Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/29361
Appears in Collections:Biological and Environmental Sciences Journal Articles
Peer Review Status: Refereed
Title: Improving species distribution models for invasive non-native species with biologically informed pseudo-absence selection
Author(s): Chapman, Daniel
Pescott, Oliver L
Roy, Helen E
Tanner, Rob
Contact Email: daniel.chapman@stir.ac.uk
Keywords: benchmarking
Biomod
climate envelope
ecological niche model
invasive alien species
Maxent
pest risk assessment
presence–absence
presence‐background
presence‐only
Issue Date: May-2019
Citation: Chapman D, Pescott OL, Roy HE & Tanner R (2019) Improving species distribution models for invasive non-native species with biologically informed pseudo-absence selection. Journal of Biogeography, 46 (5), pp. 1029-1040. https://doi.org/10.1111/jbi.13555
Abstract: Aim We present a novel strategy for species distribution models (SDMs) aimed at predicting the potential distributions of range‐expanding invasive non‐native species (INNS). The strategy combines two established perspectives on defining the background region for sampling “pseudo‐absences” that have hitherto only been applied separately. These are the accessible area, which accounts for dispersal constraints, and the area outside the environmental range of the species and therefore assumed to be unsuitable for the species. We tested an approach to combine these by fitting SDMs using background samples (pseudo‐absences) from both types of background. Location Global. Taxon Invasive non‐native plants: Humulus scandens, Lygodium japonicum, Lespedeza cuneata, Triadica sebifera, Cinnamomum camphora. Methods Presence‐background (or presence‐only) SDMs were developed for the potential global distributions of five plant species native to Asia, invasive elsewhere and prioritised for risk assessment as emerging INNS in Europe. We compared models where the pseudo‐absences were selected from the accessible background, the unsuitable background (defined using biological knowledge of the species’ key limiting factors) or from both types of background. Results Combining the unsuitable and accessible backgrounds expanded the range of environments available for model fitting and caused biological knowledge about ecological unsuitability to influence the fitted species‐environment relationships. This improved the realism and accuracy of distribution projections globally and, generally, within the species’ ranges. Main conclusions Correlative SDMs remain valuable for INNS risk mapping and management, but are often criticised for a lack of biological underpinning. Our approach partly addresses this concern by using prior knowledge of species’ requirements or tolerances to define the unsuitable background for modelling, while also accommodating dispersal constraints through considerations of accessibility. It can be implemented with current SDM software and results in more accurate and realistic distribution projections. As such, wider adoption has potential to improve SDMs that support INNS risk assessment.
DOI Link: 10.1111/jbi.13555
Rights: This item has been embargoed for a period. During the embargo please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study. This is the peer reviewed version of the following article: Chapman, D, Pescott, OL, Roy, HE, Tanner, R. Improving species distribution models for invasive non-native species with biologically informed pseudo-absence selection. Journal of Biogeography. 2019; 46: 1029– 1040, which has been published in final form at https://doi.org/10.1111/jbi.13555. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for self-archiving.
Licence URL(s): https://storre.stir.ac.uk/STORREEndUserLicence.pdf

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