PLoS ONE (Jan 2021)
Changes in the structure and composition of the 'Mexical' scrubland bee community along an elevational gradient.
Abstract
'Mexical' scrubland is a sclerophyllous evergreen Mediterranean-like vegetation occurring in the leeward slopes of the main Mexican mountain ranges, under tropical climate. This biome occupies an elevational range approximately from 1900 to 2600 meters above sea level, which frequently is the upper-most part of the mountains range. This puts it at risk of extinction in a scenario of global warming in which an upward retraction of this type of vegetation is expected. The Mexical remains one of the least studied ecosystems in Mexico. For instance, nothing is known about pollinator fauna of this vegetation. Our main objective is to make a first insight into the taxonomic identity of the bee fauna that inhabits this biome, and to study how it is distributed along the elevational gradient that it occupies. Our results highlight that elevation gradient negatively affects bee species richness and that this relationship is strongly mediated by temperature. Bee abundance had no significant pattern along elevational gradient, but shows a significant relationship with flower density. Interestingly, and contrary to previous works, we obtained a different pattern for bee richness and bee abundance. Bee community composition changed strongly along elevation gradient, mainly in relation to temperature and flower density. In a global warming scenario, as temperatures increases, species with cold preferences, occupying the highest part of the elevation gradient, are likely to suffer negative consequences (even extinction risk), if they are not flexible enough to adjust their physiology and/or some life-story traits to warmer conditions. Species occupying mid and lower elevations are likely to extend their range of elevational distribution towards higher ranges. This will foreseeably cause a new composition of species and a new scenario of interactions, the adjustment of which still leaves many unknowns to solve.