How fine is fine-scale? Questioning the use of fine-scale bioclimatic data in species distribution models used for forecasting abundance patterns in butterflies

Katharina J Filz,Jan O Engler,Thomas Schmitt

doi:10.14411/eje.2013.044

Abstract

The use of species distribution models (SDMs) to predict the spatial occurrence and abundance of species in relation to environmental predictors has been debated in terms of species' ecology and biogeography. The predictive power of these models is well recognized for vertebrates, but has not yet been tested for invertebrates. In this study, we aim to assess the use of SDMs for predicting local abundances of invertebrates at a macroscale level. A maximum entropy algorithm was used to build SDMs based on occurrence records of 61 species of butterflies and bioclimatic information with a 30 arc second resolution. Predictions of habitat suitability were correlated with butterfly abundance data derived from independently conducted field surveys in order to check for a relationship between the predictions of the model and local abundances. Even though the model accurately described the current distributions of the species in the study area at a macroscale, the observed occurrences of the species (i.e. presence/absence) recorded by the field surveys differed significantly from the model's predictions for the corresponding grid cells. Moreover, there was no correlation between observed abundance and the model's predictions for most species of butterflies. We conclude that the spatial abundance of butterflies cannot be predicted from environmental suitability modelled at a resolution as large as in this study. Using the finest scale bioclimatic information currently available (i.e. 30 arc seconds) it is not adequate to predict species abundances as structural and ecological factors as well as climatic patterns acting at a smaller scale are key determinants of the occurrence and abundance of invertebrates. Therefore, future studies have to account for the role of the resolution in environmental predictors when assessments of spatial abundances via SDMs will be conducted.

Highlights

Environmental conditions and population processes determine the spatial distribution of species and biodiversity patterns over geographic ranges (Gaston, 2003)
The basic idea behind this assumption is that environmental suitability predicted by a species distribution models (SDMs) for a given location can be used as an indicator of species' abundance as it indicates how well the physical and ecological constraints of species are met
The aim of this study was to determine the suitability of the data on bioclimatic information at the finest resolution (30 arc seconds) currently available in the Worldclim database (Hijmans et al, 2005; www.worldclim.org), which is the standard source of variables for modelling species distributions world-wide (i.e. Hijmans et al, 2005), as demonstrated by a citation index of 1,432 (ISI Web of Science query, 6-6-2012)

Summary

Introduction

Environmental conditions and population processes determine the spatial distribution of species and biodiversity patterns over geographic ranges (Gaston, 2003) In this context, species distribution models (SDMs) are commonly used to predict the potential distribution of species with regard to their ecological niches The basic idea behind this assumption is that environmental suitability predicted by a SDM for a given location can be used as an indicator of species' abundance as it indicates how well the physical and ecological constraints of species are met. If this is the case the species will be abundant at locations with high environmental suitability and vice versa. Models that predict environmental suitability based on occurrence data might provide information on spatial variation in abundance

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