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.