Multiple indicator frameworks for assessment and precautionary management

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Multiple indicator frameworksfor assessment and
precautionary management
Mike Smith
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Precautionary approach
Implies that a lack of full scientific certainty
must not be used as a reason for postponing cost
effective measures to prevent environmental
degradation (Principle 15, Rio de Janeiro
Declaration FAO, 1995) The PA requires the
following tasks to be accomplished Establishment
of management objectives Specification of
information required Assessment of the state of
the stock, putting in evidence sources of
uncertainty Definition of the rules for
management decisions, which should be robust to
uncertainty and incomplete knowledge on factors
such as stock identity and dynamics and the
effects of environment (FAO, 1995). Multiple
indicator approaches (including TL systems) can
provide a means of incorporating the above
features for systems where data do not permit
more sophisticated analytical stock assessments
in support of management rules.
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Multiple indicator frameworks
Enable the synthesis of signals from a range of
sometimes empirical indices and indicators by
converting them into qualitative (or very simple
scaled) terms (e.g. good, moderate, bad), such
that they can then all be considered on the same
scale. A framework to assemble, consider and
combine data consisting of (time series of)
indices or indicators that can inform on stock
and fishery health (and potential) and provide a
means for assessment and informing
management They utilise relatively simple
scoring systems, applied to each indicator to
provide indications of stock and fishery health.
Such scoring systems might include
distributional thresholds (e.g. quantiles) and
approaches such as fuzzy set theory/logic can be
used (e.g. to soften knife edged thresholds).
Scoring of individual indicator/indices or of
compound signals may be conditional on the score
or trend of another indicator/index. The choice
of which indicators/indices to use and/or the
weighting of their scores into compound signals
is crucial to the overall outcome and could
introduce subjectivity.
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Indicators
Indicators are defined as variables, pointers or
indices of a phenomenon (Garcia et al. 2000).
They can support the decision making process
by (i) describing the pressures affecting the
ecosystem, the state of the ecosystem and the
response of managers, (ii) tracking progress
towards meeting management objectives (iii)
communicating trends in complex impacts and
management processes to a nonspecialist audience
(Garcia et al. 2000 Rice 2000, 2003 Rochet and
Trenkel 2003). As attributes (of a pressure,
state, response system ) may not be directly
measurable, indicators can act as proxies for
them (Fulton et al. 2004a,b). However, for
indicators to support management decision making,
the relationship between the indicator current
value and/or trend and the value and/or trend of
the variable (or indicator) associated with
meeting the operational objective needs to be
known (Jennings, 2005). Most research has
focussed on indicators for state, however
management usually controls pressure and response
describes the pressure and state changes (i.e.
feedback relationships).
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Desirable properties for indicators (based on
ICES 2005, and Rice and Rochet, 2005)
Concrete directly observable and measurable
rather than abstract or only estimated
indirectly Theoretical based reflect features of
ecosystems and human impact relevant to
objectives and be based on well-defined and
validated theoretical links Consistently
understood public understanding and technical
meaning should be consistent Cost cost-effective
given limited monitoring resources Measurable
measurable using existing instruments, monitoring
programmes and analytical tools, available on
spatial and temporal scales needed for
management, have minimum or known bias and the
signal should be distinguishable from
noise Context supported by existing or
time-series of data to aid interpretation
of trends and to allow a realistic setting of
objectives Sensitive sensitive to changes in the
state, pressure or response it is intended to
measure Responsive provide rapid and reliable
feedback on the consequences of management
actions Specific respond to the properties
intended to be measured rather than to
other factors and/or it should be possible to
disentangle the other effects from the observed
response
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Structure of multiple indicator frameworks
Typically, potential indices are grouped into 3
or 4 categories representing Abundance Early
season catch rate, survey counts, commercial
fishing area, industry perspective Production Numb
er of recruits, mean size, average maximum size,
sex ratio in catches, proportion berried, density
of larvae, condition factors, disease Fishing
pressure Proportion immature in catch, total trap
hauls (per area ground), incidental mortality
(discards or other gears), landings alternative
species, exploitation rate, total mortality,
proportion females in catch, proportion of catch
taken during ovigerous period Ecosystem and
environment - harvest control rules for fish,
have tended to focus on indicators monitoring
(spawning) biomass, recruitment and fishing
mortality, although environmental linkages are
often more predictive for many invertebrates
(Caddy, 2004) Predator abundance, prey abundance,
temperature indices, wind/current flows
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Reference points
Reference points that might support management
decision making include (i) reference points for
no impact, (ii) limit reference points for the
values of indicators associated with serious or
irreversible harm (iii) target reference points
for preferred values of the indicators As
indicator values include error, precautionary
reference points may be needed to guarantee a
high (preferably specified) probability of
avoiding a limit. When indicators are used to
guide management of target stocks, there is a
tradition of setting reference points (FAO 1998).
In other fields, reference points may not be
specified and trajectories or directions may be
used to guide decision making. lt- not that way
or that way -gt(but Im not sure how
far!) Reference directions can guide management
when the value of an indicator is unsatisfactory
or close to a limit, but when a target has not or
cannot be defined (Link, 2002 Trenkel and Rochet
2003 Jennings and Dulvy 2005).
Cliff edge
Increasing fishing impact
unexploited target precautionary
limit
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An example (for shrimp, Koeller et al, 2002)
Each indicator is considered under in methods,
results (and brief interpretation) sections.
Additional supporting information can also be
presented. Traffic light colours were determined
by pre-defined limits for individual indicators,
with default transition boundaries of the 33 and
67 percentiles.
In two cases (commercial CPUE) polarity was
considered to have switched when considered with
other indicators (increased aggregation
decreased survey abundance), but the TL system
did not implement this.
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An example (for shrimp, Koeller et al, 2002)
Halliday et al. (2001) proposed that decision
rules should be based on an integrated score of
indicators measuring at least three
characteristics abundance, production, and
fishing mortality. If the proportion of
indicators triggered within a management rule
determines the severity of management response
some redundancy and smoothing should be
introduced because not all individual indicators
are likely to trigger simultaneously (Caddy
1999a, 1999b).
In this example, the aggregate signals for
abundance were green in recent years, while the
production and fishing mortality signals were
declining to red in 2001. This example was used
for assessment and information only. Management
rules were based on separate simulation
modelling.
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An example using fuzzy logic for an HCR (Murta
Silvert, 2002)
Using a knife edged threshold can lead to
flip-flop which should be avoided (Rice,2003).
For example If Biomass lt Threshold the TAC0
and If Biomass gt Threshold the TAC0.4 Biomass
Fuzzy set theory can be used to allocate biomass
as high or low (above or below a threshold). For
example if a threshold were 500t, then below 250t
could be considered 0 high biomass and above
750t 100 high biomass, with membership between
interpolated. Stochastic output could also be
used.
Now if biomass is at the threshold it is 50 high
and 50 low and the TAC would be obtained by
averaging, i.e. Low biomass High biomass TAC 0.5
0 0.5 0.4 0.2B 250t
Fuzzy sets could also be used to define TAC and a
range of indicators of fishery performance
resulting in control rules of the form If
Biomass is HIGH and Sampling is GOOD and
Assessment model is GOOD and Then TAC will be
LARGE The membership of TAC is then defuzzified
to give a crisp value for the TAC
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References
Caddy, J.F., 1999a. Deciding on precautionary
management measures for a stock based on a suite
of limit reference points (LRPs) as a basis for a
multi-LRP harvest law. NAFO Sci. Counc. Stud. 32
5568. Caddy, J.F., 1999b. A short review of
precautionary reference points and some proposals
for their use in data-poor situations. FAO Fish.
Tech. Pap. No. 379. Caddy, J.F., 2004. Current
usage of fisheries indicators and reference
points, and their potential application to
management of fisheries for marine invertebrates.
J. Fish. Aquat. Sci. 61 13071324. FAO, 1995.
FAO, 1995. Precautionary approach to fisheries.
Part I Guidelines on the precautionary approach
to capture fisheries and species introductions.
FAO Fish. Tech. Pap. 350(1), FAO, Rome, 52 pp.
Reproduced with minor editing as FAO Technical
Guidelines for Responsible Fisheries. No. 2.
FAO, 1998. A short review of precautionary
reference points and some proposals for their use
in data-poor situations. FAO Fisheries Technical
Paper No. 379, 30 pp. Fulton, E.A., Smith,
A.D.M., Webb, H. and Slater, J., 2004a.
Ecological indicators for the impacts of fishing
on non-target species, communities and
ecosystems review of potential indicators.
Australian Fisheries Management Authority Final
Research Report No. R99/1546, 116 pp.
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References
Fulton, E.A., Fuller, M., Smith, A.D.M. and Punt,
A., 2004b. Ecological indicators of the ecosystem
effects of fishing final report. Australian
Fisheries Management Authority Final Research
Report No. R99/1546, 239 pp. Garcia, S.M.,
Staples, D.J. and Chesson, J., 2000. The FAO
guidelines for the development and use of
indicators of sustainable development of marine
capture fisheries and an Australian example of
their application. Ocean and Coastal Management
43, 537556. Halliday, R.G., Fanning, L.P., and
Mohn, R.K. 2001. Use of the traffic light
method in fishery management planning. Can. Sci.
Advisory Secretariat Res. Doc. No.
2001/108. ICES (2005) Guidance on the
application of the ecosystem approach to
management of human activities in the European
marine environment. ICES Co-operative Research
Report No. 273, 22 pp. Jennings S., 2005,
Indicators to support an ecosystem approach to
fisheries. Fish Fish. 6, 212232. Jennings, S.
and Dulvy, N.K. (2005) Reference points and
reference directions for size-based indicators of
community structure. ICES Journal of Marine
Science 62, 397 404.
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References
Koeller, P.A., Cover, M. King, M., 2002. A new
traffic light assessment for the Eastern Scotian
Shelf Shrimp Fishery in 2001. Canadian Science
Advisory Secretariat, 2002. 50pp. Link, J.S.
(2002) Ecological considerations in fisheries
management when does it matter? Fisheries 27,
1017. Murta, A.G. Silvert, W., 2002. A
framework to put in practice a precautionary appro
ach to fisheries assessment based on fuzzy set
theory. ICES CM 2002/ACFM10. WD. Rice, J.C.
(2000) Evaluating fishery impacts using metrics
of community structure. ICES Journal of Marine
Science 57, 682688. Rice, J.C. (2003)
Environmental health indicators. Ocean and
Coastal Management 46, 235259. Rice, J.C. and
Rochet, M.-J. (2005) A framework for selecting a
suite of indicators for fisheries management.
ICES Journal of Marine Science 62, 516527.
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References
Rochet, M.-J. and Trenkel, V.M. (2003) Which
community indicators can measure the impact of
fishing? a review and proposals. Canadian Journal
of Fisheries and Aquatic Science 60,
8699. Trenkel, V.M. and Rochet, M.-J. (2003)
Performance of indicators derived from abundance
estimates for detecting the impact of fishing on
a fish community. Canadian Journal of Fisheries
and Aquatic Science 60, 6785.