TABLE 2:
Proposed Non-detriment Finding (NDF) Format for Queen Conch Producing and Trading Countries
RAPID ASSESSMENT FORMAT
Species: Queen Conch (Strombus gigas)
Country: ________________________
Conservation status of the species: (IUCN Red List): _________________
National Status: ___________________
Date of last NDF: _____________________
Date of new NDF: ____________________
Responsible Officer of Competent Scientific authority: _____________________________
Position in Organization: _____________________
Observations:
CATEGORIES
1.1 Species identity
DESCRIPTION
INDICATORS
Provide correct taxonomy and nomenclature of Strombus species found in
national waters.
Indicate for synonyms and local names.
Provide overall opinion on reliability, accuracy, consistency and
comprehensiveness of data used.
In the evaluation the SA should remember that the quality and quality of
information is proportionally to the degree of resource affectation.
For CITES this preliminary and overall indicator is important a it sets the tone
for the level of precaution that will be applied to any TAC.
Strombus species:
Adults per hectare benchmarks:
3.1 National distribution
Density of adults per hectare is one of the most easily measured and monitored
attributes for assessing the likelihood of survival of queen conch populations.
Despite various expert opinions and regional differences, in addition to CITES
indicator of 56 adults per hectare there appears to be a regional consensus.
1. Provide information on the average density of adults per hectare from local
studies.
2. Provide information on adult per hectare densities currently taken as
benchmark by national fisheries authorities
3. Provide information on suggested adult per hectare density as regional
reference standard.
There are generally substantial differences in the spatial distribution patterns as
the result of depth, substrate, food requirements and factors which contribute to
overall mortality.
1. Provide information on availability of spatial distribution per fishing area.
2. Provide data on underlying factors for geographical distribution per life
stage.
3. Provide information of sub-populations detected.
4. Mention which biological parameters are included in national distribution
analysis.
5. Indicate the protocol or methodology used in national queen conch
distribution analysis.
3.2 National abundance
The spatial abundance by individual fishing banks should be included in stock
Resource abundance survey data:
1.2 Application data accuracy
2.2 Population density and adults
per hectare
REF.
Local names:
Overall qualitative and quantitative level of data
in relation to state of resource:
 Low
 Medium
 High
 Don’t know
- CITES: 56 adults/ha.
1. National average:
2. National benchmark:
3. Suggested regional minimal benchmark:
Appeldoorn et al., 2011
NMFS – ESA, 2014 (pag.
18-20).
Stoner and Ray-Culp,
2000
QCWG, Miami, 2012
Resource distribution surveys data:
1. Resource distribution maps:
2. Underlying factors:
3. Sub-populations detected:
4. Biological parameters included:
5. Protocol / methodology utilized:
CFMC Manual on Queen
assessment activities.
1. Provide information of population baseline studies..
2. Inform about stock abundance per fishing area
3. Indicate the protocol or methodology used in national queen conch
abundance analysis.
3.9 Quality of queen conch sector
related information
Provide overall opinion based on reliability, accuracy, consistency and
comprehensiveness of available sources and data.
1. Inform on the type of information which is generally used.
2. Report on the overall quality of information used..
4.2 Management plan or
equivalent
The existence of a management plan and its effectiveness in terms of execution,
monitoring, control and compliance, is of major importance to the SA.
Information needed for the evaluation consists of :
1. Orientation of the management plan.
2. Purpose of management plan.
3. Type of management plan
4. Effectiveness analysis of management performance.
5. Current institutional and legal framework.
4.6 Confidence in effectiveness of
harvest management
Confidence in the management of the harvest is a key factor in the sustainable
exploitation of the resource. Confidence and effectiveness go hand in hand.
1. Evaluate factors that impact on the effectiveness of the plan and affect the
confidence in the harvest management. Indicate level of confidence on a
scale from 1 to 4.
(Scale: 1- Very little; 2- little; 3–Regular; 4- Substantial)
5.2 Harvest quotas
Harvest quotas are a major tool to limit fishing effort and overall exploitation
levels, when correctly applied and duly enforced. Within the queen conch
fishery, a number of quotas options can be employed by the competent
authorities and which can be evaluated by the SA by obtaining information on
1. Baseline studies.
2. Spatial stock abundance data or maps:
3. Protocol /methodology used:
1. Type of data:
 Quantitative (in %):
 Qualitative (in %):
2. Overall quality level of data:
 Low
 Medium
 High
Elements of management plan:
1. Orientation of plan:
 Adaptive.
 Co-management.
 Eco-system.
 Other
2. Purpose of management plan:
- Economic
- Socio-economic
- Commercial
- Ecological
- Other
3. Type of management plan :
 Queen conch specific.
 Part of management plan of other species.
 Fisheries generic.
4. Effectiveness analysis:
 SWOT
 Other
5. Institutional arrangements:
5. Legal frame work:
Confidence and effectiveness of management
hampered by:
 Budget restrictions.
 Shortage of (trained) personnel.
 Lacking enforcement.
 Failing feedback.
 Limited stakeholders involvement.
 Others:
Evaluation of harvest quotas:
1. Type of quota
 Scientific
 Commercial
Conch Stock Assessment.
Ehrhardt, 2008
the following issues:
1. Indicate if, in addition to the commercial harvest quota, a scientific harvest
quota has been allotted to the country by CITES. Provide total quota
allocated and filled.
2. Provide information on origin of quota.
3. Indicate if quotas are applied by producers’ sub-groups.
4. Indicate if fishing quotas are established y fishing area on the basis of
population dynamics analysis.
5. Evaluate trend in harvest quota and levels of compliance.
5.8 Confidence in harvesting data
The SA will need to evaluate the quality of the harvest data as harvesting is the
factor with the major influence on the sustainability levels of the resource. The
different ways queen conch is harvested and processed complicate the uniform
data collection.
1. Review the factors that affect the confidence level of the data.
2. Evaluate the confidence levels in harvesting data. (scale 1-4)
(Scale: 1- None; 2- Limited; 3–Average; 4-High)
6.1 Monitoring methods used
Monitoring systems are essential to the effective functioning and control of
relevant parameters.
1. Evaluate monitoring activities in three categories:
A. Biological aspects:
B. Harvesting aspects: (Incl. IUU)
C. Trade aspects: (Incl. IUU)
6.2
SA has to evaluate which factors affect in a positive or negative way the
confidence levels in the established monitoring systems
Confidence in monitoring
1. Establish levels of monitor confidence affectation by evaluating the impact
and performance levels of the mentioned factors, on a scale from -2 to +2.
(Scale: -2 very negative; -1 negative; 0-no affectation; +1 positive; +2-very
positive)
2. Origin of harvest quota:
 Voluntary established based on population
dynamics and CITES approved.
 CITES imposed.
3. Harvest quota per fishers’ sub-group:
 Recreational
 Subsistence
 Independent artisanal
 Industrial
4. Harvest quota by fishing area:
5. Trend in harvest quotas and levels of
compliance:
Factors that influence in the confidence levels of
data:
 No reporting.
 Processing at sea.
 Incongruity in live to meat conversion factors.
 Effectiveness of monitoring systems.
 Others:
1. Monitoring methods:
A. Biological aspects:
 Direct stock assessment
 Habitat and biodiversity observations.
 Internet and literature.
 Others:
B. Harvesting aspects:
 Revision of logbooks.
 VMS records.
 On-board observers.
 Processing plant records.
 Landing sites (incl. atolls).
 Surveillance.
 National statistics.
 Others:
C. Trade aspects:
 Export/import statistics.
 Market trend studies.
 Others:
1, Confidence in monitoring depend on:
 Periodicity of reviews
 Quality of data sources used
 Collaboration from private sector
 Levels of competence at
management
authority
 Inter-institutional collaboration
 Level and effectiveness of enforcement
McGowan and Hay,
2008.
8.2 Products & destination
8.8 Confidence in trade data
 Compliance levels
 Qualitative feedback on adjustments
 Peer reviews
 Levels of IUU
 Efficient data bases
 Others:
Five products are generally produced on the basis of queen conch (for last year on record):
Market share in volume and
Destination
Estimated %
value
IUU in total
volume
In volume
In value
Export
Local
Subsistence
Total
traded
(kilos)
(US$)
Countries
%
%
%
%
%
100%
%
 Meat (clean
fillets)
%
%
%
%
%
100%
%
 Trimmings
%
%
%
%
%
100%
%
 Pearls
%
%
%
%
%
100%
%
 Operculum
%
%
%
%
%
100%
%
 Whole
shells
%
%
%
%
%
100%
%
 Other
100%
100%
Total
Trade data are often subject to over or under reporting by producers, processors
and traders depending on prevailing tax, incentive regimes and/or established
quotas.
1. Identify trade data sources.
2. Evaluate the confidence levels in trade data sources. (scale 1-4)
(Scale: 1- None; 2- Limited; 3–Average; 4-High)
1. Trade data sources:
 National statistics
 Statistics importing countries
 FAO statistics
 CITES statistics
 Exporters’ records
 Local market information
 Others
Confidence levels in trade data sources: (1-4)
 National statistics
 Statistics importing countries
 FAO statistics
 CITES statistics
 Exporters’ records
 Extrapolated landing data
 Others: