Biological Soil Health and Water Quality in Sustainable Agroecosystems

Soil property comparison

The quantification of soil biogeochemical properties by management system indicated that forested systems were found to be significantly different from the agriculturally managed systems. Between the conventional and soil health managed systems, few differences were found (Table 1). Within these comparisons, soil indicators were also analysed by depth. In the topsoil depths (05-cm and 5-15cm), no significant management response was observed in between the two agricultural systems. The subsoils saw few significant indicators in the soil health and conventional systems in inorganic N and P indicators. Notably, no distinct pattern could be found for median value or variability of indicators when comparing the three management styles.

Additionally in this analysis, we looked at the how the commonly referenced soil health indicators were impacted by management practices including soil organic carbon (SOC), soil organic matter SOM, organic nitrogen, and microbially active carbon (MAC). Percentages presented are compared to conventionally managed indicator values. Our results showed that SOM and MAC were significantly higher in forested systems (111% SOM and 266% MAC), while organic N and SOC values alternated in pattern with forested systems being significantly different.

Table 3. Tukey test p-value of management comparisons showing only indicators with significant comparisons. Values that were not found to be significant were left blank. Values are rounded to two decimal points.

Overall, management practice did not significantly affect biological community structure (Figure 1). While forest systems were found to have twice the total biomass of agroecosystems, all three systems have similar community structure. The greater biomass observed in the forest (94%) systems might be attributed to the time and field conditions of sample collection. Since samples were obtained in the late fall after cash crops were harvested, there is reason to believe that leaflitter and live root structures in the forest systems fostered the growth of microbial communities while the agroecosystems were fallow or just seeded. A significant indicator that stood out in the PLFA analysis was rhizobia biomass. Rhizobia was only found in the 5-15 cm forest systems for each region and the 0-5 cm north-central forest system. The lack of nitrogen fixing microorganisms is a great concern for continued soybean growth in a conventional corn-soy crop rotation with no nitrogen fixing. Without rhizobia, the system is dependent on biological nitrogen fixation from a variety of gram-negative bacteria species. Gram-negative bacteria were found to be most prevalent in the FST (146%) systems followed by SHP (12.6%) and then CFP systems.

The enzyme activity analyses found that the forest systems have significantly more NAG (65%) than the agroecosystems. BG followed a similar pattern in the north-central and north-west regions but was not significant in the south-central region. Enzyme activities were highest in the forest systems but alternated in the soil health (-6.2% NAG , -.4% BG) and conventional system.

Indicator Relations

                To see how indicators interacted with each other, we ran NMDS ordnination plots with Bray-Curtis corrections and correlation plots to identify any potential relationships. Haney, PLFA, and a combined PERMANOVA were utilized at each depth to show the effects of management (separately and together) on soil tests. Using PERMANOVAs, management was found to be significant for each soil test (Table 2). These results also show the significance found with the ANOVA tests with forest systems appearing to separate from the agroecosystems. While significance was found, the NMDS axis’ values range from -0.25 to 0.25 for each plot indicating that ordination had little deviation. The 0-5 cm and 5-15 cm plots clearly show a correlation of indicators with vector clusters of the biomass and phosphorus indicators.

Table 2. One-way PERMANOVA results showing the effect of management on Haney, PLFA, and combined indicator composition.

 Region Specific Comparisons

                While the aforementioned linear model factors in region as a covariate, it is plausible that this model fails to account for all the differing environmental and physical factors that can affect soil health indicators. The soil indicator results in the north-central region displayed the hypothesized relationship values with forest > soil health > conventional managed systems. Biological indicators in the forested system were significantly different compared to the agricultural systems in 0-5cm and 5-15cm depths.  Additionally in 5-15cm, about half of the total indicators were significant different between SHP and conventional systems. Although this pattern of significance seems promising, the median values for these biological indicators do not display the expected distribution associated with a healthy community. The north-west region has more variation in the 0-5cm depths when observing C, N, and P indicators. However, this region was found to have fewer significantly different indicators when comparing agricultural managed systems. Finally, only twelve of the forty-eight indicators were found to be significantly different in the south-central region. These significant indicators did not show any discernible pattern across the three management comparisons in either median distribution or Dunn’s results.

Conclusion

The effect of long-term management practices on soil health were found to be regionally specific and limited, contrary to the hypothesis. Relatively few differences were observed between long-term soil health farming and long-term conventional farming systems for soil health indicators. The forested systems displayed significant differences in various soil health indicators compared to the two agroecosystems. Furthermore, long-term soil health management did not lead to significant differences in key soil health metrics (SOC, OM, and N). When looking at the PLFA analysis, the forested systems were clearly separated from the agricultural systems by PLFA and enzyme indicators. The microbial community in forested systems was twice as large as the two agroecosystems, but community compositions between the three systems were not significantly different. Regionally, long-term soil health managed systems were statistically more distinct from the conventional systems compared to the combined comparison. This demonstrates that climate, soil type, and location have unique effects on soil health.