A new study recently published on the Journal of Animal Ecology integrates and analyzes simultaneously several parameters, such as environmental variables (local topography, suitable habitat area, landscape permeability, weather patterns), species’ traits (e.g. habitat specialization and dispersal capabilities) and variation in climatic conditions, in order to evaluate how they influence population dynamics in Mediterranean butterflies.
Some CMCC researchers from ISC Division took part in the study.

The study takes into account a rich butterfly community in the western Mediterranean.
This region of the Western Mediterranean is an important centre of biodiversity with high levels of butterfly species richness, but over the last several decades, this and other parts of the Mediterranean basin have been subjected to major changes in land use or cover and most natural habitats have been lost to, for example, intensive agriculture, tree plantations, reservoirs and urbanization.
The analysis was based on a 17-year dataset containing detection/non-detection data on 73 butterfly species for 26 sites in North-eastern Spain, while assuming that an increasing aridity may induce higher larval mortality and higher dispersal of adults (because of lack of nectar and oviposition resources9, increasing both extinction and colonization rates.

The identification of environmental variables associated with patch occupancy and turnover may be especially useful to enhance the persistence of multiple species under current global change.

Read the summary of the article:

Summary

• Many species are found today in the form of fragmented populations occupying patches of remnant habitat in human-altered landscapes. The persistence of these population networks requires a balance between extinction and colonization events assumed to be primarily related to patch area and isolation, but the contribution of factors such as the characteristics of patch and matrix habitats, the species’ traits (habitat specialization and dispersal capabilities) and variation in climatic conditions have seldom been evaluated simultaneously.
• The identification of environmental variables associated with patch occupancy and turnover may be especially useful to enhance the persistence of multiple species under current global change. However, for robust inference on occupancy and related parameters, we must account for detection errors, a commonly overlooked problem that leads to biased estimates and misleading conclusions about population dynamics.
• Here we provide direct empirical evidence of the effects of different environmental variables on the extinction and colonization rates of a rich butterfly community in the western Mediterranean. The analysis was based on a 17-year dataset containing detection/non-detection data on 73 butterfly species for 26 sites in North-eastern Spain. Using multi-season occupancy models, which take into account species’ detectability, we were able to obtain robust estimates of local extinction and colonization probabilities for each species and test the potential effects of site covariates such as the area of suitable habitat, topographic variability, landscape permeability around the site and climatic variability in aridity conditions.
• Results revealed a general pattern across species with local habitat composition and landscape features as stronger predictors of occupancy dynamics compared to topography and local aridity. Increasing area of suitable habitat in a site strongly decreased local extinction risks and, for a number of species, both higher amounts of suitable habitat and more permeable landscapes increased colonization rates. Nevertheless, increased topographic variability decreased the extinction risk of bad dispersers, a group of species with significantly lower colonization rates.
• Our models predicted higher sensitivity of the butterfly assemblages to deterministic changes in habitat features rather than to stochastic weather patterns, with some relationships being clearly dependent on the species’ traits.

Download the full paper.