Labadie, Guillemette;
Hardy, Clément;
Boulanger, Yan;
Vanlandeghem, Virginie;
Hebblewhite, Mark;
Fortin, Daniel
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2023-03-01
<p>Datasets generated and analyzed within the study area located in the Côte-Nord region of Québec, Canada. To identify species-specific movement rules that were implemented in the IBM, we used empirical data collected for caribou, moose, and wolves over the study area.</p>
<p>"DataFinal_SSF_Species_season.csv" (6 files) were used to develop Step Selection Functions for caribou, moose, and wolves to assess habitat selection. <span lang="EN-CA">SSFs</span><span lang="EN-CA"> were estimated from data for the real animals and provide the relative probability of selection among a set of options based on the comparison of observed and random steps (i.e., the linear segment between successive locations at 8-h interval) using conditional</span><span lang="EN-CA"> logistic regression </span><span lang="EN-CA">(Fortin et al. 2005). Details on GPS data and SSF models can be found in the article in Appendix S1: Section S2. </span></p>
<p>SSFs compare resource characteristics of observed (scored 1) and random (scored 0) locations presented in column case. Habitat characteristics (columns conif_dense, conif_open, mixed, open, other, fire010, fire1020, fire20, cut010, cut1020, cut20) was extracted from the Canadian National Forest Inventory (NFI) forest cover maps. Land cover maps were updated every year by adding roads, recent (<5 years), regenerating (6–20 years) and old (21–50 years) cutblocks/fires based on information provided annually by local forestry companies and from the Canadian National Fire Database (CNFDB). Columns dist0_0.25, dist0.25_0.50, dist0.5_1.00, dist1.00_1.5, and dist1.5 are a set of 5 dichotomous covariables representing the classes of distance to the nearest road (i.e., 1) ≤250 m, 2) 251–500 m, 3) 501–1000 m, 4) 1001–1500 m and 5) >1500 m as the reference category).</p>
<p>"DataFinal_IBM_Caribou_Season.csv" (2 files) corresponded to the IBM outputs with the proportion of caribou agent killed (Prop.Caribou_killed, number of caribou killed/total number of caribou), in function of the different scenarios (CC,LUC,Year,Season,Scenario) and the response (Behavioral-Numerical responses or Behavioral response). The columns Prop.CutsRoads, Prop.Fire, Prop.Broadleaf, Homogenization, Isolation correspond to the different variable we tested to predict the cumulative impact of anthropogenic disturbance and climate change. To explore how changes in forest structure and composition impacted the proportion of caribou killed, we used the proportion of areas disturbed by cuts and roads (Prop.CutsRoads), burned areas (Prop.Fire), and landscape characteristics, such as the proportion of deciduous vegetation (Prop.Broadleaf), landscape homogenization (Homogenization) and isolation (Isolation) of mature conifer stands.</p>
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