938 resultados para Local Spatio-Temporal Features
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Natural regeneration in stone pine (Pinus pinea L.) managed forests in the Spanish Northern Plateau is not achieved successfully under current silviculture practices, constituting a main concern for forest managers. We modelled spatio-temporal features of primary dispersal to test whether (a) present low stand densities constrain natural regeneration success and (b) seed release is a climate-controlled process. The present study is based on data collected from a 6 years seed trap experiment considering different regeneration felling intensities. From a spatial perspective, we attempted alternate established kernels under different data distribution assumptions to fit a spatial model able to predict P. pinea seed rain. Due to P. pinea umbrella-like crown, models were adapted to account for crown effect through correction of distances between potential seed arrival locations and seed sources. In addition, individual tree fecundity was assessed independently from existing models, improving parameter estimation stability. Seed rain simulation enabled to calculate seed dispersal indexes for diverse silvicultural regeneration treatments. The selected spatial model of best fit (Weibull, Poisson assumption) predicted a highly clumped dispersal pattern that resulted in a proportion of gaps where no seed arrival is expected (dispersal limitation) between 0.25 and 0.30 for intermediate intensity regeneration fellings and over 0.50 for intense fellings. To describe the temporal pattern, the proportion of seeds released during monthly intervals was modelled as a function of climate variables – rainfall events – through a linear model that considered temporal autocorrelation, whereas cone opening took place over a temperature threshold. Our findings suggest the application of less intensive regeneration fellings, to be carried out after years of successful seedling establishment and, seasonally, subsequent to the main rainfall period (late fall). This schedule would avoid dispersal limitation and would allow for a complete seed release. These modifications in present silviculture practices would produce a more efficient seed shadow in managed stands.
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Antalya Gulf is situated in the Levantine Sea, the second biggest and most eastern basin in the Mediterranean Sea. This area is an ultra-oligotrophic basin, strongly affected by anthropogenic inputs, in particular in the fishing areas. For this characteristic, in the Levantine Sea, there is a strong pressure on the natural resources and benthic assemblages. Furthermore, many alien species enter from Suez Canal and are well established in the area. All these pressures are leading to a degradation of the Levantine Sea. For this reason it is important to have tools to study and monitoring the functioning of the marine ecosystem. Benthic organisms are superior to many other biological groups for their response to environmental stresses. The variability of benthic assemblages on a site can reflect, in an integrative mode, the entire functioning of the marine ecosystem. In this study, that wants to analyze the spatial and temporal distribution of the benthic macrofaunal assemblages of Antalya Gulf, 90 benthic species divided in 8 taxa (Annelida, Cnidaria, Echinodermata, Echiura, Mollusca, Porifera, Sipunculida and Tunicata) were found. All the analyses conducted on the entire benthic class and later on Mollusca and Echinodermata separately highlighted the importance of depth on structuring benthic community.
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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.
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The bathyal faunal communities of the NW Mediterranean slopes have been studied consistently in the last two decades, with a special focus on population structure, trophic dynamics and benthopelagic coupling of commercial deep-sea decapod crustaceans and fishes (reviewed in Sardà et al. 2004) and associated species (Cartes and Sardà, 1993; Company and Sardà, 1997, 2000; Cartes et al., 2001; Company et al., 2001, 2003, 2004). One of the major topographic features in the North-western Mediterranean slope is the presence of submarine canyons. Canyons play a major role in funnelling energy and organic matter from the shelf to bathyal and abyssal depths (Puig et al., 2000), but the implications of this enhanced organic supply in the deep-sea benthic communities is still mostly unknown. Trophic supply can follow two major pathways – vertical deposition in the water column (Billett et al., 1983; Baldwin et al., 1998; Lampitt et al., 2001) or down-slope advection on the margins (Puig et al., 2001; Bethoux et al., 2002; Canals et al., 2006) – and can be a limiting factor in the deep-sea, being especially important in the oligotrophic Mediterranean Sea (Sardà et al., 2004). Differences in the quantity, quality and timing of organic matter input to the deep seafloor have been used to explain patterns of biomass and abundance in benthic communities (Levin et al., 1994; Gooday & Turley, 1990; Billett et al., 2001; Galéron et al., 2001; Puig et al., 2001; Gage, 2003) as well as other biological process and in particular the existence of seasonal reproduction (Tyler et al., 1994; Company et al., 2004 (MEPS). Reproduction is a highly energetic process tightly linked to food availability and quality.
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Distribution of socio-economic features in urban space is an important source of information for land and transportation planning. The metropolization phenomenon has changed the distribution of types of professions in space and has given birth to different spatial patterns that the urban planner must know in order to plan a sustainable city. Such distributions can be discovered by statistical and learning algorithms through different methods. In this paper, an unsupervised classification method and a cluster detection method are discussed and applied to analyze the socio-economic structure of Switzerland. The unsupervised classification method, based on Ward's classification and self-organized maps, is used to classify the municipalities of the country and allows to reduce a highly-dimensional input information to interpret the socio-economic landscape. The cluster detection method, the spatial scan statistics, is used in a more specific manner in order to detect hot spots of certain types of service activities. The method is applied to the distribution services in the agglomeration of Lausanne. Results show the emergence of new centralities and can be analyzed in both transportation and social terms.
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Aim The spotted knapweed (Centaurea stoebe), a plant native to south-east and central Europe, is highly invasive in North America. We investigated the spatio-temporal climatic niche dynamics of the spotted knapweed in North America along two putative eastern and western invasion routes. We then considered the patterns observed in the light of historical, ecological and evolutionary factors. Location Europe and North America. Methods The niche characteristics of the east and west invasive populations of spotted knapweed in North America were determined from documented occurrences over 120 consecutive years (1890-2010). The 2.5 and 97.5 percentiles of values along temperature and precipitation gradients, as given by the two first axes of a principal component axis (PCA), were then calculated. We additionally measured the climatic dissimilarity between invaded and native niches using a multivariate environmental similarity surface (MESS) analysis. Results Along both invasion routes, the species established in regions with climatic conditions that were similar to those in the native range in Europe. An initial spread in ruderal habitats always preceded spread in (semi-)natural habitats. In the east, the niche gradually increased over time until it reached limits similar to the native niche. Conversely, in the west the niche abruptly expanded after an extended time lag into climates not occupied in the native range; only the native cold niche limit was conserved. Main conclusions Our study reveals that different niche dynamics have taken place during the eastern and western invasions. This pattern indicates different combinations of historical, ecological and evolutionary factors in the two ranges. We hypothesize that the lack of a well-developed transportation network in the west at the time of the introduction of spotted knapweed confined the species to a geographically and climatically isolated region. The invasion of dry rangelands may have been favoured during the agricultural transition in the 1930s by release from natural enemies, local adaptation and less competitive vegetation, but further experimental and molecular studies are needed to explain these contrasting niche patterns fully. Our study illustrates the need and benefit of applying large-scale, temporally explicit approaches to understanding biological invasions.
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Two different approaches currently prevail for predicting spatial patterns of species assemblages. The first approach (macroecological modelling, MEM) focuses directly on realised properties of species assemblages, whereas the second approach (stacked species distribution modelling, S-SDM) starts with constituent species to approximate assemblage properties. Here, we propose to unify the two approaches in a single 'spatially-explicit species assemblage modelling' (SESAM) framework. This framework uses relevant species source pool designations, macroecological factors, and ecological assembly rules to constrain predictions of the richness and composition of species assemblages obtained by stacking predictions of individual species distributions. We believe that such a framework could prove useful in many theoretical and applied disciplines of ecology and evolution, both for improving our basic understanding of species assembly across spatio-temporal scales and for anticipating expected consequences of local, regional or global environmental changes. In this paper, we propose such a framework and call for further developments and testing across a broad range of community types in a variety of environments.
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Optimal behavior relies on flexible adaptation to environmental requirements, notably based on the detection of errors. The impact of error detection on subsequent behavior typically manifests as a slowing down of RTs following errors. Precisely how errors impact the processing of subsequent stimuli and in turn shape behavior remains unresolved. To address these questions, we used an auditory spatial go/no-go task where continual feedback informed participants of whether they were too slow. We contrasted auditory-evoked potentials to left-lateralized go and right no-go stimuli as a function of performance on the preceding go stimuli, generating a 2 × 2 design with "preceding performance" (fast hit [FH], slow hit [SH]) and stimulus type (go, no-go) as within-subject factors. SH trials yielded SH trials on the following trials more often than did FHs, supporting our assumption that SHs engaged effects similar to errors. Electrophysiologically, auditory-evoked potentials modulated topographically as a function of preceding performance 80-110 msec poststimulus onset and then as a function of stimulus type at 110-140 msec, indicative of changes in the underlying brain networks. Source estimations revealed a stronger activity of prefrontal regions to stimuli after successful than error trials, followed by a stronger response of parietal areas to the no-go than go stimuli. We interpret these results in terms of a shift from a fast automatic to a slow controlled form of inhibitory control induced by the detection of errors, manifesting during low-level integration of task-relevant features of subsequent stimuli, which in turn influences response speed.
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The coverage and volume of geo-referenced datasets are extensive and incessantly¦growing. The systematic capture of geo-referenced information generates large volumes¦of spatio-temporal data to be analyzed. Clustering and visualization play a key¦role in the exploratory data analysis and the extraction of knowledge embedded in¦these data. However, new challenges in visualization and clustering are posed when¦dealing with the special characteristics of this data. For instance, its complex structures,¦large quantity of samples, variables involved in a temporal context, high dimensionality¦and large variability in cluster shapes.¦The central aim of my thesis is to propose new algorithms and methodologies for¦clustering and visualization, in order to assist the knowledge extraction from spatiotemporal¦geo-referenced data, thus improving making decision processes.¦I present two original algorithms, one for clustering: the Fuzzy Growing Hierarchical¦Self-Organizing Networks (FGHSON), and the second for exploratory visual data analysis:¦the Tree-structured Self-organizing Maps Component Planes. In addition, I present¦methodologies that combined with FGHSON and the Tree-structured SOM Component¦Planes allow the integration of space and time seamlessly and simultaneously in¦order to extract knowledge embedded in a temporal context.¦The originality of the FGHSON lies in its capability to reflect the underlying structure¦of a dataset in a hierarchical fuzzy way. A hierarchical fuzzy representation of¦clusters is crucial when data include complex structures with large variability of cluster¦shapes, variances, densities and number of clusters. The most important characteristics¦of the FGHSON include: (1) It does not require an a-priori setup of the number¦of clusters. (2) The algorithm executes several self-organizing processes in parallel.¦Hence, when dealing with large datasets the processes can be distributed reducing the¦computational cost. (3) Only three parameters are necessary to set up the algorithm.¦In the case of the Tree-structured SOM Component Planes, the novelty of this algorithm¦lies in its ability to create a structure that allows the visual exploratory data analysis¦of large high-dimensional datasets. This algorithm creates a hierarchical structure¦of Self-Organizing Map Component Planes, arranging similar variables' projections in¦the same branches of the tree. Hence, similarities on variables' behavior can be easily¦detected (e.g. local correlations, maximal and minimal values and outliers).¦Both FGHSON and the Tree-structured SOM Component Planes were applied in¦several agroecological problems proving to be very efficient in the exploratory analysis¦and clustering of spatio-temporal datasets.¦In this thesis I also tested three soft competitive learning algorithms. Two of them¦well-known non supervised soft competitive algorithms, namely the Self-Organizing¦Maps (SOMs) and the Growing Hierarchical Self-Organizing Maps (GHSOMs); and the¦third was our original contribution, the FGHSON. Although the algorithms presented¦here have been used in several areas, to my knowledge there is not any work applying¦and comparing the performance of those techniques when dealing with spatiotemporal¦geospatial data, as it is presented in this thesis.¦I propose original methodologies to explore spatio-temporal geo-referenced datasets¦through time. Our approach uses time windows to capture temporal similarities and¦variations by using the FGHSON clustering algorithm. The developed methodologies¦are used in two case studies. In the first, the objective was to find similar agroecozones¦through time and in the second one it was to find similar environmental patterns¦shifted in time.¦Several results presented in this thesis have led to new contributions to agroecological¦knowledge, for instance, in sugar cane, and blackberry production.¦Finally, in the framework of this thesis we developed several software tools: (1)¦a Matlab toolbox that implements the FGHSON algorithm, and (2) a program called¦BIS (Bio-inspired Identification of Similar agroecozones) an interactive graphical user¦interface tool which integrates the FGHSON algorithm with Google Earth in order to¦show zones with similar agroecological characteristics.
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Ozone present in the atmosphere not only absorbs the biologically harmful ultraviolet radiation but also is an important ingredient of the climate system. The radiative absorption properties of ozone make it a determining factor in the structure of the atmosphere. Ozone in the troposphere has many negative impacts on humans and other living beings. Another significant aspect is the absorption of outgoing infrared radiation by ozone thus acting as a greenhouse gas. The variability of ozone in the atmosphere involves many interconnections with the incoming and outgoing radiation, temperature circulation etc. Hence ozone forms an important part of chemistry-climate as well as radiative transfer models. This aspect also makes the quantification of ozone more important. The discovery of Antarctic ozone hole and the role of anthropogenic activities in causing it made it possible to plan and implement necessary preventive measures. Continuous monitoring of ozone is also necessary to identify the effect of these preventive steps. The reactions involving the formation and destruction of ozone are influenced significantly by the temperature fluctuations of the atmosphere. On the other hand the variations in ozone can change the temperature structure of the atmosphere. Indian subcontinent is a region having large weather and climate variability which is evident from the large interannual variability of monsoon system over the region. Nearly half of Indian region comprises the tropical region. Most of ozone is formed in the tropical region and transported to higher latitudes. The formation and transport of ozone can be influenced by changes in solar radiation and various atmospheric circulation features. Besides industrial activities and vehicular traffic is more due to its large population. This may give rise to an increase in the production of tropospheric ozone which is greenhouse gas. Hence it becomes necessary to monitor the atmospheric ozone over this region. This study probes into the spatial distribution and temporal evolution of ozone over Indian subcontinent and discusses the contributing atmospheric parameters.
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Urban domestic cat (Felis catus) populations can attain exceedingly high densities and are not limited by natural prey availability. This has generated concerns that they may negatively affect prey populations, leading to calls for management. We enlisted cat-owners to record prey returned home to estimate patterns of predation by free-roaming pets in different localities within the town of Reading, UK and questionnaire surveys were used to quantify attitudes to different possible management strategies. Prey return rates were highly variable: only 20% of cats returned ≥4 dead prey annually. Consequently, approximately 65% of owners received no prey in a given season, but this declined to 22% after eight seasons. The estimated mean predation rate was 18.3 prey cat−1 year−1 but this varied markedly both spatially and temporally: per capita predation rates declined with increasing cat density. Comparisons with estimates of the density of six common bird prey species indicated that cats killed numbers equivalent to adult density on c. 39% of occasions. Population modeling studies suggest that such predation rates could significantly reduce the size of local bird populations for common urban species. Conversely, most urban residents did not consider cat predation to be a significant problem. Collar-mounted anti-predation devices were the only management action acceptable to the majority of urban residents (65%), but were less acceptable to cat-owners because of perceived risks to their pets; only 24% of cats were fitted with such devices. Overall, cat predation did appear to be of sufficient magnitude to affect some prey populations, although further investigation of some key aspects of cat predation is warranted. Management of the predation behavior of urban cat populations in the UK is likely to be challenging and achieving this would require considerable engagement with cat owners.
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Drought characterisation is an intrinsically spatio-temporal problem. A limitation of previous approaches to characterisation is that they discard much of the spatio-temporal information by reducing events to a lower-order subspace. To address this, an explicit 3-dimensional (longitude, latitude, time) structure-based method is described in which drought events are defined by a spatially and temporarily coherent set of points displaying standardised precipitation below a given threshold. Geometric methods can then be used to measure similarity between individual drought structures. Groupings of these similarities provide an alternative to traditional methods for extracting recurrent space-time signals from geophysical data. The explicit consideration of structure encourages the construction of summary statistics which relate to the event geometry. Example measures considered are the event volume, centroid, and aspect ratio. The utility of a 3-dimensional approach is demonstrated by application to the analysis of European droughts (15 °W to 35°E, and 35 °N to 70°N) for the period 1901–2006. Large-scale structure is found to be abundant with 75 events identified lasting for more than 3 months and spanning at least 0.5 × 106 km2. Near-complete dissimilarity is seen between the individual drought structures, and little or no regularity is found in the time evolution of even the most spatially similar drought events. The spatial distribution of the event centroids and the time evolution of the geographic cross-sectional areas strongly suggest that large area, sustained droughts result from the combination of multiple small area (∼106 km2) short duration (∼3 months) events. The small events are not found to occur independently in space. This leads to the hypothesis that local water feedbacks play an important role in the aggregation process.
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The evergreen Quercus ilex L. is one of the most common trees in Italian urban environments and is considered effective in the uptake of particulate and gaseous atmospheric pollutants. However, the few available estimates on O3 and NO2 removal by urban Q. ilex originate from model-based studies (which indicate NO2/O3 removal capacity of Q. ilex) and not from direct measurements of air pollutant concentrations. Thus, in the urban area of Siena (central Italy) we began long-term monitoring of O3/NO2 concentrations using passive samplers at a distance of 1, 5, 10 m from a busy road, under the canopies of Q. ilex and in a nearby open-field. Measurements performed in the period June 2011-October 2013 showed always a greater decrease of NO2 concentrations under the Q. ilex canopy than in the open-field transect. Conversely, a decrease of average O3 concentrations under the tree canopy was found only in autumn after the typical Mediterranean post-summer rainfalls. Our results indicate that interactions between O3/NO2 concentrations and trees in Mediterranean urban ecosystems are affected by temporal variations in climatic conditions. We argue therefore that the direct measurement of atmospheric pollutant concentrations should be chosen to describe local changes of aerial pollution.
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To properly describe the interactions between the ocean and atmosphere, it is necessary to assess a variety of time and spatial scales phenomena. Here, high resolution oceanographic and meteorological data collected during an observational campaign carried out aboard a ship in the tropical Atlantic Ocean, on May 15-24, 2002, is used to describe the radiation balance at the ocean interface. Data collected by two PIRATA buoys, along the equator at 23°W and 35°W and satellite and climate data are compared with the data obtained during the observational campaign. Comparison indicates remarkable similarity for daily and hourly values of radiation fluxes components as consequence of the temporal and spatial consistence presented by the air and water temperatures measured in situ and estimated from large scale information. The discrepancy, mainly in the Sao Pedro and Sao Paulo Archipelago area, seems to be associated to the local upwelling of cold water, which is not detected in all other estimates investigated here. More in situ data are necessary to clarify whether this upwelling flow has a larger scale effect and what are the meteorological and oceanographic implications of the local upwelling area on the tropical waters at the Brazilian coast.
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O presente estudo caracteriza a distribuição espaço-temporal dos peixes com maior abundância dentre a família Sciaenidae no estuário do rio Caeté, litoral norte do Brasil. Estima-se o comprimento de inicio da maturação sexual, o comprimento médio da primeira maturação sexual e os períodos de desova. Para tal, durante os meses de outubro de 1996 a agosto de 1997, foram feitas 6 coletas bimestrais, através de arrastos de fundo. A partir de subamostras das espécies mais abundantes dentro das capturas, construíram-se distribuições de freqüência de comprimento total, que foram analisadas por período e local de coleta. De onze espécies de Sciaenidae coletadas, a maior contribuição em abundância de exemplares foi feita pelas espécies Stellifer rastrifer, Stellifer naso e Macrodon ancylodon. Determinou-se que a distribuição espacial das espécies no sistema, está relacionada com mudanças periódicas na salinidade dentro do estuário e a sua dinâmica de reprodução. Assim, os juvenis de S. rastrifer, S. naso e M. ancylodon distribuíram-se nas áreas mais internas do estuário e os adultos nas águas costeiras, com maiores teores de salinidade. Enquanto que M. ancylodon apresenta desovas periódicas durante outubro a fevereiro, S. rastrifer e S. naso apresentam desovas parceladas com dois picos mais intensos de outubro a dezembro e durante junho.