Ant diversity shows a variety of patterns across elevational gradients, though the patterns and drivers have not been evaluated comprehensively. In this systematic review and reanalysis, we use published data on ant elevational diversity to detail the observed patterns and to test the predictions and interactions of four major diversity hypotheses: thermal energy, the mid-domain effect, area, and the elevational climate model. Of sixty-seven published datasets from the literature, only those with standardized, comprehensive sampling were used. Datasets included both local and regional ant diversity and spanned 80° in latitude across six biogeographical provinces. We used a combination of simulations, linear regressions, and non-parametric statistics to test multiple quantitative predictions of each hypothesis. We used an environmentally and geometrically constrained model as well as multiple regression to test their interactions. Ant diversity showed three distinct patterns across elevations: most common were hump-shaped mid-elevation peaks in diversity, followed by low-elevation plateaus and monotonic decreases in the number of ant species. The elevational climate model, which proposes that temperature and precipitation jointly drive diversity, and area were partially supported as independent drivers. Thermal energy and the mid-domain effect were not supported as primary drivers of ant diversity globally. The interaction models supported the influence of multiple drivers, though not a consistent set. In contrast to many vertebrate taxa, global ant elevational diversity patterns appear more complex, with the best environmental model contingent on precipitation levels. Differences in ecology and natural history among taxa may be crucial to the processes influencing broad-scale diversity patterns.

The rush to assess species' responses to anthropogenic climate change (CC) has underestimated the importance of interannual population variability (PV). Researchers assume sampling rigor alone will lead to an accurate detection of response regardless of the underlying population fluctuations of the species under consideration. Using population simulations across a realistic, empirically based gradient in PV, we show that moderate to high PV can lead to opposite and biased conclusions about CC responses. Between pre- and post-CC sampling bouts of modeled populations as in resurvey studies, there is: (i) A 50% probability of erroneously detecting the opposite trend in population abundance change and nearly zero probability of detecting no change. (ii) Across multiple years of sampling, it is nearly impossible to accurately detect any directional shift in population sizes with even moderate PV. (iii) There is up to 50% probability of detecting a population extirpation when the species is present, but in very low natural abundances. (iv) Under scenarios of moderate to high PV across a species' range or at the range edges, there is a bias toward erroneous detection of range shifts or contractions. Essentially, the frequency and magnitude of population peaks and troughs greatly impact the accuracy of our CC response measurements. Species with moderate to high PV (many small vertebrates, invertebrates, and annual plants) may be inaccurate 'canaries in the coal mine' for CC without pertinent demographic analyses and additional repeat sampling. Variation in PV may explain some idiosyncrasies in CC responses detected so far and urgently needs more careful consideration in design and analysis of CC responses.

Aim Species richness is often strongly correlated with climate. The most commonly invoked mechanism for this climate‐richness relationship is the more‐individuals‐hypothesis (MIH), which predicts a cascading positive influence of climate on plant productivity, food resources, total number of individuals, and species richness. We test for a climate‐richness relationship and an underlying MIH mechanism, as well as testing competing hypotheses including positive effects of habitat diversity and heterogeneity, and the species‐area effect. Location Colorado Rocky Mountains, USA: two elevational gradients in the Front Range and San Juan Mountains. Methods We conducted standardized small mammal surveys at 32 sites to assess diversity and population sizes. We estimated vegetative and arthropod food resources as well as various aspects of habitat structure by sampling 20 vegetation plots and 40 pitfall traps per site. Temperature, precipitation and net primary productivity (NPP) were assessed along each gradient. Regressions and structural equation modelling were used to test competing diversity hypotheses and mechanistic links predicted by the MIH. Results We detected 3,922 individuals of 37 small mammal species. Mammal species richness peaked at intermediate elevations, as did productivity, whereas temperature decreased and precipitation increased with elevation. We detected strong support for a productivity‐richness relationship, but no support for the MIH mechanism. Food and mammal population sizes were unrelated to NPP or mammal species richness. Furthermore, mammal richness was unrelated to habitat diversity, habitat heterogeneity, or elevational area. Main conclusions Sites with high productivity contain high mammal species richness, but a mechanism other than a contemporary MIH underlies the productivity–diversity relationship. Possibly a mechanism based on evolutionary climatic affiliations. Protection of productive localities and mid‐elevations are the most critical for preserving small mammal richness, but may be decoupled from trends in population sizes, food resources, or habitat structure.

Understanding the forces that shape the distribution of biodiversity across spatial scales is central in ecology and critical to effective conservation. To assess effects of possible richness drivers, we sampled ant communities on four elevational transects across two mountain ranges in Colorado, USA, with seven or eight sites on each transect and twenty repeatedly sampled pitfall trap pairs at each site each for a total of 90 d. With a multi‐scale hierarchical Bayesian community occupancy model, we simultaneously evaluated the effects of temperature, productivity, area, habitat diversity, vegetation structure, and temperature variability on ant richness at two spatial scales, quantifying detection error and genus‐level phylogenetic effects. We fit the model with data from one mountain range and tested predictive ability with data from the other mountain range. In total, we detected 105 ant species, and richness peaked at intermediate elevations on each transect. Species‐specific thermal preferences drove richness at each elevation with marginal effects of site‐scale productivity. Trap‐scale richness was primarily influenced by elevation‐scale variables along with a negative impact of canopy cover. Soil diversity had a marginal negative effect while daily temperature variation had a marginal positive effect. We detected no impact of area, land cover diversity, trap‐scale productivity, or tree density. While phylogenetic relationships among genera had little influence, congeners tended to respond similarly. The hierarchical model, trained on data from the first mountain range, predicted the trends on the second mountain range better than multiple regression, reducing root mean squared error up to 65%. Compared to a more standard approach, this modeling framework better predicts patterns on a novel mountain range and provides a nuanced, detailed evaluation of ant communities at two spatial scales.

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