This work aims to contextualize and analyze the potential contribution of pecan to SDG2 under the dual perspective of carbon storage and human nutrition. Particularly, the study focuses on the pecan agroecosystems in the Americas, representing the most important pecan-producing countries (the United States, Mexico, Brazil, Argentina, Uruguay, and Peru). We observed that pecan is a reliable sink for storing atmospheric C and also for quality nuts with high nutritional density. The Americas, hold a population of ca. 23 M pecan trees, with the younger tree populations and the highest C-storing potential in South America. This pecan tree population has removed 51.3 Mt CO2eq immobilizing the OC in their aboveground biomass, but if the C sequestration for the whole system is considered, the value reaches nearly 80 Mt CO2eq. From a nutritional perspective, there are different dietary needs to cover according to the country, although the common analysis output is a low proportion of nuts in the diet, which is expected to improve, given the efforts of each country to promote domestic consumption. All the mentioned countries in this study have a low pecan consumption going from 8 to 293 g per capita yr^-1, which in the light of the Global Burden of Disease represents 0.08 to 3.2% of the recommended yearly dietary basis for nuts overall. The inclusion of pecan nuts in the daily diet is of utmost importance to offset the food nutrient dilution carbohydrates-based, linked to the excess of atmospheric CO₂. Also, pecan orchards function as a platform to integrate sustainable systems. The global benefit of having pecan and alley crops has been proved in regions other than the Americas with interesting economic outputs leading to energizing the life of rural communities. Pecan orchards and pecan agroforestry may lead to sustainable agri-food systems, with global gains in SOC and nutritional richness and diversity. Therefore, more in-depth studies are needed not only to fully understand the functioning of the systems at a productive level but also to design and plan sustainable landscapes in rural land.

Anaerobically digested dairy manure (AD) has been proposed as an alternative nitrogen source to reduce soil nitrous oxide (N₂O) emissions compared with raw dairy manure (RM). The aim of this research was to compare soil N₂O emissions associated with AD and RM according to three application methods: surface broadcasting (SB), incorporation (SBI), and injection (INJ). The field experiment was conducted on a loam soil at Elora, ON, from November 2012 to November 2014, using a randomized block design with four replications. Manure was applied in mid-November (fall), and corn (Zea mays) was planted in late-May of each year. Nitrous oxide flux was measured using nonsteady state chambers sampled weekly or bi-weekly. Cumulative N₂O emissions were significantly affected by the interaction between source and method (F = 3.99, P < 0.01), with the highest value for surface broadcast AD (6.4 kg N₂O-N ha⁻¹) and the lowest value for injected AD (2.6 kg N₂O-N ha⁻¹). Manure source affected cumulative N₂O emissions (F = 4.67, P < 0.1), with the largest emissions for AD (4.8 kg N₂O-N ha⁻¹). Anaerobically digested manure was proven to reduce cumulative N₂O emissions when it was fall injected to corn in cold climates; however, if AD is broadcasted or broadcasted and incorporated, it may result in greater N₂O emissions than those produced by RM.

Soil nitrous oxide (N₂O) fluxes are commonly measured with nonsteady state chambers using slope values derived from linear or quadratic regression, fitted to the change in N₂O concentration over time (dC/dt); however, these methods frequently underestimate N₂O flux values. Here, we propose a decision tree-based model (DTBM) to better match curve shape with linear and nonlinear models to estimate dC/dt. The DTBM was compared with linear, quadratic regression, and the Hutchinson–Mosier (H–M) equation. The objectives were to (i) evaluate curve shape classification; (ii) evaluate dC/dt response to uncertainty, and (iii) determine method effect on cumulative N₂O emissions and emission factor. Curve shapes with increasing N₂O concentration over time had the highest proportion of data (52%–55%). Mean N₂O flux calculated with DTBM showed to be less responsive to data variability, and therefore, more stable than the other methods. Data classification included in DTBM offered an improved method for calculating cumulative N₂O emissions in low-flux situations, whereas under a high-flux situation, all methods tested were acceptable to calculate N₂O emissions. The DTBM proved to be a robust method of matching each data type with the best model for calculating an individual flux and to accurately calculate cumulative N₂O emissions.

During the last 20 years, agronomists, environmentalists and related researchers have conveyed the need of producing enough food to satisfy the growing population demand, with minimum environmental footprint. Under this framework, the need for a “sustainable intensification” (SI) of agriculture has arisen, being a concept deeply contested the last several years. We aim to shed some light on the matter from the point of view of both environmental philosophy and agri-environmental sciences. We found that the lack of clarity exposes the conceptual limits of SI, since its attributions are far from being extrapolated, for example, to animal production. Agricultural science should ensure that stakeholders understand the facts and implications of SI before implementing them. In addition, if understood only as either a set of practices or a sort of panacea, SI will be closer to fail for stakeholders’ expectations. Then, a key concern we have highlighted is one which should compel agri-environmental scientists and environmental philosophers alike to hold such conceptual frameworks accountable. Ensuring communities and public actors make informed choices about food security requires that shared goals between our disciplines are enacted in research, with community well-being as a core consideration of any debate regarding sustainability.