Transport infrastructure shapes foraging habitat in a raptor community

Transport infrastructure elements are widespread and increasing in size and length in many countries, with the subsequent alteration of landscapes and wildlife communities. Nonetheless, their effects on habitat selection by raptors are still poorly understood. In this paper, we analyzed raptors ' foraging habitat selection in response to conventional roads and high capacity motorways at the landscape scale, and compared their effects with those of other variables, such as habitat structure, food availability, and presence of potential interspecific competitors. We also analyzed whether the raptors' response towards infrastructure depends on the spatial scale of observation, comparing the attraction or avoidance behavior of the species at the landscape scale with the response of individuals observed in the proximity of the infrastructure. Based on ecological hypotheses for foraging habitat selection, we built generalized linear mixed models, selected the best models according to Akaike Information Criterion and assessed variable importance by Akaike weights. At the community level, the traffic volume was the most relevant variable in the landscape for foraging habitat selection. Abundance, richness, and diversity values reached their maximum at medium traffic volumes and decreased at highest traffic volumes. Individual species showed different degrees of tolerance toward traffic, from higher abundance in areas with high traffic values to avoidance of it. Medium-sized opportunistic raptors increased their abundance near the traffic infrastructures, large scavenger raptors avoided areas with higher traffic values, and other species showed no direct response to traffic but to the presence of prey. Finally, our cross-scale analysis revealed that the effect of transport infrastructures on the behavior of some species might be detectable only at a broad scale. Also, food availability may attract raptor species to risky areas such as motorwaysAP was supported by a PhD grant of the Basque Government. This study forms part of the CENIT-OASIS Project funded by a consortium of companies supported by the Centro para el Desarrollo Tecnológico e Industrial of the Spanish Ministry of Science and Innovation (CENIT-2008 1016). The Comunidad de Madrid, together with the European Social Fund, supports the TEG research group through the REMEDINAL Research Network (S-2009/AMB/1783). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscri

Efficiency of spatio-temporal vaccination regimes in wildlife populations under different viral constraints

Classical Swine Fever (CSF) is considered an endemic disease in European wild boar populations. In view of the high economic impact of the introduction of the virus into domestic pig units, huge efforts are invested in the preventive control of CSF in wild boar populations. Recent European Community guidelines favour oral mass vaccination against CSF in wild boar populations. The guidelines are explicit on the temporal structure of the vaccination protocol, but little is known about the efficacy of different spatial application schemes, or how they relate to outbreak dynamics

What you see is where you go? Modeling dispersal in mountainous landscapes

Inter-patch connectivity can be strongly influenced by topography and matrix heterogeneity, particularly when dealing with species with high cognitive abilities. To estimate dispersal in such systems, simulation models need to incorporate a behavioral component of matrix effects to result in more realistic connectivity measures. Inter-patch dispersal is important for the persistence of capercaillie (Tetrao urogallus) in central Europe, where this endangered grouse species lives in patchy populations embedded in a mountainous landscape. We simulated capercaillie movements with an individual-based, spatially explicit dispersal model (IBM) and compared the resulting connectivity measure with distance and an expert estimation. We used a landscape comprising discrete habitat patches, temporary habitat, non-habitat forests, and non-habitat open land. First, we assumed that dispersing individuals have perfect knowledge of habitat cells within the perceptual range (null model). Then, we included constraints to perception and accessibility, i.e., mountain chains, open area and valleys (three sub-models). In a full model, all sub-models were included at once. Correlations between the different connectivity measures were high (Spearman's ρ>0.7) and connectivity based on the full IBM was closer to expert estimation than distance. For selected cases, simple distance differed strongly from the full IBM measure and the expert estimation. Connectivity based on the IBM was strongly sensitive to the size of perceptual range with higher sensitivity for the null model compared to the full model that included context dependent perceptual ranges. Our heuristic approach is adequate for simulating movements of species with high cognitive abilities in strongly structured landscapes that influence perception and permeabilit

Environmental factors associated with the prevalence of ESBL/AmpC-producing Escherichia coli in wild boar (Sus scrofa)

Antimicrobial resistances (AMR) in bacteria, such as ESBL/AmpC-producing E. coli, are a burden to human and animal health. This burden is mainly driven by the consumption and release of antimicrobial substances into the environment. The pollution and contamination of habitats by AMR in bacteria and antimicrobial substances can lead to the transmission of bacterial AMR to wildlife. Therefore, it is necessary to understand the transmission cycle of antibiotics and resistant bacteria between humans, and animals as well as their occurrences in the environment. Environmental factors associated with the occurrence of bacterial AMR in wildlife can lead to a better understanding of the distribution of bacterial AMR in humans and animals using One Health approaches. Here, we analyzed data gathered in the framework of the German zoonoses monitoring program in 2016 and 2020 using spatiotemporal statistics to identify relevant environmental factors (e.g., livestock density, climatic variables, and human density) in association with the spatial distribution of ESBL/AmpC-producing E. coli. For this purpose, we developed a generic data integration and analysis pipeline to link spatially explicit environmental factors to the monitoring data. Finally, we built a binomial generalized linear mixed model (GLMM) to determine the factors associated with the spatial distribution of ESBL/AmpC-producing E. coli. In 2016 and 2020, 807 fecal samples from hunted wild boar (Sus scrofa L.) were randomly taken in 13 federal states and selectively analyzed for ESBL/AmpC-producing E. coli. Forty-eight isolates were identified in 12 German federal states, with an overall prevalence of 6%. We observed an almost three times higher probability of ESBL/AmpC-producing E. coli isolates in wild boar in counties with high cattle densities (OR = 2.57, p ≤ 0.01). Furthermore, we identified a seasonal effect in areas with high precipitation during the off-hunting seasons (OR = 2.78, p = 0.025) and low precipitation throughout the years (OR = 0.42, p = 0.025). However, due to the low amount of identified isolates, confidence intervals were wide, indicating a high level of uncertainty. This suggests that further studies on smaller scales need to be conducted with multiannual data and improved metadata, e.g., on the location, the hunting procedure, and species characteristics to be collected during field sampling

Landscape Structures Affect Risk of Canine Distemper in Urban Wildlife

Urbanization rapidly changes landscape structure worldwide, thereby enlarging the human-wildlife interface. The emerging urban structures should have a key influence on the spread and distribution of wildlife diseases such as canine distemper, by shaping density, distribution and movements of wildlife. However, little is known about the role of urban structures as proxies for disease prevalence. To guide management, especially in densely populated cities, assessing the role of landscape structures in hampering or promoting disease prevalence is thus of paramount importance. Between 2008 and 2013, two epidemic waves of canine distemper hit the urban red fox (Vulpes vulpes) population of Berlin, Germany. The directly transmitted canine distemper virus (CDV) causes a virulent disease infecting a range of mammals with high host mortality, particularly in juveniles. We extracted information about CDV serological state (seropositive or seronegative), sex and age for 778 urban fox carcasses collected by the state laboratory Berlin Brandenburg. To assess the impact of urban landscape structure heterogeneity (e.g., richness) and shares of green and gray infrastructures at different spatial resolutions (areal of 28 ha, 78 ha, 314 ha) on seroprevalence we used Generalized Linear Mixed-Effects Models with binomial distributions. Our results indicated that predictors derived at a 28 ha resolution were most informative for describing landscape structure effects (AUC = 0.92). The probability to be seropositive decreased by 66% (0.6 to 0.2) with an increasing share of gray infrastructure (40 to 80%), suggesting that urbanization might hamper CDV spread in urban areas, owing to a decrease in host density (e.g., less foxes or raccoons) or an absence of wildlife movement corridors in strongly urbanized areas. However, less strongly transformed patches such as close-to-nature areas in direct proximity to water bodies were identified as high risk areas for CDV transmission. Therefore, surveillance and disease control actions targeting urban wildlife or human-wildlife interactions should focus on such areas. The possible underlying mechanisms explaining the prevalence distribution may be increased isolation, the absence of alternative hosts or an abiotic environment, all impairing the ability of CDV to persist without a host

Sampling variables and their thresholds for the precise estimation of wild felid population density with camera traps and spatial capture–recapture methods

1. Robust monitoring, providing information on population status, is fundamental for successful conservation planning. However, this can be hard to achieve for species that are elusive and occur at low densities, such as felids. These are often keystones of functioning ecosystems and are threatened by habitat loss and human persecution. 2. When elusive species can be individually identified by visible characteristics, for example via camera-trapping, observations of individuals can be used in combination with capture–recapture methods to calculate demographic parameters such as population density. In this context, spatial capture–recapture (SCR) outperforms conventional non-spatial methods, but the precision of results is inherently related to the sampling design, which should therefore be optimised. 3. We focussed on territorial felids in different habitats and investigated how the sampling designs implemented in the field affected the precision of population density estimates. We examined 137 studies that combined camera trapping and SCR methods for density estimation. From these, we collectedspatiotemporal parameters of their sampling designs, monitoring results, such as the number of individuals captured and the number of recaptures, as well as SCR detection parameters. We applied generalised linear mixed-effects models and tree-based regression methods to investigate the influence of variables on the precision of population density estimates and provide numerical thresholds. 4. Our analysis shows that the number of individuals, recapture frequency, and capture probability play the most crucial roles. Surveys yielding over 20 captured individuals that were recaptured on average at least once obtain the most precise population density estimates. 5. Based on our findings, we provide practical guidelines for future SCR studies that apply to all territorial felids. Furthermore, we present a standardised reporting protocol for study transparency and comparability. Our results will improve reporting and reproducibility of SCR studies and aid in setting up optimised sampling designs.publishedVersio

Wind energy production in forests conflicts with tree-roosting bats

Many countries are investing heavily in wind power generation,1 triggering a high demand for suitable land. As a result, wind energy facilities are increasingly being installed in forests,2,3 despite the fact that forests are crucial for the protection of terrestrial biodiversity.4 This green-green dilemma is particularly evident for bats, as most species at risk of colliding with wind turbines roost in trees.2 With some of these species reported to be declining,5,6,7,8 we see an urgent need to understand how bats respond to wind turbines in forested areas, especially in Europe where all bat species are legally protected. We used miniaturized global positioning system (GPS) units to study how European common noctule bats (Nyctalus noctula), a species that is highly vulnerable at turbines,9 respond to wind turbines in forests. Data from 60 tagged common noctules yielded a total of 8,129 positions, of which 2.3% were recorded at distances <100 m from the nearest turbine. Bats were particularly active at turbines <500 m near roosts, which may require such turbines to be shut down more frequently at times of high bat activity to reduce collision risk. Beyond roosts, bats avoided turbines over several kilometers, supporting earlier findings on habitat loss for forest-associated bats.10 This habitat loss should be compensated by developing parts of the forest as refugia for bats. Our study highlights that it can be particularly challenging to generate wind energy in forested areas in an ecologically sustainable manner with minimal impact on forests and the wildlife that inhabit them

Habitat selection models for European wildcat conservation

Populations of the European wildcat (Felis silvestris) are only slowly recovering in Central Europe after a severe decline in the last centuries and require specific conservation plans in many areas. However, detailed information on wildcat occurrence and habitat require- ments is still scarce and controversial. We present a fine-scale habitat selection model for wildcats based on detailed species and land use information and evaluate its accu- racy to predict habitat distribution in new areas. We analysed habitat use within home ranges using single locations of 12 radio-tracked individuals from south western Germany. Several competing models were fitted and compared using generalised linear mixed models (GLMM) and information-theoretic approaches. Radio-tracking data of 9 and 10 wildcats from two distant areas were used to evaluate the models. The selected model predicted habitat associated to close distance to forest, watercourses and mead- ows and a critical distance to villages, single houses and roads. To predict area suitable for home ranges we superimposed rules derived from home range attributes at a higher level of selection. Predictions from the combination of the fine-scale habitat model and home range rules matched well with more than 2000 wildcat observations of south- western Germany. We discuss the application of the model in wildcat conservation for finding potential reintroduction sites, identifying small isolated populations and aiding in the evaluation of the needs of mitigation and compensation within the scope of the European Habitats Directive.Peer Reviewe

Wind farm facilities in Germany kill noctule bats from near and far

Over recent years, it became widely accepted that alternative, renewable energy may come at some risk for wildlife, for example, when wind turbines cause large numbers of bat fatalities. To better assess likely populations effects of wind turbine related wildlife fatalities, we studied the geographical origin of the most common bat species found dead below German wind turbines, the noctule bat (Nyctalus noctula). We measured stable isotope ratios of non-exchangeable hydrogen in fur keratin to separate migrants from local individuals, used a linear mixed-effects model to identify temporal, spatial and biological factors explaining the variance in measured stable isotope ratios and determined the geographical breeding provenance of killed migrants using isoscape origin models. We found that 72% of noctule bat casualties (n = 136) were of local origin, while 28% were long-distance migrants. These findings highlight that bat fatalities at German wind turbines may affect both local and distant populations. Our results indicated a sex and age-specific vulnerability of bats towards lethal accidents at turbines, i.e. a relatively high proportion of killed females were recorded among migratory individuals, whereas more juveniles than adults were recorded among killed bats of local origin. Migratory noctule bats were found to originate from distant populations in the Northeastern parts of Europe. The large catchment areas of German wind turbines and high vulnerability of female and juvenile noctule bats call for immediate action to reduce the negative cross-boundary effects of bat fatalities at wind turbines on local and distant populations. Further, our study highlights the importance of implementing effective mitigation measures and developing species and scale-specific conservation approaches on both national and international levels to protect source populations of bats. The efficacy of local compensatory measures appears doubtful, at least for migrant noctule bats, considering the large geographical catchment areas of German wind turbines for this species