Amir Bazrgar

Switchgrass ( Panicum virgatum) and miscanthus ( Miscanthus spp.) are C₄ perennial biomass crops (PBCs) commonly cultivated in Ontario. The ¹³C natural abundance technique was used to assess the following: (i) quantify the proportion of C₄-derived soil organic carbon (SOC) stock (Mg C ha⁻¹) within the SOC stocks of the whole soil, (ii) determine the C₄-derived SOC sequestration rate, and (iii) quantify C₄-derived SOC stocks in soil particle size fractions. This was achieved by analyzing the δ¹³C values in SOC of both the whole soil and various soil particle size fractions in PBC fields that were converted from agriculture. At Guelph after 11 years of PBC, C₄-derived SOC stock as a proportion of SOC stock in the whole soil accounted for 30% in switchgrass and 31% in miscanthus fields, while at Elora it comprised 41% in switchgrass and 50% in miscanthus. However, in Burlington after 4 years, C₄-derived SOC represented 10%–12% in PBC fields compared to 17% in agriculture fields. The C₄-derived SOC sequestration rates were 0.8, 0.7, and 0.4 Mg C ha⁻¹ year⁻¹ in switchgrass, miscanthus, and agriculture fields, respectively at the Guelph site. In miscanthus fields, lower C₄-derived SOC stock in macro soil particles were observed, yet higher percentages were observed in micro soil particles and the silt plus clay fractions compared to switchgrass and agriculture fields. Agriculture fields had higher C₄-derived SOC in macro soil particles, indicating lower SOC stability. Therefore, cultivating PBCs on low-productive agricultural lands could contribute to climate change mitigation practices due to increased SOC stability.

As global fish consumption rises, improving fish health through immunomodulatory feed ingredients shows promise while also supporting growth performance. This study investigated the effects of yeast prebiotics, probiotics, a postbiotic (butyrate), and black soldier fly larvae (BSFL) meal on fish immune responses. Zebrafish were fed diets containing these ingredients for 63 days and then exposed to either Pseudomonas aeruginosa lipopolysaccharide (LPS) or live Flavobacterium psychrophilum to assess hepatic candidate gene expression and weight gain. No mortalities were observed post-immune challenges, and weight gains were not significantly different across treatments. Liver samples were collected for mRNA analysis, and real-time qPCR was used to evaluate the expression of immune-related genes such as TNF-α, IL-1β, hepcidin, and NF-κB/p65. NF-κB/p65 was upregulated in response to immune challenges, indicating a reaction to both LPS and pathogen exposure. Fish on the BSFL diet showed decreased NF-κB/p65 expression after the pathogen challenge, while probiotic-fed fish had reduced angiopoietin-like 4 (angptl4) levels following LPS exposure. Butyrate supplementation had the most significant impact, downregulating pro-inflammatory cytokines and other immune-related genes, suggesting a protective effect. These findings support the health benefits of BSFL and sodium butyrate during an immune challenge.

Allometric equations were developed for estimating aboveground biomass carbon (AGBC) in five tree species grown in a tree-based intercropping system at the University of Guelph Agroforestry Research Station, Guelph, Ontario, Canada. A total of 66 representative trees from five species: red oak (Quercus rubra) [n = 12], black walnut (Juglans nigra) [n = 16], black locust (Robinia pseudoacacia) [n = 10], white ash (Fraxinus americana) [n = 15], Norway spruce (Picea abies) [n = 13] were selected, harvested and their aboveground biomass and carbon content were quantified. Three commonly used allometric models were used to develop predictive equations. Regression models were developed and parameterized for each tree species and the best are presented based on information criteria (AIC, AICc, and BIC), mean absolute percentage error (MAPE), over/under estimation (MOUE), root mean square error (RMSE), R², and regression coefficients (a, b) of the observed/predicted (OP) linear regression analysis. All equations with diameter at breast height (D) only and D and tree height (H) as the predictor variables fitted the AGBC data well, with R² > 97% and RMSE < 40. However, a power model using D as the only predictor is recommended as the best model for black walnut, black locust, white ash, and Norway spruce. The models presented are the best fitted allometric equations for the indicated species and are recommended for these species, growing on similar soils under the same temperate conditions at densities of < 125 tree per hectare.

Allometric equations were developed for estimating above-ground biomass carbon (AGBC) sequestration in five tree species grown in a tree-based intercropping system at the University of Guelph Agroforestry Research Station (GARS), Guelph, Ontario, Canada. A total of 66 representative trees from five species: Red Oak (Quercus rubra) [n = 12], Black Walnut (Juglans nigra) [n = 16], Black Locust (Robinia pseudoacacia) [n = 10], White Ash (Fraxinus americana) [n = 15], Norway Spruce (Picea abies) [n = 13] were selected, harvested and their aboveground biomass and C content were quantified. Three commonly used allometric models were used to develop predictive equations. Regression models were developed and parameterized for each tree species and the best are presented based on information criteria (AIC, AICc, and BIC), mean absolute percentage error (MAPE), over/under estimation (MOUE), root mean square error (RMSE), R², and regression coefficients (a, b) of the observed/predicted (OP) linear regression analysis. All equations with diameter at breast height (D) only and D and tree height (H) as the predictor variables fitted the AGBC data well, with R² > 97% and RMSE < 40. However, a power model using D as the only predictor is recommended as the best model for Black Walnut, Black Locust, White Ash, and Norway Spruce. The models presented are the best fitted allometric equations for the indicated species and are recommended for these species, growing on similar soils under the same temperate conditions at densities of < 100 trees per hectare.

Carbon (C) storage potential was quantified for four tree species which are commonly incorporated into tree-based intercropping (TBI) systems and compared with conventional agricultural systems in southern Ontario, Canada. In the 31-year-old TBI system at the University of Guelph's Agroforestry Research Station, Norway spruce (Picea abies), white cedar (Thuja occidentalis), black walnut (Juglans nigra) and red oak (Quercus rubra) were planted in tree rows, intercropped with soybean (Glycine max). In the conventional agricultural field, soybean was grown in a monocropping system. Above and belowground tree and crop C content, soil organic C (SOC) and system level C was quantified for each tree species as well as the conventional agricultural system. Red oak TBI systems had the highest SOC followed by black walnut, Norway spruce and white cedar with values of 93.2, 83.9, 78.1, and 72.2 t C ha-1, respectively. Red oak TBI systems also had the highest mean tree C content, followed by black walnut, Norway spruce and white cedar, with values of 299.7, 285.8, 255.4 and 70.1 kg C tree-1, respectively. Total system level C, which incorporated SOC, tree C content and tree planting densities was 134.8, 126.4, 115.7, 95.6 and 75.6 t C ha-1 respectively for spruce, oak, walnut and cedar TBI systems and the agricultural field. TBI systems provide higher C sequestration potentials than conventional agricultural fields, and Norway spruce and red oak should be included into TBI systems in southern Ontario to maximize C sequestration benefits.

Riparian zones provide multiple benefits, including streambank stabilization and nutrient abatement. However, there is a knowledge gap on how the type of vegetation and environmental factors (e.g., soil temperature, moisture) within the riparian zone influence CO₂ and CH₄ emissions. Our objective was to quantify and compare CO₂ and CH₄ emissions from a herbaceous (grass) riparian zone (GRS), a rehabilitated riparian zone composed of deciduous trees, an undisturbed natural forested riparian zone with deciduous trees (UNF‐D) or coniferous trees (UNF‐C), and an agricultural field. Cumulative soil CO₂ emission ranged from 23 to 105 g CO₂–C m^–2. Carbon dioxide emissions were greatest (p < .05) in the GRS zone and lowest (p < .05) in the UNF‐C riparian zone. The best predictors for CO₂ emissions were soil temperature and soil organic carbon (SOC) content. Cumulative CH₄ emission ranged from –23 to 253 g CH₄–C m^–2. Methane emissions were greatest (p < .05) in the UNF‐D and lowest (p < .05) in the GRS riparian zone. The best predictors for CH₄ emissions were soil moisture, SOC, and photosynthetic photon flux density. The total CO₂–C equivalent (i.e., CH₄ + CO₂) was greatest (p < .05) for the GRS and lowest (p < .05) for the UNF‐C riparian zone. The environmental factors controlling CO₂ and CH₄ emissions within the various riparian zones did not change; instead, changes were due to how vegetation within riparian zones influenced these controls.

Warm season perennial C4 grasses (WSGs), switchgrass (Panicum virgatum L.) and miscanthus species (Miscanthus spp.), have been reported to positively influence short-term (15–20 years) soil organic carbon (SOC). In this study, the DayCent model was used to predict changes in long-term SOC stocks under WSGs for moderate (Representative Concentration Pathway (RCP) 4.5) and high (RCP 8.5) warming climate change scenarios in southern Ontario, Canada, and to determine how long the enhanced SOC stock will last when WSGs are converted back to annual crop rotation. The model predicted that a consistent corn–corn–soybean–winter wheat (CCSW) rotation prevented SOC from depletion over the 21st century. Under WSGs, the model predicted high rates of SOC sequestration during the first 20–30 years which then tended to stabilize after 50–60 years. However, the rate of SOC sequestration over 90 years for RCP 4.5 was 0.26 and 0.94 Mg C ha⁻¹ yr⁻¹ for switchgrass and miscanthus, respectively. If 40-year stands of WSGs are converted back to CCSW, the model predicted SOC decline to the previous level in 40–50 years. DayCent predicted that under RCP 8.5 scenario in the second half of the 21st century and in the future, there will be a reduction in SOC stocks, especially under miscanthus stands.