Data management plan for the grant "Functional Porous Organic Polymers as Advanced Decontamination Materials for Water Purification." This project seeks to develop and deploy a new class of porous organic polymers which have high capacity and selectivity to rapidly remove heavy metal contaminants well below parts per million level standards set by the Environmental Protection Agency. The project will engineer porosity and surface chemistry of porous organic polymers to clean inorganic heavy metal contaminants from both surface water and wastewater. Porous organic polymers are robust, chemically and thermally stable, scalable, and modular, with very high surface area. The modularity of these polymers allows for a molecular-level tuning of the pore structure and surface chemistry that allows for engineered site-specificity of binding sites that target the heavy metal contaminants. Recent data shows these new materials offer a significant increase in capacity relative to benchmark materials, with a rapid removal of mercury and other heavy metal ions. This project will advance the concept by exploring rational design of these porous polymers with different topologies by customizing the monomer with various binding groups. The objectives of the project include design, synthesis, and characterization, followed by assessment of these materials to remove inorganic contaminants …

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?