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© 2014 John Wiley & Sons Ltd. The use of next-generation sequencing technologies is revolutionizing microbial ecology by allowing a deep phylogenetic coverage of tens to thousands of samples simultaneously. Double Principal Coordinates Analysis (DPCoA) is a multivariate method, developed in community ecology, able to integrate a distance matrix describing differences among species (e.g. phylogenetic distances) in the analysis of a species abundance matrix. This ordination technique has been used recently to describe microbial communities taking into account phylogenetic relatedness. In this work, we extend DPCoA to integrate the information of external variables measured on communities. The constrained Double Principal Coordinates Analysis (cDPCoA) is able to enforce a priori classifications to retrieve subtle differences and (or) remove the effect of confounding factors. We describe the main principles of this new approach and demonstrate its usefulness by providing application examples based on published 16S rRNA gene data sets.

1. Movement is fundamental to individual and population dynamics, as it allows individuals to meet their basic requirements. Although movement patterns reflect interactions between internal and external factors, only few studies have examined the effects of these factors on movement simultaneously, and they generally focused on particular biological contexts (e.g. dispersal, foraging). 2. However, the relative importance of these factors in driving individual routine movements might reflect a species’ potential flexibility to cope with landscape changes and therefore buf- fer their potential impact on fitness. 3. We used data from GPS collars on Scandinavian brown bears to investigate the relative role of these factors, as well as an additional factor (period of the year) on routine move- ments at two spatial scales (hourly and daily relocations). 4. As expected, internal factors played a major role in driving movement, compared to exter- nal factors at both scales, but its relative importance was greater at a finer scale. In particu- lar, the interaction between reproductive status and period of the year was one of the most influential variables, females being constrained by the movement capacity of their cubs in the first periods of the year. The effect of human disturbance on movement was also greater for females with cubs than for lone females. 5. This study showed how reciprocal modulation of internal and external factors is shaping space use of brown bears. We stress that these factors should be studied simultaneously to avoid the risk of obtaining context-dependent inferences. Moreover, the study of their relative contribution is also highly relevant in the context of multiple-use landscapes, as human activi- ties generally affect the landscape more than they affect the internal states of an individual. Species or individuals with important internal constraints should be less responsive to changes in their environment as they have less freedom from internal c

Aim: Although the negative effects of habitat fragmentation have been widely documented at the landscape scale, much less is known about its impacts on species distributions at the biogeographical scale. We hypothesize that fragmentation influences the large-scale distribution of area- and edge-sensitive species by limiting their occurrence in regions with fragmented habitats, despite otherwise favourable environmental conditions. We test this hypothesis by assessing the interplay of climate and landscape factors influencing the distribution of the calandra lark, a grassland specialist that is highly sensitive to habitat fragmentation. Location: Iberia Peninsula, Europe. Methods: Ecological niche modelling was used to investigate the relative influence of climate/topography, landscape fragmentation and spatial structure on calandra lark distribution. Modelling assumed explicitly a hierarchically structured effect among explanatory variables, with climate/topography operating at broader spatial scales than landscape variables. An eigenvector-based spatial filtering approach was used to cancel bias introduced by spatial autocorrelation. The information theoretic approach was used in model selection, and variation partitioning was used to isolate the unique and shared effects of sets of explanatory variables. Results: Climate and topography were the most influential variables shaping the distribution of calandra lark, but incorporating landscape metrics contributed significantly to model improvement. The probability of calandra lark occurrence increased with total habitat area and declined with the number of patches and edge density. Variation partitioning showed a strong overlap between variation explained by climate/topography and landscape variables. After accounting for spatial structure in species distribution, the explanatory power of environmental variables remained largely unchanged. Main conclusions: We have shown here that landscape fragmentation can influenc