Fuzzy sets allow gaging the extent and rate of species range shift due to climate change

Abstract

The recent modification of species distribution ranges in response to a warmer climate has constituted a major and generalized biogeographic change. The main driver of the shift in distribution is the disequilibrium of the species ranges with their climatic favourability. Most species distribution modelling approaches assume equilibrium of the distribution with the environment, which hinders their applicability to the analysis of this change. Using fuzzy set theory we assessed the response to climate change of a historically African species, the Atlas Long-legged Buzzard. With this approach we were able to quantify that the Buzzard’s distribution is in a latitudinal disequilibrium of the species distribution with the current climate of 4 km, which is driving the species range northwards at a speed of around 1.3 km/year, i.e., it takes 3 years for the species to occupy new climatically favourable areas. This speed is expected to decelerate to 0.5 km/year in 2060–2080.

Testing the effect of sample prevalence and sampling methods on probability- and favourability-based SDMs

“…Furthermore, it allows obtaining more effective comparisons among SDMs of different species or populations and time scales as a consequence of a lower pixels variability. This makes the favourability an extremely powerful tool to broaden our understanding of ecological trends such as the ecological niches pattern between species (Pulido-Pastor et al, 2021), the environmental factors that favor the spread of an invasive species (Romero et al, 2014;Baquero et al, 2021) or an epidemiological vector (Aliaga-Samanez et al, 2021), the areal shift range under land and climate changes (Muñoz et al, 2005;Chamorro et al, 2020). However, it is of paramount importance to point out that the favourability-based SDMs are dependent on the extent of analysis being chosen (VanDerWal et al, 2009), as well as on the spatial resolution of the predictors , and it is unequivocally associated with the environmental features of the study area (Barbosa et al, 2009).…”

Understanding parapatry: How do environment and competitive interactions shape Iberian vipers’ distributions?

“…These rapid changes could worsen the conservation status of the species given that low densities and high vulnerability to habitat and climate change are already threatening Iberian viper populations (Brito et al, 2011; Santos et al, 2006). Favourability models are useful tools to reveal the internal complexity of species distribution ranges (Acevedo et al, 2014; Real et al, 2003), understand their origins and peculiarities (Acevedo et al, 2015) and forecast range dynamics (Chamorro et al, 2020). This study also demonstrates that this methodological approach is of practical use in the study of complex parapatric distributional patterns, provides information on the ecology of the species and helps to establish new directional hypotheses on the effect of competitive exclusion.…”

Understanding the Geographic Patterns of Closely-Related Species of Paspalum (Poaceae) Using Distribution Modelling and Seed Germination Traits

“…The spatial factor (Ysp) was built using a polynomial trend-surface analysis that includes quadratic, cubic, and interaction effects of latitude (La) and longitude (Lo) (Lo, Lo2, Lo3, La, La2, La3, LaLo, La2Lo, and LaLo2). This spatial descriptor detects geographic trends that are not evident with other environmental variables [ 21 , 100 , 101 , 102 , 103 , 104 ].…”