Data used in the application of the multi-region community model (MRCM) to detection non-detection data collected from bird communities in R=8 geographically distinct regions in northern Italy. We augmented the data for all regions such that M = M_r = 200, i.e., by 200-n_r species for each region. The data file contains the following objects: (i) dataREG: region-specific covariates; (ii) guild: species-by-region matrix indicating the functional group to which each species belongs; (iii) K_tot: number of sampling occasions for each site in each region; (iv) M: total number of species in the augmented data set; (v) mass: body mass (in grams) for each species in each region; (vi) nsites: total number of sites per region; (vii) nspec...
Accurately characterizing spatial patterns on landscapes is necessary to understand the processes th...
Factors determining species distributions have frequently been shown to vary geographically, yieldin...
Variation partitioning analyses combined with spatial predictors (Moran’s eigenvector maps, MEM) are...
<p>Data used in the application of the multi-region community model (MRCM) to detection non-detectio...
An enduring challenge in ecology is to understand what drives spatial variation in the size and stru...
In this study we focused on deciduous managed forests in north-western Italy and investigated relati...
Aim To assess the relative roles of environment and space in driving bird species distribution and t...
Aim: To assess the relative roles of environment and space in driving bird species distribution and ...
Identifying spatial patterns in species diversity represents an essential task to be accounted for ...
Identifying spatial patterns in species diversity represents an essential task to be accounted for w...
We have in this study analysed bird communities across Norway with a heterogeneous species abundance...
<div><p>We developed a statistical model to estimate the abundances of potentially interacting speci...
Breeding bird communities were studied in eight habitat types in the Majella massif (central Italy) ...
Context: Variation in biological communities is used to identify biodiversity responses to anthropog...
International audienceWe consider the problem of estimating the number of species (denoted by S) of ...
Accurately characterizing spatial patterns on landscapes is necessary to understand the processes th...
Factors determining species distributions have frequently been shown to vary geographically, yieldin...
Variation partitioning analyses combined with spatial predictors (Moran’s eigenvector maps, MEM) are...
<p>Data used in the application of the multi-region community model (MRCM) to detection non-detectio...
An enduring challenge in ecology is to understand what drives spatial variation in the size and stru...
In this study we focused on deciduous managed forests in north-western Italy and investigated relati...
Aim To assess the relative roles of environment and space in driving bird species distribution and t...
Aim: To assess the relative roles of environment and space in driving bird species distribution and ...
Identifying spatial patterns in species diversity represents an essential task to be accounted for ...
Identifying spatial patterns in species diversity represents an essential task to be accounted for w...
We have in this study analysed bird communities across Norway with a heterogeneous species abundance...
<div><p>We developed a statistical model to estimate the abundances of potentially interacting speci...
Breeding bird communities were studied in eight habitat types in the Majella massif (central Italy) ...
Context: Variation in biological communities is used to identify biodiversity responses to anthropog...
International audienceWe consider the problem of estimating the number of species (denoted by S) of ...
Accurately characterizing spatial patterns on landscapes is necessary to understand the processes th...
Factors determining species distributions have frequently been shown to vary geographically, yieldin...
Variation partitioning analyses combined with spatial predictors (Moran’s eigenvector maps, MEM) are...