The Spatial Limitations of Current Neutral Models of Biodiversity

The unified neutral theory of biodiversity and biogeography is increasingly accepted as an informative null model of community composition and dynamics. It has successfully produced macro-ecological patterns such as species-area relationships and species abundance distributions. However, the models employed make many unrealistic auxiliary assumptions. For example, the popular spatially implicit version assumes a local plot exchanging migrants with a large panmictic regional source pool. This simple structure allows rigorous testing of its fit to data. In contrast, spatially explicit models assume that offspring disperse only limited distances from their parents, but one cannot as yet test the significance of their fit to data. Here we compare the spatially explicit and the spatially implicit model, fitting the most-used implicit model (with two levels, local and regional) to data simulated by the most-used spatially explicit model (where offspring are distributed about their parent on a grid according to either a radially symmetric Gaussian or a ‘fat-tailed’ distribution). Based on these fits, we express spatially implicit parameters in terms of spatially explicit parameters. This suggests how we may obtain estimates of spatially explicit parameters from spatially implicit ones. The relationship between these parameters, however, makes no intuitive sense. Furthermore, the spatially implicit model usually fits observed species-abundance distributions better than those calculated from the spatially explicit model's simulated data. Current spatially explicit neutral models therefore have limited descriptive power. However, our results suggest that a fatter tail of the dispersal kernel seems to improve the fit, suggesting that dispersal kernels with even fatter tails should be studied in future. We conclude that more advanced spatially explicit models and tools to analyze them need to be developed

A niche remedy for the dynamical problems of neutral theory

We demonstrate how niche theory and Hubbell's original formulation of neutral theory can be blended together into a general framework modeling the combined effects of selection, drift, speciation, and dispersal on community dynamics. This framework connects many seemingly unrelated ecological population models, and allows for quantitative predictions to be made about the impact of niche stabilizing and destabilizing forces on population extinction times and abundance distributions. In particular, the existence of niche stabilizing forces in our blended framework can simultaneously resolve two major problems with the dynamics of neutral theory, namely predictions of species lifetimes that are too short and species ages that are too long.Comment: 47 pages, 4 figures, Accepted to Theoretical Ecolog

Between explanans and explanandum: biodiversity and the unity of theoretical ecology

International audienceBiodiversity is arguably a major concept in ecology. Some of the key questions of the discipline are: why are species distributed the way they are, in a given area, or across areas? Or: why are there so many animals (as Hutchinson asked in a famous paper)? It appears as what is supposed to be explained, namely an explanandum of ecology. Various families of theories have been proposed, which are nowadays mostly distinguished according to the role they confer to competition and the competitive exclusion principle. Niche theories, where the difference between "fundamental" and "realised" niches (Hutchinson 1959) through competitive exclusion explains species distributions, contrast with neutral theories, where an assumption of fitness equivalence, species abundance distributions are explained by stochastic models, inspired by Hubbell (2001). Yet, while an important part of community ecology and biogeography understands biodiversity as an explanan-dum, in other areas of ecology the concept of biodiversity rather plays the role of the explanans. This is manifest in the long lasting stability-diversity debate, where the key question has been: how does diversity beget stability? Thus explanatory reversibility of the biodiversity concept in ecology may prevent biodiversity from being a unifying object for ecology. In this chapter, I will describe such reversible explanatory status of biodiversity in various ecological fields (biogeography, functional ecology, community ecology). After having considered diversity as an explanandum, and then as an explanans, I will show that the concepts of biodiversity that are used in each of these symmetrical explanatory projects are not identical nor even equivalent. Using an approach to the concept of biodiversity in terms of "conceptual space", I will finally argue that the lack of unity of a biodiversity concept able to function identically as explanans and explanandum underlies the structural disunity of ecology that has been pointed out by some historians and philosophers

A Multi-Scale Distribution Model for Non-Equilibrium Populations Suggests Resource Limitation in an Endangered Rodent

Species distributions are known to be limited by biotic and abiotic factors at multiple temporal and spatial scales. Species distribution models, however, frequently assume a population at equilibrium in both time and space. Studies of habitat selection have repeatedly shown the difficulty of estimating resource selection if the scale or extent of analysis is incorrect. Here, we present a multi-step approach to estimate the realized and potential distribution of the endangered giant kangaroo rat. First, we estimate the potential distribution by modeling suitability at a range-wide scale using static bioclimatic variables. We then examine annual changes in extent at a population-level. We define "available" habitat based on the total suitable potential distribution at the range-wide scale. Then, within the available habitat, model changes in population extent driven by multiple measures of resource availability. By modeling distributions for a population with robust estimates of population extent through time, and ecologically relevant predictor variables, we improved the predictive ability of SDMs, as well as revealed an unanticipated relationship between population extent and precipitation at multiple scales. At a range-wide scale, the best model indicated the giant kangaroo rat was limited to areas that received little to no precipitation in the summer months. In contrast, the best model for shorter time scales showed a positive relation with resource abundance, driven by precipitation, in the current and previous year. These results suggest that the distribution of the giant kangaroo rat was limited to the wettest parts of the drier areas within the study region. This multi-step approach reinforces the differing relationship species may have with environmental variables at different scales, provides a novel method for defining "available" habitat in habitat selection studies, and suggests a way to create distribution models at spatial and temporal scales relevant to theoretical and applied ecologists

Stimulation of the midkine/ALK axis renders glioma cells resistant to cannabinoid antitumoral action

Identifying the molecular mechanisms responsible for the resistance of gliomas to anticancer treatments is an issue of great therapeutic interest. Δ9-Tetrahydrocannabinol (THC), the major active ingredient of marijuana, and other cannabinoids inhibit tumor growth in animal models of cancer, including glioma, an effect that relies, at least in part, on the stimulation of autophagy-mediated apoptosis in tumor cells. Here, by analyzing the gene expression profile of a large series of human glioma cells with different sensitivity to cannabinoid action, we have identified a subset of genes specifically associated to THC resistance. One of these genes, namely that encoding the growth factor midkine (Mdk), is directly involved in the resistance of glioma cells to cannabinoid treatment. We also show that Mdk mediates its protective effect via the anaplastic lymphoma kinase (ALK) receptor and that Mdk signaling through ALK interferes with cannabinoid-induced autophagic cell death. Furthermore, in vivo Mdk silencing or ALK pharmacological inhibition sensitizes cannabinod-resistant tumors to THC antitumoral action. Altogether, our findings identify Mdk as a pivotal factor involved in the resistance of glioma cells to THC pro-autophagic and antitumoral action, and suggest that selective targeting of the Mdk/ALK axis could help to improve the efficacy of antitumoral therapies for gliomas