At the regional and continental scale, ecologists have theorized that spatial variation in
biodiversity can be interpreted as a response to differences in climate. To test this theory,
we assumed that ecological constraints associated with current climatic conditions (2000-
2004) might best be expressed through some measure of gross primary production (GPP)
derived with remotely sensed data. To evaluate current patterns in tree diversity across
the contiguous U.S.A. we acquired information on tree composition from the United
States Forest Inventory and Analysis program recorded on more than 174,000 survey
plots distributed within 2693 cells of 1000 km2. Our forest productivity measures varied
from simple vegetation indices acquired at 16-day intervals with MODIS (MODerate
resolution Imaging Spectro-radiometer), to 8 and 10-day GPP products derived with
minimal climatic data (MODIS) and SPOT (Systeme Pour l'Observation de la Terre-
Vegetation), to 3-PGS (Physiological Principles Predicting Growth with Satellites) that
required both climate and soil data. Across the contiguous U.S.A., modeled predictions of
productivity accounted for between 51% and 77% of the recorded spatial variation in tree
diversity, which ranged from 2 to 67 species per hectare. Only 3-PGS predictions fit the
theorized unimodal function by recognizing highly productive forests in the Pacific
Northwest that support limited tree diversity. Other models predicted a continuous steep
rise in tree diversity with increasing productivity, and did so with generally better or near
equal precision with fewer data requirements.
