Lukas Graf

Evidence‐based forest and wildlife management requires precise estimates of forage availability for spatial planning and conflict mitigation. Recently, novel datasets and associated maps have been developed for use in Swedish forest and wildlife management. These foodscape maps show the estimated nationwide abundance of six tree species, within a browsing height window, that are important forage sources for Swedish ungulates. In this short communication, we tested their applicability to infer on movement and habitat selection using GPS data of 54 adult moose in two study sites in southern and central Sweden. We model habitat selection using a combination of a three‐state hidden Markov model (HMM) and integrated Step Selection Analysis. We further tested their performance in models where habitat selection was not accounted for ( behavior‐unspecific models). Models containing information on both the foodscape and landcover performed best in the foraging HMM state and in behavior‐unspecific models, across all seasons. In the encamped and travelling HMM state, forage + landcover models performed similarly to forage models. In behavioral states associated with foraging, habitat selection models containing data from the foodscape maps were consistently selected as the most parsimonious models compared to models that only included landcover information as covariates. Further, moose showed nuanced habitat selection patterns based on their behavioral state, and selection for young forest shifted once forage abundance was accounted for, from a generally preferred habitat to a generally avoided habitat. We showcase the predictive capability of the newly developed maps to draw nuanced inference on habitat selection of moose across several seasons in several behavioral states.

The spatiotemporal behavior of game species may play a critical role in their survival throughout the hunting season. Where humans are the most dominant predators, avoidance of landscape features that allow hunter access to hunting grounds can be key to increasing survival. However, in Sweden there is limited knowledge about how hunters impact populations through selection of behavioral traits. In this system, hunting pressure is generally high and approximately 30% of the moose Alces alces population is harvested per year. To test for differences in habitat selection in relation to survival under varying levels of hunting pressure in this long‐lived game species, we analyzed 10 years of individual‐based movement data of adult male and female moose in southern Sweden. We used integrated Step Selection Functions (iSSF) to analyze habitat selection in four consecutive time periods (before the rutting season, during the rut, during the first three weeks of the hunting season and the following three weeks). We matched habitat selection coefficients of individual animals with their fate and tested for behavioral differences between ‘harvested' and ‘non‐harvested'male and female moose in each period. Our findings indicate that hunters may select for sex‐specific behavioral traits in habitat selection by adult moose. We found that hunters harvested male moose that selected for higher NDVI during the rut, suggesting personality‐driven hunting mortality in male moose. In contrast, in female moose, the mortality risk increased with selection for shorter distance to roads during the hunting season, suggesting selection for behavioral traits by hunters. Our findings indicate that current harvest practices for moose result in a selection for sex‐specific behavioral traits. Our study highlights the complex dynamics of survival in a long‐lived species under high hunting pressure, revealing how sex‐specific habitat selection may impact mortality risk by hunters and, in return, might influence population management.

Background: In prey, patterns of individual habitat selection and movement can be a consequence of an individuals’ anti-predator behavior. Adjustments of anti-predator behavior are important for prey to increase their survival. Hunters may alter the anti-predator behavior of prey. In long-lived animals, experience may cause behavioral changes during individuals’ lifetime, which may result in altered habitat selection and movement. Our knowledge of which specific events related to hunting activity induce behavioral changes in solitary living species is still limited. Methods: We used offspring loss in a solitary and long-lived ungulate species, moose (Alces alces), as our model system. We investigated whether offspring loss to hunters induces behavioral changes in a species subjected to heavy human harvest but free from natural predation. To test for behavioral change in relation to two proxies for experience (calf fate and age), we combined movement data from 51 adult female moose with data on their offspring survival and female age. We tested for adjustments in females’ habitat selection and movement following calf harvest using Hidden Markov Models and integrated Step Selection Analysis to obtain behavioral state specific habitat selection coefficients. Results: We found that females with a harvested calf modified habitat selection and movement during the following hunting season. Female moose selected for shorter distance to roads during the night, selected for shorter distance to forests and greater distance to human settlements following calf harvest than females who had not lost a calf. The survival of twins in a given hunting season was related to female age. Older females we more likely to have twins survive the hunting season. Conclusions: Our findings suggest that losing offspring to human harvest imposes behavioral changes in a long-lived ungulate species, leading to adjustments in females' habitat selection and movement behavior, which may lower the risk of encountering hunters. In our study, female moose that experienced calf loss selected for lower distance to forest and selected for greater distance to human settlements during periods of high hunting pressure compared to females without the experience of calf loss during the previous hunting season. We interpret this as potential learning effects.

Golden jackals (Canis aureus) display a complex repertoire of calls, utilized in different communication types (e.g., marking territories, attraction of mating partners). Resident golden jackal groups can successfully be detected by active bioacoustic stimulation, as well as with passive recording devices. For monitoring, basic knowledge of the calls of the focal species and potential restrictions and strengths of the monitoring devices should be considered. We therefore tested possible applications of a low-budget autonomous recording unit for bioacoustic golden jackal monitoring and examined the following research questions: How far can group calls be detected? Can the distance to the recording device be estimated? To answer these questions, we placed 11 AudioMoth recording devices in a linear transect to record live imitated and replayed howls. For the estimation of the number of responding animals, the number of howling individuals was determined based on the maximum number of simultaneously visible fundamental frequencies in a spectrogram. To predict the distance of the playback howls to the recording devices, the relative sound level (RSL) of each call was measured and fitted in linear models. Reliable distance estimations using RSL were possible up to 400 m. Estimated number of responding animals showed a negative relationship with distance. Our results present a baseline for future studies and show that AudioMoths can be a helpful asset in distance estimation of golden jackal packs—both in passive but also active monitoring.