Short-term effects of four tillage practices on soil physical properties, soil water potential, and maize yield

The area cultivated using conservation tillage has recently increased in central Spain. However, soil compaction and water retention with conservation tillage still remains a genuine concern for landowners in this region be- cause of its potential effect on the crop growth and yield. The aim of this research is to determine the short- term influences of four tillage treatments on soil physical properties. In the experiment, bulk density, cone index, soil water potential, soil temperature and maize (Zea mays L.) productivity have been measured. A field experiment was established in spring of 2013 on a loamy soil. The experiment compared four tillage methods (zero tillage, ZT; reservoir tillage, RT; minimum tillage, MT; and conventional tillage, CT). Soil bulk density and soil cone index were measured during maize growing season and at harvesting time. Furthermore, the soil water potential was monitored by using a wireless sensors network with sensors at 20 and 40 cm depths. Also, soil temperatures were registered at depths of 5 and 12 cm. Results indicated that there were significant differ- ences between soil bulk density and cone index of ZT method and those of RT, MT, and CT, during the growing season; although, this difference was not significant at the time of harvesting in some soil layers. Overall, in most soil layers, tillage practice affected bulk density and cone index in the order: ZT N RT N MT N CT. Regardless oftheentireobservationperiod,results exhibited that soils under ZT and RT treatments usually resulted in higher water potential and lower soil temperature than the other two treatments at both soil depths. In addition, clear differences in maize grain yield were observed between ZT and CT treatments, with a grain yield (up to 15.4%) increase with the CT treatment. On the other hand, no significant differences among (RT, MT, and CT) on maizeyieldwerefound.Inconclusion,the impact of soil compaction increase and soil temperature decrease,pro- duced by ZT treatment is a potential reason for maize yield reduction in this tillage method. We found that RT could be certainly a viable option for farmers incentral Spain,particularly when switching to conservation tillage from conventional tillage. This technique showed a moderate and positive effect on soil physical properties and increased maize yields compared to ZT and MT, and provides an opportunity to stabilize maize yields compared to CT.

Dynamical influences of El Niño on maize yield in Spain

Climate variability and changes in the frequency of extremes events have a direct impact on crop damages and yield. In a former work of Capa et al. (2013) the crop yield variability has been studied using different reanalyses datasets with the aim of extending the time series of potential yield. The reliability of these time series have been checked using observational data. The influence of the sea surface temperature on the crop yield variability has been studied, finding a relation with El Niño phenomenon. The highest correlation between El Niño and yield was during 1960-1980. This study aims to analyse the dynamical mechanism of El Niño impacts on maize yield in Spain during 1960-1980 by comparison with atmospheric circulation patterns.

El Niño influence on potential maize yield in Iberian Peninsula

El Niño phenomenon is the leading mode of sea surface temperature interannual variability. It can affect weather patterns worldwide and therefore crop production. Crop models are useful tools for impact and predictability applications, allowing to obtain long time series of potential and attainable crop yield, unlike to available time series of observed crop yield for many countries. Using this tool, crop yield variability in a location of Iberia Peninsula (IP) has been previously studied, finding predictability from Pacific El Niño conditions. Nevertheless, the work has not been done for an extended area. The present work carries out an analysis of maize yield variability in IP for the whole twenty century, using a calibrated crop model at five contrasting Spanish locations and reanalyses climate datasets to obtain long time series of potential yield. The study tests the use of reanalysis data for obtaining only climate dependent time series of crop yield for the whole region, and to use these yield to analyze the influences of oceanic and atmospheric patterns. The results show a good reliability of reanalysis data. The spatial distribution of the leading principal component of yield variability shows a similar behaviour over all the studied locations in the IP. The strong linear correlation between El Niño index and yield is remarkable, being this relation non-stationary on time, although the air temperature-yield relationship remains on time, being the highest influences during grain filling period. Regarding atmospheric patterns, the summer Scandinavian pattern has significant influence on yield in IP. The potential usefulness of this study is to apply the relationships found to improving crop forecasting in IP.

Strategies for adapting maize to climate change and extreme temperatures in Andalusia, Spain

Climate projections indicate that rising temperatures will affect summer crops in the southern Iberian Peninsula. The aim of this study was to obtain projections of the impacts of rising temperatures, and of higher frequency of extreme events on irrigated maize, and to evaluate some adaptation strategies. The study was conducted at several locations in Andalusia using the CERES-Maize crop model, previously calibrated/validated with local experimental datasets. The simulated climate consisted of projections from regional climate models from the ENSEMBLES project; these were corrected for daily temperature and precipitation with regard to the E-OBS observational dataset. These bias-corrected projections were used with the CERES-Maize model to generate future impacts. Crop model results showed a decrease in maize yield by the end of the 21st century from 6 to 20%, a decrease of up to 25% in irrigation water requirements, and an increase in irrigation water productivity of up to 22%, due to earlier maturity dates and stomatal closure caused by CO2 increase. When adaptation strategies combining earlier sowing dates and cultivar changes were considered, impacts were compensated, and maize yield increased up to 14%, compared with the baseline period (1981-2010), with similar reductions in crop irrigation water requirements. Effects of extreme maximum temperatures rose to 40% at the end of the 21st century, compared with the baseline. Adaptation resulted in an overall reduction in extreme Tmax damages in all locations, with the exception of Granada, where losses were limited to 8%.

Effect of conservation tillage on soil physical properties, in-situ rainwater harvesting, and erosion control in arid and semi-arid regions

La escasez del agua en las regiones áridas y semiáridas se debe a la escasez de precipitaciones y la distribución desigual en toda la temporada, lo que hace de la agricultura de secano una empresa precaria. Un enfoque para mejorar y estabilizar el agua disponible para la producción de cultivos en estas regiones es el uso de tecnologías de captación de agua de lluvia in situ y su conservación. La adopción de los sistemas de conservación de la humedad del suelo in situ, tales como la labranza de conservación, es una de las estrategias para mejorar la gestión de la agricultura en zonas áridas y semiáridas. El objetivo general de esta tesis ha sido desarrollar una metodología de aplicación de labranza de depósito e investigar los efectos a corto plazo sobre las propiedades físicas del suelo de las diferentes prácticas de cultivo que incluyen labranza de depósito: (reservoir tillage, RT), la laboreo mínimo: (minimum tillage, MT), la no laboreo: (zero tillage, ZT) y laboreo convencional: (conventional tillage, CT) Así como, la retención de agua del suelo y el control de la erosión del suelo en las zonas áridas y semiáridas. Como una primera aproximación, se ha realizado una revisión profunda del estado de la técnica, después de la cual, se encontró que la labranza de depósito es un sistema eficaz de cosecha del agua de lluvia y conservación del suelo, pero que no ha sido evaluada científicamente tanto como otros sistemas de labranza. Los trabajos experimentales cubrieron tres condiciones diferentes: experimentos en laboratorio, experimentos de campo en una región árida, y experimentos de campo en una región semiárida. Para investigar y cuantificar el almacenamiento de agua a temperatura ambiente y la forma en que podría adaptarse para mejorar la infiltración del agua de lluvia recolectada y reducir la erosión del suelo, se ha desarrollado un simulador de lluvia a escala de laboratorio. Las características de las lluvias, entre ellas la intensidad de las precipitaciones, la uniformidad espacial y tamaño de la gota de lluvia, confirmaron que las condiciones naturales de precipitación son simuladas con suficiente precisión. El simulador fue controlado automáticamente mediante una válvula de solenoide y tres boquillas de presión que se usaron para rociar agua correspondiente a diferentes intensidades de lluvia. Con el fin de evaluar el método de RT bajo diferentes pendientes de superficie, se utilizaron diferentes dispositivos de pala de suelo para sacar un volumen idéntico para hacer depresiones. Estas depresiones se compararon con una superficie de suelo control sin depresión, y los resultados mostraron que la RT fue capaz de reducir la erosión del suelo y la escorrentía superficial y aumentar significativamente la infiltración. Luego, basándonos en estos resultados, y después de identificar la forma adecuada de las depresiones, se ha diseñado una herramienta combinada (sistema integrado de labranza de depósito (RT)) compuesto por un arado de una sola línea de chisel, una sola línea de grada en diente de pico, sembradora modificada, y rodillo de púas. El equipo fue construido y se utiliza para comparación con MT y CT en un ambiente árido en Egipto. El estudio se realizó para evaluar el impacto de diferentes prácticas de labranza y sus parámetros de funcionamiento a diferentes profundidades de labranza y con distintas velocidades de avance sobre las propiedades físicas del suelo, así como, la pérdida de suelo, régimen de humedad, la eficiencia de recolección de agua, y la productividad de trigo de invierno. Los resultados indicaron que la RT aumentó drásticamente la infiltración, produciendo una tasa que era 47.51% más alta que MT y 64.56% mayor que la CT. Además, los resultados mostraron que los valores más bajos de la escorrentía y pérdidas de suelos 4.91 mm y 0.65 t ha-1, respectivamente, se registraron en la RT, mientras que los valores más altos, 11.36 mm y 1.66 t ha-1, respectivamente, se produjeron en el marco del CT. Además, otros dos experimentos de campo se llevaron a cabo en ambiente semiárido en Madrid con la cebada y el maíz como los principales cultivos. También ha sido estudiado el potencial de la tecnología inalámbrica de sensores para monitorizar el potencial de agua del suelo. Para el experimento en el que se cultivaba la cebada en secano, se realizaron dos prácticas de labranza (RT y MT). Los resultados mostraron que el potencial del agua del suelo aumentó de forma constante y fue consistentemente mayor en MT. Además, con independencia de todo el período de observación, RT redujo el potencial hídrico del suelo en un 43.6, 5.7 y 82.3% respectivamente en comparación con el MT a profundidades de suelo (10, 20 y 30 cm, respectivamente). También se observaron diferencias claras en los componentes del rendimiento de los cultivos y de rendimiento entre los dos sistemas de labranza, el rendimiento de grano (hasta 14%) y la producción de biomasa (hasta 8.8%) se incrementaron en RT. En el experimento donde se cultivó el maíz en regadío, se realizaron cuatro prácticas de labranza (RT, MT, ZT y CT). Los resultados revelaron que ZT y RT tenían el potencial de agua y temperatura del suelo más bajas. En comparación con el tratamiento con CT, ZT y RT disminuyó el potencial hídrico del suelo en un 72 y 23%, respectivamente, a la profundidad del suelo de 40 cm, y provocó la disminución de la temperatura del suelo en 1.1 y un 0.8 0C respectivamente, en la profundidad del suelo de 5 cm y, por otro lado, el ZT tenía la densidad aparente del suelo y resistencia a la penetración más altas, la cual retrasó el crecimiento del maíz y disminuyó el rendimiento de grano que fue del 15.4% menor que el tratamiento con CT. RT aumenta el rendimiento de grano de maíz cerca de 12.8% en comparación con la ZT. Por otra parte, no hubo diferencias significativas entre (RT, MT y CT) sobre el rendimiento del maíz. En resumen, según los resultados de estos experimentos, se puede decir que mediante el uso de la labranza de depósito, consistente en realizar depresiones después de la siembra, las superficies internas de estas depresiones se consolidan de tal manera que el agua se mantiene para filtrarse en el suelo y por lo tanto dan tiempo para aportar humedad a la zona de enraizamiento de las plantas durante un período prolongado de tiempo. La labranza del depósito podría ser utilizada como un método alternativo en regiones áridas y semiáridas dado que retiene la humedad in situ, a través de estructuras que reducen la escorrentía y por lo tanto puede resultar en la mejora de rendimiento de los cultivos. ABSTRACT Water shortage in arid and semi-arid regions stems from low rainfall and uneven distribution throughout the season, which makes rainfed agriculture a precarious enterprise. One approach to enhance and stabilize the water available for crop production in these regions is to use in-situ rainwater harvesting and conservation technologies. Adoption of in-situ soil moisture conservation systems, such as conservation tillage, is one of the strategies for upgrading agriculture management in arid and semi-arid environments. The general aim of this thesis is to develop a methodology to apply reservoir tillage to investigate the short-term effects of different tillage practices including reservoir tillage (RT), minimum tillage (MT), zero tillage (ZT), and conventional tillage (CT) on soil physical properties, as well as, soil water retention, and soil erosion control in arid and semi-arid areas. As a first approach, a review of the state of the art has been done. We found that reservoir tillage is an effective system of harvesting rainwater and conserving soil, but it has not been scientifically evaluated like other tillage systems. Experimental works covered three different conditions: laboratory experiments, field experiments in an arid region, and field experiments in a semi-arid region. To investigate and quantify water storage from RT and how it could be adapted to improve infiltration of harvested rainwater and reduce soil erosion, a laboratory-scale rainfall simulator was developed. Rainfall characteristics, including rainfall intensity, spatial uniformity and raindrop size, confirm that natural rainfall conditions are simulated with sufficient accuracy. The simulator was auto-controlled by a solenoid valve and three pressure nozzles were used to spray water corresponding to different rainfall intensities. In order to assess the RT method under different surface slopes, different soil scooping devices with identical volume were used to create depressions. The performance of the soil with these depressions was compared to a control soil surface (with no depression). Results show that RT was able to reduce soil erosion and surface runoff and significantly increase infiltration. Then, based on these results and after selecting the proper shape of depressions, a combination implement integrated reservoir tillage system (integrated RT) comprised of a single-row chisel plow, single-row spike tooth harrow, modified seeder, and spiked roller was developed and used to compared to MT and CT in an arid environment in Egypt. The field experiments were conducted to evaluate the impact of different tillage practices and their operating parameters at different tillage depths and different forward speeds on the soil physical properties, as well as on runoff, soil losses, moisture regime, water harvesting efficiency, and winter wheat productivity. Results indicated that the integrated RT drastically increased infiltration, producing a rate that was 47.51% higher than MT and 64.56% higher than CT. In addition, results showed that the lowest values of runoff and soil losses, 4.91 mm and 0.65 t ha-1 respectively, were recorded under the integrated RT, while the highest values, 11.36 mm and 1.66 t ha -1 respectively, occurred under the CT. In addition, two field experiments were carried out in semi-arid environment in Madrid with barley and maize as the main crops. For the rainfed barley experiment, two tillage practices (RT, and MT) were performed. Results showed that soil water potential increased quite steadily and were consistently greater in MT and, irrespective of the entire observation period, RT decreased soil water potential by 43.6, 5.7, and 82.3% compared to MT at soil depths (10, 20, and 30 cm, respectively). In addition, clear differences in crop yield and yield components were observed between the two tillage systems, grain yield (up to 14%) and biomass yield (up to 8.8%) were increased by RT. For the irrigated maize experiment, four tillage practices (RT, MT, ZT, and CT) were performed. Results showed that ZT and RT had the lowest soil water potential and soil temperature. Compared to CT treatment, ZT and RT decreased soil water potential by 72 and 23% respectively, at soil depth of 40 cm, and decreased soil temperature by 1.1 and 0.8 0C respectively, at soil depth of 5 cm. Also, ZT had the highest soil bulk density and penetration resistance, which delayed the maize growth and decreased the grain yield that was 15.4% lower than CT treatment. RT increased maize grain yield about 12.8% compared to ZT. On the other hand, no significant differences among (RT, MT, and CT) on maize yield were found. In summary, according to the results from these experiments using reservoir tillage to make depressions after seeding, these depression’s internal surfaces are consolidated in such a way that the water is held to percolate into the soil and thus allowing time to offer moisture to the plant rooting zone over an extended period of time. Reservoir tillage could be used as an alternative method in arid and semi-arid regions and it retains moisture in-situ, through structures that reduce runoff and thus can result in improved crop yields.

The impact of large-scale circulation patterns on summer crop in Iberian Peninsula

Large-scale circulations patterns (ENSO, NAO) have been shown to have a significant impact on seasonal weather, and therefore on crop yield over many parts of the world(Garnett and Khandekar, 1992; Aasa et al., 2004; Rozas and Garcia-Gonzalez, 2012). In this study, we analyze the influence of large-scale circulation patterns and regional climate on the principal components of maize yield variability in Iberian Peninsula (IP) using reanalysis datasets. Additionally, we investigate the modulation of these relationships by multidecadal patterns. This study is performed analyzing long time series of maize yield, only climate dependent, computed with the crop model CERES-maize (Jones and Kiniry, 1986) included in Decision Support System for Agrotechnology Transfer (DSSAT v.4.5).

Climate variability effects on field crops in Iberian Peninsula. Predictability

La presente Tesis constituye un avance en el conocimiento de los efectos de la variabilidad climática en los cultivos en la Península Ibérica (PI). Es bien conocido que la temperatura del océano, particularmente de la región tropical, es una de las variables más convenientes para ser utilizado como predictor climático. Los océanos son considerados como la principal fuente de almacenamiento de calor del planeta debido a la alta capacidad calorífica del agua. Cuando se libera esta energía, altera los regímenes globales de circulación atmosférica por mecanismos de teleconexión. Estos cambios en la circulación general de la atmósfera afectan a la temperatura, precipitación, humedad, viento, etc., a escala regional, los cuales afectan al crecimiento, desarrollo y rendimiento de los cultivos. Para el caso de Europa, esto implica que la variabilidad atmosférica en una región específica se asocia con la variabilidad de otras regiones adyacentes y/o remotas, como consecuencia Europa está siendo afectada por los patrones de circulaciones globales, que a su vez, se ven afectados por patrones oceánicos. El objetivo general de esta tesis es analizar la variabilidad del rendimiento de los cultivos y su relación con la variabilidad climática y teleconexiones, así como evaluar su predictibilidad. Además, esta Tesis tiene como objetivo establecer una metodología para estudiar la predictibilidad de las anomalías del rendimiento de los cultivos. El análisis se centra en trigo y maíz como referencia para otros cultivos de la PI, cultivos de invierno en secano y cultivos de verano en regadío respectivamente. Experimentos de simulación de cultivos utilizando una metodología en cadena de modelos (clima + cultivos) son diseñados para evaluar los impactos de los patrones de variabilidad climática en el rendimiento y su predictibilidad. La presente Tesis se estructura en dos partes: La primera se centra en el análisis de la variabilidad del clima y la segunda es una aplicación de predicción cuantitativa de cosechas. La primera parte está dividida en 3 capítulos y la segundo en un capitulo cubriendo los objetivos específicos del presente trabajo de investigación. Parte I. Análisis de variabilidad climática El primer capítulo muestra un análisis de la variabilidad del rendimiento potencial en una localidad como indicador bioclimático de las teleconexiones de El Niño con Europa, mostrando su importancia en la mejora de predictibilidad tanto en clima como en agricultura. Además, se presenta la metodología elegida para relacionar el rendimiento con las variables atmosféricas y oceánicas. El rendimiento de los cultivos es parcialmente determinado por la variabilidad climática atmosférica, que a su vez depende de los cambios en la temperatura de la superficie del mar (TSM). El Niño es el principal modo de variabilidad interanual de la TSM, y sus efectos se extienden en todo el mundo. Sin embargo, la predictibilidad de estos impactos es controversial, especialmente aquellos asociados con la variabilidad climática Europea, que se ha encontrado que es no estacionaria y no lineal. Este estudio mostró cómo el rendimiento potencial de los cultivos obtenidos a partir de datos de reanálisis y modelos de cultivos sirve como un índice alternativo y más eficaz de las teleconexiones de El Niño, ya que integra las no linealidades entre las variables climáticas en una única serie temporal. Las relaciones entre El Niño y las anomalías de rendimiento de los cultivos son más significativas que las contribuciones individuales de cada una de las variables atmosféricas utilizadas como entrada en el modelo de cultivo. Además, la no estacionariedad entre El Niño y la variabilidad climática europea se detectan con mayor claridad cuando se analiza la variabilidad de los rendimiento de los cultivos. La comprensión de esta relación permite una cierta predictibilidad hasta un año antes de la cosecha del cultivo. Esta predictibilidad no es constante, sino que depende tanto la modulación de la alta y baja frecuencia. En el segundo capítulo se identifica los patrones oceánicos y atmosféricos de variabilidad climática que afectan a los cultivos de verano en la PI. Además, se presentan hipótesis acerca del mecanismo eco-fisiológico a través del cual el cultivo responde. Este estudio se centra en el análisis de la variabilidad del rendimiento de maíz en la PI para todo el siglo veinte, usando un modelo de cultivo calibrado en 5 localidades españolas y datos climáticos de reanálisis para obtener series temporales largas de rendimiento potencial. Este estudio evalúa el uso de datos de reanálisis para obtener series de rendimiento de cultivos que dependen solo del clima, y utilizar estos rendimientos para analizar la influencia de los patrones oceánicos y atmosféricos. Los resultados muestran una gran fiabilidad de los datos de reanálisis. La distribución espacial asociada a la primera componente principal de la variabilidad del rendimiento muestra un comportamiento similar en todos los lugares estudiados de la PI. Se observa una alta correlación lineal entre el índice de El Niño y el rendimiento, pero no es estacionaria en el tiempo. Sin embargo, la relación entre la temperatura del aire y el rendimiento se mantiene constante a lo largo del tiempo, siendo los meses de mayor influencia durante el período de llenado del grano. En cuanto a los patrones atmosféricos, el patrón Escandinavia presentó una influencia significativa en el rendimiento en PI. En el tercer capítulo se identifica los patrones oceánicos y atmosféricos de variabilidad climática que afectan a los cultivos de invierno en la PI. Además, se presentan hipótesis acerca del mecanismo eco-fisiológico a través del cual el cultivo responde. Este estudio se centra en el análisis de la variabilidad del rendimiento de trigo en secano del Noreste (NE) de la PI. La variabilidad climática es el principal motor de los cambios en el crecimiento, desarrollo y rendimiento de los cultivos, especialmente en los sistemas de producción en secano. En la PI, los rendimientos de trigo son fuertemente dependientes de la cantidad de precipitación estacional y la distribución temporal de las mismas durante el periodo de crecimiento del cultivo. La principal fuente de variabilidad interanual de la precipitación en la PI es la Oscilación del Atlántico Norte (NAO), que se ha relacionado, en parte, con los cambios en la temperatura de la superficie del mar en el Pacífico Tropical (El Niño) y el Atlántico Tropical (TNA). La existencia de cierta predictibilidad nos ha animado a analizar la posible predicción de los rendimientos de trigo en la PI utilizando anomalías de TSM como predictor. Para ello, se ha utilizado un modelo de cultivo (calibrado en dos localidades del NE de la PI) y datos climáticos de reanálisis para obtener series temporales largas de rendimiento de trigo alcanzable y relacionar su variabilidad con anomalías de la TSM. Los resultados muestran que El Niño y la TNA influyen en el desarrollo y rendimiento del trigo en el NE de la PI, y estos impactos depende del estado concurrente de la NAO. Aunque la relación cultivo-TSM no es igual durante todo el periodo analizado, se puede explicar por un mecanismo eco-fisiológico estacionario. Durante la segunda mitad del siglo veinte, el calentamiento (enfriamiento) en la superficie del Atlántico tropical se asocia a una fase negativa (positiva) de la NAO, que ejerce una influencia positiva (negativa) en la temperatura mínima y precipitación durante el invierno y, por lo tanto, aumenta (disminuye) el rendimiento de trigo en la PI. En relación con El Niño, la correlación más alta se observó en el período 1981 -2001. En estas décadas, los altos (bajos) rendimientos se asocian con una transición El Niño - La Niña (La Niña - El Niño) o con eventos de El Niño (La Niña) que están finalizando. Para estos eventos, el patrón atmosférica asociada se asemeja a la NAO, que también influye directamente en la temperatura máxima y precipitación experimentadas por el cultivo durante la floración y llenado de grano. Los co- efectos de los dos patrones de teleconexión oceánicos ayudan a aumentar (disminuir) la precipitación y a disminuir (aumentar) la temperatura máxima en PI, por lo tanto el rendimiento de trigo aumenta (disminuye). Parte II. Predicción de cultivos. En el último capítulo se analiza los beneficios potenciales del uso de predicciones climáticas estacionales (por ejemplo de precipitación) en las predicciones de rendimientos de trigo y maíz, y explora métodos para aplicar dichos pronósticos climáticos en modelos de cultivo. Las predicciones climáticas estacionales tienen un gran potencial en las predicciones de cultivos, contribuyendo de esta manera a una mayor eficiencia de la gestión agrícola, seguridad alimentaria y de subsistencia. Los pronósticos climáticos se expresan en diferentes formas, sin embargo todos ellos son probabilísticos. Para ello, se evalúan y aplican dos métodos para desagregar las predicciones climáticas estacionales en datos diarios: 1) un generador climático estocástico condicionado (predictWTD) y 2) un simple re-muestreador basado en las probabilidades del pronóstico (FResampler1). Los dos métodos se evaluaron en un caso de estudio en el que se analizaron los impactos de tres escenarios de predicciones de precipitación estacional (predicción seco, medio y lluvioso) en el rendimiento de trigo en secano, sobre las necesidades de riego y rendimiento de maíz en la PI. Además, se estimó el margen bruto y los riesgos de la producción asociada con las predicciones de precipitación estacional extremas (seca y lluviosa). Los métodos predWTD y FResampler1 usados para desagregar los pronósticos de precipitación estacional en datos diarios, que serán usados como inputs en los modelos de cultivos, proporcionan una predicción comparable. Por lo tanto, ambos métodos parecen opciones factibles/viables para la vinculación de los pronósticos estacionales con modelos de simulación de cultivos para establecer predicciones de rendimiento o las necesidades de riego en el caso de maíz. El análisis del impacto en el margen bruto de los precios del grano de los dos cultivos (trigo y maíz) y el coste de riego (maíz) sugieren que la combinación de los precios de mercado previstos y la predicción climática estacional pueden ser una buena herramienta en la toma de decisiones de los agricultores, especialmente en predicciones secas y/o localidades con baja precipitación anual. Estos métodos permiten cuantificar los beneficios y riesgos de los agricultores ante una predicción climática estacional en la PI. Por lo tanto, seríamos capaces de establecer sistemas de alerta temprana y diseñar estrategias de adaptación del manejo del cultivo para aprovechar las condiciones favorables o reducir los efectos de condiciones adversas. La utilidad potencial de esta Tesis es la aplicación de las relaciones encontradas para predicción de cosechas de la próxima campaña agrícola. Una correcta predicción de los rendimientos podría ayudar a los agricultores a planear con antelación sus prácticas agronómicas y todos los demás aspectos relacionados con el manejo de los cultivos. Esta metodología se puede utilizar también para la predicción de las tendencias futuras de la variabilidad del rendimiento en la PI. Tanto los sectores públicos (mejora de la planificación agrícola) como privados (agricultores, compañías de seguros agrarios) pueden beneficiarse de esta mejora en la predicción de cosechas. ABSTRACT The present thesis constitutes a step forward in advancing of knowledge of the effects of climate variability on crops in the Iberian Peninsula (IP). It is well known that ocean temperature, particularly the tropical ocean, is one of the most convenient variables to be used as climate predictor. Oceans are considered as the principal heat storage of the planet due to the high heat capacity of water. When this energy is released, it alters the global atmospheric circulation regimes by teleconnection1 mechanisms. These changes in the general circulation of the atmosphere affect the regional temperature, precipitation, moisture, wind, etc., and those influence crop growth, development and yield. For the case of Europe, this implies that the atmospheric variability in a specific region is associated with the variability of others adjacent and/or remote regions as a consequence of Europe being affected by global circulations patterns which, in turn, are affected by oceanic patterns. The general objective of this Thesis is to analyze the variability of crop yields at climate time scales and its relation to the climate variability and teleconnections, as well as to evaluate their predictability. Moreover, this Thesis aims to establish a methodology to study the predictability of crop yield anomalies. The analysis focuses on wheat and maize as a reference crops for other field crops in the IP, for winter rainfed crops and summer irrigated crops respectively. Crop simulation experiments using a model chain methodology (climate + crop) are designed to evaluate the impacts of climate variability patterns on yield and its predictability. The present Thesis is structured in two parts. The first part is focused on the climate variability analyses, and the second part is an application of the quantitative crop forecasting for years that fulfill specific conditions identified in the first part. This Thesis is divided into 4 chapters, covering the specific objectives of the present research work. Part I. Climate variability analyses The first chapter shows an analysis of potential yield variability in one location, as a bioclimatic indicator of the El Niño teleconnections with Europe, putting forward its importance for improving predictability in both climate and agriculture. It also presents the chosen methodology to relate yield with atmospheric and oceanic variables. Crop yield is partially determined by atmospheric climate variability, which in turn depends on changes in the sea surface temperature (SST). El Niño is the leading mode of SST interannual variability, and its impacts extend worldwide. Nevertheless, the predictability of these impacts is controversial, especially those associated with European climate variability, which have been found to be non-stationary and non-linear. The study showed how potential2 crop yield obtained from reanalysis data and crop models serves as an alternative and more effective index of El Niño teleconnections because it integrates the nonlinearities between the climate variables in a unique time series. The relationships between El Niño and crop yield anomalies are more significant than the individual contributions of each of the atmospheric variables used as input in the crop model. Additionally, the non-stationarities between El Niño and European climate variability are more clearly detected when analyzing crop-yield variability. The understanding of this relationship allows for some predictability up to one year before the crop is harvested. This predictability is not constant, but depends on both high and low frequency modulation. The second chapter identifies the oceanic and atmospheric patterns of climate variability affecting summer cropping systems in the IP. Moreover, hypotheses about the eco-physiological mechanism behind crop response are presented. It is focused on an analysis of maize yield variability in IP for the whole twenty century, using a calibrated crop model at five contrasting Spanish locations and reanalyses climate datasets to obtain long time series of potential yield. The study tests the use of reanalysis data for obtaining only climate dependent time series of simulated crop yield for the whole region, and to use these yield to analyze the influences of oceanic and atmospheric patterns. The results show a good reliability of reanalysis data. The spatial distribution of the leading principal component of yield variability shows a similar behaviour over all the studied locations in the IP. The strong linear correlation between El Niño index and yield is remarkable, being this relation non-stationary on time, although the air temperature-yield relationship remains on time, being the highest influences during grain filling period. Regarding atmospheric patterns, the summer Scandinavian pattern has significant influence on yield in IP. The third chapter identifies the oceanic and atmospheric patterns of climate variability affecting winter cropping systems in the IP. Also, hypotheses about the eco-physiological mechanism behind crop response are presented. It is focused on an analysis of rainfed wheat yield variability in IP. Climate variability is the main driver of changes in crop growth, development and yield, especially for rainfed production systems. In IP, wheat yields are strongly dependent on seasonal rainfall amount and temporal distribution of rainfall during the growing season. The major source of precipitation interannual variability in IP is the North Atlantic Oscillation (NAO) which has been related in part with changes in the Tropical Pacific (El Niño) and Atlantic (TNA) sea surface temperature (SST). The existence of some predictability has encouraged us to analyze the possible predictability of the wheat yield in the IP using SSTs anomalies as predictor. For this purpose, a crop model with a site specific calibration for the Northeast of IP and reanalysis climate datasets have been used to obtain long time series of attainable wheat yield and relate their variability with SST anomalies. The results show that El Niño and TNA influence rainfed wheat development and yield in IP and these impacts depend on the concurrent state of the NAO. Although crop-SST relationships do not equally hold on during the whole analyzed period, they can be explained by an understood and stationary ecophysiological mechanism. During the second half of the twenty century, the positive (negative) TNA index is associated to a negative (positive) phase of NAO, which exerts a positive (negative) influence on minimum temperatures (Tmin) and precipitation (Prec) during winter and, thus, yield increases (decreases) in IP. In relation to El Niño, the highest correlation takes place in the period 1981-2001. For these decades, high (low) yields are associated with an El Niño to La Niña (La Niña to El Niño) transitions or to El Niño events finishing. For these events, the regional associated atmospheric pattern resembles the NAO, which also influences directly on the maximum temperatures (Tmax) and precipitation experienced by the crop during flowering and grain filling. The co-effects of the two teleconnection patterns help to increase (decrease) the rainfall and decrease (increase) Tmax in IP, thus on increase (decrease) wheat yield. Part II. Crop forecasting The last chapter analyses the potential benefits for wheat and maize yields prediction from using seasonal climate forecasts (precipitation), and explores methods to apply such a climate forecast to crop models. Seasonal climate prediction has significant potential to contribute to the efficiency of agricultural management, and to food and livelihood security. Climate forecasts come in different forms, but probabilistic. For this purpose, two methods were evaluated and applied for disaggregating seasonal climate forecast into daily weather realizations: 1) a conditioned stochastic weather generator (predictWTD) and 2) a simple forecast probability resampler (FResampler1). The two methods were evaluated in a case study where the impacts of three scenarios of seasonal rainfall forecasts on rainfed wheat yield, on irrigation requirements and yields of maize in IP were analyzed. In addition, we estimated the economic margins and production risks associated with extreme scenarios of seasonal rainfall forecasts (dry and wet). The predWTD and FResampler1 methods used for disaggregating seasonal rainfall forecast into daily data needed by the crop simulation models provided comparable predictability. Therefore both methods seem feasible options for linking seasonal forecasts with crop simulation models for establishing yield forecasts or irrigation water requirements. The analysis of the impact on gross margin of grain prices for both crops and maize irrigation costs suggests the combination of market prices expected and the seasonal climate forecast can be a good tool in farmer’s decision-making, especially on dry forecast and/or in locations with low annual precipitation. These methodologies would allow quantifying the benefits and risks of a seasonal weather forecast to farmers in IP. Therefore, we would be able to establish early warning systems and to design crop management adaptation strategies that take advantage of favorable conditions or reduce the effect of adverse conditions. The potential usefulness of this Thesis is to apply the relationships found to crop forecasting on the next cropping season, suggesting opportunity time windows for the prediction. The methodology can be used as well for the prediction of future trends of IP yield variability. Both public (improvement of agricultural planning) and private (decision support to farmers, insurance companies) sectors may benefit from such an improvement of crop forecasting.

CSM-IXIM: A New Maize Simulation Model for DSSAT Version 4.5

Th e CERES-Maize model is the most widely used maize (Zea mays L.) model and is a recognized reference for comparing new developments in maize growth, development, and yield simulation. Th e objective of this study was to present and evaluate CSMIXIM, a new maize simulation model for DSSAT version 4.5. Code from CSM-CERES-Maize, the modular version of the model, was modifi ed to include a number of model improvements. Model enhancements included the simulation of leaf area, C assimilation and partitioning, ear growth, kernel number, grain yield, and plant N acquisition and distribution. Th e addition of two genetic coeffi cients to simulate per-leaf foliar surface produced 32% smaller root mean square error (RMSE) values estimating leaf area index than did CSM-CERES. Grain yield and total shoot biomass were correctly simulated by both models. Carbon partitioning, however, showed diff erences. Th e CSM-IXIM model simulated leaf mass more accurately, reducing the CSM-CERES error by 44%, but overestimated stem mass, especially aft er stress, resulting in similar average RMSE values as CSM-CERES. Excessive N uptake aft er fertilization events as simulated by CSM-CERES was also corrected, reducing the error by 16%. Th e accuracy of N distribution to stems was improved by 68%. Th ese improvements in CSM-IXIM provided a stable basis for more precise simulation of maize canopy growth and yield and a framework for continuing future model developments

Climate Change Impacts on Maize and Dry Bean Yields of smallholder farmers in Honduras

The rotation maize and dry bean provides the main food supply of smallholder farmers in Honduras. Crop model assessment of climate change impacts (2070?2099 compared to a 1961?1990 baseline) on a maize?dry bean rotation for several sites across a range of climatic zones and elevations in Honduras. Low productivity systems, together with an uncertain future climate, pose a high level of risk for food security. The cropping systems simulation dynamic model CropSyst was calibrated and validated upon field trail site at Zamorano, then run with baseline and future climate scenarios based upon general circulation models (GCM) and the ClimGen synthetic daily weather generator. Results indicate large uncertainty in crop production from various GCM simulations and future emissions scenarios, but generally reduced yields at low elevations by 0 % to 22 % in suitable areas for crop production and increased yield at the cooler, on the hillsides, where farming needs to reduce soil erosion with conservation techniques. Further studies are needed to investigate strategies to reduce impacts and to explore adaptation tactics.

Even-sowing pattern strategies for a low-input agricultural system in forage maize

The objective of this study was to verify the effectiveness of new patterns of sowing and to achieve a low-input organic system in two different environments (northern and southern Europe). The study was motivated by the hypothesis that more even sowing patterns (triangular and square) would significantly enhance the growth and yield of forage maize under widely varying conditions, compared with traditional mechanised rectangular seed patterns. An experiment was conducted in Madrid and duplicated in Copenhagen during 2010. A random block design was used with a 2 × 2 factorial arrangement based on two seed-sowing patterns: traditional (rectangular) and new (even) and two weed-management conditions (herbicide use and a low-input system). In both weed-management conditions and locations, the production of aerial maize biomass was greater for the new square seed patterns. In addition, the new pattern showed a greater effectiveness in the control of weeds, both at the initial crop stages (36 and 33% fewer weeds m-2 at the 4- and 8-leaf stages, respectively, in the Copenhagen field experiment) and at the final stage. The final weed biomass for the new pattern was 568 kg ha-1 lower for the Copenhagen experiment and 277 kg ha-1 lower in Madrid field experiments. In the light of these results, the new pattern could potentially reduce the use of herbicides. The results of the experiments support the hypothesis formulated at the beginning of this study that even-sowing patterns would be relatively favourable for the growth and yield of the maize crop. In the near future, new machinery could be used to achieve new seed patterns for the optimisation of biomass yield under low-input systems. This approach is effective because it promotes natural crop-weed competition.

Role of maize stover incorporation on nitrogen oxide emissions in a non-irrigated Mediterranean barley field.

Aims Agricultural soils in semiarid Mediterranean areas are characterized by low organic matter contents and low fertility levels. Application of crop residues and/or manures as amendments is a cost-effective and sustainable alternative to overcome this problem. However, these management practices may induce important changes in the nitrogen oxide emissions from these agroecosystems, with additional impacts on carbon dioxide emissions. In this context, a field experiment was carried out with a barley (Hordeum vulgare L.) crop under Mediterranean conditions to evaluate the effect of combining maize (Zea mays L.) residues and N fertilizer inputs (organic and/or mineral) on these emissions. Methods Crop yield and N uptake, soil mineral N concentrations, dissolved organic carbon (DOC), denitrification capacity, N2O, NO and CO2 fluxes were measured during the growing season. Results The incorporation of maize stover increased N2O emissions during the experimental period by c. 105 %. Conversely, NO emissions were significantly reduced in the plots amended with crop residues. The partial substitution of urea by pig slurry reduced net N2O emissions by 46 and 39 %, with and without the incorporation of crop residues respectively. Net emissions of NO were reduced 38 and 17 % for the same treatments. Molar DOC:NO 3 − ratio was found to be a robust predictor of N2O and NO fluxes. Conclusions The main effect of the interaction between crop residue and N fertilizer application occurred in the medium term (4–6 month after application), enhancing N2O emissions and decreasing NO emissions as consequence of residue incorporation. The substitution of urea by pig slurry can be considered a good management strategy since N2O and NO emissions were reduced by the use of the organic residue.

How do various maize crop models vary in their responses to climate change factors?

Comments This article is a U.S. government work, and is not subject to copyright in the United States. Abstract Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data for calibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly 0.5 Mg ha 1 per °C. Doubling [CO2] from 360 to 720 lmol mol 1 increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2] among models. Model responses to temperature and [CO2] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information.