The role of predation, forestry and productivity in moose harvest at different spatial levels of management units

Management of ungulate populations to the desired density and/or demographic composition are challenged by contrasting aims of different stakeholders. For example, hunters may want to maximize hunting opportunities whereas commercial forest owners may want to minimize moose densities to mitigate browsing damage. In addition, the return of large predators such as wolves (Canis lupus) affects the possible harvest yield of ungulates and influences the population composition through their selection of specific age classes. The aim of this study was to gain a better understanding of factors related to the variation in moose (Alces alces) harvest. We used moose harvest statistics from the period 2012-2020, wolf annual monitoring data, annual brown bear (Ursus arctos) density, proportion of young forest per management unit, and proportion of agricultural land per management unit (index for productivity and roe deer (Capreolus capreolus) density) to explain variation in moose harvest across dif..., , , # The role of predation, forestry and productivity in moose harvest at different spatial levels of management units

Description of the data files and structure:

There are three datasets that correspond to the three spatial levels of management units. Specifically, the Regional level is composed of regional management units (RMUs), the Local level is composed of local management units (LMUs), and the Hunting areas (HA). See the paragraph 'Harvest statistics' in Material and Methods for more details.

Below is a description of the columns:
country = Sweden or Norway
hunting_area = License area or Management area
year = year (2012 is 2012/2013)
size_RMU/size_HA = size of management unit
short_term_wolf_index = index of wolf territory density as an average during two years
long_term_wolf_index = index of wolf territory density as an average during five years
brown_bear_density = density of brown bear
young_forest = proportion of young forest
roe_deer_index = index of roe deer density meas...