Data management plan for the research grant "Generating pathogen- / pest-resistant non-GMO cotton through targeted genome editing of oxylipin signaling pathways."

Data management plan for the grant, "NSFDEB-NERC: Collaborative Research: Wildlife corridors: do they work and who benefits?" Research on the impact of wildlife corridors using genetics as the measure of effectiveness. The study will use 20 independent landscapes to quantify how corridor traits affect gene flow, and will use non-flying mammals as focal species because they are strongly affected by fragmentation. The research team hypothesizes (1) a strong non-linear decline in success (gene flow) with corridor length, reflecting the skewed distribution of dispersal distances within species; (2) success will drop steeply as corridor width falls below a threshold, with the threshold determined by species traits; and (3) species that are bigger, are habitat specialists, or have greater dispersal abilities (relative to brain size or reproductive rate) will benefit more from corridors. Testing these hypotheses will allow generalization to a wide range of mammal species not included in this project. It will use highly flexible Random Forest models to answer the overarching question: What landscape traits (e.g., corridor width, degree of human disturbance) and species traits (mobility, affinity to particular land cover types) are associated with effective corridors?

This report discusses a proposed framework for modifications to AI/ML-based SaMD that is based on the internally harmonized International Medical Device Regulators Forum risk categorization principles, FDA's benfit-risk framework, risk management principles in the software modifications guidance, and the organization-based TPLC approach as envisioned in the Digital health Software Precertification Program. The authors ask for public feedback about the questions posed in the report.