Ecosystem services (ES) can be incorporated into two distinct forms of assessment:
Scenario analysis (SA), or estimating change in ecosystem service values due to change in management, policy, natural resource condition, or project implementation.
Green accounting (GA), or developing jurisdictional (national, state, local) accounts that record the economic contributions of ecosystem services over time, through adjusted versions of macroeconomic measures (e.g., “comprehensive” or “inclusive” wealth, “adjusted” or “genuine” savings, and “green GDP”).
Scenario analysis is more straightforward conceptually and what the ES paradigm is most commonly used for in practice. It is also more directly relevant for land and resource managers. For this reason, the SA use of the ES framework has been the primary focus of this guidebook. However, there is considerable interest in green accounting, especially on the part of parties interested in broad-scale issues of placing ecosystem value “on an even footing” with traditional measures of economic performance such as gross domestic product (GDP) or national wealth accounts. Green accounting can provide more inclusive measures of national (or other jurisdictional) economic variables as they are tracked over time. These more inclusive measures can be used to inform how policy and other factors are affecting economic outcomes, once the value of natural capital and ecosystem services are taken into account.
Both forms of ES assessment are intended to inform decisions, but they address different decisions and answer different questions, as illustrated in Table 1.
Table 1. Examples of Questions Addressed and Decisions Informed by Form of ES Assessment
|How would adopting an alternative management plan for Forest X affect the value of ecosystem services generated?||Which forest management plan to adopt|
|Which projects are most justified given a fixed budget, taking net ecosystem benefits into consideration?||Resource allocation decisions in implementing management plans under an agency budget constraint|
|How do ecosystem service losses contribute to economic damages from an oil spill?||Compensation decisions under natural resource damage assessments|
|How much does consideration of the economic value of ES change aggregate measures of an economy’s performance, in particular its sustainability?||Economic and environmental policy design at broad (macro) levels, such as saving, investment, and industrial policies and climate, energy, and conservation policies|
|What portion of total GDP is attributable to ecosystem services that are hidden in income accounts as conventionally constructed?||Resource allocation decisions at the federal or other jurisdictional level; identification of potential opportunities for payment for ES programs|
|Is Country (state) A’s forestry policy leading to an increase or decrease in the aggregate value of nonmarket ecosystem goods and services, in addition to timber production and consumption?||National (state-level) overall forest policy decisions, balancing commodity production versus other nonmarket ecosystem servicesPrivate decisions on commodity and ES investments|
Scenario analysis is primarily focused on the consequences of geographically specific discrete actions such as management plans, narrowly targeted policies, projects, or natural resource damage assessment. The ES framework provides the theoretical and empirical foundation for determining the effect of these actions on human welfare. As discussed below, these assessments can be conducted ex ante to assess options or ex post to evaluate performance.
The idea of incorporating ecosystem services into jurisdictional accounts through green accounting, however, has different objectives. Jurisdictional accounting, such as national income and wealth accounting, and the aggregate measures that are based on it, such as gross domestic product (GDP), are developed to provide a barometer of the state of the economy rather than to assess the consequences of specific actions. Nevertheless, measures such as GDP are used to inform public policy and private sector decisions. For instance, if GDP growth is slow, policy makers may opt to take action to stimulate the economy. Investors may adjust their stock valuations to reflect any revised expectations of future economic growth. More inclusive measures, enabled by green accounting to consider aggregate measures of natural wealth (capital) and the value of ecosystem services produced, can alter these perceptions and strategies. Stimulative policies, for instance, might also include those that spur investment in natural capital.
The analytical approach to ES assessment covered in this guidebook focuses on scenario analysis to inform management decisions. The assessment framework presents a structured decision-making approach that incorporates the preferences and values of people in framing the assessment. When possible, the assessment also incorporates these preferences and values in comparisons of the ecological outcomes of alternative scenarios. Although the basic intent is to connect ecological outcomes to human preferences, the reported outcomes may or may not be monetized.
Green accounting generally seeks to incorporate ecosystem services into a monetary measure of production or consumption that acts as a signal of an economy’s growth and health. This task ultimately involves the compilation of biophysical measures (either stocks or flows) in aggregate form for the jurisdiction of interest and, correspondingly, placement of a price on them to provide a monetary measure of the jurisdiction’s natural wealth (stocks) or production (flows). This task is complicated by the fact that many natural stocks and flows do not have market prices, therefore proxies are often developed through nonmarket valuation approaches. In some cases, these proxies are the biophysical measures themselves.
The SA approach is often used to assess management options before a decision is made (ex ante), but it can be modified to examine events after they occur (ex post). In either case, analysts must define a baseline that reflects expectations of what would likely occur ex ante if the option is not chosen or what likely would have occurred ex post if the event of interest had not happened.
By comparison, green accounting is more typically used to track the status of natural capital stocks and flows from the past to the present (ex post) to reveal the status of and trends for the given jurisdiction. However, this does not mean that GA analysis is always backward looking. Ideally, the monetary values assigned to biophysical measures of natural capital stocks incorporate people’s current perceptions about future demands, scarcity, and substitutes for the resource, whether they are revealed by market prices or by nonmarket valuation methods. Moreover, analysts can develop ex ante simulations of future natural capital stocks and flows using GA principles embedded in large integrated assessment models (e.g., computable general equilibrium models of the economy with biophysical production elements). These models can then be used to assess the future consequences of changes in policy regime, technology, environmental conditions such as climate change, or other large-scale factors.
Finally, if collected over a sufficiently long period and with sufficient geographical detail, the biophysical time series data used to track non-market production in green accounting can be used to empirically test the effect of policies on biophysical outcomes—a capability that can greatly improve forward-looking scenario analysis.
In the last few decades, the United Nations Statistics Division, the World Bank, the United Nations Environment Programme, and various other organizations have focused attention on the failure of conventional income and wealth accounts to incorporate the effects of natural resource depletion and environmental degradation.1 Most of the attention has focused on adjustments to the wealth accounts—the “balance sheets”—to measure the value of natural capital (“natural capital accounting”) as a component of a country’s total national wealth. The underlying idea is that a sustained increase in a country’s standard of living requires a sustained increase in its national wealth. If natural capital is depleted, other forms of capital need to be built up to offset its loss. For example, countries that draw down their mineral wealth could eventually suffer economic decline—a phenomenon known as the natural resource curse—if they do not invest the proceeds from the extraction and sale of minerals in other forms of capital (produced, human, or natural).2 This idea draws on a sometimes-controversial (especially outside of economics) notion of sustainability, which allows for the substitution of natural capital for other forms of physical capital. This interpretation of sustainability has been articulated by Nobel laureate Robert Solow, drawing from others, including John Hartwick.3
Over time there has been an increase in estimated and published national wealth accounts. The World Bank’s online World Development Indicators database provides estimates of annual changes in different forms of capital for most of the world’s countries from the early 1970s to the present; these estimates were originally called “genuine savings,” but more recently have been called “adjusted net savings.”4 In the case of natural capital, the Bank’s estimates refer mainly to changes in the value of stocks of priced natural resources, such as fossil fuel deposits, minerals, and timber: what the Millennium Ecosystem Assessment labels “provisioning resources.”5 The World Bank has also published periodic national estimates of “comprehensive wealth,” snapshots of the total value of countries’ wealth stocks, not just changes in those stocks (e.g., World Bank 2011);6 UNEP has published an independent set of estimates, which it labels the “Inclusive Wealth Index”.7 The United Nation’s System of Environmental Economic Accounting-Central Framework (SEEA-CF), which was issued in 2014, provides guidelines for wealth accounting related to these types of natural resources.8
Accounting for unpriced ecosystem services is at an earlier stage; appropriately, the UN’s report on them is titled “Experimental Ecosystem Accounts.”9 The World Bank’s Wealth Accounting and Valuation of Ecosystem Services (WAVES) program is sponsoring projects in selected countries to learn more about the practical challenges of designing and implementing ecosystem accounts.
The focus of official GA initiatives on wealth accounts instead of the better-known product accounts—which are the source of GDP estimates—reflects national accountants’ reluctance to extend the boundary of product accounts beyond the market economy to areas in which prices and quantities are less easily measured. The nonmarket nature of most ecosystem services thus creates a roadblock for including them in national product accounts. National accountants and economists alike have long recognized that GDP is an incomplete measure of economic well-being. Economists have pointed out that GDP excludes many components that contribute to well-being (utility) such as goods and services that are not traded in markets, including uncompensated household work, leisure, and environmental public goods. National accountants accept this view but argue that the measurement of well-being is not the purpose of the accounts; instead, it is the measurement of the size of the exchange economy. Consequently, although an environmental economist would argue that a more complete measure of national economic well-being should include existence values provided by a country’s protected area system, a national accountant would object to their inclusion because these values cannot be readily imputed from market exchanges between suppliers and users. Moreover, the omission of many ecosystem services from product accounts is not unique in making these accounts imperfect measures of economic welfare. As such, focusing on the inclusion of natural capital in wealth accounts may be a more feasible initial step toward green accounting than redefining national income to be a more complete measure of national well-being.
On the product accounts side, green accounting faces certain challenges in developing measures that are theoretically consistent with national income accounting, the presumed benchmark. Boyd and Banzhaf (2007) take up several of the issues associated with GA in the product account.10 They argue that symmetry with national income accounting requires separate accounting of ES quantities and prices. “Prices” need not be market prices—they often are not with ecosystem services—but consistency requires that they be some measure of marginal willingness to pay. They also argue that, for adjustments that affect the level of GDP, ES quantities should be final consumption quantities and not intermediate goods.11 Although this is true, national accountants will be less opposed to accounting for ecosystem services that can be interpreted as intermediate goods, as such accounting does not require changing the production boundary of the accounts. The economic impacts of many important ecosystem services, especially regulating services, are already reflected in market outcomes. For example, a loss of water purification services due to deforestation affects the water utility industry’s treatment costs (which increase) and operating surpluses (which decrease). Green accounting can be used to make hidden flows of ecosystem services between industries and sectors in the product accounts explicit, without changing the overall level of GDP.
Another challenge is actually measuring ES (either intermediate or final) quantities and prices and aggregating them to the jurisdictional level of the accounting system. The challenges there are practical. Not all ecosystem services have been measured, and some that have been measured have not been priced. Moreover, as described throughout this guidebook, ecosystem services are spatially differentiated in that ES quantities are distributed across the landscape. Because they are generally not fungible with each other and have different values (prices) by location, aggregation is difficult, but not impossible. Where are missing, proxies may be needed. As Boyd and Banzhaf point out, these aggregation challenges are not too different than some of the other more conventional elements of national accounts such as restaurants, banking, and other services and are all practical problems under the development of economic indexes.12 They have been solved for other goods and services, and presumably can be solved for ecosystem services if sufficient investment is made in the required data-collection processes.
An ideal classification scheme for defining and tracking natural capital and ecosystem services would
The reasoning for the first three characteristics are provided in the previous section. The fourth characteristic—applicability of the classification scheme to both project-scale scenario analysis and jurisdictional GA measures—would be useful in ensuring consistency across decisions at different scales of operation, much like evaluation of individual projects for conventional investment decisions follows generally accepted accounting standards established at the jurisdictional level. A conceptual model for a broadly applicable ecosystem service classification system could draw from systems like the North American Industrial Classification System (NAICS)/North American Product Code System (NAPCS). These economic classification systems organize sectors and products logically from large industrial categories all the way down to detailed product codes within each sector. The model might also draw from existing environmental classification schemes, such as water quality classification schemes (e.g., waterways that are boatable, fishable, or swimmable).
Currently, no generally agreed-on classification scheme exists for natural capital and ecosystem services. Boyd and Banzhaf argue that initial efforts to classify ecosystem services, such as Daily (1997) and the Millennium Ecosystem Assessment (2005), although useful for describing the connections between ecosystems and human well-being, are limited as formal classification systems.13 They certainly do not address all of four characteristics listed above. For instance, they do not attempt to distinguish final and intermediate ecosystem services.
Efforts are under way internationally to develop more formal ES classification systems. For example, the European Environment Agency is developing the Common International Classification of Ecosystem Services.14 This system builds on the basic Millennium Ecosystem Assessment classification structure, which distinguishes among provisioning, cultural, regulating, and supporting service categories.15 It is primarily being designed to support GA efforts, in particular the revision of the System of Environmental-Economic Accounting.
In the United States, the U.S. Environmental Protection Agency is developing ES classification systems. These systems include the Final Ecosystem Goods and Services Classification System (FEGS-CS) and the National Ecosystem Services Classification System (NESCS).16 Given its mission as a regulatory agency, the EPA’s main motivation for developing these classification systems is to support SA applications; however, the systems may also prove useful for GA applications. Both systems are focused on identifying and classifying final ecosystem services by linking specific environmental classes with specific categories of human benefits and uses. FEGS-CS approaches the human dimension through a detailed classification of final ES “beneficiaries,” whereas NESCS includes classifications for both human “uses” and human “users” of ecosystem end-products.
Further development, application, and evaluation of these ES classification systems will be needed to determine whether a single unified system that addresses both SA and GA applications is feasible and appropriate.