Anticipating and Managing Future Trade-offs and Complementarities between Ecosystem Services

This paper shows how, with the aid of computer models developed in close collaboration with decision makers and other stakeholders, it is possible to quantify and map how policy decisions are likely to affect multiple ecosystem services in future. In this way, potential trade-offs and complementarities between different ecosystem services can be identified, so that policies can be designed to avoid the worst trade-offs, and where possible, enhance multiple services. The paper brings together evidence from across the Rural Economy and Land Use Programme’s Sustainable Uplands project for the first time, with previously unpublished model outputs relating to runoff, agricultural suitability, biomass, heather cover, age, and utility for Red Grouse (Lagopus scotica), grass cover, and accompanying scenario narratives and video. Two contrasting scenarios, based on policies to extensify or intensify land management up to 2030, were developed through a combination of interviews and discussions during site visits with stakeholders, literature review, conceptual modeling, and process-based computer models, using the Dark Peak of the Peak District National Park in the UK as a case study. Where extensification leads to a significant reduction in managed burning and grazing or land abandonment, changes in vegetation type and structure could compromise a range of species that are important for conservation, while compromising provisioning services, amenity value, and increasing wildfire risk. However, where extensification leads to the restoration of peatlands damaged by former intensive management, there would be an increase in carbon sequestration and storage, with a number of cobenefits, which could counter the loss of habitats and species elsewhere in the landscape. In the second scenario, land use and management was significantly intensified to boost UK self-sufficiency in food. This would benefit certain provisioning services but would have negative consequences for carbon storage and water quality and would lead to a reduction in the abundance of certain species of conservation concern. The paper emphasizes the need for spatially explicit models that can track how ecosystem services might change over time, in response to policy or environmental drivers, and in response to the changing demands and preferences of society, which are far harder to anticipate. By developing such models in close collaboration with decision makers and other stakeholders, it is possible to depict scenarios of real concern to those who need to use the research findings. By engaging these collaborators with the research findings through film, it was possible to discuss adaptive options to minimize trade-offs and enhance the provision of multiple ecosystem services under the very different future conditions depicted by each scenario. By preparing for as wide a range of futures as possible in this way, it may be possible for decision makers to act rapidly and effectively to protect and enhance the provision of ecosystem services in the face of unpredictable future change.Additional co-authors: Nanlin Jin, Brian J Irvine, Mike J Kirkby, William E Kunin, Christina Prell, Claire H Quinn, Bill Slee, Sigrid Stagl, Mette Termansen, Simon Thorp, and Fred Worral

What is social learning?

Social learning is increasingly becoming a normative goal in natural resource management and policy. However, there remains little consensus over its meaning or theoretical basis. There are still considerable differences in understanding of the concept in the literature, including a number of articles published in Ecology & Society. Social learning is often conflated with other concepts such as participation and proenvironmental behavior, and there is often little distinction made between individual and wider social learning. Many unsubstantiated claims for social learning exist, and there is frequently confusion between the concept itself and its potential outcomes. This lack of conceptual clarity has limited our capacity to assess whether social learning has occurred, and if so, what kind of learning has taken place, to what extent, between whom, when, and how. This response attempts to provide greater clarity on the conceptual basis for social learning. We argue that to be considered social learning, a process must: (1) demonstrate that a change in understanding has taken place in the individuals involved; (2) demonstrate that this change goes beyond the individual and becomes situated within wider social units or communities of practice; and (3) occur through social interactions and processes between actors within a social network. A clearer picture of what we mean by social learning could enhance our ability to critically evaluate outcomes and better understand the processes through which social learning occurs. In this way, it may be possible to better facilitate the desired outcomes of social learning processes.Publisher PDFPeer reviewe