Soil Texture: This map was created by joining polygons from the Land Potential Database of Canada with corresponding data in an attribute table called Soil Inventory. The data joined included characteristics of soil texture, with the categories “Clayey,” “Sandy,” “Loamy,” and blank areas which appear to mostly correlate with densely glaciated, mountainous regions (such as the bottom left corner) or lakes (Kluane Lake is the little forked shape in bottom left). The layer was then converted to raster and reclassified into five classes of ascending desirability (shown by darker brown) to prepare it for the weighted overlay analysis.

Proximity to Water: This map was created from a line map of the drainage networks in the Yukon. A path distance analysis was run with a base raster of derived from a polygon of the Yukon Territory, and the distance map was reclassified into five classes with the darkest regions showing areas close to some kind of river. Unfortunately, time and metadata constraints meant I couldn't find a way to separate major rivers from creeks. This will be further addressed in the discussion section.

Proximity to Roads: This map was created similarly to the water map, with major roads as the network from which path distance was calculated. There was a limit to the extent of the calculated map, and I'm not sure where this arose from. I redid the analysis many times and made sure to use the Yukon territory as the base raster, and did not assign a maximum distance, but there continued to be a limit. This will also be discussed in the discussion section.

Effective Growing Degree Days Reference Map: This map reflects effective growing degree days based on the EGDDs calculated by NRCAN. To build it, I joined the ecodistrict polygons to the EGDD attribute table, used a symbology of quantities, and assigned 5 discrete classes based on the classes described in the background section.

Slope:This map was created from a 90m DEM of the Yukon Territory. Slopes were calculated with Spatial Analyst and reclassified into five classes according to flat slopes (0-5º), moderately flat slopes (5-10º), moderate slopes (10-15º), moderately steep slopes (15-25º), and very steep slopes (25º-89.9). The un-equal interval is a result of the functionality of steep slopes: past a certain point they will be unlikely to be stable and will be equally difficult to work with whether they are at 35º or 75º. Therefore I grouped all of the higher slopes into the single lowest class.

Effective Growing Degree Days Present Day:  Each of the following maps were created in the following way:

 Using Excel, I started with mean monthly temperature values for each ecodistrict. I then built calculated tables using If/Then statements that summed all values above 5º for each month, multiplied those values by 30 to estimate the number of days in each month, and multiplied that value by 1.18 in order to obtain Effective GDD for the latitude around Whitehorse (info from Infarmation bulletin). For the 2050 and 2100 values, I first recalculated the mean monthly temperature tables to be 3º higher and 6º higher, respectively, and then carried out the same analysis. Temperature increases are based on this map for 2050 and this map for 2100 .

I also performed a minor error analysis to show that the majority of the calculated EGDD Present Day values underestimated rather than overestimated EGDD (which is good given that more EGDD is better, and an underestimate won't tend to raise false hopes). A graph of this can be found in the discussion section.