<p>Boosted Regression Trees fitted model showing the relative importance of influential factors of undercover cropland area calculated from field estimated percent cover.</p
Regression equations for the relationship between percentages of tree cover and stem density (stems ...
<p>Relative influence of each of the variables (climate, land cover and physical) on each of the fou...
<p>The most likely explanatory variables are shown in bold (based on model-average estimate being di...
<p>Undercover cropland area predicted from most influential topographic factors identified using Boo...
<p>Influential factors of undercover cropland area (ha) calculated from field estimated percent cove...
<p>Summary of the relative contributions (%) of predictor variables (average Bray-Curtis values, tre...
Generalized additive models were not used as the number of distribution records was insufficient for...
Relative influence of predictor variables in models of climatic suitability for boosted regression t...
<p>Final regression model of drought impact patch hotspots (2-km kernel density) as a function of en...
<p>Partial dependence plots showing fitted functions of each of the top five influential variables c...
<p>Boosted regression tree partial dependency plots show the response form of average taxa tolerance...
<p>Boosted regression tree partial dependency plots show the response form of average taxa tolerance...
<p>Relative influence of each environmental variable from three categories (physical, land use and c...
<p>The graphs show Observed vs. Fitted tree occurrences (A) and smoothed partial contributions withi...
The worldwide demand for food has been increasing due to the rapidly growing global population, and ...
Regression equations for the relationship between percentages of tree cover and stem density (stems ...
<p>Relative influence of each of the variables (climate, land cover and physical) on each of the fou...
<p>The most likely explanatory variables are shown in bold (based on model-average estimate being di...
<p>Undercover cropland area predicted from most influential topographic factors identified using Boo...
<p>Influential factors of undercover cropland area (ha) calculated from field estimated percent cove...
<p>Summary of the relative contributions (%) of predictor variables (average Bray-Curtis values, tre...
Generalized additive models were not used as the number of distribution records was insufficient for...
Relative influence of predictor variables in models of climatic suitability for boosted regression t...
<p>Final regression model of drought impact patch hotspots (2-km kernel density) as a function of en...
<p>Partial dependence plots showing fitted functions of each of the top five influential variables c...
<p>Boosted regression tree partial dependency plots show the response form of average taxa tolerance...
<p>Boosted regression tree partial dependency plots show the response form of average taxa tolerance...
<p>Relative influence of each environmental variable from three categories (physical, land use and c...
<p>The graphs show Observed vs. Fitted tree occurrences (A) and smoothed partial contributions withi...
The worldwide demand for food has been increasing due to the rapidly growing global population, and ...
Regression equations for the relationship between percentages of tree cover and stem density (stems ...
<p>Relative influence of each of the variables (climate, land cover and physical) on each of the fou...
<p>The most likely explanatory variables are shown in bold (based on model-average estimate being di...
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