SFSU Public Affairs Press ReleasePublished by the Public Affairs Office at San Francisco State University, Diag Center.
New "niche model" reveals striking similarities between complex food webs and offers ecologists an analytical tool for predicting the impact of species loss on ecosystems as diverse as oceans and deserts.
SAN FRANCISCO, Calif., March 8, 2000-Chemistry has the periodic table of the elements, physics has the law of gravity, and biology has natural selection. According to new research published by San Francisco State University (SFSU) scientists in the March 9 issue of Nature, ecology may also one day get its own set of natural laws.
Applying a simple set of rules to a new food web model, the researchers revealed deep similarities between highly diverse ecosystems, suggesting the rules could be generalized.
"What makes this so compelling is that our model shows there are fundamental regularities in nature where ecologists thought there were none," said author Neo Martinez, an aquatic ecologist at SFSU's Romberg Tiburon Center for Environmental Studies who has made a career of studying food webs. "Having an accurate model of food webs gives us a valuable tool for predicting the impact of biodiversity loss on ecosystems as different as oceans and deserts."
Working from their assertion that complex food webs arise from species having a simple pecking order of "who eats whom," Martinez and adjunct biology professor Richard Williams devised a theoretical model of food web organization based on two simple rules: one, that species higher up in the pecking order tend to eat lower-ordered species; and two, that if a species eats more than one species in the pecking order, it must also eat the species in between. While the basis of the pecking order is not yet kn own, similar rules are played out daily in nature: for example, a predator such as a wolf eats large and small herbivores such as deer and mice. Following the rules, it also eats intermediate herbivores, such as rabbits.
Called the "niche model," it is named for the theory's premise that each trophic species (a group of animal types that share the same predators and prey, such as some lizards) fits a specific niche based on what it eats and, in turn, what eats it.
According to Martinez, scientists have long believed that food webs, or intractable "tangled banks" as Charles Darwin once called them, are uniquely formed and governed by their respective ecosystems. For example, scorpions, cacti and woodpeckers native to the Sonoran Desert, it is generally thought, abide by food-web laws distinct from the laws dictating the food-web structure of fish, crabs and plankton in the Chesapeake Bay.
To test their theory, the researchers selected seven of the most complex food webs available in the literature, representing an array of ecosystems-from estuaries and deserts to lakes and islands. These included the largest food web on record, the Little Rock Lake in Wisconsin, which Martinez helped develop, as well as food webs representing the Chesapeake Bay, Skipwith Pond and the Coachella Desert, among others. By plugging two parameters into the model-the number of species and links in the food web- the researchers were able to predict the structural properties of each web.
"It turned out that the model yielded computerized food webs stunningly close to the real food webs, all of which were developed from in-depth field studies," said Martinez.
What sets the "niche model" apart from current models of food web organization, say the researchers, is its ability to accurately predict a set of 12 characteristics, such as the length of food chains, the number of omnivores and cannibals, the distribution of specialists and generalists, and the vulnerability of species within each food web. The most widely accepted model to date-the cascade model-successfully predicts only a few food web properties: top species, such as predators; intermediate species , such as herbivores; and basal species, such as plants. The niche model performed similarly across the different food webs and consistently predicted their individual properties more accurately than the cascade model.
A computer-imaging program designed by Williams to process the data also allowed the researchers to create a three-dimensional color diagram of each of the food webs, showing in visual form their basic properties, such as links between species (in the form of a line between species, which are represented by balls colored to correspond to their respective trophic level) and cannibalism (represented by a line shaped like a loop, or handle, on the ball).
"The fact that the model can reasonably predict properties for such a diverse range of systems-lakes, river estuaries, a Carribean Island and a desert-suggests there are deep similarities to these very different ecosystems," said Williams. "On a practical level, the model can be tied into other areas of research, such as studying population dynamics and species loss."
Eric Berlow, PhD., a research scientist from the University of California, Berkeley, who studies food webs, agreed: "It's fascinating that such a simple model could nail so many of the topological characteristics of complex natural communities. Being able to easily simulate randomly constructed food webs with realistic properties opens the door to richer theoretical investigations of the effects of biodiversity loss in complex webs."
"At this point, our model is a surprisingly successful theory," said Martinez, but he cautioned that further testing is required before the model could be considered a law. "While it's not as simple or accurate as, say, the basic law of physics-'force equals mass times acceleration'-the niche model offers the same type of general framework by which to understand a complex natural system: You give the general model specific inputs, and it gives you remarkably accurate predictions."
Author contact information: Neo Martinez, (415) 338-1213, email@example.com; Richard Williams, (831) 425-7849, firstname.lastname@example.org.
This press release, along with other San Francisco State University news, can be viewed at: http://www.sfsu.edu/~pubaff.
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Last modified April 24, 2007, by Office of Public Affairs