Publication | Closed Access
Modeling contemporary climate profiles of whitebark pine (Pinus albicaulis) and predicting responses to global warming
18
Citations
0
References
2006
Year
Unknown Venue
EngineeringClimate VariablesForestryClimate ModelingWhitebark PineForest ProductivityPlot LocationEarth ScienceSocial SciencesVegetation-atmosphere InteractionsBiogeographyContemporary Climate ProfilesForest MeteorologyClimate ChangeForest HealthSpline Climate ModelGeographyGlobal WarmingForest Health MonitoringClimate Change EffectForest BiologyClimate DynamicsClimatologyGlobal ClimateClimate ModellingForest Inventory
The Random Forests multiple regression tree was used to develop an empirically-based bioclimate model for the distribution of Pinus albicaulis (whitebark pine) in western North America, latitudes 31° to 51° N and longitudes 102° to 125° W. Independent variables included 35 simple expressions of temperature and precipitation and their interactions. These climate variables were derived from a spline climate model that provides point estimates (latitude, longitude, and altitude). The analysis used presence-absence data from more than 119,000 plot locations largely from USDA Forest Inventory and Analysis. Of these plots, 2738 contained whitebark pine. Climate estimates were made for each plot location and assembled into 10 data sets containing all of the plots where whitebark pine was present at a proportion of 40%. The remaining 60% were randomly selected from the database.