Species distribution modelling is needed to support ecological impact assessments.

Published online
05 Mar 2021
Content type
Journal article
Journal title
Journal of Applied Ecology
DOI
10.1111/1365-2664.13782

Author(s)
Baker, D. J. & Maclean, I. M. D. & Goodall, M. & Gaston, K. J.
Contact email(s)
d.baker2@exeter.ac.uk

Publication language
English

Abstract

1. Legislation commonly mandates the mitigation of impacts to biodiversity in planning and development processes, with potential impacts identified through some form of ecological impact assessment. Yet, protections for biodiversity are frequently undermined because the distributions of priority species are poorly known in most locations at the spatial scales required to inform planning decisions (i.e. c. 1-100 ha). 2. Planning applications are often screened against opportunistic records to deter-mine potential impacts to priority species. However, raw occurrence records pro-vide information only on where a species has been detected and cannot be used to indicate if a species is likely to be absent from a site.3. Inferences drawn from these data on the likelihood of a species being present at a site can only be correctly interpreted through an appropriate species distribu-tion modelling (SDM) framework that ensures assumptions about the data and models are formalised and documented. We argue that SDM frameworks must be integrated into ecological impact assessments to improve support for biodiversity protections within planning and development processes.4. Biases and uncertainties in opportunistic data create modelling challenges, but recent methodological advances can minimise their impacts on predictions. We advocate co-production with practitioners of SDM tools, mapping products and best-practice guidelines specific to planning processes.5. Policy implications. The integration of species distribution modelling frameworks into ecological impact assessments will strengthen biodiversity protections in planning and development processes by ensuring methodological transparency and rigour in the interpretation of species occurrence data.

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