Overview of Friedman’s Test and Post-hoc Analysis

When the null hypothesis of Friedman’s test is rejected, there is a wide variety of multiple comparisons that can be used to determine which treatments differ from each other. We will discuss the contexts where different multiple comparisons should be applied, when the population follows some discrete distributions commonly used to model count data in biological and ecological fields. Our simulation study shows that sign test is very conservative. Fisher’s LSD and Tukey’s HSD tests computed with ranks are the most liberal. Theoretical considerations are illustrated with data of the Azores Buzzard (Buteo buteo rothschildi) population from Azores, Portugal.     

Langevin incremental mixture importance sampling

This work proposes a novel method through which local information about the target density can be used to construct an efficient importance sampler. The backbone of the proposed method is the incremental mixture importance sampling (IMIS) algorithm of Raftery and Bao (Biometrics 66(4):1162–1173, 2010), which builds a mixture importance distribution incrementally, by positioning new mixture components where the importance density lacks mass, relative to the target. The key innovation proposed here is to construct the mean vectors and covariance matrices of the mixture components by numerically solving certain differential equations, whose solution depends on the local shape of the target log-density. The new sampler has a number of advantages: (a) it provides an extremely parsimonious parametrization of the mixture importance density, whose configuration effectively depends only on the shape of the target and on a single free parameter representing pseudo-time; (b) it scales well with the dimensionality of the target; (c) it can deal with targets that are not log-concave. The performance of the proposed approach is demonstrated on two synthetic non-Gaussian densities, one being defined on up to eighty dimensions, and on a Bayesian logistic regression model, using the Sonar dataset. The Julia code implementing the importance sampler proposed here can be found at https://github.com/mfasiolo/LIMIS.     

Influence of habitat type and distance from source area on bird taxonomic and functional diversity in a Neotropical megacity

The Neotropical region has been subjected to massive urbanization, which poses high risks for some global biodiversity hotspots and losses of ecosystem functions and services. In this study, we investigate how distance from large patches of native forests (source areas) and vegetation (green)/and infrastructure (gray) characteristics affect bird species richness and functional diversity in São Paulo megacity, southeastern Brazil. We analyzed the effects of source areas and green/gray characteristics on species richness and functional diversity (richness, evenness, and divergence) indices. We detected 231 bird species, and our data confirmed our predictions: (1) bird species richness in urbanized habitats was found to be (~?50–85%) lower than in source habitats; (2) species richness and trait composition significantly decreased as the distance from the source area increased, while functional richness was not affected by this metric; and (3) shrub and herbaceous covers and maximum height of trees were positively correlated with species richness and unique functional traits regarding habitat, diet, foraging and nesting strata and dispersal ability of birds in the forest-urban matrix. The number of buildings was negatively correlated with bird species richness and functional richness. Maximum height of buildings caused dramatic declines in functional evenness. Functional divergence was notably lower in sites with high shrub cover. Our study stresses the complexity of vegetation embedded in large Neotropical urban settlements and the need to maintain large protected areas surrounding megacities to mitigate the impacts of urbanization on birds.