Valuation of Marine Ecosystem Goods and
Services and Man’s Impact on European Seas
Thomas van Rensburg (Department of Economics, NUIG)
SEMRU Workshop, Marine Institute, Oranmore 2/11/09
Co Authors: Prem. Wattage, Helen Glenn, Simon Mardle, Naomi Foley, Anthony Grehan
CEMARE/NUIG
Overview
Protect project on Marine Protected Areas
For MPAs – a big challenge is to quantify ecological and non-use
benefits alongside fishing & other priced outputs from the marine
resource within CBAs. CE and the production function approach can
be used to quantify these different values and assess the tradeoffs
between these different goods and services.
Why Value Ecosystem Goods and Services?
Standard bioeconomic models have two problems:
They don’t account for the ecosystem services that support the fishery
They don’t take account of the ecosystem services related to non-use values
We attempt to measure these external effects related to ecosystem service
provision using cold water coral as a case study
We evaluate two ecosystem services – the role of habitat as an
input to the fishery; the use/non use values related to cold water
coral protection.
CEMARE/NUIG
Background: Cold Water Corals
Found in most oceans in the world
Lophelia pertusa predominant reef
forming species in Europe
Depths from 40 - 1200m
Temperature range 4-13ºC
Long lived and slow growing
Threats
Bottom trawling
Oil & gas exploration
Cable & pipe laying
Destructive scientific sampling
CWC Ecosystem goods and Services
Cold Water Corals
Provision of goods and services
Fish habitat
Nursery and spawning grounds
Paleoclimate indicator
CO2 sequestration
Pharmaceutical compounds
Focus: Functional Services
Habitat
Nursery grounds
Refuge
Bioeconomic model (Redfish) with and without social costs
Revenue,
cost (€)
TSC
Open access = EOA and HOA
Defined property rights = EPROF and
Preservation value (external costs) = HSOC
TC = WE
HPROF
HOA
R - C = Max
(scarcity rent)
Hsoc
TR = PH
Xzero
Esoc
EPROF
EOA
CEMARE, University of Portsmouth
EMAX
Effort (E)
Cold Water Coral Study
Gordon-schaefer harvest function
Logistic growth function
F ( X ) = rX (1 − X / K )
Adjust growth function to allow for influence of
Lophelia (L)
Essential Habitat
F ( X , L ) = rX ( K ( L ) − X )
Change in growth function of redfish
F(X,L)
Slope r(L)
X
K(L)new
K(L)
Growth Function: Impact of a decrease in Lophelia on both carrying capacity and intrinsic growth.
Redfish Data
Lophelia / CWC:
Estimated spatial coverage: 2000km2
Corals grounds depleted by 30 - 50% between 1986 – 1999
1999 Norwegian Ministry of Fisheries issued regulations for the protection of coral reefs
Range coral decline 30% - 50%
Effort:
Norwegian Fisheries Directorate (1986 – 2002)
3 trawl types; factory, fresh fish and vessels under 250 GRT
data standardised for relative fishing power (RFP)
Harvest:
assume no further damage to corals from 2000 – 2002
ICES reports area I and II (1986 – 2002)
Price:
Norwegian annual auction prices (1986 – 2002)
Real prices 1998 base year
Analysis/Results
Marginal decline in CWC area (1km2):
Loss of between 68 and 110 tonnes of redfish
harvest
In monetary terms; fall of between $73,222 and
$119,107 per annum for each square km of coral
lost
Percentage loss in revenue between 11% and 29%
for fall in CWC of 30% and 50% respectively
Total Economic Value
TEV of Coral Ecosystem
Use value
1. Direct
use value
Forest
products
(timber)
Educational,
Recreational
& cultural
uses
2. Indirect
use value
External support:
Essential habitat
Resilience,
Stability,
Nutrient cycling,
Carbon store
Non-Use value
3. Option
value
Future uses as
per 1 and 2.
4. Quasi option
value
Expected future
uses as per 1, 2,
3
5. Existence
value
Cultural,
heritage,
intrinsic
worth
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6. Bequest
value
Future
generations
Measuring non-market values associated with
Irish CWC using choice experiments (CE)
CE presents respondents with options consisting
of multiple attributes with different levels
Respondents make their choice from the options
(demonstrating their trade-offs & marginal rates
of substitution between the attributes)
CE measures the relative importance of the
individual attributes and the total satisfaction or
utility scores for different combinations of
attributes
CEMARE/NUIG
Example: Attributes and accompanying
target levels
Table 2: Attributes and accompanying management objective levels.
Attributes
1. ACTIVITY –
the fishing
activity
allowed in the
MPA
2. AREA – MPA
strategy to
protect cold
water corals
Level I
Level II
Status quo
Ban trawling
(allow all fishing) (but allow
other fishing
methods)
Status quo
(currently
identified coral
reefs)
3. COST–
€ 0 (No
management additional tax)
& monitoring
cost
Level III
Ban all
fishing
All known coral All coral areas
reefs
(where coral
reefs are
thought to
exists)
€ 1 (Additional € 10 (Additional
yearly tax)
yearly tax)
CEMARE, University of Portsmouth
Example slides of the levels of one of the attributes - Area
Figure 1: Status Quo - Continue to protect Irish cold-water
coral SACs (red) already protected
CEMARE, University of Portsmouth
Figure 2: Protect all known coral areas - Location of additional
MPAs (blue) for newly discovered undamaged corals.
CEMARE/NUIG
Figure 3: Protect via additional MPAs (purple) all areas
thought to contain corals between 500m-1000m.
CEMARE/NUIG
Generating options for CE survey
Using Previous (attribute & levels) table:
full factorial design yields a total of 27 possible
combinations of attributes & levels
three attributes have three levels; thus there are (33) =27
possible alternatives
ADX Interface for the design of Experiments (SAS 9.1)
(an orthogonal main effects design - where all interactions
are assumed to be insignificant), this was subsequently
reduced to 9 profiles/choice options for use in the study.
This tests all the main combinations of attributes
CEMARE/NUIG
SECTION 1 (Please TICK the box (only one) next to your preferred option)
AREA: Status quo
ACTIVITY: Status quo
1.
COST
€0
THIS IS MY
PREFERRED
OPTION
AREA: Known coral reefs
ACTIVITY: Status quo
2.
COST
€1
THIS IS MY
PREFERRED
OPTION
AREA: All coral areas
ACTIVITY: Status quo
3.
COST
€10
THIS IS MY
PREFERRED
OPTION
The options
as presented
AREA: Status quo
ACTIVITY: Ban trawling
4.
COST
€1
THIS IS MY
PREFERRED
OPTION
AREA: Known coral reefs
ACTIVITY: Ban trawling
5.
COST
€10
THIS IS MY
PREFERRED
OPTION
Can present all
or a subset to each
respondent.
AREA: All coral areas
ACTIVITY: Ban trawling
6.
COST
€0
THIS IS MY
PREFERRED
OPTION
AREA: Status quo
ACTIVITY: Ban all fishing
7.
COST
€10
THIS IS MY
PREFERRED
OPTION
AREA: Known coral reefs
ACTIVITY: Ban all fishing
8.
COST
€0
THIS IS MY
PREFERRED
OPTION
AREA: All coral areas
9.
ACTIVITY: Ban all fishing
COST
€1
THIS IS MY
PREFERRED
OPTION
In survey all
were presented
to each
respondent, who
made a single
choice
Estimation procedure
Multinomial Logit Model (MNL) is used
Several χ2 (Chi-square) likelihood ratio tests were
run.
All tests indicated that the model was significant
at the α=0.01 level.
Test
Likelihood Ratio
Score
Wald
χ2
228.4
254.2180
214.6333
DF
6
6
6
CEMARE, University of Portsmouth
Pr > χ2
<0.0001
<0.0001
<0.0001
Most preferred options individually..
the ranking of attributes and levels suggests that
the top 2 preferences for MPA management are
to:
ban trawling and
protect all coral areas.
Next in the order of ranking comes:
a tax of €1
no tax, followed by
a tax of €10 and the protection of known corals.
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Estimation of the degree of importance attached to each
attribute from the model (derived from the full set of 27 alternatives)
CEMARE/NUIG
Conclusions
Red fish study - Preliminary results indicate that coral decline is of significantly
greater importance than high effort levels in explaining changes in redfish harvest
Lophelia appears to play a role in the decline of redfish stocks
CE study: The results confirm the importance attached by the Irish public to MPAs in
the Irish deep-sea coral areas and demonstrate their preferences
Without a second case study, however, it is difficult to say whether there is any
uniformity of opinion over MPA management
The outputs provide tangible, quantified support for MPA planning and management
Choice experiments appear to be a useful tool for the evaluation of MPAs
The method is flexible to the needs of particular MPAs and for similar sites in relative
proximity there is also the potential (albeit limited given current methodologies) for
“benefit transfer” between sites
The quantified outputs can be incorporated into CBA and used in baseline and goal
setting, and given funding for survey repetition, monitoring programs for MPAs
The quantified outputs can also form inputs into bioeconomic models for targeted
MPAs (& as such are useful evaluators)
Further work - Hermione (FP7)
Consider optimal management for CWC & the impacts of this management
on fish stocks and fishers
Extend model to age class model
Quantification of ecosystem values
Management scenarios
Non-use values