Network analysis unravels patterns of species richness along a climatic gradient in Spanish forests

Background/Question/Methods

The study of species richness at large extent along climate gradients is commonly investigated aggregating local site data at coarser grain, although this technique may introduce artifacts, such as introducing spurious species co-occurrences, or changing the steepness of the relationships between species richness and the explanatory climatic variables. In this work, we examined woody species richness in mainland Spain, with the main objectives of  (i) examining whether (or not) climate is connected to species richness, and (ii) highlighting the effectiveness of a new technique in unfolding hidden patterns in an ecological presence/absence dataset. For this, we used data from the Spanish Forest Inventory, which describes forests at small, local scale (i.e. circular plot side of ≤25 m radius), and we introduced the “method of reflections”, a network technique that redefined species richness at the local level including information about species distribution and the inter-species structure in the whole dataset, integrating locally the global signal without the need of data geographical aggregation.

Results/Conclusions

Annual precipitation and (to a lesser extent) mean annual temperature explained large parts of the variance of the newly defined “generalized” species richness, and therefore of the whole plant network structure. The method highlighted that, at the local scales, communities in the drier and warmer areas were the species richest, while geographical upscaling of the data did not unfold this pattern. The most diverse sites followed more closely the climate prediction, while sites poor in species were more likely to deviate. The insights obtained this way strongly suggest that the method of reflections is a powerful instrument to detect main factors underlying the distribution of a certain group of species, and thus it could have numerous applications in ecology.