Agricultural Resilience Under Synergistic Compensation Policies: A System Dynamics Study of Nenjiang, Heilongjiang Province, China

Policies designed to enhance agricultural resilience may produce unintended trade-offs among ecological, industrial, and social subsystems due to resource competition, structural constraints, and cross-subsystem feedback. This study conceptualizes these unintended effects as a “resilience compensation trap.” Taking Nenjiang City, Heilongjiang Province, China, as a case study, we integrate social–ecological systems theory with system dynamics modeling to examine the evolution of agricultural resilience from 2015 to 2035 under five scenarios: baseline development, ecological priority, industrial upgrading, talent revitalization, and comprehensive optimization. The results show that overall agricultural resilience increases slowly under the baseline scenario. Industrial upgrading raises overall resilience to 16.43 in 2035, representing an increase of 60.92% relative to the baseline, but reduces ecological resilience by 26.94%, thereby producing a clear cross-subsystem compensation effect. By contrast, the comprehensive optimization scenario increases overall resilience to 18.07, 76.98% above the baseline, while reducing conflicts among the three subsystems. These results indicate that single-objective interventions may activate negative feedback that offset their intended benefits. By operationalizing absorptive, adaptive, and transformative capacities as interacting variables and feedback loops, this study provides a process-based explanation of agricultural resilience trade-offs. The findings further highlight the importance of coordinated ecological, industrial, and social policies.