Soil quality indices based on long‐term conservation cropping systems management

Abstract

The Soil Management Assessment Framework (SMAF) may provide insight into how conservation practices affect soil quality (SQ) regionally. Therefore, we aimed to quantify SQ in a long‐term (15‐yr) crop rotation and bio‐covers experiment under no‐tillage using SMAF. Main effects were cropping rotations of soybean [Glycine max (L.) Merr.], corn (Zea mays L.), and cotton (Gossypium hirsutum L.). Split‐block bio‐cover treatments consisted of winter wheat (Triticum aestivum L.), Austrian winter pea (Pisum sativum L. sativum var. arvense), hairy vetch (Vicia villosa Roth), poultry litter, and fallow (control). Seven SQ indicators—soil pH, total organic carbon (TOC), bulk density (BD), soil extractable P and K, electrical conductivity (EC), and sodium adsorption ration (SAR)—were scored using SMAF algorithms, and investigated individually and as an overall soil quality index (SQI). Simple linear regressions were performed between SQI and crop yields. Differences (p < .05) in SQI within rotations varied when analyzed across and by depth. Overall, cotton–corn and/or continuous corn had greater SQI than soybean‐based rotations. Poultry litter had the greatest TOC, pH, K, and BD scores at the 0‐ to 15‐cm soil depth, and the lowest SQI. Reductions in SQI within bio‐covers were linked to P scores. A positive relationship was found between SQI and cotton yield at the 15‐ to 30‐cm soil depth (R2 = .48; p < .05). Investigating SMAF scores individually and separately per depth addresses the effects of long‐term conservation practices on SQ. Overall, SMAF can be used to develop best management practices and nutrient management strategies.

Soil quality indices as affected by long‐term burning, irrigation, tillage, and fertility management

“…No relationships were identified between simple addition SQI and wheat or soybean yields obtained between 2013 and 2018 ( p > .05). The lack of correlations was probably a result of the overall reduced variation in SQI values across treatments, suggesting that the differences in SQ, even after more than 16 complete cropping cycles, were not enough to explain the variation in crop productivity (Amorim et al., 2020b). Moreover, the high‐residue treatment had a positive impact on wheat yield (Table 6) but had a negative impact on soil pH, P, and K scores, contributing to a reduced SQI under NT–high‐residue systems.…”

“…The SOC scoring curve has an upper asymptotic form, as soils with increased SOC are more likely to perform their agronomic and environmental functions better (Wienhold et al., 2008). Soil organic C scores usually have lower values than physical and chemical indicators (Amorim et al., 2020b; Mbuthia et al., 2015; Karlen et al., 2013), suggesting that physical and chemical properties are more easily managed towards optimum values or ranges than SOC, but are less dynamic than biological properties (Ashworth et al., 2014). Moreover, these results indicate that CA practices that increase C retention in soils should be prioritized in long‐term cropping systems to improve SQ (Reeves, 1997).…”

“…Soil quality indicators are soil properties that are sensitive to management‐induced changes and reflect functions and ecosystem services (Andrews & Carroll, 2001; Wienhold, Karlen, Andrews, & Stott, 2009). For instance, biological indicators such as SOC, microbial biomass C, and enzyme activity (Mbuthia et al., 2015; Nakajima, Shrestha, & Lal, 2016), and chemical indicators such as P and K (Amorim et al., 2020b; Karlen, Cambardella, Kovar, & Colvin, 2013) are sensitive to changes induced by long‐term management practices, and reflect the performance of soils for sustained crop productivity. The integration of individual soil indicators into an overall SQ index (SQI) can provide an overview of management practices at a regional scale and may assist land managers in decision‐making processes with respect to land use or function as a guide towards specific management goals (Amorim et al., 2020a; Karlen et al., 2006).…”

“…The Soil Management Assessment Framework (SMAF) (Andrews, Karlen, & Cambardella, 2004) is an example of a SQ evaluation tool and has been successfully applied to investigate the impacts of long‐term conservation practices on SQ in numerous settings (Veum et al., 2015; Cherubin et al., 2016b; Amorim et al., 2020a; 2020b; Karlen, Veum, Sudduth, Obrycki, & Nunes, 2019). Initially, a minimum dataset with soil biological, physical, and chemical indicators is defined, which can be obtained through principal component analysis (PCA) or expert knowledge (Andrews & Carroll, 2001; Cherubin et al., 2016a).…”

Microbiological Study in Petrol-Spiked Soil

“…According to Nesme [ 15 ], one gram of soil can provide a habitat for over 10,000 various bacterial species. However, the assessment of soil ecosystem functioning is usually based on the physical soil indicators related to its texture, aggregation, porosity, and humidity [ 16 , 17 , 18 , 19 ], as well as the chemical ones, including the contents of organic carbon [ 20 , 21 ], total nitrogen [ 22 ], available phosphorus and potassium [ 23 , 24 ], and also soil pH value [ 25 , 26 ]. The methods used for soil quality assessment usually take no account of the microbiological processes ongoing in the soil, such as e.g., ISO standards [ 27 ].…”