Climate change mitigation in food systems: the environmental and health impacts of shifting towards sustainable diets, a systematic review protocol.

Food systems contribute greatly to global climate change due to their substantial contributions to greenhouse gas emissions, water use, and resource allocation. In addition, current food systems fail to deliver healthy and sustainable foods for all, with obesity as well as undernourishment remaining a pertinent global issue. Mounting pressures such as population growth and urbanisation urge rapid and transformational adaptations in food systems to sustainably feed a growing population. Sustainable diets have been promoted as a potential climate change mitigation strategy, and are characterized by high plant based foods and reduced animal-sourced and processed foods. While the evidence base on the potential health and environmental impacts of shifts towards sustainable diets has been growing rapidly over the past decade, there has been no recent synthesis of the evidence surrounding the health and climate mitigation benefits of sustainable consumption patterns. This systematic review will synthesize the evidence of both empirical and modelling studies assessing the direct health outcomes (such as all-cause mortality and body mass index) as well as environmental impacts (greenhouse gas emissions, land use, water use etc.) of shifts towards sustainable diets. Eight literature databases will be searched to identify studies published between 1999-2019 that report both health and environmental outcomes of sustainable diets. Evidence will be mapped and subsequently analysed based on the comparability of results and reported outcomes

Carbon pricing, health co-benefits and trade-offs: protocol for a systematic framework synthesis

Carbon pricing is considered an important instrument in the fight against climate change (World Bank, 2022). In particular, many experts and stakeholders have called for the implementation of carbon pricing as a part of ambitious climate policy agendas (Hepburn et al., 2020). This requires consideration of the interactions of carbon pricing with other policies, as well as of the societal outcomes of carbon pricing. In particular, carbon pricing has been found to have potentially large health impacts, leading to important co-benefits as well as potentially some trade-offs (Parry et al., 2014), (Hasegawa et al., 2018). Information on health impacts of carbon pricing, their distribution and how they are affected by policy design is necessary in order to progress towards more socially sustainable and politically feasible policy design. Recent reviews have focussed on various aspects of carbon pricing design and outcomes, synthesizing evidence on its effectiveness, equity impacts or societal perception (Boyce, 2018), (Green, 2021), (Maestre-Andrés et al., 2019). Others have reviewed the evidence on health co-benefits of mitigation, but do not analyse specific policies or issues of policy design Gao et al.(2018). This review will narratively synthesize the evidence on the health impacts of carbon pricing between 2010 and 2021 and identify gaps in the literature. We will use a framework synthesis approach to analyse different categories of policy-relevant information in contexts where carbon pricing is implemented as part of wider, coordinated policy agendas or complex policy mixes. This includes for example impacts on health inequalities and how health co-benefits are affected by issues of policy design and policy interactions.</ns4:p

A framework for characterising and evaluating the effectiveness of environmental modelling

Environmental modelling is transitioning from the traditional paradigm that focuses on the model and its quantitative performance to a more holistic paradigm that recognises successful model-based outcomes are closely tied to undertaking modelling as a social process, not just as a technical procedure. This paper redefines evaluation as a multi-dimensional and multi-perspective concept, and proposes a more complete framework for identifying and measuring the effectiveness of modelling that serves the new paradigm. Under this framework, evaluation considers a broader set of success criteria, and emphasises the importance of contextual factors in determining the relevance and outcome of the criteria. These evaluation criteria are grouped into eight categories: project efficiency, model accessibility, credibility, saliency, legitimacy, satisfaction, application, and impact. Evaluation should be part of an iterative and adaptive process that attempts to improve model-based outcomes and foster pathways to better futures

A checklist for model credibility, salience, and legitimacy to improve information transfer in environmental policy assessments

Modelers involved in environmental policy assessments are commonly confronted with the lack of uptake of model output by policy actors. Actors have different expectations of models, condensed into three quality criteria: credibility, salience, and legitimacy. The fulfilment of quality criteria is also dynamic as expectations vary, change, and possibly counteract each other. We present a checklist for modelers involved in model-based assessments that is aimed at the identification and monitoring of issues, limitations and trade-offs regarding model quality criteria. It draws upon the literature of integrated assessments as well as case study analysis of environmental policy assessments for the Dutch government, based on expert interviews and embedded experience. The checklist is intended to be consulted during assessments; its application may result in greater awareness among modelers involved in assessments regarding model quality criteria, and may positively affect the uptake of model-based knowledge from environmental policy assessments by policy actors

Biophysical Measures to Support Analysis and Communication of Existence Values

A recent focus of ecosystem services research has been on the definition of biophysical outcomes and measures most closely linked to social welfare. There is a particular need to identify biophysical outcomes corresponding to existence values. (Values associated with existence apart from any current or future use.) We review economic and ecological evidence to answer two key questions: First, what are ideal characteristics of linking indicators for existence values? Linking indicators should be: understandable, subject to direct sensory perception, represented at relevant temporal and spatial scales, comprehensive, and quantifiable in a repeatable manner. Second, what types of ecosystem outcomes are most likely to be associated with these values? We distinguish between indicators of taxa and ecological landscapes, and then multiple subcategories within each. Our fundamental conclusion is that while there are general principles informing the specification of linking indicators of existence values, there is no compact set of indicators or measures that applies universally. The case-specific nature of these issues — general guidelines notwithstanding — implies the need for sustained partnerships between social and biophysical scientists to address questions of indicator choice. © 2023 J. Boyd, R. J. Johnston and P. Ringold

Human Dimensions of a Participatory, Collaborative Modeling Process - Oysterfutures

Participatory, collaborative modeling processes represent a unique decision-making technique within natural resources management that allows for the combination of stakeholder involvement with the analytical and predictive power of scientific models. The continued use of participatory modeling within decision-making processes depends in part upon the willingness of stakeholders to participate. Continued participation of stakeholders is key to the persistence and overall success of these processes, and yet limited information exists concerning the impacts of these processes on participants. The consideration of human dimensions advances our understanding of the design and function of participatory modeling processes, including their ability to create consensus outcomes, their capacity to integrate natural and social sciences, and their capability to advance sustainable natural resources policy and management. Within this thesis, I analyzed stakeholders’ advice and communication social networks and their attitudes towards scientific models to better understand the impact of these participatory modeling processes on participants. I found that the development of group cohesion was more heterogeneous than previously thought. While there was a significant increase in advice ties between OysterFutures members, silos of advice within stakeholder groups remained. There was also a high level of between-stakeholder group advice ties that existed prior to the OysterFutures process. This history between stakeholders and stakeholder groups is also thought to have impacted the development of advice ties. Lastly, the transition of the advice network structure over time supports arguments in the literature that suggest that different network structures are necessary at certain time points during participatory processes. Stakeholder group silos also persisted within the communication network. These silos are thought to have helped stakeholder groups develop their own attitude towards scientific models based on their unique “way of knowing”. As a result, attitudes towards models were significantly different between stakeholder groups. This strength of stakeholder group impact on attitudes likely limited overall changes in attitudes towards models over the course of OysterFutures. The importance of considering social network structure of participatory modeling processes was demonstrated through results that certain brokering network positions significantly impacted attitudes towards models. Methods to facilitate more between group communications during participatory modeling processes could help mitigate the strong impact of stakeholder group membership on attitudes. Overall, results for attitudes towards models support the idea that models are acting as “boundary objects” that help facilitate discussion during these processes