Minimum temperature and precipitation determine fish richness pattern in China's nature reserves

Abstract

Understanding the drivers of geographic variation in species richness is one of the fundamental goals in ecology and biogeography. Fish is the key element in freshwater ecosystem and the focus of fishery production and biological conservation. Chinese freshwater fish fauna is rich and largely endemic due to variable geography and climate. By compiling the published data on fish richness for 86 nature reserves, and taking environmental predictors into consideration, we aimed to test latitudinal and longitudinal gradients in fish richness and the relative roles of energy availability, physiological tolerance, climatic seasonality and habitat heterogeneity hypotheses in explaining geographic fish richness pattern. Fish richness in China's nature reserves decreases with latitude and showed a hump-shaped relationship with longitude. Latitudinal fish richness is mainly shaped by mean temperature of the coldest month. Mean elevation and associated changes in temperature lead to longitudinal fish richness gradient. Among the four hypotheses tested, physiological tolerance hypothesis performs best and accounts for 55.4 % of the spatial variance in fish richness. Minimum temperature and precipitation are the primary determinants of fish species richness. Habitat heterogeneity is not negligible since adding river density to physiological tolerance model can explain additional 2 % variance in fish richness. Our results can provide useful information for regional fish production and conservation.

Relationship of minimum winter temperature and temperature seasonality to the northern range limit and species richness of trees in North America

“…The latitudinal diversity gradient (i.e., the decrease of species richness with increasing latitude) is one of the most conspicuous and robust biogeographic patterns (Rosenzweig, 1995;Hillebrand, 2004). Previous studies have shown that the northern limits of species distributions in North America are associated with low temperature in winter (Huntley et al, 1989;Zanne et al, 2014; hereafter minimum winter temperature or minimum temperature), which is often measured as the average minimum temperature of the coldest month (e.g., Hawkins et al, 2014) or the average overall temperature of the coldest month (e.g., Chen et al, 2018;Wang et al, 2018;Chen and Su, 2020). These two measures of minimum temperature are often nearly perfectly correlated (e.g., r = 0.996 in data from WorldClim for North America, www.worldclim.org).…”