Community composition is a primary determinant of how biodiversity change influences ecosystem functioning and, therefore, the relationship between biodiversity and ecosystem functioning (BEF). We examine the consequences of community composition across six structurally realistic plant community models. We find that a positive correlation between species’ functioning in monoculture vs. their dominance in mixture with regards to a specific function (the “function-dominance correlation”) generates a positive relationship between realized diversity and ecosystem functioning across species richness treatments. However, because realised diversity declines when few species dominate, a positive function-dominance correlation generates a negative relationship between realized diversity and ecosystem functioning within species richness treatments. Removing seed inflow strengthens the link between the function-dominance correlation and BEF relationships across species richness treatments but weakens it within them. These results suggest that changes in species’ identities in a local species pool may more strongly affect ecosystem functioning than changes in species richness.
To predict plant responses under climate change, we need to understand how thermal conditions and herbivory contribute to shoot growth. Here, we used empirical dynamic modelling (EDM) to analyse an 18-year time series from an experimental system at the forest-tundra ecotone to identify relationships between growth, climate, insect herbivores, browsers and ramet age. We found that negative effects of insect herbivory on willow shoot growth are intensified during warmer years. Moreover, the negative effect of insect herbivores was moderated by ramet age, but this moderation was only realized in the absence of vertebrate herbivores – under browsing by both ptarmigans and reindeer, the positive effects of ramet age were eliminated. Jointly, these results demonstrate the context-dependent and dynamic effects of climate and multiple herbivores on shoot growth, and improve our ability to predict effects of climatic warming in arctic environments.