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Framing natural assets for advancing sustainability research: translating different perspectives into actions

  • Maria Jose Martinez-Harms
  • Stefan Gelcich
  • Rainer M. Krug
  • Fleur J. F. Maseyk
  • Hannah Moersberger
  • Archi Rastogi
  • Geoffrey Wambugu
  • Cornelia B. Krug
  • Eva M. Spehn
  • Unai Pascual
Open Access
Special Feature: Overview Article Integrated Knowledge Generation for Transformations towards Sustainability from Local to Global Scales
Part of the following topical collections:
  1. Special Feature: Integrated Knowledge Generation for Transformations towards Sustainability from Local to Global Scales

Abstract

Sustainability is a key challenge for humanity in the context of complex and unprecedented global changes. Future Earth, an international research initiative aiming to advance global sustainability science, has recently launched knowledge–action networks (KANs) as mechanisms for delivering its research strategy. The research initiative is currently developing a KAN on “natural assets” to facilitate and enable action-oriented research and synthesis towards natural assets sustainability. ‘Natural assets’ has been adopted by Future Earth as an umbrella term aiming to translate and bridge across different knowledge systems and different perspectives on peoples’ relationships with nature. In this paper, we clarify the framing of Future Earth around natural assets emphasizing the recognition on pluralism and identifying the challenges of translating different visions about the role of natural assets, including via policy formulation, for local to global sustainability challenges. This understanding will be useful to develop inter-and transdisciplinary solutions for human–environmental problems by (i) embracing richer collaborative decision processes and building bridges across different perspectives; (ii) giving emphasis on the interactions between biophysical and socioeconomic drivers affecting the future trends of investments and disinvestments in natural assets; and (iii) focusing on social equity, power relationships for effective application of the natural assets approach. This understanding also intends to inform the scope of the natural asset KAN’s research agenda to mobilize the translation of research into co-designed action for sustainability.

Keywords

Sustainability Knowledge exchange Ecosystem services Natural capital Human actions 

Introduction

Global efforts to achieve the United Nations sustainable development goals (SDGs) require an understanding of how nature and biodiversity will be impacted by global environmental change. Many natural systems are being pushed beyond their limits (Rockström et al. 2009), as the ability to produce socially desired goods in the short term is favoured over critical longer-term ecosystem processes (Rasmussen et al. 2018). Consequently, signs of escalating and compounded stresses are evident at global, national and local scales and are reflected in local and regional scarcities of water, widespread land degradation and loss of biodiversity (Griggs et al. 2013; IPBES 2018). The consequences of biodiversity loss for ecosystem functioning, the provision of an array of regulating ecosystem services, and ultimately for human well-being have been identified as a major concern amongst the scientific community (Hooper et al. 2005; Balvanera et al. 2006; Díaz et al. 2006; Worm et al. 2006; Cardinale et al. 2012; Rasmussen et al. 2018).

The sister twin “natural capital” and “ecosystem services” approach, putting emphasis on the multidimensional analysis of the benefits provided by ecosystems, has gained increasing attention in some policy circles and business in the last 20 years (Costanza et al. 2017). This is mainly because it allows considering these benefits in decisions from which they were usually absent (Maes et al. 2012; Bennett 2016). This has the potential to result in decision-making processes that take into account the benefits that nature provides to people facilitating communication and collaboration among scientists, practitioners, decision-makers, and other stakeholders. Ecosystem services science has experienced great popularity and advances (De Groot et al. 2010; Bennett and Chaplin-Kramer 2016) with several high profile and referenced efforts (MA 2005; Sukhdev 2010). While the importance of natural capital (i.e. the stock of natural resources) and ecosystem services is increasingly being recognized (Dasgupta 2010; Dominati et al. 2010; Kareiva 2011; Bateman et al. 2013; Guerry et al. 2015; Maseyk et al. 2017), there has been a relatively modest uptake of these advances in decision-making (Laurans et al. 2013; Martinez-Harms et al. 2015) and practical guidance on taking responsibility and actions for management are still lacking.

In a recent contribution, Díaz et al. (2018) presented the notion of “Nature’s Contributions to People” (NCP) as a central element of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services’ (IPBES) conceptual framework. The authors proposed NCP as a broader framing building on the ecosystem services approach while opening up to other perspectives, mostly associated with the social sciences and humanities, which are rich in explaining the complex and diverse realities about people’s relationships with nature. The NCP approach has triggered a lively debate with some players in the ecosystem services science community questioning whether a paradigm shift or drift from ecosystem services to NCP is justified (e.g. Maes et al. 2018; Peterson et al. 2018; Faith 2018). We believe that the diversity of perspectives across scientific disciplines enriches and facilitates progress in science, without inhibiting policy making. To foster support to the IPBES process, we agree that there is no one-size-fits all framework to cover all the diverse problems that nature and people face (Peterson et al. 2018) and that the attempt by the NCP approach to enlarge the tent which can advance integrating a growing knowledge base and the need for transformative action towards sustainability. The NCP approach can help to find a flexible and adaptive approach according to the specific policy process objectives and decision-making audience, facilitating collaboration and knowledge exchange among different stakeholders connecting knowledge and action.

Future Earth, a global network for sustainability science, has recently launched a new global initiative, the natural assets knowledge–action network (KAN), which directly connects to IPBES. Similar to the broadening of the ecosystem services approach by the framing of NCP, a new flexible and adaptive framing has recently been adopted by Future Earth based on the notion of ‘natural assets’. As with NCP, the aim is also to translate and bridge among different knowledge systems and different perspectives about people’s relationships with nature. The natural assets approach emphasizes the role of human actions on reshaping nature and can complement the NCP framework. Emphasizing on human actions to protect or responsibly manage nature can help connect knowledge systems and actors engaged in reshaping nature. To operationalize the natural assets approach, the KAN brings together scientists and other stakeholders from a wide variety of disciplines, sectors and organizations with the ambitious challenge of creating a community of practice for achieving sustainable stewardship of natural assets underpinning human well-being. Activities within the natural assets KAN strive to respond and shape nature under conditions of uncertainty and change.

This paper aims to clarify the natural assets concept for the global Natural Assets KAN community discussing challenges that the KAN will face in operationalizing the natural assets concept. These challenges are:
  1. (i)

    embracing richer collaborative decision processes to build bridges between different human-nature perspectives;

     
  2. (ii)

    Emphasis on the interactions between biophysical and socioeconomic drivers affecting the future of natural assets; and

     
  3. (iii)

    focusing on social equity, power relationships and discourses for effective application of the natural assets approach.

     

Addressing these challenges will be useful to inform the scope and definition of objectives, and ensure the relevance of the activities of the natural assets KAN.

Concepts underlying the natural assets approach: natural capital, ecosystem services and nature’s contributions to people

There has been a boom of interest in writing and reading about nature as people seek to reconnect with ecosystems. This explains the increment of concepts and notions (e.g. natural assets, natural capital, natural capital stocks, ecosystem services, nature’s contributions to people, natural-based solutions) and the literature to explain human–nature relationships attached to efforts to conserve and manage ecosystems (see Table 1).
Table 1

Definitions of the most common terms used to explain people’s relationships with nature appearing in the literature

Terms

Definitions

Links

Natural assets (NA)

Biotic and abiotic components that are owned and managed leading to the flow of ecosystem services over time (Mace et al. 2015)

NA = N = E

Natural capital (NC)

The abiotic and biotic elements of nature, including all natural resources (such as soil, water, vegetation, species) and physical, biological, and chemical processes (Mace et al. 2015)

NA → NC

Natural capital stocks (NCS)

Natural capital consists of stocks of natural assets—the amount of a material in a given pool, form, or state in an ecosystem (Mace et al. 2012) that yield a flow of valuable ecosystem goods or services into the future (Costanza and Daly 1992)

NA → NC/NCS

Nature (N)

Natural world with an emphasis on the diversity of living organisms and their interactions among themselves and with their environment (Díaz et al. 2015)

NA = N=E

Ecosystem (E)

A dynamic complex of plant, animal, and microorganism communities and their non-living environment interacting as a functional unit (MA 2005)

E → BD

Biodiversity (BD)

The variability amongst the different levels (ecosystem, species, genes) of ecological organization including living organisms from all sources such as inter alia, terrestrial, marin,e and other aquatic ecosystems, and the ecological complexes of which they are part (CBD 2010; Mace et al. 2012)

E → BD → EP → ES

Ecosystem functions and processes (EP)

An interaction among organisms; ecological processes frequently regulate the dynamics of ecosystems and the structure and dynamics of biological communities (Mace et al. 2012)

E → BD → EP → ES

Nature contributions to people (NCP)

“All the contributions, both positive and negative, of living nature (diversity of organisms, ecosystems, and their associated ecological and evolutionary processes) to people’s quality of life” (Díaz et al. 2018)

NCP → ES

Ecosystem services (ES)

Benefits that flow from natural capital to society (Boyd and Banzhaf 2007; Guerry et al. 2015)

ES → B

Flows (F)

It is the realization of an ecosystem service to people (Mitchell et al. 2015)

E → B

Benefits (B)

The ways in which ecosystems improve human well-being through the provision of ecosystem services (Mitchell et al. 2015)

ES → B→V

Values (V)

“Values can refer to a principle associated with a given worldview or cultural context, a preference someone has for a particular state of the world, the importance of something for itself or for others, or simply a measure” (Pascual et al. 2017)

V → NCP → A

Nature-based solutions (NBS)

Concept to promote nature as a means for providing solutions to climate mitigation and adaptation, food security, social and economic development (Nesshöver et al. 2017)

N ← NBS

Ecological infrastructure (EI)

Landscape elements, ecosystems, ecosystem services, and the interconnections within and between them (Bristow et al. 2010)

N ← EI

Governance (G)

Describes how the process of management decisions are made or the development of how policies and strategies may be constructed (Díaz et al. 2015)

NA ← A←G

Human actions (A)

Principles, rules, and guidelines designed to influence and determine all major decisions

NA ← A←G

The links column indicates how the authors of this publication interpret the relationship between the concepts, indicating if they are interchangeable (=) or whether the concepts are interrelated but not the same (→)

Among the diverse terminology, the twin stock-flow sisters “natural capital” and “ecosystem services” have been the most popular ones during the last two decades. For example, between 1997 and 2016 there have been more than 13,500 peer-reviewed publications containing the term “ecosystem services” in the ISI Web of Science and 910 for “natural capital” (see Supplementary Material for detailed description of topic analysis tool). Ecosystem service research has predominately been focused on the topics related to social–ecological systems, local development, land/sea management, and global change scenarios, among other topics (see Fig. 1a). While there are similarities like the recurrent management aspect, the natural capital term has been mainly focused on wealth, assets and production landscapes (see Fig. 1b). The ecosystem services research timeline clearly shows the rapid increase in papers published since the emergence of the concept with the publication of Nature’s Services (Daily 1997) and the Millennium Ecosystem Assessment (MA 2005).
Fig. 1

Research available in the ISI Web of Knowledge identifying the number of publications within the eight most frequently researched topics on ecosystem services representing a sample of ~ 4000 papers (a) and natural capital representing a sample of ~ 350 papers (b), derived using a topic-modelling approach (https://code.google.com/archive/p/topic-modeling-tool/) (see supplementary material for detailed methods)

Natural capital

Natural capital is the “stock” from which useful ecosystem goods and services can flow to people, comparable conceptually to the stock of human or financial capital (Costanza et al. 1997; Akerman 2003; Gómez-Baggethun and De Groot 2010; Mace et al. 2015; Maseyk et al. 2017). Natural capital comprises all abiotic and biotic elements as well as ecosystems and within ecosystems biodiversity (Mace et al. 2015). There is plenty of scientific evidence linking biodiversity to ecosystem functioning and their effects on ecosystem services provision (Balvanera et al. 2006; Cardinale et al. 2012; Mace et al. 2012; Duncan et al. 2015). Ecosystem functioning depends on biodiversity and changes in its composition, abundance and function could change the structure of ecosystems affecting the flow of ecosystem services to society (Balvanera et al. 2006; Mace et al. 2012). The links between biodiversity and ecosystem service provision are still not sufficiently well known to predict the consequences of biodiversity changes (Harrison et al. 2014); however, there is evidence that a decline in biodiversity limits the provision of some ecosystem services in favour of others, which is relevant for management (Cardinale et al. 2012).

The characteristics of ecosystems and landscapes, such as species composition, land cover, climatic conditions, and landscape configuration modulate the nature and magnitude of ecosystem services that flow from the natural capital to societies. Societies are deeply embedded within ecosystems, depending on them for survival, while simultaneously creating both positive and negative impacts on them. While many of the benefits that flow from natural capital can be enhanced with technology and engineering, they cannot be replaced (Mace et al. 2015). For natural capital to contribute to human well-being and the provision of ecosystem services, there is need for some input of human capital in the form of management interventions.

Ecosystem services

Ecosystem services are the benefit flows from natural capital to society. The provision of ecosystem services is supported by the relationships between natural capital and the distribution of people in the landscape, as well as those management actions that modulate access to ecosystem services. Three types of ecosystem services can be distinguished (MA 2005). Provisioning services are directly taken out and consumed from ecosystems and can often be quantified and valued in economic terms such as clean water, raw materials like timber and fibres, and food production among others. Regulating services are those acting as regulators of ecosystem processes such as climate regulation, erosion control, flood regulation, and soil waste assimilation among others. Cultural services are the tangible and intangible benefits that result from human relations with the natural environment (Chan et al. 2012), for example: nature-based tourism and recreation, natural heritage, inspiration, scenic beauty, and many other relational values.

Nature’s contributions to people

The nature’s contributions to people (NCP) approach by IPBES (Pascual et al. 2017; Díaz et al. 2018) allows considering nature as an asset, but it also goes beyond regarding nature as a stock of resources. A generalizing perspective, similar in spirit to the ecosystem services approach, and a context-specific perspective that allows other than a stock-flow relationship with nature implies that the values of NCP embrace a diversity of worldviews across cultures and in so doing recognizes value pluralism (Pascual et al. 2017). For example, relational values, defined as the importance of nature in fostering desirable relationships between people and nature (Chan et al. 2016), are an important component of IPBES’ inclusive valuation of NCP (Pascual et al. 2017). Such inclusive valuation stems from the realization that the benefits and detriments to humans from natural assets are linked to well-being in diverse and manifold ways. For example, the benefits derived from NCP contribute to changes in living standards, nutritional status, mortality rates, equity and social conflicts, security in the face of extreme environmental conditions, or happiness. Values are differentially perceived either as costs (detriments from nature) or benefits (positive contributions) by individuals and societies (van Oudenhoven et al. 2012; Pascual et al. 2017).

Framing human well-being

Numerous frameworks linking human well-being with natural capital and the provision of ecosystem services have been developed during these last two decades and are rapidly evolving (MA 2005; Boyd and Banzhaf 2007; De Groot et al. 2010; Dominati et al. 2010; Haines-Young and Potschin 2010; Sukhdev 2010; Tallis et al. 2012; van Oudenhoven et al. 2012; Díaz et al. 2015; Maseyk et al. 2017).The focus of the frameworks has been on understanding the mechanisms behind the delivery of ecosystem services. The delivery of ecosystem services depends on the capacity of the ecosystem to provide a service (supply), on the anthropogenic and natural stressors influencing ecosystem service delivery (ecological pressures), the amount of the service required by society (demand), and the realization of a service experienced by people (flow) (Haines-Young and Potschin 2010; Tallis et al. 2012; Villamagna et al. 2013; Mitchell et al. 2015).

Recent frameworks address ecosystem service assessments from the supply to the demand side, covering three value domains of ecosystem services: biophysical, sociocultural, and monetary (Martín-López et al. 2014). For example, the supply side addresses the domain of biophysical value representing ecosystem service potential delivery, while the demand side refers to benefits to human well-being that have a sociocultural and/or monetary value (Martín-López et al. 2014).

The conceptual framework of the IPBES proposes three basic elements constituting a human–environmental system operating at different temporal and spatial scales: (a) nature (the natural environment with its diversity of living organisms—adding to this evolutionary processes and embracing other world views), (b) NCP, and (c) a good quality of life (Díaz et al. 2015, 2018). IPBES is launching (in 2018) an assessment on the inclusive valuation of NCP for decision-making which is targeted at science-policy initiatives highlighting a pluralistic approach to recognize the multiple values that different stakeholder groups hold on NCP (Pascual et al. 2017).

While the breadth of approaches to describe the provision of ecosystem services from natural capital has facilitated progress in sustainability research, the most critical questions posed by decision-makers in the realm of sustainability have not yet been answered (Villamagna et al. 2013; Bennett and Chaplin-Kramer 2016). For example, why has research that underlies environmental policy agendas (e.g. SDGs, Aichi targets) not always been effectively translated into practice? Where in a human–environmental system should we intervene to change its overall behaviour? A critical limitation to implementing a natural assets approach for decision-making is that existing frameworks lack explicit reference to human actions (Mace et al. 2015; Maseyk et al. 2017). To provide informed management interventions, it needs to be clarified how the provision of ecosystem services is underpinned by the complex interactions between ecological and human dimensions.

Natural assets: contributing to an inclusive framing on people’s relationships with nature

The way society interacts with and perceives nature shapes many of the paradigms underpinning human–environmental systems (e.g. ecosystem services, natural capital, NCP). The functioning of a system partly depends on the degree to which people’s dependency of nature is acknowledged, and the extent to which human–nature relationships are identified as essential to human well-being. In a recent publication, people’s relationships with nature and their impacts on conservation and management outcomes were identified as a pathway in which transformational change towards sustainability can be leveraged (Abson et al. 2017). Moreover, the implementation of the natural assets approach is very timely, as several initiatives (Convention on Biological Diversity Aichi Targets, CBD (2010); The Economics of Ecosystems and Biodiversity TEEB (Sukhdev 2010); and The Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services, IPBES (Perrings et al. 2011) are focusing attention on the recognition of human–nature relationships for human livelihoods and a good quality of life. The implementation challenge is to turn this recognition into policies and decisions that can guide the wise management of nature. The natural assets approach could play a key role by emphasizing the role of human actions aiming to connect knowledge systems and actors engaged in reshaping nature.

Human–nature relationships are also moral and ethical obligations that govern appropriate human actions towards the environment (Abson et al. 2017). Human actions influence the condition of natural assets influencing the provision of ecosystem services (Dominati et al. 2010; Palomo et al. 2016, Maseyk et al. 2017). This is illustrative of the need to embed both the social and ecological dimensions of the natural assets approach in policy making. Focusing on changes in condition (quality and quantity) of natural assets allows for an understanding of the impact of policy outcomes on natural assets. Policy processes provide pre-conditions, limitations, and motivations for human actions.

Natural assets have been previously defined as the components of natural capital that can be owned or managed, for example, ecological communities, minerals, freshwaters, land, the atmosphere, coasts, as well as the natural processes and functions that underpin their operation (Mace et al. 2015). Here, natural assets are defined as an umbrella term aiming to translate and bridge among different knowledge systems and different perspectives on people’s relationships with nature. The natural assets approach embraces the need for richer processes of knowledge exchange among different perspectives on peoples’ relationship with nature, ranging from the production of knowledge to the transformation of knowledge into actions (see Table 2).
Table 2

Definitions of the different knowledge process stages since its production to its transformation

Knowledge process stage

Definition

Knowledge production

New knowledge produced as an output of a process either in isolation or co-created through participation and engagement with knowledge users (Berkes 2009; Fazey et al. 2013)

Knowledge transfer

One-way process implying linear delivery and reception of knowledge (Fazey et al. 2013)

Co-production of knowledge

It is a collaboration process aiming to bring together a diversity of knowledge systems to address a defined problem and build an integrated understanding of that problem (Armitage et al. 2011)

Knowledge exchange

Multiple path knowledge process implying multiple delivery and reception of knowledge with mutual benefits and mutual learning (Fazey et al. 2013; Reed et al. 2014; Nguyen et al. 2017)

Knowledge mobilization

Multiple path knowledge process of linking scientists, decision-makers, and practitioners to improve the use of knowledge in practice (Edelstein 2016)

Sharing knowledge

Multiple path knowledge process implying multiple delivery and reception of knowledge with mutual benefits and mutual learning with greater recognition of the value of the knowledge of those sharing the knowledge (Fazey et al. 2013)

Knowledge translation

Implies communication of knowledge using a language modified for knowledge actors (Fazey et al. 2013)

Knowledge systems

Networks of agents, practices, and institutions that organize the production, transfer, and use of knowledge (Peterson et al. 2018)

Knowledge actors

Individual players involved in the exchange and mobilization of knowledge (knowledge producers, intermediaries and users) (Reed et al. 2014)

Knowledge-action

Outcome of the knowledge expressed in change of practices (Nguyen et al. 2017)

Knowledge transformation

Changing the knowledge towards a different state or condition through its internalization as social constructions. (Fazey et al. 2013; Abson et al. 2017)

The key is bridging strategically across multiple knowledge–action interfaces to ensure relevancy across a diversity of perspectives and values. Building natural assets knowledge for sustainability requires approaches that can cope with pluralism and link different knowledge systems (Clark et al. 2016; Peterson et al. 2018) while respecting the integrity of each knowledge system.

An agenda for natural assets research

This section discusses some key areas that Future Earth will need to tackle in its aim to bridge knowledge and action with regard to sustainability through a natural assets lens. These areas are associated with various challenges and current knowledge gaps identified in the sustainability science literature (e.g. Martinez-Harms et al. 2015; Bennett 2016; Rose et al. 2017, 2018; Pascual et al. 2014; Berbés-Blázquez et al. 2016).

Embrace richer collaborative decision processes

Despite increasing awareness of the need for evidence-based decision-making (Sutherland et al. 2004; Sutherland and Burgman 2015; Tengo et al. 2017), current research has failed to inform practice as intended (Knight et al. 2006; Cowling et al. 2008; Toomey et al. 2017). The gap between the knowledge generated by scientists and its uptake by policy and actions is a widely recognized challenge in applied ecology (Hulme 2014), conservation (Arlettaz et al. 2010; Toomey et al. 2017), and ecosystem services science (Cowling et al. 2008). Numerous researchers have highlighted the urgent need to narrow the gap between sustainability science and its application in decision-making (Knight et al. 2006; Cowling et al. 2008; Toomey et al. 2017). Despite some advances (Gelcich et al. 2010; Ruckelshaus et al. 2015), further progress is required as translating knowledge into practice change is fraught with difficulties, and several challenges remain that create barriers which prevent narrowing the gap further (Abson et al. 2017). A key issue is to identify spaces of agreement and be able to collaboratively engage with problems faced by policy-makers (Oldekop et al. 2016). Any bid to inform decision-making requires research to be inspirational and useful for end users, be responsive to stakeholder needs from the outset, and ensure collaboration with practitioners both before research initiation, during the research process, and after its completion (Cowling et al. 2008; Gelcich et al. 2010; Martinez-Harms et al. 2015). Advancement requires both scientists and practitioners to participate in a reciprocal and frequent exchange of information and knowledge (Hulme 2014). The field of knowledge exchange (Dunlop 2014; Jordan and Russel 2014) can help to embrace the complexity of translating different knowledge systems (Verburg et al. 2015) and seek to address the constraints that might limit effective knowledge transfer (Scarlett 2013).

Future Earth has adopted the core principle of knowledge co-production (see Table 2), and this will be particularly relevant in narrowing the gap between the implementation of the natural assets approach in decision-making (Reyers et al. 2015). The knowledge co-production approach is a collaborative process to respond to complex problems by bringing together different types of knowledge and creating an integrated understanding of those issues (Armitage et al. 2011). The principle of co-production is presented as the most innovative aspect of Future Earth and is the key attribute distinguishing the research programme from existing initiatives (van der Hel 2016). The knowledge co-production approach enables collaboration between stakeholders with different visions of the role of science to human well-being. For example, Reyers et al. (2015) applied and assessed a knowledge co-production approach with beneficiaries and managers of natural assets and found the approach to be successful in generating shared knowledge and knowledge–action outcomes for sustainability (see Table 2 for definitions). Participatory approaches may have the potential to better provide evidence for local interests and requirements for natural assets (Dunlop 2014); empower stakeholders to act locally (Armitage et al. 2011); enable sustainable transformations; and improve land governance through collective decisions on natural assets (Gelcich et al. 2010; Verburg et al. 2015).

A recent comprehensive review (Martinez-Harms et al. 2015) found that very few studies on ecosystem services management have adequately dealt with implementing evidence-based decisions. If the research supported by the Natural Assets KAN aims to better link knowledge to real-world actions and outcomes, it must consider transparent objectives, seek to evaluate the consequences of alternative management actions, and facilitate closer engagement between science and practice. Evidence-based knowledge should underpin management decisions for natural assets, and these decisions should account for the multiple values and preferences of stakeholders.

As natural assets management takes place in complex, uncertain, and dynamic social–ecological contexts (Folke et al. 2005), there is increasing attention towards better methods for linking knowledge to action (Schwartz et al. 2017). Decision support tools like structured decision-making (Bower et al. 2017), systematic mapping (Dicks et al. 2014), and the multiple evidence approach (Tengö et al. 2014, 2017) offer a set of responses to this challenge. The structured decision-making framework (Gregory et al. 2012) offers an avenue for making better evidence-based decisions, emphasizing the need for proper problem consideration and formulation and including steps for monitoring and evaluation (Bower et al. 2017) (see Fig. 2). Recently, Bower et al. (2017) recommended the implementation of clear and documented structured decision-making processes and archiving results in a global database to support environmental professionals in making future evidence-based decisions. This solution aims to improve knowledge–action outcomes (see Table 2), enhancing transparency and information sharing.
Fig. 2

Example of one of the decision support tools to connect knowledge into action. The structured decision-making process represents a flowchart outlining decisions on natural assets. The figure represents a semi-dynamic process starting with the problem formulation and defining a well-defined social–ecological context followed by setting transparent objectives that are those natural assets elements relevant for the study context and the performance measures to test those objectives. The following stages are the dynamic part of the process (setting management alternatives and scenarios, assessment of trade-offs between potential management alternatives, prioritization of alternatives and the implementation of polices), in which one could link any of these stages at any direction. The arrow connecting the trade-offs with the objectives means a decision-maker’s value with respect to multiple objectives. Adaptive management is presented as the overarching cyclical pattern, such that the final stage cycle back to the problem formulation stage based on the outcome of the previous cycle. Adapted from Gregory et al. (2012)

Systematic mapping is a rigorous technique used to synthesize the state of knowledge for a question or topic, giving a reliable overview of the breadth of science often needed for policy-based questions. On the other hand, the multiple evidence base approach aims to connect and bridge among different epistemologies, producing inclusive understandings that can be used as a starting point for collaborative problem formulation and knowledge co-production (Tengö et al. 2014, 2017). These approaches go beyond just focusing on the quantification of natural assets and instead look through the lens of the whole decision-making process, starting with understanding the human–environmental context with a focus on representing the concerns and aspirations of multiple knowledge systems (Runge et al. 2011; Gregory et al. 2012).

Focus the decision process on the development of scenarios that capture interactions between human and ecological dimensions of natural assets

Natural assets management deals with high uncertainty due to constant changes in socioeconomic trends, environmental conditions, and social values (Brunner et al. 2017). The scenarios are powerful mechanisms to explore possible outcomes for the future of natural assets due to multiple pathways of future human development, thus explicitly incorporating uncertainty (Rosa et al. 2017). Currently, however, the majority of scenario applications have been targeted to explore the effects of humans on ecosystems, ignoring the role of ecosystems underpinning development and human well-being (Cavender-Bares et al. 2015; Rosa et al. 2017). The next generation of scenarios supported by Future Earth should focus on targets for human development. This is particularly important for achieving the United Nations’ sustainable development goals (SDG), as human development targets within these goals are increasingly connected with targets for nature (Rosa et al. 2017). Future scenarios should focus on the potential synergies and trade-offs between ecosystem services, as well as maintaining or enhancing natural capital to generate future services (Cavender-Bares et al. 2015), and should also address social–ecological feedbacks that are critical for anticipating regime shifts (Bauch et al. 2016). The IPBES considers scenarios as a key tool to assess policy outcomes on nature and nature contributions to people (Díaz et al. 2015; Kok et al. 2016). However, to improve the policy relevance of future IPBES scenarios, the panel needs to engage with the great diversity of local contexts through transdisciplinary approaches, integrating multiple sectors, and linking local to global scale contexts (Kok et al. 2016). Future Earth is a critical contributor to helping IPBES achieve this target, e.g. through mobilizing stakeholder communities and through providing expertise on the co-production of transformative scenarios.

Reporting uncertainty and assessing the robustness of potential outcomes are also critical for ensuring the production of quality scenarios and for delivering credible conclusions (Hamel and Bryant 2017). To identify areas that require management interventions, it is critical to quantify and locate where these uncertainties occur. Nonetheless, there has been a poor uptake of uncertainty analyses within scenarios describing ecosystem service provision (Hamel and Bryant 2017). Most studies dealing with scenarios have several limitations in capturing all the different possible sources of uncertainty and modelling future outcomes that warrant consideration. Scenarios rarely consider emergent properties, complexities, interconnections, and synergistic interactions among the multiple drivers of change and ecosystem services (Liu et al. 2015).

Recently, Hamel and Bryant (2017) and Milner-Gulland and Shea (2017) summarized the commonly perceived challenges for addressing uncertainty analysis in ecosystem services assessments and ecological studies. These include: avoiding uncertainty because it is too difficult and takes time, focusing on trivial uncertainties, and allowing scarce and poorly characterized data to create too much uncertainty which in turn makes it difficult to assess and communicate uncertainty. Substantial knowledge of relevance to natural assets already exists in other fields (e.g. climatology, hydrology, integrated assessment) to address the uncertainty that can be directly transferred to natural assets and help inform more credible decisions (Henrichs et al. 2010; Milner-Gulland and Shea 2017).

Existing models could be improved with more finely-tuned parameters under future conditions, as natural assets are likely to vary across landscapes and seascapes according to biophysical and socioeconomic parameters. Models that couple social and ecological dynamics require the use of powerful decision support tools (e.g. Markov decision-making, supply chain analysis, multilevel modelling, agent-based modelling) to be able to predict the emergence of unexpected drivers of change (Liu et al. 2015). Agent-based models, for example, can be very useful to model human well-being in different scenarios and to model individual’s motivations that can impact the different possible pathways of global change drivers (Rosa et al. 2017).

When resources or modelling expertise is not available for managers, even the simplest conceptual model can be useful in communicating and enhancing understanding of the ramifications of uncertainty (Henrichs et al. 2010; Milner-Gulland and Shea 2017). Model simplicity is also desirable in decision-making for transparency, ease of validation, and description of the models (Caro et al. 2012). An important aspect in the development and operationalization of scenarios will be to translate them in a way that allows end users (policy makers, civil society organizations among others) to incorporate them into their decision-making. This can either be done by systematically co-designing scenarios with stakeholders, or by translating existing scenarios into a commonly understandable language.

Focus on social equity, power relations, and discourses

An unequal distribution of benefits derived from natural assets has important implications for human well-being and social equity (Berbés-Blázquez et al. 2016). Recently, Schröter et al. (2017) provided a framework to link ecosystem services to sustainable development through strategies to achieve sustained provision of ecosystem services. These include strategies for the equitable intra- and inter-generational distribution of ecosystem services. Although central to the United Nation’s SDGs, the assessment of how ecosystem services benefits and values are distributed has not frequently been addressed in the sustainability literature (Boerema et al. 2016). Social equity is about recognition of multiple value systems, effective participation in decision-making, and just/fair distribution of benefits and burdens (Pascual et al. 2014). Social equity in the distribution of benefits must be addressed in future efforts to respond and contribute to the achievement of the SDGs such as the promotion of peaceful and inclusive societies (SDG 16), ending poverty (SDG 1), and promoting protection and restoration of ecosystems (SDG 15), and to better target the development of capacity building towards achieving sustainability (SDG 17) (Griggs et al. 2013). Incorporating the assessment of fairness in the distribution of services and benefits among social groups is urgently needed, as the concept is increasingly adopted to address issues relating to poverty and vulnerability. Further, as inequity is often seen as a source of conflict, prioritizing equity and fairness in the access to ecosystem services and benefits can facilitate acceptance and subsequent higher likelihood policy uptake (Halpern et al. 2013). Addressing these dimensions will steer science and policy towards targeting ecosystem services management for achieving sustainability and social justice.

Imbalances of power are a relevant variable determining access, use, and distribution of natural assets. This is challenging, as these imbalances result from interactions between multiple factors such as political, ecological, and socioeconomic (Hicks and Cinner 2014; Pascual et al. 2014). For example, many South American landscapes are intensively managed for intensive agricultural use—such as soybean (in Brazil and Argentina), banana (in Ecuador), and avocado (in Mexico)—that are often surrounded by poor and marginalized communities. These agricultural goods are often then traded in the market benefiting stakeholders who are often disconnected from the local human-environmental context of these places (Berbés-Blázquez et al. 2016). Future natural assets research should focus on addressing power imbalances across actors to deliver socially fairer outcomes and more equitable access to natural assets (Pascual et al. 2017).

Understanding how different actors exercise power through their discourses is one of the critical mechanisms for the knowledge of natural assets to be tailored to local realities. According to Dryzek (1997), a discourse is:

‘‘A shared way of apprehending the world. Embedded in language, it enables those who subscribe to it to interpret bits of information and put them together into coherent stories or accounts’’.

Getting the discourse right is critical for achieving natural assets sustainability, as this can provide a narrative through which individuals and communities can validate and initiate actions, addressing issues of agency and empowerment which are important for framing relations with natural assets (Rose 1990; Fortmann et al. 1995; McHenry 1996; Gelcich et al. 2005). Stakeholders are considered to be actively involved in the production of discourses, which are then used to give meaning to social–ecological phenomena (Fortmann 1990; Hajer 1995). Local discourses are important as a way of legitimizing worldviews and positioning actors in relation to natural assets (Rose 1990; Fortmann et al. 1995; Gelcich et al. 2005). In doing so they allow incentives and dominance of particular sets of values to be addressed when extending the natural assets concept to real-world applications.

Conclusion

There is a momentum for the implementation of the natural assets approach, as several international initiatives are focusing attention on the recognition of human–nature relationships for human well-being. The challenge is to turn this recognition into policies and decisions that can guide the sustainable management of natural assets. The natural assets approach could play a key role by emphasizing the role of human actions and aiming to connect epistemologies and knowledge actors engaged in management and conservation. However, this potential will remain unrealized in the absence of an implementation pathway that addresses the inherent challenges of turning knowledge into actions. Our clarification of the natural assets framing and its underlying concepts coupled with the need to translate and bridge among different knowledge systems and different perspectives on people’s relationships with nature provides such a pathway. The solutions are outlined as follows: embracing richer collaborative decision processes towards sustainability to improve environmental decision-making; focusing on the development of scenarios capturing social and ecological interactions and focusing on social equity, power relationships, and discourses to guide natural assets decision-making for more socially fair outcomes. These insights can be used to inform and prioritize future research facilitated under the Natural Assets KAN.

Notes

Acknowledgements

We would like to thank Georgina Mace for her insightful comments and suggestions that largely improved the paper. We would like to thank Diego Carrillo Sandrock for his help improving the figures. We thank the 18 researchers from across the sciences gathered in a scoping “natural assets” workshop in September 2017 at the University of Bern, Switzerland, organized by bioDISCOVERY, GMBA, GLP, and PAGES under the auspices of Future Earth, for their great discussions that informed this paper. We thank the University of Bern for hosting the meeting, and Future Earth and SCNAT for providing financial support. MMH and SG are supported by the Centre of Applied Ecology and Sustainability CAPES FB 0002-2014. MMH is supported by Fondo Nacional de Desarrollo Científico y Tecnológico FONDECYT 318011.

Supplementary material

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References

  1. Abson DJ et al (2017) Leverage points for sustainability transformation. Ambio 46:30–39CrossRefGoogle Scholar
  2. Akerman M (2003) What does’ natural capital’do? The role of metaphor in economic understanding of the environment. Environ Values 12:431–448CrossRefGoogle Scholar
  3. Arlettaz R, Schaub M, Fournier J, Reichlin TS, Sierro A, Watson JEM, Braunisch V (2010) From publications to public actions: when conservation biologists bridge the gap between research and implementation. Bioscience 60:835–842CrossRefGoogle Scholar
  4. Armitage D, Berkes F, Dale A, Kocho-Schellenberg E, Patton E (2011) Co-management and the co-production of knowledge: learning to adapt in Canada’s Arctic. Glob Environ Change 21:995–1004CrossRefGoogle Scholar
  5. Balvanera P, Pfisterer AB, Buchmann N, He JS, Nakashizuka T, Raffaelli D, Schmid B (2006) Quantifying the evidence for biodiversity effects on ecosystem functioning and services. Ecol Lett 9:1146–1156CrossRefGoogle Scholar
  6. Bateman IJ et al (2013) Bringing ecosystem services into economic decision-making: land use in the United Kingdom. Science 341:45–50CrossRefGoogle Scholar
  7. Bauch CT, Sigdel R, Pharaon J, Anand M (2016) Early warning signals of regime shifts in coupled human-environment systems. Proc Natl Acad Sci 113:14560–14567CrossRefGoogle Scholar
  8. Bennett EM (2016) Research frontiers in ecosystem service science. Ecosystems 20(1):31–37CrossRefGoogle Scholar
  9. Bennett E, Chaplin-Kramer R (2016) Science for the sustainable use of ecosystem services. F1000Research 5:2622Google Scholar
  10. Berbés-Blázquez M, González JA, Pascual U (2016) Towards an ecosystem services approach that addresses social power relations. Curr Opin Environ Sustain 19:134–143CrossRefGoogle Scholar
  11. Berkes F (2009) Evolution of co-management: role of knowledge generation, bridging organizations and social learning. J Environ Manag 90:1692–1702CrossRefGoogle Scholar
  12. Boerema A, Rebelo AJ, Bodi MB, Esler KJ, Meire P (2016) Are ecosystem services adequately quantified? J Appl Ecol 54(2):358–370CrossRefGoogle Scholar
  13. Bower SD, Brownscombe JW, Birnie-Gauvin K, Ford MI, Moraga AD, Pusiak RJP, Turenne ED, Zolderdo AJ, Cooke SJ, Bennett JR (2017) Making tough choices: picking the appropriate conservation decision-making tool. Conserv Lett 11(2):1–7Google Scholar
  14. Boyd J, Banzhaf S (2007) What are ecosystem services? The need for standardized environmental accounting units. Ecol Econ 63:616–626CrossRefGoogle Scholar
  15. Bristow KL, Marchant SM, Deurer M, Clothier BE (2010) Enhancing the ecological infrastructure of soils. In: 19th world congress of soil science, soil solutions for a changing world, 1–6 August 2010, BrisbaneGoogle Scholar
  16. Brunner SH, Huber R, Grêt-Regamey A (2017) Mapping uncertainties in the future provision of ecosystem services in a mountain region in Switzerland. Reg Environ Change 17(8):2309–2321CrossRefGoogle Scholar
  17. Cardinale BJ, Duffy JE, Gonzalez A, Hooper DU, Perrings C, Venail P, Narwani A, Mace GM, Tilman D, Wardle DA (2012) Biodiversity loss and its impact on humanity. Nature 486:59–67CrossRefGoogle Scholar
  18. Caro JJ, Briggs AH, Siebert U, Kuntz KM (2012) Modeling good research practices—overview: a report of the ISPOR-SMDM modeling good research practices task force-1. Value Health 15:796–803CrossRefGoogle Scholar
  19. Cavender-Bares J, Polasky S, King E, Balvanera P (2015) A sustainability framework for assessing trade-offs in ecosystem services. Ecol Soc 20(1):17CrossRefGoogle Scholar
  20. CBD (2010) Decision X/2, The strategic plan for biodiversity 2011–2020 and the Aichi biodiversity targets, Nagoya, 18–20 October 2010Google Scholar
  21. Chan KMA, Satterfield T, Goldstein J (2012) Rethinking ecosystem services to better address and navigate cultural values. Ecol Econ 74:8–18CrossRefGoogle Scholar
  22. Chan KMA et al (2016) Opinion: why protect nature? Rethinking values and the environment. Proc Natl Acad Sci 113:1462–1465CrossRefGoogle Scholar
  23. Clark WC, van Kerkhoff L, Lebel L, Gallopin GC (2016) Crafting usable knowledge for sustainable development. Proc Natl Acad Sci 113:4570–4578CrossRefGoogle Scholar
  24. Costanza R, Daly HE (1992) Natural capital and sustainable development. Conserv Biol 6:37–46CrossRefGoogle Scholar
  25. Costanza R et al (1997) The value of the world’s ecosystem services and natural capital. Nature 387:253–260CrossRefGoogle Scholar
  26. Costanza R, de Groot R, Braat L, Kubiszewski I, Fioramonti L, Sutton P, Farber S, Grasso M (2017) Twenty years of ecosystem services: how far have we come and how far do we still need to go? Ecosyst Serv 28:1–16CrossRefGoogle Scholar
  27. Cowling RM, Egoh B, Knight AT, O’Farrell PJ, Reyers B, Rouget M, Roux DJ, Welz A, Wilhelm-Rechman A (2008) An operational model for mainstreaming ecosystem services for implementation. Proc Natl Acad Sci 105:9483–9488CrossRefGoogle Scholar
  28. Daily GC (1997) Nature’s services: societal dependence on natural ecosystems. Island Press, Washington DCGoogle Scholar
  29. Dasgupta P (2010) Nature’s role in sustaining economic development. Philos Trans R Soc B Biol Sci 365:5–11CrossRefGoogle Scholar
  30. De Groot RS, Alkemade R, Braat L, Hein L, Willemen L (2010) Challenges in integrating the concept of ecosystem services and values in landscape planning, management and decision making. Ecol Complex 7:260–272CrossRefGoogle Scholar
  31. Díaz S, Fargione J, Chapin FS, Tilman D (2006) Biodiversity loss threatens human well-being. PLoS Biol 4:e277CrossRefGoogle Scholar
  32. Díaz S, Demissew S, Joly C, Lonsdale WM, Larigauderie A (2015) A Rosetta stone for nature’s benefits to people. PLoS Biol 13:e1002040CrossRefGoogle Scholar
  33. Díaz S et al (2018) Assessing nature’s contributions to people. Science 359:270–272CrossRefGoogle Scholar
  34. Dicks LV, Walsh JC, Sutherland WJ (2014) Organising evidence for environmental management decisions: a ‘4S’ hierarchy. Trends Ecol Evol 29:607–613CrossRefGoogle Scholar
  35. Dominati E, Patterson M, Mackay A (2010) A framework for classifying and quantifying the natural capital and ecosystem services of soils. Ecol Econ 69:1858–1868CrossRefGoogle Scholar
  36. Dryzek JS (1997) The politics of the earth: environmental discourses. Oxford University Press, OxfordGoogle Scholar
  37. Duncan C, Thompson JR, Pettorelli N (2015) The quest for a mechanistic understanding of biodiversity–ecosystem services relationships. Proc R Soc B 282:20151348CrossRefGoogle Scholar
  38. Dunlop CA (2014) The possible experts: how epistemic communities negotiate barriers to knowledge use in ecosystems services policy. Environ Plan C Gov Policy 32:208–228CrossRefGoogle Scholar
  39. Edelstein H (2016) Collaborative research partnerships for knowledge mobilisation. Evid Policy 12:199–216CrossRefGoogle Scholar
  40. Faith DP (2018) Avoiding paradigm drifts in IPBES: reconciling “nature’s contributions to people”, biodiversity, and ecosystem services. Ecol Soc 23(2):40CrossRefGoogle Scholar
  41. Fazey I, Evely AC, Reed MS, Stringer LC, Kruijsen J, White PC, Newsham A, Jin L, Cortazzi M, Phillipson J (2013) Knowledge exchange: a review and research agenda for environmental management. Environ Conserv 40:19–36CrossRefGoogle Scholar
  42. Folke C, Hahn T, Olsson P, Norberg J (2005) Adaptive governance of social–ecological systems. Annu Rev Environ Resour 30:441–473CrossRefGoogle Scholar
  43. Fortmann L (1990) Locality and custom: Non-aboriginal claims to customary usufructuary rights as a source of rural protest. J Rural Stud 6(2):95–208CrossRefGoogle Scholar
  44. Fortmann SP, Flora JA, Winkleby MA, Schooler C, Taylor CB, Farquhar JW (1995) Community intervention trials: reflections on the Stanford Five-City Project experience. Am J Epidemiol 142:576–586CrossRefGoogle Scholar
  45. Gelcich S, Edwards-Jones G, Kaiser MJ, Watson E (2005) Using discourses for policy evaluation: the case of marine common property rights in Chile. Soc Nat Resour 18:377–391CrossRefGoogle Scholar
  46. Gelcich S et al (2010) Navigating transformations in governance of Chilean marine coastal resources. Proc Natl Acad Sci 107:16794–16799CrossRefGoogle Scholar
  47. Gómez-Baggethun E, De Groot R (2010) Natural capital and ecosystem services: the ecological foundation of human society. Ecosyst Serv 30:105–121CrossRefGoogle Scholar
  48. Gregory R, Failing L, Harstone M, Long G, McDaniels T, Ohlson D (2012) Structured decision making: a practical guide to environmental management choices. Wiley, New YorkCrossRefGoogle Scholar
  49. Griggs D, Stafford-Smith M, Gaffney O, Rockström J, Öhman MC, Shyamsundar P, Steffen W, Glaser G, Kanie N, Noble I (2013) Policy: sustainable development goals for people and planet. Nature 495:305–307CrossRefGoogle Scholar
  50. Guerry AD et al (2015) Natural capital and ecosystem services informing decisions: from promise to practice. Proc Natl Acad Sci 112:7348–7355CrossRefGoogle Scholar
  51. Haines-Young R, Potschin M (2010) The links between biodiversity, ecosystem services and human well-being. In: Raffaelli D, Frid C (eds) Ecosystem ecology: a new synthesis. BES ecological reviews series. Cambridge University Press, CambridgeGoogle Scholar
  52. Hajer MA (1995) The politics of environmental discourse: ecological modernization and the policy process. Oxford University Press, Oxford, UK, p 332Google Scholar
  53. Halpern BS et al. (2013) Achieving the triple bottom line in the face of inherent trade-offs among social equity, economic return, and conservation. Proc Natl Acad Sci 110(15):6229–6234CrossRefGoogle Scholar
  54. Hamel P, Bryant BP (2017) Uncertainty assessment in ecosystem services analyses: seven challenges and practical responses. Ecosyst Serv 24:1–15CrossRefGoogle Scholar
  55. Harrison PA et al (2014) Linkages between biodiversity attributes and ecosystem services: a systematic review. Ecosyst Serv 9:191–203CrossRefGoogle Scholar
  56. Henrichs T, Zurek M, Eickhout B, Kok K, Raudsepp-Hearne C, Ribeiro T, van Vuuren D, Volkery A (2010) Scenario development and analysis for forward-looking ecosystem assessments. Ecosystems and human well-being: A manual for assessment practitioners 151-219Google Scholar
  57. Hicks CC, Cinner JE (2014) Social, institutional, and knowledge mechanisms mediate diverse ecosystem service benefits from coral reefs. Proc Natl Acad Sci 111:17791–17796CrossRefGoogle Scholar
  58. Hooper DU et al (2005) Effects of biodiversity on ecosystem functioning: a consensus of current knowledge. Ecol Monogr 75:3–35CrossRefGoogle Scholar
  59. Hulme PE (2014) EDITORIAL: bridging the knowing–doing gap: know-who, know-what, know-why, know-how and know-when. J Appl Ecol 51:1131–1136CrossRefGoogle Scholar
  60. IPBES (2018) Summary for policymakers of the thematic assessment report on land degradation and restoration of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. In: Scholes R, Montanarella L, Brainich A, Barger N et al (eds) IPBES secretariat. Bonn, GermanyGoogle Scholar
  61. Jordan A, Russel D (2014) Embedding the concept of ecosystem services? The utilisation of ecological knowledge in different policy venues. Environ Plan C Gov Policy 32:192–207CrossRefGoogle Scholar
  62. Kareiva P (2011) Natural capital: theory and practice of mapping ecosystem services. Oxford University Press, OxfordCrossRefGoogle Scholar
  63. Knight AT, Cowling RM, Campbell BM (2006) An operational model for implementing conservation action. Conserv Biol 20:408–419CrossRefGoogle Scholar
  64. Kok MTJ, Kok K, Peterson GD, Hill R, Agard J, Carpenter SR (2016) Biodiversity and ecosystem services require IPBES to take novel approach to scenarios. Sustain Sci 12(1):177–181CrossRefGoogle Scholar
  65. Laurans Y, Rankovic A, Billé R, Pirard R, Mermet L (2013) Use of ecosystem services economic valuation for decision making: questioning a literature blindspot. J Environ Manage 119:208–219CrossRefGoogle Scholar
  66. Liu J et al (2015) Systems integration for global sustainability. Science 347(6225):963–973Google Scholar
  67. MA (2005) Ecosystems and human well-being: synthesis. Island Press, Washington DCGoogle Scholar
  68. Mace GM, Norris K, Fitter AH (2012) Biodiversity and ecosystem services: a multilayered relationship. Trends Ecol Evol 27:19–26CrossRefGoogle Scholar
  69. Mace GM, Hails RS, Cryle P, Harlow J, Clarke SJ (2015) REVIEW: towards a risk register for natural capital. J Appl Ecol 52:641–653CrossRefGoogle Scholar
  70. Maes J et al (2012) Mapping ecosystem services for policy support and decision making in the European Union. Ecosyst Serv 1:31–39CrossRefGoogle Scholar
  71. Maes J, Burkhard B, Geneletti D (2018) Ecosystem services are inclusive and deliver multiple values. A comment on the concept of nature’s contributions to people. One Ecosyst 3:e24720Google Scholar
  72. Martinez-Harms MJ, Bryan BA, Balvanera P, Law EA, Rhodes JR, Possingham HP, Wilson KA (2015) Making decisions for managing ecosystem services. Biol Conserv 184:229–238CrossRefGoogle Scholar
  73. Martín-López B, Gómez-Baggethun E, García-Llorente M, Montes C (2014) Trade-offs across value-domains in ecosystem services assessment. Ecol Indic 37:220–228CrossRefGoogle Scholar
  74. Maseyk FJ, Mackay AD, Possingham HP, Dominati EJ, Buckley YM (2017) Managing natural capital stocks for the provision of ecosystem services. Conserv Lett 10(2):211–220CrossRefGoogle Scholar
  75. McHenry H (1996) Farming and environmental discourses: a study of the depiction of environmental issues in a German farming newspaper. J Rural Stud 12:375–386CrossRefGoogle Scholar
  76. Milner-Gulland EJ, Shea K (2017) Embracing uncertainty in applied ecology. J Appl Ecol 54(6):2063–2068CrossRefGoogle Scholar
  77. Mitchell MGE, Suarez-Castro AF, Martinez-Harms M, Maron M, McAlpine C, Gaston KJ, Johansen K, Rhodes JR (2015) Reframing landscape fragmentation’s effects on ecosystem services. Trends Ecol Evol 30:190–198CrossRefGoogle Scholar
  78. Nesshöver C et al (2017) The science, policy and practice of nature-based solutions: an interdisciplinary perspective. Sci Total Environ 579:1215–1227CrossRefGoogle Scholar
  79. Nguyen V, Young N, Cooke S (2017) A roadmap for knowledge exchange and mobilization research in conservation and natural resource management. Conserv Biol 31:789–798CrossRefGoogle Scholar
  80. Oldekop JA et al (2016) 100 key research questions for the post-2015 development agenda. Dev Policy Rev 34:55–82CrossRefGoogle Scholar
  81. Palomo I, Felipe-Lucia MR, Bennett EM, Martín-López B, Pascual U (2016) Disentangling the pathways and effects of ecosystem service co-production. Adv Ecol Res 54:245–283CrossRefGoogle Scholar
  82. Pascual U, Phelps J, Garmendia E, Brown K, Corbera E, Martin A, Gomez-Baggethun E, Muradian R (2014) Social equity matters in payments for ecosystem services. Bioscience 64:1027–1036CrossRefGoogle Scholar
  83. Pascual U et al (2017) Valuing nature’s contributions to people: the IPBES approach. Curr Opin Environ Sustain 26–27:7–16CrossRefGoogle Scholar
  84. Perrings C, Duraiappah A, Larigauderie A, Mooney H (2011) The biodiversity and ecosystem services science-policy interface. Science 331:1139–1140CrossRefGoogle Scholar
  85. Peterson GD, Harmá, ková ZV, Meacham M, Queiroz C, Jiménez-Aceituno A, Kuiper JJ, Malmborg K, Sitas N, Bennett EM, (2018) Welcoming different perspectives in IPBES: “Nature’s contributions to people” and “Ecosystem services”. Ecol Soc 23(1):39CrossRefGoogle Scholar
  86. Rasmussen L, Coolsaet B, Martin A, Mertz O, Pascual U, Corbera E, Dawson N, Fisher J, Franks P, Ryan C (2018) Social–ecological outcomes of agricultural intensification. Nat Sustain 1:275–282CrossRefGoogle Scholar
  87. Reed MS, Stringer LC, Fazey I, Evely AC, Kruijsen JHJ (2014) Five principles for the practice of knowledge exchange in environmental management. J Environ Manag 146:337–345CrossRefGoogle Scholar
  88. Reyers B, Nel JL, O’Farrell PJ, Sitas N, Nel DC (2015) Navigating complexity through knowledge coproduction: mainstreaming ecosystem services into disaster risk reduction. Proc Natl Acad Sci 112:7362–7368CrossRefGoogle Scholar
  89. Rockström J, Steffen W, Noone K, Persson Å, Chapin FS, Lambin EF, Lenton TM, Scheffer M, Folke C, Schellnhuber HJ (2009) A safe operating space for humanity. Nature 461:472–475CrossRefGoogle Scholar
  90. Rosa IM, Pereira HM, Ferrier S, Alkemade R, Acosta LA, Akcakaya HR, den Belder E, Fazel AM, Fujimori S, Harfoot M (2017) Multiscale scenarios for nature futures. Nat Ecol Evol 1:1416CrossRefGoogle Scholar
  91. Rose CM (1990) Property as storytelling: perspectives from game theory, narrative theory, feminist theory. Yale JL & Human 2:37Google Scholar
  92. Rose D, Sutherland W, Amano T, González-Varo J, Robertson R, Simmons B, et al. (2018) The major barriers to evidence-informed conservation policy and possible solutions. Conserv Lett 0:e12564Google Scholar
  93. Ruckelshaus M et al. (2015) Notes from the field: lessons learned from using ecosystem service approaches to inform real-world decisions. Ecol Econ 115:11–21CrossRefGoogle Scholar
  94. Runge MC, Converse SJ, Lyons JE (2011) Which uncertainty? Using expert elicitation and expected value of information to design an adaptive program. Biol Conserv 144:1214–1223CrossRefGoogle Scholar
  95. Scarlett L (2013) Collaborative adaptive management: challenges and opportunities. Ecol Soc 18(3):26CrossRefGoogle Scholar
  96. Schröter M, Stumpf KH, Loos J, van Oudenhoven APE, Böhnke-Henrichs A, Abson DJ (2017) Refocusing ecosystem services towards sustainability. Ecosyst Serv 25:35–43CrossRefGoogle Scholar
  97. Schwartz MW, Cook CN, Pressey RL, Pullin AS, Runge MC, Salafsky N, Sutherland WJ, Williamson MA (2017) Decision support frameworks and tools for conservation. Conserv Lett 11 (2):1–12Google Scholar
  98. Sukhdev P (2010) The economics of ecosystems and biodiversity: mainstreaming the economics of nature: a synthesis of the approach, conclusions and recommendations of TEEB. UNEP, Geneva SwitzerlandGoogle Scholar
  99. Sutherland WJ, Burgman MA (2015) Use experts wisely. Nature 526:317–318CrossRefGoogle Scholar
  100. Sutherland WJ, Pullin AS, Dolman PM, Knight TM (2004) The need for evidence-based conservation. Trends Ecol Evol 19:305–308CrossRefGoogle Scholar
  101. Tallis H et al (2012) A global system for monitoring ecosystem service change. Bioscience 62:977–986CrossRefGoogle Scholar
  102. Tengo M, Hill R, Malmer P, Raymond CM, Spierenburg M, Danielsen F, Elmqvist T, Folke C (2017) Weaving knowledge systems in IPBES, CBD and beyond-lessons learned for sustainability. Curr Opin Environ Sustain 26–27:17–25CrossRefGoogle Scholar
  103. Tengö M, Brondizio ES, Elmqvist T, Malmer P, Spierenburg M (2014) Connecting diverse knowledge systems for enhanced ecosystem governance: the multiple evidence base approach. Ambio 43:579–591CrossRefGoogle Scholar
  104. Toomey AH, Knight AT, Barlow J (2017) Navigating the space between research and implementation in conservation. Conserv Lett 10(5): 619–625CrossRefGoogle Scholar
  105. van der Hel S (2016) New science for global sustainability? The institutionalisation of knowledge co-production in Future Earth. Environ Sci Policy 61:165–175CrossRefGoogle Scholar
  106. van Oudenhoven APE, Petz K, Alkemade R, Hein L, de Groot RS (2012) Framework for systematic indicator selection to assess effects of land management on ecosystem services. Ecol Indic 21:110–122CrossRefGoogle Scholar
  107. Verburg PH et al (2015) Land system science and sustainable development of the earth system: a global land project perspective. Anthropocene 12:29–41CrossRefGoogle Scholar
  108. Villamagna AM, Angermeier PL, Bennett EM (2013) Capacity, pressure, demand, and flow: a conceptual framework for analyzing ecosystem service provision and delivery. Ecol Complex 15:114–121CrossRefGoogle Scholar
  109. Worm B et al (2006) Impacts of biodiversity loss on ocean ecosystem services. Science 314:787–790CrossRefGoogle Scholar

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© The Author(s) 2018

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  • Maria Jose Martinez-Harms
    • 1
    • 2
  • Stefan Gelcich
    • 1
  • Rainer M. Krug
    • 3
  • Fleur J. F. Maseyk
    • 2
    • 4
  • Hannah Moersberger
    • 5
  • Archi Rastogi
    • 6
  • Geoffrey Wambugu
    • 7
  • Cornelia B. Krug
    • 8
    • 12
  • Eva M. Spehn
    • 9
  • Unai Pascual
    • 10
    • 11
    • 13
  1. 1.Center for Applied Ecology and Sustainability (CAPES), Center for the Study of Multiple-Drivers on Marine Socio-Ecological SystemsPontificia Universidad Catolica de ChileSantiagoChile
  2. 2.Australian Research Council Centre of Excellence for Environmental Decisions, School of Biological SciencesThe University of QueenslandSaint LuciaAustralia
  3. 3.Department of Evolutionary Biology and Environmental StudiesUniversity of ZurichZurichSwitzerland
  4. 4.The Catalyst GroupPalmerston NorthNew Zealand
  5. 5.Future Earth Paris HubCentre National de la Recherche Scientifique (CNRS)75005 ParisFrance
  6. 6.Universalia Management GroupWestmountCanada
  7. 7.School of Natural Resources and Environmental StudiesKaratina UniversityKaratinaKenya
  8. 8.URPP Global Change and BiodiversityUniversity of ZurichZurichSwitzerland
  9. 9.Global Mountain Biodiversity Assessment, Institute of Plant SciencesUniversity of BernBernSwitzerland
  10. 10.Basque Centre for Climate Change, University of the Basque Country (UPV-EHU)BilbaoSpain
  11. 11.Ikerbasque, Basque Foundation for ScienceBilbaoSpain
  12. 12.bioDISCOVERY, Department of GeographyUniversity of ZurichZurichSwitzerland
  13. 13.Centre for Development and EnvironmentUniversity of BernBernSwitzerland

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