Abstract

The zone of influence (ZOI) is the area in the vicinity of industrial development where avoidance by caribou Rangifer tarandus or other wildlife species is observed. Here we examine ZOI around two diamond mines in the Northwest Territories (NWT), Canada from 1998 to 2017. In this paper, we further develop segmented/piecewise regression methods to analyze collar location and aerial survey data with a focus on yearly trend in ZOI for the Bathurst caribou herd. A base habitat model was initially formulated to account for habitat selection around mines followed by estimation of ZOI distance and magnitude. Seasonal ranges of the herd contracted from 2009 to 2017 due to decline in herd size, which influenced the distribution of caribou relative to the mines as well as larger scale habitat selection. Models with year-specific estimates of ZOI were more supported than models assuming a constant ZOI across years. Significant ZOI's occurred for aerial survey and/or collar data in 9 of 15 years from 2003 to 2017 when both mines were in full operation, with ZOI distances ranging from 6.1 to 18.7 km. Non-significant ZOI's occurred from 1998 to 2002 before both mines were fully operational. Caribou were attracted to lakes in drought years which significantly influenced distribution relative to mines as well as the magnitude of the ZOI detected. The ZOI extent averaged 7.2 km (CI = 3.8–10.5) when standardized for mean levels of drought. Our analysis suggests that ZOI varies both annually and spatially because of the location of mines relative to habitat selection and seasonal range size. Therefore, exacting analysis methods that account for these sources of variation are required for robust ZOI estimates. Segmented regression methods have become available in the R statistical program that allow flexible ZOI estimation for implementation of the methods in this study for caribou or other wildlife species.

Highlights

  • A model with yearly ZOI estimates with distance from perimeter of mine footprint was most supported

  • When added to the trend and drought models, data type was not a significant predictor of effect size. These results suggest an overall reduction in ZOI effect size which was negatively influenced by drought level

  • ZOI estimates when drought level was higher compared to years with lower levels of drought (Fig. 6)

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Summary

Objectives

The objective of our research was to estimate yearly ZOI using both aerial survey and collar data to estimate yearly trends in ZOI distance and magnitude for the Bathurst herd and explore climatic factors affecting trends in ZOI

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