The effects of moose and pine density on browsing damage in Swedish pine forests

Franklin, O. ORCID: https://orcid.org/0000-0002-0376-4140, Kalén, C., Felton, A.M., & Wallgren, M. (2026). The effects of moose and pine density on browsing damage in Swedish pine forests. Wildlife Biology 10.1002/wlb3.01614. (In Press)

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Abstract

Moose Alces alces is a culturally and economically important game species in Sweden, but their browsing on regenerating Scots pine trees Pinus sylvestris often causes extensive damage to the production and quality of timber. Forest and wildlife managers are faced with the dilemma of how to reduce damage to timber trees while also supporting moose populations and hunting opportunities. The proportion of damaged trees can be reduced by decreasing the number of moose, but also by increasing the number of pines. However, the relative effectiveness of these two approaches is debated and has not been conclusively determined. Here, we addressed this question by analyzing the effects of moose and pine density on pine damage based on yearly data from almost all of Sweden's moose management areas (MMAs) over a 10‐year period (2015–2024; 718 observations). We developed a mechanistic model to realistically represent the browsing process and used regression with mixed models to account for variable vulnerability (variation in damage risk at a fixed moose per pine ratio) among MMAs in the statistical analysis. The model explained 53% of the variation in the proportion of damaged trees and showed that, on average, the relative damage reduction effect of a decreased moose population was ~ 1.5× larger (25%) than the effect of increased pine density (17%). Vulnerability to browsing varied substantially among MMAs and between years within each MMA, especially in areas with low pine density. This variability prevents reliable predictions of management effects at the individual MMA level for most MMAs. Such local predictions may be improved in the future by incorporating longer time series of observations and additional variables, such as alternative forage sources, browsing by other deer species, and snow cover and duration.

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