资源环境科技发展态势分析平台

Climate change, land-use change and introductions of non-native species are key determinants of biodiversity change worldwide. However, the extent to which anthropogenic drivers of environmental change interact to affect biological communities is largely unknown, especially over longer time periods. Here, we show that plant community composition in 996 Swedish landscapes has consistently shifted to reflect the warmer and wetter climate that the region has experienced during the second half of the 20th century. Using community climatic indices, which reflect the average climatic associations of the species within each landscape at each time period, we found that species compositions in 74% of landscapes now have a higher representation of warm-associated species than they did previously, while 84% of landscapes now host more species associated with higher levels of precipitation. In addition to a warmer and wetter climate, there have also been large shifts in land use across the region, while the fraction of non-native species has increased in the majority of landscapes. Climatic warming at the landscape level appeared to favour the colonization of warm-associated species, while also potentially driving losses in cool-associated species. However, the resulting increases in community thermal means were apparently buffered by landscape simplification (reduction in habitat heterogeneity within landscapes) in the form of increased forest cover. Increases in non-native species, which generally originate from warmer climates than Sweden, were a strong driver of community-level warming. In terms of precipitation, both landscape simplification and increases in non-natives appeared to favour species associated with drier climatic conditions, to some extent counteracting the climate-driven shift towards wetter communities. Anthropogenic drivers can act both synergistically and antagonistically to determine trajectories of change in biological communities over time. Therefore, it is important to consider multiple drivers of global change when trying to understand, manage and predict biodiversity in the future.