fcs2-package: Fisheries Classification Scheme 2 For SNIFFER

Description Details Author(s)

Description

Provides functions that carry out SNIFFER's implementation of the Environment Agency's Fisheries Classification Scheme 2 (FCS2). This package was developed for use in Scotland, Northern Ireland and the Republic of Ireland as part of SNIFFER project WFD68c: Science Work.

Details

The main functions are fcs2FitModel which fits the FCS2 statistical model, fcs2JointEQR which calculates samples of the joint EQR and fcs2Classify which uses these to produce probabilistic WFD classifications.

The FCS2 approach consists primarily of two main tasks:

  1. Fit the statistical model for each species.

  2. Produce EQRs and classifications.

This package provides functions for carrying out all stages of this analysis. Other packages may be of use, for example RODBC can be used to read data into from a database.

Fitting the model for a single species consists of the following steps:

  1. Select covariate terms for prevalence and abundance regressions.
    For this, fcs2FitModel can be used with runBUGS = FALSE to find approximate parameter estimates using INLA with which to judge the significance of each suggested term. Alternatively fcs2ModelSelection can be used to automatically select a set of significant regression terms.

  2. Set prior distributions.
    Default priors are given but plot.fcs2Fit and fcs2Priors can be used to check the priors so that they can be modified if necessary before fitting the full Bayesian model.

  3. Fit the full model.
    fcs2FitModel used with runBUGS = TRUE will fit the model using MCMC via either WinBUGS or OpenBUGS. This can take much time.

  4. Check Monte Carlo samples.
    The convergence of the MCMC chains can be checked with plotBUGSTrace and the sample can be thinned if necessary with thinBUGSSamples.

After fitting the model for every species, the EQRs and classifications can be found by the following steps:

  1. Select values for pressure variables at reference conditions.
    Observed values of pressure variables are replaced with reference values for the model to make predictions of reference conditions.

  2. Calculate EQR samples.
    fcs2SingleEQR can calculate EQRs for single species and surveys and fcs2JointEQR calculates combined EQR values.

  3. Select EQR class boundaries.
    These may be selected by comparing the mean EQR values produced from surveys of each class.

  4. Calculate probability of each class.
    This can be calculated using fcs2Classify.
    Alternatively, the function fcs2EQRSummaryMatrix can be used to provide a tabulated summary of joint and single EQRs as well as probabilities of class.

Author(s)

David Wyncoll d.wyncoll@hrwallingford.co.uk of HR Wallingford http://www.hrwallingford.co.uk for SNIFFER http://www.sniffer.org.uk


aquaMetrics/fcs2 documentation built on Aug. 21, 2021, 12:55 p.m.