PLoS Biol. 2004 December; 2(12): e440.
Ecology's
Big, Hot Idea
John Whitfield
Life is complicated. It comes in all sorts of
shapes, sizes, places, and combinations, and has evolved a dizzying variety of
solutions to the problem of carrying on living. Yet look inside a cell and life
takes on, if not simplicity, then at least a certain
uniformity—a genetic system based around nucleic acids, for example, and a
common set of chemical reactions for turning food into fuel. And
looked at in broad swathes, life shows striking generalities and patterns.
Every mammal's heart will beat about one billion times in its lifetime. Both
within and between species, the density of a population declines in a regular
way as the size of individuals increases. And the number of species in all
environments declines as you move from the equator towards the poles.
Wouldn't it be good if there were a simple theory that used life's shared
fundamentals to explain its large-scale regularities, via its diversity of
individuals? In the past few years, a team of ecologists and physicists have
come up with just such a theory. At its heart is metabolism: the way life uses
energy is, they claim, a unifying principle for ecology in the same way that
genetics underpins evolutionary biology. They believe that energy use, in the
form of metabolic rate, can be understood from the first principles of physics,
and that metabolic rate can explain growth, development, population dynamics,
molecular evolution, the flux of chemicals through the environment, and
patterns of species diversity—to name a few.
The work, its originators insist, is not a theory of everything for biology,
or even ecology. But it can often seem that way. “We're making advances on a
broad range of questions almost on a weekly basis,” says James Gillooly, of the University of New Mexico, Albuquerque.
“We've been having an awful lot of fun.”
Beneath the Surface
Metabolic ecology, as it has become known, is still controversial. Some
think its mathematical foundations are unsound, and that it explains
nonexistent trends. It also divides researchers on philosophical lines—those
that see life's patterns as fundamental versus those who think that variation
is the key, those who think that simple, general ideas can help us understand
nature versus those who think that complicated problems require complicated
answers. A lot is riding on the debate: “If the theory is right, it's one of
the most significant in biology for a long time,” says ecologist David Robinson
of the University of Aberdeen. “It would provide a common functional basis for
all biodiversity.”
Scientists have known for nearly two centuries that larger animals have
relatively slower metabolisms than small ones. A mouse must eat about half its
body weight every day not to starve; a human gets by on only 2%. The first
theories to explain this trend, developed in the late nineteenth century by the
German nutritionist Max Rubner and the French
physiologist Charles Richet, were based on the ratio between an animal's surface area,
which changes with the square of its length, and its volume, which is
proportional to its length cubed. So large animals have proportionately less
surface area, lose heat more slowly, and, pound for pound, need less food. The
square-versus-cube relationship makes the area of a solid proportional to the
two-third power of its mass, so metabolic rate should also be proportional to
mass2/3. For many years, most biologists thought that it was.
But in 1932, Max Kleiber, an animal physiologist
working at the University of California's agricultural station in Davis,
re-examined the question, and found that, for mammals and birds, metabolic rate
was mass0.73—closer to three quarters than two thirds. Kleiber looked at animals ranging in size from a rat to a
steer. By the mid-1930s, other workers had put together a “mouse to elephant”
curve that supported the three-quarter-power law, and by the 1960s, the plot
had been extended for everything from microbes to whales, still seeming to show
the same relationship. Quarter-power scaling also began to stretch beyond
metabolic rate. Biological times, such as lifespan and heart rate, were found
to be proportional to mass1/4, and fractions related to one-quarter
show up in other scaling relationships: the diameter of the aorta and tree
trunks is proportional to mass3/8, for example.
It was, however, much harder to find a theoretical
reason for why metabolic rate should be proportional to mass3/4—and
more generally, why quarter-power scaling laws should be so prevalent in
biology. The impasse meant that by the mid-1980s interest in scaling had waned.
But it sparked back into life in 1997, when two ecologists—James Brown of the
University of New Mexico, Albuquerque, and his graduate student Brian Enquist, now at the University of Arizona, Tucson—and a
physicist, Geoffrey West of the Santa Fe Institute, developed a new explanation
of why metabolic rate should equal the three-quarter power of body mass.
West, Brown, and Enquist's theory is based on the
structure of biological distribution networks, such as blood vessels in
vertebrates and xylem in plants. The trio assumed that metabolic rate equals
the rate at which these networks deliver resources, and that evolution has
minimized the time and energy needed to get materials from where they are taken
up—the lungs or roots, for example—to the cells. They also assumed that,
although organisms vary greatly in size, the terminal units in their
distribution networks, such as blood capillaries or leaf stalks, do not.
Bigger plants and animals take longer to transport
materials, and so use them more slowly. In West, Brown, and Enquist's
model, the maximally efficient network that serves every part of a body has a
fractal structure, showing the same geometry at different scales. And the number of uniform terminal units in such a network—and so
the rate at which resources are delivered to the cells—is proportional to the
three-quarter power of body mass.
Pattern versus Variation
Whether metabolic rate really varies with the
three-quarter power of body mass is still debated—some researchers still favor
two-thirds, others think that no one exponent fits all the data—but a majority
of biologists favor three-quarters. And whether the fractal theory really explains
the relationship of metabolic rate to body size is also still contentious. In
the most wide-ranging critique so far, published this April, two Polish
researchers, Jan Kozlowski, of Jagiellonian
University, Krakow, and Marek Konarzewski
of the University of Bialystok, claimed that the
theory's maths could not simultaneously contain both
uniform terminal units and three-quarter-power scaling, that large animals
built along such lines would have more blood than their bodies could contain,
that biological scaling laws were not built around quarter powers, and that
biological networks were not generally branching fractals.
“I don't believe there's anything to explain—there's no universal scaling
exponent,” says Kozlowski. He is also struck by what is left unexplained when
size is accounted for: animals of the same size can still show more than an
order of magnitude variation in metabolic rate. “What's striking in nature is
the variability,” he says. “There are regularities that call
for explanation, but that doesn't mean ignoring the variability is correct.”
Kozlowski is the co-author of a theory that relates metabolic rate to cell size
and the amount of DNA an organism has, one of several alternative explanations
of the scaling of metabolic rate published since West, Brown, and Enquist's model.
The criticisms are serious, says Robinson. “The jury is out—questions about
the fundamental maths are worrying a few people.” On
the other hand, he says, West, Brown, and Enquist's
model seems a plausible template for designing an organism, and itspredictions fit real-world data remarkably well. Whether
this fit truly captures the physical and chemical mechanisms underlying the
patterns remains to be seen; Robinson hopes that criticism can strengthen West,
Brown, and Enquist's model, perhaps leading to a new,
improved theory.
The metabolic theory's authors are not budging. “We've yet
to see a criticism we feel we can't answer pretty readily,” says Brown.
Kozlowski and Konarzewski's arguments are based on a
misreading of the work, he says, and criticisms that focus on one aspect, such
as the structure of mammalian vascular systems, miss the key point, which is
generality: “If we're wrong on quarter powers, why do they keep showing up in
everything from life-history processes to evolutionary rates?”
From Sharks to Tomatoes
After accounting for size, Brown's group turned
its attention to the second most important influence on metabolism:
temperature. The effect is exponential, and a 5 °C rise in body temperature
equals a roughly 150% rise in metabolic rate. The team built an equation for
metabolic rate that combined the mass3/4 term with the Boltzmann factor. The latter is an expression of the
probability that two molecules bumping into each other will spark a chemical
reaction. The higher the temperature, the greater the
probability, and the faster the reaction.
Adding temperature explained much of the variation in metabolic rate that
remained after adjusting for size. It also explained some of the metabolic
differences between groups. For example, a reptile has a slower metabolic rate
than a mammal of the same size. But adjusting for its lower body temperature
removes much of the difference, suggesting that the two groups share
fundamental metabolic processes. The same even goes for plants and animals.
“When you correct for size and temperature, the metabolic rates of a shark, a
tomato plant and a tree are remarkably similar,” says Gillooly,
who joined Brown's group as a grad student to work on the temperature question.
It's not yet clear what the activation energy represents, says Gillooly. It could be a kind of average for all the
hundreds of chemical reactions in metabolism, or maybe the energy needed to get
over one crucial hump in the path.
The metabolic theory's third component, resources, is also something of a
black box at this stage. Nutrient supply, the team reasons, is the next most
important determinant of metabolic rate, and will account for some of the
remaining unexplained variation. As with temperature, the overall effect could
be a balance of many processes, or it could be due to one limiting element—the
growth of lake phytoplankton is often limited by phosphorus, for example, while
for marine phytoplankton iron is usually the crucial nutrient. “It's a work in
progress,” says Brown. “But our vision for a metabolic theory of life is
ultimately going to include material resource limitation.”
These three things still do not account for all the variation in metabolic
rate, but more detailed knowledge of species can yield more precise
predictions. Using body size, altitude, and diet, Brian McNab,
of the University of Florida, Gainesville, has explained 99.0% of the variation
in metabolic rate for birds of paradise, and 99.4% of the rate variation in
leaf-nosed bats. Nevertheless, when McNab sees
attempts to explain variation in metabolism using a few parameters applied
across a wide range of sizes and taxonomic groups, what isn't explained strikes
him as forcefully as what is.
“I have serious reservations as to whether there is a single relationship
for body size and metabolic rate,” he says. “I think we will be able to find
generalizations in ecology, but they're not going to be simple—there will be a
bunch of clauses and restrictions, and animals have a lot of ways to bend the
rules.”
No theory matches data exactly, Brown points out; having a baseline
prediction for metabolism lets you identify exceptional cases worthy of further
investigation. Viewed from this angle, the metabolic theory is a kind of null
hypothesis of how organisms work. “Until you have a theory that makes a
prediction, you don't know how to interpret any of the variation,” says Brown.
And, he adds, despite this variation, the underlying trends are also
meaningful. “There are themes of life that are deep-seated and fundamental.”
All the business of life needs energy. So if you know the rate at which an
organism burns fuel—or if you know how big and hot it is, and apply the
metabolic theory—you can make a suite of predictions about its biology, such as
how fast it will grow and reproduce, and how long it will live.
By correcting for mass and temperature, Brown, Gillooly, and their colleagues believe they have revealed
underlying similarities in all the rates of life. The hatching times for
egg-laying animals, including birds, fish, amphibians, insects, and plankton,
turn out to follow the same relationship—if a fish egg were the same size and
temperature as a bird egg, it would take equally long to hatch. The same goes
for growth: a tree and a mammal of equal size and temperature would gain mass
at the same speed. And size and temperature even explain much of the variation
in mortality rates between species—which one might have thought to be strongly
dependent on external factors such as predators—perhaps through metabolism's
influence on aging processes, such as free-radical damage to the genome.
In the future, Brown's group plans to examine the dynamics
of colonial organisms and societies through the lens of metabolic ecology;
instead of capillaries, the terminal units of the networks would become ants,
or people. There are also many applied problems within the theory's scope,
including some of the most significant human impacts on the biosphere. Carbon
emissions and the consequent global warming are increasing both the temperature
and nutrient supply. And exploited populations, such as fisheries often show a
decrease in individual size, as larger animals are preferentially killed. Both
these would tend to speed up biological processes. Another team of United States
and Italian researchers has found that the same model that describes the growth
of individuals can also predict the growth of tumors, hinting that metabolic
ecology may have medical applications.
Brown hopes that metabolic ecology will one day become an uncontroversial
part of researchers' toolkits, like the theories population geneticists use to
predict changes in the frequencies of genes. Before that happens, both the
theory's proponents and its opponents have years of work ahead of them. Adopting
the theory may also require a shift in ecologists' worldview. Most ecologists
work by carrying out experimental manipulations on small groups of similar
organisms: the warblers in a woodland, for example, or the grasses of a meadow.
When they build models, they do so from empirical data, not from physical first
principles. The philosophy behind metabolic ecology disconcerts many
researchers, says Robinson. “A lot of traditional biologists are uncomfortable
with thinking about data in these terms.”
Kozlowski doubts that simple theories can make precise predictions about the
behavior of biological systems on large scales. He believes that metabolic
ecology risks leading the discipline up a blind alley: “If I'm right, and the
basic model contains an error, correcting the results will be a very long
process. If they're not right, they'll have done a disservice to ecology.”
But many ecologists are more optimistic that some unifying
principles of nature can be found, and that metabolic ecology, and the debate
around it, is a step in the right direction. Some think the theory may be part
of an even grander idea. Stephen Hubbell, of the University of Georgia, is one
of the architects of another idea causing a stir among ecologists. Called
neutral ecology, it proposes a general explanation of how competition between
individuals produces the dynamics of birth, death, and migration seen in
ecosystems, and its predictions match closely the abundance and diversity of
species in the wild. He believes that metabolic and neutral ecology can become
elements of some larger theoretical framework.
“I've never been more excited in my life,” says Hubbell.
“Ecology now is like quantum mechanics in the 1930s—we're on the cusp of some
major rearrangements and syntheses. I'm having a lot of fun.”
Further Reading
·
Allen AP, Brown JH, Gillooly
JF. Global biodiversity, biochemical kinetics and the energy equivalence rule.
Science 2002;297:1545–1548.
·
Brown JH, Gillooly JF,
Allen AP, Savage VM, West GB. Towards a metabolic theory of ecology. Ecology
2004;85:1771–1789. (Part of
a forum on metabolic ecology in the August 2004 issue of Ecology.).
·
Enquist BJ, Economo EP, Huxman TE, Allen AP, Ignace DD, et al. Scaling metabolism from organisms to
ecosystems. Nature 2003;423:639–642.
·
Gillooly JF, Brown JH,
West GB, Savage VM, Charnov EL. Effects of size and
temperature on metabolic rate. Science 2001;293:2248–2251. Gillooly
JF, Charnov EL, West GB, Savage VM, Brown JH. Effects
of size and temperature on developmental time. Nature 2002;417:70–73. Gillooly JF,
Allen AP, West GB, Brown JH. Metabolic rate calibrates the molecular clock:
Reconciling molecular and fossil estimates of evolutionary divergence. Proc Natl Acad Sci
U S A. 2004 In press.
·
Guiot C, Degiorgis PG, Delsanto PP,
Gabriele P, Deisboeck TS. Does tumor growth follow a
“universal law”? J Theor Biol
2003;225:147–151.
·
Hubbell, SP. The unified neutral theory of
biodiversity and biogeography. Princeton (New Jersey): Princeton University
Press; 2001. 448 p.
·
Jetz W, Carbone C, Fulford J, Brown JH.
The scaling of animal space use. Science 2004;306:266–268. Kozlowski J, Konarzewski
M. Is West, Brown and Enquist's
model of allometric scaling mathematically correct
and biologically relevant? Funct Ecol 2004;18:283–289. (The April 2004
issue of Functional Ecology contains several more papers on scaling and
metabolism.).
·
Kozlowski J, Konarzewski
M, Gawelczyk AT. Cell size as a link between noncoding DNA and metabolic rate scaling. Proc Natl Acad Sci
U S A 2003;100:14080–14085.
·
McNab BK. Ecology
shapes bird bioenergetics. Nature 2003;426:620–621.
·
McNab BK. Standard
energetics of phyllostomid bats: The inadequacies of phylogenetic-contrast analysis. Comp Biochem
Physiol A 2003;135:357–368.
·
West GB, Brown JH, Enquist
BJ. A general model for the origin of allometric
scaling models in biology. Science 1997;276:122–126.
West GB, Brown JH, Enquist BJ. A general model for
ontogenetic growth. Nature 2001;413:628–631.
·
Whitfield
J. All creatures great and small. Nature 2001;413:342–344.