104 resultados para Fine spatial scale


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This study aimed to establish relationships between maize yield and rainfall on different temporal and spatial scales, in order to provide a basis for crop monitoring and modelling. A 16-year series of maize yield and daily rainfall from 11 municipalities and micro-regions of Rio Grande do Sul State was used. Correlation and regression analyses were used to determine associations between crop yield and rainfall for the entire crop cycle, from tasseling to 30 days after, and from 5 days before tasseling to 40 days after. Close relationships between maize yield and rainfall were found, particularly during the reproductive period (45-day period comprising the flowering and grain filling). Relationships were closer on a regional scale than at smaller scales. Implications of the crop-rainfall relationships for crop modelling are discussed.

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1 Adaptation of plant populations to local environments has been shown in many species but local adaptation is not always apparent and spatial scales of differentiation are not well known. In a reciprocal transplant experiment we tested whether: (i) three widespread grassland species are locally adapted at a European scale; (ii) detection of local adaptation depends on competition with the local plant community; and (iii) local differentiation between neighbouring populations from contrasting habitats can be stronger than differentiation at a European scale. 2 Seeds of Holcus lanatus, Lotus corniculatus and Plantago lanceolata from a Swiss, Czech and UK population were sown in a reciprocal transplant experiment at fields that exhibit environmental conditions similar to the source sites. Seedling emergence, survival, growth and reproduction were recorded for two consecutive years. 3 The effect of competition was tested by comparing individuals in weeded monocultures with plants sown together with species from the local grassland community. To compare large-scale vs. small-scale differentiation, a neighbouring population from a contrasting habitat (wet-dry contrast) was compared with the 'home' and 'foreign' populations. 4 In P. lanceolata and H. lanatus, a significant home-site advantage was detected in fitness-related traits, thus indicating local adaptation. In L. corniculatus, an overall superiority of one provenance was found. 5 The detection of local adaptation depended on competition with the local plant community. In the absence of competition the home-site advantage was underestimated in P. lanceolata and overestimated in H. lanatus. 6 A significant population differentiation between contrasting local habitats was found. In some traits, this small-scale was greater than large-scale differentiation between countries. 7 Our results indicate that local adaptation in real plant communities cannot necessarily be predicted from plants grown in weeded monocultures and that tests on the relationship between fitness and geographical distance have to account for habitat-dependent small-scale differentiation. Considering the strong small-scale differentiation, a local provenance from a different habitat may not be the best choice in ecological restoration if distant populations from a more similar habitat are available.

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The arthropod species richness of pastures in three Azorean islands was used to examine the relationship between local and regional species richness over two years. Two groups of arthropods, spiders and sucking insects, representing two functionally different but common groups of pasture invertebrates were investigated. The local-regional species richness relationship was assessed over relatively fine scales: quadrats (= local scale) and within pastures (= regional scale). Mean plot species richness was used as a measure of local species richness (= alpha diversity) and regional species richness was estimated at the pasture level (= gamma diversity) with the 'first-order-Jackknife' estimator. Three related issues were addressed: (i) the role of estimated regional species richness and variables operating at the local scale (vegetation structure and diversity) in determining local species richness; (ii) quantification of the relative contributions of alpha and beta diversity to regional diversity using additive partitioning; and (iii) the occurrence of consistent patterns in different years by analysing independently between-year data. Species assemblages of spiders were saturated at the local scale (similar local species richness and increasing beta-diversity in richer regions) and were more dependent on vegetational structure than regional species richness. Sucking insect herbivores, by contrast, exhibited a linear relationship between local and regional species richness, consistent with the proportional sampling model. The patterns were consistent between years. These results imply that for spiders local processes are important, with assemblages in a particular patch being constrained by habitat structure. In contrast, for sucking insects, local processes may be insignificant in structuring communities.

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Background: Variation in carrying capacity and population return rates is generally ignored in traditional studies of population dynamics. Variation is hard to study in the field because of difficulties controlling the environment in order to obtain statistical replicates, and because of the scale and expense of experimenting on populations. There may also be ethical issues. To circumvent these problems we used detailed simulations of the simultaneous behaviours of interacting animals in an accurate facsimile of a real Danish landscape. The models incorporate as much as possible of the behaviour and ecology of skylarks Alauda arvensis, voles Microtus agrestis, a ground beetle Bembidion lampros and a linyphiid spider Erigone atra. This allows us to quantify and evaluate the importance of spatial and temporal heterogeneity on the population dynamics of the four species. Results: Both spatial and temporal heterogeneity affected the relationship between population growth rate and population density in all four species. Spatial heterogeneity accounted for 23–30% of the variance in population growth rate after accounting for the effects of density, reflecting big differences in local carrying capacity associated with the landscape features important to individual species. Temporal heterogeneity accounted for 3–13% of the variance in vole, skylark and spider, but 43% in beetles. The associated temporal variation in carrying capacity would be problematic in traditional analyses of density dependence. Return rates were less than one in all species and essentially invariant in skylarks, spiders and beetles. Return rates varied over the landscape in voles, being slower where there were larger fluctuations in local population sizes. Conclusion: Our analyses estimated the traditional parameters of carrying capacities and return rates, but these are now seen as varying continuously over the landscape depending on habitat quality and the mechanisms of density dependence. The importance of our results lies in our demonstration that the effects of spatial and temporal heterogeneity must be accounted for if we are to have accurate predictive models for use in management and conservation. This is an area which until now has lacked an adequate theoretical framework and methodology.

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A detailed spore investigation of spore release and dispersal from an isolated colony of Phascum cuspidatum Hedw. indicated that approximately 98% of the spores originally present remained within the colony. The spatial distribution of colonies of P.cuspidatum and Pottia truncata (Hedw.) Fürer. in relation to those of the previous year was investigated by mapping the occurrence of colonies in five permanent quadrats for each species during two successive years. Phascum cuspidatum reoccurred in three quadrats during the second year, and P. truncata in only one, in the latter case apparently due to invasion by other mosses, principally Barbula hornschuchiana Schultz. A substantial proportion of the second year colonies overlapped in position with the first year colonies, particularly in P.cuspidatum. The results are discussed in relation to data on spore dispersal and other aspects of the life-history of these annual or short-lived shuttle mosses.

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1.There is concern over the possibility of unwanted environmental change following transgene movement from genetically modified (GM) rapeseed Brassica napus to its wild and weedy relatives. 2. The aim of this research was to develop a remote sensing-assisted methodology to help quantify gene flow from crops to their wild relatives over wide areas. Emphasis was placed on locating sites of sympatry, where the frequency of gene flow is likely to be highest, and on measuring the size of rapeseed fields to allow spatially explicit modelling of wind-mediated pollen-dispersal patterns. 3. Remote sensing was used as a tool to locate rapeseed fields, and a variety of image-processing techniques was adopted to facilitate the compilation of a spatially explicit profile of sympatry between the crop and Brassica rapa. 4. Classified satellite images containing rapeseed fields were first used to infer the spatial relationship between donor rapeseed fields and recipient riverside B. rapa populations. Such images also have utility for improving the efficiency of ground surveys by identifying probable sites of sympatry. The same data were then also used for the calculation of mean field size. 5. This paper forms a companion paper to Wilkinson et al. (2003), in which these elements were combined to produce a spatially explicit profile of hybrid formation over the UK. The current paper demonstrates the value of remote sensing and image processing for large-scale studies of gene flow, and describes a generic method that could be applied to a variety of crops in many countries. 6.Synthesis and applications. The decision to approve or prevent the release of a GM cultivar is made at a national rather than regional level. It is highly desirable that data relating to the decision-making process are collected at the same scale, rather than relying on extrapolation from smaller experiments designed at the plot, field or even regional scale. It would be extremely difficult and labour intensive to attempt to carry out such large-scale investigations without the use of remote-sensing technology. This study used rapeseed in the UK as a model to demonstrate the value of remote sensing in assembling empirical information at a national level.

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Concentrations of dissolved organic carbon have increased in many, but not all, surface waters across acid impacted areas of Europe and North America over the last two decades. Over the last eight years several hypotheses have been put forward to explain these increases, but none are yet accepted universally. Research in this area appears to have reached a stalemate between those favouring declining atmospheric deposition, climate change or land management as the key driver of long-term DOC trends. While it is clear that many of these factors influence DOC dynamics in soil and stream waters, their effect varies over different temporal and spatial scales. We argue that regional differences in acid deposition loading may account for the apparent discrepancies between studies. DOC has shown strong monotonic increases in areas which have experienced strong downward trends in pollutant sulphur and/or seasalt deposition. Elsewhere climatic factors, that strongly influence seasonality, have also dominated inter-annual variability, and here long-term monotonic DOC trends are often difficult to detect. Furthermore, in areas receiving similar acid loadings, different catchment characteristics could have affected the site specific sensitivity to changes in acidity and therefore the magnitude of DOC release in response to changes in sulphur deposition. We suggest that confusion over these temporal and spatial scales of investigation has contributed unnecessarily to the disagreement over the main regional driver(s) of DOC trends, and that the data behind the majority of these studies is more compatible than is often conveyed.

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Gaussian multi-scale representation is a mathematical framework that allows to analyse images at different scales in a consistent manner, and to handle derivatives in a way deeply connected to scale. This paper uses Gaussian multi-scale representation to investigate several aspects of the derivation of atmospheric motion vectors (AMVs) from water vapour imagery. The contribution of different spatial frequencies to the tracking is studied, for a range of tracer sizes, and a number of tracer selection methods are presented and compared, using WV 6.2 images from the geostationary satellite MSG-2.

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The spatial distribution of CO2 level in a classroom carried out in previous field work research has demonstrated that there is some evidence of variations in CO2 concentration in a classroom space. Significant fluctuations in CO2 concentration were found at different sampling points depending on the ventilation strategies and environmental conditions prevailing in individual classrooms. However, how these variations are affected by the emitting sources and the room air movement remains unknown. Hence, it was concluded that detailed investigation of the CO2 distribution need to be performed on a smaller scale. As a result, it was decided to use an environmental chamber with various methods and rates of ventilation, for the same internal temperature and heat loads, to study the effect of ventilation strategy and air movement on the distribution of CO2 concentration in a room. The role of human exhalation and its interaction with the plume induced by the body's convective flow and room air movement due to different ventilation strategies were studied in a chamber at the University of Reading. These phenomena are considered to be important in understanding and predicting the flow patterns in a space and how these impact on the distribution of contaminants. This paper attempts to study the CO2 dispersion and distribution at the exhalation zone of two people sitting in a chamber as well as throughout the occupied zone of the chamber. The horizontal and vertical distributions of CO2 were sampled at locations with a probability that CO2 variation is considered high. Although the room size, source location, ventilation rate and location of air supply and extract devices all can have influence on the CO2 distribution, this article gives general guidelines on the optimum positioning of CO2 sensor in a room.

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The spatial variability of soil nitrogen (N) mineralisation has not been extensively studied, which limits our capacity to make N fertiliser recommendations. Even less attention has been paid to the scale-dependence of the variation. The objective of this research was to investigate the scale-dependence of variation of mineral N (MinN, N–NO3− plus N–NH4+) at within-field scales. The study was based on the spatial dependence of the labile fractions of SOM, the key fractions for N mineralisation. Soils were sampled in an unbalanced nested design in a 4-ha arable field to examine the distribution of the variation of SOM at 30, 10, 1, and 0.12 m. Organic matter in free and intra-aggregate light fractions (FLF and IALF) was extracted by physical fractionation. The variation occurred entirely within 0.12 m for FLF and at 10 m for IALF. A subsequent sampling on a 5-m grid was undertaken to link the status of the SOM fractions to MinN, which showed uncorrelated spatial dependence. A uniform application of N fertiliser would be suitable in this case. The failure of SOM fractions to identify any spatial dependence of MinN suggests that other soil variables, or crop indicators, should be tested to see if they can identify different N supply areas within the field for a more efficient and environmentally friendly N management.

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Monitoring Earth's terrestrial water conditions is critically important to many hydrological applications such as global food production; assessing water resources sustainability; and flood, drought, and climate change prediction. These needs have motivated the development of pilot monitoring and prediction systems for terrestrial hydrologic and vegetative states, but to date only at the rather coarse spatial resolutions (∼10–100 km) over continental to global domains. Adequately addressing critical water cycle science questions and applications requires systems that are implemented globally at much higher resolutions, on the order of 1 km, resolutions referred to as hyperresolution in the context of global land surface models. This opinion paper sets forth the needs and benefits for a system that would monitor and predict the Earth's terrestrial water, energy, and biogeochemical cycles. We discuss six major challenges in developing a system: improved representation of surface‐subsurface interactions due to finescale topography and vegetation; improved representation of land‐atmospheric interactions and resulting spatial information on soil moisture and evapotranspiration; inclusion of water quality as part of the biogeochemical cycle; representation of human impacts from water management; utilizing massively parallel computer systems and recent computational advances in solving hyperresolution models that will have up to 109 unknowns; and developing the required in situ and remote sensing global data sets. We deem the development of a global hyperresolution model for monitoring the terrestrial water, energy, and biogeochemical cycles a “grand challenge” to the community, and we call upon the international hydrologic community and the hydrological science support infrastructure to endorse the effort.

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We investigate the spatial characteristics of urban-like canopy flow by applying particle image velocimetry (PIV) to atmospheric turbulence. The study site was a Comprehensive Outdoor Scale MOdel (COSMO) experiment for urban climate in Japan. The PIV system captured the two-dimensional flow field within the canopy layer continuously for an hour with a sampling frequency of 30 Hz, thereby providing reliable outdoor turbulence statistics. PIV measurements in a wind-tunnel facility using similar roughness geometry, but with a lower sampling frequency of 4 Hz, were also done for comparison. The turbulent momentum flux from COSMO, and the wind tunnel showed similar values and distributions when scaled using friction velocity. Some different characteristics between outdoor and indoor flow fields were mainly caused by the larger fluctuations in wind direction for the atmospheric turbulence. The focus of the analysis is on a variety of instantaneous turbulent flow structures. One remarkable flow structure is termed 'flushing', that is, a large-scale upward motion prevailing across the whole vertical cross-section of a building gap. This is observed intermittently, whereby tracer particles are flushed vertically out from the canopy layer. Flushing phenomena are also observed in the wind tunnel where there is neither thermal stratification nor outer-layer turbulence. It is suggested that flushing phenomena are correlated with the passing of large-scale low-momentum regions above the canopy.

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The application of automatic segmentation methods in lesion detection is desirable. However, such methods are restricted by intensity similarities between lesioned and healthy brain tissue. Using multi-spectral magnetic resonance imaging (MRI) modalities may overcome this problem but it is not always practicable. In this article, a lesion detection approach requiring a single MRI modality is presented, which is an improved method based on a recent publication. This new method assumes that a low similarity should be found in the regions of lesions when the likeness between an intensity based fuzzy segmentation and a location based tissue probabilities is measured. The usage of a normalized similarity measurement enables the current method to fine-tune the threshold for lesion detection, thus maximizing the possibility of reaching high detection accuracy. Importantly, an extra cleaning step is included in the current approach which removes enlarged ventricles from detected lesions. The performance investigation using simulated lesions demonstrated that not only the majority of lesions were well detected but also normal tissues were identified effectively. Tests on images acquired in stroke patients further confirmed the strength of the method in lesion detection. When compared with the previous version, the current approach showed a higher sensitivity in detecting small lesions and had less false positives around the ventricle and the edge of the brain

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A novel approach is presented for combining spatial and temporal detail from newly available TRMM-based data sets to derive hourly rainfall intensities at 1-km spatial resolution for hydrological modelling applications. Time series of rainfall intensities derived from 3-hourly 0.25° TRMM 3B42 data are merged with a 1-km gridded rainfall climatology based on TRMM 2B31 data to account for the sub-grid spatial distribution of rainfall intensities within coarse-scale 0.25° grid cells. The method is implemented for two dryland catchments in Tunisia and Senegal, and validated against gauge data. The outcomes of the validation show that the spatially disaggregated and intensity corrected TRMM time series more closely approximate ground-based measurements than non-corrected data. The method introduced here enables the generation of rainfall intensity time series with realistic temporal and spatial detail for dynamic modelling of runoff and infiltration processes that are especially important to water resource management in arid regions.

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This study analyzes the regional spatial dynamics of the New York region for a period of roughly twenty years and places the effects of the 9/11 terrorist attacks in the context of longer-term regional dynamics. The analysis reveals that office-using industries are still heavily concentrated in Manhattan despite ongoing decentralization in many of these industries over the last twenty years. Financial services tend to be highly concentrated in Manhattan whereas administrative and support services are the least concentrated of the six major office-using industry groups. Although office employment has been by and large stagnant in Manhattan for at least two decades, growth of output per worker has outpaced the CMSA as well as the national average. This productivity differential is mainly attributable to competitive advantages of office-using industries in Manhattan and not to differences in industry composition. Finally, the zip-code level analysis of the Manhattan core area yielded further evidence of the existence of significant spillover effects at the small-scale level.