Abundance of phytoplankton in the Cilician Basin during the Bilim 2 cruise in March 2008

The dataset is composed of 57 samples from 15 stations. The phytoplankton samples were collected by 5l Niskin bottles attached to the CTD system. The sampling depths were selected according to the CTD profiles and the in situ fluorometer readings. The samples (50 ml sea water) were preserved with prefiltered (0.2 micron) glutardialdehyde solution (1.5 ml of commercial glutardialdehyde (25%)) into dark colored glass bottles. Preserved samples were poured into 10 or 25 ml settling chambers (Hydro-Bios) for cells to settle on the bottom over a day. Species identification and enumeration were done under an inverted microscope (Olympus IX71). At least 400 specimen were tried to be counted in each sample.

Abundance of phytoplankton in the Black Sea during the Bilim 2 cruise in October 2008

The dataset is composed of 34 samples from 23 stations. The phytoplankton samples were collected by 5l Niskin bottles attached to the CTD system. The sampling depths were selected according to the CTD profiles and the in situ fluorometer readings. The samples (50 ml sea water) were preserved with prefiltered (0.2 micron) glutardialdehyde solution (1.5 ml of commercial glutardialdehyde (25%)) into dark colored glass bottles. Preserved samples were poured into 10 or 25 ml settling chambers (Hydro-Bios) for cells to settle on the bottom over a day. Species identification and enumeration were done under an inverted microscope (Olympus IX71). At least 400 specimen were tried to be counted in each sample.

Abundance of phytoplankton in the Marmara Sea collected during the Bilim 2 cruise in Oktober 2008

The dataset is composed of 22 samples from 14 stations. The phytoplankton samples were collected by 5l Niskin bottles attached to the CTD system. The sampling depths were selected according to the CTD profiles and the in situ fluorometer readings. The samples (50 ml sea water) were preserved with prefiltered (0.2 micron) glutardialdehyde solution (1.5 ml of commercial glutardialdehyde (25%)) into dark colored glass bottles. Preserved samples were poured into 10 or 25 ml settling chambers (Hydro-Bios) for cells to settle on the bottom over a day. Species identification and enumeration were done under an inverted microscope (Olympus IX71). At least 400 specimen were tried to be counted in each sample.

Abundance and biomass of phytoplankton in the western part of the Black Sea during Parshin cruise BSRP in September and October 2005

The dataset is composed of 61 samples from 15 stations. The phytoplankton samples were collected by 5l Niskin bottles attached to the CTD system. The sampling depths were selected according to the CTD profile and the in situ fluorometer readings: surface, temperature, salinity and fluorescence gradients and 1 m above the bottom. At some stations phytoplankton net samples (20 µm mesh-size) were collected to assist species biodiversity examination. The samples (1l sea water) were preserved in 4% buffered to pH 8-8.2 with disodiumtetraborate formaldehyde solution and stored in plastic containers. On board at each station few live samples were qualitatively examined under microscope for preliminary analysis of taxonomic composition and dominant species. Taxon-specific phytoplankton abundance were concentrated down to 50 cm**3 by slow decantation after storage for 20 days in a cool and dark place. The species identification was done under light microscope OLIMPUS-BS41 connected to a video-interactive image analysis system at magnification of the ocular 10X and objective - 40X. A Sedgwick-Rafter camera (1ml) was used for counting. 400 specimen were counted for each sample, while rare and large species were checked in the whole sample (Manual of phytoplankton, 2005). Species identification was mainly after Carmelo T. (1997) and Fukuyo, Y. (2000). The cell biovolume of the taxon-specific phytoplankton biomass was determined based on morpho-metric measurement of phytoplankton units and the corresponding geometric shapes as described in detail in (Edier, 1979).

Abundance of phytoplankton in the Black Sea during the Bilim 2 cruise in April 2008

The dataset is composed of 46 samples from 9 stations. The phytoplankton samples were collected by 5l Niskin bottles attached to the CTD system. The sampling depths were selected according to the CTD profiles and the in situ fluorometer readings. The samples (50 ml sea water) were preserved with prefiltered (0.2 micron) glutardialdehyde solution (1.5 ml of commercial glutardialdehyde (25%)) into dark colored glass bottles. Preserved samples were poured into 10 or 25 ml settling chambers (Hydro-Bios) for cells to settle on the bottom over a day. Species identification and enumeration were done under an inverted microscope (Olympus IX71). At least 400 specimen were tried to be counted in each sample.

Abundance of phytoplankton in the Marmara Sea collected during the Bilim 2 cruise in April 2008

The dataset is composed of 48 samples from 17 stations. The phytoplankton samples were collected by 5l Niskin bottles attached to the CTD system. The sampling depths were selected according to the CTD profiles and the in situ fluorometer readings. The samples (50 ml sea water) were preserved with prefiltered (0.2 micron) glutardialdehyde solution (1.5 ml of commercial glutardialdehyde (25%)) into dark colored glass bottles. Preserved samples were poured into 10 or 25 ml settling chambers (Hydro-Bios) for cells to settle on the bottom over a day. Species identification and enumeration were done under an inverted microscope (Olympus IX71). At least 400 specimen were tried to be counted in each sample.

Abundance of phytoplankton in the Cilician Basin during the Bilim 2 cruise in September 2008

The dataset is composed of 20 samples from 14 stations. The phytoplankton samples were collected by 5l Niskin bottles attached to the CTD system. The sampling depths were selected according to the CTD profiles and the in situ fluorometer readings. The samples (50 ml sea water) were preserved with prefiltered (0.2 micron) glutardialdehyde solution (1.5 ml of commercial glutardialdehyde (25%)) into dark colored glass bottles. Preserved samples were poured into 10 or 25 ml settling chambers (Hydro-Bios) for cells to settle on the bottom over a day. Species identification and enumeration were done under an inverted microscope (Olympus IX71). At least 400 specimen were tried to be counted in each sample.

Abundance and biomass of phytoplankton in the western part of the Black Sea during the R/V Akademik cruise Ak082001 in August 2001

The dataset is composed of 41 samples from 10 stations. The phytoplankton samples were collected by 5l Niskin bottles attached to the CTD system. The sampling depths were selected according to the CTD profile and the in situ fluorometer readings: surface, temperature, salinity and fluorescence gradients and 1 m above the bottom. At some stations phytoplankton net samples (20 µm mesh-size) were collected to assist species biodiversity examination. The samples (1l sea water) were preserved in 4% buffered to pH 8-8.2 with disodiumtetraborate formaldehyde solution and stored in plastic containers. On board at each station few live samples were qualitatively examined under microscope for preliminary analysis of taxonomic composition and dominant species. The taxon-specific phytoplankton abundance samples were concentrated down to 50 cm**3 by slow decantation after storage for 20 days in a cool and dark place. The species identification was done under light microscope OLIMPUS-BS41 connected to a video-interactive image analysis system at magnification of the ocular 10X and objective - 40X. A Sedgwick-Rafter camera (1ml) was used for counting. 400 specimen were counted for each sample, while rare and large species were checked in the whole sample (Manual of phytoplankton, 2005). Species identification was mainly after Carmelo T. (1997) and Fukuyo, Y. (2000). Total phytoplankton abundance was calculated as sum of taxon-specific abundances. Total phytoplankton biomass was calculated as sum of taxon-specific biomasses. The cell biovolume was determined based on morpho-metric measurement of phytoplankton units and the corresponding geometric shapes as described in detail in (Edier, 1979).

Abundance and biomass of phytoplankton in the western part of the Black Sea during Branimir Ormanov cruise BO092000 in September 2000

The samples were concentrated down to 50 cm**3 by slow decantation after storage for 20 days in a cool and dark place. The species identification was done under light microscope OLIMPUS-BS41 connected to a video-interactive image analysis system at magnification of the ocular 10X and objective - 40X. A Sedgwick-Rafter camera (1ml) was used for counting. 400 specimen were counted for each sample, while rare and large species were checked in the whole sample (Manual of phytoplankton, 2005). Species identification was mainly after Carmelo T. (1997) and Fukuyo, Y. (2000). Taxon-specific phytoplankton abundance and biomass were analysed by Moncheva S., B. Parr, 2005. Manual for Phytoplankton Sampling and Analysis in the Black Sea. The cell biovolume was determined based on morpho-metric measurement of phytoplankton units and the corresponding geometric shapes as described in detail in (Edier, 1979).

MARECHIARA-phytoplankton long-term time-series (1984-2006) at the fixed coastal station in the Gulf of Naples, Southern Tyrrhenian Sea

The "MARECHIARA-phytoplankton" dataset contains phytoplankton data collected in the ongoing time-series at Stn MC ( 40°48.5' N, 14°15' E) in the Gulf of Naples. This dataset spans over the period 1984-2006 and contains data of phytoplankton species composition and abundance. Phytoplankton sampling was regularly conducted from January 1984 till July 1991 and in 1995-2006. Sampling was interrupted from August 1991 till January 1995. The sampling frequency was fortnightly till 1991 and weekly since 1995. Phytoplankton samples were collected at 0.5 m depth using Niskin bottles and immediately fixed with formaldehyde (0.8-1.6% final concentration) for species identification and counts.

Análisis y clasificación de maderas mediante técnicas no invasivas de baja energía

El estudio de materiales, especialmente biológicos, por medios no destructivos está adquiriendo una importancia creciente tanto en las aplicaciones científicas como industriales. Las ventajas económicas de los métodos no destructivos son múltiples. Existen numerosos procedimientos físicos capaces de extraer información detallada de las superficie de la madera con escaso o nulo tratamiento previo y mínima intrusión en el material. Entre los diversos métodos destacan las técnicas ópticas y las acústicas por su gran versatilidad, relativa sencillez y bajo coste. Esta tesis pretende establecer desde la aplicación de principios simples de física, de medición directa y superficial, a través del desarrollo de los algoritmos de decisión mas adecuados basados en la estadística, unas soluciones tecnológicas simples y en esencia, de coste mínimo, para su posible aplicación en la determinación de la especie y los defectos superficiales de la madera de cada muestra tratando, en la medida de lo posible, no alterar su geometría de trabajo. Los análisis desarrollados han sido los tres siguientes: El primer método óptico utiliza las propiedades de la luz dispersada por la superficie de la madera cuando es iluminada por un laser difuso. Esta dispersión produce un moteado luminoso (speckle) cuyas propiedades estadísticas permiten extraer propiedades muy precisas de la estructura tanto microscópica como macroscópica de la madera. El análisis de las propiedades espectrales de la luz laser dispersada genera ciertos patrones mas o menos regulares relacionados con la estructura anatómica, composición, procesado y textura superficial de la madera bajo estudio que ponen de manifiesto características del material o de la calidad de los procesos a los que ha sido sometido. El uso de este tipo de láseres implica también la posibilidad de realizar monitorizaciones de procesos industriales en tiempo real y a distancia sin interferir con otros sensores. La segunda técnica óptica que emplearemos hace uso del estudio estadístico y matemático de las propiedades de las imágenes digitales obtenidas de la superficie de la madera a través de un sistema de scanner de alta resolución. Después de aislar los detalles mas relevantes de las imágenes, diversos algoritmos de clasificacion automatica se encargan de generar bases de datos con las diversas especies de maderas a las que pertenecían las imágenes, junto con los márgenes de error de tales clasificaciones. Una parte fundamental de las herramientas de clasificacion se basa en el estudio preciso de las bandas de color de las diversas maderas. Finalmente, numerosas técnicas acústicas, tales como el análisis de pulsos por impacto acústico, permiten complementar y afinar los resultados obtenidos con los métodos ópticos descritos, identificando estructuras superficiales y profundas en la madera así como patologías o deformaciones, aspectos de especial utilidad en usos de la madera en estructuras. La utilidad de estas técnicas esta mas que demostrada en el campo industrial aun cuando su aplicación carece de la suficiente expansión debido a sus altos costes y falta de normalización de los procesos, lo cual hace que cada análisis no sea comparable con su teórico equivalente de mercado. En la actualidad gran parte de los esfuerzos de investigación tienden a dar por supuesto que la diferenciación entre especies es un mecanismo de reconocimiento propio del ser humano y concentran las tecnologías en la definición de parámetros físicos (módulos de elasticidad, conductividad eléctrica o acústica, etc.), utilizando aparatos muy costosos y en muchos casos complejos en su aplicación de campo. Abstract The study of materials, especially the biological ones, by non-destructive techniques is becoming increasingly important in both scientific and industrial applications. The economic advantages of non-destructive methods are multiple and clear due to the related costs and resources necessaries. There are many physical processes capable of extracting detailed information on the wood surface with little or no previous treatment and minimal intrusion into the material. Among the various methods stand out acoustic and optical techniques for their great versatility, relative simplicity and low cost. This thesis aims to establish from the application of simple principles of physics, surface direct measurement and through the development of the more appropriate decision algorithms based on statistics, a simple technological solutions with the minimum cost for possible application in determining the species and the wood surface defects of each sample. Looking for a reasonable accuracy without altering their work-location or properties is the main objetive. There are three different work lines: Empirical characterization of wood surfaces by means of iterative autocorrelation of laser speckle patterns: A simple and inexpensive method for the qualitative characterization of wood surfaces is presented. it is based on the iterative autocorrelation of laser speckle patterns produced by diffuse laser illumination of the wood surfaces. The method exploits the high spatial frequency content of speckle images. A similar approach with raw conventional photographs taken with ordinary light would be very difficult. A few iterations of the algorithm are necessary, typically three or four, in order to visualize the most important periodic features of the surface. The processed patterns help in the study of surface parameters, to design new scattering models and to classify the wood species. Fractal-based image enhancement techniques inspired by differential interference contrast microscopy: Differential interference contrast microscopy is a very powerful optical technique for microscopic imaging. Inspired by the physics of this type of microscope, we have developed a series of image processing algorithms aimed at the magnification, noise reduction, contrast enhancement and tissue analysis of biological samples. These algorithms use fractal convolution schemes which provide fast and accurate results with a performance comparable to the best present image enhancement algorithms. These techniques can be used as post processing tools for advanced microscopy or as a means to improve the performance of less expensive visualization instruments. Several examples of the use of these algorithms to visualize microscopic images of raw pine wood samples with a simple desktop scanner are provided. Wood species identification using stress-wave analysis in the audible range: Stress-wave analysis is a powerful and flexible technique to study mechanical properties of many materials. We present a simple technique to obtain information about the species of wood samples using stress-wave sounds in the audible range generated by collision with a small pendulum. Stress-wave analysis has been used for flaw detection and quality control for decades, but its use for material identification and classification is less cited in the literature. Accurate wood species identification is a time consuming task for highly trained human experts. For this reason, the development of cost effective techniques for automatic wood classification is a desirable goal. Our proposed approach is fully non-invasive and non-destructive, reducing significantly the cost and complexity of the identification and classification process.

Evaluation of cover crops based on characteristics of nitrogen use, and aerial and root growth

La caracterización de los cultivos cubierta (cover crops) puede permitir comparar la idoneidad de diferentes especies para proporcionar servicios ecológicos como el control de la erosión, el reciclado de nutrientes o la producción de forrajes. En este trabajo se estudiaron bajo condiciones de campo diferentes técnicas para caracterizar el dosel vegetal con objeto de establecer una metodología para medir y comparar las arquitecturas de los cultivos cubierta más comunes. Se estableció un ensayo de campo en Madrid (España central) para determinar la relación entre el índice de área foliar (LAI) y la cobertura del suelo (GC) para un cultivo de gramínea, uno de leguminosa y uno de crucífera. Para ello se sembraron doce parcelas con cebada (Hordeum vulgare L.), veza (Vicia sativa L.), y colza (Brassica napus L.). En 10 fechas de muestreo se midieron el LAI (con estimaciones directas y del LAI-2000), la fracción interceptada de la radiación fotosintéticamente activa (FIPAR) y la GC. Un experimento de campo de dos años (Octubre-Abril) se estableció en la misma localización para evaluar diferentes especies (Hordeum vulgare L., Secale cereale L., x Triticosecale Whim, Sinapis alba L., Vicia sativa L.) y cultivares (20) en relación con su idoneidad para ser usadas como cultivos cubierta. La GC se monitorizó mediante análisis de imágenes digitales con 21 y 22 muestreos, y la biomasa se midió 8 y 10 veces, respectivamente para cada año. Un modelo de Gompertz caracterizó la cobertura del suelo hasta el decaimiento observado tras las heladas, mientras que la biomasa se ajustó a ecuaciones de Gompertz, logísticas y lineales-exponenciales. Al final del experimento se determinaron el C, el N y el contenido en fibra (neutrodetergente, ácidodetergente y lignina), así como el N fijado por las leguminosas. Se aplicó el análisis de decisión multicriterio (MCDA) con objeto de obtener un ranking de especies y cultivares de acuerdo con su idoneidad para actuar como cultivos cubierta en cuatro modalidades diferentes: cultivo de cobertura, cultivo captura, abono verde y forraje. Las asociaciones de cultivos leguminosas con no leguminosas pueden afectar al crecimiento radicular y a la absorción de N de ambos componentes de la mezcla. El conocimiento de cómo los sistemas radiculares específicos afectan al crecimiento individual de las especies es útil para entender las interacciones en las asociaciones, así como para planificar estrategias de cultivos cubierta. En un tercer ensayo se combinaron estudios en rhizotrones con extracción de raíces e identificación de especies por microscopía, así como con estudios de crecimiento, absorción de N y 15N en capas profundas del suelo. Las interacciones entre raíces en su crecimiento y en el aprovisionamiento de N se estudiaron para dos de los cultivares mejor valorados en el estudio previo: uno de cebada (Hordeum vulgare L. cv. Hispanic) y otro de veza (Vicia sativa L. cv. Aitana). Se añadió N en dosis de 0 (N0), 50 (N1) y 150 (N2) kg N ha-1. Como resultados del primer estudio, se ajustaron correctamente modelos lineales y cuadráticos a la relación entre la GC y el LAI para todos los cultivos, pero en la gramínea alcanzaron una meseta para un LAI>4. Antes de alcanzar la cobertura total, la pendiente de la relación lineal entre ambas variables se situó en un rango entre 0.025 y 0.030. Las lecturas del LAI-2000 estuvieron correlacionadas linealmente con el LAI, aunque con tendencia a la sobreestimación. Las correcciones basadas en el efecto de aglutinación redujeron el error cuadrático medio del LAI estimado por el LAI-2000 desde 1.2 hasta 0.5 para la crucífera y la leguminosa, no siendo efectivas para la cebada. Esto determinó que para los siguientes estudios se midieran únicamente la GC y la biomasa. En el segundo experimento, las gramíneas alcanzaron la mayor cobertura del suelo (83-99%) y la mayor biomasa (1226-1928 g m-2) al final del mismo. Con la mayor relación C/N (27-39) y contenido en fibra digestible (53-60%) y la menor calidad de residuo (~68%). La mostaza presentó elevadas GC, biomasa y absorción de N en el año más templado en similitud con las gramíneas, aunque escasa calidad como forraje en ambos años. La veza presentó la menor absorción de N (2.4-0.7 g N m-2) debido a la fijación de N (9.8-1.6 g N m-2) y escasa acumulación de N. El tiempo térmico hasta alcanzar el 30% de GC constituyó un buen indicador de especies de rápida cubrición. La cuantificación de las variables permitió hallar variabilidad entre las especies y proporcionó información para posteriores decisiones sobre la selección y manejo de los cultivos cubierta. La agregación de dichas variables a través de funciones de utilidad permitió confeccionar rankings de especies y cultivares para cada uso. Las gramíneas fueron las más indicadas para los usos de cultivo de cobertura, cultivo captura y forraje, mientras que las vezas fueron las mejor como abono verde. La mostaza alcanzó altos valores como cultivo de cobertura y captura en el primer año, pero el segundo decayó debido a su pobre actuación en los inviernos fríos. Hispanic fue el mejor cultivar de cebada como cultivo de cobertura y captura, mientras que Albacete como forraje. El triticale Titania alcanzó la posición más alta como cultiva de cobertura, captura y forraje. Las vezas Aitana y BGE014897 mostraron buenas aptitudes como abono verde y cultivo captura. El MCDA permitió la comparación entre especies y cultivares proporcionando información relevante para la selección y manejo de cultivos cubierta. En el estudio en rhizotrones tanto la mezcla de especies como la cebada alcanzaron mayor intensidad de raíces (RI) y profundidad (RD) que la veza, con valores alrededor de 150 cruces m-1 y 1.4 m respectivamente, comparados con 50 cruces m-1 y 0.9 m para la veza. En las capas más profundas del suelo, la asociación de cultivos mostró valores de RI ligeramente mayores que la cebada en monocultivo. La cebada y la asociación obtuvieron mayores valores de densidad de raíces (RLD) (200-600 m m-3) que la veza (25-130) entre 0.8 y 1.2 m de profundidad. Los niveles de N no mostraron efectos claros en RI, RD ó RLD, sin embargo, el incremento de N favoreció la proliferación de raíces de veza en la asociación en capas profundas del suelo, con un ratio cebada/veza situado entre 25 a N0 y 5 a N2. La absorción de N de la cebada se incrementó en la asociación a expensas de la veza (de ~100 a 200 mg planta-1). Las raíces de cebada en la asociación absorbieron también más nitrógeno marcado de las capas profundas del suelo (0.6 mg 15N planta-1) que en el monocultivo (0.3 mg 15N planta-1). ABSTRACT Cover crop characterization may allow comparing the suitability of different species to provide ecological services such as erosion control, nutrient recycling or fodder production. Different techniques to characterize plant canopy were studied under field conditions in order to establish a methodology for measuring and comparing cover crops canopies. A field trial was established in Madrid (central Spain) to determine the relationship between leaf area index (LAI) and ground cover (GC) in a grass, a legume and a crucifer crop. Twelve plots were sown with either barley (Hordeum vulgare L.), vetch (Vicia sativa L.), or rape (Brassica napus L.). On 10 sampling dates the LAI (both direct and LAI-2000 estimations), fraction intercepted of photosynthetically active radiation (FIPAR) and GC were measured. A two-year field experiment (October-April) was established in the same location to evaluate different species (Hordeum vulgare L., Secale cereale L., x Triticosecale Whim, Sinapis alba L., Vicia sativa L.) and cultivars (20) according to their suitability to be used as cover crops. GC was monitored through digital image analysis with 21 and 22 samples, and biomass measured 8 and 10 times, respectively for each season. A Gompertz model characterized ground cover until the decay observed after frosts, while biomass was fitted to Gompertz, logistic and linear-exponential equations. At the end of the experiment C, N, and fiber (neutral detergent, acid and lignin) contents, and the N fixed by the legumes were determined. Multicriteria decision analysis (MCDA) was applied in order to rank the species and cultivars according to their suitability to perform as cover crops in four different modalities: cover crop, catch crop, green manure and fodder. Intercropping legumes and non-legumes may affect the root growth and N uptake of both components in the mixture. The knowledge of how specific root systems affect the growth of the individual species is useful for understanding the interactions in intercrops as well as for planning cover cropping strategies. In a third trial rhizotron studies were combined with root extraction and species identification by microscopy and with studies of growth, N uptake and 15N uptake from deeper soil layers. The root interactions of root growth and N foraging were studied for two of the best ranked cultivars in the previous study: a barley (Hordeum vulgare L. cv. Hispanic) and a vetch (Vicia sativa L. cv. Aitana). N was added at 0 (N0), 50 (N1) and 150 (N2) kg N ha-1. As a result, linear and quadratic models fitted to the relationship between the GC and LAI for all of the crops, but they reached a plateau in the grass when the LAI > 4. Before reaching full cover, the slope of the linear relationship between both variables was within the range of 0.025 to 0.030. The LAI-2000 readings were linearly correlated with the LAI but they tended to overestimation. Corrections based on the clumping effect reduced the root mean square error of the estimated LAI from the LAI-2000 readings from 1.2 to less than 0.50 for the crucifer and the legume, but were not effective for barley. This determined that in the following studies only the GC and biomass were measured. In the second experiment, the grasses reached the highest ground cover (83- 99%) and biomass (1226-1928 g/m2) at the end of the experiment. The grasses had the highest C/N ratio (27-39) and dietary fiber (53-60%) and the lowest residue quality (~68%). The mustard presented high GC, biomass and N uptake in the warmer year with similarity to grasses, but low fodder capability in both years. The vetch presented the lowest N uptake (2.4-0.7 g N/m2) due to N fixation (9.8-1.6 g N/m2) and low biomass accumulation. The thermal time until reaching 30% ground cover was a good indicator of early coverage species. Variable quantification allowed finding variability among the species and provided information for further decisions involving cover crops selection and management. Aggregation of these variables through utility functions allowed ranking species and cultivars for each usage. Grasses were the most suitable for the cover crop, catch crop and fodder uses, while the vetches were the best as green manures. The mustard attained high ranks as cover and catch crop the first season, but the second decayed due to low performance in cold winters. Hispanic was the most suitable barley cultivar as cover and catch crop, and Albacete as fodder. The triticale Titania attained the highest rank as cover and catch crop and fodder. Vetches Aitana and BGE014897 showed good aptitudes as green manures and catch crops. MCDA allowed comparison among species and cultivars and might provide relevant information for cover crops selection and management. In the rhizotron study the intercrop and the barley attained slightly higher root intensity (RI) and root depth (RD) than the vetch, with values around 150 crosses m-1 and 1.4 m respectively, compared to 50 crosses m-1 and 0.9 m for the vetch. At deep soil layers, intercropping showed slightly larger RI values compared to the sole cropped barley. The barley and the intercropping had larger root length density (RLD) values (200-600 m m-3) than the vetch (25-130) at 0.8-1.2 m depth. The topsoil N supply did not show a clear effect on the RI, RD or RLD; however increasing topsoil N favored the proliferation of vetch roots in the intercropping at deep soil layers, with the barley/vetch root ratio ranging from 25 at N0 to 5 at N2. The N uptake of the barley was enhanced in the intercropping at the expense of the vetch (from ~100 mg plant-1 to 200). The intercropped barley roots took up more labeled nitrogen (0.6 mg 15N plant-1) than the sole-cropped barley roots (0.3 mg 15N plant-1) from deep layers.

Evidence for clonal propagation in natural isolates of Plasmodium falciparum from Venezuela

We have analyzed 75 isolates of Plasmodium falciparum, collected in Venezuela during both the dry (November) and rainy (May–July) seasons, with a range of genetic markers including antigen genes and 14 random amplified polymorphic DNA (RAPD) primers. Thirteen P. falciparum stocks from Kenya and four other Plasmodium species are included in the analysis for comparison. Cross-hybridization shows that the 14 RAPD primers reveal 14 separate regions of the parasite's genome. The P. falciparum isolates are a monophyletic clade, significantly different from the other Plasmodium species. We identify three RAPD characters that could be useful as “tags” for rapid species identification. The Venezuelan genotypes fall into two discrete genetic subdivisions associated with either the dry or the rainy season; the isolates collected in the rainy season exhibit greater genetic diversity. There is significant linkage disequilibrium in each seasonal subsample and in the full sample. In contrast, no linkage disequilibrium is detected in the African sample. These results support the hypothesis that the population structure of P. falciparum in Venezuela, but not in Africa, is predominantly clonal. However, the impact of genetic recombination on Venezuelan P. falciparum seems higher than in parasitic species with long-term clonal evolution like Trypanosoma cruzi, the agent of Chagas' disease. The genetic structure of the Venezuelan samples is similar to that of Escherichia coli, a bacterium that propagates clonally, with occasional genetic recombination.