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Rivers support some of Earth’s richest biodiversity1and provide essential ecosystem services to society2, but they are often fragmented by barriers to free flow3. In Europe, attempts to quantify river connectivity have been hampered by the absence of a harmonized barrier database. Here we show that there are at least 1.2 million instream barriers in 36 European countries (with a mean density of 0.74 barriers per kilometre), 68 per cent of which are structures less than two metres in height that are often overlooked. Standardized walkover surveys along 2,715 kilometres of stream length for 147 rivers indicate that existing records underestimate barrier numbers by about 61 per cent. The highest barrier densities occur in the heavily modified rivers of central Europe and the lowest barrier densities occur in the most remote, sparsely populated alpine areas. Across Europe, the main predictors of barrier density are agricultural pressure, density of river-road crossings, extent of surface water and elevation. Relatively unfragmented rivers are still found in the Balkans, the Baltic states and parts of Scandinavia and southern Europe, but these require urgent protection from proposed dam developments. Our findings could inform the implementation of the EU Biodiversity Strategy, which aims to reconnect 25,000 kilometres of Europe’s rivers by 2030, but achieving this will require a paradigm shift in river restoration that recognizes the widespread impacts caused by small barriers.

Previous studies of the effects of fur trapping on marten populations have not considered habitat variation and how trappers use available habitat. We investigated the behavior of fur trappers with respect to roads, waterways, and the forest habitats on trap lines, using registered trap lines in northern Ontario as a study system. The objectives of this study were to 1) develop models for predicting trap location based on access and habitat features, 2) determine whether trappers target the same habitat preferred by American marten, and 3) investigate effects of spatial resolution on predictive models, using a geographic information system (GIS) for coarse resolution variables and direct forest mensuration for fine resolution variables. Distance to roads and water were by far the most influential factors in logistic models for predicting trap presence, accounting for 51.2–61.7% of the observed deviance. At a coarse spatial resolution, trappers selected sites that were close to vehicular access, and in older mixed wood forest stands. Similarly, at a coarse resolution, marten selected old stands, but dominated by coniferous trees. At a finer spatial resolution, trappers selected sites with high basal area of trees, pronounced proportion of black spruce, high canopy cover, and high density of coarse woody debris, consistent with previous studies on marten habitat selection at a fine resolution. Although coarse resolution models are easily applicable because of the wide availability of GIS land cover data, fine resolution models had greater predictive power when considering habitat variables. By quantifying trapper behaviors, these results suggest that the effectiveness of marten sanctuaries used in forest management depend not only on the age and species composition of forest stands left unlogged, but also on the degree to which they are accessible to trappers. © 2012 The Wildlife Society.

Statisticians frequently voice concern that their interactions with applied researchers start only after data have been collected. The same can be said for our experience with home-range studies. Too often, conversations about home range begin with questions concerning estimation methods, smoothing parameters, or the nature of autocorrelation. More productive efforts start by asking good (and interesting) research questions; once these questions are defined, it becomes possible to ask how various design and analysis strategies influence one's ability to answer these questions. With this process in mind, we address key sample-design and data-analysis issues related to the topic of home range. The impact of choosing a particular home-range estimator (e.g., minimum convex polygon, kernel density estimator, or local convex hull) will be question dependent, and for some problems other movement or use-based metrics (e.g., mean step lengths or time spent in particular areas) may be worthy of consideration. Thus, we argue the need for more question-driven and focused research and for clearly distinguishing the biological concept of an animal's home range from the statistical quantities one uses to investigate this concept. For comparative studies, it is important to standardize sampling regimes and estimation methods as much as possible, and to pay close attention to missing data issues. More attention should also be given to temporally changing space-use patterns, with biologically meaningful time periods (e.g., life-history stages) used to define sampling periods. Last, we argue the need for closer connections between theoretical and empirical researchers. Advances in ecological theory, and its application to natural resources management, will require carefully designed research studies to test theoretical predictions from more mechanistic modeling approaches.