**AWARDS ISSUED PRIOR TO JANUARY 20, 2025, WERE FUNDED UNDER PREVIOUS ADMINISTRATIONS AND MAY NOT REFLECT THE PRIORITIES AND POLICIES OF THE CURRENT ADMINISTRATION.** ADVERSE WEATHER CONDITIONS ASSOCIATED WITH A CHANGING CLIMATE POSE SERIOUS CHALLENGES TO PRODUCTIVITY OF SIMPLIFIED AGRIFOOD SYSTEMS. WE WILL USE A DATABASE OF LEGACY DATA FROM 21 LONG-TERM CROPPING-SYSTEMS EXPERIMENTS IN NORTH AMERICA TO ADDRESS KNOWLEDGE GAPS ABOUT ROTATIONAL DIVERSITY AS A CLIMATE ADAPTATION STRATEGY. THIS UNIQUE DATABASE, BUILT BY THE DRIVES PROJECT (DIVERSE ROTATIONS IMPROVE VALUABLE ECOSYSTEM SERVICES), PROVIDES A ROBUST RESOURCE FOR EXPLORING ROTATIONAL DIVERSITY EFFECTS ON CROPPING SYSTEM PERFORMANCE OVER A WIDE GEOGRAPHIC AND TEMPORAL RANGE. WE WILL QUANTIFY THE BENEFITS AND TRADE-OFFS OF CROP ROTATIONAL DIVERSITY UNDER ADVERSE WEATHER CONDITIONS BY EXAMINING KEY ASPECTS OF VULNERABILITY--I.E., EXPOSURE, SENSITIVITY, POTENTIAL IMPACTS, AND ADAPTIVE CAPACITY--SEPARATELY AND TOGETHER. WE WILL USE MULTILEVEL BAYESIAN STATISTICAL MODELING TO EVALUATE IF INCREASING CROP ROTATION DIVERSITY: (1) REDUCES NEGATIVE IMPACTS OF ADVERSE WEATHER BECAUSE CROPS DIFFER IN SENSITIVITY AND EXPOSURE TO WEATHER EVENTS; (2) IMPROVES PRODUCER ECONOMIC STABILITY AND ADAPTIVE CAPACITY DUE TO DIFFUSED RISK OF VOLATILITY IN YIELDS, CROP PRICES, AND INPUT COSTS; AND (3) IMPROVES NUTRITIVE OUTPUT FOR PEOPLE DUE TO DIFFERING NUTRIENT PROFILES AMONG CROPS. OUR BAYESIAN APPROACH ALLOWS US TO INCORPORATE PRIOR SCIENTIFIC KNOWLEDGE AND PROVIDES IMPORTANT INFORMATION ABOUT PARAMETER UNCERTAINTY, ALLOWING US TO EVALUATE THE RELIABILITY OF STATISTICAL INFERENCES FROM VARYING EXPERIMENTAL DESIGNS. OUR PROJECT ADDRESSES THE FOUNDATIONAL KNOWLEDGE PROGRAM AREAS CONDUCT SYNTHESES OF EXISTING DATA TO DERIVE GENERAL PRINCIPLES ABOUT PERFORMANCE OF AGRICULTURAL PRODUCTION SYSTEMS, AND INVESTIGATE HOW DIVERSIFICATION OF CROPPING SYSTEMS AFFECT OUTCOMES BENEFICIAL TO SYSTEM RESILIENCE.