Effects of vehicle traffic on space use and road crossings of caribou in the Arctic [2024 INV#WO0000000110111]
Description
Assessing the effects of industrial development on wildlife is a key objective of managers and conservation practitioners. However, wildlife responses are often only investigated with respect to the footprint of infrastructure, even though human activity can strongly mediate development impacts. In Arctic Alaska, there is substantial interest in expanding energy development, raising concerns about the potential effects on barren-ground caribou (Rangifer tarandus granti). While caribou generally avoid industrial infrastructure, little is known about the role of human activity in moderating their responses, and whether managing activity levels could minimize development effects. To address this uncertainty, we examined the influence of traffic volume on caribou summer space use and road crossings in the Central Arctic Herd within the Kuparuk and Milne Point oil fields on the North Slope of Alaska.
Detailed example
Prediction of liquefaction potential at input site, as it compares to existing case history dataset.
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
Expected benefit
gradient-boosted machine learning models to predict hourly traffic volumes for road segments across the study and generalized additive models (GAMs) to assess effects of traffic volume on caribou fine-scale summer movements
Controls / human review
ATO: No; PIA: Not published
Data needed
This use case is being developed on existing enterprise data and analytics platforms within the agency rather than procuring additional platforms or SaaS to operate.