Evaluation of a photosynthesis-based biogenic isoprene emission scheme in JULES and simulation of isoprene emissions under present-day climate conditions

We have incorporated a semi-mechanistic isoprene emission module into the JULES land-surface scheme, as a first step towards a modelling tool that can be applied for studies of vegetation – atmospheric chemistry interactions, including chemistry-climate feedbacks. Here, we evaluate the coupled model against local above-canopy isoprene emission flux measurements from six flux tower sites as well as satellite-derived estimates of isoprene emission over tropical South America and east and south Asia. The model simulates diurnal variability well: correlation coefficients are significant (at the 95 % level) for all flux tower sites. The model reproduces day-to-day variability with significant correlations (at the 95 % confidence level) at four of the six flux tower sites. At the UMBS site, a complete set of seasonal observations is available for two years (2000 and 2002). The model reproduces the seasonal pattern of emission during 2002, but does less well in the year 2000. The model overestimates observed emissions at all sites, which is partially because it does not include isoprene loss through the canopy. Comparison with the satellite-derived isoprene-emission estimates suggests that the model simulates the main spatial patterns, seasonal and inter-annual variability over tropical regions. The model yields a global annual isoprene emission of 535 ± 9 TgC yr−1 during the 1990s, 78 % of which from forested areas.

Variability and trends in stratospheric NO2 in Antarctic summer, and implications for stratospheric NOy

NO2 measurements during 1990–2007, obtained from a zenith-sky spectrometer in the Antarctic, are analysed to determine the long-term changes in NO2. An atmospheric photochemical box model and a radiative transfer model are used to improve the accuracy of determination of the vertical columns from the slant column measurements, and to deduce the amount of NOy from NO2. We find that the NO2 and NOy columns in midsummer have large inter-annual variability superimposed on a broad maximum in 2000, with little or no overall trend over the full time period. These changes are robust to a variety of alternative settings when determining vertical columns from slant columns or determining NOy from NO2. They may signify similar changes in speed of the Brewer-Dobson circulation but with opposite sign, i.e. a broad minimum around 2000. Multiple regressions show significant correlation with solar and quasi-biennial-oscillation indices, and weak correlation with El Nino, but no significant overall trend, corresponding to an increase in Brewer-Dobson circulation of 1.4±3.5%/decade. There remains an unexplained cycle of amplitude and period at least 15% and 17 years, with minimum speed in about 2000.

MetUM-GOML: a near-globally coupled atmosphere–ocean-mixed-layer model

Well-resolved air–sea interactions are simulated in a new ocean mixed-layer, coupled configuration of the Met Office Unified Model (MetUM-GOML), comprising the MetUM coupled to the Multi-Column K Profile Parameterization ocean (MC-KPP). This is the first globally coupled system which provides a vertically resolved, high near-surface resolution ocean at comparable computational cost to running in atmosphere-only mode. As well as being computationally inexpensive, this modelling framework is adaptable– the independent MC-KPP columns can be applied selectively in space and time – and controllable – by using temperature and salinity corrections the model can be constrained to any ocean state. The framework provides a powerful research tool for process-based studies of the impact of air–sea interactions in the global climate system. MetUM simulations have been performed which separate the impact of introducing inter- annual variability in sea surface temperatures (SSTs) from the impact of having atmosphere–ocean feedbacks. The representation of key aspects of tropical and extratropical variability are used to assess the performance of these simulations. Coupling the MetUM to MC-KPP is shown, for example, to reduce tropical precipitation biases, improve the propagation of, and spectral power associated with, the Madden–Julian Oscillation and produce closer-to-observed patterns of springtime blocking activity over the Euro-Atlantic region.

Future changes of wind energy potentials over Europe in a large CMIP5 multi-model ensemble

A statistical-dynamical downscaling method is used to estimate future changes of wind energy output (Eout) of a benchmark wind turbine across Europe at the regional scale. With this aim, 22 global climate models (GCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble are considered. The downscaling method uses circulation weather types and regional climate modelling with the COSMO-CLM model. Future projections are computed for two time periods (2021–2060 and 2061–2100) following two scenarios (RCP4.5 and RCP8.5). The CMIP5 ensemble mean response reveals a more likely than not increase of mean annual Eout over Northern and Central Europe and a likely decrease over Southern Europe. There is some uncertainty with respect to the magnitude and the sign of the changes. Higher robustness in future changes is observed for specific seasons. Except from the Mediterranean area, an ensemble mean increase of Eout is simulated for winter and a decreasing for the summer season, resulting in a strong increase of the intra-annual variability for most of Europe. The latter is, in particular, probable during the second half of the 21st century under the RCP8.5 scenario. In general, signals are stronger for 2061–2100 compared to 2021–2060 and for RCP8.5 compared to RCP4.5. Regarding changes of the inter-annual variability of Eout for Central Europe, the future projections strongly vary between individual models and also between future periods and scenarios within single models. This study showed for an ensemble of 22 CMIP5 models that changes in the wind energy potentials over Europe may take place in future decades. However, due to the uncertainties detected in this research, further investigations with multi-model ensembles are needed to provide a better quantification and understanding of the future changes.

Latitudinal gradients in butterfly population variability are influenced by landscape heterogeneity

The variability of populations over time is positively associated with their risk of local extinction. Previous work has shown that populations at the high-latitude boundary of species’ ranges show higher inter-annual variability, consistent with increased sensitivity and exposure to adverse climatic conditions. However, patterns of population variability at both high- and low-latitude species range boundaries have not yet been concurrently examined. Here, we assess the inter-annual population variability of 28 butterfly species between 1994 and 2009 at 351 and 18 sites in the United Kingdom and Catalonia, Spain, respectively. Local population variability is examined with respect to the position of the species’ bioclimatic envelopes (i.e. whether the population falls within areas of the ‘core’ climatic suitability or is a climatically ‘marginal’ population), and in relation to local landscape heterogeneity, which may influence these range location – population dynamic relationships. We found that butterfly species consistently show latitudinal gradients in population variability, with increased variability in the more northerly UK. This pattern is even more marked for southerly distributed species with ‘marginal’ climatic suitability in the UK but ‘core’ climatic suitability in Catalonia. In addition, local landscape heterogeneity did influence these range location – population dynamic relationships. Habitat heterogeneity was associated with dampened population dynamics, especially for populations in the UK. Our results suggest that promoting habitat heterogeneity may promote the persistence of populations at high-latitude range boundaries, which may potentially aid northwards expansion under climate warming. We did not find evidence that population variability increases towards southern range boundaries. Sample sizes for this region were low, but there was tentative evidence, in line with previous ecological theory, that local landscape heterogeneity may promote persistence in these retracting low-latitude range boundary populations.

Genetic variability among the wild boars (Sus scrofa scrofa), crossbred animals and pigs using microsatellite markers (STRs)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Peptide diversity in the venom of the social wasp Polybia paulista (Hymenoptera): A comparison of the intra- and inter-colony compositions

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Intra- and inter-individual variation of BIS-index and Entropy during controlled sedation with midazolam/remifentanil and dexmedetomidine/remifentanil in healthy volunteers: an interventional study

INTRODUCTION: We studied intra-individual and inter-individual variability of two online sedation monitors, BIS and Entropy, in volunteers under sedation. METHODS: Ten healthy volunteers were sedated in a stepwise manner with doses of either midazolam and remifentanil or dexmedetomidine and remifentanil. One week later the procedure was repeated with the remaining drug combination. The doses were adjusted to achieve three different sedation levels (Ramsay Scores 2, 3 and 4) and controlled by a computer-driven drug-delivery system to maintain stable plasma concentrations of the drugs. At each level of sedation, BIS and Entropy (response entropy and state entropy) values were recorded for 20 minutes. Baseline recordings were obtained before the sedative medications were administered. RESULTS: Both inter-individual and intra-individual variability increased as the sedation level deepened. Entropy values showed greater variability than BIS(R) values, and the variability was greater during dexmedetomidine/remifentanil sedation than during midazolam/remifentanil sedation. CONCLUSIONS: The large intra-individual and inter-individual variability of BIS and Entropy values in sedated volunteers makes the determination of sedation levels by processed electroencephalogram (EEG) variables impossible. Reports in the literature which draw conclusions based on processed EEG variables obtained from sedated intensive care unit (ICU) patients may be inaccurate due to this variability. TRIAL REGISTRATION: clinicaltrials.gov Nr. NCT00641563.

Zur interindividuellen Variabilität affektiver Reaktionen im Verlauf von Freizeit- und Gesundheitssportprogrammen

Positive Effekte sportlicher Aktivität auf das aktuelle Befinden sind meta-analytisch gut dokumentiert. Eine Generalisierung der Befunde wird dadurch eingeschränkt, dass zunehmend eine hohe interindividuelle Variabilität beobachtet wird und Prozesse während der Aktivität defizitär berücksichtigt wurden. Dieser Beitrag geht den Fragen nach, wie groß das Ausmaß interindividueller Variabilität affektiver Reaktionen im Verlauf von gruppenbasierten Freizeit- und Gesundheitssportaktivitäten ist und welchen Einfluss personale Voraussetzungen (Fitnesszustand) und Faktoren der Auseinandersetzung mit der Aktivität (Beanspruchungserleben, Kompetenzwahrnehmung, positives Gruppenerleben) nehmen. Speziell interessiert, inwieweit affektive Reaktionen in Abhängigkeit vom Zeitpunkt sowie in Abhängigkeit der Intensität von unterschiedlichen Faktoren beeinflusst werden. Dazu wurden 110 Universitätsangestellte (M = 49.5 Jahre) wiederholt im Rahmen von mehrwöchigen Programmen befragt. An insgesamt sechs Terminen wurden Handheld-PC-Befragungen vor, zweimal während und nach der Kursstunde durchgeführt, mit denen das aktuelle Befinden und mögliche Einflussfaktoren erfasst wurden. Die Ergebnisse zeigen, dass die Variabilität affektiver Reaktionen im ersten Abschnitt der Sportprogramme am größten ist, während die Reaktionen am Ende der Kursstunde insgesamt positiver und homogener ausfallen. Im ersten Abschnitt sind personale Voraussetzungen noch wichtige Einflussfaktoren, während die Bedeutung der wahrgenommenen Kompetenz und des positiven Gruppenerlebens im Verlauf der Sportaktivität größer wird. Im Einklang mit der Dual Mode Theory weist die Kompetenzwahrnehmung bei anstrengender Intensität im Vergleich zu moderater Intensität einen größeren Zusammenhang mit dem Befinden auf.

Synoptic drivers of 400 years of summer temperature and precipitation variability on Mt. Olympus, Greece

The Mediterranean region has been identified as a global warming hotspot, where future climate impacts are expected to have significant consequences on societal and ecosystem well-being. To put ongoing trends of summer climate into the context of past natural variability, we reconstructed climate from maximum latewood density (MXD) measurements of Pinus heldreichii (1521–2010) and latewood width (LWW) of Pinus nigra (1617–2010) on Mt. Olympus, Greece. Previous research in the northeastern Mediterranean has primarily focused on inter-annual variability, omitting any low-frequency trends. The present study utilizes methods capable of retaining climatically driven long-term behavior of tree growth. The LWW chronology corresponds closely to early summer moisture variability (May–July, r = 0.65, p < 0.001, 1950–2010), whereas the MXD-chronology relates mainly to late summer warmth (July–September, r = 0.64, p < 0.001; 1899–2010). The chronologies show opposing patterns of decadal variability over the twentieth century (r = −0.68, p < 0.001) and confirm the importance of the summer North Atlantic Oscillation (sNAO) for summer climate in the northeastern Mediterranean, with positive sNAO phases inducing cold anomalies and enhanced cloudiness and precipitation. The combined reconstructions document the late twentieth—early twenty-first century warming and drying trend, but indicate generally drier early summer and cooler late summer conditions in the period ~1700–1900 CE. Our findings suggest a potential decoupling between twentieth century atmospheric circulation patterns and pre-industrial climate variability. Furthermore, the range of natural climate variability stretches beyond summer moisture availabilityobserved in recent decades and thus lends credibility to the significant drying trends projected for this region in current Earth System Model simulations.

Analysis of hand kinematics reveals inter-individual differences in intertemporal decision dynamics

During intertemporal decisions, the preference for smaller, sooner reward over larger-delayed rewards (temporal discounting, TD) exhibits substantial inter-subject variability; however, it is currently unclear what are the mechanisms underlying this apparently idiosyncratic behavior. To answer this question, here we recorded and analyzed mouse movement kinematics during intertemporal choices in a large sample of participants (N = 86). Results revealed a specific pattern of decision dynamics associated with the selection of “immediate” versus “delayed” response alternatives, which well discriminated between a “discounter” versus a “farsighted” behavior—thus representing a reliable behavioral marker of TD preferences. By fitting the Drift Diffusion Model to the data, we showed that differences between discounter and farsighted subjects could be explained in terms of different model parameterizations, corresponding to the use of different choice mechanisms in the two groups. While farsighted subjects were biased toward the “delayed” option, discounter subjects were not correspondingly biased toward the “immediate” option. Rather, as shown by the dynamics of evidence accumulation over time, their behavior was characterized by high choice uncertainty.

Continuous 25-years aerosol records at coastal Antarctica: Part I. Variability and climate implications of ionic compounds

The aerosol climatology at the coastal Antarctic Neumayer Station (NM) was investigated based on continuous, 25-yr long observations of biogenic sulphur components (methanesulfonate and non-sea salt sulphate), sea salt and nitrate. Although significant long-term trends could only be detected for nitrate (-3.6 ± 2.5% per year between 1983 and 1993 and +4.0 ± 3.2% per year from 1993-2007), non-harmonic periodicities between 2 and 5 yr were typical for all species. Dedicated time series analyses revealed that relations to sea ice extent and various circulation indices are weak at best or not significant. In particular, no consistent link between sea ice extent and sea salt loadings was evident suggesting only a rather local relevance of the NM sea salt record. Nevertheless, a higher Southern Annular Mode index tended to entail a lower biogenic sulphur signal. In examining the spatial uniformity of the NM findings we contrasted them to respective 17 yr records from the coastal Dumont d'Urville Station. We found similar long-term trends for nitrate, indicating an Antarctic-wide but not identifiable atmospheric signal, although any significant impact of solar activity or pollution could be ruled out. No inter-site variability on the multiannual scale was evident for the other ionic compounds.

Generalización de variables medioambientales mediante interpolación GIS

La investigación de esta tesis se centra en el estudio de técnicas geoestadísticas y su contribución a una mayor caracterización del binomio factores climáticos-rendimiento de un cultivo agrícola. El inexorable vínculo entre la variabilidad climática y la producción agrícola cobra especial relevancia en estudios sobre el cambio climático o en la modelización de cultivos para dar respuesta a escenarios futuros de producción mundial. Es información especialmente valiosa en sistemas operacionales de monitoreo y predicción de rendimientos de cultivos Los cuales son actualmente uno de los pilares operacionales en los que se sustenta la agricultura y seguridad alimentaria mundial; ya que su objetivo final es el de proporcionar información imparcial y fiable para la regularización de mercados. Es en este contexto, donde se quiso dar un enfoque alternativo a estudios, que con distintos planteamientos, analizan la relación inter-anual clima vs producción. Así, se sustituyó la dimensión tiempo por la espacio, re-orientando el análisis estadístico de correlación interanual entre rendimiento y factores climáticos, por el estudio de la correlación inter-regional entre ambas variables. Se utilizó para ello una técnica estadística relativamente nueva y no muy aplicada en investigaciones similares, llamada regresión ponderada geográficamente (GWR, siglas en inglés de “Geographically weighted regression”). Se obtuvieron superficies continuas de las variables climáticas acumuladas en determinados periodos fenológicos, que fueron seleccionados por ser factores clave en el desarrollo vegetativo de un cultivo. Por ello, la primera parte de la tesis, consistió en un análisis exploratorio sobre comparación de Métodos de Interpolación Espacial (MIE). Partiendo de la hipótesis de que existe la variabilidad espacial de la relación entre factores climáticos y rendimiento, el objetivo principal de esta tesis, fue el de establecer en qué medida los MIE y otros métodos geoestadísticos de regresión local, pueden ayudar por un lado, a alcanzar un mayor entendimiento del binomio clima-rendimiento del trigo blando (Triticum aestivum L.) al incorporar en dicha relación el componente espacial; y por otro, a caracterizar la variación de los principales factores climáticos limitantes en el crecimiento del trigo blando, acumulados éstos en cuatro periodos fenológicos. Para lleva a cabo esto, una gran carga operacional en la investigación de la tesis consistió en homogeneizar y hacer los datos fenológicos, climáticos y estadísticas agrícolas comparables tanto a escala espacial como a escala temporal. Para España y los Bálticos se recolectaron y calcularon datos diarios de precipitación, temperatura máxima y mínima, evapotranspiración y radiación solar en las estaciones meteorológicas disponibles. Se dispuso de una serie temporal que coincidía con los mismos años recolectados en las estadísticas agrícolas, es decir, 14 años contados desde 2000 a 2013 (hasta 2011 en los Bálticos). Se superpuso la malla de información fenológica de cuadrícula 25 km con la ubicación de las estaciones meteorológicas con el fin de conocer los valores fenológicos en cada una de las estaciones disponibles. Hecho esto, para cada año de la serie temporal disponible se calcularon los valores climáticos diarios acumulados en cada uno de los cuatro periodos fenológicos seleccionados P1 (ciclo completo), P2 (emergencia-madurez), P3 (floración) y P4 (floraciónmadurez). Se calculó la superficie interpolada por el conjunto de métodos seleccionados en la comparación: técnicas deterministas convencionales, kriging ordinario y cokriging ordinario ponderado por la altitud. Seleccionados los métodos más eficaces, se calculó a nivel de provincias las variables climatológicas interpoladas. Y se realizaron las regresiones locales GWR para cuantificar, explorar y modelar las relaciones espaciales entre el rendimiento del trigo y las variables climáticas acumuladas en los cuatro periodos fenológicos. Al comparar la eficiencia de los MIE no destaca una técnica por encima del resto como la que proporcione el menor error en su predicción. Ahora bien, considerando los tres indicadores de calidad de los MIE estudiados se han identificado los métodos más efectivos. En el caso de la precipitación, es la técnica geoestadística cokriging la más idónea en la mayoría de los casos. De manera unánime, la interpolación determinista en función radial (spline regularizado) fue la técnica que mejor describía la superficie de precipitación acumulada en los cuatro periodos fenológicos. Los resultados son más heterogéneos para la evapotranspiración y radiación. Los métodos idóneos para estas se reparten entre el Inverse Distance Weighting (IDW), IDW ponderado por la altitud y el Ordinary Kriging (OK). También, se identificó que para la mayoría de los casos en que el error del Ordinary CoKriging (COK) era mayor que el del OK su eficacia es comparable a la del OK en términos de error y el requerimiento computacional de este último es mucho menor. Se pudo confirmar que existe la variabilidad espacial inter-regional entre factores climáticos y el rendimiento del trigo blando tanto en España como en los Bálticos. La herramienta estadística GWR fue capaz de reproducir esta variabilidad con un rendimiento lo suficientemente significativo como para considerarla una herramienta válida en futuros estudios. No obstante, se identificaron ciertas limitaciones en la misma respecto a la información que devuelve el programa a nivel local y que no permite desgranar todo el detalle sobre la ejecución del mismo. Los indicadores y periodos fenológicos que mejor pudieron reproducir la variabilidad espacial del rendimiento en España y Bálticos, arrojaron aún, una mayor credibilidad a los resultados obtenidos y a la eficacia del GWR, ya que estaban en línea con el conocimiento agronómico sobre el cultivo del trigo blando en sistemas agrícolas mediterráneos y norteuropeos. Así, en España, el indicador más robusto fue el balance climático hídrico Climatic Water Balance) acumulado éste, durante el periodo de crecimiento (entre la emergencia y madurez). Aunque se identificó la etapa clave de la floración como el periodo en el que las variables climáticas acumuladas proporcionaban un mayor poder explicativo del modelo GWR. Sin embargo, en los Bálticos, países donde el principal factor limitante en su agricultura es el bajo número de días de crecimiento efectivo, el indicador más efectivo fue la radiación acumulada a lo largo de todo el ciclo de crecimiento (entre la emergencia y madurez). Para el trigo en regadío no existe ninguna combinación que pueda explicar más allá del 30% de la variación del rendimiento en España. Poder demostrar que existe un comportamiento heterogéneo en la relación inter-regional entre el rendimiento y principales variables climáticas, podría contribuir a uno de los mayores desafíos a los que se enfrentan, a día de hoy, los sistemas operacionales de monitoreo y predicción de rendimientos de cultivos, y éste es el de poder reducir la escala espacial de predicción, de un nivel nacional a otro regional. ABSTRACT This thesis explores geostatistical techniques and their contribution to a better characterization of the relationship between climate factors and agricultural crop yields. The crucial link between climate variability and crop production plays a key role in climate change research as well as in crops modelling towards the future global production scenarios. This information is particularly important for monitoring and forecasting operational crop systems. These geostatistical techniques are currently one of the most fundamental operational systems on which global agriculture and food security rely on; with the final aim of providing neutral and reliable information for food market controls, thus avoiding financial speculation of nourishments of primary necessity. Within this context the present thesis aims to provide an alternative approach to the existing body of research examining the relationship between inter-annual climate and production. Therefore, the temporal dimension was replaced for the spatial dimension, re-orienting the statistical analysis of the inter-annual relationship between crops yields and climate factors to an inter-regional correlation between these two variables. Geographically weighted regression, which is a relatively new statistical technique and which has rarely been used in previous research on this topic was used in the current study. Continuous surface values of the climate accumulated variables in specific phenological periods were obtained. These specific periods were selected because they are key factors in the development of vegetative crop. Therefore, the first part of this thesis presents an exploratory analysis regarding the comparability of spatial interpolation methods (SIM) among diverse SIMs and alternative geostatistical methodologies. Given the premise that spatial variability of the relationship between climate factors and crop production exists, the primary aim of this thesis was to examine the extent to which the SIM and other geostatistical methods of local regression (which are integrated tools of the GIS software) are useful in relating crop production and climate variables. The usefulness of these methods was examined in two ways; on one hand the way this information could help to achieve higher production of the white wheat binomial (Triticum aestivum L.) by incorporating the spatial component in the examination of the above-mentioned relationship. On the other hand, the way it helps with the characterization of the key limiting climate factors of soft wheat growth which were analysed in four phenological periods. To achieve this aim, an important operational workload of this thesis consisted in the homogenization and obtention of comparable phenological and climate data, as well as agricultural statistics, which made heavy operational demands. For Spain and the Baltic countries, data on precipitation, maximum and minimum temperature, evapotranspiration and solar radiation from the available meteorological stations were gathered and calculated. A temporal serial approach was taken. These temporal series aligned with the years that agriculture statistics had previously gathered, these being 14 years from 2000 to 2013 (until 2011 for the Baltic countries). This temporal series was mapped with a phenological 25 km grid that had the location of the meteorological stations with the objective of obtaining the phenological values in each of the available stations. Following this procedure, the daily accumulated climate values for each of the four selected phenological periods were calculated; namely P1 (complete cycle), P2 (emergency-maturity), P3 (flowering) and P4 (flowering- maturity). The interpolated surface was then calculated using the set of selected methodologies for the comparison: deterministic conventional techniques, ordinary kriging and ordinary cokriging weighted by height. Once the most effective methods had been selected, the level of the interpolated climate variables was calculated. Local GWR regressions were calculated to quantify, examine and model the spatial relationships between soft wheat production and the accumulated variables in each of the four selected phenological periods. Results from the comparison among the SIMs revealed that no particular technique seems more favourable in terms of accuracy of prediction. However, when the three quality indicators of the compared SIMs are considered, some methodologies appeared to be more efficient than others. Regarding precipitation results, cokriging was the most accurate geostatistical technique for the majority of the cases. Deterministic interpolation in its radial function (controlled spline) was the most accurate technique for describing the accumulated precipitation surface in all phenological periods. However, results are more heterogeneous for the evapotranspiration and radiation methodologies. The most appropriate technique for these forecasts are the Inverse Distance Weighting (IDW), weighted IDW by height and the Ordinary Kriging (OK). Furthermore, it was found that for the majority of the cases where the Ordinary CoKriging (COK) error was larger than that of the OK, its efficacy was comparable to that of the OK in terms of error while the computational demands of the latter was much lower. The existing spatial inter-regional variability between climate factors and soft wheat production was confirmed for both Spain and the Baltic countries. The GWR statistic tool reproduced this variability with an outcome significative enough as to be considered a valid tool for future studies. Nevertheless, this tool also had some limitations with regards to the information delivered by the programme because it did not allow for a detailed break-down of its procedure. The indicators and phenological periods that best reproduced the spatial variability of yields in Spain and the Baltic countries made the results and the efficiency of the GWR statistical tool even more reliable, despite the fact that these were already aligned with the agricultural knowledge about soft wheat crop under mediterranean and northeuropean agricultural systems. Thus, for Spain, the most robust indicator was the Climatic Water Balance outcome accumulated throughout the growing period (between emergency and maturity). Although the flowering period was the phase that best explained the accumulated climate variables in the GWR model. For the Baltic countries where the main limiting agricultural factor is the number of days of effective growth, the most effective indicator was the accumulated radiation throughout the entire growing cycle (between emergency and maturity). For the irrigated soft wheat there was no combination capable of explaining above the 30% of variation of the production in Spain. The fact that the pattern of the inter-regional relationship between the crop production and key climate variables is heterogeneous within a country could contribute to one is one of the greatest challenges that the monitoring and forecasting operational systems for crop production face nowadays. The present findings suggest that the solution may lay in downscaling the spatial target scale from a national to a regional level.

Paediatric population pharmacokinetics of itraconazole and its active metabolite hydroxy-itraconazole in cystic fibrosis and bone marrow transplant patients

Objectives: The aim of the study was to characterise the population pharmacokinetics (popPK) properties of itraconazole (ITRA) and its active metabolite hydroxy-ITRA in a representative paediatric population of cystic fibrosis (CF) and bone marrow transplant (BMT) patients. The goals were to determine the relative bioavailability between the two oral formulations, and to explore improved dosage regimens in these patients. Methods: All paediatric patients with CF taking oral ITRA for the treatment of allergic bronchopulmonary aspergillosis and patients undergoing BMT who were taking ITRA for prophylaxis of any fungal infection were eligible for the study. A minimum of two blood samples were drawn after the capsules and also after switching to oral solution, or vice versa. ITRA and hydroxy-ITRA plasma concentrations were measured by HPLC[1]. A nonlinear mixed-effect modelling approach (NONMEM 5.1.1) was used to describe the PK of ITRA and hydroxy-ITRA simultaneously. Simulations were used to assess dosing strategies in these patients. Results: Forty-nine patients (29CF, 20 BMT) were recruited to the study who provided 227 blood samples for the population analysis. A 1-compartment model with 1st order absorption and elimination best described ITRA kinetics, with 1st order conversion to hydroxy-ITRA. For ITRA, the apparent clearance (ClItra/F) and volume of distribution (Vitra/F) was 35.5L/h and 672L, respectively; the absorption rate constant for the capsule formulation was 0.0901 h-1 and for the oral solution formulation it was 0.959 h-1. The capsule comparative bioavailability (vs. solution) was 0.55. For hydroxy-ITRA, the apparent volume of distribution and clearance were 10.6 L and 5.28 L/h, respectively. Of several screened covariates only allometrically scaled total body weight significantly improved the fit to the data. No difference between the two populations was found. Conclusion: The developed popPK model adequately described the pharmacokinetics of ITRA and hydroxy-ITRA in paediatric patients with CF and patients undergoing BMT. High inter-patient variability confirmed previous data in CF[2], leukaemia and BMT[3] patients. From the population model, simulations showed the standard dose (5 mg/kg/day) needs to be doubled for the solution formulation and even 4 times more given of the capsules to achieve an adequate target therapeutic trough plasma concentration of 0.5 mg/L[4] in these patients.