Akaike Information Criterion, with finite sample size correction (AICc), for distribution models of limber pine trained at the local extent using six different combinations of bioclimatic variables.

<p>Akaike Information Criterion, with finite sample size correction (AICc), for distribution models of limber pine trained at the local extent using six different combinations of bioclimatic variables.</p

Predicted probability of current (1981–2010) limber pine occurrence in Rocky Mountain National Park.

<p>MaxEnt models trained at two spatial extents: A) rangewide, and B) at the local extent considering only those areas where limber pine is the dominant vegetation class.</p

Future projections (2035–2100) of the distribution of limber pine in Rocky Mountain National Park.

<p>MaxEnt models trained at two spatial extents (rangewide and local) and projected under two future climate scenarios reflecting different GHG concentration pathways (RCP 4.5 and 8.5). Distributional summaries calculated from probability of occurrence maps rendered binary by the model thresholds reported in parentheses: A) total area; B) percentage area, within current observed area where limber pine is dominant; C) mean elevation; D) percentage elevational range, within current observed elevational range where limber pine is dominant; E) core patch index, and F) percentage core area, within current observed core area where limber pine is dominant.</p

Examples of field plots containing limber pine in Rocky Mountain National Park, according to photos collected as part of the vegetation inventory[33].

<p>A) Plot number 318, representative of the subalpine (dominant) limber pine map class. B) Plot number 303, representative of the subalpine (dominant) limber pine map class. C) Plot number 506, representative of the herbaceous upland alpine fellfield map class. D) Plot number 311, representative of the lodgepole pine – low elevation <9500 ft map class.</p

Capital indicator labels, descriptions, units of measurement, summary, and source.

<p>^a Standard error as reported for the AgSurf survey data only</p><p>^b Indicates time-invariant data (i.e. varies by region only)</p><p>^c Australian Bureau of Statistics</p><p>^d Bureau of Meteorology</p><p>^e Australian Soil Resources Information System</p><p>^f Geoscience Australia</p><p>^g Numerical Terradynamic Simulation Group, University of Montana</p><p>Capital indicator labels, descriptions, units of measurement, summary, and source.</p

Results of the final fixed effects regression analysis.

<p>Results of the final fixed effects regression analysis.</p

Sowing windows and cultivars used in APSIM modeling.

<p>Sowing windows and cultivars used in APSIM modeling.</p

Wheat yield and adaptive capacity indices.

<p>Actual and expected wheat yield indices and adaptive capacity index for each region from 1991–2010.</p

Adaptive capacity index for wet and dry years.

<p>Mean and standard deviation of adaptive capacity index by region for all years, wet years (where expected WYI^Exp ≥ 1), and dry years (where expected <i>WYI</i>^<i>Exp</i> < 1). * indicates significant difference in ACI between dry and wet years (<i>α</i> = 0.1).</p

Study area.

<p>Location of the 12 ABARES regions in the wheat-sheep zone of Australia.</p