Fertilization Management: Assessing New Techniques and Key Interactions to Increase Crop Yields With Less N2O Emissions

El óxido nitroso (N2O) es un potente gas de efecto invernadero (GHG) proveniente mayoritariamente de la fertilización nitrogenada de los suelos agrícolas. Identificar estrategias de manejo de la fertilización que reduzcan estas emisiones sin suponer un descenso de los rendimientos es vital tanto a nivel económico como medioambiental. Con ese propósito, en esta Tesis se han evaluado: (i) estrategias de manejo directo de la fertilización (inhibidores de la nitrificación/ureasa); y (ii) interacciones de los fertilizantes con (1) el manejo del agua, (2) residuos de cosecha y (3) diferentes especies de plantas. Para conseguirlo se llevaron a cabo meta-análisis, incubaciones de laboratorio, ensayos en invernadero y experimentos de campo. Los inhibidores de la nitrificación y de la actividad ureasa se proponen habitualmente como medidas para reducir las pérdidas de nitrógeno (N), por lo que su aplicación estaría asociada al uso eficiente del N por parte de los cultivos (NUE). Sin embargo, su efecto sobre los rendimientos es variable. Con el objetivo de evaluar en una primera fase su efectividad para incrementar el NUE y la productividad de los cultivos, se llevó a cabo un meta-análisis. Los inhibidores de la nitrificación dicyandiamide (DCD) y 3,4-dimetilepyrazol phosphate (DMPP) y el inhibidor de la ureasa N-(n-butyl) thiophosphoric triamide (NBPT) fueron seleccionados para el análisis ya que generalmente son considerados las mejores opciones disponibles comercialmente. Nuestros resultados mostraron que su uso puede ser recomendado con el fin de incrementar tanto el rendimiento del cultivo como el NUE (incremento medio del 7.5% y 12.9%, respectivamente). Sin embargo, se observó que su efectividad depende en gran medida de los factores medioambientales y de manejo de los estudios evaluados. Una mayor respuesta fue encontrada en suelos de textura gruesa, sistemas irrigados y/o en cultivos que reciben altas tasas de fertilizante nitrogenado. En suelos alcalinos (pH ≥ 8), el inhibidor de la ureasa NBPT produjo el mayor efecto. Dado que su uso representa un coste adicional para los agricultores, entender las mejores prácticas que permitan maximizar su efectividad es necesario para posteriormente realizar comparaciones efectivas con otras prácticas que incrementen la productividad de los cultivos y el NUE. En base a los resultados del meta-análisis, se seleccionó el NBPT como un inhibidor con gran potencial. Inicialmente desarrollado para reducir la volatilización de amoniaco (NH3), en los últimos años algunos investigadores han demostrado en estudios de campo un efecto mitigador de este inhibidor sobre las pérdidas de N2O provenientes de suelos fertilizados bajo condiciones de baja humedad del suelo. Dada la alta variabilidad de los experimentos de campo, donde la humedad del suelo cambia rápidamente, ha sido imposible entender mecanísticamente el potencial de los inhibidores de la ureasa (UIs) para reducir emisiones de N2O y su dependencia con respecto al porcentaje de poros llenos de agua del suelo (WFPS). Por lo tanto se realizó una incubación en laboratorio con el propósito de evaluar cuál es el principal mecanismo biótico tras las emisiones de N2O cuando se aplican UIs bajo diferentes condiciones de humedad del suelo (40, 60 y 80% WFPS), y para analizar hasta qué punto el WFPS regula el efecto del inhibidor sobre las emisiones de N2O. Un segundo UI (i.e. PPDA) fue utilizado para comparar el efecto del NBPT con el de otro inhibidor de la ureasa disponible comercialmente; esto nos permitió comprobar si el efecto de NBPT es específico de ese inhibidor o no. Las emisiones de N2O al 40% WFPS fueron despreciables, siendo significativamente más bajas que las de todos los tratamientos fertilizantes al 60 y 80% WFPS. Comparado con la urea sin inhibidor, NBPT+U redujo las emisiones de N2O al 60% WFPS pero no tuvo efecto al 80% WFPS. La aplicación de PPDA incrementó significativamente las emisiones con respecto a la urea al 80% WFPS mientras que no se encontró un efecto significativo al 60% WFPS. Al 80% WFPS la desnitrificación fue la principal fuente de las emisiones de N2O en todos los tratamientos mientras que al 60% tanto la nitrificación como la desnitrificación tuvieron un papel relevante. Estos resultados muestran que un correcto manejo del NBPT puede suponer una estrategia efectiva para mitigar las emisiones de N2O. Con el objetivo de trasladar nuestros resultados de los estudios previos a condiciones de campo reales, se desarrolló un experimento en el que se evaluó la efectividad del NBPT para reducir pérdidas de N y aumentar la productividad durante un cultivo de cebada (Hordeum vulgare L.) en secano Mediterráneo. Se determinó el rendimiento del cultivo, las concentraciones de N mineral del suelo, el carbono orgánico disuelto (DOC), el potencial de desnitrificación, y los flujos de NH3, N2O y óxido nítrico (NO). La adición del inhibidor redujo las emisiones de NH3 durante los 30 días posteriores a la aplicación de urea en un 58% y las emisiones netas de N2O y NO durante los 95 días posteriores a la aplicación de urea en un 86 y 88%, respectivamente. El uso de NBPT también incrementó el rendimiento en grano en un 5% y el consumo de N en un 6%, aunque ninguno de estos incrementos fue estadísticamente significativo. Bajo las condiciones experimentales dadas, estos resultados demuestran el potencial del inhibidor de la ureasa NBPT para mitigar las emisiones de NH3, N2O y NO provenientes de suelos arables fertilizados con urea, mediante la ralentización de la hidrólisis de la urea y posterior liberación de menores concentraciones de NH4 + a la capa superior del suelo. El riego por goteo combinado con la aplicación dividida de fertilizante nitrogenado disuelto en el agua de riego (i.e. fertirriego por goteo) se considera normalmente una práctica eficiente para el uso del agua y de los nutrientes. Algunos de los principales factores (WFPS, NH4 + y NO3 -) que regulan las emisiones de GHGs (i.e. N2O, CO2 y CH4) y NO pueden ser fácilmente manipulados por medio del fertirriego por goteo sin que se generen disminuciones del rendimiento. Con ese propósito se evaluaron opciones de manejo para reducir estas emisiones en un experimento de campo durante un cultivo de melón (Cucumis melo L.). Los tratamientos incluyeron distintas frecuencias de riego (semanal/diario) y tipos de fertilizantes nitrogenados (urea/nitrato cálcico) aplicados por fertirriego. Fertirrigar con urea en lugar de nitrato cálcico aumentó las emisiones de N2O y NO por un factor de 2.4 y 2.9, respectivamente (P < 0.005). El riego diario redujo las emisiones de NO un 42% (P < 0.005) pero aumentó las emisiones de CO2 un 21% (P < 0.05) comparado con el riego semanal. Analizando el Poder de Calentamiento global en base al rendimiento así como los factores de emisión del NO, concluimos que el fertirriego semanal con un fertilizante de tipo nítrico es la mejor opción para combinar productividad agronómica con sostenibilidad medioambiental en este tipo de agroecosistemas. Los suelos agrícolas en las áreas semiáridas Mediterráneas se caracterizan por su bajo contenido en materia orgánica y bajos niveles de fertilidad. La aplicación de residuos de cosecha y/o abonos es una alternativa sostenible y eficiente desde el punto de vista económico para superar este problema. Sin embargo, estas prácticas podrían inducir cambios importantes en las emisiones de N2O de estos agroecosistemas, con impactos adicionales en las emisiones de CO2. En este contexto se llevó a cabo un experimento de campo durante un cultivo de cebada (Hordeum vulgare L.) bajo condiciones Mediterráneas para evaluar el efecto de combinar residuos de cosecha de maíz con distintos inputs de fertilizantes nitrogenados (purín de cerdo y/o urea) en estas emisiones. La incorporación de rastrojo de maíz incrementó las emisiones de N2O durante el periodo experimental un 105%. Sin embargo, las emisiones de NO se redujeron significativamente en las parcelas enmendadas con rastrojo. La sustitución parcial de urea por purín de cerdo redujo las emisiones netas de N2O un 46 y 39%, con y sin incorporación de residuo de cosecha respectivamente. Las emisiones netas de NO se redujeron un 38 y un 17% para estos mismos tratamientos. El ratio molar DOC:NO3 - demostró predecir consistentemente las emisiones de N2O y NO. El efecto principal de la interacción entre el fertilizante nitrogenado y el rastrojo de maíz se dio a los 4-6 meses de su aplicación, generando un aumento del N2O y una disminución del NO. La sustitución de urea por purín de cerdo puede considerarse una buena estrategia de manejo dado que el uso de este residuo orgánico redujo las emisiones de óxidos de N. Los pastos de todo el mundo proveen numerosos servicios ecosistémicos pero también suponen una importante fuente de emisión de N2O, especialmente en respuesta a la deposición de N proveniente del ganado mientras pasta. Para explorar el papel de las plantas como mediadoras de estas emisiones, se analizó si las emisiones de N2O dependen de la riqueza en especies herbáceas y/o de la composición específica de especies, en ausencia y presencia de una deposición de orina. Las hipótesis fueron: 1) las emisiones de N2O tienen una relación negativa con la productividad de las plantas; 2) mezclas de cuatro especies generan menores emisiones que monocultivos (dado que su productividad será mayor); 3) las emisiones son menores en combinaciones de especies con distinta morfología radicular y alta biomasa de raíz; y 4) la identidad de las especies clave para reducir el N2O depende de si hay orina o no. Se establecieron monocultivos y mezclas de dos y cuatro especies comunes en pastos con rasgos funcionales divergentes: Lolium perenne L. (Lp), Festuca arundinacea Schreb. (Fa), Phleum pratense L. (Php) y Poa trivialis L. (Pt), y se cuantificaron las emisiones de N2O durante 42 días. No se encontró relación entre la riqueza en especies y las emisiones de N2O. Sin embargo, estas emisiones fueron significativamente menores en ciertas combinaciones de especies. En ausencia de orina, las comunidades de plantas Fa+Php actuaron como un sumidero de N2O, mientras que los monocultivos de estas especies constituyeron una fuente de N2O. Con aplicación de orina la comunidad Lp+Pt redujo (P < 0.001) las emisiones de N2O un 44% comparado con los monocultivos de Lp. Las reducciones de N2O encontradas en ciertas combinaciones de especies pudieron explicarse por una productividad total mayor y por una complementariedad en la morfología radicular. Este estudio muestra que la composición de especies herbáceas es un componente clave que define las emisiones de N2O de los ecosistemas de pasto. La selección de combinaciones de plantas específicas en base a la deposición de N esperada puede, por lo tanto, ser clave para la mitigación de las emisiones de N2O. ABSTRACT Nitrous oxide (N2O) is a potent greenhouse gas (GHG) directly linked to applications of nitrogen (N) fertilizers to agricultural soils. Identifying mitigation strategies for these emissions based on fertilizer management without incurring in yield penalties is of economic and environmental concern. With that aim, this Thesis evaluated: (i) the use of nitrification and urease inhibitors; and (ii) interactions of N fertilizers with (1) water management, (2) crop residues and (3) plant species richness/identity. Meta-analysis, laboratory incubations, greenhouse mesocosm and field experiments were carried out in order to understand and develop effective mitigation strategies. Nitrification and urease inhibitors are proposed as means to reduce N losses, thereby increasing crop nitrogen use efficiency (NUE). However, their effect on crop yield is variable. A meta-analysis was initially conducted to evaluate their effectiveness at increasing NUE and crop productivity. Commonly used nitrification inhibitors (dicyandiamide (DCD) and 3,4-dimethylepyrazole phosphate (DMPP)) and the urease inhibitor N-(n-butyl) thiophosphoric triamide (NBPT) were selected for analysis as they are generally considered the best available options. Our results show that their use can be recommended in order to increase both crop yields and NUE (grand mean increase of 7.5% and 12.9%, respectively). However, their effectiveness was dependent on the environmental and management factors of the studies evaluated. Larger responses were found in coarse-textured soils, irrigated systems and/or crops receiving high nitrogen fertilizer rates. In alkaline soils (pH ≥ 8), the urease inhibitor NBPT produced the largest effect size. Given that their use represents an additional cost for farmers, understanding the best management practices to maximize their effectiveness is paramount to allow effective comparison with other practices that increase crop productivity and NUE. Based on the meta-analysis results, NBPT was identified as a mitigation option with large potential. Urease inhibitors (UIs) have shown to promote high N use efficiency by reducing ammonia (NH3) volatilization. In the last few years, however, some field researches have shown an effective mitigation of UIs over N2O losses from fertilized soils under conditions of low soil moisture. Given the inherent high variability of field experiments where soil moisture content changes rapidly, it has been impossible to mechanistically understand the potential of UIs to reduce N2O emissions and its dependency on the soil water-filled pore space (WFPS). An incubation experiment was carried out aiming to assess what is the main biotic mechanism behind N2O emission when UIs are applied under different soil moisture conditions (40, 60 and 80% WFPS), and to analyze to what extent the soil WFPS regulates the effect of the inhibitor over N2O emissions. A second UI (i.e. PPDA) was also used aiming to compare the effect of NBPT with that of another commercially available urease inhibitor; this allowed us to see if the effect of NBPT was inhibitor-specific or not. The N2O emissions at 40% WFPS were almost negligible, being significantly lower from all fertilized treatments than that produced at 60 and 80% WFPS. Compared to urea alone, NBPT+U reduced the N2O emissions at 60% WFPS but had no effect at 80% WFPS. The application of PPDA significantly increased the emissions with respect to U at 80% WFPS whereas no significant effect was found at 60% WFPS. At 80% WFPS denitrification was the main source of N2O emissions for all treatments. Both nitrification and denitrification had a determinant role on these emissions at 60% WFPS. These results suggest that adequate management of the UI NBPT can provide, under certain soil conditions, an opportunity for N2O mitigation. We translated our previous results to realistic field conditions by means of a field experiment with a barley crop (Hordeum vulgare L.) under rainfed Mediterranean conditions in which we evaluated the effectiveness of NBPT to reduce N losses and increase crop yields. Crop yield, soil mineral N concentrations, dissolved organic carbon (DOC), denitrification potential, NH3, N2O and nitric oxide (NO) fluxes were measured during the growing season. The inclusion of the inhibitor reduced NH3 emissions in the 30 d following urea application by 58% and net N2O and NO emissions in the 95 d following urea application by 86 and 88%, respectively. NBPT addition also increased grain yield by 5% and N uptake by 6%, although neither increase was statistically significant. Under the experimental conditions presented here, these results demonstrate the potential of the urease inhibitor NBPT in abating NH3, N2O and NO emissions from arable soils fertilized with urea, slowing urea hydrolysis and releasing lower concentrations of NH4 + to the upper soil layer. Drip irrigation combined with split application of N fertilizer dissolved in the irrigation water (i.e. drip fertigation) is commonly considered best management practice for water and nutrient efficiency. Some of the main factors (WFPS, NH4 + and NO3 -) regulating the emissions of GHGs (i.e. N2O, carbon dioxide (CO2) and methane (CH4)) and NO can easily be manipulated by drip fertigation without yield penalties. In this study, we tested management options to reduce these emissions in a field experiment with a melon (Cucumis melo L.) crop. Treatments included drip irrigation frequency (weekly/daily) and type of N fertilizer (urea/calcium nitrate) applied by fertigation. Crop yield, environmental parameters, soil mineral N concentrations, N2O, NO, CH4, and CO2 fluxes were measured during the growing season. Fertigation with urea instead of calcium nitrate increased N2O and NO emissions by a factor of 2.4 and 2.9, respectively (P < 0.005). Daily irrigation reduced NO emissions by 42% (P < 0.005) but increased CO2 emissions by 21% (P < 0.05) compared with weekly irrigation. Based on yield-scaled Global Warming Potential as well as NO emission factors, we conclude that weekly fertigation with a NO3 --based fertilizer is the best option to combine agronomic productivity with environmental sustainability. 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 CO2 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. 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. 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:NO3 - ratio was found to be a robust predictor of N2O and NO fluxes. 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. Grassland ecosystems worldwide provide many important ecosystem services but they also function as a major source of N2O, especially in response to N deposition by grazing animals. In order to explore the role of plants as mediators of these emissions, we tested whether and how N2O emissions are dependent on grass species richness and/or specific grass species composition in the absence and presence of urine deposition. We hypothesized that: 1) N2O emissions relate negatively to plant productivity; 2) four-species mixtures have lower emissions than monocultures (as they are expected to be more productive); 3) emissions are lowest in combinations of species with diverging root morphology and high root biomass; and 4) the identity of the key species that reduce N2O emissions is dependent on urine deposition. We established monocultures and two- and four-species mixtures of common grass species with diverging functional traits: Lolium perenne L. (Lp), Festuca arundinacea Schreb. (Fa), Phleum pratense L. (Php) and Poa trivialis L. (Pt), and quantified N2O emissions for 42 days. We found no relation between plant species richness and N2O emissions. However, N2O emissions were significantly reduced in specific plant species combinations. In the absence of urine, plant communities of Fa+Php acted as a sink for N2O, whereas the monocultures of these species constituted a N2O source. With urine application Lp+Pt plant communities reduced (P < 0.001) N2O emissions by 44% compared to monocultures of Lp. Reductions in N2O emissions by species mixtures could be explained by total biomass productivity and by complementarity in root morphology. Our study shows that plant species composition is a key component underlying N2O emissions from grassland ecosystems. Selection of specific grass species combinations in the context of the expected nitrogen deposition regimes may therefore provide a key management practice for mitigation of N2O emissions.

Crop rotation and residues influence N2O emission and N efficiency rather than tillage under a rainfed Mediterranean agroecosystem

Conservation tillage and crop rotation have spread during the last decades because promotes several positive effects (increase of soil organic content, reduction of soil erosion, and enhancement of carbon sequestration) (Six et al., 2004). However, these benefits could be partly counterbalanced by negative effects on the release of nitrous oxide (N2O) (Linn and Doran, 1984). There is a lack of data on long-term tillage system study, particularly in Mediterranean agro-ecosystems. The aim of this study was to evaluate the effects of long-term (>17 year) tillage systems (no tillage (NT), minimum tillage (MT) and conventional tillage (CT)); and crop rotation (wheat (W)-vetch (V)-barley (B)) versus wheat monoculture (M) on N2O emissions. Additionally, Yield-scaled N2O emissions (YSNE) and N uptake efficiency (NUpE) were assessed for each treatment.

Influence of Tillage and Liming on N2O emission from a rainfed crop

Nitrous oxide (N2O) is the main greenhouse gas (GHG) produced by agricultural soils due to microbial processes. The application of N fertilizers is associated with an increase of N2O losses. However, it is possible to mitigate these emissions by the introduction of adequate management practices (Snyder et al., 2009). Soil conservation practices (i.e.no tillage, NT) have recently become widespread because they promote several positive effects (increases in soil organic carbonand soil fertility, reduction of soil erosion, etc). In terms of GHG emissions, there is no consensus in the literature on the effects of tillage on N2O. Several studies found that NT can produce greater (Baggs et al., 2003), lower (Malhi et al., 2006) or similar (Grandey et al., 2006) N2O emissions compared to traditional tillage (TT). This large uncertainty is associated with the duration of tillage practices and climatic variability. Liming is widely use to solve problems of soil acidity (Al toxicity, yield penalties, etc). Several studies show a decrease in N2O emissions with liming (Barton et al., 2013) whereas no significant effects or increases were observed in others (Galbally et al., 2010). The aim of this work was to evaluate the effects of tillage (NT vs TT) and liming application or not of Ca-amendment) on N2O emissions from an acid soil during a rainfed crop.

Soil moisture content determines the effect of the urease inhibitor NBPT on N2O emissions

Among the mitigation strategies to prevent nitrogen (N) losses from ureic fertilizers, urease inhibitors (UIs) have been demonstrated to promote high N use efficiency by reducing ammonia (NH3) volatilization. In the last few years, some field experiments have also shown its effectiveness in reducing nitrous oxide (N2O) losses from fertilized soils under conditions of low soil moisture. An incubation experiment was carried out with the aim of assessing the main biotic mechanisms behind N2O emissions once that the UIs N-(n-butyl) thiophosphoric triamid (NBPT) and phenil phosphorodiamidate (PPDA) were applied with Urea (U) under different soil moisture conditions (40, 60 and 80 % water-filled pore space, WFPS). In the same study we tried to analyze to what extent soil WFPS regulates the effect of these inhibitors on N2O emissions. The use of PPDA in our study allowed us to compare the effect of NBPT with that of another commercially available urease inhibitor, aiming to see if the results were inhibitor-specific or not. Based on the results from this experiment, a WFPS (i.e. 60 %) was chosen for a second study (i.e. mesocosm experiment) aiming to assess the efficiency of the UIs to indirectly affect N2O emissions through influencing the pool of soil mineral N. The N2O emissions at 40 % WFPS were almost negligible, being significantly lower from all fertilized treatments than that produced at 60 and 80 % WFPS. When compared to U alone, NBPT+U reduced the N2O emissions at 60 % WFPS but had no effect at 80 % WFPS. The application of PPDA significantly increased the emissions with respect to U at 80 % WFPS whereas no significant effect was found at 60 %. At 80 % WFPS, denitrification was the main source of N2O emissions for all treatments. In the mesocosm study, the application of NBPT+U was an effective strategy to reduce N2O emissions (75 % reduction compared to U alone), due to a lower soil ammonium (NH4 +) content induced by the inhibitor. These results suggest that adequate management of the UI NBPT could provide, under certain soil conditions, an opportunity for mitigation of N2O emissions from fertilized soils.

Do cover crops enhance N2O, CO2 or CH4 emissions from soil in Mediterranean arable systems?

This study evaluates the effect of planting three cover crops (CCs) (barley, Hordeum vulgare L.; vetch, Vicia villosa L.; rape, Brassica napus L.) on the direct emission of N2O, CO2 and CH4 in the intercrop period and the impact of incorporating these CCs on the emission of greenhouse gas (GHG) from the forthcoming irrigated maize (Zea mays L.) crop. Vetch and barley were the CCs with the highest N2O and CO2 losses (75 and 47% increase compared with the control, respectively) in the fallow period. In all cases, fluxes of N2O were increased through N fertilization and the incorporation of barley and rape residues (40 and 17% increase, respectively). The combination of a high C:N ratio with the addition of an external source of mineral N increased the fluxes of N2O compared with − Ba and − Rp. The direct emissions of N2O were lower than expected for a fertilized crop (0.10% emission factor, EF) compared with other studies and the IPCC EF. These results are believed to be associated with a decreased NO3− pool due to highly denitrifying conditions and increased drainage. The fluxes of CO2 were in the range of other fertilized crops (i.e., 1118.71–1736.52 kg CO2–C ha− 1). The incorporation of CC residues enhanced soil respiration in the range of 21–28% for barley and rape although no significant differences between treatments were detected. Negative CH4 fluxes were measured and displayed an overall sink effect for all incorporated CC (mean values of − 0.12 and − 0.10 kg CH4–C ha− 1 for plots with and without incorporated CCs, respectively).

Animal feeding strategies to reduce N2O and NH3 emission from surface-applied pig slurry to a grassland soil.

It is estimated that N losses from fertilized crops range between 50-70%, depending on management practices, climate and soil conditions. Ammonia (NH3) emissions following land application of animal manures give rise to a significant proportion of the total NH3 emissions from agricultural sources.

Optimization methods for the operating room management under uncertainty: stochastic programming vs. decomposition approach

The operating theatres are the engine of the hospitals; proper management of the operating rooms and its staff represents a great challenge for managers and its results impact directly in the budget of the hospital. This work presents a MILP model for the efficient schedule of multiple surgeries in Operating Rooms (ORs) during a working day. This model considers multiple surgeons and ORs and different types of surgeries. Stochastic strategies are also implemented for taking into account the uncertain in surgery durations (pre-incision, incision, post-incision times). In addition, a heuristic-based methods and a MILP decomposition approach is proposed for solving large-scale ORs scheduling problems in computational efficient way. All these computer-aided strategies has been implemented in AIMMS, as an advanced modeling and optimization software, developing a user friendly solution tool for the operating room management under uncertainty.

The Proper Generalized Decomposition With Application In Problems Of Dynamics

In this paper we address the new reduction method called Proper Generalized Decomposition (PGD) which is a discretization technique based on the use of separated representation of the unknown fields, specially well suited for solving multidimensional parametric equations. In this case, it is applied to the solution of dynamics problems. We will focus on the dynamic analysis of an one-dimensional rod with a unit harmonic load of frequency (ω) applied at a point of interest. In what follows, we will present the application of the methodology PGD to the problem in order to approximate the displacement field as the sum of the separated functions. We will consider as new variables of the problem, parameters models associated with the characteristic of the materials, in addition to the frequency. Finally, the quality of the results will be assessed based on an example.

Fast modularisation and aomic decomposition of ontologies using axiom dependency hypergraphs

In this paper we define the notion of an axiom dependency hypergraph, which explicitly represents how axioms are included into a module by the algorithm for computing locality-based modules. A locality-based module of an ontology corresponds to a set of connected nodes in the hypergraph, and atoms of an ontology to strongly connected components. Collapsing the strongly connected components into single nodes yields a condensed hypergraph that comprises a representation of the atomic decomposition of the ontology. To speed up the condensation of the hypergraph, we first reduce its size by collapsing the strongly connected components of its graph fragment employing a linear time graph algorithm. This approach helps to significantly reduce the time needed for computing the atomic decomposition of an ontology. We provide an experimental evaluation for computing the atomic decomposition of large biomedical ontologies. We also demonstrate a significant improvement in the time needed to extract locality-based modules from an axiom dependency hypergraph and its condensed version.

Strong Connectivity in Directed Hypergraphs and its Application to the Atomic Decomposition of Ontologies

Los hipergrafos dirigidos se han empleado en problemas relacionados con lógica proposicional, bases de datos relacionales, linguística computacional y aprendizaje automático. Los hipergrafos dirigidos han sido también utilizados como alternativa a los grafos (bipartitos) dirigidos para facilitar el estudio de las interacciones entre componentes de sistemas complejos que no pueden ser fácilmente modelados usando exclusivamente relaciones binarias. En este contexto, este tipo de representación es conocida como hiper-redes. Un hipergrafo dirigido es una generalización de un grafo dirigido especialmente adecuado para la representación de relaciones de muchos a muchos. Mientras que una arista en un grafo dirigido define una relación entre dos de sus nodos, una hiperarista en un hipergrafo dirigido define una relación entre dos conjuntos de sus nodos. La conexión fuerte es una relación de equivalencia que divide el conjunto de nodos de un hipergrafo dirigido en particiones y cada partición define una clase de equivalencia conocida como componente fuertemente conexo. El estudio de los componentes fuertemente conexos de un hipergrafo dirigido puede ayudar a conseguir una mejor comprensión de la estructura de este tipo de hipergrafos cuando su tamaño es considerable. En el caso de grafo dirigidos, existen algoritmos muy eficientes para el cálculo de los componentes fuertemente conexos en grafos de gran tamaño. Gracias a estos algoritmos, se ha podido averiguar que la estructura de la WWW tiene forma de “pajarita”, donde más del 70% del los nodos están distribuidos en tres grandes conjuntos y uno de ellos es un componente fuertemente conexo. Este tipo de estructura ha sido también observada en redes complejas en otras áreas como la biología. Estudios de naturaleza similar no han podido ser realizados en hipergrafos dirigidos porque no existe algoritmos capaces de calcular los componentes fuertemente conexos de este tipo de hipergrafos. En esta tesis doctoral, hemos investigado como calcular los componentes fuertemente conexos de un hipergrafo dirigido. En concreto, hemos desarrollado dos algoritmos para este problema y hemos determinado que son correctos y cuál es su complejidad computacional. Ambos algoritmos han sido evaluados empíricamente para comparar sus tiempos de ejecución. Para la evaluación, hemos producido una selección de hipergrafos dirigidos generados de forma aleatoria inspirados en modelos muy conocidos de grafos aleatorios como Erdos-Renyi, Newman-Watts-Strogatz and Barabasi-Albert. Varias optimizaciones para ambos algoritmos han sido implementadas y analizadas en la tesis. En concreto, colapsar los componentes fuertemente conexos del grafo dirigido que se puede construir eliminando ciertas hiperaristas complejas del hipergrafo dirigido original, mejora notablemente los tiempos de ejecucion de los algoritmos para varios de los hipergrafos utilizados en la evaluación. Aparte de los ejemplos de aplicación mencionados anteriormente, los hipergrafos dirigidos han sido también empleados en el área de representación de conocimiento. En concreto, este tipo de hipergrafos se han usado para el cálculo de módulos de ontologías. Una ontología puede ser definida como un conjunto de axiomas que especifican formalmente un conjunto de símbolos y sus relaciones, mientras que un modulo puede ser entendido como un subconjunto de axiomas de la ontología que recoge todo el conocimiento que almacena la ontología sobre un conjunto especifico de símbolos y sus relaciones. En la tesis nos hemos centrado solamente en módulos que han sido calculados usando la técnica de localidad sintáctica. Debido a que las ontologías pueden ser muy grandes, el cálculo de módulos puede facilitar las tareas de re-utilización y mantenimiento de dichas ontologías. Sin embargo, analizar todos los posibles módulos de una ontología es, en general, muy costoso porque el numero de módulos crece de forma exponencial con respecto al número de símbolos y de axiomas de la ontología. Afortunadamente, los axiomas de una ontología pueden ser divididos en particiones conocidas como átomos. Cada átomo representa un conjunto máximo de axiomas que siempre aparecen juntos en un modulo. La decomposición atómica de una ontología es definida como un grafo dirigido de tal forma que cada nodo del grafo corresponde con un átomo y cada arista define una dependencia entre una pareja de átomos. En esta tesis introducimos el concepto de“axiom dependency hypergraph” que generaliza el concepto de descomposición atómica de una ontología. Un modulo en una ontología correspondería con un componente conexo en este tipo de hipergrafos y un átomo de una ontología con un componente fuertemente conexo. Hemos adaptado la implementación de nuestros algoritmos para que funcionen también con axiom dependency hypergraphs y poder de esa forma calcular los átomos de una ontología. Para demostrar la viabilidad de esta idea, hemos incorporado nuestros algoritmos en una aplicación que hemos desarrollado para la extracción de módulos y la descomposición atómica de ontologías. A la aplicación la hemos llamado HyS y hemos estudiado sus tiempos de ejecución usando una selección de ontologías muy conocidas del área biomédica, la mayoría disponibles en el portal de Internet NCBO. Los resultados de la evaluación muestran que los tiempos de ejecución de HyS son mucho mejores que las aplicaciones más rápidas conocidas. ABSTRACT Directed hypergraphs are an intuitive modelling formalism that have been used in problems related to propositional logic, relational databases, computational linguistic and machine learning. Directed hypergraphs are also presented as an alternative to directed (bipartite) graphs to facilitate the study of the interactions between components of complex systems that cannot naturally be modelled as binary relations. In this context, they are known as hyper-networks. A directed hypergraph is a generalization of a directed graph suitable for representing many-to-many relationships. While an edge in a directed graph defines a relation between two nodes of the graph, a hyperedge in a directed hypergraph defines a relation between two sets of nodes. Strong-connectivity is an equivalence relation that induces a partition of the set of nodes of a directed hypergraph into strongly-connected components. These components can be collapsed into single nodes. As result, the size of the original hypergraph can significantly be reduced if the strongly-connected components have many nodes. This approach might contribute to better understand how the nodes of a hypergraph are connected, in particular when the hypergraphs are large. In the case of directed graphs, there are efficient algorithms that can be used to compute the strongly-connected components of large graphs. For instance, it has been shown that the macroscopic structure of the World Wide Web can be represented as a “bow-tie” diagram where more than 70% of the nodes are distributed into three large sets and one of these sets is a large strongly-connected component. This particular structure has been also observed in complex networks in other fields such as, e.g., biology. Similar studies cannot be conducted in a directed hypergraph because there does not exist any algorithm for computing the strongly-connected components of the hypergraph. In this thesis, we investigate ways to compute the strongly-connected components of directed hypergraphs. We present two new algorithms and we show their correctness and computational complexity. One of these algorithms is inspired by Tarjan’s algorithm for directed graphs. The second algorithm follows a simple approach to compute the stronglyconnected components. This approach is based on the fact that two nodes of a graph that are strongly-connected can also reach the same nodes. In other words, the connected component of each node is the same. Both algorithms are empirically evaluated to compare their performances. To this end, we have produced a selection of random directed hypergraphs inspired by existent and well-known random graphs models like Erd˝os-Renyi and Newman-Watts-Strogatz. Besides the application examples that we mentioned earlier, directed hypergraphs have also been employed in the field of knowledge representation. In particular, they have been used to compute the modules of an ontology. An ontology is defined as a collection of axioms that provides a formal specification of a set of terms and their relationships; and a module is a subset of an ontology that completely captures the meaning of certain terms as defined in the ontology. In particular, we focus on the modules computed using the notion of syntactic locality. As ontologies can be very large, the computation of modules facilitates the reuse and maintenance of these ontologies. Analysing all modules of an ontology, however, is in general not feasible as the number of modules grows exponentially in the number of terms and axioms of the ontology. Nevertheless, the modules can succinctly be represented using the Atomic Decomposition of an ontology. Using this representation, an ontology can be partitioned into atoms, which are maximal sets of axioms that co-occur in every module. The Atomic Decomposition is then defined as a directed graph such that each node correspond to an atom and each edge represents a dependency relation between two atoms. In this thesis, we introduce the notion of an axiom dependency hypergraph which is a generalization of the atomic decomposition of an ontology. A module in the ontology corresponds to a connected component in the hypergraph, and the atoms of the ontology to the strongly-connected components. We apply our algorithms for directed hypergraphs to axiom dependency hypergraphs and in this manner, we compute the atoms of an ontology. To demonstrate the viability of this approach, we have implemented the algorithms in the application HyS which computes the modules of ontologies and calculate their atomic decomposition. In the thesis, we provide an experimental evaluation of HyS with a selection of large and prominent biomedical ontologies, most of which are available in the NCBO Bioportal. HyS outperforms state-of-the-art implementations in the tasks of extracting modules and computing the atomic decomposition of these ontologies.

Aerodynamic database reconstruction via gappy high order singular value decomposition

Esta Tesis se centra en el desarrollo de un método para la reconstrucción de bases de datos experimentales incompletas de más de dos dimensiones. Como idea general, consiste en la aplicación iterativa de la descomposición en valores singulares de alto orden sobre la base de datos incompleta. Este nuevo método se inspira en el que ha servido de base para la reconstrucción de huecos en bases de datos bidimensionales inventado por Everson y Sirovich (1995) que a su vez, ha sido mejorado por Beckers y Rixen (2003) y simultáneamente por Venturi y Karniadakis (2004). Además, se ha previsto la adaptación de este nuevo método para tratar el posible ruido característico de bases de datos experimentales y a su vez, bases de datos estructuradas cuya información no forma un hiperrectángulo perfecto. Se usará una base de datos tridimensional de muestra como modelo, obtenida a través de una función transcendental, para calibrar e ilustrar el método. A continuación se detalla un exhaustivo estudio del funcionamiento del método y sus variantes para distintas bases de datos aerodinámicas. En concreto, se usarán tres bases de datos tridimensionales que contienen la distribución de presiones sobre un ala. Una se ha generado a través de un método semi-analítico con la intención de estudiar distintos tipos de discretizaciones espaciales. El resto resultan de dos modelos numéricos calculados en C F D . Por último, el método se aplica a una base de datos experimental de más de tres dimensiones que contiene la medida de fuerzas de una configuración ala de Prandtl obtenida de una campaña de ensayos en túnel de viento, donde se estudiaba un amplio espacio de parámetros geométricos de la configuración que como resultado ha generado una base de datos donde la información está dispersa. ABSTRACT A method based on an iterative application of high order singular value decomposition is derived for the reconstruction of missing data in multidimensional databases. The method is inspired by a seminal gappy reconstruction method for two-dimensional databases invented by Everson and Sirovich (1995) and improved by Beckers and Rixen (2003) and Venturi and Karniadakis (2004). In addition, the method is adapted to treat both noisy and structured-but-nonrectangular databases. The method is calibrated and illustrated using a three-dimensional toy model database that is obtained by discretizing a transcendental function. The performance of the method is tested on three aerodynamic databases for the flow past a wing, one obtained by a semi-analytical method, and two resulting from computational fluid dynamics. The method is finally applied to an experimental database consisting in a non-exhaustive parameter space measurement of forces for a box-wing configuration.

Aerodynamic database error filtering via high order singular value decomposition

Esta Tesis presenta un nuevo método para filtrar errores en bases de datos multidimensionales. Este método no precisa ninguna información a priori sobre la naturaleza de los errores. En concreto, los errrores no deben ser necesariamente pequeños, ni de distribución aleatoria ni tener media cero. El único requerimiento es que no estén correlados con la información limpia propia de la base de datos. Este nuevo método se basa en una extensión mejorada del método básico de reconstrucción de huecos (capaz de reconstruir la información que falta de una base de datos multidimensional en posiciones conocidas) inventado por Everson y Sirovich (1995). El método de reconstrucción de huecos mejorado ha evolucionado como un método de filtrado de errores de dos pasos: en primer lugar, (a) identifica las posiciones en la base de datos afectadas por los errores y después, (b) reconstruye la información en dichas posiciones tratando la información de éstas como información desconocida. El método resultante filtra errores O(1) de forma eficiente, tanto si son errores aleatorios como sistemáticos e incluso si su distribución en la base de datos está concentrada o esparcida por ella. Primero, se ilustra el funcionamiento delmétodo con una base de datosmodelo bidimensional, que resulta de la dicretización de una función transcendental. Posteriormente, se presentan algunos casos prácticos de aplicación del método a dos bases de datos tridimensionales aerodinámicas que contienen la distribución de presiones sobre un ala a varios ángulos de ataque. Estas bases de datos resultan de modelos numéricos calculados en CFD. ABSTRACT A method is presented to filter errors out in multidimensional databases. The method does not require any a priori information about the nature the errors. In particular, the errors need not to be small, neither random, nor exhibit zero mean. Instead, they are only required to be relatively uncorrelated to the clean information contained in the database. The method is based on an improved extension of a seminal iterative gappy reconstruction method (able to reconstruct lost information at known positions in the database) due to Everson and Sirovich (1995). The improved gappy reconstruction method is evolved as an error filtering method in two steps, since it is adapted to first (a) identify the error locations in the database and then (b) reconstruct the information in these locations by treating the associated data as gappy data. The resultingmethod filters out O(1) errors in an efficient fashion, both when these are random and when they are systematic, and also both when they concentrated and when they are spread along the database. The performance of the method is first illustrated using a two-dimensional toymodel database resulting fromdiscretizing a transcendental function and then tested on two CFD-calculated, three-dimensional aerodynamic databases containing the pressure coefficient on the surface of a wing for varying values of the angle of attack. A more general performance analysis of the method is presented with the intention of quantifying the randomness factor the method admits maintaining a correct performance and secondly, quantifying the size of error the method can detect. Lastly, some improvements of the method are proposed with their respective verification.

No ·NO from NO synthase

The nitric-oxide synthase (NOS; EC 1.14.13.39) reaction is formulated as a partially tetrahydrobiopterin (H4Bip)-dependent 5-electron oxidation of a terminal guanidino nitrogen of l-arginine (Arg) associated with stoichiometric consumption of dioxygen (O2) and 1.5 mol of NADPH to form l-citrulline (Cit) and nitric oxide (·NO). Analysis of NOS activity has relied largely on indirect methods such as quantification of nitrite/nitrate or the coproduct Cit; we therefore sought to directly quantify ·NO formation from purified NOS. However, by two independent methods, NOS did not yield detectable ·NO unless superoxide dismutase (SOD; EC 1.15.1.1) was present. In the presence of H4Bip, internal ·NO standards were only partially recovered and the dismutation of superoxide (O2⨪), which otherwise scavenges ·NO to yield ONOO−, was a plausible mechanism of action of SOD. Under these conditions, a reaction between NADPH and ONOO− resulted in considerable overestimation of enzymatic NADPH consumption. SOD lowered the NADPH:Cit stoichiometry to 0.8–1.1, suggesting either that additional reducing equivalents besides NADPH are required to explain Arg oxidation to ·NO or that ·NO was not primarily formed. The latter was supported by an additional set of experiments in the absence of H4Bip. Here, recovery of internal ·NO standards was unaffected. Thus, a second activity of SOD, the conversion of nitroxyl (NO−) to ·NO, was a more likely mechanism of action of SOD. Detection of NOS-derived nitrous oxide (N2O) and hydroxylamine (NH2OH), which cannot arise from ·NO decomposition, was consistent with formation of an ·NO precursor molecule such as NO−. When, in the presence of SOD, glutathione was added, S-nitrosoglutathione was detected. Our results indicate that ·NO is not the primary reaction product of NOS-catalyzed Arg turnover and an alternative reaction mechanism and stoichiometry have to be taken into account.

The decomposition of peroxynitrite does not yield nitroxyl anion and singlet oxygen

In a recent article [Khan, A. U., Kovacic, D., Kolbanovsky, A., Desai, M., Frenkel, K. & Geacintov, N. E. (2000) Proc. Natl. Acad. Sci. USA 97, 2984–2989], the authors claimed that ONOO−, after protonation to ONOOH, decomposes into 1HNO and 1O2 according to a spin-conserved unimolecular mechanism. This claim was based partially on their observation that nitrosylhemoglobin is formed via the reaction of peroxynitrite with methemoglobin at neutral pH. However, thermochemical considerations show that the yields of 1O2 and 1HNO are about 23 orders of magnitude lower than those of ⋅NO2 and ⋅OH, which are formed via the homolysis of ONOOH. We also show that methemoglobin does not form with peroxynitrite any spectrally detectable product, but with contaminations of nitrite and H2O2 present in the peroxynitrite sample. Thus, there is no need to modify the present view of the mechanism of ONOOH decomposition, according to which initial homolysis into a radical pair, [ONO⋅ ⋅OH]cage, is followed by the diffusion of about 30% of the radicals out of the cage, while the rest recombines to nitric acid in the solvent cage.

Singular value decomposition for genome-wide expression data processing and modeling

We describe the use of singular value decomposition in transforming genome-wide expression data from genes × arrays space to reduced diagonalized “eigengenes” × “eigenarrays” space, where the eigengenes (or eigenarrays) are unique orthonormal superpositions of the genes (or arrays). Normalizing the data by filtering out the eigengenes (and eigenarrays) that are inferred to represent noise or experimental artifacts enables meaningful comparison of the expression of different genes across different arrays in different experiments. Sorting the data according to the eigengenes and eigenarrays gives a global picture of the dynamics of gene expression, in which individual genes and arrays appear to be classified into groups of similar regulation and function, or similar cellular state and biological phenotype, respectively. After normalization and sorting, the significant eigengenes and eigenarrays can be associated with observed genome-wide effects of regulators, or with measured samples, in which these regulators are overactive or underactive, respectively.