Whale sightings, group sizes and krill biomass in West Greenland in 2005

This study combined data on fin whale Balaenoptera physalus, humpback whale Megaptera novaeangliae, minke whale B. acutorostrata, and sei whale B. borealis sightings from large-scale visual aerial and ship-based surveys (248 and 157 sightings, respectively) with synoptic acoustic sampling of krill Meganyctiphanes norvegica and Thysanoessa sp. abundance in September 2005 in West Greenland to examine the relationships between whales and their prey. Krill densities were obtained by converting relationships of volume backscattering strengths at multiple frequencies to a numerical density using an estimate of krill target strength. Krill data were vertically integrated in 25 m depth bins between 0 and 300 m to obtain water column biomass (g/m**2) and translated to density surfaces using ordinary kriging. Standard regression models (Generalized Additive Modeling, GAM, and Generalized Linear Modeling, GLM) were developed to identify important explanatory variables relating the presence, absence, and density of large whales to the physical and biological environment and different survey platforms. Large baleen whales were concentrated in 3 focal areas: (1) the northern edge of Lille Hellefiske bank between 65 and 67°N, (2) north of Paamiut at 63°N, and (3) in South Greenland between 60 and 61° N. There was a bimodal pattern of mean krill density between depths, with one peak between 50 and 75 m (mean 0.75 g/m**2, SD 2.74) and another between 225 and 275 m (mean 1.2 to 1.3 g/m**2, SD 23 to 19). Water column krill biomass was 3 times higher in South Greenland than at any other site along the coast. Total depth-integrated krill biomass was 1.3 x 10**9 (CV 0.11). Models indicated the most important parameter in predicting large baleen whale presence was integrated krill abundance, although this relationship was only significant for sightings obtained on the ship survey. This suggests that a high degree of spatio-temporal synchrony in observations is necessary for quantifying predator-prey relationships. Krill biomass was most predictive of whale presence at depths >150 m, suggesting a threshold depth below which it is energetically optimal for baleen whales to forage on krill in West Greenland.

Seed Dispersal Spectrum of Woody Species in South Ecuadorian Dry Forests: Environmental Correlates and the Effect of Considering Species Abundance

This study examines the seed dispersal spectrum of the tropical dry forests of Southern Ecuador, in an effort to contribute to the knowledge of the complex dynamics of tropical dry forests. Seed dispersal spectrum was described for a total number of 160 species. Relationships of dispersal syndromes with plant growth form and climatic seasonality were explored. For a subset of 97 species, we determined whether dispersal spectrum changes when species abundance, in addition to species number, is taken into account. The same subset was used to relate dispersal syndromes with the environmental conditions. Zoochorous species dominated in the studied community. When considering the individual abundance of each species, however, anemochory was the prevalent dispersal syndrome. We found a significant difference in the frequency of dispersal syndromes among plant growth forms, with epizoochory only occurring in shrub species. The dispersal spectrum was dependent on climatic seasonality. The largest proportion of anemochorous species fructified during the dry season, while zoochorous diaspores dominated during the rainy season. A fourth-corner analysis indicated that the seed dispersal spectrum of Southern Ecuador dry forests is controlled by environmental conditions such as annual precipitation, annual temperature range or topography. Our results suggest that spatio-temporal changes in the environmental conditions may affect important ecological processes for dispersal. Thus, the predominance of one syndrome or another may depend on the spatial variation of environmental conditions.

Integration of temporal and semantic components into the Geographic Information. Part II: Methodology

The overall objective of this research project is to enrich geographic data with temporal and semantic components in order to significantly improve spatio-temporal analysis of geographic phenomena. To achieve this goal, we intend to establish and incorporate three new layers (structures) into the core of the Geographic Information by using mark-up languages as well as defining a set of methods and tools for enriching the system to make it able to retrieve and exploit such layers (semantic-temporal, geosemantic, and incremental spatio-temporal). Besides these layers, we also propose a set of models (temporal and spatial) and two semantic engines that make the most of the enriched geographic data. The roots of the project and its definition have been previously presented in Siabato & Manso-Callejo 2011. In this new position paper, we extend such work by delineating clearly the methodology and the foundations on which we will base to define the main components of this research: the spatial model, the temporal model, the semantic layers, and the semantic engines. By putting together the former paper and this new work we try to present a comprehensive description of the whole process, from pinpointing the basic problem to describing and assessing the solution. In this new article we just mention the methods and the background to describe how we intend to define the components and integrate them into the GI.

New generation of human machine interfaces for controlling UAV through depth based gesture recognition

New forms of natural interactions between human operators and UAVs (Unmanned Aerial Vehicle) are demanded by the military industry to achieve a better balance of the UAV control and the burden of the human operator. In this work, a human machine interface (HMI) based on a novel gesture recognition system using depth imagery is proposed for the control of UAVs. Hand gesture recognition based on depth imagery is a promising approach for HMIs because it is more intuitive, natural, and non-intrusive than other alternatives using complex controllers. The proposed system is based on a Support Vector Machine (SVM) classifier that uses spatio-temporal depth descriptors as input features. The designed descriptor is based on a variation of the Local Binary Pattern (LBP) technique to efficiently work with depth video sequences. Other major consideration is the especial hand sign language used for the UAV control. A tradeoff between the use of natural hand signs and the minimization of the inter-sign interference has been established. Promising results have been achieved in a depth based database of hand gestures especially developed for the validation of the proposed system.

Predicción espacio-temporal de la irradiancia solar global a corto plazo en España mediante geoestadística y redes neuronales artificiales

El enriquecimiento del conocimiento sobre la Irradiancia Solar (IS) a nivel de superficie terrestre, así como su predicción, cobran gran interés para las Energías Renovables (ER) - Energía Solar (ES)-, y para distintas aplicaciones industriales o ecológicas. En el ámbito de las ER, el uso óptimo de la ES implica contar con datos de la IS en superficie que ayuden tanto, en la selección de emplazamientos para instalaciones de ES, como en su etapa de diseño (dimensionar la producción) y, finalmente, en su explotación. En este último caso, la observación y la predicción es útil para el mercado energético, la planificación y gestión de la energía (generadoras y operadoras del sistema eléctrico), especialmente en los nuevos contextos de las redes inteligentes de transporte. A pesar de la importancia estratégica de contar con datos de la IS, especialmente los observados por sensores de IS en superficie (los que mejor captan esta variable), estos no siempre están disponibles para los lugares de interés ni con la resolución espacial y temporal deseada. Esta limitación se une a la necesidad de disponer de predicciones a corto plazo de la IS que ayuden a la planificación y gestión de la energía. Se ha indagado y caracterizado las Redes de Estaciones Meteorológicas (REM) existentes en España que publican en internet sus observaciones, focalizando en la IS. Se han identificado 24 REM (16 gubernamentales y 8 redes voluntarios) que aglutinan 3492 estaciones, convirtiéndose éstas en las fuentes de datos meteorológicos utilizados en la tesis. Se han investigado cinco técnicas de estimación espacial de la IS en intervalos de 15 minutos para el territorio peninsular (3 técnicas geoestadísticas, una determinística y el método HelioSat2 basado en imágenes satelitales) con distintas configuraciones espaciales. Cuando el área de estudio tiene una adecuada densidad de observaciones, el mejor método identificado para estimar la IS es el Kriging con Regresión usando variables auxiliares -una de ellas la IS estimada a partir de imágenes satelitales-. De este modo es posible estimar espacialmente la IS más allá de los 25 km identificados en la bibliografía. En caso contrario, se corrobora la idoneidad de utilizar estimaciones a partir de sensores remotos cuando la densidad de observaciones no es adecuada. Se ha experimentado con el modelado de Redes Neuronales Artificiales (RNA) para la predicción a corto plazo de la IS utilizando observaciones próximas (componentes espaciales) en sus entradas y, los resultados son prometedores. Así los niveles de errores disminuyen bajo las siguientes condiciones: (1) cuando el horizonte temporal de predicción es inferior o igual a 3 horas, las estaciones vecinas que se incluyen en el modelo deben encentrarse a una distancia máxima aproximada de 55 km. Esto permite concluir que las RNA son capaces de aprender cómo afectan las condiciones meteorológicas vecinas a la predicción de la IS. ABSTRACT ABSTRACT The enrichment of knowledge about the Solar Irradiance (SI) at Earth's surface and its prediction, have a high interest for Renewable Energy (RE) - Solar Energy (SE) - and for various industrial and environmental applications. In the field of the RE, the optimal use of the SE involves having SI surface to help in the selection of sites for facilities ES, in the design stage (sizing energy production), and finally on their production. In the latter case, the observation and prediction is useful for the market, planning and management of the energy (generators and electrical system operators), especially in new contexts of smart transport networks (smartgrid). Despite the strategic importance of SI data, especially those observed by sensors of SI at surface (the ones that best measure this environmental variable), these are not always available to the sights and the spatial and temporal resolution desired. This limitation is bound to the need for short-term predictions of the SI to help planning and energy management. It has been investigated and characterized existing Networks of Weather Stations (NWS) in Spain that share its observations online, focusing on SI. 24 NWS have been identified (16 government and 8 volunteer networks) that implies 3492 stations, turning it into the sources of meteorological data used in the thesis. We have investigated five technical of spatial estimation of SI in 15 minutes to the mainland (3 geostatistical techniques and HelioSat2 a deterministic method based on satellite images) with different spatial configurations. When the study area has an adequate density of observations we identified the best method to estimate the SI is the regression kriging with auxiliary variables (one of them is the SI estimated from satellite images. Thus it is possible to spatially estimate the SI beyond the 25 km identified in the literature. Otherwise, when the density of observations is inadequate the appropriateness is using the estimates values from remote sensing. It has been experimented with Artificial Neural Networks (ANN) modeling for predicting the short-term future of the SI using observations from neighbor’s weather stations (spatial components) in their inputs, and the results are promising. The error levels decrease under the following conditions: (1) when the prediction horizon is less or equal than 3 hours the best models are the ones that include data from the neighboring stations (at a maximum distance of 55 km). It is concluded that the ANN is able to learn how weather conditions affect neighboring prediction of IS at such Spatio-temporal horizons.

Heterogeneidade espacial e variabilidade temporal de dois reservatórios com diferentes graus de trofia, no Estado de São Paulo

O entendimento da comunidade fitoplanctônica em sistemas instáveis, como por exemplo reservatórios, necessita conhecimento de escalas de variabilidade. Com base nisso, um estudo sobre a heterogeneidade espacial e variabilidade temporal de dois reservatórios com diferentes graus de trofia, no Estado de São Paulo foi realizado em 20 estações no reservatório de Salto Grande e em 19 no reservatório do Lobo, em 3 dias consecutivos, em quatro períodos: outubro de 1999, janeiro, abril e junho e julho de 2000. Para tanto foram determinadas as concentrações de nutrientes totais e dissolvidos, material em suspensão, carbono inorgânico, clorofila a, biomassa, densidade, composição e produtividade primária da comunidade fitoplanctônica e os perfis de oxigênio dissolvido, temperatura, pH e condutividade. Os dois reservatórios tiveram estruturas espaciais semelhantes com a formação de três zonas distintas. A zona de rio, misturada, com menor penetração de luz e maior concentração de nutrientes, a zona de transição, e a zona lacustre, mais estratificada, com maior penetração de luz e menor concentração de nutrientes. Apesar dessa compartimentalização a heterogeneidade espacial no reservatório de Salto Grande foi maior que no reservatório do Lobo, sobretudo em função do gradiente longitudinal de nutrientes e luz. A variabilidade diária (3 dias) nos dois reservatórios não foi significativa na determinação da comunidade fitoplanctônica. A escala de variabilidade sazonal, nos dois reservatórios, foi determinada, principalmente pela variação nos padrões de estratificação e mistura sendo, assim, determinante na composição da comunidade fitoplanctônica. Essa influência foi mais evidente no reservatório do Lobo. A variação temporal e heterogeneidade espacial das mais abundantes espécies e grupos taxonômicos da comunidade fitoplanctônica, (Microcystis aeruginosa, Anabaena crassa e Anabaena circinalis em Salto Grande e Aphanocapsa delicatissima, Coelastrum reticulatum e Aulacoseira granulata no Lobo) nos dois reservatórios foram determinados pelos complexos processos de estratificação e mistura e da disponibilidade de luz. Os resultados obtidos são importantes para o entendimento da variabilidade ambiental de reservatórios tropicais e no planejamento de amostragens que visem o gerenciamento desses sistemas.

Regional subsidence modelling in Murcia city (SE Spain) using 1-D vertical finite element analysis and 2-D interpolation of ground surface displacements

Subsidence is a hazard that may have natural or anthropogenic origin causing important economic losses. The area of Murcia city (SE Spain) has been affected by subsidence due to groundwater overexploitation since the year 1992. The main observed historical piezometric level declines occurred in the periods 1982–1984, 1992–1995 and 2004–2008 and showed a close correlation with the temporal evolution of ground displacements. Since 2008, the pressure recovery in the aquifer has led to an uplift of the ground surface that has been detected by the extensometers. In the present work an elastic hydro-mechanical finite element code has been used to compute the subsidence time series for 24 geotechnical boreholes, prescribing the measured groundwater table evolution. The achieved results have been compared with the displacements estimated through an advanced DInSAR technique and measured by the extensometers. These spatio-temporal comparisons have showed that, in spite of the limited geomechanical data available, the model has turned out to satisfactorily reproduce the subsidence phenomenon affecting Murcia City. The model will allow the prediction of future induced deformations and the consequences of any piezometric level variation in the study area.

Selfmapping : o mapa colaborativo como medium de visualização espácio-temporal

THE MAP AS A COLLABORATIVE MEDIUM FOR SPATIO-TEMPORAL VISUALIZATION This dissertation focuses on the relationship between maps and spatio-temporal data visualization. It is divided into two components: theoretical framework and practical approach. The study begins by questioning the role of the map in today’s digital society and particularly its role in visualization, and finishes with the conceptualization and development of an interactive dot map that visualizes data from Instagram and Twitter. Nowadays, geographic information is no longer produced just by experts, but also by ordinary people that are able to participate in data creation and exchange. The Web 2.0 lies in the heart of this change, where social media represent a significant tool for producing geotagged content, allowing its users to share their location and to spatially reference their publications. Furthermore, amateur mapmaking and neogeography have benefited from the emergence of several new devices that enable the creation of digital maps that are interactive, adaptable and easily shared on the Web. This study adopts a descriptive approach calling upon the diverse aspects of the map and its evolution as a medium for visualizing geotagged data, highlighting collaborative mapping as an emerging subject area that is of mandatory future research. Relevant projects are also analyzed in order to identify trends and different approaches for visualizing social media data in its spatial context, intended to support the project’s conceptualization, development and evaluation. The created map demonstrates how spatial knowledge and perception of place are now redefined by the contributions of individuals; it also shows how that activity produces new sources of geographic information, forcing the development of new techniques and approaches that allow an adequate exploration of content and visualization methods of the contemporary map

Spatial and temporal variability in somatic growth of green sea turtles (Chelonia mydas) resident in the Hawaiian Archipelago

The somatic growth dynamics of green turtles ( Chelonia mydas) resident in five separate foraging grounds within the Hawaiian Archipelago were assessed using a robust non-parametric regression modelling approach. The foraging grounds range from coral reef habitats at the north-western end of the archipelago, to coastal habitats around the main islands at the southeastern end of the archipelago. Pelagic juveniles recruit to these neritic foraging grounds from ca. 35 cm SCL or 5 kg ( similar to 6 years of age), but grow at foraging-ground-specific rates, which results in quite different size- and age-specific growth rate functions. Growth rates were estimated for the five populations as change in straight carapace length ( cm SCL year) 1) and, for two of the populations, also as change in body mass ( kg year) 1). Expected growth rates varied from ca. 0 - 2.5 cm SCL year) 1, depending on the foraging-ground population, which is indicative of slow growth and decades to sexual maturity, since expected size of first-time nesters is greater than or equal to 80 cm SCL. The expected size- specific growth rate functions for four populations sampled in the southeastern archipelago displayed a non-monotonic function, with an immature growth spurt at ca. 50 - 53 cm SCL ( similar to 18 - 23 kg) or ca. 13 - 19 years of age. The growth spurt for the Midway atoll population in the northwestern archipelago occurs at a much larger size ( ca. 65 cm SCL or 36 kg), because of slower immature growth rates that might be due to a limited food stock and cooler sea surface temperature. Expected age-at-maturity was estimated to be ca. 35 - 40 years for the four populations sampled at the south-eastern end of the archipelago, but it might well be > 50 years for the Midway population. The Hawaiian stock comprises mainly the same mtDNA haplotype, with no differences in mtDNA stock composition between foraging-ground populations, so that the geographic variability in somatic growth rates within the archipelago is more likely due to local environmental factors rather than genetic factors. Significant temporal variability was also evident, with expected growth rates declining over the last 10 - 20 years, while green turtle abundance within the archipelago has increased significantly since the mid-1970s. This inverse relationship between somatic growth rates and population abundance suggests a density-dependent effect on somatic growth dynamics that has also been reported recently for a Caribbean green turtle stock. The Hawaiian green turtle stock is characterised by slow growth rates displaying significant spatial and temporal variation and an immature growth spurt. This is consistent with similar findings for a Great Barrier Reef green turtle stock that also comprises many foraging-ground populations spanning a wide geographic range.

Binocular combination at threshold: temporal filtering and summation of signals in separate ON and OFF channels

How does the brain combine spatio-temporal signals from the two eyes? We quantified binocular summation as the improvement in 2AFC contrast sensitivity for flickering gratings seen by two eyes compared with one. Binocular gratings in-phase showed sensitivity up to 1.8 times higher, suggesting nearly linear summation of contrasts. The binocular advantage decreased to 1.4 at lower spatial and higher temporal frequencies (0.25 cycle deg-1, 30 Hz). Dichoptic, antiphase gratings showed only a small binocular advantage, by a factor of 1.1 to 1.2, but no evidence of cancellation. We present a signal-processing model to account for the contrast-sensitivity functions and the pattern of binocular summation. It has linear sustained and transient temporal filters, nonlinear transduction, and half-wave rectification that creates ON and OFF channels. Binocular summation occurs separately within ON and OFF channels, thus explaining the phase-specific binocular advantage. The model also accounts for earlier findings on detection of brief antiphase flashes and the surprising finding that dichoptic antiphase flicker is seen as frequency-doubled (Cavonius et al, 1992 Ophthalmic and Physiological Optics 12 153 - 156). [Supported by EPSRC project GR/S74515/01].

Spatial and temporal dependencies of cross-orientation suppression in human vision.

A well-known property of orientation-tuned neurons in the visual cortex is that they are suppressed by the superposition of an orthogonal mask. This phenomenon has been explained in terms of physiological constraints (synaptic depression), engineering solutions for components with poor dynamic range (contrast normalization) and fundamental coding strategies for natural images (redundancy reduction). A common but often tacit assumption is that the suppressive process is equally potent at different spatial and temporal scales of analysis. To determine whether it is so, we measured psychophysical cross-orientation masking (XOM) functions for flickering horizontal Gabor stimuli over wide ranges of spatio-temporal frequency and contrast. We found that orthogonal masks raised contrast detection thresholds substantially at low spatial frequencies and high temporal frequencies (high speeds), and that small and unexpected levels of facilitation were evident elsewhere. The data were well fit by a functional model of contrast gain control, where (i) the weight of suppression increased with the ratio of temporal to spatial frequency and (ii) the weight of facilitatory modulation was the same for all conditions, but outcompeted by suppression at higher contrasts. These results (i) provide new constraints for models of primary visual cortex, (ii) associate XOM and facilitation with the transient magno- and sustained parvostreams, respectively, and (iii) reconcile earlier conflicting psychophysical reports on XOM.

Real-time heterodyned measurements of spatio-frequency dynamics in fibre lasers

We report high-resolution real-time measurements of spectrum evolution in a fibre. The proposed method combines optical heterodyning with a technique of spatio-temporal intensity measurements revealing fast spectral dynamics of cavity-based systems.

Climate change and plankton phenology in freshwater: current trends and future commitments

A solid body of empirical, experimental and theoretical evidence accumulated over recent years indicated that freshwater plankton experienced advance in phenology in response to climate change. Despite rapidly growing evidence for phenological changes, we still lack a comprehensive understanding of how climate change alters plankton phenology in freshwater. To overcome current limitations, we need to shed some light on trends and constraints in current research. The goal of this study is to identify current trends and gaps based on analysis of selected papers, by the help of which we can facilitate further advance in the field. We searched the literature for plankton phenology and confined our search to studies where climate change has been proposed to alter plankton phenology and rates of changes were quantified. We did not restrict our search for empirical ontributions; experimental and theoretical studies were considered as well. In the following we discuss the spatio-temporal setting of selected studies, contributions of different taxonomic groups, emerging methodological constraints, measures of phenological trends; and finally give a list of recommendations on how to improve our understanding in the field. The majority of studies were confined to deep lakes with a skewed geographical distribution toward Central Europe, where scientists have long been engaged in limnology. Despite these findings, recent studies suggest that plankton in running waters may experience change in phenology with similar magnitude. Average rate of advancement in phenology of freshwater plankton exceeded those of the marine plankton and the global average. Increasing study duration was not coupled either with increasing contribution of discontinuous data or with increasing rates of phenological changes. Future studies may benefit from i) delivering longterm data across scientific and political boundaries; ii) extending study sites to broader geographical areas with a more explicit consideration of running waters; iii) applying plankton functional groups; iv) increasing the application of satellite data to quantify phytoplankton bloom phenology; v) extending analyses of time series beyond the spring period; vi) using various metrics to quantify variation in phenology; vii) combining empirical, experimental and theoretical approaches; and last but not least viii) paying more attention to emergence dynamics, nonresponding species and trophic mismatch.

Treefrogs in Forested Swamps at the La Selva Biological Station: Assemblage Variation through Space and Time

Swamp-breeding treefrogs form conspicuous components of many tropical forest sites, yet remain largely understudied. The La Selva Biological Station, a rainforest reserve in Costa Rica, harbors a rich swamp-breeding treefrog fauna that has been studied in only one of the many swamps found at the site. To understand if the species composition of treefrogs at La Selva varies over space or time, frogs were censused in 1982-83, 1994-95, 2005 and 2011 at two ponds located in the reserve. Data on treefrog habitat utilization were also collected. Species composition varied spatially only in 2011. Temporal variation was observed at both ponds for all groups tested. Habitat use varied among species and between swamps. The pattern of variation suggests that temporally dynamic systems such as temporary Neotropical forest swamps will converge and diverge in species composition over time.

A conceptual model of ecological interactions in the mangrove estuaries of the Florida Everglades

A brackish water ecotone of coastal bays and lakes, mangrove forests, salt marshes, tidal creeks, and upland hammocks separates Florida Bay, Biscayne Bay, and the Gulf of Mexico from the freshwater Everglades. The Everglades mangrove estuaries are characterized by salinity gradients that vary spatially with topography and vary seasonally and inter-annually with rainfall, tide, and freshwater flow from the Everglades. Because of their location at the lower end of the Everglades drainage basin, Everglades mangrove estuaries have been affected by upstream water management practices that have altered the freshwater heads and flows and that affect salinity gradients. Additionally, interannual variation in precipitation patterns, particularly those caused to El Nin˜o events, control freshwater inputs and salinity dynamics in these estuaries. Two major external drivers on this system are water management activities and global climate change. These drivers lead to two major ecosystem stressors: reduced freshwater flow volume and duration, and sea-level rise. Major ecological attributes include mangrove forest production, soil accretion, and resilience; coastal lake submerged aquatic vegetation; resident mangrove fish populations; wood stork (Mycteria americana) and roseate spoonbill (Platelea ajaja) nesting colonies; and estuarine crocodilian populations. Causal linkages between stressors and attributes include coastal transgression, hydroperiods, salinity gradients, and the ‘‘white zone’’ freshwater/estuarine interface. The functional estuary and its ecological attributes, as influenced by sea level and freshwater flow, must be viewed as spatially dynamic, with a possible near-term balancing of transgression but ultimately a long-term continuation of inland movement. Regardless of the spatio-temporal timing of this transgression, a salinity gradient supportive of ecologically functional Everglades mangrove estuaries will be required to maintain the integrity of the South Florida ecosystem.