{"id":2249,"date":"2023-12-04T17:11:10","date_gmt":"2023-12-04T22:11:10","guid":{"rendered":"https:\/\/pressbooks.bccampus.ca\/ewemodel\/?post_type=chapter&p=2249"},"modified":"2026-04-08T18:42:53","modified_gmt":"2026-04-08T22:42:53","slug":"food-chain-model","status":"publish","type":"chapter","link":"https:\/\/pressbooks.bccampus.ca\/ewemodel\/chapter\/food-chain-model\/","title":{"raw":"Tutorial: Food chain model","rendered":"Tutorial: Food chain model"},"content":{"raw":"

Studies have indicated that fishing pressure on prey fish (planktivores) can have larger impact on their predators (piscivores) than on the prey fish.<\/p>\r\n

Construct a simple ecosystem model as a simplified version of the Anchovy Bay model to study this closer. The model can be a straight food chain, e.g., with the following functional groups and parameters.<\/p>\r\n\"\"\r\n\r\nCreate a new model Menu > File > New model<\/em> and name it (e.g., \"Food chain\"). The model will be saved as a database with .ewemdb<\/em> extension. Go to Ecopath > Input > Basic input > Define groups<\/em> and click Insert<\/em> four times. In the Group name<\/em> column, enter the first four group names from the table below. (Detritus will already be there). \u00a0Make Phytoplankton<\/em> a Producer<\/em>. \u00a0[While here, change the default colours to Random<\/em>]. Click OK<\/em>.\r\n

Enter the following parameters on the Ecopath > Input > Basic input<\/em> form, (cut\/paste works from Excel to EwE, but probably not from the table below)<\/p>\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n
Group<\/strong><\/td>\r\nBiomass (t km-2<\/sup>)<\/strong><\/td>\r\nP\/B (year-1<\/sup>)<\/strong><\/td>\r\nP\/Q<\/strong><\/td>\r\n<\/tr>\r\n
Mackerel<\/td>\r\n0.5<\/td>\r\n0.5<\/td>\r\n0.2<\/td>\r\n<\/tr>\r\n
Anchovy<\/td>\r\n2<\/td>\r\n1<\/td>\r\n0.25<\/td>\r\n<\/tr>\r\n
Zooplankton<\/td>\r\n2<\/td>\r\n10<\/td>\r\n0.3<\/td>\r\n<\/tr>\r\n
Phytoplankton<\/td>\r\n5<\/td>\r\n100<\/td>\r\n<\/td>\r\n<\/tr>\r\n
Detritus<\/td>\r\n10<\/td>\r\n<\/td>\r\n<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n
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Diets: A straight chain as in the figure. Enter them at the Ecopath > Input > Diet composition<\/em> form. <\/span><\/p>\r\n\r\n<\/div>\r\n

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Fisheries: there's already a fleet defined by default, so go to Ecopath > Fishery > Landings<\/em>,<\/em> and enter a landing of 0.1 t \u00b7 km-2 <\/sup>\u00b7 year-1 <\/sup>of mackerel<\/em>. \u00a0[Yes, we give units, units are important and best left explicit!]<\/span><\/p>\r\nBalance the model (Ecopath > Output > Basic estimates<\/em>) and examine the outputs. Make sure the model is balanced! If not (check your input data), balance it!\r\n\r\nOpen a new scenario in Ecosim by going to Ecosim > Output > Run Ecosim<\/em>, and name it, (e.g, \"Scene 1\"). Click Run<\/em>. What do you see? Why is it flatlining?\r\n\r\nThe two principal ways of forcing Ecosim are through fishing effort (by fishing fleet) or through fishing mortality (by functional group).\r\n

In this tutorial, we change fishing pressure over time. Internally, Ecosim read the fishing pressure from the effort time plot. It knows the Ecopath baseline fishing mortality = catch \/ biomass \u00a0\u2013 with symbols and units, F<\/em> (year-1<\/sup>) = C<\/em> (t km-2<\/sup> year-1<\/sup>) \/ B<\/em> (t km-2<\/sup>). When effort changes, Ecosim changes fishing mortality (F) proportionally for all the groups that are caught by the given fleet.<\/span><\/div>\r\nFirst try to increase fishing for mackerel<\/em> over time by doubling fishing effort for the fleet catching mackerel by drawing an increasing shape at Ecosim > Input > Fishing Effort<\/em>. Run Ecosim again, what happens now. Who increases, who doesn't, why? Discuss cascading effects, does it occur, and how does it propagate through the food chain?\r\n\r\nYou can see the results in more detail if you go to\u00a0Ecosim > Output > Ecosim results<\/em>, and click\u00a0Group<\/em>, landed by. Here you can see how much the biomasses of mackerel<\/em> and anchovy<\/em> changed over time (by default it compares the first year of a run with the last year, though you can change that to get results for any time period). Does the increased catch of mackerel<\/em> cause amplification or dampening through the food web?\r\n\r\n<\/div>\r\n
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To easily compare different runs, you can click\u00a0Show multiple runs<\/em> on the Ecosim > Output > Run Ecosim<\/em> form. \u00a0Also note that you have different options for what to display on this form (though the standard is what is most often used).<\/div>\r\nYou can study the results in more details if you go to\u00a0Ecosim > Output > Group plots<\/em>. These plots are very informative, showing time dynamics of what happens with fishing, predators and prey for each group.\r\n
If you have a lot of small plots (maybe 13) when you open the Ecosim > Output > Group plots<\/em> form, click the Show plots <\/em>form and un-check the plots from Total discards<\/em> on. You'll then have nine plots in a 3 x 3 matrix.<\/div>\r\nEcosim predictions are especially sensitive to vulnerability multiplier settings (Ecosim > Input > Vulnerabilities). <\/em>Vulnerability multipliers are the key foraging arena parameter, they capture density-dependent effects. \u00a0Think of it like this, the vulnerability multiplier expresses how many times a given predator can increase the predation mortality it is causing on its prey, if the predator abundance were to increase to its carrying capacity. A vulnerability multiplier of 1 thus tells us that the predator is at its carrying capacity \u2013 and hence can increase no more unless its prey becomes more abundant. That implies \"bottom-up\" control. Conversely, high vulnerability multipliers (e.g., 100) tell us that the predator is far from carrying capacity \u00a0\u2013 that's \"top-down\" control.\r\n
With the default vulnerability multiplier of 2, a predator can at most double the predation mortality it's causing on its prey.<\/div>\r\nGo to the Ecosim > Input > Vulnerabilities <\/em>form, and set the vulnerability multiplier for mackerel<\/em>\u00a0eating anchovy<\/em> to 5, run the model again, what happens. Reset the vulnerability multiplier to 2.\r\n\r\nTry setting the vulnerability multiplier for anchovy <\/em>eating zooplankton<\/em> to 5. Run again. What happens now? Does anchovy<\/em>\u00a0behave much differently from when using the default vulnerability multiplier?\r\n\r\nFinally, try setting the vulnerability multipliers for all three interactions to 100. Run again. This setting turns the model into a Lotka-Volterra<\/a> model, which tends to be unstable and produce cycles. \u00a0Lotka-Volterra models also tend to self-simplify where groups die out. Did that happen in your model?\r\n\r\nReset your model to default vulnerability multipliers (2).\r\n\r\nAs you can tell from the above, the vulnerability multipliers are important, and we will return to that later when discussing the foraging arena<\/a> and time series fitting, which indeed has vulnerability multipliers<\/a>\u00a0and density-dependence<\/a> as key factors.\r\n\r\nNow let's try fishing some anchovy;<\/em>\u00a0do the following\r\n