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Agroecology can promote climate change adaptation outcomes without compromising yield in smallholder systems

Sieglinde Snapp Yodit Kebede Eva Wollenberg (2023, [Artículo])

A critical question is whether agroecology can promote climate change mitigation and adaptation outcomes without compromising food security. We assessed the outcomes of smallholder agricultural systems and practices in low- and middle-income countries (LMICs) against 35 mitigation, adaptation, and yield indicators by reviewing 50 articles with 77 cases of agroecological treatments relative to a baseline of conventional practices. Crop yields were higher for 63% of cases reporting yields. Crop diversity, income diversity, net income, reduced income variability, nutrient regulation, and reduced pest infestation, indicators of adaptative capacity, were associated with 70% or more of cases. Limited information on climate change mitigation, such as greenhouse gas emissions and carbon sequestration impacts, was available. Overall, the evidence indicates that use of organic nutrient sources, diversifying systems with legumes and integrated pest management lead to climate change adaptation in multiple contexts. Landscape mosaics, biological control (e.g., enhancement of beneficial organisms) and field sanitation measures do not yet have sufficient evidence based on this review. Widespread adoption of agroecological practices and system transformations shows promise to contribute to climate change services and food security in LMICs. Gaps in adaptation and mitigation strategies and areas for policy and research interventions are finally discussed.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CLIMATE CHANGE CROPS FOOD SUPPLY GAS EMISSIONS GREENHOUSE GASES FARMING SYSTEMS AGROECOLOGY FOOD SECURITY LESS FAVOURED AREAS SMALLHOLDERS YIELDS NUTRIENTS BIOLOGICAL PEST CONTROL CARBON SEQUESTRATION LEGUMES

Modeling the growth, yield and N dynamics of wheat for decoding the tillage and nitrogen nexus in 8-years long-term conservation agriculture based maize-wheat system

C.M. Parihar Dipaka Ranjan Sena Prakash Chand Ghasal Shankar Lal Jat Yashpal Singh Saharawat Mahesh Gathala Upendra Singh Hari Sankar Nayak (2024, [Artículo])

Context: Agricultural field experiments are costly and time-consuming, and their site-specific nature limits their ability to capture spatial and temporal variability. This hinders the transfer of crop management information across different locations, impeding effective agricultural decision-making. Further, accurate estimates of the benefits and risks of alternative crop and nutrient management options are crucial for effective decision-making in agriculture. Objective: The objective of this study was to utilize the Crop Environment Resource Synthesis CERES-Wheat model to simulate crop growth, yield, and nitrogen dynamics in a long-term conservation agriculture (CA) based wheat system. The study aimed to calibrate the model using data from a field experiment conducted during the 2019-20-2020-21 growing seasons and evaluation it with independent data from the year 2021–22. Method: Crop simulation models, such as the Crop Environment Resource Synthesis CERES-Wheat (DSSAT v 4.8), may provide valuable insights into crop growth and nitrogen dynamics, enabling decision makers to understand and manage production risk more effectively. Therefore, the present study employed the CERES-Wheat (DSSAT v 4.8) model and calibrated it using field data, including plant phenological phases, leaf area index, aboveground biomass, and grain yield from the 2019-20-2020-21 growing seasons. An independent dataset from the year 2021–22 was used for model evaluation. The model was used to investigate the relationship between growing degree days (GDD), temperature, nitrate and ammonical concentration in soil, and nitrogen uptake by the crop. Additionally, the study explored the impact of contrasting tillage practices and fertilizer nitrogen management options on wheat yields. The experimental site is situated at ICAR-Indian Agricultural Research Institute (IARI), New Delhi, representing Indian Trans-Gangetic Plains Zone (28o 40’N latitude, 77o 11’E longitude and an altitude of 228 m above sea level). The treatments consist of four nitrogen management options, viz., N0 (zero nitrogen), N150 (150 kg N ha−1 through urea), GS (Green seeker based urea application) and USG (urea super granules @150 kg N ha−1) in two contrasting tillage systems, i.e., CA-based zero tillage (ZT) and conventional tillage (CT). Result: The outcomes exhibited favorable agreement between the model’s simulations and the observed data for crop phenology (With less than 2 days variation in 50% onset of flowering), grain and biomass yield (Root mean square error; RMSE 336 kg ha−1 and 649 kg ha−1, respectively), and leaf area index (LAI) (RMSE 0.28 & normalized RMSE; nRMSE 6.69%). The model effectively captured the nitrate-N (NO3−-N) dynamics in the soil profile, exhibiting a remarkable concordance with observed data, as evident from its low RMSE = 12.39 kg ha−1 and nRMSE = 13.69%. Moreover, as it successfully simulated the N balance in the production system, the nitrate leaching and ammonia volatilization pattern as described by the model are highly useful to understand these critical phenomena under both conventional tillage (CT) and CA-based Zero Tillage (ZT) treatments. Conclusion: The study concludes that the DSSAT-CERES-Wheat model has significant potential to assess the impacts of tillage and nitrogen management practices on crop growth, yield, and soil nitrogen dynamics in the western Indo-Gangetic Plains (IGP) region. By providing reliable forecasts within the growing season, this modeling approach can facilitate better planning and more efficient resource management. Future implications: The successful implementation of the DSSAT-CERES-Wheat model in this study highlights its applicability in assessing crop performance and soil dynamics. Future research should focus on expanding the model’s capabilities by reducing its sensitivity to initial soil nitrogen levels to refine its predictions further. Moreover, the model’s integration with decision support systems and real-time data can enhance its usefulness in aiding agricultural decision-making and supporting sustainable crop management practices.

Nitrogen Dynamics Mechanistic Crop Growth Models Crop Simulation CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA NITROGEN CONSERVATION AGRICULTURE WHEAT MAIZE CROP GROWTH RATE SIMULATION MODELS

Economics of crop residue management

Vijesh Krishna Maxwell Mkondiwa (2023, [Artículo])

More than five billion metric tons of agricultural residues are produced annually worldwide. Despite having multiple uses and significant potential to augment crop and livestock production, a large share of crop residues is burned, especially in Asian countries. This unsustainable practice causes tremendous air pollution and health hazards while restricting soil nutrient recycling. In this review, we examine the economic rationale for unsustainable residue management. The sustainability of residue utilization is determined by several economic factors, such as local demand for and quantity of residue production, development and dissemination of technologies to absorb excess residue, and market and policy instruments to internalize the social costs of residue burning. The intervention strategy to ensure sustainable residue management depends on public awareness of the private and societal costs of open residue burning.

Crop Biomass Residue Burning Environmental Effects CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CROPS BIOMASS RESIDUES ENVIRONMENTAL IMPACT CLIMATE CHANGE SMALLHOLDERS TECHNOLOGY ADOPTION

Simulación del escurrimiento directo de eventos en cuencas pequeñas con el modelo Hidras

Antonio Quevedo Tiznado NABIL MOBAYED KHODR CARLOS FUENTES RUIZ Enrique Gonzalez Sosa CARLOS ALBERTO CHAVEZ GARCIA (2016, [Artículo])

El escurrimiento directo es el efecto integrado de la lluvia, intercepción, evapotranspiración, infiltración y el escurrimiento en lámina sobre el terreno, en un punto específico de una cuenca. La conversión de las lluvias a escurrimiento es un proceso complejo que depende tanto de la distribución espacial y temporal de las lluvias como de las características físicas de la cuenca. Este estudio tuvo por objetivo plantear procedimientos para simular el escurrimiento directo a escala de evento en cuencas pequeñas. Como casos de estudio se eligieron dos cuencas experimentales de México con características diferentes en cuanto a tamaño, ubicación, tipo de vegetación, topografía y régimen pluviométrico: río Mixcoac, en el valle de México; y la unidad de escurrimiento Cerro Blanco, en Tabasco.

Hidrogramas sintéticos Modelación hidrológica Calibración de hidrogramas INGENIERÍA Y TECNOLOGÍA