Developing soil health scoring indices based on a comprehensive database under different land management practices in Florida

Abstract A standardized soil health scoring system would be a beneficial tool for accessing and interpreting the status of soil health in Florida. However, because of the climate variability and diverse soil types, a soil health soring function designed in one location may not be useful for other places. In this study, we focused on developing scoring functions for Florida soil using a soil health indicator database under different land management practices across Florida. A soil health scoring index for 11 soil health indicators was calculated for 398 soil samples using comprehensive assessment of soil health (CASH), linear or nonlinear scoring function, and additive and weighted‐additive methods. Based on communality and weights of total data sets (TDS), Mehlich‐3 phosphorus (M3P) contributed the most, whereas pH contributed the least to the indices. The nonlinear scoring function had higher scores than other scoring functions. Only mixed cropping systems had significant changes in soil health indicators before and after treatment. The principal component analysis (PCA) showed that OM and M3P had the highest loading values compared with other indicators. Therefore, OM and M3P need to be considered if minimum number of indicators is to be measured while examining soil health indices pertinent to Florida soil types and land management practices. Overall, the findings of this study provide a foundation for creating and enhancing soil health indices in Florida.

Abstract licence: CC BY-NC-ND

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