Analyzing global tree and climate datasets to quantify the response of forest biodiversity to environmental change
Ecological theory makes two opposing predictions about the effect of temporal environmental variance on species richness. On the one hand, in community ecology, greater environmental variance has been predicted to create more temporal niches and hence increase species richness; on the other hand, in population ecology, greater environmental variance has been predicted to increase the probability of extinction and thereby decrease species richness. Testing these predictions in forest ecosystems has not been feasible until recently, where collation of large datasets has opened up a new frontier for ecological research.
We tested the two predictions using a global long-term tree census dataset maintained by the Center for Tropical Forest Science-Forest Global Earth Observatories (CTFS-ForestGEO) network. The dataset used represents decadal monitoring of millions of individuals spread over thousands of species. Temporal environmental variance was measured in two ways: (1) indirectly as variation in species' abundances over time and (2) directly as variation in annual temperature and rainfall. Species richness was measured as the number of tree species at each site. We used a suite of statistical models to quantify the relationship between environmental variance and species richness.
Preliminary results from analyses of data for 21 sites largely uphold the second hypothesis: sites with higher temporal environmental variance tended to have lower species richness. This suggests that under greater environmental fluctuations, the negative effects of increased extinction risk on richness typically outweighed the positive effects of a greater number of temporal niches. The trend was consistent for species in different abundance classes, although it was weaker for rare species, likely reflecting the greater influence of demographic variance.
Our results thus predict that the number of tree species in forest ecosystems would generally decline in the face of increasing environmental variance, which could potentially have negative effects on ecosystem functioning. These findings advance fundamental ecological science by providing quantitative predictions at unprecedented scales for forests. Given forecasts of increased environmental variability due to climate change, our results also have important implications for conservation and sustainable management.