Changes between Version 3 and Version 4 of EwEugVulnerabilitiesInEcosim


Ignore:
Timestamp:
2010-11-21 22:35:53 (9 years ago)
Author:
shermanl
Comment:

--

Legend:

Unmodified
Added
Removed
Modified
  • EwEugVulnerabilitiesInEcosim

    v3 v4  
    11== 3.3 Vulnerabilities in Ecosim == 
    22 
    3 One of the most important features of Ecosim is its ability to allow exploring the implications on system dynamics of different views of how the biomass of different groups in the ecosystem is controlled.  The two extreme views are ‘predator’ control’ (also called top-down control) and ‘prey control’ (or bottom-up). We model this using ‘vulnerabilities,’ which represent the degree to which a large increase in predator biomass will cause in predation mortality for a given prey. Low vulnerability (close to 1) means that an increase in predator biomass will not cause any noticeable increase in the predation mortality the predator may cause on the given prey (see Figure 3.1). A high vulnerability, e.g., of 100, indicates that if the predator biomass is for instance doubled, it will cause close to a doubling in the predation mortality it causes for a given prey. 
     3One of the most important features of Ecosim is its ability to allow exploring the implications on system dynamics of different views of how the biomass of different groups in the ecosystem is controlled.  The two extreme views are 'predator' control' (also called top-down control) and 'prey control' (or bottom-up). We model this using 'vulnerabilities,' which represent the degree to which a large increase in predator biomass will cause in predation mortality for a given prey. Low vulnerability (close to 1) means that an increase in predator biomass will not cause any noticeable increase in the predation mortality the predator may cause on the given prey (see Figure 3.1). A high vulnerability, e.g., of 100, indicates that if the predator biomass is for instance doubled, it will cause close to a doubling in the predation mortality it causes for a given prey. 
    44 
    5 If we illustrate the relationship between predator biomass and ''Q/B'' (this is not an assumption in the actual Ecosim calculations) and assume that the predator in question does not cause any substantial (actually no) change in the prey biomass, we can calculate the relative ''Q/B'' for the predator (see Figure 3.1). For higher predator biomass a change will result in relatively stable predation mortality. Hence, if biomass is impacted so as to cause a reduction, the individual predators will get more, their ''Q/B'' increase and this will largely compensate for the reduction in their abundance, bringing the biomass back up again. At lower biomass ''Q/B'' will also increase, but to a lower degree. This is illustrated in Figure 3.2 showing how halving or doubling the predator biomass will impact the relative ''Q/B''. At high biomasses, halving biomass results in close to a doubling in ''Q/B'', which will tend to keep biomass high. There is, however, less and less relative surplus production as we move to the left on the curve. If biomasses are doubled instead, the ''Q/B'' will be decreased when biomasses are high, resulting in a decrease in biomass back toward the original level, i.e., the biomasses will be stable when close to carrying capacity (where v’s are low), and unstable when far below carrying capacity (where v’s are high). 
     5If we illustrate the relationship between predator biomass and ''Q/B'' (this is not an assumption in the actual Ecosim calculations) and assume that the predator in question does not cause any substantial (actually no) change in the prey biomass, we can calculate the relative ''Q/B'' for the predator (see Figure 3.1). For higher predator biomass a change will result in relatively stable predation mortality. Hence, if biomass is impacted so as to cause a reduction, the individual predators will get more, their ''Q/B'' increase and this will largely compensate for the reduction in their abundance, bringing the biomass back up again. At lower biomass ''Q/B'' will also increase, but to a lower degree. This is illustrated in Figure 3.2 showing how halving or doubling the predator biomass will impact the relative ''Q/B''. At high biomasses, halving biomass results in close to a doubling in ''Q/B'', which will tend to keep biomass high. There is, however, less and less relative surplus production as we move to the left on the curve. If biomasses are doubled instead, the ''Q/B'' will be decreased when biomasses are high, resulting in a decrease in biomass back toward the original level, i.e., the biomasses will be stable when close to carrying capacity (where v's are low), and unstable when far below carrying capacity (where v's are high). 
    66 
    77If vulnerabilities are high, the amount of prey consumed by the predator is the product of predator x prey biomass, i.e., the predator biomass impact how much of the prey is consumed.  Such situation may occur in situation where the prey has no refuge, and is thus always taken upon being encountered by a predator. Such top-down control, also known as Lotka-Volterra dynamics, easily leads to rapid oscillations of prey and predator biomasses and/or unpredictable behaviour. 
    88 
    9 The converse (bottom-up control) is the situation that occurs when a prey is protected most of the time, (e.g., by hiding in crevices) and becomes available to predators only when it leaves the feature that protects it. Here being caught is a function of the preys behaviour.  Bottom-up control usually leads to unrealistically little biomass changes in the prey and predator(s) concerned, but which usually do not propagate through the other elements of a food web. 
     9The converse (bottom-up control) is the situation that occurs when a prey is protected most of the time, (e.g., by hiding in crevices) and becomes available to predators only when it leaves the feature that protects it. Here being caught is a function of the prey's behaviour.  Bottom-up control usually leads to unrealistically little biomass changes in the prey and predator(s) concerned, but which usually do not propagate through the other elements of a food web. 
    1010 
    11 To model this aspect of predator-prey interactions, the group biomasses (B) on the underlying Ecopath model were reconceived in Ecosim as consisting of two components, one vulnerable, the other invulnerable to predation (B and V, respectively in Figure 3.3). Further, it is assumed that there is a flow (''''v,,ij,,'''') of organisms from the invulnerable to the vulnerable stage, and conversely (''v,,ji,,''), with the assumption v = ''''v,,ij,,'''' = ''v,,ji,,''. 
     11To model this aspect of predator-prey interactions, the group biomasses (B) on the underlying Ecopath model were reconceived in Ecosim as consisting of two components, one vulnerable, the other invulnerable to predation (B' and V, respectively in Figure 3.3). Further, it is assumed that there is a flow (''''v,,ij,,'''') of organisms from the invulnerable to the vulnerable stage, and conversely (''v,,ji,,''), with the assumption v = ''''v,,ij,,'''' = ''v,,ji,,''. 
    1212 
    1313As might be seen in Figure 3.3, when v is high, the rapid replenishment of vulnerable biomass depleted by predator will rapidly drain the invulnerable part of the biomass.  Thus, with v set high, predation control will be top down. Conversely, if v is low, replacement of depleted biomass from the invulnerable to the vulnerable part of the population will be slow, and the amount that the predators consume will be largely determined by the low value of v, rather than by their own biomass.  Thus, when v is low, control is bottom up. 
    1414 
    15 The vulnerability parameters are among the most important parameters that users change to improve the agreement of the model’s predictions with historical data (see [[Time series fitting in Ecosim.htm|Time series fitting in Ecosim]], [[Hints for fitting models to.htm|Hints for fitting models to time series reference data]] and [[Effect of P B Z and vulnerability.htm|Effect of P/B (Z) and vulnerability for time series fitting]]). See [[Vulnerabilities flow control.htm#_Vulnerabilities|Vulnerabilities]] for help on setting vulnerabilities in Ecosim. See [[Fit to time series.htm|Fit to time series]] for help with Ecosim’s parameter search interface. 
     15The vulnerability parameters are among the most important parameters that users change to improve the agreement of the model's predictions with historical data (see [[Time series fitting in Ecosim.htm|Time series fitting in Ecosim]], [[Hints for fitting models to.htm|Hints for fitting models to time series reference data]] and [[Effect of P B Z and vulnerability.htm|Effect of P/B (Z) and vulnerability for time series fitting]]). See [[Vulnerabilities flow control.htm#_Vulnerabilities|Vulnerabilities]] for help on setting vulnerabilities in Ecosim. See [[Fit to time series.htm|Fit to time series]] for help with Ecosim's parameter search interface. 
    1616 
    1717Further reading: Walters and Juanes (1993), Walters et al. (1997), Walters and Korman 1999, and Walters and Martell (2004).