title: Metabolic theory predicts whole-ecosystem properties.
abstract: Understanding the effects of individual organisms on material cycles and energy fluxes within ecosystems is central to predicting the impacts of human-caused changes on climate, land use, and biodiversity. Here we present a theory that integrates metabolic (organism-based bottom-up) and systems (ecosystem-based top-down) approaches to characterize how the metabolism of individuals affects the flows and stores of materials and energy in ecosystems. The theory predicts how the average residence time of carbon molecules, total system throughflow (TST), and amount of recycling vary with the body size and temperature of the organisms and with trophic organization. We evaluate the theory by comparing theoretical predictions with outputs of numerical models designed to simulate diverse ecosystem types and with empirical data for real ecosystems. Although residence times within different ecosystems vary by orders of magnitude-from weeks in warm pelagic oceans with minute phytoplankton producers to centuries in cold forests with large tree producers-as predicted, all ecosystems fall along a single line: residence time increases linearly with slope = 1.0 with the ratio of whole-ecosystem biomass to primary productivity (B/P). TST was affected predominantly by primary productivity and recycling by the transfer of energy from microbial decomposers to animal consumers. The theory provides a robust basis for estimating the flux and storage of energy, carbon, and other materials in terrestrial, marine, and freshwater ecosystems and for quantifying the roles of different kinds of organisms and environments at scales from local ecosystems to the biosphere.
authors.affiliation: College of Engineering, University of Georgia, Athens, GA 30602; jschrams@uga.edu jhbrown@unm.edu.
authors.forename: John R
authors.initials: JR
authors.lastname: Schramski
authors.affiliation: Systemic Conservation Biology, Department of Biology, Georg August University, Göttingen 37073, Germany; National Great Rivers Research and Education Center, Alton, IL 62024;
authors.forename: Anthony I
authors.initials: AI
authors.lastname: Dell
authors.affiliation: Department of Biology, University of New Mexico, Albuquerque, NM 87131; and.
authors.forename: John M
authors.initials: JM
authors.lastname: Grady
authors.affiliation: School of Biological Sciences, University of Reading, Reading RG6 6AS, United Kingdom.
authors.forename: Richard M
authors.initials: RM
authors.lastname: Sibly
authors.affiliation: Department of Biology, University of New Mexico, Albuquerque, NM 87131; and jschrams@uga.edu jhbrown@unm.edu.
authors.forename: James H
authors.initials: JH
authors.lastname: Brown
mesh_terms: D002244:Carbon / Q000378:metabolism; D057486:Carbon Cycle; D003198:Computer Simulation; D017753:Ecosystem; D006801:Humans; D016014:Linear Models; D008660:Metabolism; D008954:Models, Biological; D009584:Nitrogen / Q000378:metabolism; D009716:Numerical Analysis, Computer-Assisted; D015203:Reproducibility of Results; D013997:Time Factors
chemical_list: D002244:Carbon; D009584:Nitrogen
keywords: cycling; metabolic theory; residence time; systems ecology; total system throughflow