Empirical and other stock assessment approaches

1
Empirical and other stock assessment approaches

• FMSP Stock Assessment Tools
• Training Workshop
• Bangladesh
• 19th - 25th September 2005

2
Reference points from minimal population
parameters (Beverton Holt invariants)

• Assume that a species has an average life history
  pattern, with the following relationships
• M / K 1.5,
• M tm 1.65, and
• Lm 0.66
• (where M is natural mortality, K is the growth
  rate, tm is the age at maturity and Lm is the
  length at maturity as a proportion of the
  asymptotic length L8, see Chapter 11).

FAO Fish. Tech. Paper 487 Section 4.2, Chapter
11
3
Inputs and outputs from Beverton Holt
invariants method
See FAO Fish. Tech. Paper 487 Section 4.2,
Chapter 11
4
Setting fishing effort in multi-species fisheries

• FMSP Project R5484 derived guidelines for setting
  F in multi-species, deep reef-slope, hook and
  line fisheries
• Management by size limits not practical for hook
  and line fisheries
• No detectable evidence of biological interactions
  (competition, predation, prey release etc)
• Estimate FMSY as a proportion of M, based on Lc50
  and Lm for each key species (see next slide)
• Set overall multi-species F as required for most
  vulnerable species

Section 4.4, Chapter 12
5
Setting fishing effort in multi-species fisheries
Lm 0.5 L8
Lm 0.7 L8
Section 4.4, Chapter 12
6
Empirical approaches

• Predicting yields from other similar sites
• based on resource areas and fishing effort
• Multivariate modeling of fishery systems
• GLM approaches
• Bayesian network approaches
• See FAO Fish. Tech. Paper 487, Chapter 14

Section 4.7, Chapter 14
7
Predicting yields from resource areas, by
habitat type

• Asian river fisheries African lakes
• loge catch 0.9 0.096 loge area loge catch
  2.668 0.818 loge area

Section 4.7, Chapter 14
8
Predicting yields from resource areas and fishing
effort
Maximum yield (MY) 13.2 t km-2 yr-1 132 kg ha-1
yr-1 At effort of 12 fishers km-2
For data sets FTR for FMSP Project R7834 at
http//www.fmsp.org.uk/FTRs.htm
Section 4.7, Chapter 14
9
Multivariate modelling of fishery systems

• Management performance (outcome) variables
• Production / yield / sustainability /
  biodiversity
• Well being of fishers / fishing households etc
• Institutional performance equity / compliance
  with rules etc
• Explanatory variables
• Resource / environment
• Technology fishing gear / fishing effort /
  stocking etc
• Community characteristics
• Management characteristics decision making
  institutions etc
• Fishing effort is not always the most important
  factor!

Section 4.7, Chapter 14
10
Multivariate modelling methods

• General Linear Modeling (GLM) methods for dealing
  with quantitative management performance
  indicators (or outcome variables) such as indices
  of yield or abundance
• Bayesian network models for qualitative
  performance indicators such as equity, compliance
  and empowerment, that must be subjectively
  measured or scored along with many of the
  explanatory variables
• Useful for adaptive management and co-management
  in inland and coastal fishery systems (divisible
  into resource/village units)
• See Final Technical Reports for FMSP Projects
  R7834 (analysis methods) and R8462 (data
  collection for co-management) at
  http//www.fmsp.org.uk/

Section 4.7, Chapter 14
11
Example of a Bayesian network model

• Input variables
• Output variables
• Compliance,
• CPUE change
• Equity

12
Example of a Bayesian network model

• Exploring the effects of government management on
  outcomes

13
Example of a Bayesian network model

• Inputs most likely to achieve favourable states
  in all three of the main management outcomes
  simultaneously

14
Special approaches for inland fisheries

• Management guidelines for Asian floodplain river
  fisheries
• See Hoggarth et al (1999) - FAO Fish. Tech. Pap.
  384/1
• http//www.fao.org/DOCREP/006/X1357E/X1357E00.HTM
  
• http//p15166578.pureserver.info/fmsp/r8486.htm
• Stocking models
• See analysis of eight stocking projects by FMSP
  Project R6494 (summarised in Hoggarth et al,
  1999, Part 2)
• And forthcoming ParFish-based stocking model
• Adaptive management
• See Garaway and Arthur (2002), and other papers
  from FMSP projects R7335 and R8292
  (http//www.adaptivelearning.info/)

Section 4.8