First week back in CSIS after the holiday and I got cracking with the winter white-tailed deer density paper we’re working. Understanding the winter spatial distribution of deer are important for the wider simulation modelling project we’re working on as the model needs to be able to estimate deer densities at each model timestep. We need to do this so that we might represent the impacts of deer on tree regeneration following timber harvest in the simulation model. The work the paper will present is using data from several sources:
- data we collected this summer regarding forest stand composition and structure,
- similar data kindly shared with us by the Michigan DNR,
- estimates of deer density derived from deer pellet counts we also made this year,
- other environmental data such as snow depth data from SNODAS.
Here’s my first stab at the opening paragraph (which will no doubt change before publication):
Spatial distributions of wildlife species in forest landscapes are known to be influenced by forest-cover composition and pattern. The influence of forest stand structure on the spatial distribution of wildlife is less well understood. However, understanding the spatial distribution of herbivorous ungulate species that modify vegetation regeneration dynamics is vital for forest managers entrusted with the goal of ensuring both ecological and economic sustainability of their forests. Feedbacks between timber harvest, landscape pattern, stand structure, and herbivore population density may lead to spatial variation in tree regeneration success. In this paper we explore how forest stand structure and landscape pattern, and their interactions with other environmental factors, can be used to predict and understand the winter spatial distribution of white-tailed deer (Odocoileus virginianus) during in the managed forests of the central Upper Peninsula (U.P.) of Michigan, USA.
I’ll update the status of the paper here periodically.