Questions: (1) Is climate a strong driver of vegetation dynamics, including interannual variation, in a range margin steppic community? (2) Are there long-term trends in cover and species richness in this community, and are these consistent across species groups and species within groups? (3) Can long-term trends in plant community data be related to variation in local climate over the last three decades?
Location: A range margin steppic grassland community in central Germany.
Methods: Cover, number and size of all individuals of all plant species present in three permanent 1-m2 plots were recorded in spring for 26 years (1980–2005). Climatic data for the study area were used to determine the best climatic predictor for each plant community, functional group and species variable (annual data and interannual variation) using best subsets regression.
Results: April and autumn temperature showed the highest correlation with total cover and species richness and with interannual variations of cover and richness. However, key climate drivers differed between the five most abundant species. Similarly, total cover and number and cover of perennials significantly decreased over time, while no trend was found for the cover and number of annuals. However, within functional groups there were also contrasting species-specific responses. Long-term temperature increases and high interannual variability in both temperature and precipitation were strongly related to long-term trends and interannual variations in plant community data.
Conclusions: Temporal trends in vegetation were strongly associated with temporal trends in climate at the study site, with key roles for autumn and spring temperature and precipitation. Dynamics of functional groups and species within groups and their relationships to changes in temperature and precipitation reveal complex long-term and interannual patterns that cannot be inferred from short-term studies with only one or a few individual species. Our results also highlight that responses detected at the functional group level may mask contrasting responses within functional groups. We discuss the implications of these findings for attempts to predict the future response of biodiversity to climate change.