# Metabolic theory of ecology

The metabolic theory of ecology (MTE) is an extension of Kleiber's law and posits that the metabolic rate of organisms is the fundamental biological rate that governs most observed patterns in ecology.[1][2] MTE is part of a larger set of theory known as metabolic scaling theory that attempts to provide a unified theory for the importance of metabolism in driving pattern and process in biology from the level of cells all the way to the biosphere.

MTE is based on an interpretation of the relationships between body size, body temperature, and metabolic rate across all organisms. Small-bodied organisms tend to have higher mass-specific metabolic rates than larger-bodied organisms. Furthermore, organisms that operate at warm temperatures through endothermy or by living in warm environments tend towards higher metabolic rates than organisms that operate at colder temperatures. This pattern is consistent from the unicellular level up to the level of the largest animals and plants on the planet.

In MTE, this relationship is considered to be the single constraint that defines biological processes at all levels of organization (from individual up to ecosystem level), and is a macroecological theory that aims to be universal in scope and application.[2][3]

## Theoretical background

Metabolic rate scales with the mass of an organism of a given species according to Kleiber's law where B is whole organism metabolic rate (in watts or other unit of power), M is organism mass (in kg), and Bo is a mass-independent normalization constant (given in a unit of power divided by a unit of mass. In this case, watts per kilogram):

${\displaystyle B=B_{o}M^{3/4}\,}$

At increased temperatures, chemical reactions proceed faster. This relationship is described by the Boltzmann factor, where E is activation energy in electronvolts or joules, T is absolute temperature in kelvins, and k is the Boltzmann constant in eV/K or J/K:

${\displaystyle e^{-{\frac {E}{k\,T}}}}$

While Bo in the previous equation is mass-independent, it is not explicitly independent of temperature. To explain the relationship between body mass and temperature, building on earlier work [4] showing that the effects of both body mass and temperature could be combined multiplicatively in a single equation, the two equations above can be combined to produce the primary equation of the MTE, where bo is a normalization constant that is independent of body size or temperature:

${\displaystyle B=b_{o}M^{3/4}e^{-{\frac {E}{k\,T}}}}$

According to this relationship, metabolic rate is a function of an organism’s body mass and body temperature. By this equation, large organisms have higher metabolic rates (in Watts) than small organisms, and organisms at high body temperatures have higher metabolic rates than those that exist at low body temperatures. However, specific metabolic rate (SMR, in Watts/kg) is given by

${\displaystyle SMR=(B/M)=b_{o}M^{-1/4}e^{-{\frac {E}{k\,T}}}}$

Hence SMR for large organisms are lower than small organisms.

## Controversy over mechanisms and the allometric constant

Researchers disagree about the two main aspects of this theory, the pattern and the mechanism. The primary pattern in question is whether metabolic rate scales to the power of ¾ or ⅔w, or whether either of these can even be considered a universal constant.[5][6] The majority view is currently that ¾ is the correct exponent, but a large minority believe that ⅔ is the more accurate value. In addition to disagreeing about the pattern, researchers also disagree about mechanism. Various authors have proposed at least eight different types of mechanisms that predict an allometric scaling exponent of either ⅔ or ¾. Some of these models make a large number of testable predictions while others are less comprehensive.[5]

Much of the current debate focuses on two particular types of mechanisms.[6] One of these assumes energy or resource transport across the external surface area of three-dimensional organisms is the key factor driving the relationship between metabolic rate and body size. The surface area in question may be skin, lungs, intestines, or, in the case of unicellular organisms, cell membranes. In general, the surface area (SA) of a three dimensional object scales with its volume (V) as SA = cV, where c is a proportionality constant. The Dynamic Energy Budget model is currently the most promising version of these, and it predicts exponents that vary between ⅔ – 1, depending on the organism's developmental stage, basic body plan and resource density [7][8] Smaller organisms tend to have higher surface area to volume ratios, causing them to gain resources at a proportionally higher rate than large organisms. As a consequence, small organisms can have higher volume-specific metabolic rates.

In contrast, the arguments for a ¾ scaling factor are based on resource transport network models,[6] where the limiting resources are distributed via some optimized network to all resource consuming cells or organelles.[1][9] These models are based on the assumption that metabolism is proportional to the rate at which an organism’s distribution networks (such as circulatory systems in animals or xylem and phloem in plants) deliver nutrients and energy to body tissues.[1][10][11] Larger organisms are necessarily less efficient because more resource is in transport at any one time than in smaller organisms: size of the organism and length of the network imposes an inefficiency due to size. It therefore takes somewhat longer for large organisms to distribute nutrients throughout the body and thus they have a slower mass-specific metabolic rate. An organism that is twice as large cannot metabolize twice the energy—it simply has to run more slowly because more energy and resources are wasted being in transport, rather than being processed. Nonetheless, natural selection appears to have minimized this inefficiency by favoring resource transport networks that maximize rate of delivery of resources to the end points such as cells and organelles.[9][10] This selection to maximize metabolic rate and energy dissipation results in the allometric exponent that tends to D/(D+1), where D is the primary dimension of the system. A three dimensional system, such as an individual, tends to scale to the 3/4 power, whereas a two dimensional network, such as a river network in a landscape,tends to scale to the 2/3 power.[9][11][12]

Despite the controversy over the value of the exponent, the implications of this theory might remain true regardless of its precise numerical value.

## Implications of the theory

The metabolic theory of ecology’s main implication is that metabolic rate, and the influence of body size and temperature on metabolic rate, provide the fundamental constraints by which ecological processes are governed. If this holds true from the level of the individual up to ecosystem level processes, then life history attributes, population dynamics, and ecosystem processes could be explained by the relationship between metabolic rate, body size, and body temperature. While different underlying mechanisms[1][8] make somewhat different predictions, the following provides an example of some of the implications of the metabolism of individuals.

### Organism level

Small animals tend to grow fast, breed early, and die young.[13] According to MTE, these patterns in life history traits are constrained by metabolism.[14] An organism's metabolic rate determines its rate of food consumption, which in turn determines its rate of growth. This increased growth rate produces trade-offs that accelerate senescence. For example, metabolic processes produce free radicals as a by-product of energy production.[15] These in turn cause damage at the cellular level, which promotes senescence and ultimately death. Selection favors organisms which best propagate given these constraints. As a result, smaller, shorter lived organisms tend to reproduce earlier in their life histories.

### Population and community level

MTE has profound implications for the interpretation of population growth and community diversity.[13] Classically, species are thought of as being either r selected (where populations tend to grow exponentially, and are ultimately limited by extrinsic factors) or K selected (where population size is limited by density-dependence and carrying capacity). MTE explains this diversity of reproductive strategies as a consequence of the metabolic constraints of organisms. Small organisms and organisms that exist at high body temperatures tend to be r selected, which fits with the prediction that r selection is a consequence of metabolic rate.[2] Conversely, larger and cooler bodied animals tend to be K selected. The relationship between body size and rate of population growth has been demonstrated empirically,[16] and in fact has been shown to scale to M−1/4 across taxonomic groups.[13] The optimal population growth rate for a species is therefore thought to be determined by the allometric constraints outlined by the MTE, rather than strictly as a life history trait that is selected for based on environmental conditions.

Observed patterns of diversity can be similarly explained by MTE. It has long been observed that there are more small species than large species.[17] In addition, there are more species in the tropics than at higher latitudes.[2] Classically, the latitudinal gradient in species diversity has been explained by factors such as higher productivity or reduced seasonality.[18] In contrast, MTE explains this pattern as being driven by the kinetic constraints imposed by temperature on metabolism.[19] The rate of molecular evolution scales with metabolic rate,[20] such that organisms with higher metabolic rates show a higher rate of change at the molecular level.[2] If a higher rate of molecular evolution causes increased speciation rates, then adaptation and ultimately speciation may occur more quickly in warm environments and in small bodied species, ultimately explaining observed patterns of diversity across body size and latitude.

MTE’s ability to explain patterns of diversity remains controversial. For example, researchers analyzed patterns of diversity of New World coral snakes to see whether the geographical distribution of species fit within the predictions of MTE (i.e. more species in warmer areas).[21] They found that the observed pattern of diversity could not be explained by temperature alone, and that other spatial factors such as primary productivity, topographic heterogeneity, and habitat factors better predicted the observed pattern. Extensions of metabolic theory to diversity that include eco-evolutionary theory show that an elaborated metabolic theory can account for differences in diversity gradients by including feedbacks between ecological interactions (size-dependent competition and predation) and evolutionary rates (speciation and extinction) [22]

### Ecosystem processes

At the ecosystem level, MTE explains the relationship between temperature and production of total biomass.[23] The average production to biomass ratio of organisms is higher in small organisms than large ones.[24] This relationship is further regulated by temperature, and the rate of production increases with temperature.[25] As production consistently scales with body mass, MTE provides a framework to assess the relative importance of organismal size, temperature, functional traits, soil and climate on variation in rates of production within and across ecosystems.[23] Metabolic theory shows that variation in ecosystem production is characterized by a common scaling relationship, suggesting that global change models can incorporate the mechanisms governing this relationship to improve predictions of future ecosystem function.

## References

1. ^ a b c d West, G. B., Brown, J. H., & Enquist, B. J. (1997). "A general model for the origin of allometric scaling laws in biology". Science. 276 (7): 122–126. doi:10.1126/science.276.5309.122. PMID 9082983.CS1 maint: Multiple names: authors list (link)
2. Brown, J. H., Gillooly, J. F., Allen, A. P., Savage, V. M., & G. B. West (2004). "Toward a metabolic theory of ecology". Ecology. 85 (7): 1771–89. doi:10.1890/03-9000.CS1 maint: Multiple names: authors list (link)
3. ^ Enquist, B. J., Economo, E. P., Huxman, T. E., Allen, A. P., Ignace, D. D., & Gillooly, J. F. (2003). "Scaling metabolism from organisms to ecosystems". Nature. 423 (6940): 639–642. Bibcode:2003Natur.423..639E. doi:10.1038/nature01671.CS1 maint: Multiple names: authors list (link)
4. ^ Robinson, W. R., Peters, R. H., & Zimmermann, J. (1983). "The effects of body size and temperature on metabolic rate of organisms". Canadian Journal of Zoology. 61 (2): 281–288. doi:10.1139/z83-037.CS1 maint: Multiple names: authors list (link)
5. ^ a b Agutter, P.S., Wheatley, D.N. (2004). "Metabolic scaling: consensus or controversy?". Theoretical Biology and Medical Modelling. 1: 1–13. doi:10.1186/1742-4682-1-13. PMC 539293. PMID 15546492.CS1 maint: Multiple names: authors list (link)
6. ^ a b c Hirst, A. G., Glazier, D. S., & Atkinson, D. (2014). "Body shape shifting during growth permits tests that distinguish between competing geometric theories of metabolic scaling". Ecology Letters. 17 (10): 1274–1281. doi:10.1111/ele.12334. PMID 25060740.CS1 maint: Multiple names: authors list (link)
7. ^ Kooijman, S. A. L. M. "Energy budgets can explain body size relations". Journal of Theoretical Biology. 121 (3): 269–282. doi:10.1016/S0022-5193 (inactive 2019-07-13).
8. ^ a b Kooijman, S. A. L. M. (2010). "Dynamic energy budget theory for metabolic organisation". Cambridge University Press, Cambridge.
9. ^ a b c Banavar, J. R., Maritan, A., & Rinaldo, A. (1999). "Size and form in efficient transportation networks". Nature. 399 (6732): 130–132. Bibcode:1999Natur.399..130B. doi:10.1038/20144. PMID 10335841.CS1 maint: Multiple names: authors list (link)
10. ^ a b West, G.B., Brown, J.H., & Enquist, B.J. (1999). "The fourth dimension of life: Fractal geometry and allometric scaling of organisms". Science. 284 (5420): 1677–9. Bibcode:1999Sci...284.1677W. doi:10.1126/science.284.5420.1677. PMID 10356399.CS1 maint: Multiple names: authors list (link)
11. ^ a b Banavar, J. R., Damuth, J., Maritan, A., & Rinaldo, A. (2002). "Supply-demand balance and metabolic scaling". Proceedings of the National Academy of Sciences. 99 (16): 10506–10509. Bibcode:2002PNAS...9910506B. doi:10.1073/pnas.162216899. PMC 124956. PMID 12149461.CS1 maint: Multiple names: authors list (link)
12. ^ Rinaldo, A., Rigon, R., Banavar, J. R., Maritan, A., & Rodriguez-Iturbe, I. (2014). "Evolution and selection of river networks: Statics, dynamics, and complexity". Proceedings of the National Academy of Sciences. 111 (7): 2417–2424. Bibcode:2014PNAS..111.2417R. doi:10.1073/pnas.1322700111. PMC 3932906. PMID 24550264.CS1 maint: Multiple names: authors list (link)
13. ^ a b c Savage V.M.; Gillooly J.F.; Brown J.H.; West G.B.; Charnov E.L. (2004). "Effects of body size and temperature on population growth". American Naturalist. 163 (3): 429–441. doi:10.1086/381872. PMID 15026978.
14. ^ Enquist, B. J., West, G. B., Charnov, E. L., & Brown, J. H. (1999). "Allometric scaling of production and life-history variation in vascular plants". Nature. 401 (6756): 907–911. Bibcode:1999Natur.401..907E. doi:10.1038/44819.CS1 maint: Multiple names: authors list (link)
15. ^ Enrique Cadenas; Lester Packer, eds. (1999). Understanding the process of ages : the roles of mitochondria, free radicals, and antioxidants. New York: Marcel Dekker. ISBN 0-8247-1723-6.
16. ^ Denney N.H., Jennings S. & Reynolds J.D. (2002). "Life history correlates of maximum population growth rates in marine fishes". Proceedings of the Royal Society of London B. 269 (1506): 2229–37. doi:10.1098/rspb.2002.2138. PMC 1691154. PMID 12427316.
17. ^ Hutchinson, G., MacArthur, R. (1959). "A theoretical ecological model of size distributions among species of animals". Am. Nat. 93 (869): 117–125. doi:10.1086/282063.CS1 maint: Multiple names: authors list (link)
18. ^ Rohde, K. (1992). "Latitudinal gradients in species-diversity: the search for the primary cause". Oikos. 65 (3): 514–527. doi:10.2307/3545569. JSTOR 3545569.
19. ^ Allen A.P., Brown J.H. & Gillooly J.F. (2002). "Global biodiversity, biochemical kinetics, and the energetic-equivalence rule". Science. 297 (5586): 1545–8. Bibcode:2002Sci...297.1545A. doi:10.1126/science.1072380. PMID 12202828.
20. ^ Gillooly, J.F., Allen, A.P., West, G.B., & Brown, J.H. (2005). "The rate of DNA evolution: Effects of body size and temperature on the molecular clock". Proc Natl Acad Sci U S A. 102 (1): 140–5. Bibcode:2005PNAS..102..140G. doi:10.1073/pnas.0407735101. PMC 544068. PMID 15618408.CS1 maint: Multiple names: authors list (link)
21. ^ Terribile, L.C., & Diniz-Filho, J.A.F. (2009). "Spatial patterns of species richness in New World coral snakes and the metabolic theory of ecology". Acta Oecologica. 35 (2): 163–173. Bibcode:2009AcO....35..163T. doi:10.1016/j.actao.2008.09.006.CS1 maint: Multiple names: authors list (link)
22. ^ Stegen, J. C., Enquist, B. J., & Ferriere, R. (2009). "Advancing the metabolic theory of biodiversity". Ecology Letters. 12 (10): 1001–1015. doi:10.1111/j.1461-0248.2009.01358.x. PMID 19747180.CS1 maint: Multiple names: authors list (link)
23. ^ a b Michaletz, S. T., Cheng, D., Kerkhoff, A. J., & Enquist, B. J. (2014). "Convergence of terrestrial plant production across global climate gradients". Nature. 512 (39): 39–44. Bibcode:2014Natur.512...39M. doi:10.1038/nature13470. PMID 25043056.CS1 maint: Multiple names: authors list (link)
24. ^ Banse K. & Mosher S. (1980). "Adult body mass and annual production/biomass relationships of field populations". Ecol. Monogr. 50 (3): 355–379. doi:10.2307/2937256. JSTOR 2937256.
25. ^ Ernest S.K.M.; Enquist B.J.; Brown J.H.; Charnov E.L.; Gillooly J.F.; Savage V.M.; White E.P.; Smith F.A.; Hadly E.A.; Haskell J.P.; Lyons S.K.; Maurer B.A.; Niklas K.J.; Tiffney B. (2003). "Thermodynamic and metabolic effects on the scaling of production and population energy use". Ecology Letters. 6 (11): 990–5. doi:10.1046/j.1461-0248.2003.00526.x.
Allometry

Allometry is the study of the relationship of body size to shape, anatomy, physiology and finally behaviour, first outlined by Otto Snell in 1892, by D'Arcy Thompson in 1917 in On Growth and Form and by Julian Huxley in 1932.

Body size and species richness

The body size-species richness distribution is a pattern observed in the way taxa are distributed over large spatial scales. The number of species that exhibit small body size generally far exceed the number of species that are large-bodied. Macroecology has long sought to understand the mechanisms that underlie the patterns of biodiversity, such as the body size-species richness pattern.

This pattern was first observed by Hutchinson and MacArthur (1959), and it appears to apply equally well to a broad range of taxa: from birds and mammals to insects, bacteria (May, 1978; Brown and Nicoletto, 1991) and deep sea gastropods (McClain, 2004). Nonetheless, its ubiquity remains undecided. Most studies focus on the distribution of taxonomic fractions of largely non-interacting species such as birds or mammals; this article is primarily based on those data.

An ecological cascade effect is a series of secondary extinctions that is triggered by the primary extinction of a key species in an ecosystem. Secondary extinctions are likely to occur when the threatened species are: dependent on a few specific food sources, mutualistic (dependent on the key species in some way), or forced to coexist with an invasive species that is introduced to the ecosystem. Species introductions to a foreign ecosystem can often devastate entire communities, and even entire ecosystems. These exotic species monopolize the ecosystem's resources, and since they have no natural predators to decrease their growth, they are able to increase indefinitely. Olsen et al. showed that exotic species have caused lake and estuary ecosystems to go through cascade effects due to loss of algae, crayfish, mollusks, fish, amphibians, and birds. However, the principal cause of cascade effects is the loss of top predators as the key species. As a result of this loss, a dramatic increase (ecological release) of prey species occurs. The prey is then able to overexploit its own food resources, until the population numbers decrease in abundance, which can lead to extinction. When the prey's food resources disappear, they starve and may go extinct as well. If the prey species is herbivorous, then their initial release and exploitation of the plants may result in a loss of plant biodiversity in the area. If other organisms in the ecosystem also depend upon these plants as food resources, then these species may go extinct as well. An example of the cascade effect caused by the loss of a top predator is apparent in tropical forests. When hunters cause local extinctions of top predators, the predators' prey's population numbers increase, causing an overexploitation of a food resource and a cascade effect of species loss. Recent studies have been performed on approaches to mitigate extinction cascades in food-web networks.

Dynamic energy budget theory

The Dynamic Energy Budget (DEB) theory is a formal metabolic theory which provides a single quantitative framework to dynamically describe the aspects of metabolism (energy and mass budgets) of all living organisms at the individual level, based on assumptions about energy uptake, storage, and utilization of various substances. The DEB theory adheres to stringent thermodynamic principles, is motivated by universally observed patterns, is non-species specific, and links different levels of biological organization (cells, organisms, and populations) as prescribed by the implications of energetics. Models based on the DEB theory have been successfully applied to over a 1000 species with real-life applications ranging from conservation, aquaculture, general ecology, and ecotoxicology (see also the Add-my-pet collection). The theory is contributing to the theoretical underpinning of the emerging field of metabolic ecology.

The explicitness of the assumptions and the resulting predictions enable testing against a wide variety of experimental results at the various levels of biological organization. The theory explains many general observations, such as the body size scaling relationships of certain physiological traits, and provides a theoretical underpinning to the widely used method of indirect calorimetry. Several popular empirical models are special cases of the DEB model, or very close numerical approximations.

Effective evolutionary time

The hypothesis of effective evolutionary time attempts to explain gradients, in particular latitudinal gradients, in species diversity. It was originally named "time hypothesis".

Energy flow (ecology)

In ecology, energy flow, also called the calorific flow, refers to the flow of energy through a food chain, and is the focus of study in ecological energetics. In an ecosystem, ecologists seek to quantify the relative importance of different component species and feeding relationships.

A general energy flow scenario follows:

Solar energy is fixed by the photoautotrophs, called primary producers, like green plants. Primary consumers absorb most of the stored energy in the plant through digestion, and transform it into the form of energy they need, such as adenosine triphosphate (ATP), through respiration. A part of the energy received by primary consumers, herbivores, is converted to body heat (an effect of respiration), which is radiated away and lost from the system. The loss of energy through body heat is far greater in warm-blooded animals, which must eat much more frequently than those that are cold-blooded. Energy loss also occurs in the expulsion of undigested food (egesta) by excretion or regurgitation.

Secondary consumers, carnivores, then consume the primary consumers, although omnivores also consume primary producers. Energy that had been used by the primary consumers for growth and storage is thus absorbed into the secondary consumers through the process of digestion. As with primary consumers, secondary consumers convert this energy into a more suitable form (ATP) during respiration. Again, some energy is lost from the system, since energy which the primary consumers had used for respiration and regulation of body temperature cannot be utilized by the secondary consumers.

Tertiary consumers, which may or may not be apex predators, then consume the secondary consumers, with some energy passed on and some lost, as with the lower levels of the food chain.

A final link in the food chain are decomposers which break down the organic matter of the tertiary consumers (or whichever consumer is at the top of the chain) and release nutrients into the soil. They also break down plants, herbivores and carnivores that were not eaten by organisms higher on the food chain, as well as the undigested food that is excreted by herbivores and carnivores. Saprotrophic bacteria and fungi are decomposers, and play a pivotal role in the nitrogen and carbon cycles.The energy is passed on from trophic level to trophic level and each time about 90% of the energy is lost, with some being lost as heat into the environment (an effect of respiration) and some being lost as incompletely digested food (egesta). Therefore, primary consumers get about 10% of the energy produced by autotrophs, while secondary consumers get 1% and tertiary consumers get 0.1%. This means the top consumer of a food chain receives the least energy, as a lot of the food chain's energy has been lost between trophic levels. This loss of energy at each level limits typical food chains to only four to six links.

Evolutionary physiology

Evolutionary physiology is the study of physiological evolution, which is to say, the manner in which the functional characteristics of individuals in a population of organisms have responded to selection across multiple generations during the history of the population.It is a subdiscipline of both physiology and evolutionary biology. Practitioners in this field come from a variety of backgrounds, including physiology, evolutionary biology, ecology and genetics.

Accordingly, the range of phenotypes studied by evolutionary physiologists is broad, including life history, behavior, whole-organism performance, functional morphology, biomechanics, anatomy, classical physiology, endocrinology, biochemistry, and molecular evolution. It is closely related to comparative physiology and environmental physiology, and its findings are a major concern of evolutionary medicine. One definition that has been offered is "the study of the physiological basis of fitness, namely, correlated evolution (including constraints and trade-offs) of physiological form and function associated with the environment, diet, homeostasis, energy management, longevity, and mortality and life history characteristics".

Geoffrey West

Geoffrey Brian West (born 15 December 1940) is a British theoretical physicist, former president and distinguished professor of the Santa Fe Institute. He is one of the leading scientists working on a scientific model of cities. Among other things his work states that with the doubling of a city's size, salaries per capita will generally increase by 15%.

Guild (ecology)

A guild (or ecological guild) is any group of species that exploit the same resources, or that exploit different resources in related ways. It is not necessary that the species within a guild occupy the same, or even similar, ecological niches. An ecological niche is defined as the role an organism plays in its community, i.e. decomposer, primary producer, etc. Guilds are defined according to the locations, attributes, or activities of their component species. For example, the mode of acquiring nutrients, the mobility, and the habitat zones that the species occupy or exploit can be used to define a guild. The number of guilds occupying an ecosystem is termed its disparity. Members of a guild within a given ecosystem could be competing for resources, such as space or light, while cooperating in resisting wind stresses, attracting pollinators, or detecting predators, such as happens among savannah-dwelling antelope and zebra.

A guild does not typically have strict, or even clearly defined boundaries, nor does it need to be taxonomically cohesive. A broadly defined guild will almost always have constituent guilds; for example, grazing guilds will have some species that concentrate on coarse, plentiful forage, while others concentrate on low-growing, finer plants. Each of those two sub-guilds may be regarded as guilds in appropriate contexts, and they might, in turn, have sub-guilds in more closely selective contexts. Some authorities even speak of guilds in terms of a fractal resource model. This concept arises in several related contexts, such as the metabolic theory of ecology, the scaling pattern of occupancy, and spatial analysis in ecology, all of which are fundamental concepts in defining guilds.

An ecological guild is not to be confused with a taxocene, a group of phylogenetically related organisms in a community that do not necessarily share the same or similar niches (for example, "the insect community"). Nor is a guild the same as a trophic species, organisms of the same species that have mutual predators and prey.

James Brown (ecologist)

James Hemphill Brown (born 1942) is an American biologist and academic.

He is an ecologist, and as of 2001 a Distinguished Professor of Biology at the University of New Mexico. His work has focused on 3 distinct aspects of ecology: 1) the population and community ecology of rodents and harvester ants in the Chihuahuan Desert, 2) large-scale questions relating to the distribution of body size, abundance and geographic range of animals, leading to the development of the field of macroecology, a term that was coined in a paper Brown co-authored with Brian Maurer of Michigan State University. and 3) the Metabolic Theory of Ecology. In 2005 he was awarded the Robert H. MacArthur Award by the Ecological Society of America for his work, including his work toward a metabolic theory of ecology. Between 1969 and 2011 he was awarded over \$18.4 million in grants for his research.

Kleiber's law

Kleiber's law, named after Max Kleiber for his biology work in the early 1930s, is the observation that, for the vast majority of animals, an animal's metabolic rate scales to the ¾ power of the animal's mass. Symbolically: if q0 is the animal's metabolic rate, and M the animal's mass, then Kleiber's law states that q0 ~ M¾. Thus, over the same timespan, a cat having a mass 100 times that of a mouse will consume only about 32 times the energy the mouse uses.

The exact value of the exponent in Kleiber's law is unclear, in part because there is currently no completely satisfactory theoretical explanation for the law.

MTE

The abbreviation MTE or M.T.E. may refer to:

The Metabolic Theory of Ecology, which argues that ecological phenomena result from metabolic constraints

The Brazilian Ministry of Labor and Employment

MCA Television Entertainment, a former division of Universal Television

Materiel de Traction Electrique joint subsidiary of Creusot-Loire and Jeumont-Schneider

MAC-then-Encrypt (MtE), one of approaches to Authenticated encryption

Mathematical Table Errata, an increasingly numbered periodical column about errors in mathematical tables in the journal Mathematics of Computation

Mesopredator release hypothesis

The mesopredator release hypothesis is an ecological theory used to describe the interrelated population dynamics between apex predators and mesopredators within an ecosystem, such that a collapsing population of the former results in dramatically-increased populations of the latter. This hypothesis describes the phenomenon of trophic cascade in specific terrestrial communities.

A mesopredator is a medium-sized, middle trophic level predator, which both preys and is preyed upon. Examples are raccoons, skunks, snakes, cownose rays, and small sharks.

Peto's paradox is the observation, named after Richard Peto, that at the species level, the incidence of cancer does not appear to correlate with the number of cells in an organism. For example, the incidence of cancer in humans is much higher than the incidence of cancer in whales. This is despite the fact that a whale has many more cells than a human. If the probability of carcinogenesis were constant across cells, one would expect whales to have a higher incidence of cancer than humans.

Productivity (ecology)

In ecology, productivity refers to the rate of generation of biomass in an ecosystem. It is usually expressed in units of mass per unit surface (or volume) per unit time, for instance grams per square metre per day (g m−2 d−1). The mass unit may relate to dry matter or to the mass of carbon generated. Productivity of autotrophs such as plants is called primary productivity, while that of heterotrophs such as animals is called secondary productivity.

Robert H. MacArthur Award

The Robert H. MacArthur Award is a biennial prize given by the Ecological Society of America to ecologists for their pivotal contributions to their field. The acceptance speeches of many recipients have been given at the annual meeting of the society and subsequently published in the ESA's Journal of Ecology.

The following is a self-descriptive quote taken from the Robert H. MacArthur Award page on the ESA's website:

"The Robert H. MacArthur Award is given biennially to an established ecologist in mid-career for meritorious contributions to ecology, in the expectation of continued outstanding ecological research. Nominees may be from any country and need not be ESA members. The recipient is invited to prepare an address for presentation at the annual meeting of the society and for publication in Ecology."

Robert Henry Peters

Robert Henry Peters (August 2, 1946 – June 26, 1996) was a Canadian ecologist and limnologist that championed a predictive approach to science in order to make quantitative models relevant to public needs. He proposed that predictive limnology could be an effective tool for producing empirical models about relevant processes and organisms in lakes. He was a Professor in the Biology Department of McGill University, Montreal, Canada from 1974 to his death in 1996.

Square–cube law

The square–cube law (or cube–square law) is a mathematical principle, applied in a variety of scientific fields, which describes the relationship between the volume and the surface area as a shape's size increases or decreases. It was first described in 1638 by Galileo Galilei in his Two New Sciences as the "...ratio of two volumes is greater than the ratio of their surfaces".This principle states that, as a shape grows in size, its volume grows faster than its surface area. When applied to the real world this principle has many implications which are important in fields ranging from mechanical engineering to biomechanics. It helps explain phenomena including why large mammals like elephants have a harder time cooling themselves than small ones like mice, and why building taller and taller skyscrapers is increasingly difficult.

Sustainable gardening

Sustainable gardening includes the more specific sustainable landscapes, sustainable landscape design, sustainable landscaping, sustainable landscape architecture, resulting in sustainable sites. It comprises a disparate group of horticultural interests that can share the aims and objectives associated with the international post-1980s sustainable development and sustainability programs developed to address the fact that humans are now using natural biophysical resources faster than they can be replenished by nature.Included within this compass are those home gardeners, and members of the landscape and nursery industries, and municipal authorities, that integrate environmental, social, and economic factors to create a more sustainable future.

Organic gardening and the use of native plants are integral to sustainable gardening.

General
Producers
Consumers
Decomposers
Microorganisms
Food webs
Example webs
Processes
Defense,
counter
Ecology: Modelling ecosystems: Other components
Population
ecology
Species
Species
interaction
Spatial
ecology
Niche
Other
networks
Other

### Languages

This page is based on a Wikipedia article written by authors (here).
Text is available under the CC BY-SA 3.0 license; additional terms may apply.
Images, videos and audio are available under their respective licenses.