FIA and environmental data to model tree range boundaries and potential changes in suitable habitats under climate change

Background/Question/Methods

Tree species Importance Values (IV) were derived from FIA basal area and the number of stems reported at plot locations and statistically correlated to 38 environmental variables (climate, elevation, land cover, and soil) with the DISTRIB model. Using current climate conditions and three future General Circulation Models with two CO₂ scenarios for the end of the century, 134 eastern US tree species were modeled for suitable habitat. The output, with a 20-km resolution, interpolates habitat suitability where FIA hasn’t sampled producing a continuous grid of potential abundance. However, for certain analyses a well-defined polygon delineating the species core range may be necessary. Therefore, using the core area, a continuous region of high to low modeled habitat, a semi-automated method was developed to create Generalized Species Boundaries (GSB). The process uses R statistical algorithms and a series of GIS scripts to delineate boundaries by first identifying grid cells that makeup the core area and then with FIA records and other ancillary data the boundary is manually adjusted. The final smoothed GSBs were evaluated by the percentage of FIA presence and DISTRIB IVs they captured in addition to comparing areal statistics to historical ranges of the species’ extent.

Results/Conclusions

Model reliability for DISTRIB output was high, medium, and low for 55, 48, and 31 species respectively. Modeled current suitable habitat for 6 to 6617 20-km grid cells contained FIA records, with <1-44% of the modeled output being suitable and not sampled. Areal statistics for the GSBs indicate that most capture an average of 85% of FIA presence even though the area is smaller than the historical range (i.e., Little’s ranges). Additionally, the GSB’s area beyond the historical range was calculated, and 98 species have between 2-95% of the GSB extending beyond the historical range. Utilizing extensive inventories, such as, FIA records and continuous environmental data sets are ideal for regression tree modeling, where relatively few samples (~100,000 FIA plots) can be used to predict suitable habitat. Models for current and future climate scenarios allow researchers to examine potential changes in species habitat and assess regions vulnerable to losses in species abundance. GSBs are suited for analysis of colonization potential out from the core area and migrational shifts and could be used to identify outlier populations.