This document describes the development of a sensitivity assessment tool for spatially and temporally managing fishing techniques. The tool aims to assess the sensitivity of different marine species to various pressures from fishing gear by evaluating intolerance and recoverability on species-specific traits. Sensitivity scores and maps are generated to identify impacts across gears, times, and locations. Uncertainty from data limitations is explicitly addressed. The tool takes a comprehensive, evidence-based approach to balance knowledge gaps and facilitate marine spatial planning.

1. SENSITIVITY ASSESSMENT
A TOOL FOR SPATIO-TEMPORAL MANAGEMENT
OF FISHING TECHNIQUES
Jochen Depestele
Wouter Courtens, Steven Degraer, Jan Haelters, Kris Hostens, Hans Polet,
Marijn Rabaut, Eric Stienen, Sofie Vandendriessche, Magda Vincx
29 September 2011
World Conference on Marine Biodiversity
Institute for Agricultural and Fisheries Research
www.ilvo.vlaanderen.be/wako

2. Question?

3. Question?
Which fishing gear is the least damaging?

4. Objective: Develop a tool !
1. No black or white pill can cure
nuances anticipated
Include spatial and temporal aspects
2. No longer see the wood for the trees
few data, but many effects
How to deal with this?

5. Tool = SENSITIVITY ASSESSMENT !
What?
INTOLERANCE
SENSITIVITY
RECOVERABILITY
Existing applications? Range of …
 ecosystem components
 activities
 terminologies
But also: APROACHES !

6. Roadmap
SCOPING
SELECTION OF UNIT OF ANALYSIS
uncertainty
SPEC. SENSITIVITY ASSESSMENT
SENSITIVITY MAPS

7. Roadmap
SCOPING
Assumptions & limitations
1 fishing „event‟
no reference condition
SELECTION OF UNIT OF ANALYSIS
uncertainty
Which marine feature? How?
(1) species within
(2) adult specimen
(3) which species?
SPEC. SENSITIVITY ASSESSMENT
SENSITIVITY MAPS

8. Roadmap
SCOPING
SELECTION OF UNIT OF ANALYSIS
uncertainty
SPEC. SENSITIVITY ASSESSMENT
recoverability assessment
intolerance assessment
SPECIES
PRESSURES
SENSITIVITY
FISHING SPECIES INDEX
TRAITS
SENSITIVITY MAPS

9. Intolerance: pressure selection
 Be comprehensive:
 Rio de Janeiro Declaration (1992):
“lack of full scientific certainty shall not be used as a
reason for postponing cost-effective measures to
prevent environmental degradation”
 Pressure categories: DBP, IBP, IPP, ICP
 Pressures:
 within ecosystem components
 for both fishing gears
 With or without stakeholders

10. Intolerance: scoring principle
Objective = discriminate species and gears
“+3” “-3”
(neg intolerance = pos effect)
Scoring mechanisms
1. Quantitative data
2. Traits-based scoring
3. No information

11. Intolerance: scoring example
 DBP = “extraction of epibenthic spp.”
Mortalities Beam trawl Trammel net
catch X X
tow path X /
ghost fishing / X
others N.N. N.N.
No information:
Highlight lack of data
or
Delphi-technique for scoring

12. Intolerance: scoring example
 DBP = “extraction of epibenthic spp.”
Mortalities Beam trawl Trammel net
catch X X
tow path X /
ghost fishing / X
others N.N. N.N.
Quantitative data available:
- standardize by fishing effort or landings
- divide in 4 equal parts for scoring

13. Intolerance: scoring example
 DBP = “extraction of epibenthic spp.”
Mortalities Beam trawl Trammel net
catch X X
tow path X /
ghost fishing / X
others N.N. N.N.
Traits-based approach (modified ERAEF)
- encounterability
- selectivity
- post-capture mortality

14. Intolerance: scoring example
 DBP = “extraction of epibenthic spp.”
Mortalities catch tow path ghost Weighed
Factor 0.1 0.9 0.1*0.15 sum
Beam Trawl
Asterias rubens 2 1 0 1.1
Liocarcinus holsatus 3 2 0 2.1
Ophiura ophiura 2 3 0 2.9
Trammel Net
Asterias rubens 2 0 0 0.2
Liocarcinus holsatus 3 0 2 0.33
Ophiura ophiura 0 0 0 0

15. Intolerance: scoring example
 DBP = “extraction of epibenthic spp.”
Mortalities catch tow path ghost Weighed
Factor 0.1 0.9 0.1*0.15 sum
Beam Trawl
Asterias rubens 2 1 0 1.1
Liocarcinus holsatus 3 2 0 2.1
Ophiura ophiura 2 3 0 2.9
Trammel Net
Asterias rubens 2 0 0 0.2
Liocarcinus holsatus 3 0 2 0.33
Ophiura ophiura 0 0 0 0

16. Intolerance score
Towards one intolerance score?
 Worst case scenario/score (ie. lethal)
 Weighing based on expert judgement
lethal scores can be worse than others?
 Adding up all pressures
but aggregated in well thought categories
 Pressures per category without adding up
Scoring ~ N(pressures)

17. Recoverability
= ability to return to a state before disturbance
 bio-geographical population size
 opportunistic equilibrium
(Life history traits: clutch size, growth rate…)

18. Sensitivity
= f(intolerance, recoverabilty)
 Single ranking of species over gears
 Expert-based
 matrix
 (a)symmetric
Recoverability
Low Moderate Immediat
Very low High (1 - Very high
None (>10–25 (>5 -10 e (< 1
(>25 yr.) 5 yr.) (<1 yr.)
yr.) yr.) week)
High Very high Very high High Moderate Moderate Low Very low
Intermediate Very high High High Moderate Low Low Very Low
Low High Moderate Moderate Low Low Very Low NS
Intolerance
Tolerant NS NS NS NS NS NS NS
© MarLIN
Tolerant* NS* NS* NS* NS* NS* NS* NS*
Not relevant NR NR NR NR NR NR NR

19. Sensitivity
= f(intolerance, recoverabilty)
 Single ranking of species over gears
 Algorithm-based
 intol * recov
 Euclidean distance
 SI  1  e  (int/ rec )
© Smith et al. (2007)

20. Sensitivity maps
Gear * time period X
 Stelzenmüller et al. (2010): Species X Ecosystem
component
POspecies * SI species
S species  1 S
max SI allspecies
 Spatial scale
~ bio-geographical population S
of ecosystem component
S

21. Sensitivity maps
Gear * time period X
 Stelzenmüller et al. (2010): © INBO
POspecies * SI species
S species  1
max SI allspecies
 Spatial scale
~ bio-geographical population
of ecosystem component
beam trawl in winter
S f(DBP, density)

22. Sensitivity maps
Gear * time period X
 Stelzenmüller et al. (2010): © INBO
POspecies * SI species
S species  1
max SI allspecies
 Spatial scale
~ bio-geographical population
of ecosystem component
trammel net in winter
S f(DBP, density)

23. Sensitivity maps
Gear * time period X
 Stelzenmüller et al. (2010): © INBO
POspecies * SI species
S species  1
max SI allspecies
 Spatial scale
~ bio-geographical population
of ecosystem component
trammel net in summer
S f(DBP, density)

24. Roadmap
SCOPING
SELECTION OF UNIT OF ANALYSIS
uncertainty
SPEC. SENSITIVITY ASSESSMENT
SENSITIVITY MAPS

25. Uncertainty
To avoid that what is not known, remains
not known
 explicit referral to missing data
 Pedigree index
Pedigree criteria low high
Proxy of pressure-species
Understanding of activity-pressure
Empirical basis
Methodological rigour
Validation

26. Uncertainty
To avoid that what is nottheory
Preliminary known, remains
e.g. vessel disturbance
not known
 explicit referral to missing data good fit for measure
e.g. discard survival from
 Pedigree index tank experiments
Pedigree criteria low high
Proxy of pressure-species
Understanding of activity-pressure
Empirical basis
Methodological rigour
Validation

27. Uncertainty
Local, in situ data
To avoid that what is not known, remains
Acceptable method,
Preliminary theory
e.g. vessel disturbance
not known
limited consensus on
reliability
 explicit referral to missing data
e.g. discard estimation
good fit for measure
from LFD-selectivity e.g. discard survival from
 Pedigree index tank experiments
Pedigree criteria low high
Proxy of pressure-species
Understanding of activity-pressure
Empirical basis
Methodological rigour
Validation
Replicated?
e.g. 3 peer-reviewed papers

28. Lessons learnt
I’m starting to see the wood for the trees!

29. Lessons learnt
I’m starting to see the wood for the trees!
Comprehensive approach
Spatially and temporally explicit
Qualitative information
=/=
no assessment

30. Thank you for your attention
Contact: Jochen.Depestele@ilvo.vlaanderen.be
Website: www.ilvo.vlaanderen.be/wako
Financially supported by
Institute for Agricultural and Fisheries Research
www.ilvo.vlaanderen.be/wako