Top-down and bottom-up control on cougar and its prey in a central Mexican natural reserve

Top-down and bottom-up controls are hypothesized to regulate population structures in many ecosystems. However, few studies have had the opportunity to analyze both processes in the natural environment, especially on large carnivores like the cougar (Puma concolor). Previously, studies show that cougar diet in the Sierra Nanchititla Natural Reserve (SNNR), central Mexico, is mainly armadillo, coati, and white-tailed deer. We assess whether top-down and/or bottom-up control regulate this endangered food web: (a) we predicted that seasonal per capita changes in abundance (pca) of cougar will be positively affected by the abundance of their main prey; (b) primary productivity in SNNR will affect the pca of prey species, driving bottom-up control; and (c) armadillo, coati, and white-tailed deer pca will be affected by the abundance of cougar, generating top-down control. Using 15 camera traps for 6 years in the SNNR, we calculated a relative abundance index (RAI) and pca for cougar and each of the focal prey, and we used the normalized difference vegetation index (NDVI) as a proxy of primary productivity. We constructed multiple regression models and selected the best linear models based on ranking the AICc values. Our analysis suggests that P. concolor pca is best explained by bottom-up control and intraspecific feedback. White-tailed deer and armadillo pca were both significantly affected by cougar abundance, indicating top-down control for these prey species, but NDVI was not retained in any of the models selected for prey pca. Our results indicate that both bottom-up and top-down control are involved in regulating this endangered food web in the SNNR, Mexico

Disentangling the role of remotely sensed spectral heterogeneity as a proxy for North American plant species richness

Due to the difficulties of field-based species data collection at wide spatial scales, remotely sensed spectral diversity has been advocated as one of the most effective proxies of ecosystem and species diversity. It is widely accepted that the relationship between species and spectral diversity is scale dependent. However, few studies have evaluated the impacts of scale on species diversity estimates from remote sensing data. In this paper we tested the species versus spectral relationship over very large scales (extents) with a varying spatial grain using floristic data of North America. Spectral diversity explained a low amount of variance while spatial extent of the sampling units (floras) explained a high amount of variance based on results from our variance partitioning analyses. This leads to the conclusion that spectral diversity must be carefully related to species diversity, explicitly taking into account potential area effect