Thermodynamic and metabolic effects on the scaling of production and population energy use

Ernest, S. K. Morgan; Enquist, Brian J.; Brown, James H.; Charnov, Eric L.; Gillooly, James F.; Savage, Van M.; White, Ethan; Smith, Felisa A.; Hadly, Elizabeth A.; Haskell, John P.; Lyons, S. Kathleen; Maurer, Bill; Niklas, Karl J.; Tiffney, Bruce H.

doi:10.1046/j.1461-0248.2003.00526.x

Cited by 221 publications

(221 citation statements)

References 38 publications

Supporting

Mentioning

215

Contrasting

Order By: Relevance

“…In this vein, traits linked to energy and matter demands, such as growth rate, feeding strength or body size [78][79][80][81][82][83], seem most promising in order to achieve a synthesis of BEF relationships in interaction networks. Ultimately, energetic and matter constraints are the primary currencies that link biodiversity to ecosystem functions in real ecosystems [14].…”

Section: Resultsmentioning

confidence: 99%

Biodiversity and ecosystem functioning in dynamic landscapes

Brose

Hillebrand

2016

Phil. Trans. R. Soc. B

164

165

View full text Add to dashboard Cite

One contribution of 17 to a theme issue 'Biodiversity and ecosystem functioning in dynamic landscapes'. The relationship between biodiversity and ecosystem functioning (BEF) and its consequence for ecosystem services has predominantly been studied by controlled, short-term and small-scale experiments under standardized environmental conditions and constant community compositions. However, changes in biodiversity occur in real-world ecosystems with varying environments and a dynamic community composition. In this theme issue, we present novel research on BEF in such dynamic communities. The contributions are organized in three sections on BEF relationships in (i) multi-trophic diversity, (ii) non-equilibrium biodiversity under disturbance and varying environmental conditions, and (iii) large spatial and long temporal scales. The first section shows that multi-trophic BEF relationships often appear idiosyncratic, while accounting for species traits enables a predictive understanding. Future BEF research on complex communities needs to include ecological theory that is based on first principles of species-averaged body masses, stoichiometry and effects of environmental conditions such as temperature. The second section illustrates that disturbance and varying environments have direct as well as indirect (via changes in species richness, community composition and species' traits) effects on BEF relationships. Fluctuations in biodiversity (species richness, community composition and also trait dominance within species) can severely modify BEF relationships. The third section demonstrates that BEF at larger spatial scales is driven by different variables. While species richness per se and community biomass are most important, species identity effects and community composition are less important than at small scales. Across long temporal scales, mass extinctions represent severe changes in biodiversity with mixed effects on ecosystem functions. Together, the contributions of this theme issue identify new research frontiers and answer some open questions on BEF relationships in dynamic communities of real-world landscapes.

show abstract

Section: Resultsmentioning

confidence: 99%

Biodiversity and ecosystem functioning in dynamic landscapes

Brose

Hillebrand

2016

Phil. Trans. R. Soc. B

164

165

View full text Add to dashboard Cite

show abstract

“…Rate of carbon uptake is the rate of gross primary production in autotrophic cyanobacteria, algae, and higher plants, which obtain energy from sunlight, and the rate of gross assimilation in heterotrophic bacteria, fungi, and animals, which obtain energy by consuming living or dead biomass. These uptake rates scale similarly to the metabolic rates of the organisms (17,25), which are usually measured in units of power but can equally well be expressed in units of carbon. Following Eq.…”

Section: Significancementioning

confidence: 99%

Metabolic theory predicts whole-ecosystem properties

Schramski

Dell

Grady

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

127

122

View full text Add to dashboard Cite

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 topdown) 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. metabolic theory | systems ecology | total system throughflow | residence time | cycling I n most ecosystems, energy and materials flow through trophic networks comprised of plant primary producers, animal consumers, and microbial decomposers (Fig. 1). The individual organisms that make up these networks control the storage and flux of energy, carbon, and other materials. Consequently, a theoretical framework that can account for how different kinds of organisms and ecosystems affect fluxes and stores of energy and materials in ecosystems is central to understanding the carbon cycle of the biosphere and to predicting the impacts of humancaused changes in climate, land use, and biodiversity (1-3). Although it has long been recognized that different kinds of organisms play important roles in the processing of energy and materials in ecosystems, existing treatments are incomplete. Most studies have focused on particular trophic levels, such as primary producers or herbivores, specific ecosystem types, such as tropical forest or pelagic marine, or single species, such as top predators or ecosystem engineers (4-14). Still missing is a simple mechanistic theory that can make precise, quantitative predictions based on the mechanistic relationships between traits of the organisms in the different trophic levels and whole-ecosystem properties, such as carbon flux or recycling.Two main t...

show abstract

“…For the predator model, we explore the special case where is proportional to the prey mass-specific metabolic rate u M i (Brown et al 2000;Charnov 2001;Ernest et al 2003) and the prey density exponent d equals the negative of the prey metabolic rate exponent. Thus, total population production rates across prey types remain constant (i.e., energy equivalence) and the exponent term in equation (9a) 1 ϩ d ϩ u equals zero (Farlow 1976;Damuth 1981;Peters 1983).…”

Section: Model Of Animal Densitymentioning

confidence: 99%

The Scaling of Abundance in Consumers and Their Resources: Implications for the Energy Equivalence Rule

Carbone

Rowcliffe

Cowlishaw

et al. 2007

The American Naturalist

View full text Add to dashboard Cite

The negative scaling of plant and animal abundance with body mass is one of the most fundamental relationships in ecology. However, theoretical approaches to explain this phenomenon make the unrealistic assumption that species share a homogeneous resource. Here we present a simple model linking mass and metabolism with density that includes the effects of consumer size on resource characteristics (particle size, density, and distribution). We predict patterns consistent with the energy equivalence rule (EER) under some scenarios. However, deviations from EER occur as a result of variation in resource distribution and productivity (e.g., due to the clumping of prey or variation in food particle size selection). We also predict that abundance scaling exponents change with the dimensionality of the foraging habitat. Our model predictions explain several inconsistencies in the observed scaling of vertebrate abundance among ecological and taxonomic groups and provide a broad framework for understanding variation in abundance.Keywords: population density, diet, allometry, energy equivalence rule.Understanding the relationship between the abundance of organisms and their resources is a key challenge in ecology (Brown 1995;Gaston and Blackburn 2000). One of the most widely used measures of abundance is population density (McNab 1963;Damuth 1981;Peters and Raelson 1984;Lindstedt et al. 1986;Silva et al. 2001 extensive empirical evidence for negative scaling of species population density in relation to body size (Damuth 1987;Duarte et al. 1987;Enquist et al. 1998). Many have also found support for invariance in population energy use across taxa within a trophic level (Damuth 1981(Damuth , 1998Enquist et al. 1998;Ackerman et al. 2004), a phenomenon known as the energy equivalence rule (EER; Nee et al. 1991). However, we still have a poor understanding of how these relationships emerge given the complexity of interactions among members of ecological communities. Many previous theoretical frameworks used to predict density do not take into account the characteristics of the resources, including particle size and availablity (Damuth 1987;Bohlin et al. 1994;Enquist et al. 1998;Carbone and Gittleman 2002;Haskell et al. 2002;Jetz et al. 2004). Most species within communities do not share common resources: consumers exploit different resources according to their ecological function (diet strategy and trophic level), body size, and phylogeny (Demment and Van Soest 1985;Vezina 1985;Shine 1991;Illius and Gordon 1992;Carbone et al. 1999;Schmid et al. 2000). Thus, in order to fully understand patterns in animal abundance, we need to understand the scaling of population density not only in relation to metabolic rate (resource need) but also in relation to the characteristics of the resources (particle size, distribution, and availability; Schmid et al. 2000).Here we develop a simple model of the scaling of animal abundance (measured as population density) in relation to the scaling of resource needs (metabolic rate) based on...

show abstract

Thermodynamic and metabolic effects on the scaling of production and population energy use

Cited by 221 publications

References 38 publications

Biodiversity and ecosystem functioning in dynamic landscapes

Biodiversity and ecosystem functioning in dynamic landscapes

Metabolic theory predicts whole-ecosystem properties

The Scaling of Abundance in Consumers and Their Resources: Implications for the Energy Equivalence Rule

Contact Info

Product

Resources

About