Distinguishing niche and neutral processes: issues in variation partitioning statistical methods and further perspectives

Variance partitioning methods, which are built upon multivariate statistics, have been widely applied in different taxa and habitats in community ecology. Here, I performed a literature review on the development and application of the methods, and then discussed the limitation of available methods and the difficulties involved in sampling schemes. The central goal of the work is then to propose some potential practical methods that might help to overcome different issues of traditional least-square-based regression modeling. A variety of regression models has been considered for comparison. In initial simulations, I identified that generalized additive model (GAM) has the highest accuracy to predict variation components. Therefore, I argued that other advanced regression techniques, including the GAM and related models, could be utilized in variation partitioning for better quantifying the aggregation scenarios of species distribution.Comment: 19 pages; 4 figure

Does residence time affect responses of alien species richness to environmental and spatial processes?

One of the most robust emerging generalisations in invasion biology is that the probability of invasion increases with the time since introduction (residence time). We analysed the spatial distribution of alien vascular plant species in a region of north-eastern Italy to understand the influence of residence time on patterns of alien species richness. Neophytes were grouped according to three periods of arrival in the study region (1500–1800, 1800–1900, and > 1900). We applied multiple regression (spatial and nonspatial) with hierarchical partitioning to determine the influence of climate and human pressure on species richness within the groups. We also applied variation partitioning to evaluate the relative importance of environmental and spatial processes. Temperature mainly influenced groups with species having a longer residence time, while human pressure influenced the more recently introduced species, although its influence remained significant in all groups. Partial regression analyses showed that most of the variation explained by the models is attributable to spatially structured environmental variation, while environment and space had small independent effects. However, effects independent of environment decreased, and spatially independent effects increased, from older to the more recent neophytes. Our data illustrate that the distribution of alien species richness for species that arrived recently is related to propagule pressure, availability of novel niches created by human activity, and neutral-based (dispersal limitation) processes, while climate filtering plays a key role in the distribution of species that arrived earlier. This study highlights the importance of residence time, spatial structure, and environmental conditions in the patterns of alien species richness and for a better understanding of its geographical variation

Development of a land use regression model for black carbon using mobile monitoring data and its application to pollution-avoiding routing

Black carbon is often used as an indicator for combustion-related air pollution. In urban environments, on-road black carbon concentrations have a large spatial variability, suggesting that the personal exposure of a cyclist to black carbon can heavily depend on the route that is chosen to reach a destination. In this paper, we describe the development of a cyclist routing procedure that minimizes personal exposure to black carbon. Firstly, a land use regression model for predicting black carbon concentrations in an urban environment is developed using mobile monitoring data, collected by cyclists. The optimal model is selected and validated using a spatially stratified cross-validation scheme. The resulting model is integrated in a dedicated routing procedure that minimizes personal exposure to black carbon during cycling. The best model obtains a coefficient of multiple correlation of R = 0.520. Simulations with the black carbon exposure minimizing routing procedure indicate that the inhaled amount of black carbon is reduced by 1.58% on average as compared to the shortest-path route, with extreme cases where a reduction of up to 13.35% is obtained. Moreover, we observed that the average exposure to black carbon and the exposure to local peak concentrations on a route are competing objectives, and propose a parametrized cost function for the routing problem that allows for a gradual transition from routes that minimize average exposure to routes that minimize peak exposure