PanGet - downloads multiple data sets from PANGAEA

The software PanGet is a special tool for the download of multiple data sets from PANGAEA. It uses the PANGAEA data set ID which is unique and part of the DOI. In a first step a list of ID's of those data sets to be downloaded must be created. There are two choices to define this individual collection of sets. Based on the ID list, the tool will download the data sets. Failed downloads are written to the file *_failed.txt. The functionality of PanGet is also part of the program Pan2Applic (choose File > Download PANGAEA datasets...) and PanTool2 (choose Basic tools > Download PANGAEA datasets...).

Benthic and substrate cover data derived from a time series of photo-transect surveys for the Eastern Banks, Moreton Bay Australia, 2004-2015

This paper describes seagrass species and percentage cover point-based field data sets derived from georeferenced photo transects. Annually or biannually over a ten year period (2004-2015) data sets were collected using 30-50 transects, 500-800 m in length distributed across a 142 km**2 shallow, clear water seagrass habitat, the Eastern Banks, Moreton Bay, Australia. Each of the eight data sets include seagrass property information derived from approximately 3000 georeferenced, downward looking photographs captured at 2-4 m intervals along the transects. Photographs were manually interpreted to estimate seagrass species composition and percentage cover (Coral Point Count excel; CPCe). Understanding seagrass biology, ecology and dynamics for scientific and management purposes requires point-based data on species composition and cover. This data set, and the methods used to derive it are a globally unique example for seagrass ecological applications. It provides the basis for multiple further studies at this site, regional to global comparative studies, and, for the design of similar monitoring programs elsewhere.

Discarge compilation from The Global River Discharge (RivDIS) Project

The Global River Discharge (RivDIS) data set contains monthly discharge measurements for 1018 stations located throughout the world. The period of record varies widely from station to station, with a mean of 21.5 years. These data were digitized from published UNESCO archives by Charles Voromarty, Balaze Fekete, and B.A. Tucker of the Complex Systems Research Center (CSRC) at the University of New Hampshire. River discharge is typically measured through the use of a rating curve that relates local water level height to discharge. This rating curve is used to estimate discharge from the observed water level. The rating curves are periodically rechecked and recalibrated through on-site measurement of discharge and river stage.

Determinants of government consumption expenditure in developing countries : a panel data analysis

The paper focuses on the recent pattern of government consumption expenditure in developing countries and estimates the determinants which have influenced government expenditure. Using a panel data set for 111 developing countries from 1984 to 2004, this study finds evidence that political and institutional variables as well as governance variables significantly influence government expenditure. Among other results, the paper finds new evidence of Wagner's law which states that peoples' demand for service and willingness to pay is income-elastic hence the expansion of public economy is influenced by the greater economic affluence of a nation (Cameron1978). Corruption is found to be influential in explaining the public expenditure of developing countries. On the contrary, size of the economy and fractionalization are found to have significant negative association with government expenditure. In addition, the study finds evidence that public expenditure significantly shrinks under military dictatorship compared with other form of governance.

Feature selection in the reconstruction of complex network representations of spectral data

Complex networks have been extensively used in the last decade to characterize and analyze complex systems, and they have been recently proposed as a novel instrument for the analysis of spectra extracted from biological samples. Yet, the high number of measurements composing spectra, and the consequent high computational cost, make a direct network analysis unfeasible. We here present a comparative analysis of three customary feature selection algorithms, including the binning of spectral data and the use of information theory metrics. Such algorithms are compared by assessing the score obtained in a classification task, where healthy subjects and people suffering from different types of cancers should be discriminated. Results indicate that a feature selection strategy based on Mutual Information outperforms the more classical data binning, while allowing a reduction of the dimensionality of the data set in two orders of magnitude

Nematodes as indicators of the effect of soil fumigants on soil functioning

Debido al futuro incierto de la mayor parte de los fumigantes edáficos usados actualmente en la Unión Europea, que pueden implicar riesgos para la salud humana/animal y el medio ambiente, es necesario desarrollar programas de manejo integrado para el control de plagas de cultivos. Estos programas se incluyen como obligatorios en el Reglamento (EC) No. 1107/2009. De acuerdo con este Reglamento, es obligatoria la evaluación del riesgo asociado al uso de productos fitosanitarios sobre los organismos edáficos no diana y sus funciones, además de llevar a cabo ensayos con diferentes especies indicadoras para obtener datos de toxicidad que puedan ser usados posteriormente en la evaluación de riesgo. Sin embargo, la baja representatividad de algunas de estas especies indicadoras en el área Mediterránea supone una gran limitación. En esta situación, el Panel Científico de Productos Fitosanitarios y sus Residuos de la Autoridad Europea en Seguridad Alimentaria (EFSA), ha señalado la necesidad de modificar los datos ecotoxicológicos requeridos para evaluar los efectos adversos de los productos fitosanitarios de una manera más integrada, incluyendo criterios funcionales y estructurales mediante organismos como bacterias, hongos, protozoos y nematodos. De este modo, la EFSA ha recomendado el uso de los nematodos en la evaluación de la funcionalidad y estructura del suelo. Los nematodos están globalmente distribuidos y son morfológicamente diversos; esto junto con su gran abundancia y diversidad de respuestas a las perturbaciones edáficas, los convierte en indicadores adecuados del estado del suelo. Puesto que los nematodos interaccionan con muchos otros organismos que participan en diferentes eslabones de la red trófica edáfica, jugando papeles importantes en procesos edáficos esenciales en los agroescosistemas, la diversidad de nematodos es, a menudo, usada como indicador biológico de los efectos de las prácticas agrícolas en el estado del suelo. En los últimos años, diferentes índices basados en la comunidad nematológica han facilitado la interpretación de datos complejos sobre la ecología del suelo. Los índices de la red trófica edáfica, basados en la abundancia de grupos funcionales definidos como grupos C-P y grupos tróficos, permiten la evaluación de la funcionalidad de la red trófica edáfica. Por otra parte, la dificultad en la identificación taxonómica de nematodos para explicar su uso limitado como indicadores ecológicos, es ampliamente discutida, y existe cierta controversia en cuanto a la eficacia de los diferentes métodos de identificación de nematodos. Se argumenta que la identificación morfológica es difícil y puede llevar mucho tiempo debido a la falta de expertos especializados, y se afirma que las técnicas moleculares pueden resolver algunas limitaciones de las técnicas morfológicas como la identificación de juveniles. Sin embargo, los métodos de identificación molecular tienen también limitaciones; la mayoría de las bases de datos de secuencias de ADN están fuertemente orientadas hacia los nematodos fitoparásitos, los cuales representan sólo una parte de la comunidad edáfica de nematodos, mientras que hay poca información disponible de nematodos de vida libre a pesar de representar la mayoría de los nematodos edáficos. Este trabajo se centra en el estudio de los efectos de fumigantes edáficos en la funcionalidad del suelo a través del uso de diferentes indicadores basados en la comunidad de nematodos, como los índices de la red trófica, índices de diversidad, abundancia de los taxones más relevantes etc. También se han analizado otros indicadores funcionales relacionados con la supresividad edáfica, el ciclo de nutrientes o la actividad de la microfauna del suelo. En el capítulo 1, la diversidad de nematodos estudiada en una explotación comercial de fresa y sus alrededores durante dos campañas consecutivas en el suroeste español, fue baja en los suelos fumigados con fumigantes químicos ambas campañas y, aunque se observó una recuperación a lo largo de la campaña en la zona tratada, los suelos fumigados mostraron una condición perturbada permanente. La comunidad de nematodos estuvo más asociada al ciclo de nutrientes en la zona sin cultivar que en los suelos cultivados, y se observó poca relación entre la biomasa de las plantas y la estructura de la comunidad de nematodos. Los surcos sin tratar dentro de la zona de cultivo funcionaron como reservorio tanto de nematodos fitoparásitos como beneficiosos; sin embargo estas diferencias entre los surcos y los lomos de cultivo no fueron suficientes para mantener la supresividad edáfica en los surcos. Los suelos tratados fueron menos supresivos que los suelos sin tratar, y se observaron correlaciones positivas entre la supresividad edáfica y la estructura de la red trófica edáfica y la diversidad de nematodos. En el capítulo 2, se evaluaron los efectos de dos pesticidas orgánicos con efecto nematicida y dos nematicidas convencionales sobre las propiedades físico químicas del suelo, la diversidad de nematodos y la biomasa de las plantas en condiciones experimentales en dos tipos de suelo: suelos agrícolas poco diversos y suelos provenientes de una zona de vegetación natural muy diversos. El mayor efecto se observó en el tratamiento con neem, el cual indujo un gran incremento en el número de dauerlarvas en los suelos pobres en nutrientes, mientras que el mismo tratamiento indujo un incremento de poblaciones de nematodos bacterívoros, más estables y menos oportunistas, en los suelos del pinar ricos en materia orgánica. En el capítulo 3, se comparó la eficacia de métodos moleculares (TRFLP, Terminal Restriction Fragment Length Polymorphism) y morfológicos (microscopía de alta resolución) para la identificación de diferentes comunidades denematodos de España e Irlanda. Se compararon estadísticamente las diferencias y similitudes en la diversidad de nematodos, otros indicadores ecológicos y de la red trófica edáfica. Las identificaciones mediante el uso de TRFLP sólo detectó un porcentaje de los taxones presentes en las muestras de suelo identificadas morfológicamente, y los nematodos omnívoros y predadores no fueron detectados molecularmente en nuestro estudio. Los índices calculados en base a los nematodos micróboros mostraron más similitud cuando se identificaron morfológica y molecularmente que los índices basados en grupos tróficos más altos. Nuestros resultados muestran que, al menos con la técnica usada en este estudio, la identificación morfológica de nematodos es una herramienta fiable y más precisa que la identificación molecular, puesto que en general se obtiene una mayor resolución en la identificación de nematodos. En el capítulo 4, se estudiaron también los efectos de los nematicidas químicos sobre la comunidad de nematodos y la biomasa de las plantas en condiciones experimentales de campo, donde se aplicaron en una rotación de cultivo judía-col durante un ciclo de cultivo. Se aplicaron dos tipos de enmiendas orgánicas con el objetivo de mitigar el efecto negativo de los productos fitosanitarios sobre la diversidad edáfica. El efecto de los nematicidas sobre las propiedades del suelo y sobre la comunidad de nematodos fue más agudo que el efecto de las enmiendas. La incorporación de los restos de cosecha al final del ciclo de cultivo de la judía tuvo un gran efecto sobre la comunidad de nematodos, y aunque el número total de nematodos incrementó al final del experimento, se observó una condición perturbada permanente de la red trófica edáfica a lo largo del experimento. ABSTRACT Due to the uncertain future of the soil fumigants most commonly used in the EU, that might involve risks for human/animal health and the environment, there is a need to develop new integrated pest management programs, included as mandatory in the Regulation (EC) No. 1107/2009, to control crop diseases. According to this Regulation, evaluating the risk associated to the use of the plant production products (PPP) on non-target soil fauna and their function, and developing assays with different indicator species to obtain toxicity data to be used in the risk evaluation is mandatory. However, the low representativeness of some of these indicator species in the Mediterranean area is a relevant limitation. In this situation, the Scientific Panel of Plant Protection Products and their Residues of the European Food Safety Authority (EFSA) has pointed out the necessity of modifying the ecotoxicological data set required to evaluate non-target effects of PPP in a more integrated way, including structural and functional endpoints with organism such as bacteria, fungi, protists and nematodes. Thus, EFSA has recommended the use of nematodes in the assessment of the functional and structural features of the soil. Nematodes are globally distributed and morphologically diverse, and due to their high abundance and diversity of responses to soil disturbance, they are suitable indicators of the soil condition. Since nematodes interact with many other organisms as participants in several links of the soil food web, playing important roles in essential soil processes in agroecosystems, nematode diversity is often used as a biological indicator of the effects of agricultural practices on soil condition. In the last years, various indices based on soil nematode assemblages, have facilitated the interpretation of complex soil ecological data. Soil food web indices based on the abundances of functional guilds defined by C-P groups and trophic groups, permit evaluating soil food web functioning. On the other hand, the difficulty of nematode taxonomical identification is commonly argued to explain their limited used as ecological indicators, and there is a certain controversy in terms of the efficacy of various nematode identification methods. It is argued that the morphological identification is difficult and time consuming due to the lack of specialist knowledge, and it is claimed that molecular techniques can solve some limitations of morphological techniques such as the identification of juveniles. Nevertheless, molecular identification methods are limited too, since most of the DNA-based databases are strongly oriented towards plant-parasitic nematodes that represent only a fraction of the soil nematode community, while there is little information available on free-living nematodes, which represent most soil nematodes. This work focuses on the study of the effects of soil fumigants on soil functioning through the use of different indicators based on soil nematode community as soil food web indices, diversity indices, the abundance of more relevant taxa etc. Other functional indicators related to soil suppressiveness, nutrient cycling, or the activity of soil microfauna have been also studied. In chapter 1, nematode diversity assessed in a commercial strawberry farm and its surroundings for two consecutive growing seasons in southern Spain, was low in fumigated soils with chemical pesticides throughout both seasons and, although yearly recovery occurred within the treated fields, fumigated soils showed a permanent perturbed condition. The nematode community was more closely associated to nutrient cycling in the non-cropped than in the cropped soils, and the link between plant biomass and nematode community structure was weak. Non-treated furrows within the treated fields were a reservoir of both beneficial and plant-parasitic nematodes, but such difference between furrows and beds was not enough to maintain more suppressive soil assemblages in the furrows. Treated soils were less suppressive than unmanaged soils, and there was a positive and significant correlation between soil suppressiveness and soil food web structure and diversity. In chapter 2, the effects of two organic pesticides with nematicide effect and two chemical nematicides on soil physicalchemical properties, soil nematode diversity and plant biomass in experimental conditions were assessed in two types of soils: low diversity soils from an agricultural farm, and high diversity soils from a natural vegetation area. The larger effect was observed on the neem treatment, which induced a large boost of dauer juveniles in the nutrient-depleted soil, while the same treatment induced the increase of more stable, less opportunistic, populations of generalist bacterivore nematodes in the pine forest soil, rich in organic matter. In chapter 3, comparison of the efficiency of molecular (TRFLP, Terminal Restriction Fragment Length Polymorphism) and morphological (microscopy at high magnification) identification methods was carried out in different nematode communities from five sites of different land uses in Spain and Ireland. Differences and similarities on nematode diversity and other ecological and soil food web indices assessed by both methods, were statistically compared. Molecular identification with TRFLP only detected a percentage of the taxa present in the soil samples identified morphologically, and omnivores and predators were not detected molecularly in our study. Indices involving microbial feeding nematodes were more similar between identification methods than indices involving higher trophic links. Our results show that, at least with the technique used in this study, identifying nematodes morphologically is a reliable and more precise identification tool than molecular identification, since a higher taxonomic resolution is in general obtained compared to TRFLP. In chapter 4, the effect of chemical nematicides on nematode community descriptors and plant biomass was also studied in field conditions in an experimental area in which dazomet and dimethyl disulfide was applied in a bean-cabbage rotation system for a single season. Organic amendments were incorporated into the soil with the aim of mitigate the negative effect of the pesticides on soil diversity. The effect of the nematicides was much more noticeable than the effect of the amendments on soil properties and nematode community descriptors. The incorporation of bean crop residues into the soil at the end of bean crop cycle affected soil nematode community descriptors to a great extent, and although total number of nematodes increased at the end of the experiment, a permanent perturbed soil food web condition was observed along the experiment.

Nuevos Esquemas de Visualizaciones para Mejorar la Comprensibilidad de Modelos de Data Mining

La gran cantidad de datos que se registran diariamente en los sistemas de base de datos de las organizaciones ha generado la necesidad de analizarla. Sin embargo, se enfrentan a la complejidad de procesar enormes volúmenes de datos a través de métodos tradicionales de análisis. Además, dentro de un contexto globalizado y competitivo las organizaciones se mantienen en la búsqueda constante de mejorar sus procesos, para lo cual requieren herramientas que les permitan tomar mejores decisiones. Esto implica estar mejor informado y conocer su historia digital para describir sus procesos y poder anticipar (predecir) eventos no previstos. Estos nuevos requerimientos de análisis de datos ha motivado el desarrollo creciente de proyectos de minería de datos. El proceso de minería de datos busca obtener desde un conjunto masivo de datos, modelos que permitan describir los datos o predecir nuevas instancias en el conjunto. Implica etapas de: preparación de los datos, procesamiento parcial o totalmente automatizado para identificar modelos en los datos, para luego obtener como salida patrones, relaciones o reglas. Esta salida debe significar un nuevo conocimiento para la organización, útil y comprensible para los usuarios finales, y que pueda ser integrado a los procesos para apoyar la toma de decisiones. Sin embargo, la mayor dificultad es justamente lograr que el analista de datos, que interviene en todo este proceso, pueda identificar modelos lo cual es una tarea compleja y muchas veces requiere de la experiencia, no sólo del analista de datos, sino que también del experto en el dominio del problema. Una forma de apoyar el análisis de datos, modelos y patrones es a través de su representación visual, utilizando las capacidades de percepción visual del ser humano, la cual puede detectar patrones con mayor facilidad. Bajo este enfoque, la visualización ha sido utilizada en minería datos, mayormente en el análisis descriptivo de los datos (entrada) y en la presentación de los patrones (salida), dejando limitado este paradigma para el análisis de modelos. El presente documento describe el desarrollo de la Tesis Doctoral denominada “Nuevos Esquemas de Visualizaciones para Mejorar la Comprensibilidad de Modelos de Data Mining”. Esta investigación busca aportar con un enfoque de visualización para apoyar la comprensión de modelos minería de datos, para esto propone la metáfora de modelos visualmente aumentados. ABSTRACT The large amount of data to be recorded daily in the systems database of organizations has generated the need to analyze it. However, faced with the complexity of processing huge volumes of data over traditional methods of analysis. Moreover, in a globalized and competitive environment organizations are kept constantly looking to improve their processes, which require tools that allow them to make better decisions. This involves being bettered informed and knows your digital story to describe its processes and to anticipate (predict) unanticipated events. These new requirements of data analysis, has led to the increasing development of data-mining projects. The data-mining process seeks to obtain from a massive data set, models to describe the data or predict new instances in the set. It involves steps of data preparation, partially or fully automated processing to identify patterns in the data, and then get output patterns, relationships or rules. This output must mean new knowledge for the organization, useful and understandable for end users, and can be integrated into the process to support decision-making. However, the biggest challenge is just getting the data analyst involved in this process, which can identify models is complex and often requires experience not only of the data analyst, but also the expert in the problem domain. One way to support the analysis of the data, models and patterns, is through its visual representation, i.e., using the capabilities of human visual perception, which can detect patterns easily in any context. Under this approach, the visualization has been used in data mining, mostly in exploratory data analysis (input) and the presentation of the patterns (output), leaving limited this paradigm for analyzing models. This document describes the development of the doctoral thesis entitled "New Visualizations Schemes to Improve Understandability of Data-Mining Models". This research aims to provide a visualization approach to support understanding of data mining models for this proposed metaphor visually enhanced models.

Integrated fossil and molecular data reconstruct bat echolocation

Molecular and morphological data have important roles in illuminating evolutionary history. DNA data often yield well resolved phylogenies for living taxa, but are generally unattainable for fossils. A distinct advantage of morphology is that some types of morphological data may be collected for extinct and extant taxa. Fossils provide a unique window on evolutionary history and may preserve combinations of primitive and derived characters that are not found in extant taxa. Given their unique character complexes, fossils are critical in documenting sequences of character transformation over geologic time and may elucidate otherwise ambiguous patterns of evolution that are not revealed by molecular data alone. Here, we employ a methodological approach that allows for the integration of molecular and paleontological data in deciphering one of the most innovative features in the evolutionary history of mammals—laryngeal echolocation in bats. Molecular data alone, including an expanded data set that includes new sequences for the A2AB gene, suggest that microbats are paraphyletic but do not resolve whether laryngeal echolocation evolved independently in different microbat lineages or evolved in the common ancestor of bats and was subsequently lost in megabats. When scaffolds from molecular phylogenies are incorporated into parsimony analyses of morphological characters, including morphological characters for the Eocene taxa Icaronycteris, Archaeonycteris, Hassianycteris, and Palaeochiropteryx, the resulting trees suggest that laryngeal echolocation evolved in the common ancestor of fossil and extant bats and was subsequently lost in megabats. Molecular dating suggests that crown-group bats last shared a common ancestor 52 to 54 million years ago.

Recursive partitioning for tumor classification with gene expression microarray data

Precise classification of tumors is critically important for cancer diagnosis and treatment. It is also a scientifically challenging task. Recently, efforts have been made to use gene expression profiles to improve the precision of classification, with limited success. Using a published data set for purposes of comparison, we introduce a methodology based on classification trees and demonstrate that it is significantly more accurate for discriminating among distinct colon cancer tissues than other statistical approaches used heretofore. In addition, competing classification trees are displayed, which suggest that different genes may coregulate colon cancers.

Improving some thermodynamic consistency tests for VLE data evaluation

Thermodynamics Conference 2013 (Statistical Mechanics and Thermodynamics Group of the Royal Society of Chemistry), The University of Manchester, 3-6 September 2013.

Boston, Massachusetts Region LIDAR First Return Elevation Data, 2002

LIDAR (LIght Detection And Ranging) first return elevation data of the Boston, Massachusetts region from MassGIS at 1-meter resolution. This LIDAR data was captured in Spring 2002. LIDAR first return data (which shows the highest ground features, e.g. tree canopy, buildings etc.) can be used to produce a digital terrain model of the Earth's surface. This dataset consists of 74 First Return DEM tiles. The tiles are 4km by 4km areas corresponding with the MassGIS orthoimage index. This data set was collected using 3Di's Digital Airborne Topographic Imaging System II (DATIS II). The area of coverage corresponds to the following MassGIS orthophoto quads covering the Boston region (MassGIS orthophoto quad ID: 229890, 229894, 229898, 229902, 233886, 233890, 233894, 233898, 233902, 233906, 233910, 237890, 237894, 237898, 237902, 237906, 237910, 241890, 241894, 241898, 241902, 245898, 245902). The geographic extent of this dataset is the same as that of the MassGIS dataset: Boston, Massachusetts Region 1:5,000 Color Ortho Imagery (1/2-meter Resolution), 2001 and was used to produce the MassGIS dataset: Boston, Massachusetts, 2-Dimensional Building Footprints with Roof Height Data (from LIDAR data), 2002 [see cross references].

Boston, Massachusetts, 2-Dimensional Building Footprints with Height Data (from LIDAR data), 2002

This dataset consists of 2D footprints of the buildings in the metropolitan Boston area, based on tiles in the orthoimage index (orthophoto quad ID: 229890, 229894, 229898, 229902, 233886, 233890, 233894, 233898, 233902, 237890, 237894, 237898, 237902, 241890, 241894, 241898, 241902, 245898, 245902). This data set was collected using 3Di's Digital Airborne Topographic Imaging System II (DATIS II). Roof height and footprint elevation attributes (derived from 1-meter resolution LIDAR (LIght Detection And Ranging) data) are included as part of each building feature. This data can be combined with other datasets to create 3D representations of buildings and the surrounding environment.

Global compilation of chlorophyll fluorescence profiles from several data bases, and from published and unpublished individual sources

The present data set includes 268,127 vertical in situ fluorescence profiles obtained from several available online databases and from published and unpublished individual sources. Metadata about each profiles are given in the file provided here in further details. The majority of profiles comes from the National Oceanographic Data Center (NODC) and the fluorescence profiles acquired by Bio-Argo floats available on the Oceanographic Autonomous Observations (OAO) platform (63.7% and 12.5% respectively). Different modes of acquisition were used to collect the data presented in this study: (1) CTD profiles are acquired using a fluorometer mounted on a CTD-rosette; (2) OSD (Ocean Station Data) profiles are derived from water samples and are defined as low resolution profiles; (3) the UOR (Undulating Oceanographic Recorder) profiles are acquired by a equipped with a fluorometer and towed by a research vessel; (4) PA profiles are acquired by autonomous platforms (here profiling floats or elephant seals equipped with a fluorometer). Data acquired from gliders are not included in the compilation.