Species' assessments must frequently be derived from opportunistic observations made by volunteers (i.e., citizen scientists). Interpretation of the resulting data to estimate population trends is plagued with problems, including teasing apart genuine population trends from variations in observation effort. We devised a way to correct for annual variation in effort when estimating trends in occupancy (species distribution) from faunal or floral databases of opportunistic observations. First, for all surveyed sites, detection histories (i.e., strings of detection-nondetection records) are generated. Within-season replicate surveys provide information on the detectability of an occupied site. Detectability directly represents observation effort; hence, estimating detectability means correcting for observation effort. Second, site-occupancy models are applied directly to the detection-history data set (i.e., without aggregation by site and year) to estimate detectability and species distribution (occupancy, i.e., the true proportion of sites where a species occurs). Site-occupancy models also provide unbiased estimators of components of distributional change (i.e., colonization and extinction rates). We illustrate our method with data from a large citizen-science project in Switzerland in which field ornithologists record opportunistic observations. We analyzed data collected on four species: the widespread Kingfisher (Alcedo atthis) and Sparrowhawk (Accipiter nisus) and the scarce Rock Thrush (Monticola saxatilis) and Wallcreeper (Tichodroma muraria). Our method requires that all observed species are recorded. Detectability was <1 and varied over the years. Simulations suggested some robustness, but we advocate recording complete species lists (checklists), rather than recording individual records of single species. The representation of observation effort with its effect on detectability provides a solution to the problem of differences in effort encountered when extracting trend information from haphazard observations. We expect our method is widely applicable for global biodiversity monitoring and modeling of species distributions.

Conceived to combat widescale biodiversity erosion in farmland, agri-environment schemes have largely failed to deliver their promises despite massive financial support. While several common species have shown to react positively to existing measures, rare species have continued to decline in most European countries. Of particular concern is the status of insectivorous farmland birds that forage on the ground. We modelled the foraging habitat preferences of four declining insectivorous bird species (hoopoe, wryneck, woodlark, common redstart) inhabiting fruit tree plantations, orchards and vineyards. All species preferred foraging in habitat mosaics consisting of patches of grass and bare ground, with an optimal, species-specific bare ground coverage of 30–70% at the foraging patch scale. In the study areas, birds thrived in intensively cultivated farmland where such ground vegetation mosaics existed. Not promoted by conventional agri-environment schemes until now, patches of bare ground should be implemented throughout grassland in order to prevent further decline of insectivorous farmland birds.

Ongoing monitoring in the Swiss Alps has shown that Rock Ptarmigan (Lagopus muta helvetica) has suffered a significant population decrease over the last decade and climate change has been proposed as a potential cause. In this study, we investigate the response of this high alpine grouse species to rapid climate change. We address a problem often neglected in macro-ecological studies on species distribution: scale-dependency of distribution models. The models are based on empirical field data and on environmental databases for large-scale models. The implementation of several statistical modelling approaches, external validation strategies and the implementation of a recent study on regional climate change in Switzerland ensure robust predictions of future range shifts. Our results demonstrate that, on the territory level, variables depicting vegetation, heterogeneity of local topography and habitat structure have greatest explanatory power. In contrast at the meso-scale and macro-scale (with grain sizes of 1 and 100 km 2 , respectively), bioclimatic and land cover-related variables play a prominent role. The models predict that, based on increasing temperatures during the breeding season, potential habitat will decrease by up to two-thirds until the year 2070. At the same time, a shift of potential habitat towards the mountain tops is predicted. The multiscale approach highlights the true extent of potential habitat for this species with its patchy distribution in steep terrain. The small-scale analysis pinpoints the key habitat areas within the extensive areas of suitable habitat predicted by models on large grain sizes and in this way reveals sub-grid variability. Our results can facilitate the adaptation of species conservation strategies to a quickly changing environment. ZusammenfassungHabitat auf den Gipfeln der Berge: Wie lange kann das Alpenschneehuhn (Lagopus muta helvetica) raschen Klimawandel in den Schweizer Alpen ü berleben? Ein mehrskaliger Ansatz.Fortlaufendes Monitoring hat gezeigt, dass innerhalb des letzten Jahrzehnts die Population des Alpenschneehuhns (Lagopus muta helvetica) in den Schweizer Alpen stark abgenommen hat. Als mögliche Ursache kommt der Klimawandel in Betracht. In dieser Studie untersuchen wir die Auswirkungen raschen Klimawandels auf dieses hochalpine Raufußhuhn. Dabei setzten wir uns mit einem Aspekt auseinander, der in vielen makroökologischen Studien oft vernachlässigt wird: die Skalenabhängigkeit von Habitatmodellen. Die Modelle basieren auf empirischen Felddaten und auf Umweltdatenbanken für die Communicated by T. Gottschalk.

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