The overarching rationale for market-based approaches to environmental conservation is that they are more efficient for society than non-market-based approaches. Instead of blocking development projects to prevent environmental harm, market-based conservation approaches allow that harm so long as it is offset by environmental restoration elsewhere. The goal is to prevent net environmental losses, and perhaps even create environmental gains. The common language for describing this is that debits (environmental harms) are compensated for via the purchase of credits (environmental improvements).
This sounds straightforward, and clearly has some appeal to both market and conservation advocates: there are now markets for ecosystem services on every continent except Antarctica, designed to address a wide range of issues from species habitat preservation to water quality improvement to atmospheric carbon sequestration. Despite their geographical and environmental variety, these markets face a common set of issues that each must address if they are to successfully conserve the environment via economic incentives.
This chapter first lays out what, exactly, a market for ecosystem service is. Next it explores the fundamental challenges MES face along with the common tactics used to address them. We then illustrate how these core challenges are addressed in practice via the examples of forest carbon credits and conservation banking.
What do we imagine when we think of a market? Put simply, two (or more) participants voluntarily exchange a good or service for money, whether buying a loaf of bread or paying for a haircut. The voluntary part is key: a person may choose to purchase a particular loaf of bread or they may choose not to; similarly, the baker is under no obligation to sell the product of their labor. Further, as we imagine a market, we often assume there will be multiple products that might meet a purchaser’s needs, and that they will choose among those products based on their own preferences or priorities. Price is one obvious criterion, but a purchaser’s choices may also be influenced by the quality of the goods or services, their particular characteristics, or the interchangeability of the products or services offered for sale.
Markets for ecosystem services, by contrast, typically belong to another category of market—a regulatory market—in which participants enter the market out of government compulsion, not out of choice. In the words of one EPA staff member we interviewed: “At the end of the day, we can say the people are gonna do voluntary restoration, but I’m gonna hold that one of the biggest drivers in any of the ecosystems services markets is that people do it because of regulation and they have to.”1
In regulatory markets, purchasers may not actually want to purchase the product or service they are buying. It is simply a means to an end: meeting regulatory requirements. There is therefore no reason other than price for a purchaser in a regulatory market to choose one product or service over another as long as the product meets regulatory requirements.
An example of a more familiar regulatory market is vehicle emissions inspections. In order to relicense a vehicle each year, many states require that the vehicle must pass an emissions inspection. Importantly, the requirements of the inspection are mandated by the state, and every certified inspection is, by design, identical and interchangeable. Because of government standardization and regulatory compulsion, there is no market competition based on quality; all competition is on price or possibly convenience of the inspection stations. Further, the purchaser has no incentive to seek out a higher quality inspection because they are not entering the market voluntarily. In fact, purchasers are not in the market for an inspection at all; what they seek from the transaction is the sticker confirming regulatory compliance of their vehicle’s emissions level. This distinction between voluntary and regulatory markets is important because most markets for ecosystem services are regulatory markets: buyers enter the market to purchase compliance, not ecosystem services (table 2.1).
Table 2.1
Key differences between voluntary and regulatory markets
| Free market | Regulatory market |
|---|---|
|
Voluntary purchase: buy something because you want to |
Mandatory purchase: buy something because you are required to by regulators |
|
Variety of goods/services for sale, at a range of prices |
Very limited range of goods/services for sale, determined by regulators; variation primarily by price |
|
Competition, and thus innovation |
Competition only on price; very limited innovation |
Regulators (i.e., government staff) play an outsized role in regulatory markets in comparison to their role in a voluntary market. Regulators determine most of the central characteristics of an ecosystem service market, including what the commodity for sale is, such as tons of carbon, acres of species habitat, or emissions certification for vehicles. Regulators also determine what specific requirements must be met in order to create those commodities. Finally, regulators create the demand for these commodities: they determine what types of impacts (debits) require the offsetting purchase of the commodity (credits), and they monitor whether the appropriate commodity has been purchased given the impacting activity. In many ways, the government role in regulatory markets distorts them to the point that they are not particularly market-like at all.
Nevertheless, MES are advocated as a market-like approach for regulatory agencies to achieve conservation goals. And MES do carry some characteristics of markets. While the regulated community must participate in the market, the people or organizations who produce credits for sale enter the market voluntarily and typically as entrepreneurs. Also, there are price differentials—sometimes large, sometimes quite small—between credit providers, and people purchasing credits to offset environmental harms can choose from whom they purchase their credits. As such, there can be competition between providers and price-based selection by purchasers. Finally, competition on price between credit providers occasionally drives innovation, another characteristic of markets.2
The key consideration is that markets for ecosystem services must perform a balancing act between the needs of the market and the realities of regulatory compliance. Critics and thoughtful proponents have put forward a fairly consistent set of concerns about whether or not ecosystem service markets actually deliver their intended environmental benefits or their presumed market-like advantages. These include concerns about:
Some of these issues are considered by MES advocates to be straightforward to address. For instance, the durability of habitat compensation can be ensured through conservation easements.4 Even issues that are difficult to resolve are not viewed by MES advocates as dealbreakers, but rather as subjects for policy adaptation or as opportunities for another market innovation. For example, while it may be difficult to protect forests used to sequester carbon from forest fires, the durability of the sequestration credits sold can be addressed via required insurance contracts if a fire does result in the loss of the offsetting forest.
There are two central concerns with MES, however, that both critics and supporters acknowledge have the potential to undermine their rationale entirely: establishing equivalence, and addressing uncertainty.
The first central concern facing any ecosystem service market is equivalence—whether the benefits produced or gained at a compensation site are equivalent to the benefits lost at the developed site (typically referred to as the impact site). Without equivalence, the rationale for a market-based compensation/offset approach to environmental management crumbles.
Strict equivalence obviously is impossible: the ecosystem at any given site is too complex and contingent, too particularly a product of its unique eco-social history, to be completely or exactly replicated elsewhere. Such ecological purity, however, disallows the entire project of MES. Thus, some accommodation is needed. Instead, supporters argue for something more generalizable: rather than exact replacement of damaged ecosystems, the goal of an ecosystem service market should be net enhancement of equivalent ecological structure and function, or of a discrete set of ecosystem services.5 Assessing even this somewhat relaxed form of comparability between debits (the damage at the impact site) and credits (the improvements conducted at the mitigation site) requires paring away the ecological specificity of particular sites, an act of simplification that is itself not a simple task. Many critics argue that it cannot be done, while supporters argue that it is difficult but doable.6
Uncertainty is a second central concern for any ecosystem service market. If we cannot be reasonably sure that the actions we take to produce credits actually create the ecological benefits we seek, the entire project of MES is moot. More simply, MES require restoring something: uncertainty is whether that restored ecosystem results in the ecological benefits intended. This uncertainty has both physical/ecological and social/political aspects. In both cases, it centers on our ability to control short- and long-term environmental outcomes. On the physical front, uncertainty can revolve around the very notion of ecosystem restoration generally: are we able to successfully restore ecosystems at all? Can we obtain our desired outcomes and preserve them over the long term? On the social front, uncertainty revolves around whether regulatory frameworks will change with shifts in political power, and also whether human actions on site or nearby will affect the efficacy or durability of restoration at a particular site. There is widespread agreement that any credible ecosystem service market must provide satisfactory responses to these concerns, demonstrating our ability to control environmental outcomes to produce the results we seek.7 It is worth noting, however, that even strong advocates of MES agree that while many ecosystems can be reliably restored, there are some that are so difficult to restore or recreate that impacts to them cannot be offset, and thus should not be allowed.8
Different MES attempt to address equivalence and uncertainty in different ways, depending on their geographic, regulatory, and environmental context. Typically, questions of equivalence are addressed through the metrics by which the commodity for sale is defined, while questions of uncertainty are addressed through the regulatory framework that sets the rules for that market.
The overarching purpose of an ecosystem service market is to create a socioeconomic system in which ecosystem damage can be offset. But because no ecosystem can be exactly replicated, the goal of MES is to incentivize (and require) the conservation of some aspects of the impacted ecosystem. Markets for carbon, for instance, do not require conservation of underground coal to compensate for emissions of carbon from coal-fired power plants; rather, they require conservation of atmospheric carbon, thus enabling a newly planted forest to compensate for extracted and burned coal. Markets for stream temperature do not require installation of water-chilling services; rather, they require conservation of thermal loading (i.e., solar input) to streams, thus enabling planted riparian vegetation along headwater streams to compensate for increased warm water inputs from an industrial facility.
In short, equivalence requires a dramatic reconceptualization and abstraction of ecosystems into only those narrow, limited aspects that society deems relevant to conserve at that time. These limited aspects can be functions (e.g., biogeochemical processes such as carbon sequestration or nitrogen retention), structures (wetlands, streams, species habitat), or communities (specific species, or groups of species). Without this abstraction from complex ecosystem to function, structure, or community, MES are impossible. If equivalence were taken literally, the only way to offset the impacts of digging up and burning coal would be to create coal and replace it underground; by abstracting out only one aspect of coal—its contribution to atmospheric carbon—a market for carbon becomes possible because there are numerous potential ways to produce offsets for sale (not to mention numerous emitters of CO2 who would need to purchase offsets for their emissions). The key thing to note is that the more abstractly equivalence is defined, the thicker and more robust the potential market because of the numerous possible ways to produce the equivalent characteristic, and the numerous potential purchasers of that surrogate characteristic.
This abstraction of ecosystem aspects (function, structure, community) to create equivalence requires distilling entire ecosystems into a small set of metrics that are measurable and translatable between sites. This is the central pivot of equivalence: the metrics used in MES must be able to capture both debits and credits and so capture key attributes of sites that are damaged and those that are conserved. MES require that we be able to assess whether there is equivalence between ecological loss and ecological gain, and they require metrics that quantify these losses and gains. Metrics thus convert ecological complexity into a simplified set of characteristics that can be measured, regulated, and sold. The ecological specificity of the impact and conservation sites must be radically reduced to an ecologically coherent core indicator or set of indicators. This simplified metric or indicator, when placed in a regulatory market context, becomes the measurable commodity to be bought and sold. In the parlance of MES, this becomes the credit for sale.9
In any ecosystem service market, simplicity is crucial for enabling comparison of the equivalence of ecosystem debits and credits, but it is not sufficient to ensure a smoothly functioning market. To function well, markets require commodities that are not just simple, but also stable and predictable for market participants. Those producing credits must know that if they go through the effort and cost of production (i.e., restoring a site), there will be a market for those credits—demand—in the future (see chapter 5). Those who are purchasing credits will be more willing to do so if the regulations requiring the purchase are durable, thus providing legitimacy to the incurred costs. Because this is a regulatory market (with credits defined by a regulator), if regulators frequently change how equivalence, and thus credits, are defined, that creates significant regulatory uncertainty for credit producers. Vice versa, credit purchasers need to be sure that when they purchase a credit, it will extinguish their regulatory liability; if there is any uncertainty about this, then there will be far less willingness to use this type of market mechanism for regulatory compliance. Thus, both credit producers and purchasers require that the ways in which equivalence between credits and debits are defined remain stable, or they will be very reluctant to enter the market.
Creating these simple, stable commodities out of complex, dynamic ecosystems, and thus ensuring equivalence between debits and credits, is a far more difficult task than it may initially appear. Ecosystems are characteristically dynamic; they are in constant flux over the time scale of days (e.g., ecosystem production by day; respiration by night), seasons (e.g., floods in spring and droughts in summer; organismal hibernation), and even decades and centuries (e.g., organismal recruitment; migration; forest succession). While some of these changes are predictable, others are not: invasive species or natural disasters such as forest fires or hurricanes have profound impacts on most aspects of the ecosystems regulated via MES. Quite simply, ecosystems are characterized by a lack of the very same simplicity, stability, and predictability on which functional markets depend.
Reducing the particularities of an ecosystem to establish equivalence and define a simple, stable commodity for sale requires grappling with ecosystem dynamics in two ways. From the perspective of a regulator, the system restored must be sufficiently stable or controllable so that what is assessed represents what will exist over some period of time; it must not simply be a snapshot of a condition that may soon degrade. Thus, it must be possible to control the measured characteristics of a system, the system itself must be invariant, or the metrics used by the regulator must be able to integrate over time to capture some average condition that accounts for natural instability but draws attention to degradation or failure of conservation.
For instance, if the equivalent ecosystem service is nitrogen retention in riparian vegetation, then measuring (directly) nitrogen reaching the stream can vary tremendously on whether that measurement occurs during late-winter runoff (when flow and nitrogen loading are high and plant growth minimal) or during late-summer (when flow and nitrogen loading are small and plant growth high). Alternatively, the metric could focus on characteristics of riparian vegetation, which are far less variable; while the number of plants per square meter is an imperfect surrogate for the actual function of interest, density of riparian vegetation provides a more stable metric of nitrogen retention for regulators and for market participants. Thus, riparian vegetation could be used as a proxy for equivalent nitrogen retention in large part because it is temporally stable and is an integrative measure over time.
In sum, equivalency in MES is addressed through highly simplified metrics. These metrics distill complex ecosystems into what is perceived to be their most critical functions or attributes. The metrics must also be relatively stable in the face of natural fluctuations or social dynamics, or both; that is, the particular function or characteristic that metrics quantify must be static, or at least controllable, over the lifetime of a conservation project in order to meet market needs.
Markets for ecosystem services, and ecosystem restoration more generally, are inherently uncertain (as discussed in chapter 3) because of the wide variety of functions underlying ecosystems and the peculiarities of people and markets. To be blunt, it is unclear whether many types of ecosystem restoration actually reverse the ecological damages they are intended to undo. In an attempt to address these eco-social uncertainties, MES require standards of practice, typically in the form of regulatory frameworks developed by public agencies or authorities. In some cases, the participants in an ecosystem service market—those who will produce the credits for sale, or those who will be required to purchase the credits, or both—are consulted in setting the basic rules for these regulatory markets; in most cases, however, public agency staff develop regulatory frameworks for MES on their own, although iteratively based on experiences. Because MES are regulatory markets, regulatory frameworks effectively set the rules to address fundamental concerns and questions, most notably:
Regulatory frameworks can address and potentially alleviate many sources of uncertainty for credit providers, purchasers, and regulators, but these frameworks must do so in a way that does not stifle the potential market. This forces trade-offs between different kinds of uncertainty. For example, in order to address regulatory uncertainty about whether or not an endangered animal will be able to survive the loss of its habitat, most MES intend that new, conserved habitat should already be present before any credits can be sold. However, this requires credit providers to invest a great deal of money to build a conservation project long before any generated credits can be sold, creating tremendous financial uncertainty for credit providers. In this type of regulatory approach, a credit provider has to wait a long time before realizing even the potential to generate a return on their investment, along with experiencing uncertainty about how many credits the project will generate and whether there will be buyers for those credits in the future. To balance these competing sources of uncertainty (i.e., to balance regulators’ need to ensure endangered species have access to high-quality habitat with credit providers’ unwillingness to participate in a regulatory market without some reasonable expectation of profit), the regulatory frameworks for MES often allow credits to be sold by producers before the credit site has been fully completed and assessed. That is, credits can be sold that do not yet exist.10 This is a mechanism developed by regulators to strike a balance between the uncertainty of credit providers and the uncertainty associated with the needs of a species or ecosystem, a constant tension and balancing act for any ecosystem service market.
There is also high uncertainty about the long-term prospects of conserved ecosystems. Will a project continue to provide ecological benefits over years or decades, or will it either degrade over time or be destroyed for a new development project? Can we control the site itself and the impacts of outside forces upon it sufficiently well to obtain the environmental outcomes we seek? MES typically require a monitoring period after conservation project completion to demonstrate some ecological effectiveness over time. But again, the regulator must balance the needs of market uncertainty with those of ecological uncertainty. The regulator could minimize ecological uncertainty by requiring monitoring and demonstrable benefits for many years, or even decades, allowing only very slow, gradual release of credits over time. This would place tremendous uncertainty on the credit provider, however, as they would be forced to internalize uncertainty over how their conserved project performs over time, recognizing that they cannot control broader environmental conditions that inevitably drive site performance (e.g., droughts, fires, invasive species). Alternatively, if the regulator allows the credit provider to have immediate financial returns in very short periods of time, there is significant uncertainty for the ecological trajectory of the site.
A trade-off to balance the uncertainty of long-term disposition with the needs of the market has been to combine several years of monitoring with conservation easements: regulators typically mandate that compensation sites be monitored for several years (e.g., five to seven years for streams and wetlands) and then maintained in perpetuity (often via conservation easements managed by state agencies or private land trusts) to ensure that the ecological benefits created via MES will not be lost to subsequent development.11 This assumes that even if we cannot control what happens at the site and the benefits of the conservation activities themselves prove transient, the land will not be developed, providing at least a minimal level of conservation and reduction of ecological uncertainty for the future.
A particularly problematic source of uncertainty is whether many kinds of ecosystem conservation can be accomplished successfully. In some cases, ecosystem conservation and restoration are relatively novel in terms of type or scale, and thus best thought of as emerging science and technology.12 In other cases (such as stream restoration; see chapter 3), ongoing science and long-term monitoring raise questions about the efficacy of what were thought to be well-established practices.13 Most scientists and regulators accept the fact that restored ecosystems will have biological communities and functions that are poorer (or at least different) from their undisturbed counterparts, or that restored ecosystems take a period of time to gain functions comparable to undisturbed systems. That is, the basic efficacy of ecosystem conservation, which undergirds market-based approaches, is highly uncertain.
In order to address this most basic source of uncertainty while still allowing MES to proceed, regulators use trading ratios, by which a particular number of debits can only be offset by a higher number of credits. Importantly, trading ratios are intricately linked with metrics that address equivalency issues in myriad ways, as we will explain. Trading ratios work in very much the same way that factors of safety do in engineering. For example, when designing a bridge, there are sources of uncertainty when calculating the size of a pier or the stiffness of a beam. Engineers conduct rigorous analyses to specify such dimensions, but then increase the final value by some percentage to offset the risks associated with uncertainty in scientific precision or accuracy present in the many analyses leading to that final value. If the analyses suggest that a bridge pier should be 1.5 meters in diameter, the engineer may use a safety factor of 2, and recommend a pier 3 meters in diameter. Factors of safety are used to quickly mitigate the effects of the many inevitable sources of uncertainty in any design project that cannot be fully accounted for or controlled. Similarly, if regulators feel the science underlying a particular type of stream restoration—say, restoration of cold-water small streams for an endangered frog species—is fairly certain, then a small trading ratio can be used, perhaps 1.5:1 (i.e., 1.5 units of restoration are needed to offset 1 unit of impact). If instead regulators are uncertain about the scientific basis of this kind of restoration, then a larger trading ratio may be used in an attempt to compensate for the uncertain outcome (e.g., 5:1). As scientific understanding and experience increase the likelihood of success (and uncertainty decreases), the trading ratio can become less lopsided.
Regulators also use trading ratios to address issues of equivalence: larger trading ratios can be used to compensate for a lack of equivalence between impact site and compensation site. In the case of wetland markets, if a conservation site is to be used to compensate for an already degraded impact site, then a trading ratio of only 1.5:1 or 2:1 might be used. But if that same conservation site were to be used to compensate for impacts at a nearly pristine site, then a trading ratio of 6:1 might apply. Similarly, geographic proximity of a conservation site to an impact site typically is considered ecologically beneficial because it increases the similarity between the functions and communities lost and those gained via conservation. Thus, regulators apply lower trading ratios for nearby compensation sites, and higher ratios for more distant sites. A similar approach can be used to address temporal disparities, or even differences in types of systems; for example, a certain type of ecosystem impact is offset by compensation of a different type altogether, and the greater the difference in types, the greater the trading ratio applied.
There are multiple reasons to use trading ratios, but a fundamental one is that trading ratios enable the continued use of simplified metrics to represent complex ecosystems. While the sources of uncertainty are real, they are also quite subtle and complex. Distinguishing the ecosystem variations of impact and compensation sites between locations or types or timing at the level necessary to ensure that a trade results in equal amounts of functional loss and gain (equivalence) would push the bounds of science while also requiring significant data collection, analysis, and expertise to be deployed for each individual transaction. Such effort would undermine one of the chief rationales of market-based approaches—improving the efficiency of complying with environmental regulation—by creating untenable delays and increasing the costs of each transaction. Each impact would need to be studied in detail before deciding how many credits would need to be purchased on the market; meanwhile, each restoration site would likewise need to be studied in exceptionally high detail. These delays and associated costs would preclude any market from developing at all. By subsuming all of these sources of uncertainty into trading ratios, regulators are able to continue using the same metrics of site assessment for both impact and compensation sites. Regulators can also respond to scientists’ calls for higher precision, or to environmental advocates’ concerns that markets result in the loss of net ecosystem function, by hedging with higher trading ratios. Thus regulators can say that regardless of the effectiveness of restoration, the end result is a net gain in permanently conserved land (through the requirement of easements coupled with >1:1 trading ratios). Moreover, this approach of using higher and higher trading ratios also increases the flow of credits through increasing demand from impactors, thus bolstering the overall market side of MES. Quite simply, trading ratios amplify and accelerate both sides of the balancing act that regulators must negotiate: increasing a trading ratio decreases the ecological risk that the restored ecosystem will not offset damages, while simultaneously increasing the demand for more credits (i.e., increasing the thickness of the market). Trading ratios offer regulators and market participants a ready cure for many of the underlying uncertainties in MES. Yet using trading ratios obscures the fact that they do not address the root causes of uncertainty; rather, all of the uncertainty of ecosystem restoration is subsumed under the umbrella of trading ratios.
Trading ratios have received considerable attention in the literature about MES. In studies of the economics of trading ratios, it is presumed that their creation and application is unproblematic.14 Yet there is substantial debate as to whether ratios are an adequate avenue for addressing this fundamental uncertainty.15 Studies that carefully consider the uncertainty of restoration efficacy find that to ensure equivalency would require trading ratios many times higher than those typically used.16 This raises questions about what, exactly, trading ratios are addressing. After all, if attempts at restoration are fundamentally inadequate, simply expanding their scope and scale through greater numbers of restored ecosystems—a result of higher trading ratios—seems unlikely to produce desired conservation results. Thus, there is not yet consensus as to whether uncertainty can be successfully addressed via regulatory frameworks.
Perhaps the easiest way to understand how MES address these complex issues of equivalence and uncertainty is to see how two quite different ecosystem service markets—forest carbon credits and species conservation banking—address them in practice via credit definitions (metrics) and regulatory frameworks.
The Clean Development Mechanism (CDM) is a market-based regulatory framework for addressing atmospheric carbon and associated climate change laid out in the Kyoto Protocol. Under the CDM, developed countries required to offset their greenhouse gas emissions can purchase offsets from developing countries. In this MES, the commodity for sale is the Certified Emission Reduction unit, which can be produced by a range of possible activities (e.g., replacing coal-fired power sources with solar arrays or capturing fugitive emissions of powerful greenhouse gases), all of which are exactingly specified in the CDM. Particularly in comparison to the complexities of defining equivalence between ecosystems, defining equivalence between tons of CO2 emitted or reduced is relatively straightforward: a unit of CO2 is neither internally complex nor in any way specific to the eco-social context that produced it. The source of complexity and uncertainty lies in which types of projects are allowed to produce those relatively simple credits.
Initially, the CDM specified that Certified Emission Reduction units could be produced by reducing carbon emissions, but not by absorbing (i.e., sequestering) greenhouse gases after they had been emitted, such as via reforestation. Put differently, credits could be produced by reducing sources of emissions, but not by producing sinks. This type of constraint on the market is possible because it is a regulatory market not a voluntary one, so that the commodity for sale (i.e., credit) is created by government fiat rather than by voluntary participation and creation.
Advocates for including reforestation projects in the CDM as an allowable mechanism of producing Certified Emission Reduction units argued that terrestrial carbon sinks could play a crucial role in greenhouse gas reductions by absorbing excess emissions until developed countries could feasibly reduce them, creating a “wooden bridge” into a clean energy future. Critics were skeptical about the impermanence of these credits: there was a very real possibility that Certified Emission Reduction units sold for carbon sink projects could vanish abruptly due to natural or human disturbances (e.g., forest fires), destabilizing the CDM market and efforts to combat climate change.17 Dutschke and Angelsen, for example, identified five major issues that could lead to early re-release of carbon including risks from natural disturbances, from climate change, and from direct human reversal of reforestation via logging, burning, or neglect.18 Critics thus were concerned about the durability and stability of credits over time in the face of profound broader uncertainty.
After extensive debate, the CDM was expanded to include sink projects in 2003 via the Afforestation and Reforestation protocol.19 The uncertainty about whether reforestation projects would be able to sequester carbon reliably even over relatively short timespans became a central topic of debate, and the way in which reforestation was eventually accepted into the CDM reflects this: unlike conservation projects intended to persist in perpetuity, credits from reforestation come with set expiration dates. Rather than trying to achieve permanence, these credits are predicated on impermanence. In the case of temporary Certified Emissions Reduction units, for example, the credits expire every five years; even long-term Certified Emissions Reduction units have a maximum lifespan of forty years. Once credits expire, their initial purchasers must find other sources of Certified Emission Reduction units to offset their impacts.
The development of the CDM has been heavily influenced by the concerns of the scientific community, as demonstrated by the complex and carefully specified metrics and guidelines for producing carbon sequestration credits. While concerns for market viability are clearly present, imperatives for stability and simplicity seem to have taken a backseat to attempts to address the plausible uncertainty about physical and social risks.
It is perhaps unsurprising, then, that the CDM market is not functioning as well as its advocates had hoped, with credit prices at a mere fraction of their original values.20 Carefully addressing issues of uncertainty and equivalence came at a steep cost: the credits for sale were widely perceived as too complicated and unstable and thus not worth the investment, and the carbon market has been anemic at best.
While the U.S. Endangered Species Act (ESA) is often portrayed as the ultimate inflexible regulatory hammer, the ESA in fact allows impacts to habitat of federally listed species (e.g., threatened or endangered) to occur as long as they are offset by habitat conservation elsewhere.21 These offsetting projects are often called conservation banks, and are comparable to mitigation banks used for offsetting dredge/fill impacts to aquatic ecosystems (introduced in the previous chapter). The rationale for conservation banking at the federal level stems from the ESA’s prohibition of take (i.e., harm, harassment, or killing) of individuals from endangered species or destruction of their habitat. Conservation banks allow take to occur as long as there are offsetting conservation measures elsewhere, providing the equivalent ecosystem service of habitat for the species in question.
Like most other MES, there are no voluntary participants in the conservation banking market. Rather, credits are purchased from conservation banks because of regulatory compulsion, typically by land or oil/gas developers, and increasingly by large land-intensive alternative energy projects such as wind and solar production facilities. Regulatory agencies determine what characteristics must be present for a conserved ecosystem to count as a conservation bank for a particular species, and thus to produce habitat credits for sale.
The first conservation bank was established in the United States in 1995 in California. As late as 2002, conservation banks could only be found in California, and even as of 2015, more than three-quarters of the 137 federally approved conservation banks were in that state.22 As of 2013, 73 percent of conservation banks were private, for-profit ventures. These banks vary in size by three orders of magnitude, from eight acres to just over four thousand acres, and have been established to compensate for impacts to a wide range of protected species, from tortoises to foxes to bats.23
Compared with the highly detailed international regulatory framework for forest carbon credits, the regulatory framework for conservation banking is quite limited and case specific. There was no federal guidance for conservation banking at all until 2003, and even that is far less detailed than the regulatory framework for Certified Emission Reduction units. Also, unlike forest carbon credits, conservation banking depends primarily on preservation of existing high-quality habitat rather than restoration or creation;24 according to one study, 94 percent of conservation banks through 2005 were primarily preservation projects.25 Thus, uncertainty in this ecosystem service market is addressed because the habitat protected is already of very high quality, so the risks of unsuccessful restoration are greatly reduced, and via trading ratios determined by comparing the quality of the habitat at the credit site to that at the impact site.
How equivalence—and thus the actual conservation credits for sale—is determined is specific to each bank and the species preserved there.26 Early in the history of conservation banking, credit determination methodologies were often quite complex, based on careful, nuanced attention to the ecological needs of specific species. For example, in 1998, credit calculations for vernal pool banks in Central California paid careful attention to equivalence, taking into consideration the size of the proposed bank, the rarity of the type or types of vernal pools included, the relative rarity of the endangered species at the site, the condition of the habitat, and its long-term feasibility based on surrounding land uses. The result of this ecologically specific definition of equivalence between impact and credit sites was a complex set of calculations dependent on careful ecological surveying combined with a healthy dose of best professional judgment. This state of affairs seems not to have lasted long; by 2008 vernal pool credits were calculated on the far simpler basis of acreage, as are 91 percent of conservation banks nationwide.27
Another illustrative example of conservation banking is the market for the federally listed red cockaded woodpecker. Breeding pairs of woodpeckers are the lynchpin of species survival, and would be a suitable metric in terms of scientific and ecological rationales. However, the birds themselves are difficult and resource intensive to monitor. Moreover, their viability and breeding are subject to myriad external factors beyond the possible influence or control of credit providers, constraining the durability of any credit (based on breeding pairs) that might be created. Rather than establish a market based on breeding pairs, regulators instead established credits for this species based only on acres of suitable habitat. Yet even this relatively simple metric has proven difficult to sustain and regulate: while there is supposed to be careful long-term monitoring to ensure that high-quality habitat is maintained, such monitoring has been “haphazard and limited, and it is not at all clear whether these banks are supplying the habitat for which they were established.”28
In conservation banking for ESA compliance, concerns about stability, ease of measurement, and durability have superseded attempts to address complexity, unpredictability, and equivalence. The market for conservation credits appears to be doing very well even if we cannot determine whether the target species are in fact being conserved.29 But these experiences demonstrate the tightrope ecosystem measures and metrics must walk: precise enough to represent the ecosystem while nebulous enough to allow a market to operate. This is the balancing act that all MES must confront.
Markets for ecosystem services share a set of issues that must be addressed, regardless of whether their focus is carbon sequestration or woodpecker habitat. First, any ecosystem service market must determine how it will define equivalence between the impact and compensation sites and manage the trade-offs between ecological complexity and economic stability. Second, any ecosystem service market must find ways to address the many physical and social forms of uncertainty about whether credit producers can actually deliver gains equivalent to the losses we expect them to offset. Therefore, regardless of the impact they are intended to address, MES face a series of trade-offs between ecological and economic concerns, balancing the requirements of robust markets and ecosystems.
We turn now to the history of the regulatory market at the heart of this book: stream mitigation banking. How and why did humans begin intervening to improve the ecological health of rivers and streams? How have those interventions evolved over time? And how did they set the stage for creating an ecosystem service market for streams in the 1990s?