Life on the Scales
Simple mathematical relationships underpin
much of biology and ecology
Erica Klarreich
A mouse lives just a few years, while an elephant
can make it to age 70. In a sense, however,
both animals fit in the same amount of life
experience. In its brief life, a mouse squeezes
in, on average, as many heartbeats and breaths
as an elephant does. Compared with those of
an elephant, many aspects of a mouse's life—such
as the rate at which its cells burn energy,
the speed at which its muscles twitch, its gestation
time, and the age at which it reaches maturity—are
sped up by the same factor as its life span
is. It's as if in designing a mouse, someone
had simply pressed the fast-forward button on
an elephant's life. This pattern relating life's
speed to its length also holds for a sparrow,
a gazelle, and a person—virtually any of the
birds and mammals, in fact. Small animals live
fast and die young, while big animals plod through
much longer lives.
"It appears as if we've been gifted with just
so much life," says Brian Enquist, an ecologist
at the University of Arizona in Tucson. "You
can spend it all at once or slowly dribble it
out over a long time."
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Scientists have long known that most biological
rates appear to bear a simple mathematical relationship
to an animal's size: They are proportional to
the animal's mass raised to a power that is
a multiple of 1/4. These relationships are known
as quarter-power scaling laws. For instance,
an animal's metabolic rate appears to be proportional
to mass to the 3/4 power, and its heart rate
is proportional to mass to the –1/4 power.
The reasons behind these laws were a mystery
until 8 years ago, when Enquist, together with
ecologist James Brown of the University of New
Mexico in Albuquerque and physicist Geoffrey
West of Los Alamos (N.M.) National Laboratory
proposed a model to explain quarter-power scaling
in mammals (SN: 10/16/99, p. 249). They and
their collaborators have since extended the
model to encompass plants, birds, fish and other
creatures. In 2001, Brown, West, and several
of their colleagues distilled their model to
a single formula, which they call the master
equation, that predicts a species' metabolic
rate in terms of its body size and temperature.
"They have identified the basic rate at which
life proceeds," says Michael Kaspari, an ecologist
at the University of Oklahoma in Norman.
In the July 2004 Ecology, Brown, West,
and their colleagues proposed that their equation
can shed light not just on individual animals'
life processes but on every biological scale,
from subcellular molecules to global ecosystems.
In recent months, the investigators have applied
their equation to a host of phenomena, from
the mutation rate in cellular DNA to Earth's
carbon cycle.
Carlos Martinez del Rio, an ecologist at the
University of Wyoming in Laramie, hails the
team's work as a major step forward. "I think
they have provided us with a unified theory
for ecology," he says.
The biological clock
In 1883, German physiologist Max Rubner proposed
that an animal's metabolic rate is proportional
to its mass raised to the 2/3 power. This idea
was rooted in simple geometry. If one animal
is, say, twice as big as another animal in each
linear dimension, then its total volume, or
mass, is 23 times as large, but its
skin surface is only 22 times as
large. Since an animal must dissipate metabolic
heat through its skin, Rubner reasoned that
its metabolic rate should be proportional to
its skin surface, which works out to mass to
the 2/3 power.
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In 1932, however, animal scientist Max Kleiber
of the University of California, Davis looked
at a broad range of data and concluded that
the correct exponent is 3/4, not 2/3. In subsequent
decades, biologists have found that the 3/4-power
law appears to hold sway from microbes to whales,
creatures of sizes ranging over a mind-boggling
21 orders of magnitude.
For most of the past 70 years, ecologists had
no explanation for the 3/4 exponent. "One colleague
told me in the early '90s that he took 3/4-scaling
as 'given by God,'" Brown recalls.
The beginnings of an explanation came in 1997,
when Brown, West, and Enquist described metabolic
scaling in mammals and birds in terms of the
geometry of their circulatory systems. It turns
out, West says, that Rubner was on the right
track in comparing surface area with volume,
but that an animal's metabolic rate is determined
not by how efficiently it dissipates heat through
its skin but by how efficiently it delivers
fuel to its cells.
Rubner should have considered an animal's "effective
surface area," which consists of all the inner
surfaces across which energy and nutrients pass
from blood vessels to cells, says West. These
surfaces fill the animal's entire body, like
linens stuffed into a laundry machine.
The idea, West says, is that a space-filling
surface scales as if it were a volume, not an
area. If you double each of the dimensions of
your laundry machine, he observes, then the
amount of linens you can fit into it scales
up by 23, not 22. Thus,
an animal's effective surface area scales as
if it were a three-dimensional, not a two-dimensional,
structure.
This creates a challenge for the network of
blood vessels that must supply all these surfaces.
In general, a network has one more dimension
than the surfaces it supplies, since the network's
tubes add one linear dimension. But an animal's
circulatory system isn't four dimensional, so
its supply can't keep up with the effective
surfaces' demands. Consequently, the animal
has to compensate by scaling back its metabolism
according to a 3/4 exponent.
Though the original 1997 model applied only
to mammals and birds, researchers have refined
it to encompass plants, crustaceans, fish, and
other organisms. The key to analyzing many of
these organisms was to add a new parameter:
temperature.
Mammals and birds maintain body temperatures
between about 36°C and 40°C, regardless of their
environment. By contrast, creatures such as
fish, which align their body temperatures with
those of their environments, are often considerably
colder. Temperature has a direct effect on metabolism—the
hotter a cell, the faster its chemical reactions
run.
In 2001, after James Gillooly, a specialist
in body temperature, joined Brown at the University
of New Mexico, the researchers and their collaborators
presented their master equation, which incorporates
the effects of size and temperature. An organism's
metabolism, they proposed, is proportional to
its mass to the 3/4 power times a function in
which body temperature appears in the exponent.
The team found that its equation accurately
predicted the metabolic rates of more than 250
species of microbes, plants, and animals. These
species inhabit many different habitats, including
marine, freshwater, temperate, and tropical
ecosystems.
The equation gave the researchers a way to
compare organisms with different body temperatures—a
person and a crab, or a lizard and a sycamore
tree— and thereby enabled the team not just
to confirm previously known scaling laws but
also to discover new ones. For instance, in
2002, Gillooly and his colleagues found that
hatching times for eggs in birds, fish, amphibians,
and plankton follow a scaling law with a 1/4
exponent.
When the researchers filter out the effects
of body temperature, most species adhere closely
to quarter-power laws for a wide range of properties,
including not only life span but also population
growth rates. The team is now applying its master
equation to more life processes—such as cancer
growth rates and the amount of time animals
sleep.
"We've found that despite the incredible diversity
of life, from a tomato plant to an amoeba to
a salmon, once you correct for size and temperature,
many of these rates and times are remarkably
similar," says Gillooly.
A single equation predicts so much, the researchers
contend, because metabolism sets the pace for
myriad biological processes. An animal with
a high metabolic rate processes energy quickly,
so it can pump its heart quickly, grow quickly,
and reach maturity quickly.
Unfortunately, that animal also ages and dies
quickly, since the biochemical reactions involved
in metabolism produce harmful by-products called
free radicals, which gradually degrade cells.
"Metabolic rate is, in our view, the fundamental
biological rate," Gillooly says. There is a
universal biological clock, he says, "but it
ticks in units of energy, not units of time."
Scaling up
The researchers propose that their framework
can illuminate not just properties of individual
species, such as hours of sleep and hatching
times, but also the structure of entire communities
and ecosystems. Enquist, West, and Karl Niklas
of Cornell University have been looking for
scaling relationships in plant communities,
where they have uncovered previously unnoticed
patterns.
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REGULAR ON AVERAGE.
Newly discovered scaling laws have revealed
an unexpected relationship between the
spacing of trees and their trunk diameters
in a mature forest.
PhotoDisc |
The researchers have found, for instance, that
in a mature forest, the average distance between
trees of the same mass follows a quarter-power
scaling law, as does trunk diameter. These two
scaling laws are proportional to each other,
so that on average, the distance between trees
of the same mass is simply proportional to the
diameter of their trunks.
"When you walk in a forest, it looks random,
but it's actually quite regular on average,"
West says. "People have been measuring size
and density of trees for 100 years, but no one
had noticed these simple relationships."
The researchers have also discovered that the
number of trees of a given mass in a forest
follows the same scaling law governing the number
of branches of a given size on an individual
tree. "The forest as a whole behaves as if it
is a very large tree," West says.
Gillooly, Brown, and their New Mexico colleague
Andrew Allen have now used these scaling laws
to estimate the amount of carbon that is stored
and released by different plant ecosystems.
Quantifying the role of plants in the carbon
cycle is critical to understanding global warming,
which is caused in large part by carbon dioxide
released to the atmosphere when animals metabolize
food or machines burn fossil fuels.
Plants, by contrast, pull carbon dioxide out
of the air for use in photosynthesis. Because
of this trait, some ecologists have proposed
planting more forests as one strategy for counteracting
global warming.
In a paper in an upcoming Functional Ecology,
the researchers estimate carbon turnover and
storage in ecosystems such as oceanic phytoplankton,
grasslands, and old-growth forests. To do this,
they apply their scaling laws to the mass distribution
of plants and the metabolic rate of individual
plants. The model predicts, for example, how
much stored carbon is lost when a forest is
cut down to make way for farmlands or development.
Martinez del Rio cautions that ecologists making
practical conservation decisions need more-detailed
information than the scaling laws generally
give. "The scaling laws are useful, but they're
a blunt tool, not a scalpel," he says.
Scaling down
The team's master equation may resolve a longstanding
controversy in evolutionary biology: Why do
the fossil record and genetic data often give
different estimates of when certain species
diverged?
Geneticists calculate when two species branched
apart in the phylogenetic tree by looking at
how much their DNA differs and then estimating
how long it would have taken for that many mutations
to occur. For instance, genetic data put the
divergence of rats and mice at 41 million years
ago. Fossils, however, put it at just 12.5 million
years ago.
The problem is that there is no universal clock
that determines the rate of genetic mutations
in all organisms, Gillooly and his colleagues
say. They propose in the Jan. 4 Proceedings
of the National Academy of Sciences that,
instead, the mutation clock—like so many other
life processes—ticks in proportion to metabolic
rate rather than to time.
The DNA of small, hot organisms should mutate
faster than that of large, cold organisms, the
researchers argue. An organism with a revved-up
metabolism generates more mutation-causing free
radicals, they observe, and it also produces
offspring faster, so a mutation becomes lodged
in the population more quickly.
When the researchers use their master equation
to correct for the effects of size and temperature,
the genetic estimates of divergence times—including
those of rats and mice—line up well with the
fossil record, says Allen, one of the paper's
coauthors.
The team plans to use its metabolic framework
to investigate why the tropics are so much more
diverse than temperate zones are and why there
are so many more small species than large ones.
Most evolutionary biologists have tended to
approach biodiversity questions in terms of
historical events, such as landmasses separating,
Kaspari says. The idea that size and temperature
are the driving forces behind biodiversity is
radical, he says.
"I think if it holds up, it's going to rewrite
our evolutionary-biology books," he says.
Enthusiasm and skepticism
While the metabolic-scaling theory has roused
much enthusiasm, it has its limitations. Researchers
agree, for instance, that while the theory produces
good predictions when viewed on a scale from
microbes to whales, the theory is rife with
exceptions when it's applied to animals that
are relatively close in temperature and size.
For example, large animals generally have longer
life spans than small animals, but small dogs
live longer than large ones.
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MacAdam
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Brown points out that the metabolic-scaling
law may be useful by calling attention to such
exceptions. "If you didn't have a general theory,
you wouldn't know that big dogs are something
interesting to look at," he observes.
Many questions of particular interest to ecologists
concern organisms that are close in size. Metabolic
theory may not explain, for example, why certain
species coexist or why particular species invade
a given ecosystem, says John Harte, an ecologist
at the University of California, Berkeley.
Some scientists question the very underpinnings
of the team's model. Raul Suarez, a comparative
physiologist at the University of California,
Santa Barbara disputes the model's starting
assumption that an animal's metabolic rate is
determined by how efficiently it can transport
resources from blood vessels to cells. Suarez
argues that other factors are equally important,
or even more so. For instance, whether the animal
is resting or active determines which organs
are using the most energy at a given time.
"Metabolic scaling is a many-splendored thing,"
he says.
Suarez' concern is valid, agrees Kaspari. However,
he says, the master equation's accurate predictions
about a huge range of phenomena are strong evidence
in its favor.
Ecologists, physiologists, and other biologists
appear to be unanimous on one point: The team's
model has sparked a renaissance for biological-scaling
theory.
"West and Brown deserve a great deal of credit
for rekindling the interest of the scientific
community in this phenomenon of metabolic scaling,"
Suarez says. "Their ideas have stimulated a
great deal of discussion and debate, and that's
a good thing."
References:
Brown, J.H., J.F. Gillooly,
A.P. Allen, V.M. Savage, and G.B. West. 2004.
Toward a metabolic theory of ecology. Ecology
85(July):1771-1789. Abstract.
Gillooly, J.F., A.P. Allen,
G.B. West, and J.H. Brown. 2005. The rate of
DNA evolution: Effects of body size and temperature
on the molecular clock. Proceedings of the
National Academy of Sciences 102(Jan. 4):140-145.
Abstract available at http://www.pnas.org/cgi/content/abstract/102/1/140.
Gillooly, J.F. . . . G.B. West
. . . and J.H. Brown. 2002. Effects of size
and temperature on developmental time. Nature
417(May 2):70-73. Abstract available at http://dx.doi.org/10.1038/417070a.
Gillooly, J.F., J.H. Brown,
G.B. West, et al. 2001. Effects of size
and temperature on metabolic rate. Science
293(Sept. 21):2248-2251. Available at http://www.sciencemag.org/cgi/content/full/293/5538/2248.
Savage, V.M., J.F. Gillooly,
J.H. Brown, G.B. West, and E.L. Charnov. 2004.
Effects of body size and temperature on population
growth. American Naturalist 163(March):429-441.
Available at http://www.journals.uchicago.edu/AN/
journal/issues/v163n3/20308/20308.html.
Suarez, R.K., C.A. Darveau,
and J.J. Childress. 2004. Metabolic scaling:
A many-splendoured thing. Comparative Biochemistry
and Physiology, Part B 139(November):531-541.
Abstract available at http://dx.doi.org/10.1016/j.cbpc.2004.05.001.
West, G.B., J.H. Brown, and
B.J. Enquist. 1997. A general model for the
origin of allometric scaling models in biology.
Science 276(April 4):122-126. Available
at http://www.sciencemag.org/cgi/content/full/276/5309/122.
Further Readings:
Savage, V.M., J.F. Gillooly,
. . . A.P. Allen . . . and J.H. Brown. 2004.
The predominance of quarter-power scaling in
biology. Functional Ecology 18(April):257-282.
Abstract available at http://dx.doi.org/10.1111/j.0269-8463.2004.00856.x.
Weiss, P. 1999. Built to scale.
Science News 156(Oct. 16):249-251. References
and sources available at http://www.sciencenews.org/pages/sn_arc99/10_16_99/bob1ref.htm.
Sources:
Anurag Agrawal
Ecology and Evolutionary Biology
Cornell University
Ithaca, NY 14853
Andrew Allen
Biology Department
University of New Mexico
Albuquerque, NM 87131
James H. Brown
Biology Department
University of New Mexico
Albuquerque, NM 87131
Steven Buskirk
Department of Zoology and Physiology
University of Wyoming
1000 E. University Avenue
Laramie, WY 82071
Brian Enquist
Department of Ecology and Evolutionary Biology
University of Arizona
Tucson, AZ 85721
James Gillooly
Biology Department
University of New Mexico
Albuquerque, NM 87131
John Harte
Energy and Resources Group
310 Barrows Hall
University of California, Berkeley
Berkeley, CA 94720
Michael Kaspari
Department of Zoology
University of Oklahoma
Norman, OK 73019
Carlos Martínez del Rio
Department of Zoology and Physiology
University of Wyoming
Laramie, WY 82071
Karl Niklas
Department of Plant Biology
Cornell University
Ithaca, NY 14853
Raul Suarez
Department of Ecology, Evolution and Marine
Biology
University of California, Santa Barbara
Santa Barbara, CA 93016
Geoffrey B. West
Theoretical Physics Division
Los Alamos National Laboratory
MS B285
Los Alamos, NM 87545
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