English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

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.

european journal of entomology

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