Abstract
Aim
The integration of high-quality field data with high-resolution remote sensing data can give detailed insights into the spatial distribution of biodiversity and provide valuable information for biodiversity conservation at a scale relevant for management action. We developed a framework based on remote sensing data and field surveys for modelling species richness and abundance of butterflies at high spatial resolution to inform about the spatial distribution of butterfly species richness and abundance and analyse their drivers and the scale of effect of landscape factors.
Location
Western Austria.
Methods
We combined structured butterfly surveys at 175 grassland sites in western Austria with remote sensing variables describing topography, grassland characteristics, and the landscape composition and configuration at different radii around a site. For spatial predictions of butterfly species richness and abundance, generalised linear models with elastic net regularisation were used and compared with stepwise variable selection. To analyse the influence of selected variables and their scale of effect, models with landscape variables in different radii around the sites and variables describing topography were applied.
Results
For species richness, the Spearman rank correlation between predicted and measured values was 0.62. For abundance, predictive power was lower with a correlation of 0.52. Models with variables from smaller radii (125 and 250 m) generally showed better predictive performance than those at larger radii (500 and 1000 m). We found an effect of elevation, maximum grassland productivity, northness, and forest ecotone density in most models.
Main Conclusions
Integrating remote sensing data with spatial modelling techniques substantially enhances our ability to understand patterns and identify key drivers of butterfly species richness at high spatial resolution. Our study highlights the positive influence of forest edges, small woody features, and moderate grassland productivity on butterfly species richness and abundance.