Strengthen causal models for better conservation outcomes for human well-being

This is the final version. Available from the publisher via the DOI in this record.All data files are available on github at www.github.com/scheng87/ toc.Background Understanding how the conservation of nature can lead to improvement in human conditions is a research area with significant growth and attention. Progress towards effective conservation requires understanding mechanisms for achieving impact within complex social-ecological systems. Causal models are useful tools for defining plausible pathways from conservation actions to impacts on nature and people. Evaluating the potential of different strategies for delivering co-benefits for nature and people will require the use and testing of clear causal models that explicitly define the logic and assumptions behind cause and effect relationships. Objectives and methods In this study, we outline criteria for credible causal models and systematically evaluated their use in a broad base of literature (~1,000 peer-reviewed and grey literature articles from a published systematic evidence map) on links between nature-based conservation actions and human well-being impacts. Results Out of 1,027 publications identified, only ~20% of articles used any type of causal models to guide their work, and only 14 total articles fulfilled all criteria for credibility. Articles rarely tested the validity of models with empirical data. Implications Not using causal models risks poorly defined strategies, misunderstanding of potential mechanisms for affecting change, inefficient use of resources, and focusing on implausible efforts for achieving sustainability.Science for Nature and People Partnership (SNAPP)National Institute for Health Research (NIHR

Using machine learning to advance synthesis and use of conservation and environmental evidence

This is the final version. Available from Wiley via the DOI in this record. National Institute for Health ResearchScience for Nature and People Partnershi

What are the effects of nature conservation on human well-being? A systematic map of empirical evidence from developing countries

This is the final version of the article. Available from BioMed Central via the DOI in this record.Background: Global policy initiatives and international conservation organizations have sought to emphasize and strengthen the link between the conservation of natural ecosystems and human development. While many indices have been developed to measure various social outcomes to conservation interventions, the quantity and strength of evidence to support the effects, both positive and negative, of conservation on different dimensions of human well-being, remain unclear, dispersed and inconsistent. Methods: We searched 11 academic citation databases, two search engines and 30 organisational websites for relevant articles using search terms tested with a library of 20 relevant articles. Key informants were contacted with requests for articles and possible sources of evidence. Articles were screened for relevance against predefined inclusion criteria at title, abstract and full text levels according to a published protocol. Included articles were coded using a questionnaire. A critical appraisal of eight systematic reviews was conducted to assess the reliability of methods and confidence in study findings. A visual matrix of the occurrence and extent of existing evidence was also produced. Results: A total of 1043 articles were included in the systematic map database. Included articles measured effects across eight nature conservation-related intervention and ten human well-being related outcome categories. Linkages between interventions and outcomes with high occurrence of evidence include resource management interventions, such as fisheries and forestry, and economic and material outcomes. Over 25 % of included articles examined linkages between protected areas and aspects of economic well-being. Fewer than 2 % of articles evaluated human health outcomes. Robust study designs were limited with less than 9 % of articles using quantitative approaches to evaluate causal effects of interventions. Over 700 articles occurred in forest biomes with less than 50 articles in deserts or mangroves, combined. Conclusions: The evidence base is growing on conservation-human well-being linkages, but biases in the extent and robustness of articles on key linkages persist. Priorities for systematic review, include linkages between marine resource management and economic/material well-being outcomes; and protected areas and governance outcomes. Greater and more robust evidence is needed for many established interventions to better understand synergies and trade-offs between interventions, in particular those that are emerging or contested.This study was made possible by a grant from the Gordon and Betty Moore Foundation to Conservation International (Grant No. 3519). This research was conducted by the Evidence-based Conservation Working Group and financially supported in part by SNAP: Science for Nature and People, a collaboration of The Nature Conservancy, the Wildlife Conservation Society and the National Center for Ecological Analysis and Synthesis (NCEAS)

Strengthen causal models for better conservation outcomes for human well-being.

BACKGROUND: Understanding how the conservation of nature can lead to improvement in human conditions is a research area with significant growth and attention. Progress towards effective conservation requires understanding mechanisms for achieving impact within complex social-ecological systems. Causal models are useful tools for defining plausible pathways from conservation actions to impacts on nature and people. Evaluating the potential of different strategies for delivering co-benefits for nature and people will require the use and testing of clear causal models that explicitly define the logic and assumptions behind cause and effect relationships. OBJECTIVES AND METHODS: In this study, we outline criteria for credible causal models and systematically evaluated their use in a broad base of literature (~1,000 peer-reviewed and grey literature articles from a published systematic evidence map) on links between nature-based conservation actions and human well-being impacts. RESULTS: Out of 1,027 publications identified, only ~20% of articles used any type of causal models to guide their work, and only 14 total articles fulfilled all criteria for credibility. Articles rarely tested the validity of models with empirical data. IMPLICATIONS: Not using causal models risks poorly defined strategies, misunderstanding of potential mechanisms for affecting change, inefficient use of resources, and focusing on implausible efforts for achieving sustainability

Using expert knowledge to develop a vulnerability and adaptation framework and methodology for application in tropical island communities

Climate change threatens tropical coastal communities and ecosystems. Governments, resource managers, and communities recognize the value of assessing the social and ecological impacts of climate change, but there is little consensus on the most effective framework to support vulnerability and adaptation assessments. The framework presented in this research is based on a gap analysis developed from the recommendations of climate and adaptation experts. The article highlights social and ecological factors that affect vulnerability to climate change; adaptive capacity and adaptation options informing policy and conservation management decisions; and a methodology including criteria to assess current and future vulnerability to climate change. The framework is intended for conservation practitioners working in developing countries, small island nations, and traditional communities. It identifies core components that assess climate change impacts on coastal communities and environments at the local scale, and supports the identification of locally relevant adaptation strategies. Although the literature supporting vulnerability adaptation assessments is extensive, little emphasis has been placed on the systematic validation of these tools. To address this, we validate the framework using the Delphi technique, a group facilitation technique used to achieve convergence of expert opinion, and address gaps in previous vulnerability assessment

Conservation organizations need to consider adaptive capacity: why local input matters

Conservation organizations are increasingly applying adaptive capacity assessments in response to escalating climate change impacts. These assessments are essential to identify climate risks to ecosystems, prioritize management interventions, maximize the effectiveness of conservation actions, and ensure conservation resources are allocated appropriately. Despite an extensive literature on the topic, there is little agreement on the most relevant factors needed to support local scale initiatives, and additional guidance is needed to clarify how adaptive capacity should be assessed. This paper discusses why adaptive capacity assessment represents a critical tool supporting conservation planning and management. It also evaluates key factors guiding conservation NGOs conducting these assessments in tropical island communities, and explores alternative priorities based on input from academic experts and key local stakeholders. Our results demonstrate that important differences exist between local stakeholders and non-local academic experts on key factors affecting adaptation and coping mechanisms. The exclusion of local community input affects the validity of adaptive capacity assessment findings, and has significant implications for the prioritization and effectiveness of conservation strategies and funding allocation

Achieving social and ecological goals of coastal management through integrated monitoring

Successful resource management relies on an understanding of the complex relationships between social and natural systems and their governance (Berkes et al., 2016). Taken together these interacting systems have been described as part of a social?ecological system (SES). Here, natural system refers to the biological and physical (biophysical) system and is used interchangeably with ecological system or ecosystem. Social system is used to characterize the interactions within and among human communities and their institutions, particularly those related to resource governance. The SES framework was developed to explain the many complexities of these relationships, but also to characterize what contexts and processes could help improve the management of natural resources (Ostrom, 2009). More specifically, SES has been defined as 'a system that includes societal (human) and ecological (biophysical) subsystems in mutual interactions' (Harrington et al., 2010) or a system 'where social and ecological systems are mutually dependent' (Fidel, Kliskey, Alessa, & Sutton, 2014). Management is most successful when it maximizes the benefits that natural resources provide to people and human stewardship of the environment. To date, limited evidence linking conservation and natural resource management interventions to human well?being exists (McKinnon et al., 2016). Monitoring must adapt to capture this complexity, and in particular, focus sharply on the interactions and interdependencies of natural and social systems. In the sustainability sciences, when monitoring is part of adaptive management, the purpose is to track ecosystem change over time, assess management implementation, and evaluate how well objectives were achieved (Kendall & Moore, 2012). Natural resource managers have monitored the biophysical status of ecosystems for decades; however, monitoring social systems has not been as well defined nor have the links between biophysical and social systems been adequately addressed (Wongbusarakum & Heenan, 2018). While conceptual frameworks for SES have advanced (Ostrom, 2009), practical approaches are needed to examine human–environment interactions in different contexts and specific scales (Fleischman et al., 2014; Kittinger, Finkbeiner, Glazier, & Crowder, 2012). Integration of monitoring efforts may enhance the understanding of human?derived benefits from natural systems and improve natural resource management