About This Project

Berries are a crucial fall resource for a multitude of wildlife species including migratory birds, threatened grizzly bears, black bears, and a variety of small mammals. Berries are also an important socioeconomic and cultural resource for local communities and indigenous populations. We leverage satellite and aerial imagery data within a machine learning framework to develop species-specific maps of shrub distributions along the biologically diverse Rocky Mountain Front.

Ask the Scientists

What is the context of this research?

Our previous research has shown that mapping a single keystone shrub species (Vaccinnium sp.) on a landscape-scale via unique phenology is possible with moderate-to-good accuracy. The Rocky Mountain Front in northern Montana, USA encompasses portions of Glacier National Park, the Blackfeet Indian Reservation, and the Badger-Two Medicine area, a culturally and spiritually significant region for the Blackfeet tribe under USFS management. Although the region is vast, climate change and human land-use threaten populations and habitats of sensitive species like grizzly bears, migratory birds, and migratory ungulates, but remain understudied. Plants are unequal in the eyes of wildlife populations, and berry-producing shrubs are some of the most productive in terms of caloric value to wildlife.

What is the significance of this project?

Species-specific food source maps are an integral part of any wildlife study. Current best practice assigns food source importance in an ambiguous way, often assigning food source importance based on rough differences in growth form, e.g. grasses vs. trees. Wildlife choose habitat and food in a much more specific way. Dispersing grizzly bears do not view a patch of stunted quaking aspen in the same way they view a patch of huckleberries, serviceberries, or chokecherries. Similarly, in the autumn, migratory waxwings find large caloric differences between juniper berries and the grasses this unique shrub may be labeled as in current landcover maps. The micro-placement of these shrubs on the landscape influences day-to-day wildlife movements perhaps more than any other single variable.

What are the goals of the project?

We are prioritizing shrub species for mapping based on two criteria; 1) Importance to sensitive wildlife populations, e.g. grizzly bears, and 2) efficacy of mapping a species accurately following initial pilots. We will then begin by collecting location data for the highest priority species and summarize aerial imagery, satellite imagery, and radar-derived variables to describe each species’ unique signature. Half of the location data will be used to train the computer using a machine-learning algorithm to detect and predict our priority species, and half will be used to test our prediction. We will map the two highest priority berry-producing shrub species at 1-meter resolution, scaling from site to landscape across the Northern Rocky Mountain Front.