Responses of soil health to seasonal change under different land cover types in a sub-tropical preserve ecosystem.

In subtropical preserve ecosystems, natural factors combined with anthropogenic activities have led to significant seasonal changes, including distinct dry and rainy seasons. These changes can potentially impact soil health indicators, which are keystone properties that control ecosystem services across terrestrial landscapes. Few studies have evaluated the impact of seasonal changes on soil health within non-agronomic landscapes, such as preserves. As part of this study, we collected topsoil samples (0-15 cm) from twenty-three land cover types within a 109 km² preserve in central Florida during two different seasons (dry and wet) to advance the understanding of how soil health responds to seasonal changes and to explore the environmental factors controlling soil health within non-agronomic landscapes. Ten soil indicators were analyzed and incorporated into the total dataset (TDS). From the TDS, a minimum dataset was derived using Principal Component Analysis, which was then used to calculate the Soil Health Index (SHI) for soil health assessment. Our findings showed that changes in soil indicators, their relationships, and the SHI across seasons depend on land cover type. Based on soil health classification grades, soil health status either improved, declined, or remained constant between seasons, depending on land cover type. The regression analysis of eight selected environmental factors, such as soil profile moisture (SPM), surface soil wetness (SSW), precipitation (P), soil temperature (T), elevation (El), slope gradient (S), global horizontal irradiance (GHI) and surface albedo (ALB), showed that only slope gradient significantly explains variations in SHI during wet season, whereas other environmental factors do not show significant explanatory power for SHI variations in either dry or wet season. These findings highlight the dominant influence of slope gradient on soil health within non-agronomic landscapes, while indicating that other evaluated environmental factors may have limited relevance in this context. Furthermore, the non-significant findings among soil indicators across seasons may be attributed to the study's small sample size (i.e., three replications), a limitation stemming from constrained funding. This highlights the importance of future research incorporating larger sample size to validate the findings of this study.