The mid‐domain effect matters: simulation analyses of range‐size distribution data from Mount Kinabalu, Borneo

Abstract

Aim In simulation exercises, mid-domain peaks in species richness arise as a result of the random placement of modelled species ranges within simulated geometric constraints. This has been called the mid-domain effect (MDE). Where close correspondence is found between such simulations and empirical data, it is not possible to reject the hypothesis that empirical species richness patterns result from the MDE rather than being the outcome (wholly or largely) of other factors. To separate the influence of the MDE from other factors we therefore need to evaluate variables other than species richness. The distribution of range sizes gives different predictions between models including the MDE or not. Here, we produce predictions for species richness and distribution of range sizes from one model without the MDE and from two MDE models: a classical MDE model encompassing only species with their entire range within the domain (rangerestricted MDE), and a model encompassing all species with the theoretical midpoint within the domain (midpoint-restricted MDE). These predictions are compared with observations from the elevational pattern of range-size distributions and species richness of vascular plants. Location Mount Kinabalu, Borneo.Methods The data set analysed comprises more than 28,000 plant specimens with information on elevation. Species ranges are simulated with various assumptions for the three models, and the species simulated are subsequently subjected to a sampling that simulates the actual collection of species on Mount Kinabalu. The resulting pattern of species richness and species range-size distributions are compared with the observed pattern. ResultsThe comparison of simulated and observed patterns indicates that an underlying monotonically decreasing trend in species richness with elevation is essential to explain fully the observed pattern of richness and range size. When the underlying trend is accounted for, the MDE model that restricts the distributions of theoretical midpoints performs better than both the classical MDE model and the model that does not incorporate geometric constraints.Main conclusions Of the three models evaluated here, the midpoint-restricted MDE model is found to be the best for explaining species richness and species range-size distributions on Mount Kinabalu.

Elevational diversity of terrestrial rainforest herbs: when the whole is less than the sum of its parts

“…A large number of partly non-exclusive explanations have been proposed for taxon-specific elevational richness patterns, including (1) current climatic variables such as temperature and humidity (Heaney 2001;Kessler 2001;Bhattarai et al 2004) which in turn determine energy availability and ecosystem productivity (Hawkins et al 2003;Currie et al 2004), (2) spatial aspects including regional area size (Rosenzweig and Ziv 1999) and geometric constraints (Colwell et al 2004;Grytnes et al 2008), (3) historical and evolutionary processes (Ricklefs 2004), and (4) biotic processes such as the Rapoport rescue hypothesis (Stevens 1989) or source-sink effects (Grytnes 2003;Kessler 2009). All of these factors may covary with both hump-shaped and linear species richness patterns, and discrimination between them is frequently difficult, especially due to a lack of relevant ecological data.…”

Elevational patterns of species richness and density of rattan palms (Arecaceae: Calamoideae) in Central Sulawesi, Indonesia

“…Bromeliaceae: Kessler 2001b, ferns: Kluge et al 2006). While the causes determining elevational richness patterns in plants remain poorly understood, available explanations may be grouped into four factor complexes (McCain 2009), namely (1) current climatic variables such as temperature and humidity (Kessler 2001a;Bhattarai et al 2004), which in turn determine energy availability and ecosystem productivity (Hawkins et al 2003;Currie et al 2004), (2) spatial aspects including regional areal size (Rosenzweig and Ziv 1999) and geometric constraints (Bachmann et al 2004, Grytnes et al 2008, (3) historical and evolutionary processes (Ricklefs 2004) and (4) biotic processes such as the Rapoport rescue hypothesis (Stevens 1989) or source-sink effects (Grytnes 2003;Kessler et al 2009). With the exception of area, which usually declines continuously with elevation, all of these factors may be related with hump-shaped species richness patterns.…”

Constraining null models with environmental gradients: a new method for evaluating the effects of environmental factors and geometric constraints on geographic diversity patterns

“…If not, the idea that geometric constraints affect richness patterns should be rejected (Lees and Colwell 2007, Rahbek et al 2007, Currie and Kerr 2008, Grytnes et al 2008. When the environmental gradients underlying geographic richness patterns are estimated correctly, the EGCM can provide a robust method to assess the role of geometric constraints.…”