摘要：Integrated crop-livestock systems can have subtle effects on soil quality over time, particularly in semiarid regions where soil responses to management occur slowly. We tested if analyzing temporal trajectories of soils could detect trends in soil quality data which were not detected using traditional statistical and index approaches. Principal component and cluster analyses were used to assess the evolution in ten soil properties at three sampling times within two production systems (annually cropped, perennial grass). Principal component 1 explained 33% of the total variance of the complete dataset and corresponded to gradients in extractable N, available P, and C : N ratio. Principal component 2 explained 25.4% of the variability and corresponded to gradients of soil pH, soil organic C, and total N. While previous analyses found no differences in Soil Quality Index (SQI) scores between production systems, annually cropped treatments and perennial grasslands were clearly distinguished by cluster analysis. Cluster analysis also identified greater dispersion between plots over time, suggesting an evolution in soil condition in response to management. Accordingly, multivariate statistical techniques serve as a valuable tool for analyzing data where responses to management are subtle or anticipated to occur slowly.
