The economic feedbacks of loss of

biodiversity and ecosystems services

Anil Markandya

Basque Centre for Climate Change

October 2014

Purpose of the Scoping Study • The cost of past economic growth in terms of loss

of biodiversity and functioning of ecosystems and has been studies in some detail.

• But less has been done on the effects these losses have in terms of reductions in economic performance.

• Or on what the benefits would be of shifting to green growth paths.

• This study aims to examine the evidence on the two questions and outline what further work is needed incorporate losses of biodiversity and ecosystem services within CGE models.

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Ecosystem Services: A Key Concept

• The Millennium Ecosystem Assessment set up in 2005 a generic framework of ecosystem services (ESS), categorising them into four typologies: provisioning services, regulating services, cultural services, and supporting services.

• This has been adopted widely, with variations in the detailed definitions of the different services.

• If our interest is valuation it is useful to focus on final ecosystem services, while accounting for ecosystem processes and intermediate ESS as relevant in determining the final values.

• The categories of final services vary across studies.

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Categories of ESS in TEEB

Provisioning Services Food

Water Raw Materials Genetic Resources Medicinal Resources Ornamental Resources

Habitat Services Nursery Service Genetic Diversity

Regulating Services Air Quality Climate Regulation Disturbance Moderation Water Flow Regulation Erosion Prevention Nutrient Recycling Pollination

Biological Control

Cultural Services Esthetic Information Recreation Inspiration Spiritual Experience Cognitive Development

Empirical estimates have been made for all these categories. 4

ESS and Biodiversity • Biodiversity: “the variability among living organisms from

all sources including, inter alia, terrestrial, marine and other aquatic ecosystems and the ecological complexes of which they are part.

• Ecosystem are “a dynamic complex of plant, animal and micro-organism communities and their non-living environment interacting as a functional unit” and ESS are benefits derived from ecosystems.

• Loss of biodiversity affects ecosystems significantly but links are complex and direct valuation of biodiversity is difficult.

• For this reason operational focus has been on ESS but some account of biodiversity loss on ESS has been taken through measures of Mean Species Abundance (MSA) in different habitats.

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Valuation of ESS

• Considerable work on valuing final services by biome and geographical location.

• TEEB review documented 320 studies across 10 biomes, covering 300 locations. Derived from many databases such as EVRI, COPI etc. There are many more “studies” but details are not sufficient for them to be evaluated.

• Less work on valuing changes in final services when the ESS is modified or degraded.

6 see www.es-partnership.org for information on most of these databases

Global Studies: 10 Biomes

Biome Biome

Marine (Open Oceans) Freshwater (Rivers/Lakes)

Coral Reefs Tropical Forests

Coastal Systems (1) Temperate Forests

Coastal Wetlands (1) Woodlands

Inland Wetlands Grasslands

(1) Coastal systems include estuaries, continental shelf areas and sea grass but not wetlands such as tidal marshes, mangroves and salt water wetlands

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Main Valuation Findings for ESS

• Considerable work in reviewing and synthesizing valuation studies was done in the TEEB report.

• Values are generally expressed in terms of $/ha./yr.

• Some studies carry out a meta analysis giving these values as a function of site characteristics.

• The average values across studies are significant but with large ranges indicating the need to work at a spatially disaggregated level.

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How Are the Values Derived? ESS Direct Market

Values Cost Based Methods

Revealed Preference

Stated Preference

Provisioning 84% 8% 0% 3%

Regulating 18% 66% 0% 5%

Habitat 32% 6% 0% 47%

Cultural 39% 0% 19% 36%

• Direct Market Values include: market pricing; payment for environmental services; and factor income/production function methods

• Cost Based Methods include: avoided cost, restoration cost; and replacement cost

• Revealed Preference: hedonic pricing and travel cost • Stated Preference: contingent valuation, conjoint choice and

group valuation 9

What Are the Numbers?

• Values are Int.$/Ha./Yr., 2007 price levels ESS Mean Median Min/Mean Max/Mean

Oceans 491 135 17% 339%

Coral Reefs 352,915 197,900 10% 603%

Coastal Systems 28,917 26,760 90% 145%

Coastal Wetlands 193,845 12,163 0.2% 458%

Inland Wetlands 25,682 16,534 12% 409%

Rivers & Lakes 4,267 3,938 34% 182%

Tropical Forest 5,264 2,355 30% 396%

Temperate Forest 3,013 1,127 9% 545%

Woodlands 1,588 1,522 86% 138%

Grasslands 2,871 2,698 4% 207%

De Groot et al, Ecosystem Services, 2012. 10

Comments on Values • The values vary by biome, both means and

ranges. • Other review studies come up with different

mean values • Numbers of studies on oceans, coastal systems

and woodlands and grasslands are relatively few in number. Many more for wetlands and forests.

• Relatively few studies in developing countries (although there are some in most categories)

• Estimates can be targeted for a given site in a given location using meta analytical functions.

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Meta Analytical Functions Estimated • Unit value as a function of site and user

characteristics have been made for: – Inland wetlands, Tropical and Temperate forests,

Grasslands, Mangroves, Coral Reefs

• Main explanatory variables include: – Size of the site, income level in the country, number

of people using the site, NPP in the area around the site, presence of other sites nearby, method of estimation used.

– Quality of the site rarely appears as a variable

• Functions not all well determined.

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Application in Economic Models

• The usual databases are not so useful for estimating the impact of changes in the quality of biomes

• We have to look at more detailed studies of different ESS and how changes in their function due to external factors can effect the services they provide.

• A number of studies have attempted to do that using spatially disaggregated data but economic valuation is included only in some, and to a limited extent.

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Incorporating ESS Values in Economic Models: Key Questions

• Does the model include ESS in both directions – i.e. the impact of economic changes on ESS and thereby on welfare as well as the impact of ESS changes on production possibilities for goods and services and thereby on growth?

• Does the model take account of the inter-relationships between markets – i.e. does it have a general equilibrium structure –allowing for market imperfections such as unemployment, trade barriers etc.?

• Does the model include a spatial dimension so that ecosystems impacts of

growth can be taken into account different depending n where they occur?

• Is the coverage of ecosystems complete – i.e. are all biomes included in

the system?

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Models and Approaches Examined

Model Ecosystem Economics Other

GUMBO* 11 biomes, ESS feed into production and welfare functions

Economic output based on capital, labor, knowledge. Links from ESS to Economic module

No spatial modeling. Economic module not CGE. ESS valuation sketchy

GLOBIO-IMAGE

ESS from biomes affected by socio- economic drivers

LEITAP, extended version of GTAP, used to model land use changes

Changes in land for agriculture affects different biomes. Spatially explicit.

InVEST Production functions linking LULC type to ESS

Economic production functions determine demand for land & ESS

Still developing. Coverage not global as yet. Not CGE.

UK NEA ESS from different biomes spatially disaggregated scale

Scenarios estimate changes in ESS

No economic modeling but ESS changes valued for some services

* MIMES, spatial version of GUMBO is being developed 15

Causality from ESS Changes to

Economic Functions • All the above models examine the implications of

economic development growth on ESS in either physical or monetary terms.

• However, the only models that explicitly account for the impact of ESS changes on economic performance are the GUMBO-MIMES set. In these ESS services affect the measure of “natural capital”, which in turns enters as an input to the production function for other goods and services.

• But modelling is at a very aggregate level and there is a need to develop it further.

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Use of a general equilibrium structure • The only model that has a link with a general

equilibrium structure is the IMAGE-GLOBIO model, which consists of an economic module which examines different development scenarios. It also has a spatial disaggregation.

• Effects of different growth paths on MSA-adjusted ESS are estimated for a number of services (but not all).

• But ESS do not directly enter the production of goods and services and so the feedback from a loss of ESS to the economy cannot be tracked in the model.

• It also does not have money values for ESS, although some parallel work has been done on these.

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Inclusion of a Spatial Dimension

• The spatial dimension is incorporated into GLOBIO-IMAGE, InVEST and the UK NEA but not in GUMBO (although MIMES is working on developing that).

• The importance of including this aspect into the modelling is highlighted by the fact that the impacts of different scenarios on ecosystem functioning are found to vary considerably by location.

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Coverage of Ecosystems in monetary terms

• The coverage of ecosystem services in monetary terms is not entirely complete in the models examined.

• E.g. Those models that do value ESS in money terms cover marine ecosystems to a limited extent if at all.

• Focus on valuation tends to be on forests, wetlands, lakes and rivers and croplands.

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Need for Further Development

• More work is needed to model the linkages from changes in ESS to the functioning of the economy.

• Modelling that exists (e.g. GUMBO) is too aggregated and does not have a CGE structure.

• CGE models on the other hand do not have ESS in the production functions.

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Possible Steps Forward • First a soft link can be made between the ESS

value changes and the economic models. • Alternative growth paths can be evaluated in

terms of the losses or gains they imply for different ESS and these values can be used to adjust the estimated GDP growth rate, to give a “corrected GDP”.

• This work can be based on the IMPAGE-GLOBIO Model, for example, with valuation work that has been done using that model, being linked to the typical OECD growth models.

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Possible Steps Forward • At the same time a second approach needs to be developed, in

which the integrated CGE models include ESS as specific inputs into key sectors and where the output of these sectors affects the functioning of the ESS.

• The inclusion of ESS into some sectors such as agriculture and forestry should be relatively straightforward because linkages to marketed goods are well developed

• It will be more challenging to cover services such as recreation, tourism, and health (

• It will also be important to take account of connections between ESS (e.g. the quality of cultural services depend on how well the regulating services are functioning). This stream of work needs to be undertaken in conjunction with the dynamic modellers who are developing the combined framework of the OECD’s ENV-Growth model as well as the dynamic computable general equilibrium (CGE) OECD’s ENV-Linkages model.

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Possible Work Plan? A. Set up a database of state-of-the-art estimates of the

value of ESS at a spatially differentiated level so it can be used in the economic models.

B. Calculate the losses of ESS associated with alternative growth paths and use these figures to calculate an adjusted GDP figure for each path, indicating the effect that the losses have on “true GDP”.

C. Initiate work on integrating ESS into the economic models. This can be done first for agriculture and forestry where there is considerable information and then go on to consider the more difficult sectors.

D. Combine the work on adjusted GDP with that on sectoral production links to produce an integrated system that includes both the effects of growth on ESS and the effects of declines in ESS on growth.

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Useful Readings

• Ten Brink P. (ed.) (2012)The Economics of Ecosystems and Biodiversity in National and International Policy Making. London: Earthscan, 352pp.

• De Groot R. et al. (2012) Global estimates of the value of ecosystems and their services, Ecosystem Services, 1, 50-61.

• Hussain S. et al. (2013) “The Challenge of Ecosystems and Biodiversity”. in Lomborg B. (ed.) Global Problems, Smart Solutions, Cambridge University Press.

• Bateman, I. et al. (2013) Bringing Ecosystem Services into Economic Decision-Making: Land Use in the United Kingdom, Science, July.

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