Assessment of climatically suitable area for Syrmaticus reevesii under climate change

Abstract

Global climate change is one of the major threats to biodiversity. Global warming caused by the excess emission of greenhouse gases affects the distribution and physiology of species, and threatens their survival. Thus, predicting and evaluating the consequences of changing climates on species' distributions is important for biodiversity conservation. The goal of our study was to assess the influence of future climate scenarios on the extent and geographic location of climatically suitable areas for Reeves's pheasant Syrmaticus reevesii, a species endemic to China, using geographic information systems and ecological niche modeling techniques. We compared model prediction under present climate with the species' historical range and land-cover data, both of which enable a plausible assessment of present-day climatically suitable areas for the species. The areas predicted suitable under future climates showed differences among emission scenarios, but several common trends emerged. Specifically, our results indicated that future climatically suitable area for S. reevesii would decrease and shift to higher altitudes, and the geographic centroids of the climatically suitable areas would mainly move northwest. Additionally, we assessed future changes of climatically suitable areas in the nature reserves where S. reevesii is known to occur, and provided suggestions for conserving the species under climate change scenarios.

Collinearity in ecological niche modeling: Confusions and challenges

“…However, given the role of collinearity shift and the independence between degree of predictor collinearity and collinearity shift, Maxent is not totally immune to issues of collinearity. Our results showed that removing highly correlated variables did not significantly influence the accuracy of Maxent model (Table 1), regardless of model transfer scenario, because Maxent can regulate the contribution of redundant predictors; the aspect that matters more in Maxent modeling is the collinearity shift in model transfer scenarios; therefore, we recommend to quantify the collinearity shift as a proxy of model accuracy (e.g., Feng et al, 2015).…”

“…Maxent has been applied to a wide range of studies, including those related to discovering rare species (Fois, Fenu, Lombrana, Cogoni, & Bacchetta, 2015;Jackson & Robertson, 2011;Menon, Choudhury, Khan, & Peterson, 2010), conservation and invasive species management (Feng, Lin, Qiao, & Ji, 2015;Ficetola, Thuiller, & Miaud, 2007;Park & Potter, 2015a, 2015bRoura-Pascual, Brotons, Peterson, & Thuiller, 2009), and disease transmission (Escobar et al, 2015;Gonzalez et al, 2011). Concurrently, many methodological studies have aimed to optimize model performance.…”

Changes in the range of the medicinal herb Eriocaulon buergerianum Körnicke. (Eriocaulaceae) under climate change

“…; Feng et al . ): (i) any combination of environmental variables may affect a species’ fundamental niche; (ii) dispersal limitations from climate, physiology, geography or human factors; (iii) species interactions may also affect the range change; and (iv) unstable supplies of herbal medicines may lead to a range change.…”

Gap analysis and implications for seasonal management on a local scale

“…Environmental variables were calculated by interpolation of complex multivariate data using thin-plate smoothing splines with ANUSPLIN version 4.36. Based on previous research (Feng et al, 2015; Petitpierre et al, 2016) and survey results, nine environmental variables (two topography variables and seven climate variables) which can present species physiological limits were selected. We divided environmental variables into three groups: annual, summer, and winter (see details in Appendix I).…”