BIG DATA ANALYTICS SHOW HUGE PROMISE TO ADVANCE AGROECOLOGICAL AND NATURAL RESOURCES MANAGEMENT BY UNCOVERING HIDDEN RELATIONSHIPS BETWEEN HUMAN, AGRICULTURAL, AND NATURAL SYSTEMS FROM VAST AND DIVERSE DATASETS. HOWEVER, UTILIZING ANALYTICS TO STUDY AGROECOSYSTEM DYNAMICS AND DEVELOP DECISION-SUPPORT PLATFORMS REMAINS A SIGNIFICANT CHALLENGE FOR THE AGRICULTURAL AND ENVIRONMENTAL MANAGEMENT COMMUNITIES. THE OVERALL GOAL OF THIS PROJECT IS TO ADDRESS THIS ANALYTICAL BOTTLENECK WITH THE DEVELOPMENT OF AN OPEN-ACCESS AND READILY USEABLE PACKAGE OF NOVEL COMPUTATIONAL TOOLS (CULTIVATR) THAT WILL ENABLE USERS TO CULTIVATE THEIR AGROECOLOGICAL DATA TO GENERATE PREDICTIVE DATA-DRIVEN DECISION SUPPORT TOOLS. SPECIFIC PROJECT OBJECTIVES INCLUDE: (1) IDENTIFY STAKEHOLDER PRIORITIES AND CURRENT KNOWLEDGE GAPS IN DECISION-SUPPORT CAPABILITIES; (2) DEVELOP AND APPLY CULTIVATR FUNCTIONS IN R TO CREATE AN OPEN-ACCESS DATA-DRIVEN DECISION-SUPPORT TOOL THAT ADDRESSES STAKEHOLDER NEEDS BY BLENDINGFLEXIBLE STATISTICAL, MACHINE LEARNING, DATA MANAGEMENT, AND HIGH-PERFORMANCE COMPUTING APPROACHES; AND (3) EXTEND THE DATA ANALYTICS PLATFORM TO OTHER AGRICULTURAL AND ENVIRONMENTAL SYSTEMS THAT HAVE EXTENSIVE OBSERVATIONAL DATASETS AND DECISION-SUPPORT NEEDS IN ORDER TO VALIDATE CULTIVATR'S TRANSFERABILITY AND SCALABILITY. THIS WORK WILL BE CARRIED OUT BY A MULTIDISCIPLINARY TEAM OF RESEARCHERS WHO HAVE EXPERTISE IN DATA ANALYTICS, STATISTICAL MODELING, GEOSPATIAL AND TEMPORAL ANALYSIS, INTEGRATED MODELING, AND AGROECOSYSTEM, FOOD, AND NATURAL RESOURCE MANAGEMENT.