A Principal Component Analysis-Based Farm Adaptive Capacity Index for Assessing Agricultural Resilience Across Maryland Counties.
Description
This study hypothesized that Maryland counties with greater human, financial, and physical capital would have higher farm adaptive capacity and be better able to respond to environmental, climatic, and economic challenges. County-level data were obtained from the USDA Census of Agriculture for 2012, 2017, and 2022. Seven indicators were selected to represent adaptive capacity: Average Years Working on Farm, Hired Farm Labor, Farm-Related Income, Net Cash Farm Income, Federal Government Payments, Irrigation, and Machinery and Equipment Assets. These variables capture the knowledge, financial resources, labor, and infrastructure available to support agricultural adaptation. A Farm Adaptive Capacity Index (FACI) was developed using Principal Component Analysis (PCA), which combined the indicators into a single measure of relative adaptive capacity. Higher FACI scores indicate greater access to resources that support adaptation and recovery. Results showed substantial variation among Maryland counties. Frederick, Carroll, Queen Anne’s, Cecil, and Baltimore counties consistently exhibited the highest adaptive capacity, while Calvert, Charles, Allegany, Garrett, and Somerset ranked among the lowest. Financial indicators, machinery and equipment assets, hired labor, and government payments were the strongest contributors to adaptive capacity, suggesting that economically stronger agricultural systems possess greater ability to adapt to changing conditions. Spatial patterns revealed clusters of higher adaptive capacity in north-central Maryland and parts of the Eastern Shore, while lower-capacity counties were concentrated in other regions. The findings indicate that adaptive capacity is unevenly distributed across Maryland agriculture, with lower-capacity counties potentially facing greater vulnerability due to limited financial and productive resources. The FACI is a relative measure of adaptive capacity rather than actual resilience outcomes. It can be used to identify capacity gaps, target resilience investments, guide Extension programming, and inform agricultural adaptation and policy decisions. Overall, the study demonstrates that access to human, financial, and physical capital is a key determinant of farm adaptive capacity in Maryland.
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Institutions
- University of Maryland Eastern ShoreMaryland, Princess Anne