Table 1 Landscape variables. A summary of all variables by category rescaled to 1 km2 and used in the prediction of wolverine genetic connectivity. Because of correlation among variables in the same categories (r > 0.3), composite climate and human disturbance variables were also created using the indicated variables in a Principal Components Analysis (PCA). The Hypothesis column indicates whether an increase in a given variable is expected to result in an increase (+) or a decrease (-) in genetic connectivity. TPI = Topographic Position Index; TRI = Topographic Ruggedness Index; HF = Human footprint; Dstrb = Disturbance Category; Topo = Topography Category; For = Forest Category.

From: Genetic connectivity of wolverines in western North America

Variable

Category

Source

Climate PCA

HF PCA

Hypo-thesis

Description

Snow Days

Climate

NDVI1

 

+

Number of days with snow cover from NDVI NoData values (Fig. S5)

SWE

Climate

CHELSA2

 

+

30-year average (1981–2010) of snow-water equivalent with permanent water bodies removed

Temp

Climate

CHELSA2

 

-

30-year average (1981–2010) of annual maximum temperature

Building density

Dstrb

Micro-soft3

 

-

From all buildings in North America with point density tool in ARCGIS

Human footprint 1

Dstrb

NASA

 

-

8 anthropogenic variables: built-up environment, population density, electric power infrastructure, crop lands, pasture lands, roads, railways, navigable waterways

SEDAC4

Human footprint 2

Dstrb

Earth Systems Science Data5

 

-

14 anthropogenic variables: urban, crop land, grazing, mining, energy production (oil and gas, renewable), roads, railways, power lines, electrical infrastructure, logging, human intrusion, reservoirs, air pollution

HWY All

Dstrb

Street

 

-

Major Canadian and US Highways

Maps6

HWY 1

Dstrb

Street

  

-

North or south of Trans-Canada Highway 1

Maps6

Lights

Dstrb

NASA7

 

-

Nighttime lights

DEM

Topo

USGS8

  

+

30-m digital elevation model

TPI

Topo

USGS8

  

+

Topographic position index: From DEM using R terrain() in ‘raster’

TRI

Topo

USGS8

  

+

Terrain ruggedness index: From DEM using R terrain() in ‘raster’

Forest cover

For

NALCMS9

  

+

Proportion of cells in window of conifer or mixed forest type, 30-m

Forest edge

For

NALCMS9

  

+

Proportion of 30-m cells in window where conifer/mixed forest was adjacent to non-forested habitat

  1. 1https://modis.gsfc.nasa.gov. 2https://chelsa-climate.org. 3https://www.github.com/Microsoft/USBuildingFootprints. 4https://sedac.ciesin.columbia.edu/data/set/wildareas-v3-2009-human-footprint. 5https://zenodo.org/record/3963013#.YAG7DuhKiUk. 6https://openstreetmap.org. 7https://www.earthdata.nasa.gov/learn/backgrounders/nighttime-lights. 8https://www.usgs.gov/the-national-map-data-delivery/gis-data-download. 9http://www.cec.org/north-american-land-change-monitoring-system/.