Ant diversity in Neotropical savannas: Hierarchical processes acting at multiple spatial scales

Abstract

Understanding what creates and maintains macroscale biodiversity gradients is a central focus of ecological and evolutionary research. Spatial patterns in diversity are driven by a hierarchy of factors operating at multiple scales. Historical and climatic factors drive large‐scale patterns of diversity by affecting the size of regional species pools, while habitat heterogeneity or microhabitat characteristics further influence species coexistence at small scales. We tested the degree to which the species–energy, historical factors, habitat heterogeneity and local environment hypotheses explain observed patterns of ant diversity across hierarchical spatial scales. We sampled ground‐dwelling ants at 29 sites within a Neotropical savanna region, the Brazilian Cerrado. We measured species density – an abundance‐dependent diversity metric – and rarefied species richness – an abundance‐independent metric – at spatial scales with varying grain sizes. For each hypothesis, two correlates were used to predict ant diversity patterns: (a) species–energy: rainfall and productivity; (b) historical factors: historical variation in rainfall and refugial areas; (c) habitat heterogeneity: heterogeneity in greenness and diversity of land cover; and (d) local factors: contents of sand and coarse fragments in the soil. Ant diversity patterns correlated to net primary productivity and to the proportion of coarse fragments in the soil, corroborating the species–energy and local environment hypotheses, respectively. Soil negatively influenced species density, but not rarefied species richness, which was positively influenced by productivity. We found scale dependencies in the effects of soil/productivity on species density; productivity best predicted species density patterns at large scales, since sampling completeness offset the abundance‐driven effects of soil. Considering abundance differences may help to discern the mechanisms underlying the relationship between macroscale diversity patterns and its ecological drivers. Plant productivity affected ant diversity independently of abundance, possibly by limiting the size of regional species pools. On the other hand, soil properties had an abundance‐dependent effect on ant diversity, indicating a sampling mechanism. Our findings are consistent with predictions of the hierarchical theory of diversity. Large‐scale patterns of productivity limit regional diversity, an effect that cascades down to finer spatial scales, where soil properties influence the number of coexisting species.

Microhabitats shape ant community structure in a spatially heterogeneous grassy woodland

“…Vegetation and habitat cover therefore appears to shape the distribution of ant species in Australia's temperate grassy woodlands over scales of only a few meters. This finding is congruent with other multiscale studies of ant communities that have identified important small-scale drivers of ant community structure (Maravalhas & Vasconcelos, 2020;Pérez-S anchez et al, 2023). Similar findings have been reported for arthropods and soil microbes in grassy woodlands (Barton et al, 2010(Barton et al, , 2017Hamonts et al, 2017).…”

“…Studies on animal communities, including ant communities (Cushman & McGarigal, 2002; Whittaker et al, 2001), have identified a hierarchical suite of factors affecting diversity and community composition, including large‐scale biogeographic factors like primary productivity down to small‐scale environmental heterogeneity and soil characteristics (Maravalhas & Vasconcelos, 2020; Pérez‐Sánchez et al, 2023; Spiesman & Cumming, 2008). Within this range of scales, vegetation or land use type can vary across landscapes, whereas vegetation cover or complexity can vary at much smaller, local scales (Oliver et al, 2016; Spiesman & Cumming, 2008).…”

The Subhabitat Dependence of Biogeographic Pattern

“…As a result, biogeographic patterns for regional biotas are sometimes necessarily inferred based on subsets of data. For instance, many biogeographic surveys have focused only on specific groups of organisms, such as birds (Hazzi et al, 2018), fish (Cowman et al, 2017), trees (Dick and Pennington, 2019), algae (Stekoll, 2019), crustaceans (Brun et al, 2020), or ants (Maravalhas and Vasconcelos, 2020), to name just a few. To some extent, however, different groups of organisms may differ in biogeographic pattern within a region, as the various drivers of species distribution may vary in importance among the groups (Qian et al, 1998;Hart and Chen, 2006;Chiu et al, 2020).…”