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Forest restoration occupies center stage in global conversations about carbon removal and biodiversity conservation, but recent research rarely acknowledges social dimensions or environmental justice implications related to its implementation. We find that 294.5 million people live on tropical forest restoration opportunity land in the Global South, including 12% of the total population in low-income countries. Forest landscape restoration that prioritizes local communities by affording them rights to manage and restore forests provides a promising option to align global agendas for climate mitigation, conservation, environmental justice, and sustainable development.

The awareness of the need for robust impact evaluations in conservation is growing and statistical matching techniques are increasingly being used to assess the impacts of conservation interventions. Used appropriately matching approaches are powerful tools, but they also pose potential pitfalls. We outlined important considerations and best practice when using matching in conservation science. We identified 3 steps in a matching analysis. First, develop a clear theory of change to inform selection of treatment and controls and that accounts for real-world complexities and potential spillover effects. Second, select the appropriate covariates and matching approach. Third, assess the quality of the matching by carrying out a series of checks. The second and third steps can be repeated and should be finalized before outcomes are explored. Future conservation impact evaluations could be improved by increased planning of evaluations alongside the intervention, better integration of qualitative methods, considering spillover effects at larger spatial scales, and more publication of preanalysis plans. Implementing these improvements will require more serious engagement of conservation scientists, practitioners, and funders to mainstream robust impact evaluations into conservation. We hope this article will improve the quality of evaluations and help direct future research to continue to improve the approaches on offer. Emparejamiento Estadístico para la Ciencia de la ConservaciónResumen: Hay más conciencia sobre la necesidad de evaluaciones de impacto más rigurosas y las técnicas de emparejamiento estadístico se están usan con más frecuencia para evaluar los impactos de intervenciones de conservación. Las técnicas de emparejamiento pueden ser herramientas poderosas si son utilizadas correctamente, pero también pueden llevar a conclusiones erróneas. En este artículo describimos consideraciones importantes para realizar estudios de conservación que utilizan técnicas de emparejamiento estadístico. Identificamos tres pasos dentro de un análisis de emparejamiento. Primero, es importante desarrollar una teoría del cambio que considere las complejidades del mundo real y las posibles consecuencias indirectas para poder seleccionar unidades de tratamiento y controles. Segundo, es clave seleccionar las covarianzas y la estrategia de emparejamiento apropiadas. Tercero, evaluar la calidad del emparejamiento a través de una serie de revisiones. El segundo y el tercer paso pueden ser repetidos y deben concluirse antes de que se exploren los resultados. Evaluaciones de impacto de intervenciones de conservación podrían mejorarse con una mejor planeación de las evaluaciones junto con la intervención, una mejor integración de los métodos cualitativos, mejor consideración de consecuencias indirectas Article impact statement: The article identifies 3 steps in using matching in conservation impact evaluation, highlighting best practice and areas for improvement.

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Paragraph: 20Since the 1980's, decentralized forest management has been promoted as a way to enhance sustainable forest use and reduce rural poverty. Rural communities manage increasing amounts of the world's forests, yet rigorous evidence using large-N data on whether community-based forest management (CFM) can jointly reduce both deforestation and poverty remains scarce. We estimate impacts of CFM using a large 25 longitudinal dataset that integrates national-census-based poverty measures with highresolution forest cover change data, and near-complete information on Nepal's > 18,000 community forests. We compare changes in forest cover and poverty from 2000-2012 for sub-districts with presence or absence of CFM arrangements, but that are otherwise similar in terms of socioeconomic and biophysical baseline measures. Our 30 results indicate that CFM has, on average, contributed to significant net reductions in both poverty and deforestation across Nepal, and that CFM increases the likelihood of win-win outcomes. We also find that the estimated reduced deforestation impacts of community forests are lower where baseline poverty levels are high, and greater where community forests are larger and have existed longer. These results indicate that greater 35 benefits may result from longer-term investments and larger areas committed to community forest management, but that community forests established in poorer areas may require additional support to minimize tradeoffs between socioeconomic and environmental outcomes. Main text: 40Forests are critical to sustainable development 1,2 . They regulate climate, sequester carbon, harbour biodiversity, and contribute to national incomes and local livelihoods 3 .Over the past four decades, governments and international organizations have promoted decentralized community-based forest management (CFM) to achieve sustainable forest use and reduce rural poverty 4 . In decentralized decision-making arrangements, 45 the primary responsibility for day-to-day management rests with forest-user communities. Ideally, this allows communities to make better use of their time and place-specific knowledge to promote more efficient, equitable, and sustainable multifunctional landscapes 5 .Local communities now legally manage approximately 13% of the world's 50 forests 6 . Debates about whether CFM truly reduces forest loss and alleviates poverty, nonetheless, continue 7,8 . Case studies from Latin America, Africa, and South Asia show that some CFM initiatives have improved forest and livelihood outcomes 9,10 , but that others have not achieved intended objectives 4,11 . The vast majority of existing studies have focused on limited sets of cases, and have used qualitative assessments of poverty 55 and livelihood outcomes that are difficult to compare across space and over time 7 .These studies have helped to identify how land tenure, local autonomy, and collective action may contribute to effective and equitable CFM, but have not tested whether CFM programs lead to net environmental and socioe...

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