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Political borders dictate how biological diversity is monitored and managed, yet wild animals often move freely between jurisdictions. We quantified bias in brown bear (Ursus arctos) abundance estimates introduced when analytical methods ignore that the same individuals may be accounted for in more than one jurisdiction. A spatially explicit population model revealed that up to 49% of female bears detected in Norway via microsatellite analysis of scat and hair samples have their center of activity in neighboring countries (Finland, Russia, and Sweden). Not accounting for detections of "foreign residents" resulted in abundance estimates that were inflated by as much as 119%. Like man- agement and conservation, monitoring of transboundary wildlife populations should take place at ecologically relevant scales to avoid biased abundance es- timates and a false sense of control. When political realities isolate jurisdictions from their neighbors, spatially explicit analytical approaches can allow local or national programs a glimpse beyond their borders. Jurisdiction; large carnivore management; natural resource policy; noninvasive genetic monitoring; spatially explicit capture-recapture; transboundary wildlife.

- ; Political borders dictate how biological diversity is monitored and managed, yet wild animals often move freely between jurisdictions. We quantified bias in brown bear (Ursus arctos) abundance estimates introduced when analytical methods ignore that the same individuals may be accounted for in more than one jurisdiction. A spatially explicit population model revealed that up to 49% of female bears detected in Norway via microsatellite analysis of scat and hair samples have their center of activity in neighboring countries (Finland, Russia, and Sweden). Not accounting for detections of "foreign residents" resulted in abundance estimates that were inflated by as much as 119%. Like man- agement and conservation, monitoring of transboundary wildlife populations should take place at ecologically relevant scales to avoid biased abundance es- timates and a false sense of control. When political realities isolate jurisdictions from their neighbors, spatially explicit analytical approaches can allow local or national programs a glimpse beyond their borders. Jurisdiction; large carnivore management; natural resource policy; noninvasive genetic monitoring; spatially explicit capture-recapture; transboundary wildlife.

Political borders dictate how biological diversity is monitored and managed, yet wild animals often move freely between jurisdictions. We quantified bias in brown bear (Ursus arctos) abundance estimates introduced when analytical methods ignore that the same individuals may be accounted for in more than one jurisdiction. A spatially explicit population model revealed that up to 49% of female bears detected in Norway via microsatellite analysis of scat and hair samples have their center of activity in neighboring countries (Finland, Russia, and Sweden). Not accounting for detections of "foreign residents" resulted in abundance estimates that were inflated by as much as 119%. Like man- agement and conservation, monitoring of transboundary wildlife populations should take place at ecologically relevant scales to avoid biased abundance es- timates and a false sense of control. When political realities isolate jurisdictions from their neighbors, spatially explicit analytical approaches can allow local or national programs a glimpse beyond their borders. Jurisdiction; large carnivore management; natural resource policy; noninvasive genetic monitoring; spatially explicit capture-recapture; transboundary wildlife.

Large carnivore populations are recovering in many parts of the world and this generates conflicts with humans, notably in terms of livestock depredation. Governmental programs of mitigation measures and compensation for losses are often implemented to reduce conflicts, but the factors affecting losses are poorly understood. We used 11 years of data on domestic sheep (Ovis aries) claimed, and confirmed, to have been killed by predators in Norway to evaluate how predator density, flock management, and other environmental or habitat‐related variables are related to losses. The percentage of animals claimed as lost that was found and confirmed to have been killed by large predators (i.e., the detection rate) was low, especially for sheep claimed as killed by Eurasian lynx (Lynx lynx), wolverine (Gulo gulo) and golden eagle (Aquila chrysaetos). Still, we generally found that similar factors predicted the number of claims and number of carcasses found across predator species. Predator density was strongly associated with losses, especially for sheep claimed as killed by brown bears (Ursus arctos), lynx and wolverines. Percentage of forest in the pastures, average slaughter weight of the lambs (an indicator of the forage conditions during summer) and vegetation characteristics in the spring also predicted the number of sheep claimed and found killed by lynx, wolverines and eagles. Factors related to losses due to wolves (Canis lupus) were harder to ascertain, possibly because of the severity of mitigation measures (e.g., electric fences) taken to protect sheep in wolf territories, a factor we were not able to include in our large scale analyses. Patrolling of the grazing area and early gathering of sheep in the autumn were not associated with a substantial reduction in losses. However, our dataset was not well suited to evaluate the efficiency of those mitigation strategies. Our findings could help develop new mitigation strategies as alternatives to predator removal where large carnivore conservation is a concern.

Harvesting large carnivores can be a management tool for meeting politically set goals for their desired abundance. However, harvesting carnivores creates its own set of conflicts in both society and among conservation professionals, where one consequence is a need to demonstrate that management is sustainable, evidence‐based, and guided by science. Furthermore, because large carnivores often also have high degrees of legal protection, harvest quotas have to be carefully justified and constantly adjusted to avoid damaging their conservation status. We developed a Bayesian state‐space model to support adaptive management of Eurasian lynx harvesting in Scandinavia. The model uses data from the annual monitoring of lynx abundance and results from long‐term field research on lynx biology, which has provided detailed estimates of key demographic parameters. We used the model to predict the probability that the forecasted population size will be below or above the management objectives when subjected to different harvest quotas. The model presented here informs decision makers about the policy risks of alternative harvest levels. Earlier versions of the model have been available for wildlife managers in both Sweden and Norway to guide lynx harvest quotas and the model predictions showed good agreement with observations. We combined monitoring data with data on vital rates and were able to estimate unobserved additional mortality rates, which are most probably due to poaching. In both countries, the past quota setting strategy suggests that there has been a de facto threshold strategy with increasing proportion, which means that there is no harvest below a certain population size, but above this threshold there is an increasing proportion of the population harvested as the population size increases. The annual assessment of the monitoring results, the use of forecasting models, and a threshold harvest approach to quota setting will all reduce the risk of lynx population sizes moving outside the desired goals. The ...