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121.
Human activity and associated landscape modifications alter the movements of animals with consequences for populations and ecosystems worldwide. Species performing long-distance movements are thought to be particularly sensitive to human impact. Despite the increasing anthropogenic pressure, it remains challenging to understand and predict animals' responses to human activity. Here we address this knowledge gap using 1206 Global Positioning System movement trajectories of 815 individuals from 14 red deer (Cervus elaphus) and 14 elk (Cervus canadensis) populations spanning wide environmental gradients, namely the latitudinal range from the Alps to Scandinavia in Europe, and the Greater Yellowstone Ecosystem in North America. We measured individual-level movements relative to the environmental context, or movement expression, using the standardized metric Intensity of Use, reflecting both the directionality and extent of movements. We expected movement expression to be affected by resource (Normalized Difference Vegetation Index, NDVI) predictability and topography, but those factors to be superseded by human impact. Red deer and elk movement expression varied along a continuum, from highly segmented trajectories over relatively small areas (high intensity of use), to directed transitions through restricted corridors (low intensity of use). Human activity (Human Footprint Index, HFI) was the strongest driver of movement expression, with a steep increase in Intensity of Use as HFI increased, but only until a threshold was reached. After exceeding this level of impact, the Intensity of Use remained unchanged. These results indicate the overall sensitivity of Cervus movement expression to human activity and suggest a limitation of plastic responses under high human pressure, despite the species also occurring in human-dominated landscapes. Our work represents the first comparison of metric-based movement expression across widely distributed populations of a deer genus, contributing to the understanding and prediction of animals' responses to human activity.  相似文献   
122.
Every autumn, large numbers of raptors migrate through geographical convergence zones to avoid crossing large bodies of water. At coastal convergence zones, raptors may aggregate along coastlines because of convective or wind conditions. However, the effect of wind and thermal convection on migrating raptors may vary depending on local landscapes and weather, and on the flight strategies of different raptors. From 20 August to 14 October 2008 and 2009, we studied the effect of cloud development and crosswinds on the flight paths of raptors migrating through the eastern Black Sea convergence zone, where coastal lowlands at the foothills of the Pontic Mountains form a geographical bottleneck 5‐km‐wide near Batumi, the capital of the Independent Republic of Ajaria in southwestern Georgia. To identify key correlates of local aggregation, we examined diurnal variation in migration intensity and coastal aggregation of 11 species of raptors categorized based on size and flight strategies. As reported at other convergence zones, migration intensity of large obligate‐soaring species peaked during the core period of thermal activity at mid‐day. When clouds developed over interior mountains and limited thermal convection, these large obligate‐soaring species aggregated near the coast. However, medium‐sized soaring migrants that occasionally use flapping flight did not aggregate at the coast when clouds over the mountains weakened thermal convection. Numbers of alternate soaring‐flapping harriers (Circus spp.) peaked during early morning, with these raptors depending more on flapping flight during a time of day with poor thermal convection. Small sparrowhawks (Accipiter spp.) aggregated at the coast during periods when winds blew offshore, suggesting aggregation caused by wind drift. Thus, weather conditions, including cloud cover and wind speed and direction, can influence the daily rhythm and flight paths of migrating raptors and, therefore, should be accounted for before inferring population trends from migration counts.  相似文献   
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