCiD, Isabelle Chuine, Catherine Graham, Florian Hartig, Michael Kearney, Xavier Morin, Christine Römermann, Boris Schröder-EsselbachORCiDGND, Alexander Singer
DOI:https://doi.org/10.1111/j.1365-2699.2011.02659.x
ISSN:0305-0270
Titel des übergeordneten Werks (Englisch):Journal of biogeography
Verlag:Wiley-Blackwell
Verlagsort:Hoboken
Publikationstyp:Rezension
Sprache:Englisch
Jahr der Erstveröffentlichung:2012
Erscheinungsjahr:2012
Datum der Freischaltung:26.03.2017
Freies Schlagwort / Tag:Hypothesis generation; SDM; mechanistic model; parameterization; process-based model; species distribution model; uncertainty; validation
Band:39
Ausgabe:12
Seitenanzahl:13
Erste Seite:2119
Letzte Seite:2131
Fördernde Institution:LOEWE- BiK-F Biodiversity and the Climate Research Centre Frankfurt; Helmholtz Association [VH-NG 247]; German Research Foundation DFG [DO 686/5-1]; Max Planck Society; DFG [RO 3842/1-1]; Biodiversity and Climate Research Centre (BiK-F), part of the LOEWE programme 'Landes-Offensive zur Entwicklung Wissenschaftlich-okonomischer Exzellenz' of Hesse's Ministry of Higher Education, Research and the Arts
Organisationseinheiten:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Geowissenschaften
Peer Review:Referiert
Name der Einrichtung zum Zeitpunkt der Publikation:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Erd- und Umweltwissenschaften
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