When, Where, and How Nature Matters for Ecosystem Services: Challenges for the Next Generation of Ecosystem Service Models

Many decision-makers are looking to science to clarify how nature supports human well-being. Scientists\u27 responses have typically focused on empirical models of the provision of ecosystem services (ES) and resulting decision-support tools. Although such tools have captured some of the complexities of ES, they can be difficult to adapt to new situations. Globally useful tools that predict the provision of multiple ES under different decision scenarios have proven challenging to develop. Questions from decision-makers and limitations of existing decision-support tools indicate three crucial research frontiers for incorporating cutting-edge ES science into decision-support tools: (1) understanding the complex dynamics of ES in space and time, (2) linking ES provision to human well-being, and (3) determining the potential for technology to substitute for or enhance ES. We explore these frontiers in-depth, explaining why each is important and how existing knowledge at their cutting edges can be incorporated to improve ES decision-making tools

Reimagining the potential of Earth observations for ecosystem service assessments

The benefits nature provides to people, called ecosystem services, are increasingly recognized and accounted for in assessments of infrastructure development, agricultural management, conservation prioritization, and sustainable sourcing. These assessments are often limited by data, however, a gap with tremendous potential to be filled through Earth observations (EO), which produce a variety of data across spatial and temporal extents and resolutions. Despite widespread recognition of this potential, in practice few ecosystem service studies use EO. Here, we identify challenges and opportunities to using EO in ecosystem service modeling and assessment. Some challenges are technical, related to data awareness, processing, and access. These challenges require systematic investment in model platforms and data management. Other challenges are more conceptual but still systemic; they are byproducts of the structure of existing ecosystem service models and addressing them requires scientific investment in solutions and tools applicable to a wide range of models and approaches. We also highlight new ways in which EO can be leveraged for ecosystem service assessments, identifying promising new areas of research. More widespread use of EO for ecosystem service assessment will only be achieved if all of these types of challenges are addressed. This will require non-traditional funding and partnering opportunities from private and public agencies to promote data exploration, sharing, and archiving. Investing in this integration will be reflected in better and more accurate ecosystem service assessments worldwide

Substitutability of natural and human capitals: lessons from a simple exploratory model

ABSTRACTMost ecosystem services (ES) are co-produced, to varying degrees, by interactions between people and ecosystems. Although ES research has tended to emphasize the role of ecosystems, or natural capital, in ES provision, the need for a deeper understanding of the role of human-derived capitals, like technology, labour, and management, is increasingly being recognized. Understanding the capacity for, and limitations of, human-derived capitals to enhance or substitute for natural capital is important for environmental decision-making, especially for decisions about when to promote conservation of natural capital to provide ecosystem services and when to employ technological alternatives. From the perspective of long-term sustainable ecosystem management, such decisions are further complicated by dynamics and interactions between different types of capital. We created a simple simulation model to compare how different assumptions around the temporal dynamics and interactions between natural and human-derived capitals affect long-term outcomes of different management choices on ES provision. We found that the extent to which different capitals are substitutable in the long-term depends on how individual capitals change over time and how different capitals interact with each other, and that replicating the near-term function of natural capital does not necessarily mean human-derived capitals are a viable long-term substitute. With an understanding of the dynamics and interactions of natural and human-derived capitals, it is possible to determine general long-term ES management strategies that are more likely to produce the desired benefits

Inequalities in the adaptive cycle: reorganizing after disasters in an unequal world

Natural hazards can trigger disasters that lead to the collapse and reorganization of social-ecological systems. This reorganization can involve systems transitioning to more positive trajectories. The Panarchy framework, which conceptualizes social-ecological systems as dynamic interrelated adaptive cycles, is a common conceptual framework for understanding system reorganization. However, it is unclear how inequalities, social mechanisms known to influence disaster recovery outcomes, shape a system's adaptive cycle post-disaster. Understanding the roles of inequalities can help develop social-ecological models to identify processes that build resilience into disaster recovery. We applied the Panarchy framework to inform propositions describing how inequalities can influence the reorganization of social-ecological systems after disasters triggered by natural hazards. We qualitatively analyzed a selection of case studies that discussed inequalities pre- and post-disasters and related these to adaptive-cycle system characteristics (i.e., potential, connectedness, and resilience). We identified three propositions: 1) The ability of groups to reorganize after a disaster varies across the inequality spectrum; 2) The reorganizing abilities of groups across the inequality spectrum impact one another; and 3) The presence of inequalities affect connectedness within the system. Incorporating these propositions into social-ecological system modeling can improve our understanding of how inequalities impact system reorganization. This information can support disaster recovery plans that strengthen a system's ability to enter a more positive trajectory post-disaster

When, where, and how nature matters for ecosystem services: challenges for the next generation of ecosystem service models

Many decision-makers are looking to science to clarify how nature supports human well-being. Scientists’ responses have typically focused on empirical models of the provision of ecosystem services (ES) and resulting decision-support tools. Although such tools have captured some of the complexities of ES, they can be difficult to adapt to new situations. Globally useful tools that predict the provision of multiple ES under different decision scenarios have proven challenging to develop. Questions from decision-makers and limitations of existing decision-support tools indicate three crucial research frontiers for incorporating cutting-edge ES science into decision-support tools: (1) understanding the complex dynamics of ES in space and time, (2) linking ES provision to human well-being, and (3) determining the potential for technology to substitute for or enhance ES. We explore these frontiers in-depth, explaining why each is important and how existing knowledge at their cutting edges can be incorporated to improve ES decision-making tools