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1. Toward a national eDNA strategy for the United States

   https://doi.org/10.1002/edn3.432  

   Kelly, Ryan P.; Lodge, David M.; Lee, Kai N.; Theroux, Susanna; Sepulveda, Adam J.; Scholin, Christopher A.; Craine, Joseph M.; Andruszkiewicz Allan, Elizabeth; Nichols, Krista M.; Parsons, Kim M.; et al (January 2024, Environmental DNA)

   Abstract Environmental DNA (eDNA) data make it possible to measure and monitor biodiversity at unprecedented resolution and scale. As use‐cases multiply and scientific consensus grows regarding the value of eDNA analysis, public agencies have an opportunity to decide how and where eDNA data fit into their mandates. Within the United States, many federal and state agencies are individually using eDNA data in various applications and developing relevant scientific expertise. A national strategy for eDNA implementation would capitalize on recent scientific developments, providing a common set of next‐generation tools for natural resource management and public health protection. Such a strategy would avoid patchwork and possibly inconsistent guidelines in different agencies, smoothing the way for efficient uptake of eDNA data in management. Because eDNA analysis is already in widespread use in both ocean and freshwater settings, we focus here on applications in these environments. However, we foresee the broad adoption of eDNA analysis to meet many resource management issues across the nation because the same tools have immediate terrestrial and aerial applications. 

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2. Impacts of climate change on multiple use management of Bureau of Land Management land in the Intermountain West, USA

   https://doi.org/10.1002/ecs2.3286  

   Brice, Elaine_M; Miller, Brett_A; Zhang, Hongchao; Goldstein, Kirsten; Zimmer, Scott_N; Grosklos, Guenchik_J; Belmont, Patrick; Flint, Courtney_G; Givens, Jennifer_E; Adler, Peter_B; et al (November 2020, Ecosphere)

   Abstract Although natural resource managers are concerned about climate change, many are unable to adequately incorporate climate change science into their adaptation strategies or management plans, and are not always aware of or do not always employ the most current scientific knowledge. One of the most prominent natural resource management agencies in the United States is the Bureau of Land Management (BLM), which is tasked with managing over 248 million acres (>1 million km²) of public lands for multiple, often conflicting, uses. Climate change will affect the sustainability of many of these land uses and could further increase conflicts between them. As such, the purpose of our study was to determine the extent to which climate change will affect public land uses, and whether the BLM is managing for such predicted effects. To do so, we first conducted a systematic review of peer‐reviewed literature that discussed potential impacts of climate change on the multiple land uses the BLM manages in the Intermountain West, USA, and then expanded these results with a synthesis of projected vegetation changes. Finally, we conducted a content analysis of BLM Resource Management Plans in order to determine how climate change is explicitly addressed by BLM managers, and whether such plans reflect changes predicted by the scientific literature. We found that active resource use generally threatens intrinsic values such as conservation and ecosystem services on BLM land, and climate change is expected to exacerbate these threats in numerous ways. Additionally, our synthesis of vegetation modeling suggests substantial changes in vegetation due to climate change. However, BLM plans rarely referred to climate change explicitly and did not reflect the results of the literature review or vegetation model synthesis. Our results suggest there is a disconnect between management of BLM lands and the best available science on climate change. We recommend that the BLM actively integrates such research into on‐the‐ground management plans and activities, and that researchers studying the effects of climate change make a more robust effort to understand the practices and policies of public land management in order to effectively communicate the management significance of their findings. 

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3. Zero to a trillion: Advancing surface process studies with open access to high resolution topography

   https://doi.org/10.1016/B978-0-444-64177-9.00011-4  

   Crosby, C. J.; Arrowsmith, J R.; Nandigam, V. (January 2020, Developments in earth surface processes)

   Tarolli, P.; Mudd, S. (Ed.)

   High-resolution topography (HRT) is a powerful observational tool for studying the Earth's surface, vegetation, and urban landscapes, with broad scientific, engineering, and education-based applications. Submeter resolution imaging is possible when collected with laser and photogrammetric techniques using the ground, air, and space-based platforms. Open access to these data and a cyberinfrastructure platform that enables users to discover, manage, share, and process then increases the impact of investments in data collection and catalyzes scientific discovery. Furthermore, open and online access to data enables broad interdisciplinary use of HRT across academia and in communities such as education, public agencies, and the commercial sector. OpenTopography, supported by the US National Science Foundation, aims to democratize access to Earth science-oriented, HRT data and processing tools. We utilize cyberinfrastructure, including large-scale data management, high-performance computing, and service-oriented architectures to provide efficient web-based visualization and access to large, HRT datasets. OT colocates data with processing tools to enable users to quickly access custom data and derived products for their application, with the ultimate goal of making these powerful data easier to use. OT's rapidly growing data holdings currently include 283 lidar and photogrammetric, point cloud datasets (>1.2 trillion points) covering 236,364km2. As a testament to OT's success, more than 86,000 users have processed over 5 trillion lidar points. This use has resulted in more than 290 peer-reviewed publications across numerous academic domains including Earth science, geography, computer science, and ecology. 

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4. Evaluation of Docker Containers for Scientific Workloads in theCloud

   Saha, Pankaj; Beltre, Angel; Uminski, Piotr; Govindaraju, Madhusudhan (July 2018, Practice and Experience in Advanced Research Computing (PEARC), 2018.)

   The HPC community is actively researching and evaluating tools to support execution of scientific applications in cloud-based environ- ments. Among the various technologies, containers have recently gained importance as they have significantly better performance compared to full-scale virtualization, support for microservices and DevOps, and work seamlessly with workflow and orchestration tools. Docker is currently the leader in containerization technology because it offers low overhead, flexibility, portability of applications, and reproducibility. Singularity is another container solution that is of interest as it is designed specifically for scientific applications. It is important to conduct performance and feature analysis of the container technologies to understand their applicability for each application and target execution environment. This paper presents a (1) performance evaluation of Docker and Singularity on bare metal nodes in the Chameleon cloud (2) mecha- nism by which Docker containers can be mapped with InfiniBand hardware with RDMA communication and (3) analysis of mapping elements of parallel workloads to the containers for optimal re- source management with container-ready orchestration tools. Our experiments are targeted toward application developers so that they can make informed decisions on choosing the container tech- nologies and approaches that are suitable for their HPC workloads on cloud infrastructure. Our performance analysis shows that sci- entific workloads for both Docker and Singularity based containers can achieve near-native performance. Singularity is designed specifically for HPC workloads. However, Docker still has advantages over Singularity for use in clouds as it provides overlay networking and an intuitive way to run MPI applications with one container per rank for fine-grained resources allocation. Both Docker and Singularity make it possible to directly use the underlying network fabric from the containers for coarse- grained resource allocation. 

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5. APLU AAU Accelerating Public Access to Research Data Workshop Report

   https://doi.org/10.31219/osf.io/63mxh  

   Redd, Kacy; Steen, Katie; Nusser, Sarah; Smith, Tobin; Walters, Tyler; Chasen, Jeff; Luther, James; and Reecy, James (August 2019, APLU AAU Accelerating Public Access to Research Data Workshop (2018))

   The Association of Public and Land-grant Universities (APLU) and the Association of American Universities (AAU), with support from the National Science Foundation, convened the Accelerating Public Access to Research Data Workshop on October 29-30, 2018. The purpose of the workshop was to provide a venue for learning, sharing, and planning (campus roadmaps) to support research universities as they create and implement institutional and cross-institutional strategies and systems to provide public access to research data. It also provided a forum for participants to hear from federal agencies concerning their current activities and plans regrading data access. To date, institutional efforts to provide public access to research data have lacked coordination. Additionally, a long-term multi-institutional strategy for data access has been slow to develop due to the complexities of data management and the decentralized nature of the research enterprise. Access to data presents a particularly difficult challenge given the technical knowledge required and the variation in data creation and use across disciplines. While providing the public with access to tax-payer-funded research data is challenging, it will ultimately speed the pace of scientific advancement and innovation and strengthen research integrity. The workshop and report, together with prior and subsequent engagement by APLU and AAU, will help to accelerate public access to research data. 

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