Protracted speciation revitalizes the neutral theory of biodiversity.

Understanding the maintenance and origin of biodiversity is a formidable task, yet many ubiquitous ecological patterns are predicted by a surprisingly simple and widely studied neutral model that ignores functional differences between species. However, this model assumes that new species arise instantaneously as singletons and consequently makes unrealistic predictions about species lifetimes, speciation rates and number of rare species. Here, we resolve these anomalies - without compromising any of the original models existing achievements and retaining computational and analytical tractability - by modelling speciation as a gradual, protracted, process rather than an instantaneous event. Our model also makes new predictions about the diversity of incipient species and rare species in the metacommunity. We show that it is both necessary and straightforward to incorporate protracted speciation in future studies of neutral models, and argue that non-neutral models should also model speciation as a gradual process rather than an instantaneous one

Spatial scaling of forest soil microbial communities across a temperature gradient.

Temperature is an important correlate of global patterns of biodiversity, yet the mechanisms driving these relationships are not well understood. Taxa-area relationships (TARs) have been intensively examined, but the effects of temperature on TARs, particularly for microbial communities, are largely undocumented. Here we present a continental-scale description of temperature-dependent nested TARs of microbial communities (bacteria and archaea) from soils of six forest sites spanning a temperature gradient from subalpine Colorado to tropical Panama. Our results revealed that spatial scaling rates (z-values) of microbial communities varied with both taxonomic resolutions and phylogenetic groups. Additionally, microbial TAR z-values increased with temperature (r = 0.739, P < 0.05), but were not correlated with other environmental variables tested (P > 0.05), indicating that microbial spatial scaling rate is temperature-dependent. Understanding how temperature affects the spatial scaling of microbial biodiversity is of fundamental importance for preservation of soil biodiversity and management of ecosystems

How climatic variability is linked to the spatial distribution of range sizes: seasonality versus climate change velocity in sphingid moths

Aim: To map the spatial variation of range sizes within sphingid moths, and to test hypotheses on its environmental control. In particular, we investigate effects of climate change velocity since the Pleistocene and the mid-Holocene, temperature and precipitation seasonality, topography, Pleistocene ice cover, and available land area. Location: Old World and Australasia, excluding smaller islands. Methods: We used fine-grained range maps (based on expert-edited distribution modelling) for all 972 sphingid moth species in the research region and calculated, at a grain size of 100 km, the median of range sizes of all species that co-occur in a pixel. Climate, topography and Pleistocene ice cover data were taken from publicly available sources. We calculated climate change velocities (CCV) for the last 21ky as well as 6ky. We compared the effects of seasonality and CCV on median range sizes with spatially explicit models while accounting for effects of elevation range, glaciation history and available land area. Results: Range sizes show a clear spatial pattern, with highest median values in deserts and arctic regions and lowest values in isolated tropical regions. Range sizes were only weakly related to absolute latitude (predicted by Rapoport’s effect), but there was a strong north-south pattern of range size decline. Temperature seasonality emerged as the strongest environmental correlate of median range size, in univariate as well as multivariate models, whereas effects of CCV were weak and unstable for both time periods. These results were robust to variations in the parameters in alternative analyses, among them multivariate CCV. Main conclusions: Temperature seasonality is a strong correlate of spatial range size variation, while effects of longer-term temperature change, as captured by CCV, received much weaker support.The attached document is the author(’s’) final accepted/submitted version of the journal article. You are advised to consult the publisher’s version if you wish to cite from i

Species abundance distribution results from a spatial analogy of central limit theorem

The frequency distribution of species abundances [the species abundance distribution (SAD)] is considered to be a fundamental characteristic of community structure. It is almost invariably strongly right-skewed, with most species being rare. There has been much debate as to its exact properties and the processes from which it results. Here, we contend that an SAD for a study plot must be viewed as spliced from the SADs of many smaller nonoverlapping subplots covering that plot. We show that this splicing, if applied repeatedly to produce subplots of progressively larger size, leads to the observed shape of the SAD for the whole plot regardless of that of the SADs of those subplots. The widely reported shape of an SAD is thus likely to be driven by a spatial parallel of the central limit theorem, a statistically convergent process through which the SAD arises from small to large scales. Exact properties of the SAD are driven by species spatial turnover and the spatial autocorrelation of abundances, and can be predicted using this information. The theory therefore provides a direct link between SADs and the spatial correlation structure of species distributions, and thus between several fundamental descriptors of community structure. Moreover, the statistical process described may lie behind similar frequency distributions observed in many other scientific fields

SESAM - a new framework integrating macroecological and species distribution models for predicting spatio-temporal patterns of species assemblages

Two different approaches currently prevail for predicting spatial patterns of species assemblages. The first approach (macroecological modelling, MEM) focuses directly on realised properties of species assemblages, whereas the second approach (stacked species distribution modelling, S-SDM) starts with constituent species to approximate assemblage properties. Here, we propose to unify the two approaches in a single 'spatially-explicit species assemblage modelling' (SESAM) framework. This framework uses relevant species source pool designations, macroecological factors, and ecological assembly rules to constrain predictions of the richness and composition of species assemblages obtained by stacking predictions of individual species distributions. We believe that such a framework could prove useful in many theoretical and applied disciplines of ecology and evolution, both for improving our basic understanding of species assembly across spatio-temporal scales and for anticipating expected consequences of local, regional or global environmental changes. In this paper, we propose such a framework and call for further developments and testing across a broad range of community types in a variety of environments

Multifractal diversity-area relationship at small scales in dune slack plant communities

The species-area relationship, SAR, is the first approximation to describe the spatial structure at the community level. This relation, however, takes only species richness into account and ignores interspecific differences in spatial patterns, such as dominance or rarity. The description of such patterns may be achieved via multifractal analysis, allowing the transition from SAR to the diversity-area relation, DAR. This study analyzes the spatial structure of a dune slack plant community, which can be considered as a multifractal object, at a scale level between 25 cm and 2 m. We applied a complete multifractal analysis including both Renyi spectrum and multifractal spectrum, using confidence intervals. The results indicated that we succeeded for the first time deriving generalized Renyi dimensions' spectrum without anomalies for diversity patterns in a plant community. We propose an interpretation of the multifractal spectrum in ecological terms as diversity patterns of subsets of species with a similar spatial distribution