Multiscale approaches are essential for understanding ecological processes and detecting the scale of effect. However, nested multiscale approaches retain the effect of the landscape attributes from the smaller spatial scales into the larger ones. Thus, decoupling local vs. regional scales can reveal detailed ecological responses to landscape context, but this multiscale approach is poorly explored.
We evaluated the scale of effect of the forest cover (%) and landscape heterogeneity on Euglossini bees combining coupled and decoupled multiscale approaches.
The Euglossini males were sampled in forest patches from 15 landscapes within the Atlantic Forest, southeast Brazil. For simplicity, we defined that the coupled approaches represented the local scales and decoupled approaches the regional scales. We decoupled the scales by cutting out the smaller scales inserted into larger ones. We estimated the relationship of the bee community attributes with forest cover (%) and landscape heterogeneity in local and regional scales using Generalized Linear Models.
We found positive effects of landscape heterogeneity on species richness for regional scales. Forest cover and landscape heterogeneity in local scales showed positive effects on the euglossine abundances. The scale of effect for euglossine richness was higher than species abundances.
Combining coupled and decoupled multiscale approaches showed adequate capture of the scale of effect of the landscape composition on bee communities. Therefore, it is of paramount importance to measure the influence of the landscape context on biodiversity. Maintaining landscapes with larger forest cover and spatial heterogeneity is essential to keep euglossine species requirements.