Grazing lands can be considered a conservation land use providing value to farmers and society. An underappreciated value of these lands may be in C and N storage and cycling. However, soil organic C (SOC) and total soil N (TSN) storage under humid-temperate zone pastures have not been well characterized. A survey of 31 farms in Virginia USA characterized SOC and TSN depth distributions under a diversity of grassland management scenarios, as well as in comparison with long-term no-till cropland and woodland uses on the same farms. Root-zone enrichment calculations separated management-controlled SOC and TSN stocks from a baseline condition characterized at 30-cm depth. Total stock of SOC at 0–30-cm depth varied from 46 to 88 Mg C ha⁻¹ (5%–95% range from 304 soil profiles) across all land uses. Root-zone enrichment of SOC was maximized under mature pastures (≥20 years old) at 38.3 ± 1.6 Mg C ha⁻¹, which was not different from that under woodland (39.8 ± 1.2 Mg C ha⁻¹), but was greater than under no-till cropland (28.3 ± 1.3 Mg C ha⁻¹) and conventional-till cropland (15.1 ± 5.1 Mg C ha⁻¹). Root-zone enrichment of TSN was optimized at stocking rate of ~1 Mg live weight ha⁻¹, but was not affected by stocking method, N fertilization history, or low levels of hay feeding. These results suggest that grazed pastures in Virginia are storing significant amounts of SOC and TSN, with at least half due to management-induced compared with pedogenic-controlled accumulation.

1 INTRODUCTION

Soil organic carbon (SOC) is a key indicator of soil health (Lorenz et al., 2019), as it drives delivery of numerous ecosystem services (Franzluebbers, 2010c; Sollenberger et al., 2019), including the supply of nutrients to plants (Farmaha et al., 2022; Ghimire et al., 2018), facilitates infiltration and storage of water in soil (Franzluebbers, 2022c; Libohova et al., 2018), provides habitat and energy to foster soil biodiversity (Crotty et al., 2015; Viruel et al., 2022), and offers resiliency to soil and plant production potential despite climatic perturbations (Liu & Basso, 2020; Minasny et al., 2017). Ultimately, SOC is an important regulator of the global C cycle, being both a source of greenhouse gas emissions from soil respiration and a sink of emissions through soil organic matter formation (Chang et al., 2021; Don et al., 2009; Scurlock & Hall, 1998). Although many studies rightfully focus on SOC dynamics, the contribution of nitrogen (N) to soil organic matter formation and biological activity may be equally important. Therefore, total soil N (TSN) should be investigated simultaneously, especially since C:N ratio can be a key indicator of ecological status and function (Mosier et al., 2021).

Pasture and rangeland in the United States occupies 177 Mha, or 49% of all farmland (USDA-NASS, 2023). In the 26 states east of the Mississippi River, pastureland occupies 13.4 Mha, or 18% of all farmland in the region. Virginia has 1.0 Mha of pastureland, which is 33% of all farmland in the state.

Soil organic C and TSN under grazing lands in the eastern US have not been well characterized under the wide diversity of environmental, edaphic, socio-economic, and historical management conditions present (Sollenberger et al., 2012), despite the prevalence and ecological impacts of grazing lands throughout the region (Sanderson et al., 2011). Significant SOC accumulation (~0.8 Mg C ha⁻¹ yr⁻¹) can be achieved with conversion of conventional-till cropland to pastures in the southeastern US region (Franzluebbers, 2010a). However, rates of SOC and TSN accumulation appear to be non-linear, as larger increases occur early in pasture development but shifting towards smaller increases over time as soil becomes steadily enriched (Franzluebbers et al., 2012; Franzluebbers & Stuedemann, 2010). Grazing of mixed bermudagrass-tall fescue pastures continuously stocked to maintain at least 1.5 Mg ha⁻¹ of residual forage mass had greater SOC and TSN accumulation rates in surface soil compared with unharvested management or frequent haying (Franzluebbers & Stuedemann, 2010). Nitrogen fertilization of tall fescue (Schedonorus arundinaceus [Schreb.] Dumort.) pastures led to significant SOC and TSN accumulation due to stimulation of plant productivity (Franzluebbers, 2010b), but there may be a steady-state balance at maturation between soil N supply and pasture N demand. This balance may be achieved when nutrient export is limited with animal harvest and losses to the environment (i.e. runoff, leaching, or gaseous emission) are minimized (Franzluebbers et al., 2018; Silveira et al., 2013).

Impacts of stocking rate on SOC and TSN sequestration have received relatively little attention, likely due to resource constraints required to conduct long-term trials, so data are relatively sparse. In a 5-year evaluation of two stocking rates in Georgia along with unharvested and frequent hay harvest of ‘Coastal’ bermudagrass (Cynodon dactylon [L.] Pers.) to extend the boundaries of forage utilization, SOC content was maximized at ~1.5 Mg live weight ha⁻¹ (Franzluebbers, 2010b). In southcentral Texas, SOC content was reduced with high stocking rate (5–7.4 cow-calf pairs ha⁻¹) compared with low stocking rate (2–2.5 cow-calf pairs ha⁻¹) when grazed for 9 of 12 months on bermudagrass-ryegrass (Lolium multiflorum Lam.) pastures for 32 years (Wright et al., 2004). Compared with no grazing, moderate grazing of pastures in Florida led to greater SOC storage (Gomez-Casanovas et al., 2018). Therefore, in aggregate these studies suggest that moderate stocking rate will optimize SOC storage.

Impacts of stocking method on forage production and livestock performance have been extensively studied (Rouquette et al., 2023; Sollenberger et al., 2012). However, impacts of stocking method on SOC and TSN sequestration have been rarely studied in randomized, replicated trials due to the need for long-term investigations that can be resource intensive. Therefore, investigations of stocking method on soil responses have been typically from paired-farm approaches (Mosier et al., 2021; Teague et al., 2011). Despite a general lack of quantitative information on soil changes with stocking method, robust debate continues about the ecological merits and outcomes of rotational stocking, particularly on soil organic matter changes inferred from changes in nutrient distribution on the landscape and forage utilization and productivity (Briske et al., 2011; Rouquette et al., 2023; Teague & Kreuter, 2020). Paired farm approaches to stocking method evaluation have resulted in greater observed SOC stock under rotational than continuous stocking in Texas (Teague et al., 2011), in Virginia (Conant et al., 2003), and a group of southeastern US states (Mosier et al., 2021). However, no differences in SOC and TSN stocks were observed after a few years from converting continuously stocked native grassland to rotational stocking in Oklahoma (Franzluebbers et al., 2019). In contrast, SOC stock change of 8.0 Mg C ha⁻¹ yr⁻¹ was asserted in an unreplicated chronosequence of management-intensive rotational stocking of newly established cool-season pastures under irrigation following conventional-till cropland in Georgia (Machmuller et al., 2015). Critique of the types of soils selected in this study and reanalysis of data using a root-zone enrichment calculation approach suggests that SOC sequestration rate could have been lower than reported. A management-intensive grazing system with multiple livestock species in Georgia had SOC stock change of 2.3 Mg C ha⁻¹ yr⁻¹ from a chronosequence evaluation on a single farm (Rowntree et al., 2020), but limited sampling of a selected few pastures was a methodological constraint. As well, SOC sequestration rate was estimated as 3.6 Mg C ha⁻¹ yr⁻¹ with adaptive multi-paddock grazing (rotational stocking) of a mixed cool-season pasture in Michigan (Stanley et al., 2018). Such high rates of SOC sequestration with rotational compared with continuous stocking contrast with other studies (0.41 Mg C ha⁻¹ yr⁻¹, Conant et al., 2003; 0.48 Mg C ha⁻¹ yr⁻¹, Mosier et al., 2021). The emergence of SOC sequestration data from limited farm pairs or over short evaluation periods without a counterfactual control suggests that more research is needed to bolster interpretations, as some estimates of SOC sequestration appear unrealistic.

Although SOC has been measured in numerous research studies, its depth distribution on private farms has not been extensively studied. A wealth of information could be obtained from farmers who have historical records of management. In fact, when sampling soil health conditions using a variety of soil physical, chemical, and biological properties and processes across 111 field trials in the southeastern US, SOC concentration in the surface 10 cm was 37% greater on private cropland farms than on research stations (Franzluebbers, 2020). The growing interest and implementation of various conservation and agroecological approaches (sometimes referred in popular press and trade magazines as ‘regenerative agriculture’) throughout the US suggest that SOC on private farms may be significantly different than reported in research-station trials, but further testing is needed. The diversity of management conditions deployed by farmers within a region could also reveal how management interacts with the environment to influence SOC and TSN sequestration. Use of a root-zone enrichment sampling approach could provide robust estimates of change in SOC, TSN, and other properties with adoption of conservation management approaches, especially when matched with neighbouring land uses (Franzluebbers, 2022a). Even when large differences in soil type exist among farms, the root-zone enrichment approach can lead to consistent interpretations of how management influences SOC and TSN accumulation because of the accounting of unique baseline conditions (Franzluebbers, 2023).

The objective of this study was to survey a diversity of pasture-based livestock farms throughout Virginia to determine root-zone enrichment of SOC and TSN. The root-zone enrichment approach was used to separate pedogenic-controlled SOC and TSN concentrations in the soil profile from those of management-controlled SOC and TSN concentrations that predominate in the surface 0–30-cm depth, i.e. the primary root zone. Additional land uses on the same farms, particularly undisturbed woodland and no-tillage cropland if available, were also sampled for comparison of land-use effects on root-zone enrichment of SOC and TSN.

2 MATERIALS AND METHODS

2.1 Site selection

A total of 31 farms in the central to western part of Virginia were selected for this on-farm evaluation of land uses and management (Figure 1). Farms were identified through a combination of volunteer agreement and additional requests via agricultural advisors. Following a set of soil health sessions at the winter conference of the Virginia Forage and Grassland Council, 21 farmers volunteered to participate in the sampling. At each of the soil health sessions during the week of 17–21 January 2022, one or two participant farmers near each of the four conference locations (Wytheville, Chatham, Rapidan, and Weyers Cave) were recruited by Virginia Cooperative Extension, in which both grazed pastures and no-till cropland were present (total of 6 farms). An additional four farmers were arranged by other agricultural advisors in the state to increase geographic distribution. The common characteristic among farms was grassland management. Almost all farms had beef cow-calf herds, with three exceptions (one dairy only, one beef stockers only, one cropland only). Following informal agreements to participate, sampling ensued during the remainder of the winter/early spring with suitable weather. Selection of fields was agreed upon between the farmer and investigator to achieve a diversity of historical conditions. Targeted fields on each farm were three grazed pastures or hayfields, as well as three no-till cropland fields and one to three separate woodland plots.

Details are in the caption following the image — **FIGURE 1**
Open in figure viewer PowerPoint

Geographical distribution of 31 farms sampled in Virginia.

2.2 Environmental conditions

Climatic conditions varied across the study area. Geographic coordinates (5th and 95th percentiles) were 36.72 to 38.75 °N, 77.97 to 81.21 °W, and 120 to 784 m above sea level. Farms were in the Southern Piedmont Major Land Resource Area (MLRA), Northern Piedmont MLRA, Southern Appalachian Ridges and Valleys MLRA, Northern Appalachian Ridges and Valleys MLRA, Southern Blue Ridge MLRA, and Northern Blue Ridge MLRA (USDA-NRCS, 2022). Mean annual temperature varied from 10.6°C near Wytheville to 13.7°C near Chase City and mean annual precipitation varied from 911 mm near Woodstock to 1201 mm near Charlottesville (1961–1990; worldclimate.com). Of the 304 soil profiles sampled, 77% were Ultisols in USDA Soil Taxonomy (85 Paleudults, 75 Hapludults, 63 Kanhapludults, 7 Fragiudults, 2 Endoaquults, 2 Rhodudults), 11% were Inceptisols (30 Dystrudepts, 1 Endoaquepts, 1 Eutrudepts), 10% were Alfisols (29 Hapludalfs, 1 Endoqualfs), and 3% were Mollisols (8 Hapludolls).

2.3 Management

Land use was broadly classified into conventional-till cropland, no-till cropland, grassland, and woodland in this study, but emphasis was on perennial grazing lands in the region. Most grassland swards were dominated by tall fescue, although significant orchardgrass (Dactylis glomerata L.), red clover (Trifolium pratense L.), white clover (Trifolium repens L.), and other naturalized annual and perennial species were also present in many cases. Management varied among farms and sometimes among fields within a farm, and this was characterized with a standardized query. Farmers were posed a series of standard management questions via Google Forms to describe conditions on the farm and specifically to those fields sampled on the farm. Of course, management on a farm may have varied over time as new information was processed and implemented into practice, so there are uncertainties associated with responses. These changes in management over time can confound soil responses, but this is a reality on many private farms. Therefore, the focus of the management history form was on those variables that were considered relatively stable or particularly prescient. To make the form simpler and easier to complete in a short period of time, pre-planned responses according to expected categorical ranges were posed for selection, although free responses were also allowed.

Livestock units were considered the equivalent of 454 kg in questions to farmers. The following contrasts and pre-planned responses were considered the most relevant to evaluate pasture management: (1) stocking rate (transformed into head ha⁻¹ from pre-planned answers of <1, 1, 1.1–2, 2.1–3, 3.1–4 acres cow⁻¹), (2) pasture age (1–5, 6–15, 16–30, 31–50, >50 years), (3) stocking method (based on frequency of livestock moves with pre-planned answers of none, seasonally, monthly, weekly, subweekly, daily), (4) N fertilizer rate (0, 1–56, 57–112, >112 kg N ha⁻¹ yr⁻¹), (5) hay feeding (farm level based on choices of 25–100, 101–200, 201–1000, >1000 grazeable acres and number of hay bales fed each year of <25, 26–100, 101–500, 501–1000, >1000; ratio transformed into Mg hay ha⁻¹), (6) organic amendment (none, occasionally, every year), and (7) forage utilization (grazed only, grazed + periodically hayed).

Cropland fields were mostly with minimal soil disturbance using chemical control of weeds and mostly managed with cover crops. Duration of no-till management was 37 ± 8 years. Crops were typically corn (Zea mays L.), soybean (Glycine max [L.] Merr.), and wheat (Triticum aestivum L.). Only a few cropland fields were managed traditionally with disk tillage, and those were primarily from one farm that grew tobacco (Nicotiana tabacum L.). Depth of soil tillage was 20–25 cm.

Woodlands were primarily hardwood farmstead areas that were matched with landscape position in the uplands, if possible, to avoid sediment deposition-prone areas. Typical woodland species included Acer, Carya, Fagus, Liquidamber, Pinus, and Quercus. Age of woodlands was not readily known, but in general many woodlands had standing trees with diameter at breast height > 30 cm. Selected thinning in the past would have occurred on some but not all woodlands.

2.4 Soil sampling and analyses

Soil was sampled from 304 profiles (186 under grassland, 66 under woodland, 48 under no-till cropland, and 4 under conventional-till cropland; Supplementary Table S1) on the 31 private farms during a 7-week period from 10 March to 29 April 2022. Within each field, a representative site ~50 m from entry was selected and marked with GPS coordinates to match with soil taxonomical description from SoilWeb (https://casoilresource.lawr.ucdavis.edu/gmap/). A second site ~50 m away from the first was sampled in grassland and no-till cropland. One to three sites were selected in woodland and conventional-till cropland in a similar manner.

At each sampling site, up to five cores were composited, i.e. in the center and at 4 cardinal directions at distances of 10 m from the central location. Most woodlands were an exception, in which a transect with cores separated by 10 m sampled along a walkable pathway. Soil at 0–10 cm depth was collected with a 4-cm-inside diameter push probe at each of the five coring locations after moving surface residue to the side by hand. Soil at 10–30 and 30–60 cm depths was collected with a 3.2-cm diameter auger using a battery-powered drill that deposited soil into a 7.6-L plastic bucket through a steel-flange-reinforced opening at the bottom. The bucket had a 10-cm pipe extending from the bottom that prevented surface soil from contaminating deeper soil drawn up to the bucket with the auger. All five coring locations were collected for the 10–30 cm depth and three coring locations were collected for the 30–60 cm depth. A total of 292–816 g dry soil (5%–95% range) was collected from each site and sampling depth. Soil was deposited into labelled paper bags in the field and dried in an oven at 55°C for ≥3 days until constant weight. Soil was passed through a screen with 4.75-mm openings. Stones and visible plant residues were removed before further processing. Coarse fragments (>4.75 mm) accounted for 1.5 ± 3.1% of the 0–10-cm depth. Surface residue from one 30-cm diameter ring was collected at each location, dried, weighed, and ground coarsely. A subsample was ground to <1 mm in a cyclone mill (Udy Corp., Fort Collins, CO).

A soil subsample ground to a fine powder in a ball mill for 1 min was analysed for total C and N with a Leco TruMac combustion analyser. Surface residue subsamples were also analysed for total C and N. Total C was assumed to represent SOC since pH was ≤7.0 for all but seven of the samples and was 7.1–7.2 in these cases. Across sites, soil pH was 6.0 ± 0.7 at 0–10-cm depth, 5.8 ± 0.6 at 10–30-cm depth, and 5.7 ± 0.7 at 30–60-cm depth.

Soil texture of the 0–10-cm depth was determined with a hydrometer for clay and with a sieve (0.053 mm openings) for sand. A 59-mL scoop of soil was shaken overnight (9–12 h) with 80 mL of 0.1 M Na₄P₂O₇ in a 125-mL plastic bottle and subsequent dilution in a 1-L sedimentation cylinder with deionized water, mixed thoroughly, and solution density recorded with a hydrometer at the end of 5 h of settling time along with a blank solution for every 24 samples. Soil and solution were poured over a screen with 0.053-mm openings to collect the sand fraction after washing with a stream of water. Sand-sized material that included particulate organic matter was transferred to a small jar and dried until constant mass (24 h past visual dryness) and mass recorded. Silt was calculated from the difference between unity and summed fractions of clay and sand. Mass of soil in the 59 mL scoop of soil was used to calculate sieved soil density. Sand concentration was 185–622 g kg⁻¹ (5–95% range), silt concentration was 166–535 g kg⁻¹, and clay concentration was 163–388 g kg⁻¹.

2.5 Calculations and statistical analyses

Stocks of SOC and TSN in the 0–30-cm depth were calculated from a non-linear mathematical expression of depth distribution of SOC and TSN concentrations and estimated bulk density using a pedotransfer function based on SOC concentration (Franzluebbers, 2023). The pedotransfer function was derived from Franzluebbers (2010a):

BD = 1.71 \cdot e^{(- 0.013 \cdot SOC)} .

in which, BD is bulk density (Mg m⁻³) and SOC is soil organic C (g kg⁻¹). Concentrations of SOC and TSN were fitted to a non-linear function dependent on soil depth, according to the descriptions provided in Franzluebbers (2021b):

SOC = A + B \times [1 - e^{(- b \times SD)}] .

in which, SOC is soil organic C (g kg⁻¹), A is SOC concentration deep in the profile without management influence (A ≥ 0 only), and B is the portion of SOC that accumulates at the soil surface and declines exponentially as a function of a rate constant (b, |cm|⁻¹) for a given soil depth (SD, |cm|). All nonlinear regressions were fitted to available data using SigmaPlot v. 14 (Systat Software Inc.). In cases where this equation produced an estimate of A < 0, A was set to 0 using a modified form:

SOC = B \times [1 - e^{(- b \times SD)}] .

Data for TSN concentration were fitted in the same manner as that for SOC. Coefficient of determination for non-linear depth distribution of SOC and TSN was 0.99 ± 0.04. These equations were used to produce estimates of SOC and TSN concentrations at 5-cm depth increments and contents at 0–5, 5–10, 10–15, 15–20, 20–25, and 25–30 cm depth increments. Summation of contents from these increments yielded the stocks of SOC and TSN within the surface 30-cm profile. Baseline SOC and TSN that was not affected by management was assumed as concentrations at 30-cm depth. Baseline SOC and TSN contents (0–30-cm depth) were calculated from concentrations at 30-cm depth (assumed baseline concentration) multiplied by estimated bulk density at 30-cm depth and this product projected across the entire 0–30-cm profile. Root-zone enrichments of SOC and TSN were calculated from the difference between total stock and baseline stock for each profile. In addition, SOC and TSN at 0–10-cm depth were combined with measured bulk density to calculate surface contents of SOC and TSN from direct measurement only.

Statistical distributions of SOC and TSN components within and across land uses were estimated as the 5%–95% range, interquartile range, median, and mean. Analysis of variance was conducted to test for the effect of land use on mean SOC and TSN stocks with farm and replicate field within a farm as blocking criteria. Means were separated using contrast statements as: (1) conventional-till cropland vs no-till cropland; (2) no-till cropland vs grassland: and (3) grassland vs woodland, which was along a gradient of conservation land use. Analysis of variance within the grassland dataset only was conducted for selected management factors on SOC and TSN stocks according to the pre-selected levels for each management factor. Replicate subsampling within a field was not considered a source of variation in the general linear model, which was performed with SAS v. 9.4 (SAS Institute Inc., Cary NC). Significance of variables was declared at α = .05.

3 RESULTS AND DISCUSSION

Across the 304 sampling sites on 31 farms in Virginia, SOC and TSN concentrations were greatest near the surface and declined with depth (Figure 2). Soil organic C was 29.6 ± 8.9 g kg⁻¹ (mean ± standard deviation) at 0–10-cm depth, 9.0 ± 3.5 g kg⁻¹ at 10–30-cm depth, and 4.7 ± 2.2 g kg⁻¹ at 30–60-cm depth. Total soil N was 2.47 ± 0.85 g kg⁻¹ at 0–10-cm depth, 0.81 ± 0.33 g kg⁻¹ at 10–30-cm depth, and 0.49 ± 0.22 g kg⁻¹ at 30–60-cm depth. Relative variation in SOC and TSN increased from near 30% at the surface to 45% at the lowest sampling depth. It is the natural variation in SOC and TSN with depth that is of prime importance for discerning how much organic matter can be considered influenced by relatively recent management, i.e. root-zone enrichment. Baseline SOC and TSN concentrations at 30-cm depth and below are assumed pedogenic-controlled concentrations, while concentrations in the upper 30 cm of soil are considered derived from a combination of (1) root-zone enrichment as a function of recent land use and management and (2) pedogenesis. Baseline SOC concentration at 30-cm depth varied from 3.2 g kg⁻¹ at the 5th percentile of values in this study to 10.6 g kg⁻¹ at the 95th percentile. Baseline TSN concentration at 30-cm depth varied from 0.30 to 1.05 g kg⁻¹ at the 5th and 95th percentiles, respectively.

The 5th and 95th percentile limits of SOC and TSN shown in Figure 2 suggest that soil types inherently rich in organic matter as indicated by elevated concentrations at 30-cm depth may have the capacity to store more SOC and TSN in the primary root zone than soil types inherently poor in organic matter. This was illustrated with greater root-zone enrichment of SOC (43.7 vs 26.5 Mg C ha⁻¹) and of TSN (3.14 vs 1.58 Mg N ha⁻¹) at 95th than at 5th percentiles, respectively. If only total stocks of SOC and TSN were calculated, then the difference between 5th and 95th percentiles would have been 48.6 Mg C ha⁻¹ (115% increase) and 4.77 Mg N ha⁻¹ (156% increase). However, root-zone enrichment differences between 5th and 95th percentiles were only 17.2 Mg C ha⁻¹ (65% increase) and 1.56 Mg N ha⁻¹ (99% increase). Therefore, it is argued that root-zone enrichment leads to a more reliable estimate of change in SOC and TSN stocks due to management influences than to the potentially confounding effects of pedogenic-controlled factors when considering total stocks only. Pedogenic-controlled factors can be quite large, as illustrated among the soils sampled in this study.

Concentrations of SOC and TSN at 30-cm depth are considered the bottom of the primary root zone. However, deep rooting of perennial grasses and trees might be thought to elevate concentrations at or below this boundary. Therefore, a paired approach among land uses was made across the numerous farms in this study to test the basic assumption of no difference in SOC and TSN concentration at 30-cm depth when using the root-zone enrichment concept. Across 9 farms with paired no-till cropland and grassland management, there was no difference (p = .54) in SOC concentration at 30-cm depth (6.3 vs 6.6 g kg⁻¹, respectively), nor that of TSN concentration at 30-cm depth (0.67 vs 0.72 g kg⁻¹, respectively). Within farms, SOC concentration at 30-cm depth was significantly greater (p ≤ .10) with no-till cropland than with grassland at 2 farms and was significantly lower with no-till cropland than with grassland at 1 farm. Total soil N concentration was significantly lower with no-till cropland than with grassland at the same farm, and there were no other differences in TSN concentration at 30-cm depth observed within individual farms. Across 27 farms with paired woodland and grassland management, there was no difference (p = .29) in SOC concentration at 30-cm depth (6.3 vs 5.8 g kg⁻¹, respectively), but there was a difference (p = .03) in TSN concentration at 30-cm depth (0.51 vs 0.60 g kg⁻¹, respectively). Within farms, SOC concentration at 30-cm depth was significantly greater with woodland than with grassland at seven farms and was significantly lower with woodland than with grassland at 2 farms. Total soil N concentration was significantly lower with woodland than with grassland at 6 farms and was significantly greater at 2 farms. Lower TSN concentration with woodland than with grassland was contrary to expectation of greater rooting depth with woody compared with herbaceous perennials, so the difference was more likely attributable to mismatch of pedogenic factors. This general lack of difference in SOC concentration at 30-cm depth among land uses was also observed among a diversity of studies that compared cropland with grasslands or woodlands (Franzluebbers, 2022b).

Predicted soil bulk density was strongly associated with measured soil bulk density at 0–10-cm depth (Figure 3). Deviations from measured values were mostly within 0.1 Mg m⁻³, although the few observations under conventional-till cropland had the greatest deviation of 0.3 Mg m⁻³. This larger difference with tilled cropland was likely due to tillage that occurred a few months prior to sampling. Prediction of bulk density was necessary due to the use of auger sampling at lower depths. Errors in prediction of SOC and TSN stocks could occur with use of predicted bulk density, but these errors should be considered random and not highly significant based on the random deviations shown in Figure 3. However, predicted bulk density was overall statistically greater (p = .01) than measured bulk density (1.17 vs 1.14 Mg m⁻³, respectively). This difference in bulk density could have led to an average difference in estimate of SOC and TSN stocks of 2.5%. Since root-zone enrichment is calculated from the difference in total minus baseline stocks, any small bias should be negated through the subtraction procedure. It should also be noted that measured soil bulk density has its own sources of error, mainly related to accurate sectioning at exactly 10-cm depth of the five cores, as well as pushing along rock fragments that can cause voids or compress soil in other cases.

Overall, the tests of assumptions presented here and in other studies (Franzluebbers, 2021a, 2021b, 2022a, 2022b, 2023) suggest that fair and reliable estimates of root-zone enrichment of SOC and TSN should have great value in assessing the effects of land use and management, particularly when assessing conservation-based strategies.

3.1 Land use

Total stocks of SOC and TSN at 0–30-cm depth were significantly affected by land use (Table 1). Although stock trends differentiated by land use were the same when computed using absolute stocks as when subtracting baseline conditions, there was greater likelihood of detecting significant differences when land use effects were calculated as root-zone enrichment. Therefore, baseline stocks of SOC and TSN were important factors to consider when calculating management-induced stock changes calculated as root-zone enrichment of SOC and TSN. As a progression from least to greatest conservation, root-zone enrichment of SOC was 87% greater when switching from conventional-till cropland to no-till cropland, 31% greater when switching from no-till cropland to grassland, and only 7% greater when switching from grassland to woodland. Root-zone enrichment of TSN was 2.2 times greater under no-till cropland than conventional-till cropland, 32% greater under grassland than under no-till cropland, and 30% lower under woodland than under grassland.

TABLE 1. Total, baseline, and root-zone enrichment stocks of soil organic C (SOC) and total soil N (TSN), surface residue C and N, and measured bulk density, SOC, and TSN at 0–10-cm depth as affected by land use across locations in Virginia.

Property	Conventional-till cropland		No-till cropland		Grassland		Woodland
Number of observations	4		48		186		66
Total stock of SOC (Mg C ha⁻¹)	51.5	NS	57.7	*	64.0	*	69.5
Baseline stock of SOC (Mg C ha⁻¹)	36.4	NS	29.3	NS	26.8	NS	29.6
Root-zone enrichment of SOC (Mg C ha⁻¹)	15.1	**	28.3	***	37.2	*	39.8
Stock of TSN (Mg N ha⁻¹)	4.74	NS	5.51	NS	5.93	***	4.62
Baseline stock of TSN (Mg N ha⁻¹)	3.64	NS	3.12	NS	2.76	†	2.40
Root-zone enrichment of TSN (Mg N ha⁻¹)	1.11	*	2.40	***	3.17	***	2.23
Surface residue C (Mg C ha⁻¹)	1.1	NS	2.9	NS	3.0	***	7.7
Surface residue N (Mg N ha⁻¹)	0.04	NS	0.12	*	0.15	***	0.22
Bulk density at 0–10-cm depth (Mg m⁻³)	1.15	NS	1.22	*	1.17	***	1.02
Soil organic C at 0–10-cm depth (Mg C ha⁻¹)	18.3	†	27.3	***	34.1	NS	35.0
Total soil N at 0–10-cm depth (Mg N ha⁻¹)	1.59	NS	2.51	***	3.07	***	2.16

Note: NS is not significant.
^† p ≤ .1;
* p ≤ .05;
** p ≤ .01;
*** p ≤ .001.

Surface residue C was not different between cropland types and grassland, but it was greater under woodland than all other land uses (Table 1). This difference in C content of surface residue could have been expected based on little soil disturbance and annual leaf and litter fall under woodland. However, the quality of surface residue was even more affected by land use. Surface residue N was greater under grassland than under cropland but was greater under woodland than all other land uses. However, C:N ratio of surface residue was 39.5 ± 5.0 (mean ± standard error) under conventional-till cropland, which was greater (p = .005) than under no-till cropland (24.8 ± 1.2). Surface residue C:N of no-till cropland was greater (p = .003) than under grassland (20.7 ± 0.6). Surface residue C:N under grassland was lower (p < .001) than under woodland (36.0 ± 1.1). Therefore, the lower surface residue C:N under grassland and no-till cropland would have been more likely to contribute to biologically available N release through mineralization than under woodland, despite the large mass of surface residues, as well as greater than under conventional-till cropland because of the low mass of residues. Levels of surface residue C and N under croplands in this study were similar to those across 25 research stations in North Carolina, but surface residue C was lower under grassland and woodland and surface residue N was lower under woodland than in the North Carolina study (Franzluebbers, 2023).

Measured soil bulk density at 0–10-cm depth was not different between conventional-till and no-till cropland but it was lower under grassland and woodland than under no-till cropland (Table 1). Bulk density was significantly lower under woodland than under grassland. Most of these effects could be attributed to differences in SOC concentration in the surface layer. Some of this effect may have also been due to the extent of tractor and livestock traffic that could have compressed surface soil (Franzluebbers & Stuedemann, 2008; Greenwood & McKenzie, 2001).

Measured SOC content at 0–10-cm depth was affected by land use: conventional-till cropland ≤ no-till cropland < grassland = woodland (Table 1). Measured TSN content at 0–10-cm depth followed the order: conventional-till cropland = no-till cropland < grassland > woodland. These trends were very similar to those observed for root-zone enrichment of SOC and TSN. The measured SOC content at 0–10-cm depth was positively associated with root-zone enrichment of SOC (r = .80, p < .001, n = 303). Similarly, measured TSN content at 0–10-cm depth was strongly associated with root-zone enrichment of TSN (r = .87, p < .001, n = 303). These associations may not be so surprising, given the strong influences of SOC and TSN concentrations at 0–10-cm depth on the final value of root-zone enrichment calculations. The calculated proportion of root-zone enrichment of SOC (0–30-cm depth) was 70 ± 5% from the 0–10-cm depth and 95 ± 2% from the 0–20-cm depth. However, calculations of root-zone enrichment account for baseline SOC and TSN concentrations throughout the 0–30-cm depth. Therefore, measured SOC and TSN contents at 0–10-cm depth do not account for this baseline condition that can cause misinterpretations of management influence when sampling soils from a diversity of landscapes among farms within a region or even within farms having natural soil variability. The ratio of measured SOC at 0–10-cm depth to root-zone enrichment was 0.76–1.26 (5–95% range) and of measured TSN at 0–10-cm depth to root-zone enrichment was 0.79–1.36.

Estimates of root-zone enrichment of SOC for conventional-till cropland in this study (interquartile range [IQR] of 7.3–17.5 Mg C ha⁻¹) covered the same range of 210 observations from various studies conducted around the world [IQR of 5.5–16.2 Mg C ha⁻¹; Franzluebbers, 2022b]. However, estimates of root-zone enrichment of SOC under no-till cropland in this study (IQR of 25.3–32.5 Mg C ha⁻¹) were considerably greater than for 270 observations from different places around the world [IQR of 8.8–21.8 Mg C ha⁻¹; Franzluebbers, 2022b]. Similarly, estimates of root-zone enrichment of SOC under grassland in this study (IQR of 33.1–41.9 Mg C ha⁻¹) were much greater than the relatively few (n = 88) observations from various regions [IQR of 13.1–26.3 Mg C ha⁻¹; Franzluebbers, 2022b]. Estimates of root-zone enrichment of SOC under woodland in this study (IQR of 35.4–44.9 Mg C ha⁻¹) elevated and narrowed the range of observations (n = 23) mostly from the Midwest US [IQR of 8.9–40.2 Mg C ha⁻¹; Franzluebbers, 2022b]. These ranges of root-zone enrichment of SOC were also similar to those found across 25 research station locations in North Carolina, at least for conventional-till cropland (IQR of 5.2–16.9 Mg C ha⁻¹) and woodland (IQR of 34.8–45.8 Mg C ha⁻¹) (Franzluebbers, 2023). However, root-zone enrichment estimates of SOC were generally greater in this Virginia study than in the neighbouring North Carolina study for no-till cropland (IQR of 16.9–26.6 Mg C ha⁻¹) and grassland (IQR of 23.5–37.0 Mg C ha⁻¹) (Franzluebbers, 2023).

Stock of TSN (0–30-cm depth) ranged from 3.19 to 7.87 Mg N ha⁻¹ (5%–95% range) in this study. Baseline stock of TSN was 32%–72% of TSN stock, amounting to 1.49 to 4.98 Mg N ha⁻¹ (5%–95% range). These total and baseline stock estimates were within the range of values across the southeastern US region using the same calculation approach (Figure 4). The current study contributed to 2% of the regional observations for conventional-till cropland (n = 192), 37% for no-till cropland (n = 131), 56% for grassland (n = 335), and 40% for woodland (n = 164) observations. The IQR distribution of root-zone enrichment of TSN under conventional-till cropland occupied 29%–78% of the distribution in Figure 4, i.e. a similar expected distribution despite the small sampling size. The IQR distribution of root-zone enrichment of TSN under no-till cropland from this study was 62%–86%, and therefore in the upper range of values from previous studies. A similar upward shift in distribution occurred under grasslands in this study (i.e. 42%–81%). Under woodland, the IQR distribution of root-zone enrichment of TSN was similar to distribution in other studies (i.e. 30%–79%). Within the IQR of root-zone enrichment values for TSN, there was clear separation of grassland (2.79–3.73 Mg N ha⁻¹) > no-till cropland (2.17–2.77 Mg N ha⁻¹) >conventional-till cropland (0.46–1.14 Mg N ha⁻¹). The IQR of root-zone enrichment of TSN under woodland (1.79–2.79 Mg N ha⁻¹) was not distinguishable from that under no-till cropland. Across a diversity of studies with similar land uses as in the current study, the IQR of root-zone enrichment of SOC was greater under grassland (13.1–26.3 Mg C ha⁻¹, n = 88) than under conventional-till cropland (5.5–16.2 Mg C ha⁻¹, n = 210), but the response under no-till cropland was intermediate between these extremes (Franzluebbers, 2022b). Therefore, the root-zone enrichment responses of TSN in this Virginia study provided greater clarity of long-term land use impacts on soil organic matter. This was the first opportunity to present root-zone enrichment of TSN with at least 100 observations in each land use.

3.2 Pasture age

Pasture age was a significant variable that affected stocks of SOC and TSN. Pasture age was classified into pre-planned levels of 1–5 years old (n = 6 fields), 6–15 years old (n = 12 fields), 16–30 years old (n = 16 fields), 31–50 years old (n = 15 fields), and >50 years old (n = 37 fields). The primary effect was that youngest pastures (1–5 years old) were lower in total and root-zone enrichment of SOC and TSN than older pastures (Figure 5). Stock of TSN was lower in 1–5-year-old pastures than in 6–15-year-old pastures (p = .02) and there were no differences among the older pasture classes. Root-zone enrichment of TSN was lower in 1–5-year-old pastures than in 16–30-year-old pastures (p = .005), and that of 6–15-year-old pastures was intermediate but not statistically different from younger (p = .14) and older pastures (p = .11). Older pastures were statistically greater in root-zone enrichment of TSN than in other land uses of conventional-till cropland, no-till cropland, and woodland.

Based on the regression in Figure 5, accumulation rate of root-zone enrichment of TSN was 183 kg N ha⁻¹ yr⁻¹ during the first 5 years, 98 kg N ha⁻¹ yr⁻¹ during 5–10 years of pasture development, 40 kg N ha⁻¹ yr⁻¹ during 10–20 years of pasture development, and only 5 kg N ha⁻¹ yr⁻¹ during 20–50 years of pasture development. These rates of TSN accumulation, at least initially, were greater in magnitude compared with rates across a greater geographical diversity of sites in Georgia, South Carolina, North Carolina, Virginia, and West Virginia, in which rates during the same time periods were calculated as 115, 70, 36, and 12 kg N ha⁻¹ yr⁻¹, respectively (Franzluebbers & Poore, 2021). In a similar manner, average rates of root-zone enrichment of SOC in the current study were 2.7, 1.8, 1.0, and 0.4 Mg C ha⁻¹ yr⁻¹ during periods of 0–5, 0–10, 0–20, and 0–50 years of pasture development, respectively. These rates of SOC accumulation were initially greater but later similar to those reported in the wider geographic region, in which rates during the same time periods were calculated as 1.9, 1.4, 0.9, and 0.4 Mg C ha⁻¹ yr⁻¹ at 0–5, 0–10, 0–20, and 0–50 years, respectively (Franzluebbers & Poore, 2021). The close correspondence between these two surveys of pastures in the region suggests that coefficients for soil C and N accumulation are realistic and practically significant across a diversity of farms.

Larger accumulation rates early in pasture development and smaller accumulation rates with pasture maturity are consistent with ecological theory that suggests significant opportunity to build soil organic matter from a depleted state, such as when following historical cropping with high soil disturbance to an elevated condition with pasture maturity (Li et al., 2018; Poeplau et al., 2011). Stabilization of soil organic matter contents after ~20 years of pasture development in these two studies indicates a new steady-state condition is generally achievable. It should be noted that steady-state is based on the general conditions from this study, and an elevated steady-state could be achieved with further improved management. Deviations from this generalized function may exist within specific soil and environmental locations within the region. Additional studies could be undertaken to describe such deviations, but if a similar sampling approach from private farms were desired, then two primary options should be considered: (1) repeated sampling of pastures over time from a few farms in a localized region or (2) one-time sampling from multiple farms having a diversity of pasture ages within a relatively homogenous topography and similar soils within ~50 km radius. These more targeted approaches may also help to reduce random variation from sampling across multiple farms from a relatively wide geographic region. Root-mean square error was reduced from 1.29 Mg N ha⁻¹ using TSN stock estimates to 0.75 Mg N ha⁻¹ when using root-zone enrichment of TSN. Similarly, root-mean square error was reduced from 10.7 Mg C ha⁻¹ with total SOC stock to 6.3 Mg C ha⁻¹ with root-zone enrichment of SOC. More controlled studies with repeated sampling of small experimental pastures as they matured resulted in least significant difference estimates of 0.3 Mg C ha⁻¹ yr⁻¹ when sampled yearly and 1.1 Mg C ha⁻¹ yr⁻¹ when sampled at 5-year intervals (Franzluebbers, 2010a). Root-mean square error of 6.3 Mg C ha⁻¹ as found in the current study with 86 fields across 2.0° latitude and 3.2° longitude in Virginia would seem to be a reasonable level of sensitivity to estimate decadal changes among pastures, particularly when the standard error compared with the root-mean square error can be reduced 4- to 5-fold with random sampling of 16–25 fields to represent a management system. Such approaches to discern land use effects on soil C and N stocks should be repeatable in other regions, especially when SOC and TSN stocks are calculated with the root-zone enrichment approach that helps to discern management-induced stock changes from those of pedogenic-stabilized stocks.

3.3 Stocking rate

Cattle stocking rate was classified into levels of 0.32 Mg live weight ha⁻¹ (3.1–4 acres cow⁻¹, n = 3 fields), 0.45 Mg live weight ha⁻¹ (2.1–3 acres cow⁻¹, n = 39 fields), 0.75 Mg live weight ha⁻¹ (1.1–2 acres cow⁻¹, n = 34 fields), 1.12 Mg live weight ha⁻¹ (1 acre cow⁻¹, n = 6 fields), and 2.25 Mg live weight ha⁻¹ (<1 acre cow⁻¹, n = 3 fields). Total stock of SOC at 0–30-cm depth appeared to be optimized as a function of cattle stocking rate (Figure 6). Although there was an optimization at 1.1 Mg live weight ha⁻¹ in total stock of SOC, a similar optimization at 1.2 Mg live weight ha⁻¹ in the baseline stock of SOC negated this function as a clear optimization point. Instead, root-zone enrichment of SOC was optimized across a broad range of stocking rates <1 Mg live weight ha⁻¹. Cattle stocking rate of 2.2 Mg live weight ha⁻¹ led to significantly lower root-zone enrichment of SOC than with all other lower stocking rate classes. This result is consistent with ecological theory for optimization of SOC storage along a gradient of forage utilization that controls plant productivity and limits C input past an optimal production limit (Franzluebbers, 2010b; Odum et al., 1979). There was no statistical separation of root-zone enrichment of SOC among any cattle stocking rates from 0.3 to 1.1 Mg live weight ha⁻¹. The strong coinciding occurrence of an optimized baseline SOC stock was important to avoid misinterpretation in this case. Since no forage utilization (i.e. without any grazing) was not a class that was evaluated, a more comprehensive evaluation of stocking rate near zero could not be obtained. Other research in Georgia suggested that optimization of SOC storage could occur at a moderate stocking rate as compared with no forage utilization (conservation reserve) and high forage utilization (frequent hay removal) at the other extreme (Franzluebbers et al., 2001).

Based on regression, greatest root-zone enrichment of SOC occurred with 0.9 Mg live weight ha⁻¹ as optimum stocking rate (Figure 6). This level was the stated practice on nearly half (45%) of the fields surveyed, resulting in root-zone enrichment of 40.4 Mg C ha⁻¹. This level of root-zone enrichment was not statistically different from that under woodland (39.8 ± 1.2 Mg C ha⁻¹) but was greater than those values under no-till cropland (28.3 ± 1.3 Mg C ha⁻¹) and conventional-till cropland (15.1 ± 5.1 Mg C ha⁻¹). The statistically greater root-zone enrichment of SOC under woodland than under grassland in Table 1, therefore should be qualified, such that optimized stocking rate on older pastures leads to equivalent root-zone enrichment of SOC compared with woodlands in Virginia. Sampling of a diversity of management conditions, therefore, led to discernment of variables influencing stocks of SOC and TSN.

3.4 Stocking method

Stocking method was categorized by frequency of typical herd moves within (i.e. as delineated by temporary, electrified polywire) or among fields. Total stock of SOC was trending greater with seasonal moves compared with more frequent moves (Figure 7). However, there was a significant effect for greater baseline stock of SOC under seasonal moves compared with more frequent moves. Therefore, root-zone enrichment of SOC was not different among any stock move classes. Having reviewed the lack of differences in root-zone enrichment of SOC among the six stock move levels, some levels were grouped to create fewer class levels (i.e. continuous [n = 4 fields], intermediate with seasonally or monthly moves [n = 14 fields], and intensive with weekly or more frequent moves [n = 68 fields]). Although there were some expected trends of greater root-zone enrichment of SOC with intermediate (39.1 ± 1.8 Mg C ha⁻¹) and intensive moves (37.0 ± 0.8 Mg C ha⁻¹) compared with continuous stocking (33.6 ± 3.4 Mg C ha⁻¹), these were not statistically significant effects. Even when increasing the number of observations (i.e. from an average of 28 observations to 57 observations per class level) by including subsampling location within a field as part of the analysis of variation, the most prominent statistical effect was between continuous stocking and intermediate moves (p = .06). The low number of observations with continuous stocking is noted, and further studies are warranted to increase robustness of this comparison. As well, no statistical differences occurred for root-zone enrichment of TSN. Therefore, there was no solid evidence that cattle stocking method was a major factor that changed stocks of SOC and TSN. This contradicts other research conducted in different regions using a few paired sites (Conant et al., 2003; Mosier et al., 2021; Teague et al., 2011). None of these studies reported separation of baseline SOC and TSN stocks from root-zone enrichment, but all studies indicated that multiple soil depths were sampled from each management. Therefore, root-zone enrichment calculations from these studies are warranted.

Recent emphasis has been on “regenerative grazing”, which appears to have a focus on short duration grazing and long rest periods to elicit change in ecological conditions, and particularly towards increasing soil organic matter (Giller et al., 2021; Spratt et al., 2021; Teague & Kreuter, 2020). However, evidence for a change in soil organic matter specifically due to a change in grazing management from continuous to rotational stocking appears to be thin (Castillo & Wallau, 2022; Sollenberger et al., 2012), or when present, should be interpreted more cautiously. In a replicated trial over 6 years, SOC in the 0–10-cm depth with more intensive rotational stocking (1–2 days grazing and ~ 24 days rest) was 3.6% greater (difference of 2 Mg C ha⁻¹) than with the typical rotational stocking system (6–10 days grazing and ~ 15 days rest) of sheep in the Basque Country of Spain (Díaz de Otálora et al., 2021). Across 92 trials conducted in North Carolina and surrounding states, improved grazing (i.e. combination of rotational stocking, routinely using fall stockpiling, and reduced N fertilizer inputs) of tall fescue-based pastures led to 26% greater SOC concentration (0–10-cm depth) and 36–42% greater particulate organic C and N concentration than conventional grazing (continuous stocking, frequent haying, and high N fertilizer inputs) (Franzluebbers & Poore, 2021). In a paired-farm approach on three ranches in northcentral Texas, soil organic matter was reported statistically greater from multi-paddock grazing and exclosures than from light and heavy continuous stocking (Teague et al., 2011). Soil organic matter from loss on ignition was reported by depth for these four treatments and these data were transformed to organic C (58% of loss on ignition) and reanalyzed for root-zone enrichment (non-linear fit was 99 ± 1%). Root-zone enrichment was 20.8 Mg C ha⁻¹ under heavy continuous stocking, 23.3 Mg C ha⁻¹ under light continuous stocking, 22.0 Mg C ha⁻¹ under multi-paddock stocking, and 20.5 Mg C ha⁻¹ with grazing exclosure. Baseline soil organic C content was 69.2 ± 10.6 Mg C ha⁻¹, which reflected a large and variable pedogenic-controlled contribution to soil profile conditions. Widely varying soil types were reported in this study, but not specific to the sampling. Therefore, change in soil organic C due to rotational stocking may have either been negligible or up to 1.2 Mg C ha⁻¹ (difference between multi-paddock rotational stocking and heavy continuous stocking). Across five pairs of farms in the southeastern US, soil organic matter to 1-m depth was reported as 9 Mg C ha⁻¹ greater and 1 Mg N ha⁻¹ greater with adaptive multi-paddock stocking than with continuous stocking (Mosier et al., 2021). Data reported in the supplementary table were reanalyzed for root-zone enrichment (non-linear fit was >99%). Root-zone enrichment was calculated as 37.5 Mg C ha⁻¹ and 3.66 Mg N ha⁻¹ under adaptive multi-paddock stocking and 34.1 Mg C ha⁻¹ and 3.27 Mg N ha⁻¹ under continuous stocking. Therefore, a difference in root-zone enrichment of SOC and TSN between cattle stocking methods was only ~39% of stock values reported. Sand concentration was different between the five sites, as well as between the management approaches (365 ± 172 g kg⁻¹ under adaptive multi-paddock stocking and 424 ± 188 g kg⁻¹ under continuous stocking). Soil texture is well known to affect soil organic matter dynamics and storage (Hassink et al., 1993; Plante et al., 2006), and is an important factor influencing baseline SOC and TSN conditions.

3.5 Nitrogen fertilizer input

Total stock of SOC was not significantly affected by N fertilizer rate (data not shown). Baseline SOC stock declined linearly with increasing N fertilizer rate (b₁ = −0.005 Mg ha⁻¹ [kg N ha⁻¹]⁻¹, p = .04). As a result, root-zone enrichment of SOC declined with low N fertilizer rates to 58 kg N ha⁻¹, and then did not change with further increases in N fertilizer rate [b₁ = −0.130 Mg ha⁻¹ (kg N ha⁻¹)⁻¹, p = .02; b₂ = 0.0011 Mg ha⁻¹ (kg N ha⁻¹)⁻², p = .008; y = a + (b₁ × N) – (b₂ × N²)].

Root-zone enrichment of TSN followed a similar trend with regards to historical N fertilization as for root-zone enrichment of SOC (Figure 8). Root-zone enrichment of TSN declined with N fertilizer rate to 56 kg N ha⁻¹, and then increased slightly with higher N fertilizer rates. Mean values were 3.78 Mg N ha⁻¹ without N fertilizer, 2.98 Mg N ha⁻¹ with 30 kg N ha⁻¹, 3.29 Mg N ha⁻¹ with 75 kg N ha⁻¹, and 3.69 Mg N ha⁻¹ with 125 kg N ha⁻¹. Probability of difference among N fertilizer levels was p < .001, .07, and .13, respectively. These results suggest that N fertilizer on mature pastures may not increase soil organic matter. These results contrast with suggestions made by others that to sequester significant quantity of SOC, large quantities of external N inputs will be needed (van Groenigen et al., 2017). In addition, natural ecosystems that have high C input and limited external N inputs, such as presumably the woodland sites in this study, have large SOC storage despite limited TSN storage. The C:N ratio of the total stock at 0–30-cm depth under woodland was 15.7 ± 3.0 kg kg⁻¹ and was 10.5 ± 0.7 kg kg⁻¹ under grassland. Even in the root-zone enrichment portion, C:N ratio was dramatically different between these two land uses (20.2 ± 9.4 kg kg⁻¹ and 12.0 ± 1.3 kg kg⁻¹, respectively), suggesting that despite the limitation of external N input in woodland systems, there was significant SOC sequestration that was taking place.

3.6 Other pasture management effects

Number of hay bales fed was queried for each farm (<25, 26–100, 101–500, 501–1000, and > 1000). Using an average bale size of 360 kg and grazeable land area per farm in the query (10–40, 41–80, 81–400, >400 ha), four levels of hay fed per hectare on a farm basis were calculated (i.e. 0.45, 0.9, 1.8, and 4.5 Mg ha⁻¹). Root-zone enrichments of SOC and TSN were not affected by hay fed on a farm, nor were total stocks of SOC and TSN. This lack of effect could be expected given the small, non-significant trend in root-zone enrichment of SOC as 1.1 Mg C ha⁻¹ (Mg hay)⁻¹ and assuming hay was fed at the same rate for the average pasture age of 39 years. This calculation yielded an average C retention rate from hay in soil of 7%. This retention rate was similar to that of 8% from broiler litter applied to pastures in Georgia, which was also not detected as a statistically significant effect (Franzluebbers et al., 2001). Assuming hay contained 1.5% N, the non-significant trend in root-zone enrichment of TSN as 0.108 Mg N ha⁻¹ (Mg hay)⁻¹ would have yielded an average N retention rate from hay in soil of 18%. Potentially, this high N retention rate could impact nutrient cycling in pasture ecosystems, and therefore, targeted hay feeding on a paddock may be an effective strategy to build natural fertility from regular hay feeding operations.

Farmers were also asked whether pastures were grazed only or occasionally hayed. The expectation was that harvesting hay would reduce C input and lead to lower root-zone enrichment of SOC. In contrast to this expectation, total and baseline stocks of SOC were greater (p = .05) with occasional hay harvest (70.0 and 31.2 Mg C ha⁻¹, respectively) than with grazing only (62.8 and 25.6 Mg C ha⁻¹, respectively). Occasionally hayed fields may have been on more agronomically productive landscape positions, resulting in elevated baseline stocks of SOC and TSN. As a result, root-zone enrichments of SOC and TSN were not different between grazed only and occasionally hayed fields.

Some farms historically used organic amendments on pastures, such as poultry litter or beef bed-pack. A total of 30 fields did not receive organic amendments, 38 fields received organic amendments occasionally, and 21 fields received organic amendments yearly. Root-zone enrichments of SOC and TSN were not affected by application frequency of organic amendments. This lack of difference is not entirely surprising given the relatively low rates of amendment that would have typically been supplied to meet pasture demand and the high decomposition environment with warm and moist conditions in the region. In a controlled study on pastures in north Georgia a similar non-significant effect of poultry litter application on SOC and TSN stocks was observed (Franzluebbers et al., 2001).

Farmer reliance on soil testing was queried. A total of five farms tested yearly, 17 farms tested approximately twice out of 5 years, 6 farms tested once every 5 years, and only 1 farm indicated no testing was typically performed. No difference in root-zone enrichments of SOC and TSN occurred as a function of soil testing frequency.

Historical land use change in the past 50 years was queried for the fields sampled. A total of 16 fields were previously in cropland at some point in time, 43 fields were in grassland for very long periods of time, 14 fields alternated between cropland and grassland usage, and 13 fields were recently cleared from woodland. Root-zone enrichment of total SOC was greatest in those fields that had a long history of grassland (38.8 Mg C ha⁻¹) or that were converted from woodland (38.0 Mg C ha⁻¹) and lowest levels were with some history of cropland cultivation (34.9 Mg C ha⁻¹). Most of this land-use history effect was already encapsulated in the pasture age factor. Root-zone enrichment of TSN was greater (p = .01) under the long history of grassland compared with all other previous land uses (3.35 vs 3.02 Mg N ha⁻¹).

Responses by farmers to management history queries should be considered accurate, but there is also the possibility that recollection of history was vague. In addition, management would have likely varied somewhat over time as various factors on and off the farm may have forced change. However, the broad, overarching management questions that were queried led to rapid responses that were not considered difficult to answer by participants. It should also be noted that this survey of soil and management factors may have been from a unique group of farmers that could be considered self-selected. However, there were 31 farmers participating, and this number allowed for significant randomization to have occurred, especially since none of the participants were privy to any expected results from this project other than from the concepts and few illustrative examples described in the soil health sessions that some farmers attended immediately prior to this study.

4 CONCLUSIONS

This survey of 31 pasture-based livestock farms in Virginia provided a glimpse into the enormous potential for soil organic carbon (SOC) and total soil nitrogen (TSN) storage with improved conservation agricultural management in the eastern US. With grassland and no-till cropland, root-zone enrichment of soil organic C was 35.5 ± 7.9 Mg C ha⁻¹ and of total soil N was 3.03 ± 0.87 Mg N ha⁻¹ (mean ± standard deviation among 234 soil profiles), which were 1.3 ± 0.5 times greater than baseline stocks. Root-zone enrichment reflects management-controlled factors of soil organic matter formation, while baseline stocks reflect pedogenic-controlled factors. Conservation management approaches were clearly affecting root-zone enrichment of total soil N, with mean values by land use of 3.26 ± 0.20 Mg N ha⁻¹ (mean ± standard error) under mature pastures >2.40 ± 0.15 Mg N ha⁻¹ under no-till cropland = 2.23 ± 0.14 Mg N ha⁻¹ under woodland >1.11 ± 0.61 Mg N ha⁻¹ under conventional-till cropland. Based on a presumed 50-year management interval, this would have led to TSN accumulation of 57 ± 19 kg N ha⁻¹ yr⁻¹ across all locations, a practically significant level of accumulation as a reserve for future production needs. Pasture age was one of the strongest factors affecting root-zone enrichment of SOC and TSN, along with stocking rate. Most other management factors had small or non-significant effects on root-zone enrichment of SOC and TSN, including stocking method, N fertilization history, hay feeding on pasture, occasional hay harvest from a pasture, application of organic amendments, and frequency of routine chemical soil testing.

Root-zone enrichment of SOC and TSN accumulated non-linearly with pasture age; SOC sequestration rate was the equivalent of 1.46 Mg C ha⁻¹ yr⁻¹ during the first 10 years of pasture development, 0.81 Mg C ha⁻¹ yr⁻¹ during the first 20 years, and 0.33 Mg C ha⁻¹ yr⁻¹ during the first 50 years. No solid evidence was found that rotational stocking changed root-zone enrichment of SOC and TSN compared with continuous stocking. Generally greater estimates of root-zone enrichment of SOC and TSN were observed for no-till cropland and grazed pastures on these private farms in Virginia compared with previous estimates of these land uses, primarily derived from research stations in the region. Variable baseline SOC and TSN conditions among and within farms confirmed that land use and management comparisons were more discernable when root-zone enrichment calculations were made. There was little evidence indicating change in SOC and TSN at or below 30-cm depth in response to differences in expected rooting distribution. This study also showed that relatively low standard errors could be obtained when sampling populations of farms or fields within farms, necessary to discern long-term management effects on SOC and TSN. Although limited in scope across one half of one state in the eastern US, these results should have relevance for stakeholders in other surrounding states and can serve as a first attempt towards a wider geographic evaluation of the root-zone enrichment concept under a diversity of agricultural management systems.

ACKNOWLEDGEMENTS

Sound technical support in the laboratory was provided by Alexandra Cohen, Elizabeth Dillon, Maxwell Dumas, Erin Silva, and Lauren Willoughby. Logistical support in arranging farmer participation is gratefully acknowledged from Shawna Bratton, J.B. Daniel, Lydia Fitzgerald, Cory Guilliams, John Hicks, Stephanie Johansen, Kenner Love, Morgan Paulette, Becky Roberts, Robert Shoemaker, Carl Stafford, and Becky Szarzynski. Hearty thanks to all collaborating farmers for their interest, participation, and responses to queries, including Bart and Gail Barton, Danny Boyer at Four Winds Farm, Robert and Stella Bradford and Virginia Rockwell, Shawna Bratton, Kevin Craun at Hillview Farm Inc, Eric Crowgey at Richdale Farm, Jeremy Engh at Lakota Ranch, John Genho at Eldon Farms LLC, Alan Graybeal and Laura Bullard at Optimal Beef, Paul Gripka, AJ and Buck Holsinger at Holsinger Homeplace Farms, Bruce Johnson at Dragon Fly Farms, Hank Maxey at Maxey Farms Inc, Chuck Miller, Donnie Moore at D Moore Inc, Richard Moyer at Moyer Family Farm, Mike Phillips at Valley View Farms, Matt Poore, Jimmy Reaves at Honey Hammer Farm, Mark Strauss, Isaac Swortzel, Glenn Szarzynski at Mountain Glen Farm, Keith Tuck, Bill Tucker at Tucker Family Farms, Jeff Wade at Wall-Wade Farms LLC, Bob Wilbanks at Wilbanks Farm, JC Winstead, Andrea and Dendy Young at Hidden Creek Farm, and Larry Younger. Financial support was provided by USDA-Agricultural Research Service and the Foundation for Food & Agriculture Research (FFAR), Grant No. 22-000279, Enhanced Soil Carbon Farming as a Climate Solution, administered by The Ohio State University. Content of this publication is solely the responsibility of the author and does not necessarily represent the official views of FFAR.

CONFLICT OF INTEREST STATEMENT

The author declares no conflict of interest.

Open Research

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Supporting Information

REFERENCES

Briske, D. D., Sayer, N. F., Huntsinger, L., Fernandez-Gimenez, M., Budd, B., & Derner, J. D. (2011). Origin, persistence, and resolution of the rotations grazing debate: Integrating human dimensions into rangeland research. Rangeland Ecology & Management, 64, 325–334.
10.2111/REM-D-10-00084.1
Web of Science® Google Scholar
Castillo, M. S., & Wallau, M. (2022). Stocking method and terminology in grazing management: Evaluation of assertions from educational, outreach, and engagement programs. Crop Science, 63, 495–500.
10.1002/csc2.20877
Web of Science® Google Scholar
Chang, J., Ciais, P., Gasser, T., Smith, P., Herrero, M., Havlík, P., Obersteiner, M., Guenet, B., Goll, D. S., Li, W., Naipal, V., Peng, S., Qiu, C., Tian, H., Viovy, N., Yue, C., & Zhu, D. (2021). Climate warming from managed grasslands cancels the cooling effect of carbon sinks in sparsely grazed and natural grasslands. Nature Communications, 12, 118. https://doi.org/10.1038/s41467-020-20406-7
10.1038/s41467-020-20406-7
CAS PubMed Web of Science® Google Scholar
Conant, R. T., Six, J., & Paustian, K. (2003). Land use effects on soil carbon fractions in the southeastern United States. I. Management-intensive versus extensive grazing. Biology and Fertility of Soils, 38, 386–392.
10.1007/s00374-003-0652-z
CAS Web of Science® Google Scholar
Crotty, F. V., Fychan, R., Scullion, J., Sanderson, R., & Marley, C. L. (2015). Assessing the impact of agricultural forage crops on soil biodiversity and abundance. Soil Biology and Biochemistry, 91, 119–126.
10.1016/j.soilbio.2015.08.036
CAS Web of Science® Google Scholar
Díaz de Otálora, X., Epelde, L., Arranz, J., Garbisu, C., Ruiz, R., & Mandaluniz, N. (2021). Regenerative rotational grazing management of dairy sheep increases springtime grass production and topsoil carbon storage. Ecological Indicators, 125, 107484.
10.1016/j.ecolind.2021.107484
CAS Web of Science® Google Scholar
Don, A., Rebmann, C., Kolle, O., Scherer-Lorenzen, M., & Schulze, E.-D. (2009). Impact of afforestation-associated management changes on the carbon balance of grassland. Global Change Biology, 15, 1990–2002.
10.1111/j.1365-2486.2009.01873.x
Web of Science® Google Scholar
Farmaha, B. S., Sekaran, U., & Franzluebbers, A. J. (2022). Cover cropping and conservation tillage improve soil health in the southeastern United States. Agronomy Journal, 114, 296–316.
10.1002/agj2.20865
CAS Web of Science® Google Scholar
Franzluebbers, A. J. (2010a). Achieving soil organic carbon sequestration with conservation agricultural systems in the southeastern United States. Soil Science Society of America Journal, 74, 347–357.
10.2136/sssaj2009.0079
CAS Web of Science® Google Scholar
Franzluebbers, A. J. (2010b). Soil organic carbon in managed pastures of the southeastern United States of America. In Grassland carbon sequestration: Management, policy and economics (pp. 163–175). Proceedings of the Workshop on the role of grassland carbon sequestration in the mitigation of climate change. April 2009.
Google Scholar
Franzluebbers, A. J. (2010c). Will we allow soil carbon to feed our needs? Carbon Management, 1, 237–251.
10.4155/cmt.10.25
CAS Web of Science® Google Scholar
Franzluebbers, A. J. (2020). Soil-test biological activity with the flush of CO2: V. Validation of nitrogen prediction for corn production. Agronomy Journal, 112, 2188–2204.
10.1002/agj2.20094
CAS Web of Science® Google Scholar
Franzluebbers, A. J. (2021a). Root-zone enrichment of carbon, nitrogen, and soil-test biological activity under cotton systems in North Carolina. Soil Science Society of America Journal, 85, 1785–1798.
10.1002/saj2.20290
CAS Web of Science® Google Scholar
Franzluebbers, A. J. (2021b). Soil organic carbon sequestration calculated from depth distribution. Soil Science Society of America Journal, 85, 158–171.
10.1002/saj2.20176
CAS Web of Science® Google Scholar
Franzluebbers, A. J. (2022a). Probing deep to express root-zone enrichment of soil-test biological activity on southeastern U.S. farms. Agricultural & Environmental Letters, 7, 20087.
10.1002/ael2.20087
CAS Web of Science® Google Scholar
Franzluebbers, A. J. (2022b). Root-zone soil organic carbon enrichment is sensitive to land management across soil types and regions. Soil Science Society of America Journal, 86, 79–91.
10.1002/saj2.20346
CAS Web of Science® Google Scholar
Franzluebbers, A. J. (2022c). Soil organic matter, texture, and drying temperature effects on water content. Soil Science Society of America Journal, 86, 1086–1095.
10.1002/saj2.20425
CAS Web of Science® Google Scholar
Franzluebbers, A. J. (2023). Soil organic carbon and nitrogen storage estimated with the root-zone enrichment method under conventional and conservation land management across North Carolina. Journal of Soil and Water Conservation, 78, 124–140.
10.2489/jswc.2023.00064
Web of Science® Google Scholar
Franzluebbers, A. J., Paine, L. K., Winsten, J. R., Krome, M., Sanderson, M. A., Ogles, K., & Thompson, D. (2012). Well-managed grazing systems: A forgotten hero of conservation. Journal of Soil and Water Conservation, 67, 100A–104A.
10.2489/jswc.67.4.100A
Web of Science® Google Scholar
Franzluebbers, A. J., Pehim-Limbu, S., & Poore, M. H. (2018). Soil-test biological activity with the flush of CO₂: IV. Fall-stockpiled tall fescue yield response to applied nitrogen. Agronomy Journal, 110, 2033–2049.
10.2134/agronj2018.03.0146
CAS Web of Science® Google Scholar
Franzluebbers, A. J., & Poore, M. H. (2021). Tall fescue management and environmental influences on soil, surface residue, and forage properties. Agronomy Journal, 113, 2029–2043.
10.1002/agj2.20577
CAS Web of Science® Google Scholar
Franzluebbers, A. J., Starks, P. J., & Steiner, J. L. (2019). Conservation of soil organic carbon and nitrogen fractions in a tallgrass prairie in Oklahoma. Agronomy, 9, 204.
10.3390/agronomy9040204
CAS Google Scholar
Franzluebbers, A. J., & Stuedemann, J. A. (2008). Soil physical responses to cattle grazing cover crops under conventional and no tillage in the southern Piedmont USA. Soil and Tillage Research, 100, 141–153.
10.1016/j.still.2008.05.011
Web of Science® Google Scholar
Franzluebbers, A. J., & Stuedemann, J. A. (2010). Surface soil changes during twelve years of pasture management in the southern Piedmont USA. Soil Science Society of America Journal, 74, 2131–2141.
10.2136/sssaj2010.0034
CAS Web of Science® Google Scholar
Franzluebbers, A. J., Stuedemann, J. A., & Wilkinson, S. R. (2001). Bermudagrass management in the southern Piedmont USA: I. Soil and surface residue carbon and sulfur. Soil Science Society of America Journal, 65, 834–841.
10.2136/sssaj2001.653834x
CAS Web of Science® Google Scholar
Franzluebbers, A. J., van Vliet, S., Young, S., & Poore, M. H. (2023). Surface-soil aggregation and organic C and N fractions under paired grassland and cropland sites in the southeastern USA. In Proceedings of the XXV international grassland congress 14-19 May, 2023. Curran Associates.
10.52202/071171-0029
Google Scholar
Ghimire, R., Norton, J. B., & Norton, U. (2018). Soil organic matter dynamics under irrigated perennial forage-annual crop rotations. Grass and Forage Science, 73, 907–917.
10.1111/gfs.12378
CAS Web of Science® Google Scholar
Giller, K. E., Hijbeek, R., Anderson, J. A., & Sumberg, J. (2021). Regenerative agriculture: An agronomic perspective. Outlook on Agriculture, 50, 13–25.
10.1177/0030727021998063
PubMed Web of Science® Google Scholar
Gomez-Casanovas, N., DeLucia, N. J., Bernacchi, C. J., Boughton, E. H., Sparks, J. P., Chamberlain, S. D., & DeLucia, E. H. (2018). Grazing alters net ecosystem C fluxes and the global warming potential of a subtropical pasture. Ecological Applications, 28, 557–572.
10.1002/eap.1670
PubMed Web of Science® Google Scholar
Greenwood, K. L., & McKenzie, B. M. (2001). Grazing effects on soil physical properties and the consequences for pastures: A review. Australian Journal of Experimental Agriculture, 41, 1231–1250.
10.1071/EA00102
Web of Science® Google Scholar
Hassink, J., Bouwman, L. A., Zwart, K. B., Bloem, J., & Brussaard, L. (1993). Relationships between soil texture, physical protection of organic matter, soil biota, and C and N mineralization in grassland soils. In L. Brussaard & M. J. Kooistra (Eds.), Soil structure/soil biota interrelationships (pp. 105–128). Elsevier.
10.1016/B978-0-444-81490-6.50059-5
Google Scholar
Li, W., Ciais, P., Guenet, B., Peng, S., Chang, J., Chaplot, V., Khudyaev, S., Peregon, A., Piao, S., Wang, Y., & Yue, C. (2018). Temporal response of soil organic carbon after grassland-related land-use change. Global Change Biology, 24, 4731–4746.
10.1111/gcb.14328
PubMed Web of Science® Google Scholar
Libohova, Z., Seybold, C., Wysocki, D., Wills, S., Schoeneberger, P., Williams, C., Lindbo, D., Stott, D., & Owens, P. R. (2018). Reevaluating the effects of soil organic matter and other properties on available water-holding capacity using the National Cooperative Soil Survey Characterization Database. Journal of Soil and Water Conservation, 73, 411–421.
10.2489/jswc.73.4.411
Web of Science® Google Scholar
Liu, L., & Basso, B. (2020). Impacts of climate variability and adaptation strategies on crop yields and soil organic carbon in the US Midwest. PLoS One, 15, e0225433.
10.1371/journal.pone.0225433
CAS PubMed Web of Science® Google Scholar
Lorenz, K., Lal, R., & Ehlers, K. (2019). Soil organic carbon stock as an indicator for monitoring land and soil degradation in relation to United Nations' sustainable development goals. Land Degradation & Development, 30, 824–838.
10.1002/ldr.3270
Web of Science® Google Scholar
Machmuller, M. B., Kramer, M. G., Cyle, T. K., Hill, N., Hancock, D., & Thompson, A. (2015). Emerging land use practices rapidly increase soil organic matter. Nature Communications, 6, 6995. https://doi.org/10.1038/ncomms7995
10.1038/ncomms7995
CAS PubMed Web of Science® Google Scholar
Minasny, B., Malone, B. P., McBratney, A. B., Angers, D. A., Arrouays, D., Chambers, A., Chaplot, V., Chen, Z.-S., Cheng, K., Das, B. S., Field, D. J., Gimona, A., Hedley, C. B., Hong, S. Y., Mandal, B., Marchant, B. P., Martin, M., McConkey, B. G., Mulder, V. L., … Winowiecki, L. (2017). Soil carbon 4 per mille. Geoderma, 292, 59–86.
10.1016/j.geoderma.2017.01.002
Web of Science® Google Scholar
Mosier, M., Apfelbaum, S., Byck, P., Calderon, F., Teague, R., Thompson, R., & Cotrufo, M. F. (2021). Adaptive multi-paddock grazing enhances soil carbon and nitrogen stocks and stabilization through mineral association in southeastern U.S. grazing lands. Journal of Environmental Management, 288, 112409.
10.1016/j.jenvman.2021.112409
CAS PubMed Web of Science® Google Scholar
Odum, E. P., Finn, J. T., & Franz, E. H. (1979). Perturbation theory and the subsidy-stress gradient. Bioscience, 29, 349–352.
10.2307/1307690
Web of Science® Google Scholar
Plante, A. F., Conant, R. T., Stewart, C. E., Paustian, K., & Six, J. (2006). Impact of soil texture on the distribution of soil organic matter in physical and chemical fractions. Soil Science Society of America Journal, 70, 287–296.
10.2136/sssaj2004.0363
CAS Web of Science® Google Scholar
Poeplau, C., Don, A., Vesterdal, L., Leifeld, J., van Wesemael, B., Schumacher, J., & Gensior, A. (2011). Temporal dynamics of soil organic carbon after land-use change in the temperate zone – Carbon response functions as a model approach. Global Change Biology, 17, 2415–2427.
10.1111/j.1365-2486.2011.02408.x
Web of Science® Google Scholar
Rouquette, F. M., Sollenberger, L. E., & Vendramini, J. M. B. (2023). Grazing management and stocking strategy decisions for pasture-based beef systems: Experimental confirmation vs. testimonials and perceptions. Translational. Animal Science, 7, txad069.
Google Scholar
Rowntree, J. E., Stanley, P. L., Maciel, I. C. F., Thorbecke, M., Rosenzweig, S. T., Hancock, D. W., Guzman, A., & Raven, M. R. (2020). Ecosystem impacts and productive capacity of a multi-species pastured livestock system. Frontiers in Sustainable Food Systems, 4, 544984.
10.3389/fsufs.2020.544984
Google Scholar
Sanderson, M. A., Franzluebbers, A., Goslee, S., Kiniry, J., Owens, L., Spaeth, K., Steiner, J., & Veith, T. (2011). Pastureland conservation effects assessment project: Status and expected outcomes. Journal of Soil and Water Conservation, 66, 148A–153A.
10.2489/jswc.66.5.148A
Web of Science® Google Scholar
Scurlock, J. M., & Hall, D. O. (1998). The global carbon sink: A grassland perspective. Global Change Biology, 4, 229–233.
10.1046/j.1365-2486.1998.00151.x
Web of Science® Google Scholar
Silveira, M. L., Liu, K., Sollenberger, L. E., Follett, R. F., & Vendramini, J. M. B. (2013). Short-term effects of grazing intensity and nitrogen fertilization on soil organic carbon pools under perennial grass pastures in the southeastern USA. Soil Biology and Biochemistry, 58, 42–49.
10.1016/j.soilbio.2012.11.003
CAS Web of Science® Google Scholar
Sollenberger, L. E., Agouridis, C. T., Vanzant, E. S., Franzluebbers, A. J., & Owens, L. B. (2012). Prescribed grazing on pasturelands. In C. J. Nelson (Ed.), Conservation outcomes from pastureland and Hayland practices (pp. 111–204). USDA.
Google Scholar
Sollenberger, L. E., Kohmann, M. M., Dubeux, J. C. B., & Silveira, M. L. (2019). Grassland management affects delivery of regulating and supporting ecosystem services. Crop Science, 59, 441–459.
10.2135/cropsci2018.09.0594
CAS Web of Science® Google Scholar
Spratt, E., Jordan, J., Winsten, J., Huff, P., van Schaik, C., Grimsbo-Jewett, J., Filbert, M., Luhman, J., Meier, E., & Paine, L. (2021). Accelerating regenerative grazing to tackle farm, environmental, and societal challenges in the upper Midwest. Journal of Soil and Water Conservation, 76, 15A–23A.
10.2489/jswc.2021.1209A
Web of Science® Google Scholar
Stanley, P. L., Rowntree, J. E., Beede, D. K., DeLonge, M. S., & Hamm, M. W. (2018). Impacts of soil carbon sequestration on life cycle greenhouse gas emissions in Midwestern USA beef finishing systems. Agricultural Systems, 162, 249–258.
10.1016/j.agsy.2018.02.003
Web of Science® Google Scholar
Teague, R., & Kreuter, U. (2020). Managing grazing to restore soil health, ecosystem function, and ecosystem services. Frontiers in Sustainable Food Systems, 4, 534187.
10.3389/fsufs.2020.534187
Web of Science® Google Scholar
Teague, W. R., Dowhower, S. L., Baker, S. A., Haile, N., DeLaune, P. B., & Conover, D. M. (2011). Grazing management impacts on vegetation, soil biota and soil chemical, physical and hydrological properties in tall grass prairie. Agriculture, Ecosystems and Environment, 141, 310–322.
10.1016/j.agee.2011.03.009
CAS Web of Science® Google Scholar
USDA-NASS (National Agricultural Statistics Service). (2023). 2017 census of agriculture. United States Department of Agriculture. Accessed at: https://www.nass.usda.gov/AgCensus/
Google Scholar
USDA-NRCS (Natural Resources Conservation Service). (2022). Land resource regions and major land resource areas of the United States, the Caribbean, and the Pacific Basin. In USDA agriculture handbook 296 (p. 646). United States Department of Agriculture.
Google Scholar
van Groenigen, J. W., van Kessel, C., Hungate, B. A., Oenema, O., Powlson, D. S., & van Groenigen, K. J. (2017). Sequestering soil organic carbon: A nitrogen dilemma. Environmental Science & Technology, 51, 4738–4739.
10.1021/acs.est.7b01427
PubMed Web of Science® Google Scholar
Viruel, E., Fontana, C. A., Puglisi, E., Nasca, J. A., Banegas, N. R., & Cocconcelli, P. S. (2022). Land-use change affects the diversity and functionality of soil bacterial communities in semi-arid Chaco region, Argentina. Applied Soil Ecology, 172, 104362.
10.1016/j.apsoil.2021.104362
Web of Science® Google Scholar
Wright, A. L., Hons, F. M., & Rouquette, F. M., Jr. (2004). Long-term management impacts on soil carbon and nitrogen dynamics of grazed bermudagrass pastures. Soil Biology and Biochemistry, 36, 1809–1816.
10.1016/j.soilbio.2004.05.004
CAS Web of Science® Google Scholar

Citing Literature

Volume79, Issue2

Special sections: Topics from EGF2023: The future of ley‐farming in cropping systems some topics from IGC2023 some topics on Green Biorefinery

June 2024

Pages 265-280

Root-zone enrichment of soil organic carbon and nitrogen under grazing and other land uses in a humid-temperate region

Abstract

1 INTRODUCTION