Abstract
AbstractAimEcological niche models (ENMs) typically require point locations of species’ occurrence as input data. Where exact locations are not available, geographical centroids of the respective administrational spatial units (ASUs) are often used as a substitute. We investigated how the use of ASU centroids in ENMs affects model performance, what role the size of ASUs plays, and what effects different grain sizes of explanatory variables have.LocationEurope.Major taxa studiedVirtual species.MethodsWe set up a two‐factorial study design with artificial ASUs of three different sizes and environmental data of four commonly used grain sizes, repeated over three study regions. To control other factors that may affect ENM performance, we created a virtual species with a known response to environmental variables, precise and even sampling and a known spatial distribution. We ran a series of Maxent models for the virtual species based on centroids and precise occurrence locations under varying ASU and grain sizes.ResultsThe use of ASU centroids introduces a value frequency mismatch of the explanatory variables between centroids and true occurrence locations, and it has a negative effect on ENM performance. Value frequency mismatch, negative effect on ENM performance and over‐prediction of the species’ range all increase with ASU size. The effect of grain size of environmental data, on the contrary, was small in comparison.Main conclusionsENMs built upon ASU centroids can suffer considerably from the introduced error. For ASUs that are sufficiently small or show low spatial heterogeneity of explanatory variables, ASU centroids can still be a viable and convenient surrogate for precise occurrence locations. When possible, however, central tendency values (median, mean) that represent the whole ASU rather than just a single point location need to be considered.
Highlights
Ecological niche models (ENMs), based on niche theory, are widely used in many fields such as invasion and conservation ecology, biogeography, as well as epidemiology (Elith & Leathwick, 2009; Escobar & Craft, 2016; Liu et al, 2018; Peterson, 2014)
Our results show that the absolute size of administrational spatial units (ASUs) affects the value frequency mismatch between true locations and centroids
Whether ASU centroids can be a viable surrogate for precise occurrence locations depends on the ASUs’ sizes and how heterogeneous they are in terms of environmental explanatory variables
Summary
Ecological niche models (ENMs), based on niche theory, are widely used in many fields such as invasion and conservation ecology, biogeography, as well as epidemiology (Elith & Leathwick, 2009; Escobar & Craft, 2016; Liu et al, 2018; Peterson, 2014). ENMs typically use geographical occurrence locations of the target species as input data These locations are related to a series of explanatory variables (spatial raster data describing the environmental and/or socio-economic conditions in the study area), forming a correlative model of the species’ environmental niche. For example, when using citizen-science databases or local monitoring systems, the occurrence locations of the species may be of a coarse precision or only available at municipal or county level (i.e., related to geographical surfaces of differing sizes). For epidemiological data, such missing spatial precision ensures information privacy
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