As part of a project exploring the technical uncertainties surrounding Puget Sound water quality, we are reviewing how computer models are used to advance our understanding of natural systems. This blog post is part of a series focused on different models and their uses within the Puget Sound ecosystem. The project is jointly sponsored by King County and the Puget Sound Institute.
In the early 1980s, NOAA scientist Jeffrey Polovina and fellow researchers at the National Marine Fisheries Service in Hawaii developed what they called the Ecopath model, designed to describe the flow of energy through a food web. Since then, this food-web model has been expanded, refined and applied to ecosystems throughout the world, including Puget Sound.
In 2007, when celebrating the 200th anniversary of the Coast and Geodetic Survey, the National Oceanic and Atmospheric Administration declared Ecopath one of the 10 greatest accomplishments by agency scientists, along with climate modeling, global positioning systems (GPS) and discovery of the ozone hole. By 2020, about 8,000 researchers had used the software in more than 170 countries, according to the Ecopath support network.
The key to the Ecopath model is to account for total biomass within an ecosystem by organizing all the various species into groups of similar nature. Predator-prey relationships are represented by equations that calculate the transfer of mass/energy from one group to another with no net loss. Individual growth and population expansion among predator species must be balanced with mortality among the prey species, even as many predators are prey for other animals. The equations include factors to account for other mass changes, such as animals coming into or leaving the system — including the effects of human fishing and death from disease.
The basic Ecopath model works for any undetermined time period, provided the interspecies relationships remain valid. Since time and space are not factors in the mass-balance equations, Ecopath is considered a static model. Thanks to its simplicity, the model’s data requirements are often available from existing monitoring studies, fishery records and research involving consumption rates and diet compositions. The essential demand for balance helps to reveal gaps in the data or the need to better understand the predator-prey relationships taking place in an ecosystem.
When Polovina first developed Ecopath in the early ’80s, scientists and policy makers were exploring new ways to describe and manage ecosystems, including the effects of fisheries and other environmental pressures. Unlike existing models at the time, Ecopath was able to represent complex ecosystems with minimal equations, computing power and start-up data.
Polovina’s original goal with Ecopath was to better understand the coral reef ecosystem in the French Frigate Shoals, the largest atoll in the Northwestern Hawaiian Islands. Starting at the top of the food web, the researchers gathered information about what tiger sharks were eating. They worked their way down through the prey species, considering all the diets, finally getting down to algae and plants — known as primary producers for their ability to live on nutrients and sunlight.
Although Ecopath is appreciated for its simplicity, various researchers have offered advanced versions of the basic software. Chief among them are Villy Christensen and Carl Walters at the University of British Columbia who introduced a dynamic model called Ecosim, which incorporates time-related changes — such as the rapid growth of algae versus the slower growth of whales, or the increased consumption rate as an animal grows older and larger, or the avoidance behavior exhibited by prey faced with increased predation.
Another advancement in Ecopath is Ecospace, a model that allows different actions to take place in different locations — such as fishing prohibitions imposed within marine protected areas, or increased productivity observed in areas with better habitat. Together, the software suite Ecopath with Ecosim or Ecospace is known as EwE.
Ecopath modeling has been used in the Puget Sound region by various researchers, including Chris Harvey and his associates at NOAA’s Northwest Fisheries Science Center. In 2010, Harvey published a description of a new EwE food-web model that he hoped would help the Puget Sound Partnership manage recovery efforts in the region.
The model focused on the Central Puget Sound area from Admiralty Inlet near Whidbey Island to Tacoma. The area was treated as a “single biogeographic box” with no spatial differences. The addition of Ecosim to the basic Ecopath model allowed a consideration of changes over time.
The model included 65 “functional groups,” which were either individual species or guilds of similar species. More than 68 percent of the living biomass was represented in seven functional groups, the first three being dwellers within bottom sediments: bivalves, soft infauna and geoducks, along with phytoplankton, small crustaceans, ratfish, and copepods.
Simulations involved introducing perturbations to see how the ecosystem responded over 50 years, as reported in the journal Estuaries and Coasts. Bottom-up effects were observed by increasing phytoplankton, while top-down effects were observed by decreasing bald eagles as a representative for birds of prey. Phytoplankton were shown to have significant effects on the food web, but many effects were delayed by up to five years for groups higher in the food web, including spiny dogfish, raptors, sea urchins and birds that consume vegetation.
In the simulation with eagles, the decreased raptor population started after 20 years. In the first phase, the natural growth of raptors led to a decreased biomass of all other bird groups, but the response was complex — probably because of the varying relationships among other birds. For example, raptors prey on all other bird groups, but gulls also prey on diving birds.
A continuing decline in eagles imposed at the 20-year mark triggered a “trophic cascade” that dramatically altered portions of the food web. Fewer raptors led to an increase in gulls and diving birds, causing a decline in their prey, including juvenile salmon, herring, mussels and bottom fish. That decrease in small fish, in turn, triggered an increase in their prey, notably large zooplankton and shrimp — the only invertebrate groups to grow larger during this scenario. Meanwhile, the decline in juvenile salmon led to a decline in adult salmon, an important food source for the raptors, and that may have accelerated the ongoing loss of raptor biomass, according to the study’s findings.
This scenario suggests that seabirds, including eagles and other raptors, are a key part of the food web. Although their biomasses are low, their consumption rates are relatively high with indirect effects on forage fish, invertebrates and possibly even primary producers.
In later model simulations, Harvey found that shifting the diet of eagles from mostly birds to mostly fish would reduce the overall effects on the food web, thus avoiding the “trophic cascade” that occurs when birds are a major food source. Differences in diet could be expected for eagles close to the water versus those farther inland.
“This goes to show that models are really useful for working through these kinds of problems,” Harvey said.
In another part of the study, the researchers ran a series of simulations to measure fishing effects on the ecosystem by increasing harvest rates from one simulation to the next. While predators and humans are often thought of as competitors for available biomass, the model runs showed that fisheries with the greatest harvest levels (salmon and geoducks) were taking more than 10 times the amount of biomass as natural predators. Even lingcod, taken in a smaller fishery, were caught in greater numbers by fishing than by predation.
The model shows that spiny dogfish are a significant predator, accounting for more than 25 percent of the mortality among six functional groups, including Pacific herring, Dungeness crabs and flatfish.
“Overall,” the authors wrote, “fishing mortality does not appear to be a major structuring force in the contemporary Puget Sound Central Basin food web, although contemporary food web structure may be a byproduct of heavier fishing in previous decades.”
While salmon fishing can remove significant numbers of fish, salmon biomass plays a lesser role in the Puget Sound food web, since most of their growth occurs in the ocean, outside the model’s domain. While fishing pressures directly affect the biomass of targeted populations, reverberations through the food web seem to be minimal, according to the study.
“Our model suggests that simply terminating fishing would not restore depleted populations of gadoids (Pacific hake, Pacific cod, walleye pollock) to historic levels of abundance,” the report concludes. This finding may be the result of a lack of data about those fish, an incomplete understanding of ecological processes, or unrecognized changes in the ecosystem that could limit potential gadoid populations.
The Ecopath model of Central Puget Sound, with its demand for mass balance, became a stepping stone for more complex models able to account for differences from place to place over much larger areas while accounting for localized differences.
“Models like this are really great for getting as much information as possible under one roof and into a common currency,” Harvey said. “Whether you are talking about concentration of nutrients or numbers of species, all your units must match up. You can then address uncertainties, figure out what you don’t know and begin to get some rough ideas about how the ecosystem would respond to various conditions.”
This blog was funded in part by King County as part of a project to explore the technical uncertainties surrounding Puget Sound water quality.
Up next: Atlantis model and the threats to salmon from a food-web perspective
Other blog posts in this series about modeling in the Puget Sound region:
- Six things that people should know about ecosystem modeling and virtual experiments
- Before supercomputers, a structural model helped scientists predict currents in Puget Sound
- Researchers use a qualitative network model to test ways to boost production at shellfish farms
- Health of killer whales examined through Bayesian network modeling and informed predictions