Occurrence data may provide unreliable thermal preferences and breadth of species

Abstract

Accurate information on the thermal preference and specialization of species is needed to understand and predict species geographical range size and vulnerability to climate change. Here we estimate the position and breadth of species within thermal gradients based on the shape of the response curve of species abundance to temperature. The objective of the study is to compare the measurements of this approach based on abundance data with those of the classical approach using species’ occurrence data. The relationship between species’ relative abundance and minimum winter temperature of 106 bird species wintering in the Iberian Peninsula is modeled at 100 Km2 resolution with quadratic logistic regressions. From these models we calculated the preferred temperature of species as the temperature at which the abundance is maximized, and the thermal breadth of species as the relative area under the temperature-abundance curve. We also estimated the thermal preferences and breadth of species as the average temperature and temperature range of the UTM cells in which the species are present. The abundance-temperature response curves reveal that birds prefer higher temperatures to overwinter, and are more thermally selective, than is measured by the classical approach. Moreover, response curves detect a higher inter-specific variability in both thermal preferences and thermal breadth of species. As occurrence data gives the same weight to cells with one or many individuals, the average temperature of the cells in which the species is present roughly reflects the average temperature in the region of study and not the environmental preferences of species.

Multidimensionality in the thermal niches of dung beetles could limit species’ responses to temperature changes

“…2). The temperature optimum of each species was assessed by fitting quadratic curves in a GLM and calculating the maxima as their inflection point (see Villén-Pérez & Carrascal 2015 for a similar procedure). Thermal niche breadth was also obtained as the area under the curve of these fitted curves.…”

Thermal niche dimensionality could limit species’ responses to temperature changes: Insights from dung beetles

“…However, occurrence‐based thermal niches may nevertheless be characterized by different attributes such as the optimum temperature and niche breadth (Gouveia et al, 2014; Löffler & Pape, 2020; Figure 2). Each species’ temperature optimum was assessed by fitting quadratic curves in a GLM and calculating the maxima as their inflection point (see Villén‐Pérez & Carrascal, 2015 for a similar procedure). Thermal niche breadth was also obtained as the area under the curve of these fitted curves.…”

Acoustic species distribution models (aSDMs): A framework to forecast shifts in calling behaviour under climate change

“…Whereas the correlative approach combines readily available biogeographical and environmental data to model species distributions (Rodríguez‐Rodríguez et al, 2020), the mechanistic one offers a process‐based approach to better examine the potential response of species to changing environments (Peterson, 2011). Biogeographical data are a key, but incomplete proxy for environmental suitability and species persistence, especially when considering presence‐only data (Villén‐Pérez & Carrascal, 2015). For instance, source‐sink dynamics may yield presence records in unsuitable habitats (sinks), supported by individual dispersal from high quality habitats (sources), which reveals the limitation of presence records to predict habitat suitability (Schurr et al, 2012).…”