Vanessa Stelzenmueller

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Practical tools, methods and
approaches to support marine
planning
Vanessa Stelzenmüller1, Janette Lee2, Eva Garnacho2
& Stuart Rogers2
1) vTI - Institute of Sea Fisheries, Hamburg, Germany
2) Centre for Environment, Fisheries & Aquaculture Science (CEFAS), Lowestoft, UK
Outline
1. Why do we need marine planning?
2. Practical tools, methods and approaches to support
marine planning
• Example 1: Mapping human activities and human pressures
• Example 2: A geospatial modeling framework to quantify the
risk of cumulative impacts of human activities
• Example 3: BN-GIS framework to assess marine planning
opinions
1. Introduction – Why do we need marine planning?
• Multiple human uses of the sea lead to two types of
conflicts: 1) uses and environment and 2) between
uses
• Potential conflicts should be solved by a more
strategic ecosystem approach to marine management
• A tool to implement an ecosystem approach to marine
management is marine planning (MP)
• Marine planning (MP) manages the spatial and
temporal distribution of human activities to achieve
ecological, economic, and social objectives
• Practical (spatial explicit) tools and methods are
required to support the implementation of MP
2. Tools to support marine planning – Example 1
Example 1: Mapping of human activities and human pressures
2. Tools to support marine planning – Example 1
• How many activities ?
• Where are the busiest areas?
GIS tool to count the
number of activities
2. Tools to support marine planning – Example 1
• From human activities to human pressures - how to
convert fishing activity with physical impact on the seabed in
fishing pressure maps ?
• Time series of VMS data (2001-2006) of UK and non-UK
fishing vessels ≥ 15 m using beam trawls, scallop dredges
and otter trawls
• Conversion of VMS pings to fishing pressure layers
More details on the method in Eastwood et al. (2007), Mills et al. (2007), and
Stelzenmüller et al. (2008)
2. Tools to support marine planning – Example 1
• Annual aggregated fishing pressure as proportion of cell
(2 x 2 nm) fished
Stelzenmüller et al. (2008). ICES Journal of Marine Science, 65: 1081–1091.
2. Tools to support marine planning – Example 1
• Average proportion of UK marine landscapes fished
Stelzenmüller et al. (2008). ICES Journal of Marine Science, 65: 1081–1091.
2. Tools to support marine planning – Example 2
Example 2: A geospatial modelling framework to
quantify the risk of cumulative impacts
• Ecosystem approach to marine management such as
marine planning (MP) needs to consider a range of
human activities
• Human activities vary in their intensities, footprints and
impacts on the marine environment
• MP requires an evaluation of the risk of cumulative and
interactive effects of numerous human activities
2. Tools to support marine planning – Example 2
•
Human activities exert pressures
Human activity 1
Pressure A
Human activity 2
Human activity 3
Pressure B
Human activity 4
2. Tools to support marine planning – Example 2
Ecosystem components are sensitive to different pressures
•
Impact = Pressure * Sensitivity
•
Cumulative impacts = combined impacts
Cumulative Impact
•
threshold
logistic
linear
Ecosystem cannot
provide service
Ecosystem can
provide service
Amount of activity/ activities
modified after Halpern et al. (2008).
2. Tools to support marine planning – Example 2
Activity 1:
footprint and
intensity
Activity 2:
footprint and
intensity
Selection
of human
activities
Activity 3:
footprint and
intensity
…
…
Mapping
ecosystem
components
Mapping of
human
pressures A
Sensitivity
scores of
ecosystem
components
Fuzzyfication of
pressure layers
Mapping of
human
pressures B
Impact maps
…
GIS – Multi-criteria-analysis
CI
CI
CI
CI
scenario 1 scenario 2 scenario 3 scenario 4
Scenario evaluation
Stelzenmüller et al (2010). MEPS 398: 19–32.
2. Tools to support marine planning – Example 2
Human uses geodata - available for UK&W waters
• Fishing (bottom trawling)
• Wind farm (licence areas and application area)
• Oil and gas (well heads and platforms)
Selection
of human
activities
• Cables
• Pipelines
• Aggregates (licence area and application area)
• Disposal
• Other constraining activities (e.g. wrecks, obstructions)
2. Tools to support marine planning – Example 2
Habitat map for
sensitivity
scores
Conner et al (2006)
LS
AR
ES
PR
SCSW
SMSW
SCSM
SMSM
SCSS
SMSS
ISSMO
0.6
0.87
0.6
0.6
0.6
0.6
0.6
0.47
0.47
ISOBS
0.44
1
0.44
0.52
0.52
0.52
0.52
0.44
0.44
ISEXT
0
1
0
1
1
1
1
1
1
………
………
ISSIL
0.2
1
0.2
0.6
0.6
0.2
0.2
0.2
0.2
ISABR
0.6
0.6
0.6
0.86
0.86
0.6
0.6
0.33
0.33
ISHCC
0.2
0.2
0.2
0.2
0.2
0.2
0.2
0.2
0.2
Sensitivity
scores of
ecosystem
components
Taken from DEFRA (2007) Cost
impact of marine biodiversity
policies on business – the
marine bill, London.
2. Tools to support marine planning – Example 2
Impact ABR
Stelzenmüller et al (2008). ICES Journal of
Marine Science, 65:1081-1091
Sensitivity Score ABR
Impact maps
2. Tools to support marine planning – Example 2
RiskCIcell   Pi  LS j  isij  wi
i
GIS Multi-criteria-analysis (GIS - MCA)
Pressure
ranked by
likelihood of
recovery
Scenario 1:
Scenario 2:
Scenario 3:
Scenario 4:
Equal weights
Linear weights
Logistic weights
Simulated
stakeholder
consultation
Pressure
OBS
ABR
HCC
SMO
SIL
EXT
weights Sc1
0.167
0.167
0.167
0.167
0.167
0.167
weights Sc2
0.261
0.223
0.185
0.147
0.109
0.071
weights Sc3
0.632
0.235
0.087
0.032
0.012
0.004
weights Sc4
0.174
0.157
0.163
0.155
0.175
0.177
2. Tools to support marine planning – Example 2
Scenario 1:
Scenario 3:
Equal weights
Logistic weights
2. Tools to support marine planning – Example 2
•
Testing the sensitivity of predicted cumulative impacts by
randomising pressure ranking
Scenario2 weights
0.261
0.223
0.185
0.147
0.109
0.071
sc2 r1
OBS
ABR
SMO
EXT
HCC
SIL
Scenario evaluation
sc2 r2
HCC
OBS
EXT
SIL
ABR
SMO
sc2 r3
EXT
ABR
SIL
HCC
OBS
SMO
sc2 r4
EXT
ABR
HCC
SIL
SMO
OBS
sc2 r5
SIL
ABR
OBS
HCC
SMO
EXT
sc2 r6
SMO
OBS
SIL
HCC
EXT
ABR
2. Tools to support marine planning – Example 2
Conclusions
•
Model outputs depend on input data quality
•
Uncertainty is partly captured by fuzzyfication of pressure
layers - uncertainty remains for sensitivity measures
•
Risk assessment framework highlights both range of
possible modelled scenarios and range of uncertainty
•
For decision making in the case of remaining uncertainty
models with less strong assumptions should be used
2. Tools to support marine planning – Example 3
Example 3: Bayesian Belief networks (BN)-GIS
framework to assess marine planning options
• Visualisation of relationships between sensitive marine
landscapes, human activities, cumulative pressures and
landscape vulnerability
• Spatial assessment of uncertainty of marine planning options
• Baseline scenario – Current status on UK continental shelf
• Scenario 1 – What are the mitigation measures under a
given marine planning objective ?
• Scenario 2 – How does the vulnerability state change after
the implementation of a spatial management measure?
2. Tools to support marine planning – Example 3
CPEC = Σ1-N IntensityHA1 + .. IntensityHAN
Conner et al (2006)
2. Tools to support marine planning – Example 3
SensitivityEC = Σ1-N SensitivityHA1 + ..SensitivityHAN
VulnerabilityEC = CPEC * SensitivityEC
2. Tools to support marine planning – Example 3
OilGas_infrastructure
BN
GIS:
Aggregate_extraction
Fishing_pressure
Landscape
Cumulative_pressure
Quantitative,
qualitative, and
categorical data
Area
nrCFP
Sensitivity
Vulnerability
•
BBNs represent probabilistic correlative and causal relationships
•
BBNs specify joint and conditional relationships, and express
uncertainty
•
Conditional probability tables are populated from GIS data
Stelzenmüller et al (submitted). Marine Pollution Bulletin.
2. Tools to support marine planning – Example 3
Baseline scenario UKCS
Landscape
SHSP
55.9
WDS
.060
SHCW
4.35
SHMW
2.99
SHMP
4.08
SCSW
9.18
PR
0.69
SCSM
6.43
SHCM
1.0
AR
0.66
SHMM
0.39
SHCS
.091
SMSS
0.36
SMSM
1.15
SCSS
2.51
SMSW
1.0
SM
1.48
SS
5.01
SUS
2.63
offshore
inshore
Area
71.2
28.8
OilGas_infrastructure
0
46.0
0 to 3
19.6
3 to 6
27.4
6 to 9
7.10
2.06 ± 2.5
Aggregate_extraction
0
97.4
0 to 3
1.24
3 to 6
0.73
6 to 9
0.64
0.0992 ± 0.74
Cumulative_pressure
0
7.58
0 to 5
61.8
5 to 10
27.6
10 to 20 2.94
4.06 ± 3.4
Fishing_pressure
0
15.1
0 to 3 67.5
3 to 6 14.4
6 to 9 3.03
1.89 ± 1.8
0
1
2
3
nrCFP
62.9
31.6
4.93
0.57
0.431 ± 0.62
Sensitivity
0.6 to 1.2 4.48
1.2 to 1.6 61.3
1.6 to 2
16.4
2 to 2.5
17.8
1.59 ± 0.38
Vulnerability
0
7.18
0 to 4
38.9
4 to 8
28.7
8 to 20
24.1
20 to 38 1.09
6.2 ± 5.8
•
Probabilities of the parent nodes reflected the proportion of grid cells in the
respective state or category
2. Tools to support marine planning – Example 3
•
Scenario 1: What are the necessary management measures to achieve a
planning objective on cumulative pressure ?
Landscape
SHSP
55.9
WDS
.060
SHCW
4.35
SHMW
2.99
SHMP
4.08
SCSW
9.18
PR
0.69
SCSM
6.43
SHCM
1.0
AR
0.66
SHMM
0.39
SHCS
.091
SMSS
0.36
SMSM
1.15
SCSS
2.51
SMSW
1.0
SM
1.48
SS
5.01
SUS
2.63
offshore
inshore
Area
71.2
28.8
OilGas_infrastructure
0
58.0
0 to 3
25.9
3 to 6
15.9
6 to 9
0.27
1.12 ± 1.7
Aggregate_extraction
0
98.6
0 to 3
0.93
3 to 6
0.24
6 to 9
0.18
0.0384 ± 0.42
Cumulative_pressure
0
0
0 to 5
100
5 to 10
0
10 to 20
0
2.5 ± 1.4
Sensitivity
0.6 to 1.2 4.48
1.2 to 1.6 61.3
1.6 to 2
16.4
2 to 2.5
17.8
1.59 ± 0.38
Vulnerability
0
0.20
0 to 4
62.3
4 to 8
34.7
8 to 20
2.61
20 to 38 0.20
3.75 ± 3.1
Fishing_pressure
0
9.94
0 to 3 80.8
3 to 6 9.06
6 to 9 0.24
1.64 ± 1.3
0
1
2
3
nrCFP
65.8
28.9
4.79
0.52
0.401 ± 0.61
2. Tools to support marine planning – Example 3
Landscape
SHSP
55.9
WDS
.060
SHCW
4.35
SHMW
2.99
SHMP
4.08
SCSW
9.18
PR
0.69
SCSM
6.43
SHCM
1.0
AR
0.66
SHMM
0.39
SHCS
.091
SMSS
0.36
SMSM
1.15
SCSS
2.51
SMSW
1.0
SM
1.48
SS
5.01
SUS
2.63
•
OilGas_infrastructure
0
58.0
0 to 3
25.9
3 to 6
15.9
6 to 9
0.27
1.12 ± 1.7
Fishing_pressure
0
9.94
0 to 3 80.8
3 to 6 9.06
6 to 9 0.24
1.64 ± 1.3
Scenario 1 outcomes inCumulative_pressure
relation to baseline scenario
(current state):
nrCFP
Oil and gas
infrastructure
0
0 to 5
5 to 10
10 to 20
0
100
0
0
2.5 ± 1.4
0
1
2
3
65.8
28.9
4.79
0.52
0.401 ± 0.61
Aggregate
extraction
Fishing pressure
State 1
+ 12 %
+ 1.2 %
-5%
State 2
+6%
- 0.3 %
+ 12.5 %
State 3
- 11.5 %
- 0.5 %
-5%
State 4
- 6.5 %
- 0.4 %
- 2.5 %
Sensitivity
0.6 to 1.2 4.48
1.2 to 1.6 61.3
1.6 to 2
16.4
2 to 2.5
17.8
1.59 ± 0.38
•
Aggregate_extraction
0
98.6
0 to 3
0.93
3 to 6
0.24
6 to 9
0.18
0.0384 ± 0.42
Vulnerability
0
0.20
0 to 4
62.3
4 to 8
34.7
8 to 20
2.61
20 to 38 0.20
3.75 ± 3.1
Human activities related to the oil and gas industry and demersal
fishing need to be regulated most
2. Tools to support marine planning – Example 3
•
Scenario 2: How does the
vulnerability state change in the
planning area after the
relocation of fishing pressure ?
2. Tools to support marine planning – Example 3
Before the implementation:
After the implementation:
•
Northern offshore area showed a reduced probability of being in
vulnerability state 1 and 2
•
Southward shift of increased vulnerability, but “pristine” areas experienced
increase in fishing pressure and showed increased vulnerability
2. Tools to support marine planning – Example 3
Before the implementation:
After the implementation:
•
Northern offshore area showed a reduced probability of being in
vulnerability state 3 and 4
•
Overall decrease of surface area being in vulnerability state 4
2. Tools to support marine planning – Example 3
Our BN-GIS framework….
•
is constrained by the available geodata, and in this case
does not reflect a comprehensive assessment of
vulnerability
•
can be applied at any spatial scale and adapted to any
relationships when data becomes available
•
can be used to address a wide range of questions and
decisions, with their potential consequences
•
allowed to examine the spatial pattern of uncertainty
related to planning targets
Future work
Future work requires ….
• the inclusion of more ecosystem components
• the consideration of socio-economic planning objectives to
promote an integrated approach for the development of
marine plans
• the development of planning tools that consider
environmental change
Thank you for your attention !
[email protected]
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