Performing Department
(N/A)
Non Technical Summary
The ongoing global climate changeshave cast large uncertainties forthe future sustainability of agricultural and natural systems. Programs are needed toprovide students the opportunity to participate in cutting edge research addressing the most pressing issues that agricultural and natural systems face, including but not limited to climate variability and change. One of the challenges ofthese programs is a shortage of students with quantitative skills in modeling, GIS, and remote sensing, which is particularly critical in minority-serving institutions or medium-to-small institutions that traditionally lack of such resources.This project aims to strengthen research capacity in geospatial data science by providing Hispanic undergraduatessystematic experiential learningopportunities via new geospatial data science modules, new research course, and subsequent summer internship. Theobjectivesare: 1) to enhance geospatial data science skills of Hispanic students with hands-on research experiences; 2) to enhance critical thinking and problem-solving skills in application of geospatial data science to research addressing challenges of climate variability and change via mentoring; 3) to attract/support Hispanic students for preparation of careers in agriculture/natural resources or graduate school; and 4) to self-sustain the systematic research training and to strengthen long-term cooperative consortium among HSIs, USDA, and State governmental agencies beyond the project implementation. Theactivitiesare: 1) to develop modules of geospatial data science in agricultural and natural resources and offer in courses of GIS, Remote Sensing, and Statistics; 2) to develop and offer a new research course on applications of geospatial data science to research of agricultural and natural resources; 3) to provide summer internships at participating USDA, State governmental agency, and HSIs; 4) to provide communication, leadership development and career advising; and 5) to recruit, retain, and keep track of participating students beyond the project.Students to be recruited: 25 summer interns, 50 participating the research course, 50 more benefiting from geospatial data science modules.Intended Impacts: The project will leadto enhanced research capacities in geospatial data science, systematic experiential learning, enriched curricula, sustainable cooperation among HSIs, USDA, and State agencies, and attracting/ retaining of Hispanic students.
Animal Health Component
0%
Research Effort Categories
Basic
100%
Applied
(N/A)
Developmental
(N/A)
Goals / Objectives
1) To enhance geospatial data science skills of Hispanic students with hands-on research experiences;2) To enhance critical thinking and problem-solving skills in application of geospatial data science to research addressing challenges of climate variability and change via mentoring;3) To attract / support Hispanic students for preparation of careers in agriculture/natural resources or graduate school; and4) To self-sustain the systematic research training and strengthen long-term cooperative consortium among HSIs, USDA, and State governmental agencies beyond the project implementation.
Project Methods
1. Student Recruitment, Selection, and Retention - The plan ensures broad coverage, fair selection, and high retention, resulting in at least 50 trained in the geospatialdata sciencemodules and the research class and 25 in summer experiential learning from the host and the small HSIs. We extend the research engagement and the mentor / student interaction into semesters and interact both onsite and online. Specifically, the plan includes1) Pre-intern recruitment information-session online and onsite; 2) Selection for trainings in geospatial data science skills and science during springs; 3) Selection for summer intern fellows; and 4) After-intern retention, feedback, and track.2. Nature of Student Activities - Tropical forests have the largest plant C pool and highest net primary productivity (Pan et al. 2013), playing essential roles in sequestrating C globally and modulating changes in climate. At the coast, mangroves sequester large amounts of C with exceedingly high water use efficiency and low decomposition (Hutchison et al. 2014). Yet, the sustainability of C sequestration is greatly challenged by warming (Cavaleri et al. 2015), sea level rise (SLR) (Krauss et al. 2014; Lovelock et al. 2015), and climate variability including severe droughts (Doughty et al. 2015; Duke et al. 2017) and frequent hurricanes (Uriarte et al. 2019; Yu and Gao 2020).The overarching scientific question for the research training is "how alternating hurricane and severe drought under warming and SLR interact to affect functions, structures, and services of tropical forests, and how they respond, adapt, and feedback to the press, pulse disturbances and their interactions?" Under this question, PD/mentors select 10 research projects linked to USDA managed lands of El Yunque and Luquillo Forest and downstream wetlands, providing students with unique exposure to different career paths and facilitating the El Yunque management plan that engages surrounding communities and agencies, e.g. DNER and Northeast Ecological Corridor.According to the overarching scientific question and corresponding research projects, the project proposes a systematic, coherent, experiential learning approach to strengthen research capacity in geospatial data science to address challenge of climate variability and change.Systematic Research Training Approach Via Hands-on exceptional quantitative skills in Geospatial Data Science and Machine Learning, Interactive research course, Experiential learning internship, and Cooperation - The integrated approach includes:1) Geospatial data science modules -curricula enrichment; 2) Research Course -curricula development, targeting geospatial data science applications in the proposed 10 research projects; 3) Summer Internship -experiential learning at multi agencies to pursue the selected research projects; and 4) Communication, leadership development and career advising.3. Mentoring Plan - Mentors are multidisciplinary, across Federal, State government agencies, high education, and diverse. Mentoring activities are streamlined via integrated hands-on experience of cutting-edge geospatial data science skills, project-oriented training on science and geospatial-data-science application, intern experiential learning on critical thinking and problem solving, and seminars on leadership, communication, and career planning. Case studies designed for the research projects will apply real research data into the geospatial analyses.4. Evaluation - Strategies: An external evaluation will document the project's objectives and serve as a foundation for assessing the project's impact in meeting the identified research needs within the scope of USDA priorities. A Process-Outcome Evaluation Methodology using formative and summative assessment tools will be followed to: 1) Identify key processes related to the accomplishment of each proposal objective, and 2) Measure the extent to which each of the objectives has been accomplished.