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dc.contributor.authorMcGonigle, Daniel F
dc.contributor.authorRota Nodari, Giulia
dc.contributor.authorPhillips, Robyn L
dc.contributor.authorAynekulu, Ermias
dc.contributor.authorEstrada-Carmona, Natalia
dc.contributor.authorJones, Sarah K
dc.contributor.authorKoziell, Izabella
dc.contributor.authorLuedeling, Eike
dc.contributor.authorRemans, Roseline
dc.contributor.authorShepherd, Keith
dc.contributor.authorWiberg, David
dc.contributor.authorWhitney, Cory
dc.contributor.authorZhang, Wei
dc.description.abstractSustainable land management is at the heart of some of the most intractable challenges facing humanity in the 21st century. It is critical for tackling biodiversity loss, land degradation, climate change and the decline of ecosystem services. It underpins food production, livelihoods, dietary health, social equity, climate change adaptation, and many other outcomes. However, interdependencies, trade-offs, time lags, and non-linear responses make it difficult to predict the combined effects of land management decisions. Policy decisions also have to be made in the context of conflicting interests, values and power dynamics of those living on the land and those affected by the consequences of land use decisions. This makes designing and coordinating effective land management policies and programmes highly challenging. The difficulty is exacerbated by the scarcity of reliable data on the impacts of land management on the environment and livelihoods. This poses a challenge for policymakers and practitioners in governments, development banks, non-governmental organisations, and other institutions. It also sets demands for researchers, who are under ever increasing pressure from funders to demonstrate uptake and impact of their work. Relatively few research methods exist that can address such questions in a holistic way. Decision makers and researchers need to work together to help untangle, contextualise and interpret fragmented evidence through systems approaches to make decisions in spite of uncertainty. Individuals and institutions acting as knowledge brokers can support these interactions by facilitating the co-creation and use of scientific and other knowledge. Given the patchy nature of data and evidence, particularly in developing countries, it is important to draw on the full range of available models, tools and evidence. In this paper we review the use of evidence to inform multiple-objective integrated landscape management policies and programmes, focusing on how to simultaneously achieve different sustainable development objectives in diverse landscapes. We set out key success factors for evidence-based decision-making, which are summarised into 10 key principles for integrated landscape management knowledge brokering in integrated landscape management and 12 key skills for knowledge brokers. We finally propose a decision-support framework to organise evidence that can be used to tackle different types of land management policy decision.
dc.publisherFrontiers Media SA
dc.rightsAttribution 4.0 International (CC BY 4.0)
dc.subjectSustainable Food Systems
dc.subjectintegrated landscape management
dc.subjectmulti-functional landscapes
dc.subjectsustainable agricultural intensification
dc.subjectnatural resource management
dc.subjectdecision support
dc.subjectknowledge broker
dc.subjectscience-policy interface
dc.subjectscience into policy
dc.titleA Knowledge Brokering Framework for Integrated Landscape Management
prism.publicationNameFrontiers in Sustainable Food Systems

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Attribution 4.0 International (CC BY 4.0)
Except where otherwise noted, this item's licence is described as Attribution 4.0 International (CC BY 4.0)