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There has been growing recognition of the importance of engaging communities in environmental health research. Among the various methods of community-engaged research, one approach is to work with community ambassadors – people who are active and well connected in their communities – to facilitate scientists’ interactions with community members. Drawing on our own experiences as community ambassadors in the WellHome Study, an investigation of indoor air quality in West London, UK, we offer 3 key insights to scientists interested in this model of community-engaged research. We argue, first, that community ambassadors can help scientists build trust and engage research participants. Second, we note the value of fully integrating community ambassadors into a project team and present suggestions for how this may be accomplished. Third, we underscore the importance of remunerating community ambassadors and the need for careful reflection on the amount and form of compensation. While much has been written about the advantages and challenges of community-engaged research, this commentary brings the voice of community members to the fore of these discussions. It highlights how the community ambassador model can bring mutual benefits, furthering research goals while also providing a meaningful experience for community members. 

Innovations in genetics and genomics have been heavily critiqued as technologies that have widely supported the privatization and commodification of natural resources. However, emerging applications of these tools to ecological restoration challenge narratives that cast genetic technoscience as inevitably enrolled in the enactment and extension of neoliberal capitalism. In this paper, we draw on Langdon Winner’s theory of technological politics to suggest that the context in which genetic technologies are developed and deployed matters for their political outcomes. We describe how genetic approaches to the restoration of functionally extinct American chestnut trees—by non-profit organizations, for the restoration of a wild, heritage forest species, and with unconventional intellectual property protections—are challenging precedents in the political economy of plant biotechnology. Through participant observation, interviews with scientists, and historical analysis, we employ the theoretical lens provided by Karl Polanyi’s double movement to describe how the anticipations and agency of the developers of blight-resistant American chestnut trees, combined with chestnut biology and the context of restoration, have thus far resisted key forms of the genetic privatization and commodification of chestnut germplasm. Still, the politics of blight-resistant American chestnut remain incomplete and undetermined; we thus call upon scholars to use the uneven and socially constructed character of both technologies and neoliberalism to help shape this and other applications of genetic technoscience for conservation. 

Given the scale and speed of contemporary environmental changes, intensive conservation interventions are increasingly being proposed that would assist the evolution of adaptive traits in threatened species. The ambition of these projects is tempered by a number of concerns, including the potential maladaptation of manipulated organisms for contemporary and future climatic conditions in their historical ranges. Following the guidelines of the International Union for the Conservation of Nature, we use a species distribution model (SDM) to consider the potential impact of climate change on the distribution and quantity of suitable habitat for American chestnut (Castanea dentata), a functionally extinct forest species that has been the focus of various restoration efforts for over 100 years. Consistent with other SDMs for North American trees, our model shows contraction of climatically suitable habitat for American chestnut within the species’ historical range and the expansion of climatically suitable habitat in regions to the north of it by 2080. These broad changes have significant implications for restoration practice. In particular, they highlight the importance of germplasm conservation, local adaptation, and addressing knowledge gaps about the interspecific interactions of American chestnut. More generally, this model demonstrates that the goals of assisted evolution projects, which often aim to maintain species in their native ranges, need to account for the uncertainty and novelty of future environmental conditions. 

Our ability to visualize and quantify the internal structures of objects via computed tomography (CT) has fundamentally transformed science. As tomographic tools have become more broadly accessible, researchers across diverse disciplines have embraced the ability to investigate the 3D structure-function relationships of an enormous array of items. Whether studying organismal biology, animal models for human health, iterative manufacturing techniques, experimental medical devices, engineering structures, geological and planetary samples, prehistoric artifacts, or fossilized organisms, computed tomography has led to extensive methodological and basic sciences advances and is now a core element in science, technology, engineering, and mathematics (STEM) research and outreach toolkits. Tomorrow's scientific progress is built upon today's innovations. In our data-rich world, this requires access not only to publications but also to supporting data. Reliance on proprietary technologies, combined with the varied objectives of diverse research groups, has resulted in a fragmented tomography-imaging landscape, one that is functional at the individual lab level yet lacks the standardization needed to support efficient and equitable exchange and reuse of data. Developing standards and pipelines for the creation of new and future data, which can also be applied to existing datasets is a challenge that becomes increasingly difficult as the amount and diversity of legacy data grows. Global networks of CT users have proved an effective approach to addressing this kind of multifaceted challenge across a range of fields. Here we describe ongoing efforts to address barriers to recently proposed FAIR (Findability, Accessibility, Interoperability, Reuse) and open science principles by assembling interested parties from research and education communities, industry, publishers, and data repositories to approach these issues jointly in a focused, efficient, and practical way. By outlining the benefits of networks, generally, and drawing on examples from efforts by the Non-Clinical Tomography Users Research Network (NoCTURN), specifically, we illustrate how standardization of data and metadata for reuse can foster interdisciplinary collaborations and create new opportunities for future-looking, large-scale data initiatives.