values of coastal ecosystems recreation services - global
TRANSCRIPT
Values of coastal ecosystems recreation services - global analysis
Ecosystem Services Training DayVenice, Italy, 29 September 2010
Andrea GhermandiCà Foscari University of Venice and Fondazione Eni Enrico Mattei
GLOBAL VALUES OF COASTAL RECREATION1
1. Value transfer as secondary valuation technique of ecosystem services
2. Case-study: a global analysis of the value of coastal ecosystem recreation services
3. Scenario analysis for informing policy-making: climate change impacts on coastal recreation in Europe
4. Scaling up ecosystem service values: scaling up the value of wetland ecosystems in Europe
Contents
GLOBAL VALUES OF COASTAL RECREATION2
(a) Market price valuation mechanisms
These include the value of the financial revenues related to the goods directly provided by ecosystems (provisioning services) and the tourism activities focused on the visits to natural areas of high outdoor recreational demand.
1.1 Monetary valuation of EGS
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1.1 Monetary valuation of EGS
(a) Market price valuation mechanisms
(b) Non-market valuation methodsThese refer to special tools used by the economist so as to retrieve consumer’s preferences for non-market benefits, including
Travel CostHedonic PricingAvoided damage
Choice experimentContingent Valuation
…
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1.1 Monetary valuation of EGS
(a) Market price valuation mechanisms
(b) Non-market valuation methods
(c) Value transfer
Secondary valuation technique involves obtaining an estimate forthe value of ecosystem services through the analysis of a singlestudy or group of studies that have been previously carried out to value similar goods or services in similar contexts.
The transfer itself refers to the application of derived values and other information from the original study site to a policy site.
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Point transfer
Value function transfer
Meta-analysis
“… the statistical analysis of a large collection of results from individual studies for the purpose of integrating the findings”(Glass, 1976)
� More flexibly adjust for differences between study and policy site
� Less subject to biases due to large sample size
� Account for methodological and context-specific issues
1.2 Value transfer techniques
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1. Value transfer as secondary valuation technique of ecosystem services
2. Case-study: a global analysis of the value of coastal ecosystem recreation services
3. Scenario analysis for informing policy-making: climate change impacts on coastal recreation in Europe
4. Scaling up ecosystem service values: scaling up the value of wetland ecosystems in Europe
Contents
GLOBAL VALUES OF COASTAL RECREATION7
� Tourism and recreation are among the main drivers of ecosystem conversion in coastal areas (MEA, 2005).
� Because unobserved by markets and difficult to quantify, recreation values are hard to convey in the policy arena.
� Valuation studies are local but impact assessment of policy and regulations is at large geographic scale.
2.1 Motivation
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1) To develop a spatially explicit methodology to
� identify the drivers of recreation values
� transfer and map recreation values with a focus on policy application
2) To implement an application of the proposed framework to produce a global map of the value of coastal recreation.
2.2 Objectives
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1) Construct a database of valuation studies of coastal recreation worldwide.
2) Estimate a meta-analytical function to identify value drivers in a GIS-based approach.
3) Develop a framework for transferring the values and draw a global map of coastal recreation values.
4) Perform an analysis of the transfer error and identify the limitations of the study.
5) Discuss policy implications of the results.
2.3 Steps in the study
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2.4 Dataset of cultural values of coastal areas
WTP for recreation and passive use in US Atlantic Coast and Caribbean
(US$ 2003 / person year)
0 - 50
50 - 100
100 - 200
200 - 400
400 - 700
700 - 1,000
1,000 - 1,500
1,500 - 2,200
2,200 - 3,300
3,300 - 6,500
0 500 1,000250 Km
Global overview of primary valuation data
590 observations153 studies33 countries
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2.4 Coastal recreation valuations
79 independent studies253 observations of use values
79 independent studies253 observations of use values
Recreational fishing (101)Non-consumptive recreation (197)
Recreational fishing (101)Non-consumptive recreation (197)
Sandy beach (61)Coral reef (53)
Lagoon / coastal marsh (16)Estuary (13)
Mangrove (11)Other / mixed (99)
Sandy beach (61)Coral reef (53)
Lagoon / coastal marsh (16)Estuary (13)
Mangrove (11)Other / mixed (99)
Contingent valuation – open-ended (30)Contingent valuation – other (63)
Choice experiment (18)Travel cost – zonal (28)
Travel cost – individual or RUM (89)Contingent behaviour (25)
Contingent valuation – open-ended (30)Contingent valuation – other (63)
Choice experiment (18)Travel cost – zonal (28)
Travel cost – individual or RUM (89)Contingent behaviour (25)
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2.4 Coastal recreation valuations
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2.5 GIS-based characterization of valued sites and c ontext
0 250 500125 Km
Great Barrier Reef (6,000 km)
Fitzroy estuary (150 km)
Fraser island (300 km)
Mooloolaba beach (4 km)
Mooloolaba beach
0 10 205 Km
20 K
m
Creating shapefiles of the valued sites allows
(1) to homogeneously characterize ecosystem size
(2) to consistently evaluate context variables across sites
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2.6 Meta-analytical function
Year of primary data
Welfare measure(marginal/average value,
individual/household, CV/EV)
Valuation method(stated, revealed preference)
Valuation study variables ( Xs)
Protection level(protected area, no protection)
Ecosystem service(fishing, non-extractive)
Ecosystem type(beach, coral reef, lagoon, salt marsh, other)
Site variables ( XW)
Geo-climatic variables(min and max monthly temperature)
Human development index(low, medium, high: georeferenced)
Anthropogenic pressure(nutrient concentration: georeferenced)
Accessibility(travel time to nearest city: georeferenced)
Biodiversity index(both marine and terrestrial)
Population density(georeferenced)
GDP per capita(at administrative level)
Context variables ( XC)
iCiCWiWSiSi uXbXbXbay ++++=)ln(
yi = unit value of coastal zones for recreational activities, standardized to 2003 $/ha/year (PPP)
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2.6 Value standardization
Values are standardized to US$/ha/year (2003) as follows:
• First, aggregate average WTP/person/year over the nr of recreationists reported in the primary study; 0 0.1 1 10 100 1,000 10,000 100,000
0
20
40
60
80
28
19
43
81
71
29
0
Value in US$/ha/year (2003)
No.
of v
alue
est
imat
es
• Second, distribute total value over a swath of 2km from coastline;
• Third, control for inflation and purchase power parity
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• Anthropogenic pressure
• Human development
• Marine biodiversity
• Average monthly max temperature
• Accessibility (travel time to nearest city)
2.6 Spatial moderator variables of the meta-model
• GDP per capita
• Political stability and absence of violence and terrorism
• Population density
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2.7 Econometric resultsCoef. Std. Err. p-level
Choice experiment -0.178 0.448 0.692Contingent valuation (open ended) -0.953 ** 0.391 0.016ZTCM 1.367 *** 0.464 0.004TCM (ITCM and RUM) 1.095 *** 0.396 0.006Contingent behaviour -2.228 *** 0.586 0.000Equivalent variation 0.289 0.361 0.424Compensating variation 0.865 ** 0.339 0.011Unpublished -1.079 *** 0.344 0.002Year of data 0.110 *** 0.023 0.000Local studies 0.150 0.547 0.785Regional studies 1.245 ** 0.560 0.027Estuarine 1.974 ** 0.812 0.016Lagoon 0.637 0.476 0.182Mangrove 0.517 0.697 0.459Beach 2.334 *** 0.426 0.000Reef 2.063 *** 0.503 0.000Recreational fishing 2.032 *** 0.423 0.000Non-consumptive recreation 3.456 *** 0.463 0.000GDP per capita (ln) 0.364 0.238 0.129Political stability 0.421 0.258 0.104Population density (ln) 0.463 *** 0.154 0.003Low human development 2.347 *** 0.384 0.000Middle human development 0.594 0.562 0.292Anthropogenic pressure (ln) -0.256 *** 0.053 0.000Accessibility (ln) -0.750 *** 0.249 0.003Marine biodiversity index 0.190 ** 0.076 0.013Constant -6.544 * 3.862 0.092
N 253r2 0.73adj r2 0.70root MSE 1.562Shapiro-Wilk W test 0.231Max VIF 5.820
Breusch-Pagan test, prob > χ2 0.089
Coef. Std. Err. p-levelChoice experiment -0.178 0.448 0.692Contingent valuation (open ended) -0.953 ** 0.391 0.016ZTCM 1.367 *** 0.464 0.004TCM (ITCM and RUM) 1.095 *** 0.396 0.006Contingent behaviour -2.228 *** 0.586 0.000
Coef. Std. Err. p-levelEstuarine 1.974 ** 0.812 0.016Lagoon 0.637 0.476 0.182Mangrove 0.517 0.697 0.459Beach 2.334 *** 0.426 0.000Reef 2.063 *** 0.503 0.000Recreational fishing 2.032 *** 0.423 0.000Non-consumptive recreation 3.456 *** 0.463 0.000
Coef. Std. Err. p-levelGDP per capita (ln) 0.364 0.238 0.129Political stability 0.421 0.258 0.104Population density (ln) 0.463 *** 0.154 0.003Low human development 2.347 *** 0.384 0.000Middle human development 0.594 0.562 0.292Anthropogenic pressure (ln) -0.256 *** 0.053 0.000Accessibility (ln) -0.750 *** 0.249 0.003Marine biodiversity index 0.190 ** 0.076 0.013
N 253r2 0.73adj r2 0.70root MSE 1.562Shapiro-Wilk W test 0.231Max VIF 5.820
Breusch-Pagan test, prob > χ2 0.089
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2.8 Setting up the value transfer framework
0 150 30075 km
• Goal is to produce a global map with 0.5 degree resolution.
• Calculate the value of spatial moderator variables in each coastal grid cell.
• Assume (conservatively) the value of the methodological binary variables for the transfer.
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2.9 The global map of coastal recreation values
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2.9 The global map of coastal recreation values
Legend
Recreational valueUS$ / ha year (ln)
High : 9.56
Low : -5.89
0 500 1,000250 Km
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2.10 Error analysis: in-sample forecast
-4
-2
0
2
4
6
8
10
12
1 51 101 151 201 251
Observations
lnva
lue
(US
$/ha
/yea
r)
Observed value Predicted value
Mean Absolute Percentage Error MAPE = | (lnvalueobs – lnvalueest) / lnvalueobs |
Average MAPE = 30%Median MAPE = 17%
Mean Absolute Percentage Error MAPE = | (lnvalueobs – lnvalueest) / lnvalueobs |
Average MAPE = 30%Median MAPE = 17%
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2.10 Transfer error analysis: n-1 data splitting
-4
-2
0
2
4
6
8
10
12
14
1 51 101 151 201 251
Observations
lnva
lue
(US
$/ha
/yea
r)
Observed value Predicted value
Mean Absolute Percentage Error MAPE = | (lnvalueobs – lnvalueest) / lnvalueobs |
Average MAPE = 33%Median MAPE = 19%
Mean Absolute Percentage Error MAPE = | (lnvalueobs – lnvalueest) / lnvalueobs |
Average MAPE = 33%Median MAPE = 19%
0
1
10
100
1000
10000
100000
1 51 101 151 201 251
Abs
olut
e E
rror
(U
S$/
ha/y
ear)
Average error = 3,533 US$/ha/year
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1. Value transfer as secondary valuation technique of ecosystem services;
2. Case-study: a global analysis of the value of coastal ecosystem recreation services
3. Scenario analysis for informing policy-making: climate change impacts on coastal recreation in Europe
4. Scaling up ecosystem service values: scaling up the value of wetland ecosystems in Europe
Contents
GLOBAL VALUES OF COASTAL RECREATION24
3. Aggregated values of coastal recreation in Europe
Values of coastal recreation at NUTS2 level
M$/year< 50
[50 - 100]
[100 - 500]
[500 - 1,000]
> 1,000
GLOBAL VALUES OF COASTAL RECREATION25
3. Climate change scenario analysis: the IPCC storyl ines
A1 (Rapid and successful economic development)
• Population (106): 376• High savings and high rate of investments and innovation at national & international level• Cumulative CO2 (ppm): 779•ΔTemperature (ºC): 4.4 • Precipitation Europe(%): -0.5
A2 (A differentiated world)
• Population (106): 419
• Eonomic growth is uneven in the world
• Income per capita: largely increased
•Cumulative CO2 (ppm): 709
•ΔTemperature (ºC): 2.8
•ΔPrecipitation Europe(%): 0.5
B1 (Global sustainable development)
•Population (106): 376• High investment in resource efficiency• Distribution Efficiency: Hgih• Cumulative CO2 (ppm): 518•ΔTemperature (ºC): 3.1 •ΔPrecipitation Europe(%): 4.8
B2 (Local and regional sustainable development)
• Population (106): 398• Human welfare, equality, and environmental protection• Cumulative CO2 (ppm): 567•ΔTemperature (ºC): 2.1•ΔPrecipitation Europe(%): 2.7
Global Regional
Economic
Environmental
The four storylines are modeled
through changes in GDP per capita,
population density, biodiversity
richness and surface air temperature
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3. Climate change scenario analysis: the IPCC storyl ines
Total values for storyline A1 versus storyline A2 (2050)
Total values for storyline B1 versus storyline A2 (2050)
Total values for storyline B2 versus storyline A2 (2050)
Legend% variation
[-20%, -10%]
[-10%, 0%]
[0%, 10%]
[10%, 20%]
[20%, 35%]
[35%, 55%]
Percentage variation in aggregated values at
country level with respect to IPCC scenario A2
(EIBURS-CLIBIO, 2009)
GLOBAL VALUES OF COASTAL RECREATION27
1. Value transfer as secondary valuation technique of ecosystem services;
2. Case-study: a global analysis of the value of coastal ecosystem recreation services
3. Scenario analysis for informing policy-making: climate change impacts on coastal recreation in Europe
4. Scaling up ecosystem service values: scaling up the value of wetland ecosystems in Europe
Contents
GLOBAL VALUES OF COASTAL RECREATION28
4 Scaling up ecosystem services values
Small (marginal) changes in ecosystem size will not affect values from the rest of the ecosystem stock.
Larger scale changes may, however, result in increasing marginal ecosystem service values (scarcity effects).
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4. European wetlands
• 50,533 wetlands in EU identified applying GIS to the Corine land cover data (EEA)
• Context- and site-specific variables can be evaluated in each of the sites
• Bottom-up aggregation of values
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4. European wetlands and wetland abundance
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4. Value of wetland loss (2000 – 2050)
-98,750,535-739,66250,533EU Total
-14,174,170-60,2952,119United Kingdom-5,820,337-218,33020,242Sweden-5,264,939-5,511344Italy-3,959,454-96,8042,173Ireland-3,429,942-7,7201,090Hungary-2,338,065-5,181302Greece
-13,970,430-28,6531,419France-3,801,342-157,75714,140Finland-1,361,400-15,8231,146Estonia
-471,178-719105Czech Rep
Change in value of ecosystem services (€)
Change in wetland area (ha)
Number of wetlands
Country
(EEA, 2010)