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Institutions have made significant investments to support public access to research data requirements; yet have little comparative data about these services, infrastructure, and costs. To address this need, the research team undertook a mixed-methods approach to understand the institution-wide expenses for research data management and sharing and began to draft an expense model for data management and sharing. This model is further useful for institutions that provide research data management and sharing. 

This dataset is the result of studies conducted during phase one (NSF-funded) of the Realities of Academic Data Sharing (RADS) Initiative, based out of the Association of Research Libraries. Studies were conducted with federally-funded researchers and institutional administrators who support data sharing practices within their department or unit at the following institutions: Cornell University, Duke University, University of Michigan, University of Minnesota, Virginia Tech, and Washington University in St. Louis. The 2022 RADS studies were retrospective, investigating data sharing and management activities and support services from 2013 to 2022. Two surveys were utilized to collect data, the Institutional Infrastructure Survey for administrators and the Researcher Survey for federally-funded researchers. This dataset presents data from both of these surveys. Project website: https://www.arl.org/realities-of-academic-data-sharing-rads-initiative/ 

Abstract Wildfire is a disturbance expected to increase in frequency and severity, changes that may impact carbon (C) dynamics in the soil ecosystem. Fire changes the types of C sources available to soil microbes, increasing pyrogenic C and coarse downed wood, and if there is substantial tree mortality, decreasing C from root exudates and leaf litter. To investigate the impact of this shift in the composition of C resources on microbial processes driving C cycling, we examined microbial activity in soil sampled from an Oregon burn 1 year after fire from sites spanning a range in soil burn severity from unburned to highly burned. We found evidence that postfire rhizosphere priming loss may reduce soil C loss after fire. We measured the potential activity of C‐acquiring and nitrogen (N)‐acquiring extracellular enzymes and contextualized the microbial resource demand using measurements of mineralizable C and N. Subsurface mineralizable C and N were unaltered by fire and negatively correlated with hydrolytic extracellular enzyme activity (EEA) in unburned, but not burned sites. EEA was lower in burned sites by up to 46%, but only at depths below 5 cm, and with greater decreases in sites with high soil burn severity. These results are consistent with a subsurface mechanism driven by tree mortality. We infer that in sites with high tree mortality, subsurface EEAs decreased due to loss of rhizosphere priming and that inputs of dead roots contributed to mineralizable C stabilization.