Water–energy, land-cover and heterogeneity drivers of the distribution of plant species richness in a mountain region of the European Alps


*Lorenzo Marini, Department of Environmental Agronomy and Crop Production, University of Padova, Viale dell’Università 16, 35020 Legnaro, Padova, Italy. E-mail: lorenzo.marini@unipd.it


Aim  To evaluate the relative importance of water–energy, land-cover, environmental heterogeneity and spatial variables on the regional distribution of Red-Listed and common vascular plant species richness.

Location  Trento Province (c. 6200 km2) on the southern border of the European Alps (Italy), subdivided regularly into 228 3′ × 5′ quadrants.

Methods  Data from a floristic inventory were separated into two subsets, representing Red-Listed and common (i.e. all except Red-Listed) plant species richness. Both subsets were separately related to water–energy, land-cover and environmental heterogeneity variables. We simultaneously applied ordinary least squares regression with variation partitioning and hierarchical partitioning, attempting to identify the most important factors controlling species richness. We combined the analysis of environmental variables with a trend surface analysis and a spatial autocorrelation analysis.

Results  At the regional scale, plant species richness of both Red-Listed and common species was primarily related to energy availability and land cover, whereas environmental heterogeneity had a lesser effect. The greatest number of species of both subsets was found in quadrants with the largest energy availability and the greatest degree of urbanization. These findings suggest that the elevation range within our study region imposes an energy-driven control on the distribution of species richness, which resembles that of the broader latitude gradient. Overall, the two species subsets had similar trends concerning the relative importance of water–energy, land cover and environmental heterogeneity, showing a few differences regarding the selection of some predictors of secondary importance. The incorporation of spatial variables did not improve the explanatory power of the environmental models and the high original spatial autocorrelation in the response variables was reduced drastically by including the selected environmental variables.

Main conclusions  Water–energy and land cover showed significant pure effects in explaining plant species richness, indicating that climate and land cover should both be included as explanatory variables in modelling species richness in human-affected landscapes. However, the high degree of shared variation between the two groups made the relative effects difficult to separate. The relatively low range of variation in the environmental heterogeneity variables within our sampling domain might have caused the low importance of this complex factor.