Guilhermo Francklin de Souza Congio

Accurate greenhouse gas inventories require region-specific emission factors (EFs). Current nitrous oxide (N ₂ O) inventories often rely on IPCC Tier 1 defaults, which may not accurately represent subtropical grazing systems where field-based data remain scarce. This study aimed to evaluate how pasture intensification gradients interact with different nitrogen sources (urea fertilizer, cattle urine, and dung) to regulate N ₂ O emission factors in the Southern Brazilian Highlands, providing regionally calibrated data to assess their alignment with IPCC default values. Nitrous oxide emissions were measured over 100 days using static chambers in four systems: natural grassland (NG), improved natural grassland (ING), perennial pasture (PP), and annual pasture with soil disturbance (AP). Measured EFs suggested a trend toward lower values than IPCC defaults for most sources. Urea in AP was the only treatment exceeding the 1.6% default (EF = 1.7%), while urea-EFs in PP and ING averaged 0.77%. Urine-EFs averaged 0.71% in AP/ING and 0.23% in NG/PP, while dung consistently showed the lowest values (mean = 0.28%). These findings suggest that N ₂ O emissions are governed by two interacting hierarchies: management intensity (NG < ING ≈ PP < AP) and nitrogen source (urea > urine ≈ dung). Overall, these findings suggest that the monitored subtropical grazing systems with stable soil structures tended to exhibit lower N ₂ O emission factors than current IPCC Tier 1 default values. Disaggregating EFs by source and management intensity improves national inventories and informs mitigation strategies, such as reducing soil disturbance to preserve the naturally low N ₂ O emission potential of subtropical pastures.

Livestock grazing strongly influences terrestrial ecosystems and plays a critical role in carbon dynamics, with outcomes highly dependent on grazing management. High-frequency rotation (HFR) grazing has been proposed to reduce the uneven spatial grazing distribution commonly associated with low-frequency rotation (LFR) grazing, potentially altering forage production and soil organic carbon (SOC). However, most ecosystem models used to assess SOC dynamics do not explicitly represent uneven grazing distribution, limiting their ability to evaluate management effects. To address this limitation, we enhanced the MEMS ecosystem model by incorporating a spatially explicit grazing distribution through the introduction of discrete spatial units and key environmental drivers, including forage availability and quality, and distance to water. Using remote sensing-derived enhanced vegetation index (EVI), we verified the simulated grazing distribution using an experimental rangeland site in Oklahoma. We tested the model’s sensitivity to grazing frequency under different management (stocking rate, timing, and duration) and climate (typical, dry, and wet) scenarios. Our results indicate that uneven grazing distribution leads to distinct spatial patterns of forage production and SOC. Notably, significant differences in field-average production and SOC between HFR and LFR emerged under heavy intensity grazing, where HFR sustained higher SOC stocks and productivity than LFR. These findings highlight the importance of spatially explicit modeling in understanding grazing distributions, suggesting that HFR grazing may be beneficial mostly under heavy intensity grazing. Our study offers actionable guidance for designing future grazing management experiments to address this critical knowledge gap and advance carbon management strategies.

This study investigated the effects of different by-products used as feedstuffs to replace ground corn in the supplement of Holstein dairy cows rotationally grazing intensively managed elephant grass. Five experiments were conducted to evaluate pelleted citrus pulp (PCP), corn gluten feed (CGF), whole cottonseed (WCS), wheat middlings (WHM), and soybean hulls (SBH) as alternatives to ground corn. The experiments followed a Latin square design and assessed blood and performance parameters such as milk yield (MY) and milk composition. Blood parameters were not affected (p > 0.05) by any by-products. The inclusion of PCP, CGF, and SBH up to 75%, and WHM up to 50% in place of corn did not affect (p > 0.05) either MY or milk composition. However, increasing the level of WCS up to 21% resulted in a significant reduction (p < 0.05) in yields of milk, 3.5% fat-corrected milk, protein, and milk solids, along with an increase (p < 0.05) in milk urea nitrogen. Our results suggest the use of PCP, CGF, WCS, WHM, and SBH replacing corn in the supplement up to 75, 75, 14, 50, and 75%, respectively, has no adverse short-term effects on MY and composition of Holstein cows grazing intensively managed elephant grass.

Multispecific pastures are considered more sustainable to animal production than monocultures. However, studies on mixtures of tropical grasses are underexplored. We aimed to assess whether a mixture of three contrasting growth strategies of perennial tropical forage grasses could outperform their respective monocultures in terms of forage yield and stability. The four treatments included three perennial tropical forage grasses: Andropogon gambagrass (AG; Andropogon gayanus cv. Planaltina), Massai guineagrass [MG; Megathyrsus maximus cv. Massai] and Piatã palisadegrass [PP; Urochloa brizantha cv. BRS Piatã], cultivated as monocultures and as a mixture of the three species. Treatments were randomly assigned to sixteen 180 m ² plots and managed intermittently under manual harvest at pre‐ and post‐harvest heights of 35 and 17.5 cm, respectively, for 2 years. The botanical composition of the mixture remained relatively stable, with a predominance of MG (68.9%), followed by PP (20.1%) and AG (6.8%). Annual forage yield varied between years ( p = 0.0017) with a difference of 3974 kg DM ha ⁻¹ year ⁻¹ , but not according to treatments ( p > 0.05) with an average of 23,012 kg DM ha ⁻¹ year ⁻¹ . No effect was observed for the intra‐annual forage yield variance among treatments ( p > 0.05). The association among PP, MG and AG in a mixture allows species to coexist with a relatively stable botanical composition, as well as forage yield and stability, similar to their monocultures.

Soil health is typically evaluated using physical, chemical, and biological parameters. However, identifying cost-effective and interpretable metrics remains a challenge. The effectiveness of ecological outcome verification (EOV) in predicting soil health in grazing lands was assessed at 22 ranches. Sixty-four soil samples were analyzed using the Haney soil health test (HSHT) and phospholipid fatty acid (PLFA). Of 104 variables, 13 were retained following principal component analysis (PCA), including variables associated with plant community, carbon dynamics, and microbial community structure. Soils with enriched microbial and organic matter (SOM) characteristics supported a healthier ecological status, as corroborated by greater EOV scores. Water-extractable organic carbon (WEOC) was positively correlated to plant functional groups, whereas SOM was positively correlated with plant biodiversity and functional groups. Total bacteria were positively correlated with all EOV parameters. Microbial biomass (MB) was positively correlated with both water and energy cycle indexes, whereas arbuscular mycorrhizal fungi (AMF) was positively correlated with the water cycle. From the multiple regression analyses, water infiltration emerged as a key predictor of soil respiration and WEOC. Overall, the ecological outcomes measured by EOV have the potential to serve as a proxy for soil health, providing a practical tool for producers to make informed land management decisions.

With the growing use of crossbred cattle in Brazilian feedlots and increasing pressure to reduce antibiotic use as growth promoters, this study examines the impact of three feed additives—monensin (MON), monensin with Lithothamnium calcareum (LCM), and a blend of essential oils (BEO)—on the performance of Nellore (NEL) and crossbred (CROSS) cattle. A total of 90 Nellore and 90 crossbred bulls were assigned to a completely randomized block design with a 2 × 3 factorial design for 112 days, and all received the same diet with varying additives. Their methane (CH₄) emissions were estimated. All data were analyzed using the emmeans package of R software (version 4.4.1). Crossbred cattle outperformed Nellore in average daily gain (ADG), hot carcass weight (HCW), and dry matter intake (DMI), though feed efficiency remained unaffected. Across additives, no significant differences were observed in ADG, HCW, or dressing percentage. However, LCM had a lower DMI than the BEO, while MON showed better feed efficiency than the BEO. A breed-by-additive interaction trend was noted for DMI as a percentage of body weight (DMI%BW), with Nellore bulls on LCM diets showing the lowest DMI%BW. Crossbreeds had greater net energy (NE) requirements for maintenance (NEm) and gain (NEg), and MON-fed animals had greater NEm and NEg than the BEO. Crossbred bulls had greater daily methane (CH₄) emissions than Nellore bulls. Animals on the BEO had greater daily CH₄ emissions and greater g CH₄/kg metabolic BW than LCM bulls. In conclusion, the addition of Lithothamnium calcareum to monensin did not enhance performance compared to monensin alone. Monensin outperformed the BEO in feed efficiency and nutrient utilization.