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Diverse tropical forests defy metabolic ecology models

ta from 14 sites around the world --over 2 million trees--and it just did not hold up anywhere," continues Muller-Landau.

The CTFS team subsequently tested other metabolic ecology-based predictions relating tree size to growth and mortality against data from 10 CTFS forests, and found that those were not supported either.

"The predictions of metabolic ecology were wrong in fundamental ways, and no one had noticed before because few datasets spanned the range from saplings to large trees. Most impressive was the consistency in the big discrepancies between observation and prediction, even in very different forests," articulates coauthor Richard Condit, STRI Staff Scientist, "For instance, diameter distribution always deviated by having far fewer large trees than the -2 slope predicts."

Shedding light on the process

The CTFS team did not stop at merely demonstrating that metabolic ecology failed to explain tropical forest structure '" they examined what alternative models might do better. Organisms live within the limits of their environment. Maybe by modifying the metabolic ecology model to include light as a limiting resource that varies with tree size, the predictions could be improved. The necessary light data were available from only one site, and, in that case, observed growth and mortality patterns were consistent with predictions. Similarly, tree size distributions corresponded more closely to a model based on demographic equilibrium theory that incorporated differences in growth and mortality among sites.

What next?

The results of these two studies clearly demonstrate that there are both qualitative similarities and significant quantitative differences in forest structure among tropical sites. This complexity defies simple characterization '" its explanation requires consideration of the diversity of environmental conditions and species traits in tropical forests, and complex feedbacks and interactions among spe
'"/>

Source:Smithsonian Tropical Research Institute


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