Dealing with non-equilibrium bias and survey effort in presence-only invasive Species Distribution Models (iSDM); predicting the range of muntjac deer in Britain and Ireland
Invasive species managers utilise species records to inform management. These data can also be used in Species Distribution Models (SDM) to predict future spread or potential invasion of new areas. However, issues with non-equilibrium (also called disequilibrium) can cause difficulties in modelling...
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| Published in: | Ecological informatics Vol. 69; p. 101683 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Elsevier B.V
01-07-2022
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| Subjects: | |
| Online Access: | Get full text |
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| Summary: | Invasive species managers utilise species records to inform management. These data can also be used in Species Distribution Models (SDM) to predict future spread or potential invasion of new areas. However, issues with non-equilibrium (also called disequilibrium) can cause difficulties in modelling invasive species that have not fully colonised their potential distribution and, in addition, sampling bias can result from a lack of information on survey effort, a particular issue for presence only modelling techniques. Geographical confounds are unavoidable when building iSDMs but there are methods that allow prediction to be optimised. We used maximum entropy (Maxent) to model suitable habitat for invasive Reeve's muntjac deer (Muntiacus reevesi) throughout Great Britain and Ireland comparing several methods that aimed to address invasive Species Distribution Modelling (iSDM) bias including spatial filtering, weighted background points and targeted background points built at varying spatial extents. Model evaluation metrics suggested that the model, which explicitly failed to account for non-equilibrium at the full extent of Great Britain and Ireland using random background points, predicted the species' current invasive range best. This highlighted that negative environmental relationships are likely to represent uncolonised areas rather than habitat selection and thus, low predicted suitability of uncolonised areas was misleading. Of the models that dealt with non-equilibrium conceptually best, by restricting the training extent to their current invasive range or core range, and utilised targeted background points accounting for survey effort (cells with other deer species recorded as present yet with no records for muntjac) as the best model evaluation metric, yielded relatively poor predictive performance. This implied limited habitat selectivity or avoidance within the colonised range which, when spatially extrapolated, suggested virtually all regions in Great Britain and Ireland may be vulnerable to future muntjac invasion.
•SDMs for invasive species are highly vulnerable to non-equilibrium.•iSDMs utilise random, targeted or weighted background points and spatial filtering.•Spatial extent of training models was restricted to the species' invasive range.•Background points were best targeted to cells with known survey effort.•iSDMs suggested everywhere in Britain or Ireland is vulnerable to muntjac invasion. |
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| ISSN: | 1574-9541 |
| DOI: | 10.1016/j.ecoinf.2022.101683 |