Temperature, but not productivity or geometry, predicts elevational diversity gradients in ants across spatial grains

Abstract

Aim This research aims to understand the factors that shape elevational diversity gradients and how those factors vary with spatial grain. Specifically, we test the predictions of the species-productivity hypothesis, species-temperature hypothesis, the metabolic theory of ecology and the mid-domain effects null model. We also examine how the effects of productivity and temperature on richness depend on spatial grain. Location Deciduous forests along an elevational gradient in Great Smoky MountainsNational Park, USA. MethodsWe sampled 22 leaf litter ant assemblages at three spatial grains, from 1-m 2 quadrats to 50 × 50 m plots using Winkler samplers.Results Across spatial grains, warmer sites had more species than did cooler sites, and primary productivity did not predict ant species richness. We found some support for the predictions of the metabolic theory of ecology, but no support for the mid-domain effects null model. Thus, our data are best explained by some version of a species-temperature hypothesis. Main conclusionsOur results suggest that temperature indirectly affects ant species diversity across spatial grains, perhaps by limiting access to resources. Warmer sites support more species because they support more individuals, thereby reducing the probability of local extinction. Many of our results from this elevational gradient agree with studies at more global scales, suggesting that some mechanisms shaping ant diversity gradients are common across scales.

Changes of bat species composition over altitudinal gradients on northern and southern aspects of the Soutpansberg mountain range, South Africa

“…We used step-wise multiple regressions based on AIC values to analyse which variables have a significant influence on bat activity and estimated richness (Crawley 2007, Sanders et al 2007). The same modelling was repeated with the data from both aspects, excluding the continuous variables which were available solely from the study on the northern aspect (canopy cover, rainfall, temperature, vegetation density) but including the variable moon phase.…”

Species diversity of bats along an altitudinal gradient on Mount Mulanje, southern Malawi

“…These were average nightly temperature and relative humidity at the time of sampling, mean annual temperature, mean annual relative humidity, total and forested area within 100-m altitudinal bands centred around each sampling site, and the Normalized Difference Vegetation Index (NDVI) as a proxy for productivity. Because the low number of sampling sites prevented application of a multivariate approach to elucidate the role of these predictors, such as stepwise multiple regression (Sanders et al 2007), we tested each predictor for a univariate correlation with diversity using simple linear regression. Additional information pertaining to the study, including a detailed account of the methodology used to derive these additional variables, can be found at http://sites.google.com/site/jakobfahr.…”

“…Fisher's α has also been shown to perform well at low to medium sampling intensities (Beck & Schwanghart 2010, Fisher et al 1943, Hurlbert 1971, and showed no significant relationship with any proxy of sampling effort. Some authors (Sanders et al 2007) have used Fisher's α as a direct proxy for species richness because of its robustness to undersampling, but we avoided this because the two indices measure different properties of diversity, and Fisher's α may be misleading where samples approach completeness (Beck & Schwanghart 2010).…”

Florística e fitossociologia em parcelas permanentes da Mata Atlântica do sudeste do Brasil ao longo de um gradiente altitudinal

“…Em áreas mais altas (>500 m, na Floresta Ombrófila Densa Montana) a riqueza decai em relação às áreas de altitude intermediária (400 m) (Figura 8). Há atualmente um intenso debate na literatura sobre os fatores causais deste padrão, com hipóteses relacionadas com a produtividade (Evans et al 2005), temperatura (Sanders et al 2007), a Teoria Metabólica da Ecologia (MET) , o efeito geométrico ("mid-domain effect" Colwell & Lees 2000) e o efeito "Massenerhebung" (Grubb 1971, Bruijnzeel et al 1993.…”