Escenarios futuros de eventos extremos de precipitación y temperatura en México

Future changes of precipitation and temperature extremes in Mexico

Ernesto Ramos Esteban (2024, [Tesis de maestría])

Diferentes estudios a escala mundial indican un incremento en frecuencia de eventos climáticos extremos debido al calentamiento global y sugieren que podrían intensificarse en el futuro. El objetivo de este trabajo es analizar los posibles cambios de 12 índices climáticos extremos (ICE) de precipitación y temperatura en 15 regiones de México, el sur de los Estados Unidos y Centroamérica para un período histórico (1981-2010), un futuro cercano (2021-2040), un futuro intermedio (2041-2060) y un futuro lejano (2080-2099). Se utilizó el reanálisis ERA5 como referencia en la evaluación histórica de los modelos climáticos globales (MCG) y para las proyecciones se analizaron los ICE de diez MCG del Proyecto de Intercomparación de Modelos Climáticos, fase 6 (CMIP6), de acuerdo con dos escenarios de Vías Socioeconómicas Compartidas (SSPs), uno de bajas emisiones (SSP2-4.5) y otro de altas emisiones (SSP3-7.0). Los MCG reproducen muy bien los índices extremos de temperatura histórica y los días consecutivos secos, pero subestiman la lluvia promedio y la lluvia extrema en las zonas más lluviosas desde el centro de México hasta Centroamérica. Históricamente, se observaron tendencias positivas de las temperaturas extremas (TXx y TNn) en todas las regiones, pero sólo en algunas regiones fueron significativas, mientras que los índices de lluvia extrema (R95p, R10mm y R20mm) presentaron tendencias negativas, pero pequeñas. Las proyecciones indican que las temperaturas extremas podrían seguir incrementándose en el futuro, desde 2° C hasta 5° C a mitad y final de siglo, respectivamente. La contribución de la precipitación extrema arriba del percentil 95 (R95p) se podría incrementar entre un 10 % y 30 %, especialmente en la región subtropical, mientras que la precipitación podría disminuir en las regiones tropicales. Este estudio es el primero que analiza los cambios futuros de índices extremos del CMIP6 a escala regional (en 15 regiones) de México, el sur de Estados Unidos y Centroamérica.

Global-scale studies indicate an increase in the frequency of extreme weather events due to global warming and suggest that they could further intensify in the future. This study aims to assess potential changes in 12 extreme climate indices (ECI) related to precipitation and temperature in 15 regions in Mexico, the southern United States, and Central America for different periods: a historical period (1981-2010), a near future (2021-2040), an intermediate future (2041-2060), and a far future (2080-2099). The ERA5 reanalysis was used as a reference for the historical evaluation of global climate models (GCMs), and ECI from ten GCMs of phase 6 (CMIP6) from the Coupled Model Intercomparison Project were employed for the projections and examined under two Shared Socioeconomic Pathways (SSPs) scenarios, one characterized by low emissions (SSP2-4.5) and another representing high greenhouse gas emissions (SSP3-7.0). The GCMs reproduce historical extreme temperature indices and consecutive dry days very well. However, they underestimate average and extreme rainfall from central Mexico to Central America in the wetter areas. Historically, positive trends in extreme temperatures (TXx and TNn) were observed across all regions. However, statistical significance was only present in certain regions, while extreme rainfall indices (R95p, R10mm, and R20mm) exhibited small negative trends. The projections suggest that extreme temperatures could continue to increase in the future, from 2°C to 5°C by the mid and late century, respectively. The contribution of extreme precipitation above the 95th percentile (R95p) could increase by 10% to 30%, particularly in the subtropical regions, while precipitation might decrease in tropical regions. This study is the first to analyze future changes in extreme indices from CMIP6 at a regional scale (across 15 regions) in Mexico, the southern United States, and Central America.

Centroamérica, CMIP6, escenarios SSP, extremos climáticos, intercomparación de modelos climáticos, México Central America, climate extremes, CMIP6, intercomparison of climate models, Mexico, SSP scenarios CIENCIAS FÍSICO MATEMÁTICAS Y CIENCIAS DE LA TIERRA CIENCIAS DE LA TIERRA Y DEL ESPACIO OCEANOGRAFÍA OCEANOGRAFÍA FÍSICA (VE R 5603 .04) OCEANOGRAFÍA FÍSICA (VE R 5603 .04)

Optimizing nitrogen fertilizer and planting density levels for maize production under current climate conditions in Northwest Ethiopian midlands

Kindie Tesfaye Dereje Ademe Enyew Adgo (2023, [Artículo])

This study determined the most effective plating density (PD) and nitrogen (N) fertilizer rate for well-adapted BH540 medium-maturing maize cultivars for current climate condition in north west Ethiopia midlands. The Decision Support System for Agrotechnology Transfer (DSSAT)-Crop Environment Resource Synthesis (CERES)-Maize model has been utilized to determine the appropriate PD and N-fertilizer rate. An experimental study of PD (55,555, 62500, and 76,900 plants ha−1) and N (138, 207, and 276 kg N ha−1) levels was conducted for 3 years at 4 distinct sites. The DSSAT-CERES-Maize model was calibrated using climate data from 1987 to 2018, physicochemical soil profiling data (wilting point, field capacity, saturation, saturated hydraulic conductivity, root growth factor, bulk density, soil texture, organic carbon, total nitrogen; and soil pH), and agronomic management data from the experiment. After calibration, the DSSAT-CERES-Maize model was able to simulate the phenology and growth parameters of maize in the evaluation data set. The results from analysis of variance revealed that the maximum observed and simulated grain yield, biomass, and leaf area index were recorded from 276 kg N ha−1 and 76,900 plants ha−1 for the BH540 maize variety under the current climate condition. The application of 76,900 plants ha−1 combined with 276 kg N ha−1 significantly increased observed and simulated yield by 25% and 15%, respectively, compared with recommendation. Finally, future research on different N and PD levels in various agroecological zones with different varieties of mature maize types could be conducted for the current and future climate periods.

Maize Model Planting Density CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MAIZE MODELS SPACING NITROGEN FERTILIZERS YIELDS

“Mexico half way of making”: Carlos Chávez and the foundation of the National Institute of Fine Arts (INBA) (1945-1947)

Ana Garduño (2023, [Artículo, Artículo])

I am focusing on the interaction between a cultural agent, Carlos Chávez, and the government elite, related to the circumstances of the enunciation of a public and official organism, INBA (The National Institute of Fine Arts), because I assume that political relations are fundamental to understand a process that endorsed the official culture as an appendage of politics. In spite of its relevance, this subject has not been studied. Based on archival documentation (at the National Archive of Mexico and the archive of INBA) I am examining the cultural policies derived from the foundation of INBA. Due to the current pandemic situation, it was not possible to consult other documental sources. I am formulating that the concept of “high culture” was at the core of a wider conflict between governmental interests and those of representative social actors, and I conclude that this obstacle would have conferred a major political and symbolical importance to the Institute, and consequently, would restrict its budget.

Carlos Chávez INBA Agentes culturales Políticas institucionales Centralización artística HUMANIDADES Y CIENCIAS DE LA CONDUCTA HUMANIDADES Y CIENCIAS DE LA CONDUCTA Foundation of the National Institute of Fine Arts in Mexico (INBA), Cultural agents Institutional policies Artistic centralization

Structural violence against children in Chihuahua

Hector Castro-Loera Gabriela Orozco Lopez (2022, [Artículo, Artículo])

Within the framework of philosophy and its social function, structural violence against children in Chihuahua is studied; To approach the phenomenon and propose alternatives, three theories will be related: i) feminist studies regarding violence, concepts such as intersectionality, pedagogies of cruelty and structural violence will be used, ii) the philosophy of children's rights, child´s play will be appreciated as a necessity and legal position of freedom, and iii) the event of the Aufklärung, that is, the assimilation of the present of humanity or the Enlightenment in Foucault's thought.

Structural violence Philosophy and children´s rights Chihuahua Violencia estructural Filosofía y derechos de niños CIENCIAS SOCIALES CIENCIAS SOCIALES

Using an incomplete block design to allocate lines to environments improves sparse genome-based prediction in plant breeding

Osval Antonio Montesinos-Lopez ABELARDO MONTESINOS LOPEZ RICARDO ACOSTA DIAZ Rajeev Varshney Jose Crossa ALISON BENTLEY (2022, [Artículo])

Genomic selection (GS) is a predictive methodology that trains statistical machine-learning models with a reference population that is used to perform genome-enabled predictions of new lines. In plant breeding, it has the potential to increase the speed and reduce the cost of selection. However, to optimize resources, sparse testing methods have been proposed. A common approach is to guarantee a proportion of nonoverlapping and overlapping lines allocated randomly in locations, that is, lines appearing in some locations but not in all. In this study we propose using incomplete block designs (IBD), principally, for the allocation of lines to locations in such a way that not all lines are observed in all locations. We compare this allocation with a random allocation of lines to locations guaranteeing that the lines are allocated to

the same number of locations as under the IBD design. We implemented this benchmarking on several crop data sets under the Bayesian genomic best linear unbiased predictor (GBLUP) model, finding that allocation under the principle of IBD outperformed random allocation by between 1.4% and 26.5% across locations, traits, and data sets in terms of mean square error. Although a wide range of performance improvements were observed, our results provide evidence that using IBD for the allocation of lines to locations can help improve predictive performance compared with random allocation. This has the potential to be applied to large-scale plant breeding programs.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA Bayes Theorem Genome Inflammatory Bowel Diseases Models, Genetic Plant Breeding

Maize seed aid and seed systems development: Opportunities for synergies in Uganda

Jason Donovan Rachel Voss Pieter Rutsaert (2024, [Artículo])

In the name of food security, governments and NGOs purchase large volumes of maize seed in non-relief situations to provide at reduced or no cost to producers. At the same time, efforts to build formal maize seed systems have been frustrated by slow turnover rates – the dominance of older seed products in the market over newer, higher performing ones. Under certain conditions, governments and NGO seed aid purchases can support formal seed systems development in three ways: i) support increased producer awareness of new products, ii) support local private seed industry development, and iii) advance equity goals by targeting aid to the most vulnerable of producers who lack the capacity to purchase seeds. This study explores the objectives and activities of seed aid programmes in Uganda and their interactions with the maize seed sector. We draw insights from interviews with representatives of seed companies, NGOs and government agencies, as well as focus group discussions with producers. The findings indicated that seed aid programme objectives are largely disconnected from broader seed systems development goals. There is little evidence of public-private collaboration in design of these programmes. Better designed programs have the potential to align with varietal turnover objectives, commercial sector development and targeting of underserved markets could promote equity and ‘crowd in’ demand.

Seed Business Varietal Turnover Seed Aid CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA SEED SEED SYSTEMS SOCIAL INCLUSION MAIZE

Advancing the science and practice of ecological nutrient management for smallholder farmers

Sieglinde Snapp (2022, [Artículo])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA AGROECOLOGY DEGRADATION NUTRIENT CYCLES NUTRIENT USE EFFICIENCY SOIL ORGANIC MATTER SMALLHOLDERS

Big data, small explanatory and predictive power: Lessons from random forest modeling of on-farm yield variability and implications for data-driven agronomy

Martin van Ittersum (2023, [Artículo])

Context: Collection and analysis of large volumes of on-farm production data are widely seen as key to understanding yield variability among farmers and improving resource-use efficiency. Objective: The aim of this study was to assess the performance of statistical and machine learning methods to explain and predict crop yield across thousands of farmers’ fields in contrasting farming systems worldwide. Methods: A large database of 10,940 field-year combinations from three countries in different stages of agricultural intensification was analyzed. Random effects models were used to partition crop yield variability and random forest models were used to explain and predict crop yield within a cross-validation scheme with data re-sampling over space and time. Results: Yield variability in relative terms was smallest for wheat and barley in the Netherlands and for wheat in Ethiopia, intermediate for rice in the Philippines, and greatest for maize in Ethiopia. Random forest models comprising a total of 87 variables explained a maximum of 65 % of cereal yield variability in the Netherlands and less than 45 % of cereal yield variability in Ethiopia and in the Philippines. Crop management related variables were important to explain and predict cereal yields in Ethiopia, while predictive (i.e., known before the growing season) climatic variables and explanatory (i.e., known during or after the growing season) climatic variables were most important to explain and predict cereal yield variability in the Philippines and in the Netherlands, respectively. Finally, model cross-validation for regions or years not seen during model training reduced the R2 considerably for most crop x country combinations, while for wheat in the Netherlands this was model dependent. Conclusion: Big data from farmers’ fields is useful to explain on-farm yield variability to some extent, but not to predict it across time and space. Significance: The results call for moderate expectations towards big data and machine learning in agronomic studies, particularly for smallholder farms in the tropics where model performance was poorest independently of the variables considered and the cross-validation scheme used.

Model Accuracy Model Precision Linear Mixed Models CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MACHINE LEARNING SUSTAINABLE INTENSIFICATION BIG DATA YIELDS MODELS AGRONOMY

Teacher training in the state of Chihuahua: Between the health challenge and teacher resilience

Evangelina Cervantes Holguín Pavel Roel Gutiérrez Sandoval Cely Celene Ronquillo Chávez (2023, [Artículo, Artículo])

The article proposes to recover the response of the Teacher Training and Updating Institutions in the state of Chihuahua regarding the various challenges imposed by the Coronavirus Disease (COVID-19). The qualitative exercise analyzes the experience of 10 institutions based on the voice of their students, teachers, and principals regarding changes in academic, administrative, and organizational processes. It is concluded that the pandemic has affected each institution in different ways and with diverse intensity. Despite the achievements, the experience analyzed reveals the relative success of the using virtual platforms in the face of three basic conditions: connectivity, technological competencies, and socio-emotional skills of the teaching staff. It highlights the importance of implementing tutoring, resilience, or awareness actions of teachers and students' needs, feelings, and sufferings. It is opportune to recover the experiences of other institutions and to question especially students, thesis students and graduates.

Acceso a la educación Aprendizaje en línea Educación a distancia Formación de docentes Tecnología educacional HUMANIDADES Y CIENCIAS DE LA CONDUCTA HUMANIDADES Y CIENCIAS DE LA CONDUCTA Access to education online learning distance education teacher education educational technology

Genetic effects of Rht-B1b and Rht-D1b dwarfing alleles on plant height and agronomic traits of bread wheat (Triticum aestivum L.) breeding lines

Zine El Abidine Fellahi Abderrahmane Hannachi Susanne Dreisigacker deepmala sehgal Hamenna Bouzerzour (2023, [Artículo])

Pleiotropic Effects Reduced Height Genes CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA PLANT HEIGHT TRITICUM AESTIVUM YIELD COMPONENTS ALLELES BREEDING LINES