Testing diversity hypotheses: A global analysis of ant diversity across elevations

Background/Question/Methods

A comprehensive understanding of the patterns and drivers of diversity is essential to conserving ecosystems. A multitude of hypotheses have been proposed to explain the observed patterns. Investigating the corresponding predictions on a global scale and across multiple taxa may yield a more complete understanding of these processes. Mountain ranges, serving as replicates on every continent and each with a unique combination of potential drivers of diversity, are ideal systems for testing these hypotheses. In this study, I use published data on ant diversity across elevational gradients and a combination of non-parametric statistics and linear regression to test several predictions from each of four separate hypotheses: the Species-Area Relationship (SAR), the Mid-Domain Effect (MDE), temperature, and the Elevational Climate Model (ECM). Of 45 datasets investigated, only 20 met the a priori requirements of even sampling across elevations, coverage of at least 70% of the gradient including within the lowest 400m, and relatively low disturbance. These 20 gradients represent 6 biogeographical provinces, and include humid, arid, temperate and tropical mountains, and both regional and local diversity assessment.

Results/Conclusions

Ant elevational diversity showed four distinct patterns: (1) 60% detected a hump-shaped pattern with a peak in diversity at middle elevations, (2) 20% detected a low-elevation plateau with a mid-elevation peak, (3) 10% detected a low-elevation plateau followed by a monotonic decrease, and (4) 10% detected a simple monotonic decrease. The SAR was supported with most studies (80%) showing a significant, positive relationship according to the Arrhenius equation (S = cA^z). Only one study was consistent with all predictions of the MDE. Thus, though diversity often peaks at middle elevations, the MDE is unlikely to be responsible for this pattern. Temperature, which decreases monotonically with elevation, was also largely unsupported as a primary driver of ant diversity. The ECM predicts that diversity is governed by a combination of temperature and precipitation. The datasets showed fairly substantial support for this hypothesis with diversity on wet mountains showing a closer relationship with temperature (p = 0.003) and arid mountains having a smaller proportion of diversity at low elevations (p = 0.039). Therefore, patterns of ant diversity on mountains show support for both the SAR and the ECM as potential drivers of biodiversity.