Wolf attacks on hunting dogs are negatively related to prey abundance in Finland: an analysis at the wolf territory level

Attacks by wolves (Canis lupus) on dogs (C. familiaris) presumably are motivated both by preying and elimination of potential competitors. Regardless of these alternative motivations in wolves, the risk of attacks might be higher when the density of primary prey is low. We examined how many dogs do territorial wolves in Finland kill in relation to the population density of the most abundant ungulates, moose (Alces alces), white-tailed deer (Odocoileus virginianus), and roe deer (Capreolus capreolus). Most attacks by wolves on dogs take place in hunting with dogs. The number of wolf-killed dogs was in highly significant negative relationship to the population density of white-tailed deer and to total ungulate biomass per unit area which is largely determined by the density of white-tailed deer. Our results indicate that abundant wild prey would decrease the risk at which wolves attack dogs. On the other side of the coin prevail two hard facts which wildlife managers had to take a notice. White-tailed deer, although a potential mitigator of wolf–human conflict, is an alien species and a partner in > 6000 traffic collisions annually in Finland. One factor that seemed to increase the risk of wolf attacks on dogs is the low ungulate density in regions where moose is the only remarkable ungulate prey. Higher moose densities could decrease the risk of attacks, but on the other hand, higher densities could increase the risk of serious traffic collisions and browsing damages in forests.

Human Decision-Making as a Key Factor in the Risk of Wolf-Dog Interactions during Outdoor Activities

Simple Summary

The aim of the study was to determine the nature and causes of direct contact between a wolf and domestic dog during different forms of human recreation. The results are crucial for reducing human–nature conflicts and for education. Thanks to this study, we conclude that humans are responsible for reducing the risk of direct contact between these two canine species. The risk of interaction between wolves and a dog that is with a human depends on the distance between the dog and its owner, the number of wolves, and the size of the dog. Hunting with a dog poses a seven times greater risk of interaction with wolves compared to recreational walking.

Abstract

As a result of species protection in Poland, wolves now appear in places that are attractive for human recreation, increasing their exposure to dogs. This creates a risk of spontaneous direct interactions between these two canine species. Aggressive interactions between the gray wolf and the domestic dog lead to human–large predator conflicts. This study examined wolf–dog interactions using data collected in an online questionnaire and included questions related to factors that might influence the likelihood of interactions between these canines. One of the most important factors affecting the likelihood of interaction between a dog and a wolf was the distance between the dog and the human. The number of wolves was also important—the more wolves, the more likely they were to interact with dogs. The risk of interaction also significantly increases with decreasing distance to human settlements. There were also statistical differences in terms of the type of outdoor activity being engaged in. Hunting was seven times more likely to result in a wolf–dog interaction than normal walk. We postulate that the choices made by the human (dog control and type of recreation) caring for the dog are an important factor that can reduce the risk of direct contact between dogs and wolves.

A novel modelling framework to explicitly simulate predator interaction with poison baits

Abstract ContextManagement of human–wildlife conflicts is of critical importance for both wildlife conservation and agricultural production. Population models are commonly used to simulate population dynamics and their responses to management actions. However, it is essential that this class of models captures the drivers and mechanisms necessary to reliably forecast future system dynamics. AimsWe aimed to develop a flexible modelling framework with the capacity to explicitly simulate individual interactions with baits (with or without the presence of other management tools), for which parameter estimates from field data are available. We also intended for the model to potentially accommodate multi-species interaction and avoidance behaviours. MethodsWe expanded an existing spatially explicit, individual-based model to directly simulate bait deployment, animal movements and bait consumption. We demonstrated the utility of this model using a case study from Western Australia where we considered two possible exclusion-fence scenarios, namely, the completion of a landscape-scale and smaller-scale fences. Within each of these proposed cells, using data obtained from a camera-trap study, we evaluated the performance of two levels of baiting to control wild dogs (Canis familiaris), in contrast with the option of no control. ResultsThe present study represents a substantial step forward in accurately modelling predator dynamics. When applying our model to the case study, for example, it was straightforward to investigate whether outcomes were sensitive to the bait-encounter probability. We could further explore interactions between baiting regimes and different fence designs and demonstrate how wild dog eradication could be achieved in the smaller cell under the more intense control scenarios. In contrast, the landscape-scale fence had only minor effects unless it was implemented as a preventive measure in an area where wild dogs were not already established. ConclusionsThe new component of the model presented here provides fine-scale control of single components of individual–bait interactions. ImplicationsThe effect of management actions (e.g. lures) that affect this process can be easily investigated. Multi-species modelling and avoidance behaviours can readily be implemented, making the present study widely relevant for a range of contexts such as multi-species competition or non-target bait uptake.

Does public information about wolf (Canis lupus) movements decrease wolf attacks on hunting dogs (C. familiaris)?

The threat that wolves (Canis lupus) pose to hunting dogs is one reason why Finnish hunters have negative attitudes towards wolves and one of the potential motivations for the illegal killing of wolves. During 2010–2017, wolves killed an average of 38 dogs (range 24–50) per year in Finland. Most of the attacks (91%) were directed at hunting dogs during the hunting season. To decrease the risk of attacks, the last seven positions (one position per hour) of GPS-collared wolves were accessible to the public with a 5 × 5 km resolution during the hunting seasons (from August 20th to February 28th) of 2013/2014 (from September 2nd onwards), 2015/2016, 2016/2017 and 2017/2018. The link was visited more than 1 million times in 3 of the 4 seasons. Fatal attacks on dogs occurred on 17% of the days during the hunting seasons of our study (n = 760 days). Both the attacks and visits peaked in September–November, which is the primary hunting season in Finland. According to the general linear model, the number of daily visits to the website was higher on days when fatal attacks occurred than on other days. Additionally, season and the number of days passed from the first day of the season were significantly related to the daily visits. Visits were temporally auto-correlated, and the parameter values in the model where the dependent variable was the number of visits on the next day were only slightly different from those in the first model. A two-way interaction between season and attack existed, and the least squares means were significantly different in 2017/2018. The change in daily visits between consecutive days was related only to the number of days from the beginning of the season. We examined whether this kind of service decreased dog attacks by wolves. Wolf attacks were recorded in 32% of the wolf territories, where at least one wolf had been collared (n = 22). However, within the territories without any GPS-collared wolves, the proportion of territories with wolf attack(s) was significantly higher than those elsewhere (50%, n = 48). Although public information decreased the risk of attacks, it did not completely protect dogs from wolf attacks and may in some cases increase the risk of illegally killing wolves. The most remarkable benefit of this kind of service to the conservation of the wolf population might be the message to the public that management is not overlooking hunters’ concerns about wolf attacks on their dogs.

A landscape of overlapping risks for wolf-human conflict in Wisconsin, USA

Managing risk requires an adequate understanding of risk-factors that influence the likelihood of a particular event occurring in time and space. Risk maps can be valuable tools for natural resource managers, allowing them to better understand spatial characteristics of risk. Risk maps can also support risk-avoidance efforts by identifying which areas are relatively riskier than others. However, risks, such as human-carnivore conflict, can be diverse, multi-faceted, and overlapping in space. Yet, efforts to describe risk typically focus on only one aspect of risk. We examined wolf complaints investigated in Wisconsin, USA for the period of 1999-2011. We described the spatial patterns of four types of wolf-human conflict: livestock depredation, depredation on hunting hounds, depredation on non-hound dogs, and human health and safety concerns (HHSC). Using predictive landscape models and discriminant functions analysis, we visualized the landscape of risk as a continuous surface of overlapping risks. Each type of conflict had its own unique landscape signature; however, the probability of any type of conflict increased closer to the center of wolf pack territories and with increased forest cover. Hunting hound depredations tended to occur in areas considered to be highly suitable wolf habitat, while livestock depredations occurred more regularly in marginal wolf habitat. HHSC and non-hound dog depredations were less predictable spatially but tended to occur in areas with low housing density adjacent to large wildland areas. Similar to other research evaluating the risk of human-carnivore conflict, our data suggests that human-carnivore conflict is most likely to occur where humans or human property and large carnivores co-occur. However, identifying areas of co-occurrence is only marginally valuable from a conservation standpoint and could be described using spatially-explicit human and carnivore data without complex analytical approaches. These results challenge our traditional understanding of risk and the standard approach used in describing risk. We suggest that a more comprehensive understanding of the risk of human-carnivore conflict can be achieved by examining the spatial and non-spatial factors influencing risk within areas of co-occurrence and by describing the landscape of risk as a continuous surface of multiple overlapping risks.