Predicting Species-Area Relationships in Fragmented Forests

Maintaining high biodiversity levels is of key importance in keeping ecosystems healthy and resilient, especially in landscapes undergoing intensive anthropogenic disturbances. Habitat destruction leads to severe biodiversity decline, and its spatial configuration affects its impact. Knowing the exact impact of habitat loss and fragmentation on species richness is valuable information. Predicting the effects of different habitat loss scenarios on biodiversity will facilitate making better, well-informed management decisions, but such predictions are not yet available.

We predict species-area relationships in tropical forest landscapes undergoing habitat loss and fragmentation. To do so, we use the information theoretical framework of Maximum Entropy Theory in Ecology (METE). METE uses state variables derived from macroscale parameters (i.e. total number of individuals, total number of species, and total metabolic energy in the selected area) to provide the most uninformed distribution of the species-area relationship. While METE makes accurate predictions in undisturbed systems, METE predictions in landscapes undergoing habitat loss and fragmentation are highly imprecise. This is due to the underlying assumption that individuals are spread homogeneously across space, which fails in such environments.    

Using an individual-based model, we explored how METE’s state variables should be adjusted to provide a good species-area relationship prediction in disturbed environments. These environments were simulated using different combinations of habitat loss and habitat fragmentation levels. Our study revealed that METE’s state variable S₀(total number of species in the area) depends on habitat loss and fragmentation levels.

We demonstrate the accuracy of our predictions using empirical data. By extracting two landscape characteristics – percentage forest cover and degree of habitat clustering – from satellite images, we can adjust the state variables of METE accordingly and predict species richness. We compared the empirically derived and METE predicted species-abundance distributions, and show that our method indeed works. Our adjusted METE predictions can demonstrate the severity of fragmentation’s impact on biodiversity, relative to what could be expected in a pristine, continuous environment. With this new method, we can estimate the immediate effects of habitat loss on biodiversity loss, as well as its long-term effects.