Community dynamics under environmental change: How can next generation mechanistic models improve projections of species distributions?

2016 | journal article; research paper. A publication with affiliation to the University of Göttingen.

Jump to: Cite & Linked | Documents & Media | Details | Version history

Cite this publication

​Community dynamics under environmental change: How can next generation mechanistic models improve projections of species distributions?​
Singer, A.; Johst, K.; Banitz, T.; Fowler, M. S.; Groeneveld, J.; Gutierrez, A. G. & Hartig, F. et al.​ (2016) 
Ecological Modelling326 pp. 63​-74​.​ DOI: https://doi.org/10.1016/j.ecolmodel.2015.11.007 

Documents & Media

License

GRO License GRO License

Details

Authors
Singer, Alexander; Johst, Karin; Banitz, Thomas; Fowler, Mike S.; Groeneveld, Juergen; Gutierrez, Alvaro G.; Hartig, Florian; Krug, Rainer M.; Liess, Matthias; Matlack, Glenn; Meyer, Katrin M. ; Pe'er, Guy; Radchuk, Viktoriia; Voinopol-Sassu, Ana-Johanna; Travis, Justin M. J.
Abstract
Environmental change is expected to shift the geographic range of species and communities. To estimate the consequences of these shifts for the functioning and stability of ecosystems, reliable predictions of alterations in species distributions are needed. Projections with correlative species distribution models, which correlate species' distributions to the abiotic environment, have become a standard approach. Criticism of this approach centres around the omission of relevant biotic feedbacks and triggered the search for alternatives. A new generation of mechanistic process-based species distribution models aims at implementing formulations of relevant biotic processes to cover species' life histories, physiology, dispersal abilities, evolution, and both intra- and interspecific interactions. Although this step towards more structural realism is considered important, it remains unclear whether the resulting projections are more reliable. Structural realism has the advantage that geographic range shifting emerges from the interplay of relevant abiotic and biotic processes. Having implemented the relevant response mechanisms, structural realistic models should better tackle the challenge of generating projections of species responses to (non-analogous) environmental change. However, reliable projections of future species ranges demand ecological information that is currently only available for few species. In this opinion paper, we discuss how the discrepancy between demand for structural realism on the one hand and the related knowledge gaps on the other hand affects the reliability of mechanistic species distribution models. We argue that omission of relevant processes potentially impairs projection accuracy (proximity of the mean outcome to the true value), particularly if species range shifts emerge from species and community dynamics. Yet, insufficient knowledge that limits model specification and parameterization, as well as process complexity, increases projection uncertainty (variance in the outcome of simulated model projections). The accuracy-uncertainty-relation reflects current limits to delivering reliable projections of range shifts. We propose a protocol to improve and communicate projection reliability. The protocol combines modelling and empirical research to efficiently fill critical knowledge gaps that currently limit the reliability of species and community projections. (C) 2015 Elsevier B.V. All rights reserved.
Issue Date
2016
Journal
Ecological Modelling 
Organization
Fakultät für Forstwissenschaften und Waldökologie ; Büsgen-Institut ; Abteilung Ökosystemmodellierung 
ISSN
1872-7026; 0304-3800
Language
English
Subject(s)
Bias; Precision; Prediction; Protocol; SDM; Species interaction; Uncertainty

Reference

Citations


Social Media