Summary1. Occupancy estimates can inform biodiversity managers about the distribution of elusive species, such as the Pyrenean desman Galemys pyrenaicus, a small semi-aquatic mammal that lives along streams. Occupancy models rely on replication within a sampling site and provide estimates of the probability of detection. However, we still do not know how occupancy and detection estimates obtained from spatial vs. temporal replications differ or the appropriateness of using one or the other when cost and logistics make one approach prohibitive. Recently, the Markovian occupancy model has been developed to analyse adjacent spatial replicates and to test for spatial dependence between them. This model has already been applied to large and highly mobile mammals using trails, but never tested for any species with linear home ranges. 2. We compared detection and occupancy estimates obtained from both temporal and spatial sampling designs that were subsequently organized into four data configurations (sites with both spatial and temporal replicates, adjacent spatial replicates only, temporal replicates only at the segment and site scales). From that, five occupancy models with different assumptions (the standard occupancy model, the standard multiscale model, the multiscale model with Markovian process for detection, the Markovian detection model and the Markovian occupancy model) were used. We also assessed which occupancy model was the most appropriate for each data configuration to determine whether it is necessary to incorporate correlation into models. 3. We found that the estimated detection probabilities were relatively high (≥0Á58) and similar when the same model was applied to each data configuration. 4. Spatial replication weakly underestimated occupancy. But when using this design, the Markovian occupancy model was the most supported and minimized the underestimation of occupancy, highlighting a spatial dependence between adjacent replicates. 5. Synthesis and applications. We show that a survey based on adjacent spatial replicates for a mammal living along linear features of the landscape is a good compromise between cost and occupancy estimates, while using the Markovian occupancy model to estimate detection and occupancy. Our finding may have wider applications for the monitoring of species especially *Correspondence author. E-mail: anais.charbonnel@espaces-naturels.fr Journal of Applied Ecology 2014Ecology , 51, 1425Ecology -1433Ecology doi: 10.1111Ecology /1365Ecology -2664 when temporal replicates are difficult or unrealistic. Spatial design, for surveys based on sign detection, could thus be applied for species with linear home ranges or when surveys are constrained by linear habitats.

Habitat fragmentation is one of the most severe threats to biodiversity as it may lead to changes in population genetic structure, with ultimate modifications of species evolutionary potential and local extinctions. Nonetheless, fragmentation does not equally affect all species and identifying which ecological traits are related to species sensitivity to habitat fragmentation could help prioritization of conservation efforts. Despite the theoretical link between species ecology and extinction proneness, comparative studies explicitly testing the hypothesis that particular ecological traits underlies species-specific population structure are rare. Here, we used a comparative approach on eight bird species, co-occurring across the same fragmented landscape. For each species, we quantified relative levels of forest specialization and genetic differentiation among populations. To test the link between forest specialization and susceptibility to forest fragmentation, we assessed species responses to fragmentation by comparing levels of genetic differentiation between continuous and fragmented forest landscapes. Our results revealed a significant and substantial population structure at a very small spatial scale for mobile organisms such as birds. More importantly, we found that specialist species are more affected by forest fragmentation than generalist ones. Finally, our results suggest that even a simple habitat specialization index can be a satisfying predictor of genetic and demographic consequences of habitat fragmentation, providing a reliable practical and quantitative tool for conservation biology.