Contrasting patterns of native and non-native plants in a network of protected areas across spatial scales

Abstract

Networks of protected areas are fundamental for biodiversity conservation, but many factors determine their conservation efficiency. In particular, on top of other human-driven disturbances, invasions by non-native species can cause habitat and biodiversity loss. Jointly understanding what drives patterns of plant diversity and of non-native species in protected areas is therefore a priority. We tested whether the richness and composition of native and non-native plant species within a network of protected areas follow similar patterns across spatial scales. Specifically, we addressed three questions: (a) what is the degree of congruence in species richness between native and non-native species? (b) do changes in the composition of non-native species across ecological gradients reflect a similar turnover of native species along the same gradients ? (c) what are the main environmental and human disturbance drivers controlling species richness in these two groups of species? Species richness and composition of native and non-native plant species were compared at two spatial scales: the plot scale (10 m × 10 m) and the Protected Area scale (PA). In addition, we fit Generalized Linear Models to identify the most important drivers of native and non-native species richness at each scale, focusing on environmental conditions (climate, topography) and on the main sources of human disturbance in the area (land use and roads). We found a significant positive correlation between the turnover of native and non-native species composition at both plot and PA scales, whereas their species richness was only correlated at the larger PA scale. The lack of congruence between the richness of native and non-native species at the plot scale was likely driven by differential responses to fine scale environmental factors, with non-natives favoring drier climates and milder slopes (climate and slope). In addition, more non-native species were found closer to road-ways in the reserve network. In contrast, the congruence in the richness of native and non-native species at the broader PA scale was mainly driven by the common influence of PA area, but also by similar responses of the two groups of species to climatic heterogeneity. Thus, our study highlights the strong spatial dependence of the relationship between native and non-native species richness and of their responses to environmental variation. Taken together, our results suggest that within the study region the introduction and establishment of non-native species would be more likely in warmer and dryer areas, with high native species richness at large spatial scale but intermediate levels of anthropogenic disturbances and mild slope inclinations and elevation at fine scale. Such an exhaustive understanding of the factors that influence the spread of non-native species, especially in networks of protected areas is crucial to inform conservation managers on how to control or curb non-native species.