A test of the maximum power hypothesis along an elevational gradient in the Luquillo Mountains of Puerto Rico

TitleA test of the maximum power hypothesis along an elevational gradient in the Luquillo Mountains of Puerto Rico
Publication TypeBook Chapter
Year of Publication2013
AuthorsHarris, NL, Hall, CAS, Lugo, AE
Book TitleEcological Bulletins 54: Ecological gradient analyses in a tropical landscape
PublisherJohn Wiley & Sons
Accession NumberLUQ.1109
Keywordselevational gradient, Luquillo experimental forest, power, tropical forestry

The maximum power principle predicts that maximum transformation of available energy into useful work occurs when a system operates at an intermediate rate and efficiency. This relation is apparent in everyday situations as we shift gears to keep near the middle of each gear range when we accelerate an automobile, or operate chain saws and other machines at a load about half their stalling rate. We tested the validity of the maximum power principle in a complex natural system by quantifying patterns of photosynthesis and respiration – an ecosystem’s energy currency – along an elevation gradient in a subtropical forest of Puerto Rico. This mountain system was a useful proxy for testing the hypothesis over broader climatic gradients elsewhere. Our results indicate that metabolic rates (defined as gross primary productivity) decrease up the gradient, efficiency (defined as the ratio of net to gross primary productivity) increases up this gradient, and power (defined as net primary productivity, or the amount of useful energy produced within a given ecosystem per unit time) is maximum near the midpoint of the gradient where rate and efficiency are intermediate. These observations are non-trivially consistent with the maximum power principle and support a scalable, energy-based definition of evolutionary fitness. Given a set of environmental forcing functions in a given location, those individuals (or populations or ecosystems) that optimize the trade-off between metabolic rate and efficiency to achieve maximum power will be most fit. As environmental conditions change over the long term, this rate vs efficiency optimum will shift and those that are able to achieve maximum power in the new environment will be favored over those that are maximizing power for the old environment. We think that this net energy-as-fitness view allows for a richer series of possibilities for testing the consequences of natural selection.