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Reducing browsing damages from cervids (Cervidae) on economically valuable tree species is a challenging task in many countries. Apart from cervid abundance, landscape characteristics, such as forest composition, land use, forage availability and climatic conditions, may affect the degree of browsing through both direct and indirect effects. A better understanding of basic mechanisms in this complex system is needed to design efficient and convincing management strategies. Focusing on Sweden as a case, which has been widely studied using regression analyses only, we applied path analysis to test the validity of a model on the indirect and direct links between landscape characteristics, cervid populations, and browsing damages on Scots pine (Pinus sylvestris). Our results validated the tested model in which moose (Alces alces) density and pine availability directly influence browsing damages. Increasing amounts of pine forests, preferred deciduous trees, and young forest had positive direct effects on moose densities and thereby indirectly contributed to increased browsing damages. The density of smaller deer species showed no direct effect on browsing damages on pine. Path analysis corroborated our attempt to disentangle direct and indirect potential causal drivers of browsing damages and shows that the choice of statistical method may alter the understanding of mechanistic driving forces. [ABSTRACT FROM AUTHOR]

As wild ungulate densities increase across Europe and North America, plant–herbivore interactions are increasingly important from ecological and economic perspectives. These interactions are particularly significant where agriculture and forestry occur and where intensive grazing and browsing by wild ungulates can result in economic losses to growing crops and trees. We studied plant–herbivore interactions in a moose (Alces alces)‐dominant system where forestry is a primary economy, the primary and secondary road networks are extensive, and wolves (Canis lupus) are recolonizing. Wolves and humans use low‐traffic, secondary roads, yet roadsides provide high‐quality and quantity browse for moose. Foraging theory predicts that moose will respond to riskier landscapes by selecting habitats that reduce predation risk, sacrificing feeding time or food quality. As food becomes limiting, however, animals will accept higher predation risk in search of food. We predicted that road avoidance behavior would be strongest within wolf territories. In areas without wolves, moose should select roadsides for their high forage availability. To test these predictions, we measured moose browsing and counted pellet groups as a proxy for habitat use each spring in Norway and Sweden between 2008 and 2018, in areas with and without wolves and at different distances from primary and secondary roads. We used generalized linear mixed models to evaluate drivers of the probability of browsing occurrence and browsing pressure. We found that browsing occurrence increased closer to secondary roads but decreased closer to primary roads. We also found browsing patterns to vary among tree species. For Scots pine (Pinus sylvestris), the browsing occurrence was two times higher in young forests relative to non‐young forests and decreased further from secondary roads. Wolf territory presence and probability had neutral or positive effect on browsing occurrence and pressure for all species. However, wolf territory presence had negative effects on browsing occurrence and pressure when interacting with secondary roads, young forest, or snow cover. We showed that roads can influence browsing patterns in Norway and Sweden. However, further research is needed, particularly in the face of continued infrastructure development in Scandinavia. [ABSTRACT FROM AUTHOR]

Abstract: Across the northern hemisphere, land use changes and, possibly, warmer winters are leading to more abundant and diverse ungulate communities causing increased socioeconomic and ecological consequences. Reliable population estimates are crucial for sustainable management, but it is currently unclear which monitoring method is most suitable to track changes in multi‐species assemblages. We compared dung counts and camera trapping as two non‐invasive census methods to estimate population densities of moose Alces alces and roe deer Capreolus capreolus in Northern Sweden. For camera trapping, we tested the random encounter model (REM) which can estimate densities without the need to recognize individual animals. We evaluated different simplification options of the REM in terms of estimates of detection distance and angle (raw data vs. modelled) and of daily movement rate (camera trap based vs. telemetry based). In comparison to density estimates from camera traps, we found that, dung counts appeared to underestimate population density for roe deer, but not for moose. Estimates of detection distance and angle from modelled versus raw camera data resulted in nearly identical outcomes. The telemetry‐derived daily movement rate for moose and roe deer resulted in much higher density estimates than the camera trap‐derived estimates. We suggest that camera trapping may be a robust complement to dung counts when monitoring ungulate communities, particularly when similarities between dung pellets from sympatric deer species make unambiguous assignment difficult. Moreover, we show that a simplified use of the REM method holds great potential for large‐scale citizen science‐based programmes (e.g. involving hunters) that can track the rapidly changing European wildlife landscape. We suggest to include camera trapping in management programmes, where the analysis can be verified via web‐based applications. [ABSTRACT FROM AUTHOR]

• Predictors of winter damage differed from predictors of summer damage on Scots pine. • But dependent on spatial scale higher pine densities reduced both winter and summer damage. • Pine density predicted winter damage equally or better than deer density indices. • In multi-deer systems, all species need to be considered to interpret winter damage. • National predictors seem insufficient for regional management decisions. Population sizes and species distributions of wild ungulates in Europe have increased during the past decades, and continue to do so. As a result, browsing pressure in forests is increasing and concerns about the effects of increasingly common multi-species deer communities on forestry are rising. However, we currently lack an understanding of how the composition of deer communities affects browsing damage, particularly with respect to the role of species with different dietary requirements. Further, the relative importance of predictors of browsing damage in systems with multiple browsers remains elusive. Here, we used data from Swedish management, which is monitoring ungulates and their damage to forests, to test how deer densities, forage availability, and winter severity predict browsing damage on commercially important Scots pine (Pinus sylvestris) at national and regional scales. Moose (Alces alces) is the main browser of Scots pine, but competes with other deer over more preferred forage. During winter, a higher index of moose density was associated with higher browsing damage in northern Sweden, where there is low competition from other deer. In southern Sweden, competition from other deer is higher and a higher density index of roe deer (Capreolus capreolus) was associated with higher winter damage. However, there was no relationship between moose density and damage. We suggest that moose are forced to browse more pine due to interspecific competition over alternative forage resources in the south, yielding stronger relationships between densities of competing deer species and damage than between moose density and damage. Pine density, a proxy for forage availability, was an equally or more important determinant for browsing damage as deer density indices in most regions. Increasing pine density was associated with reduced browsing damage caused in winter in all regions and reduced damage caused in summer in central Sweden. Increased winter severity, as an index of snow depth, predicted increased winter damage in the northern region only. To reduce winter damage, our results suggest that management should consider deer densities and forage availability simultaneously, while adopting a multi-species approach. Results varied among regions, with densities of other deer being more relevant in the south and winter severity more relevant in the north. Management data did not predict summer damage well. Since national models did not capture regional variations, we conclude that management decisions and actions need to be tailored to the regional or local scale. [ABSTRACT FROM AUTHOR]