Science for the sustainable use of ecosystem services

Frameworks for assessing ecosystem services

Around the turn of the century, scientists identified the need for an international assessment of ESs. The idea was to develop something akin to the Intergovernmental Panel on Climate Change but for ecosystems, taking advantage of recent advances in ecological and other sciences in the 1990s and putting this knowledge in the hands of international policy-makers²⁴. Ultimately, this became the Millennium Ecosystem Assessment (MA). The MA developed an ES framework that reflected the thinking of the time, showing a relationship between ESs (left side of Figure 1) and HWB (right side of Figure 1); arrows generally flowed from ecosystems and their services toward wellbeing, and the focus was on understanding the intensity of linkages and the potential for mediation of the relationship^3,23.

Figure 1. The Framework of the Millennium Ecosystem Assessment (2002).

Reproduced from the Millenium Ecosystem Assessment (2002).

In an update conceived by de Groot et al.⁵ and based on the cascade model of Haines-Young and Potschin²⁵, the MA framework is broken down into more of its constituent parts (Figure 2). Here, ecosystem structure and functions (that occupy much of the early thinking on ESs noted in the previous section) support the provision of a service, which is the actual benefit of nature to people. Breaking down the concept into these parts helps to gain clarity on how services are provided by nature, allowing the ecosystem to become multi-faceted and complex in our understanding. De Groot et al.⁵ have added here the idea of feedbacks from HWB to both ESs and ecosystems, indicating that people can alter ecosystems and the services provided on the basis of their desires or differences between their perception of services provided and services required. Although we know that people are critical players in the delivery of ESs—plowing, fertilizing, seed planting, and harvesting are needed to produce food, even if there is already good natural capital (for example, high-quality soils) in place—the primary idea of even this new framework is that ecosystems alone ultimately provide services to people. That is, there is a general and primary flow from the left (ecosystems) to the right (people), and feedbacks are from the people to the ecosystem.

Figure 2. The Economics of Ecosystems and Biodiversity Framework.

WTP, willingness to pay. Reproduced from Braat and de Groot⁷⁸ (2012), adapted from Haines-Young and Potschin²⁵ (2010).

This rather linear conceptualization of ESs was given another significant update²⁶ (Figure 3), including a diagram in which it is not “nature” but social-ecological systems (nature and people together), which generate bundles of services (multiple services together), which impact various dimensions of HWB. HWB, in turn, affects management and governance. In this framework, the social system plays a critical role not only in demanding and receiving ESs but also in determining their provision. This is significant because it emphasizes the role of society in the provision of services, moving the ES conversation to the more nuanced depiction of dynamic human-nature relationships^13,27,28. Also critical in this framework is the explicit consideration of ES bundles rather than single services. Other non-linear frameworks have been proposed. For example, Liu et al.²⁹ note that telecoupling (socioeconomic and environmental interactions between different places) is increasingly important in the Anthropocene and ought to be included in the way we understand and measure ESs.

Figure 3. A social-ecological framework for ecosystem service and human wellbeing.

SES, social-ecological systems. Reprinted with permission from Reyers et al.²⁶ (2013).

Advances in mapping and measuring multiple services

Beyond frameworks, the past decade has also brought considerable advances in measuring ESs and using these measurements as tools in decision-making. One of the most critical and basic advancements brought about by ES science is the focus on the ways that we use ecosystems (actively and passively) to ensure HWB²⁸ and the (direct and indirect) contribution of ecosystems to HWB^30,31. A major challenge in this has been in approaching the science of ESs as holistically as the concept implies, especially in terms of interactions between multiple services, spatial dynamics, and change over time.

Although some early articles focused on mapping multiple ESs to understand associations among services³² or among multiple services and biodiversity (for example, 33, 34), much of the ES literature has failed to live up to the promise of ESs to link nature and HWB, or to consider all aspects of sustainability, and a great many articles examine only one service, measure services at a single time snapshot, or measure ecosystem function with little or no connection to HWB³⁵. By contrast, decision-makers most often need information about multiple services and how they affect outcomes for people in order to make decisions that improve long-term sustainability⁵. When the goal is to use ESs to improve sustainable development, considering multiple services over time is critical because any decision is likely to result in trade-offs, in which increases in some services lead to or are associated with declines in production of other services³⁶.

However, there are examples of ES studies that have focused on multiple services and sometimes on linking these to potential decisions or to HWB. For example, Bateman et al.³⁷ highlight the UK National Ecosystem Assessment, which combined spatially explicit ecological models with economic valuation to assess ESs and improve land use planning in the UK. Scientists have looked for areas that are hot spots of high provision of multiple services and understanding what creates these win-wins (for example, 32–34). Qiu and Turner³⁸, for example, found that, although most relationships among ESs were synergies, hot spots (locations where at least six services were produced at high levels) were quite rare, occupying just 3.3% of the landscape. These authors also found that trade-offs were not consistent across space. That is, whereas most locations had a trade-off between crop production and water quality, some locations had both high water quality and high crop production, suggesting that this trade-off is not inevitable or that it might be able to be ameliorated. This study not only provided specific data about ES provision in a particular place for decision-makers in that region but also developed some generalizable knowledge, such as that managing ESs over large areas is likely to improve our ability to manage for sustainable provision of services³⁸.

A recent development in ES sciences is the movement from studies of single services or pairs of services to studies that focus on bundles of ESs, associations of several ESs that appear together repeatedly in space or time. Queiroz et al.³⁹ identified five distinct types of ES bundles in Sweden: “forests and towns”, “remote forest”, “mosaic cropland-livestock”, “mosaic cropland-horse”, and “urban”. They found that the production of an ES or ES bundle was based on a combination of the social-ecological potential (ecological and biophysical conditions and management practices) of a landscape to produce it and the human demand for that same service. In this as in many studies on ES bundles, hot spots of provisioning service production are often cold spots for regulating services. Thus, it is increasingly apparent that both ecological and social gradients are needed to adequately predict patterns of ES provision across landscapes^40–45.

In addition to understanding how social-ecological landscapes provide ES bundles, progress has been made in refining the idea of trade-offs among pairs of services. Mouchet et al.⁴⁶ suggest that there are three types of trade-off assessments. Supply-supply assessments are about how supply of one service affects supply of another; supply-demand assessments are about whether the ecosystem can meet demand; and demand-demand assessments are about stakeholders’ competing interests. The method the authors propose takes a step toward embracing social-ecological systems and complexity in considering both supply and demand as well as their interactions. The importance of understanding the difference between supply, demand, and ecosystem capacity to provide services was also highlighted by Villamagna et al.⁴⁷, who pointed out that it is the comparison of supply with demand in the current time that determines satisfaction with the services provided and that it is the comparison of capacity with supply that determines the potential for sustainability.

Another advance in measuring and mapping ESs has been work to understand the role of landscape structure—the configuration of land use and land cover—in the provision of services. This is important for landscape management, especially over large areas, as suggested by Qiu and Turner, as the structure of the landscape is something that land use planners can influence with reasonable precision. Different spatial patterns of land use and cover may benefit different services, and trade-offs between services can be mitigated or exacerbated by fragmentation at different scales^48,49. Landscape complexity, measured in terms of the proportion or diversity of natural habitat or its arrangement in the areas surrounding agriculture or both, enhances the pollination of crops⁵⁰ and pest control by natural predators⁵¹ in a variety of cropping systems and regions⁵². For these mobile organisms benefitting cropland, increasing interface between human and natural systems generally increases service provision, assuming an adequate ratio of natural to agricultural habitat. Other services may be reduced by this type of natural-agricultural mosaic; Chaplin-Kramer et al.⁵³ demonstrate that forest fragmentation reduces carbon sequestration by an average of 25% across the tropics. Whereas previous studies had estimated carbon sequestration on the basis of a benefits-transfer approach that assumes a direct relationship between forest area and carbon storage, the study by Chaplin-Kramer et al. shows that the configuration of the land use, and especially the amount of forest edge created by deforestation, makes a difference to the amount of service provided. Studies of carbon storage in temperate forests also find important effects of both spatial structure and human management⁵⁴. For water-related services, the aspect of landscape configuration that matters most is hydrologic connectivity to water courses⁵⁵, which presents yet another type of spatial habitat pattern to consider in managing for multi-functional landscapes.

Although many ES studies have been snapshots of service provision at a single moment in time, it is widely acknowledged that ESs and their relationships with each other, and with the drivers that affect their supply, are unlikely to remain constant over time⁴⁶. Recent studies have begun to examine how changes in landscapes over time have affected the provision of services. Renard et al.⁵⁶ found that some individual service relationships varied through time, shifting from trade-offs or no relationship at the start of the study (1971) to synergies by the end (2006). In terms of bundles, in 1971, the landscape was diverse, but most municipalities across the landscape were all providing similar bundles; by 2006, the landscape remained fairly diverse, but each municipality tended to specialize in the provision of one or a few services.

Finally, mapping and measuring ESs have been and will continue to be critical methods for understanding past trends and anticipating future trajectories and for evaluating the impact of policy interventions and whether goals are being met. However, many decisions require more information than can be gleaned from examining changes that have already occurred; policy-makers and other incentive setters wishing to promote the sustainable use of ESs have questions about where the most important places are to invest in conservation or restoration, what the impacts of allowing different types of development will be for different stakeholders, or how to most cost-effectively mitigate those impacts (Table 1). In many cases, measuring ESs on the ground in specific places has led to empirical models that can inform decision-makers in those regions^48,57. For example, work by Fisher et al.⁵⁸ focused on understanding the various benefits of reducing deforestation in Tanzania.

Including people, governance, and resilience

These improvements in scientists’ ability to map, measure, and model individual ESs, pairs of ESs, and bundles of ESs have led to discussions about how ES science could be used to improve ecosystem management or to understand and assess progress toward policy targets such as the Sustainable Development Goals. However, actual use of ES science in decision-making has sometimes fallen short of expectations^2,59,60. Carpenter et al.⁹ suggest that part of the problem may be a discipline-bound focus of some of the science as well as failure to consider feedbacks over a range of biophysical and social systems. Reyers et al.²⁶ propose that, in the rush to gather data, science has found itself with a plethora of measures that fall short of their intended purpose. That is, we have lots of measurements, but these use conflicting definitions or poor indicators, which makes use of ESs to assess targets like the Sustainable Development Goals difficult at best. Newer studies are advancing rapidly in developing multiple ES-based methods for assessing the effect of policy interventions on sustainability. For example, Hamann et al.⁶¹ developed and tested an approach to mapping social-ecological systems on the basis of characteristic bundles of ES use. The idea was that these bundles ultimately could be used as a tool to identify different social-ecological system types and target governance interventions more appropriately.

One outcome of the focus on social-ecological systems has been increased interest in HWB and in co-design of research projects with stakeholders, research that actively involves decision-makers to improve uptake and use of information in decision-making⁶². Cundill and Fabricius⁶³ suggest that although there is a wealth of frameworks for understanding complex systems, relatively less attention has been given to co-design and other approaches that might facilitate learning as part of the monitoring process. Such co-design is important because it can help ensure that science is both interesting to the scientific community and useful to decision-makers⁶⁴. This helps mainstream ESs as a part of decision-making. Similarly, researchers are now pointing out the need to include more nuanced, quantitative analyses of ESs and HWB⁶⁵ and even developing indices to understand when and how wellbeing depends on provision of services⁶⁶. Ultimately, if decision-makers are concerned with the wellbeing of constituents or stakeholders, research that goes only as far as the biophysical components of services may be less useful than work that quantifies HWB outcomes or seeks to understand relationships between services and wellbeing.

Including social-ecological systems has also paved the way to merge concepts of resilience with ESs, a significant step forward in moving ES science to a place where it can improve ecosystem management for sustainability. Extensive anthropogenic changes, mostly to provide certain ESs such as food, have increased the likelihood of large, non-linear, and possibly irreversible changes in ecosystems^67,68. Recognizing that enhancing ES resilience is crucial for meeting current and future societal needs, Biggs et al.⁶⁹ use the literature to suggest seven principles for enhancing the resilience of ESs in social-ecological systems: maintain diversity and redundancy, manage connectivity, manage slow variables and feedbacks, foster an understanding of social-ecological systems as complex adaptive systems, encourage learning and experimentation, broaden participation, and promote polycentric governance systems. Developing this definitive set of resilience-enhancing principles for ESs and a synthetic understanding of when and where they apply is important for those in the governance arena seeking to ensure a sustainable provision of services for the long term while avoiding large, non-linear changes in service provision, which can have catastrophic effects on HWB.