Ecopath: Who’s Eating Whom?
Ecopath was originally designed in the early 1980s by Dr. Jeffrey Polovina as a marine ecosystem model. The name is intended to convey ecological pathways, or the ability to identify relationships and model complex marine ecosystems. Ecopath uses path analysis to calculate direct and indirect effects from a multitude of ecosystem components.
Ecopath software package can be used to:
- Address ecological questions
- Evaluate ecosystem effects of fishing
- Explore management policy options
- Evaluate impact and placement of marine protected and managed areas
- Evaluate effects on environmental changes
Data on predator-prey interactions is largely gathered from the body of scientific literature and any field-related surveys. These data are input into the Ecopath model with the desired situation being that the biomasses, production and consumption ratios are known for all groups of predators and prey, and that only the ecotrophic efficiency is estimated. Ecotrophic efficiency can be described as the proportion of the production that is utilized in the system. By default equations, the model fills in information gaps in order to reach mass-balance of all trophic, physical and fishing interactions.
The core of EwE is the compiled biomass groups where the trophic interactions are established. In part the model exposes the interactions between human uses and the marine ecosystem, estimating the direction and strength of all factors that influence the way marine systems function. Ecopath provides an “instantaneous” estimate of biomasses, trophic flows and mortality rates, for some reference year or multi-year averaging window.
EwE is intended to be a marine ecosystem model. There is an assumption that EwE is somehow intended to supplant or replace single-species assessment methods. This is clearly not the case; ecosystem-based methods rely on information from traditional assessment, and is best applied to address strategic management questions, not tactical management questions to which single-species assessment is much better suited. The primary goal of EwE has been to develop a capacity for asking policy questions that simply cannot be addressed with single-species assessment. Examples include questions about impacts of fishing on non-target species, and the efficacy of policy interventions aimed at limiting unintended side effects of fishing.
Ecosim: Who’s Eating Whom, When?
The time element of EwE is enabled in the Ecosim component. Ecosim turns the energy flows of a given Ecopath model into dynamic, time-varying predictions. Ecosim users can specify fishing mortality patterns over time either at the group level (fishing rate for each group over time) or the fleet level. Fleet level changes are specified as changes in relative fishing effort, and these changes impact fishing rates for the species caught by each gear type. That is, technical interactions (fishing rate effects on a variety of species caused by each gear type) are a basic part of Ecopath data input and Ecosim simulations.
Ecosystem simulation models have not been used much for fishery management. They do, however, provide insight into how marine systems function over time given a set of fishing effort variables as described in the following two examples.
Discarded bycatch can be treated as a biomass pool in Ecopath, i.e. as a diet component by species that consume discards (e.g., sharks, birds, shrimp). Bycatch and discard rates are then passed to Ecosim, accounting for changes in discard rates and biomass in relation to simulated changes in fishing fleet sizes. For example, shrimp often appear to become more productive under fishing by including the effects of both reducing abundance of predatory fishes (when they are killed as bycatch) and providing biomass for those fishes as food for the shrimp.
When a large, dominant species are fished down, Ecosim often predicts a substantial increase in smaller-sized predators that have been kept down in abundance by a combination of direct predation and competition effects with the large dominant species. Those predators then cause an increase in predation mortality rate on (or compete for food with) juveniles of the large, previously dominant group. This slows or prevents population recovery even if the fishing effects are removed. Ecosim thus warns us to be especially wary in the management of the most common, large, and dominant fish species that are the most valuable components of most fisheries.
There are also examples where Ecosim may produce misleading results (Christensen and Walters 2004).
There can be particular problems if indirect trophic effects are not recognized in the model. For example, fishing down tunas in a model of a pelagic ecosystem is likely to result in predicted increases in abundances of forage fishes, and hence to predicted increases in abundance of pelagic birds. But in fact, reducing tuna abundance may have exactly the opposite effect, resulting in bird declines due to the baitfish spending less time at the surface when tuna are less abundant.
Ecosim may also identify patterns as trophic and fishing effects that in fact have been due to habitat changes. This is a particular risk in situations where habitat change involves some fairly regular ‘regime shifts’ or cycles in habitat variables. Ecosim may well attribute cyclic biomass changes in such situations to predator-prey instabilities rather than environmental forcing.
Reference: Christensen, V. and C.J. Walters. 2004. Ecopath with Ecosim: Methods, capabilities and limitations. Ecological Modelling 172, 109-139