Predation risk from lions (Panthera leo) has been linked to habitat characteristics and availability and traits of prey. We separated the effects of

Arboviruses represent a significant burden to public health and local economies due to their ability to cause unpredictable and widespread epidemics. To maximize early detection of arbovirus emergence in non-endemic areas, surveillance efforts should target areas where circulation is most likely. However, identifying such hotspots of potential emergence is a major challenge. The ecological conditions leading to arbovirus outbreaks are shaped by complex interactions between the virus, its vertebrate hosts, arthropod vector, and abiotic environment that are often poorly understood. Here, we systematically review the ecological risk factors associated with the circulation of six arboviruses that are of considerable concern to northwestern Europe. These include three mosquito-borne viruses (Japanese encephalitis virus, West Nile virus, Rift Valley fever virus) and three tick-borne viruses (Crimean-Congo hemorrhagic fever virus, tick-borne encephalitis virus, and louping-ill virus). We consider both intrinsic (e.g. vector and reservoir host competence) and extrinsic (e.g. temperature, precipitation, host densities, land use) risk factors, identify current knowledge gaps, and discuss future directions. Our systematic review provides baseline information for the identification of regions and habitats that have suitable ecological conditions for endemic circulation, and therefore may be used to target early warning surveillance programs aimed at detecting multi-virus and/or arbovirus emergence.

Habitat loss can trigger migration network collapse by isolating migratory bird breeding grounds from nonbreeding grounds. Theoretically, habitat loss can have vastly different impacts depending on the site's importance within the migratory corridor. However, migration‐network connectivity and the impacts of site loss are not completely understood. We used GPS tracking data on 4 bird species in the Asian flyways to construct migration networks and proposed a framework for assessing network connectivity for migratory species. We used a node‐removal process to identify stopover sites with the highest impact on connectivity. In general, migration networks with fewer stopover sites were more vulnerable to habitat loss. Node removal in order from the highest to lowest degree of habitat loss yielded an increase of network resistance similar to random removal. In contrast, resistance increased more rapidly when removing nodes in order from the highest to lowest betweenness value (quantified by the number of shortest paths passing through the specific node). We quantified the risk of migration network collapse and identified crucial sites by first selecting sites with large contributions to network connectivity and then identifying which of those sites were likely to be removed from the network (i.e., sites with habitat loss). Among these crucial sites, 42% were not designated as protected areas. Setting priorities for site protection should account for a site's position in the migration network, rather than only site‐specific characteristics. Our framework for assessing migration‐network connectivity enables site prioritization for conservation of migratory species.

The increasing spatiotemporal accuracy of Global Navigation Satellite Systems (GNSS) tracking systems opens the possibility to infer animal behaviour from tracking data. We studied the relationship between high-frequency GNSS data and behaviour, aimed at developing an easily interpretable classification method to infer behaviour from location data. Behavioural observations were carried out during tracking of cows (Bos Taurus) fitted with high-frequency GPS (Global Positioning System) receivers. Data were obtained in an open field and forested area, and movement metrics were calculated for 1 min, 12 s and 2 s intervals. We observed four behaviour types (Foraging, Lying, Standing and Walking). We subsequently used Classification and Regression Trees to classify the simultaneously obtained GPS data as these behaviour types, based on distances and turning angles between fixes. GPS data with a 1 min interval from the open field was classified correctly for more than 70% of the samples. Data from the 12 s and 2 s interval could not be classified successfully, emphasizing that the interval should be long enough for the behaviour to be defined by its characteristic movement metrics. Data obtained in the forested area were classified with a lower accuracy (57%) than the data from the open field, due to a larger positional error of GPS locations and differences in behavioural performance influenced by the habitat type. This demonstrates the importance of understanding the relationship between behaviour and movement metrics, derived from GNSS fixes at different frequencies and in different habitats, in order to successfully infer behaviour. When spatially accurate location data can be obtained, behaviour can be inferred from high-frequency GNSS fixes by calculating simple movement metrics and using easily interpretable decision trees. This allows for the combined study of animal behaviour and habitat use based on location data, and might make it possible to detect deviations in behaviour at the individual level.

Aim: Although assembly processes have been studied in a wide range of taxa, determining assembly rules remains controversial, particularly in assemblages consisted of species with strong dispersal capacities. Moreover, few studies focused on communities in recently human‐created habitats. We tested two prevailing but opposing hypotheses, environmental filtering and limiting similarity, in waterbird communities across subsidence wetlands created by underground coal mining in China, with an aim to better understand assembly processes in communities composed of highly mobile species in human‐dominated landscape.Location: The North China Plain.Methods: We quantified taxonomic, functional and phylogenetic diversity of the waterbird assemblages in different seasons and compared the mean pairwise distances (MPD) and the mean nearest taxon distances (MNTD) with null models to examine whether co‐occurring species were clustered or overdispersed on the functional dendrogram or phylogenetic tree. Independent contributions of multi‐scale habitat variables therein were determined using a hierarchical partitioning method.Results: We showed asynchronous patterns of seasonal dynamics among the multiple diversity metrics, with highest species diversity during autumn migration. Generally, the co‐occurring species were functionally and phylogenetically clustered. Habitat variables had stronger effects on the functional structure than on the phylogenetic structure of the communities. The degree of functional clustering increased in older and larger wetlands, while the assemblages shifted from functional clustering to overdispersion with increasing habitat diversity, landscape connectivity and human disturbance.Main conclusions: The waterbird assemblages were mainly structured by environmental filtering, and the assembly processes were significantly affected by habitat variables, with stronger effects on functional diversity. Our study highlights the importance of environmental filtering and habitat variables in structuring assemblages dominated by species with high dispersal capacities and suggests that increasing habitat diversity and reducing disturbances will contribute to waterbird conservation in this human‐dominated landscape.