In Blue-Matter/MERA: Method Evaluation and Risk Assessment

Management Questions

The Management panel is a set of questions about what fishery management options are available and how well management advice is followed.These questions:

identify what management procedures are feasible given the types of management measures.
determine the relative success of various management procedures that provide different types of advice.

The operating model parameter mappings of each answer are provided in Appendix Table A.2.

Types of fishery management that are possible

Here you indicate which MPs are feasible given the management options that are available. Management procedures can provide management advice in terms of:

Total Allowable Catch limits (TACs, e.g. 20,000 metric tonnes).
Total Allowable Effort (TAE, e.g. 800 trap days per year).
Size limits (e.g. minimum size of 45cm).
Time-area closures (e.g. closing an area to fishing, an MPA or a Winter closure.

For more information see the UN FAO guide to fishery management types.

Or alternatively, Steffanson and Rosenberg describe and discuss fishery managment types in their 2005 paper.

TAC offset

The possible extent to which fishing operations may exceed (overages) or fall short (underages) of the specified Total Allowable Catch (TAC)? For example, given a TAC of 1000 tonnes a 10% offset (overage) would on average lead to 1100 tonnes of fish taken.,

The FAO provides a cursory introduction to uncertainties in fisheries management including implementation error here.

Fulton et al. provide a discussion of implementation error in their 2011 paper.

FigInd<-FigInd+1
plotIB()

Figure r paste(SecInd,FigInd,sep="."). An example of MERA specified TAC offset.

TAC implementation variability

In the previous question you specified the range of the possible TAC offset (mean overage or underage).In this question you add the variability (V) in the implementation of TACs among years.

For example, if on average thereis no TAC offset, a V of 10% leads to annual overages/underages within 20% of the annual TAC recommendation (the black line in the figure opposite) for 95% of cases.

The colored lines show the minimum and maximum variability superimposed on the lowest (dashed line) and highest (solid line) levels of overages/underages specified in the previous question.

FigInd<-FigInd+1
plotIV()

Figure r paste(SecInd,FigInd,sep="."). An example of MERA specified TAC implementation variability.

TAE offset

What is the possible extent to which fishing operations may exceed (overages) or fall short (underages) of the specified Total Allowable Effort (TAE)?

For example, given a TAE of 2000 boat-days of fishing a 10% overage would on average lead to 2200 boat days of effort.

Note: you have the option of selecting MATCH TAC IMPLEMENTATION and mimicking the TAC offset (e.g. assuming that if more than the TAC is taken due to lack of enforcement there would be a similar discrepancy between recommended and implemented TAE)

FigInd<-FigInd+1
plotIV_E()

Figure r paste(SecInd,FigInd,sep="."). An example of MERA specified TAE offset.

TAE implementation variability

In the previous question you specified the range of possible TAE offset (mean overages/underages). In this question you add the variability (V) in the implementation of TAEs among years.

For example, if on average there is no TAE offset, a V of 20% leads to annual TAE overages/underages within 40% of the annual TAE recommendation (the black line in the figure opposite) for 95% of cases.

The colored lines show the minimum and maximum variability superimposed on the lowest (dashed line) and highest (solid line) levels of overages/underages specified in the previous question.

As with the offset, you have the option of matching the TAC implementation variability.

FigInd<-FigInd+1
plotIV_E()

Figure r paste(SecInd,FigInd,sep="."). An example of MERA specified TAE implementation variability

Size limit offset

What is the possible extent to which fishing operations may exceed (catch larger) or fall short (catch smaller) fish than the specified minimum size limit? For example, given a size limit of 20cm (e.g. escape hole size of a trap), a value of 20% would lead to a mean minimum size in the catch of 24cm.

Note that if you match TAC implementation variability this will be inverted for size limits (going under the minimum size limit is assumed equivalent to going over the TAC).

FigInd<-FigInd+1
plotIB_SL()

Figure r paste(SecInd,FigInd,sep="."). An example of MERA specified size-limit offset

Size limit implementation variability

In the previous question you specified the range of possible mean violations of a minimum size limit. In this question you add variability (V) in size limit implementation among years.

For example, a size limit of 90cm is exceeded by an average of 10cm, a value of 5% leads to minimum catch sizes of between 90cm and 110cm (the black line in the figure opposite) for 95% of cases. The colored lines show the minimum and maximum variability superimposed on the lowest (dashed line) and highest (solid line) offset in size limit specified in the previous question.