Assessing the spatial and temporal distribution of snow for climate change impacts and its influence on wildlife habitat selection

Annual snowpack data is typically summarized at a regional scale and used to make forecasts for spring melt conditions and flooding. However the spatial pattern of snow, its accumulation and melting across the land base, also directly influences the movement and habitat selection for many wildlife species which in turn impacts forest harvesting and resource management decisions. By examining the spatial distribution of snow on a finer scale using remote sensing, and incorporating existing wildlife data, better models can be created for wildlife habitat management and climate change impacts. Such data and modelling becomes a valuable service opportunity for SGS to use in the creation of partnerships for forest harvesting, wildlife management, conservation, tourism, and heritage projects. It also becomes the leverage for climate change adaptation projects, which will influence future economic opportunities. Our goal is to incorporate this new data and analyses into our website services to inform strategic and decision-making processes.

Faculty Supervisor:

Nicholas Coops

Student:

Partner:

St’át’imc Government Services

Discipline:

Earth science

Sector:

Professional, scientific and technical services

University:

The University of British Columbia

Program: