Recent and rapid ecogeographical rule reversals in Northern Treeshrews

Abstract

Two of the most-studied ecogeographical rules describe patterns of body size variation within species. Bergmann’s rule predicts that individuals have larger body sizes in colder climates (typically at higher latitudes), and the island rule predicts that island populations of small-bodied species average larger in size than their mainland counterparts (insular gigantism). These rules are rarely tested in conjunction or assessed across space and time simultaneously. We investigated these patterns in the Northern Treeshrew (Tupaia belangeri) using museum specimens collected across a wide spatial and temporal range. Contrary to Bergmann’s rule, size increases with temperature in T. belangeri, a signal that is highly consistent across space and time. We also show that these rules are intertwined: Bergmann’s rule is reversed on the mainland but holds on islands, and therefore the island rule is upheld at higher, but not lower, latitudes. Moreover, we demonstrate a rapid reversal of both rules over time. The mechanism behind these inversions remains unclear, though temperature and precipitation are significant predictors of body size. Ecogeographical rules rely on the assumption of a constant relationship between size and the factors driving its variation. Our results highlight the need to question this assumption and reevaluate these rules in the context of accelerating and uneven climate change.

Rocky rule: the idiosyncrasy of spatial and temporal size variation in mammals

“…Better knowledge of the current range-wide patterns of size variability in a given species may inform us on the nature of its response to climate warming, potentially affecting conservation efforts for vulnerable populations (Blois et al 2013; Coristine and Kerr 2015; Razgour et al 2019). However, the mechanisms driving size variation and variability in mammals are multiple (e.g., Juman et al 2022). Here, we focused directly on latitude (and indirectly on those drivers associated with latitude), but observed heterogeneity in the patterns of size variation points to other mechanisms operating at a local scale and idiosyncratically across species.…”

“…While Bergmann's rule provides a theoretical framework for the study of size variation in mammals and their adaptation to climate warming, more and more exceptions are reported (Millien 2004; Souto-Lima and Millien 2014; Sargis et al 2018; Juman et al 2022). Additional studies using empirical data are needed to tease apart the multiple drivers of size variation, especially in the context of climate warming.…”

“…However, changes in the surface-area-to-volume ratio of an individual due to thermoregulatory shifts may have a greater impact on BW than other two-dimensional or linear metrics (Yom-Tov and Geffen 2011;Teplitsky and Millien 2014). While Bergmann's rule provides a theoretical framework for the study of size variation in mammals and their adaptation to climate warming, more and more exceptions are reported (Millien 2004;Souto-Lima and Millien 2014;Sargis et al 2018;Juman et al 2022). Additional studies using empirical data are needed to tease apart the multiple drivers of size variation, especially in the context of climate warming.…”

A practical guide to collections‐based research on ecogeographic rules

“…A distinct possibility is combining multiple measurements, either for size or the predictor variables, together through tools such as principle component analysis (PCA), typically retaining the first component as a proxy (Juman et al, 2022 ). This method eliminates intercorrelations, reduces overfitting, and improves visualization, but is harder to interpret and requires standardization.…”

“…Finally, note that a sufficiently robust dataset can often be used to test multiple rules and test geographical and temporal models simultaneously (Juman et al, 2022 ). Such studies testing multiple ecogeographic hypotheses in conjunction are uncommon now, but are expected to become the norm, so both geographic and temporal data should be incorporated into a model whenever possible if supported by the data.…”