COS 30-1
Experimental evidence for the time-area-energy hypothesis of biodiversity

Tuesday, August 11, 2015: 8:00 AM
338, Baltimore Convention Center
David W. Armitage, Department of Integrative Biology, University of California Berkeley, Berkeley, CA

Proposed drivers of regional variation in biodiversity are commonly intractable to experimental manipulation. The time-area-productivity hypothesis posits that a bioregion’s productivity-scaled spatial extent integrated over evolutionary time positively covaries with its modern diversity. This hypothesis contrasts with a majority of observational studies, which typically make use of contemporary “snapshots” of environmental factors as drivers of diversity. I tested the explanatory utility of time-integrated area and productivity compared to modern “snapshots” of these factors in explaining the extant diversity of a radiating lineage. I accomplished this using a model system for experimental adaptive radiation— the bacterium Pseudomonas fluorescens SBW25. I initiated hundreds of independent adaptive radiations under culture conditions spanning a variety of productivities, spatial extents, and temporal extents. Diversity was estimated using the frequencies of ancestral and derived colony morphotypes growing on agar plates.


Time-integrated productivity was the best predictor of extant phenotypic diversity and richness, and combined with temporal stability explained over 72% of the variance in diversity among cultures. In contrast, “snapshots” of modern environments at the time of sampling were not useful predictors of diversity patterns. These results were best explained by marked variation in population growth parameters under different productivity treatments. These findings provide the first experimental support for the time-area-productivity hypothesis as a putative driver of regional variation in biodiversity. Further, these results confirm that modern-day ecosystem metrics (e.g., area, productivity, temperature) are at best proxies for explaining extant diversity patterns. At worst, these variables can mislead analyses on purported drivers of biodiversity.