Transpose enables the conversion of data pertaining to specific taxa or functionnal groups into data by trophic class. Data can represent catches, biomasses or production in order to produce continuous distributions of those variables over trophic levels.
ET-Transpose provides a picture of an ecosystem under a given fishing mortality. ET-Diagnosis is a routine simulating how this baseline ecosystem would be impacted by increasing or decreasing fishing effort. Fishing effort can be modified per fleet and/or trophic group. Ecosystem-wide effects of altering fishing effort include potential changes in biomass, accessible biomass, production, kinetics and catch trophic spectra, as well as impacts on the mean trophic level of the catch and biomass. Additionally, ET-Diagnosis constitutes a useful exploratory tool for ecosystem-based management. It simulates how reducing or increasing fishing effort and/or preferentially targeting different trophic levels could improve yield at the ecosystem scale. Lastly, ET-Diagnosis allows to view how different assumptions on ecosystem functioning (biomass input control, top-down effect) affect both trophic level specific and ecosystem-wide properties in relation to fishing.
This example dataset is extracted from the 2004 Guinean Ecopath model (Gascuel et al., 2009). It provides a template for the input table formatting, the wanted variables names and the different capabilities of this package (used in function's examples).
create.smooth is used to create a smooth function. This function enables the conversion of data pertaining to specific taxa or functional groups into data by trophic classes. The main assumption of this Smooth function is that the distribution of the biomass (or catch...) of a trophic group around its mean trophic level follows a lognormal curve. The curve is defined by a mean (the mean TL of the trophic group) and a standart deviation (sigma), which is a measure of the trophic level variability within the group. The distribution is then defined by the lognormal function LN(mean TL, sigma).
This function loads input data from an xml file created by the user, or exported from the EwE EcoTroph plug-in, or from a web service associated to a database populated with parameters of several EwE models.
CTSA.forward enables to estimate biomass, biomass flow, kinetic of an ecosystem starting from a biomass or biomass flow at TL=1, catches, transfer efficiencies, and kinetics at virgin state.
CTSA.catch.input is used to create inputs for the CTSA.forward function. It is a list of data.frames referring to catches per fleet formatted with TL classes in rows and trophic groups in columns.
This function enables the display of the principle plots resulting from the create.ETmain function: Biomass Trophic Spectra, Accessible Biomass Trophic Spectra, Catch by fleet Trophic spectra, Total Catch Trophic Spectra and other summary plots.
E_MSY_0.1 computes two indices of exploitation: Emsy or Fmsy (maximum sustainable yield), and E0.1 or F0.1 ("start" of full exploitation) per TL class.
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