Resource selection and abundance estimation of moose: Implications for caribou recovery in a human altered landscape

Woodland caribou (Rangifer tarandus caribou) are threatened across Canada due to human disturbance altering predator-prey dynamics. The niche specialization of caribou enables them to survive in nutrient-poor habitats spatially separated from other ungulates and their shared predators. The conversion of old-growth forests to young seral stands is hypothesized to increase the abundance of moose (Alces alces), the dominant prey for wolves (Canis lupus), resulting in apparent competition. We first examined habitat selection of moose in 2 regions with differing intensities of human disturbance in west-central Alberta and east-central British Columbia to assess how human disturbance affects the spatial separation of moose and caribou. We built resource selection functions with data from global positioning system (GPS) collars deployed on 17 moose (8 in a region with high and 9 in a region with low human disturbance) at 2 spatial scales. Our results indicated that moose in our study area make forage-risk tradeoffs in a hierarchical fashion similar to caribou, potentially eroding spatial separation in human disturbed landscapes. We also evaluated the spatial partitioning of resources by comparing resource use with GPS locations from 17 moose and 17 paired caribou using logistic regression. As expected, human disturbance decreased the resource partitioning between moose and caribou. Thus, systematic moose management and monitoring will be essential for caribou conservation. Currently, a Stratified Random Block (SRB) survey design is widely used to estimate moose populations, but these surveys are expensive and often result in imprecise population estimates when not corrected for sightability bias. We evaluated the application of distance sampling as an alternative to SRB surveys, especially for use in caribou ranges. To correct for moose missed on the transect line, where a detection rate of 100% is critical, we developed a sightability model using 21 radio-collared moose. After correcting for sightability, distance sampling was more precise and efficient than SRB surveys. In this way, more efficient distance sampling methodology can be an important tool for caribou conservation. Combined, our results showed the importance of moose management in caribou ranges due to decreased spatial separation between both ungulate species in disturbed landscapes

Linking Landscape-Scale Differences in Forage to Ungulate Nutritional Ecology

Understanding how habitat and nutritional condition affect ungulate populations is necessary for informing management, particularly in areas experiencing carnivore recovery and declining ungulate population trends.  Variations in forage species availability, plant phenological stage, and the abundance of forage make it challenging to understand landscape-level effects of nutrition on ungulates.  We developed an integrated spatial modeling approach to estimate landscape-level elk (Cervus elaphus) forage quality in two adjacent study areas that differed in coarse measures of habitat quality and related the consequences of differences in forage quality to elk body condition and pregnancy rates.  We found no support for differences in dry matter digestibility between plant samples or in phenological stage based on ground sampling plots in the two study areas.  Forage quality, measured as digestible forage biomass, varied among land cover types and between study areas. We found that altered plant composition following fires was the biggest driver of forage quality differences, suggesting that maintaining a mosaic of fire history and distribution will likely benefit ungulate populations.  Study area, lactation status and year affected fall body fat of adult female elk.  Elk in the study area exposed to lower quality summer range forage had lower nutritional condition entering winter.  These differences in nutritional condition resulted in differences in pregnancy rate, with average pregnancy rates of 89% for elk exposed to higher quality forage and 72% for elk exposed to lower quality forage.  Summer range forage quality has the potential to limit elk pregnancy rate and calf production, and these nutritional limitations may predispose elk to be more sensitive to the effects of harvest or predation.  Wildlife managers should identify ungulate populations that are nutritionally limited and recognize that these populations may be more impacted by recovering carnivores or harvest than populations inhabiting more productive summer habitats

Roe deer summer habitat selection at multiple spatio-temporal scales in an alpine environment

Habitat selection is a hierarchical process that may involve different patterns depending on the spatial and temporal scales of investigation. We studied habitat selection by European roe deer (Capreolus capreolus) in a very diverse environment in the Italian eastern Alps, during summer. We sampled both coarse-grained habitat variables (topographic variables, habitat types and cover) and fine-grained habitat variables (forage components of habitat) in used and available locations along the movement trajectories of 14 adult roe deer equipped with GPS telemetry collars. We used conventional logistic regression to assess roe deer habitat selection at the seasonal home range scale, and conditional logistic regression to take into account the temporal aspect of habitat selection on a weekly basis. Our results indicate that topographic variables were not significant predictors for summer roe deer habitat selection. Roe deer strongly selected dense canopy cover, probably to avoid heat stress during warm summer days. In accordance with previous observations, roe deer preferred young forest stands dominated by pioneer species such as ash (Fraxinus spp.) and hazel (Corylus avellana) over climax environments. Roe deer positively selected shrubs (in particular Fraxinus spp., Erica herbacea, Rhododendron spp. and Vaccinium spp.) throughout the study period, whereas selection for grasses and sedges emerged only at the weekly scale. Habitat selection was clearly related to vegetation phenology, since roe deer selected plants in the most nutritive phenological stages, i.e., shrubs with buds, new leaves and fruits, and newly emergent grasses and sedges. Finally, we found stronger and more significant regression coefficients for forage components of habitat and habitat types at the weekly scale, indicating that matching spatial and temporal scales may improve our understanding of ecological patterns driving habitat selection. Conversely, selection patterns for canopy cover did not change across scales, indicating that this variable likely drives habitat selection in a similar way throughout the entire season

Roe deer summer habitat selection at multiple spatio-temporal scales in an Alpine environment

Habitat selection is a hierarchical process that may involve different patterns depending on the spatial and temporal scales of investigation. We studied habitat selection by European roe deer (Capreolus capreolus) in a very diverse environment in the Italian eastern Alps, during summer. We sampled both coarse-grained habitat variables (topographic variables, habitat types and cover) and fine-grained habitat variables (forage components of habitat) in used and available locations along the movement trajectories of 14 adult roe deer equipped with GPS telemetry collars. We used conventional logistic regression to assess roe deer habitat selection at the seasonal home range scale, and conditional logistic regression to take into account the temporal aspect of habitat selection on a weekly basis. Our results indicate that topographic variables were not significant predictors for summer roe deer habitat selection. Roe deer strongly selected dense canopy cover, probably to avoid heat stress during warm summer days. In accordance with previous observations, roe deer preferred young forest stands dominated by pioneer species such as ash (Fraxinus spp.) and hazel (Corylus avellana) over climax environments. Roe deer positively selected shrubs (in particular Fraxinus spp., Erica herbacea, Rhododendron spp. and Vaccinium spp.) throughout the study period, whereas selection for grasses and sedges emerged only at the weekly scale. Habitat selection was clearly related to vegetation phenology, since roe deer selected plants in the most nutritive phenological stages, i.e., shrubs with buds, new leaves and fruits, and newly emergent grasses and sedges. Finally, we found stronger and more significant regression coefficients for forage components of habitat and habitat types at the weekly scale, indicating that matching spatial and temporal scales may improve our understanding of ecological patterns driving habitat selection. Conversely, selection patterns for canopy cover did not change across scales, indicating that this variable likely drives habitat selection in a similar way throughout the entire season

Automated wildlife image classification: An active learning tool for ecological applications

Wildlife camera trap images are being used extensively to investigate animal abundance, habitat associations, and behavior, which is complicated by the fact that experts must first classify the images manually. Artificial intelligence systems can take over this task but usually need a large number of already-labeled training images to achieve sufficient performance. This requirement necessitates human expert labor and poses a particular challenge for projects with few cameras or short durations. We propose a label-efficient learning strategy that enables researchers with small or medium-sized image databases to leverage the potential of modern machine learning, thus freeing crucial resources for subsequent analyses. Our methodological proposal is two-fold: (1) We improve current strategies of combining object detection and image classification by tuning the hyperparameters of both models. (2) We provide an active learning (AL) system that allows training deep learning models very efficiently in terms of required human-labeled training images. We supply a software package that enables researchers to use these methods directly and thereby ensure the broad applicability of the proposed framework in ecological practice. We show that our tuning strategy improves predictive performance. We demonstrate how the AL pipeline reduces the amount of pre-labeled data needed to achieve a specific predictive performance and that it is especially valuable for improving out-of-sample predictive performance. We conclude that the combination of tuning and AL increases predictive performance substantially. Furthermore, we argue that our work can broadly impact the community through the ready-to-use software package provided. Finally, the publication of our models tailored to European wildlife data enriches existing model bases mostly trained on data from Africa and North America

The declining occurrence of moose (Alces alces) at the southernmost edge of its range raise conservation concerns

The border region between Austria, the Czech Republic, and Germany harbors the most south-western occurrence of moose in continental Europe. The population originated in Poland, where moose survived, immigrated from former Soviet Union or were reintroduced after the Second World War expanded west and southwards. In recent years, the distribution of the nonetheless small Central European population seems to have declined, necessitating an evaluation of its current status. In this study, existing datasets of moose observations from 1958 to 2019 collected in the three countries were combined to create a database totaling 771 records (observations and deaths). The database was then used to analyze the following: (a) changes in moose distribution, (b) the most important mortality factors, and (c) the availability of suitable habitat as determined using a maximum entropy approach. The results showed a progressive increase in the number of moose observations after 1958, with peaks in the 1990s and around 2010, followed by a relatively steep drop after 2013. Mortality within the moose population was mostly due to human interactions, including 13 deadly wildlife-vehicle collisions, particularly on minor roads, and four animals that were either legally culled or poached. Our habitat model suggested that higher altitudes (ca. 700–1,000 m a.s.l.), especially those offering wetlands, broad- leaved forests and natural grasslands, are the preferred habitats of moose whereas steep slopes and areas of human activity are avoided. The habitat model also revealed the availability of large core areas of suitable habitat beyond the current distribution, suggesting that habitat was not the limiting factor explaining the moose distribution in the study area. Our findings call for immediate transboundary conservation measures to sustain the moose population, such as those aimed at preventing wildlife-vehicle collisions and illegal killings. Infrastructure planning and development activities must take into account the habitat requirements of moose.publishedVersio

Deer Behavior Affects Density Estimates With Camera Traps, but Is Outwighted by Spatial Variability

Density is a key trait of populations and an essential parameter in ecological research, wildlife conservation and management. Several models have been developed to estimate population density based on camera trapping data, including the random encounter model (REM) and camera trap distance sampling (CTDS). Both models need to account for variation in animal behavior that depends, for example, on the species and sex of the animals along with temporally varying environmental factors. We examined whether the density estimates of REM and CTDS can be improved for Europe’s most numerous deer species, by adjusting the behavior-related model parameters per species and accounting for differences in movement speeds between sexes, seasons, and years. Our results showed that bias through inadequate consideration of animal behavior was exceeded by the uncertainty of the density estimates, which was mainly influenced by variation in the number of independent observations between camera trap locations. The neglection of seasonal and annual differences in movement speed estimates for REM overestimated densities of red deer in autumn and spring by ca. 14%. This GPS telemetry-derived parameter was found to be most problematic for roe deer females in summer and spring when movement behavior was characterized by small-scale displacements relative to the intervals of the GPS fixes. In CTDS, density estimates of red deer improved foremost through the consideration of behavioral reactions to the camera traps (avoiding bias of max. 19%), while species-specific delays between photos had a larger effect for roe deer. In general, the applicability of both REM and CTDS would profit profoundly from improvements in their precision along with the reduction in bias achieved by exploiting the available information on animal behavior in the camera trap data.Deer Behavior Affects Density Estimates With Camera Traps, but Is Outwighted by Spatial VariabilitypublishedVersio

Spatial variation in red deer density in a transboundary forest ecosystem

Forests in Europe are exposed to increasingly frequent and severe disturbances. The resulting changes in the structure and composition of forests can have profound consequences for the wildlife inhabiting them. Moreover, wildlife populations in Europe are often subjected to differential management regimes as they regularly extend across multiple national and administrative borders. The red deer Cervus elaphus population in the Bohemian Forest Ecosystem, straddling the Czech-German border, has experienced forest disturbances, primarily caused by windfalls and bark beetle Ips typographus outbreaks during the past decades. To adapt local management strategies to the changing environmental conditions and to coordinate them across the international border, reliable estimates of red deer density and abundance are highly sought-after by policymakers, wildlife managers, and stakeholders. Covering a 1081-km2 study area, we conducted a transnational non-invasive DNA sampling study in 2018 that yielded 1578 genotyped DNA samples from 1120 individual red deer. Using spatial capture-recapture models, we estimated total and jurisdiction-specific abundance of red deer throughout the ecosystem and quantified the role of forest disturbance and differential management strategies in shaping spatial heterogeneity in red deer density. We hypothesised that (a) forest disturbances provide favourable habitat conditions (e.g., forage and cover), and (b) contrasting red deer management regimes in different jurisdictions create a differential risk landscape, ultimately shaping density distributions. Overall, we estimated that 2851 red deer (95% Credible Interval = 2609–3119) resided in the study area during the sampling period, with a relatively even overall sex ratio (1406 females, 95% CI = 1229–1612 and 1445 males, 95% CI = 1288–1626). The average red deer density was higher in Czechia (3.5 km−2, 95% CI = 1.2–12.3) compared to Germany (2 km−2, 95% CI = 0.2–11). The effect of forest disturbances on red deer density was context-dependent. Forest disturbances had a positive effect on red deer density at higher elevations and a negative effect at lower elevations, which could be explained by partial migration and its drivers in this population. Density of red deer was generally higher in management units where hunting is prohibited. In addition, we found that sex ratios differed between administrative units and were more balanced in the non-intervention zones. Our results show that the effect of forest disturbances on wild ungulates is modulated by additional factors, such as elevation and ungulate management practices. Overall density patterns and sex ratios suggested strong gradients in density between administrative units. With climate change increasing the severity and frequency of forest disturbances, population-level monitoring and management are becoming increasingly important, especially for wide-ranging species as both wildlife and global change transcend administrative boundaries.publishedVersio

Large herbivore migration plasticity along environmental gradients in Europe: life-history traits modulate forage effects

The most common framework under which ungulate migration is studied predicts that it is driven by spatio–temporal variation in plant phenology, yet other hypotheses may explain differences within and between species. To disentangle more complex patterns than those based on single species/ single populations, we quantified migration vari-ability using two sympatric ungulate species differing in their foraging strategy, mating system and physiological constraints due to body size. We related observed variation to a set of hypotheses. We used GPS-collar data from 537 individuals in 10 roe Capreolus capreolus and 12 red deer Cervus elaphus populations spanning environmental gra-dients across Europe to assess variation in migration propensity, distance and tim-ing. Using time-to-event models, we explored how the probability of migration varied in relation to sex, landscape (e.g. topography, forest cover) and temporally-varying environmental factors (e.g. plant green-up, snow cover). Migration propensity varied across study areas. Red deer were, on average, three times more migratory than roe deer (56% versus 18%). This relationship was mainly driven by red deer males which were twice as migratory as females (82% versus 38%). The probability of roe deer migration was similar between sexes. Roe deer (both sexes) migrated earliest in spring. While territorial male roe deer migrated last in autumn, male and female red deer migrated around the same time in autumn, likely due to their polygynous mating system. Plant productivity determined the onset of spring migration in both species, but if plant productivity on winter ranges was sufficiently high, roe deer were less likely to leave. In autumn, migration coincided with reduced plant productivity for both species. This relationship was stronger for red deer. Our results confirm that ungulate migration is influenced by plant phenology, but in a novel way, that these effects appear to be modulated by species-specific traits, especially mating strategies.publishedVersio

Disentangling effects of climate and land use on biodiversity and ecosystem services - a multi‐scale experimental design

Climate and land-use change are key drivers of environmental degradation in the Anthropocene, but too little is known about their interactive effects on biodiversity and ecosystem services. Long-term data on biodiversity trends are currently lacking. Furthermore, previous ecological studies have rarely considered climate and land use in a joint design, did not achieve variable independence or lost statistical power by not covering the full range of environmental gradients. Here, we introduce a multi-scale space-for-time study design to disentangle effects of climate and land use on biodiversity and ecosystem services. The site selection approach coupled extensive GIS-based exploration (i.e. using a Geographic information system) and correlation heatmaps with a crossed and nested design covering regional, landscape and local scales. Its implementation in Bavaria (Germany) resulted in a set of study plots that maximise the potential range and independence of environmental variables at different spatial scales. Stratifying the state of Bavaria into five climate zones (reference period 1981–2010) and three prevailing land-use types, that is, near-natural, agriculture and urban, resulted in 60 study regions (5.8 × 5.8 km quadrants) covering a mean annual temperature gradient of 5.6–9.8°C and a spatial extent of ~310 × 310 km. Within these regions, we nested 180 study plots located in contrasting local land-use types, that is, forests, grasslands, arable land or settlement (local climate gradient 4.5–10°C). This approach achieved low correlations between climate and land use (proportional cover) at the regional and landscape scale with |r ≤ 0.33| and |r ≤ 0.29| respectively. Furthermore, using correlation heatmaps for local plot selection reduced potentially confounding relationships between landscape composition and configuration for plots located in forests, arable land and settlements. The suggested design expands upon previous research in covering a significant range of environmental gradients and including a diversity of dominant land-use types at different scales within different climatic contexts. It allows independent assessment of the relative contribution of multi-scale climate and land use on biodiversity and ecosystem services. Understanding potential interdependencies among global change drivers is essential to develop effective restoration and mitigation strategies against biodiversity decline, especially in expectation of future climatic changes. Importantly, this study also provides a baseline for long-term ecological monitoring programs