914 resultados para Spatial Variability


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1. The spatial and temporal abundance of the aphid Euceraphis betulae was investigated in relation to heterogeneity in host plant ( Betula pendula) vigour and pathogenic stress. The performance of aphids feeding on vigorous and stressed foliage was also examined. 2. The plant stress and plant vigour hypotheses have been suggested as opposing ways in which foliage quality influences herbivore abundance. In many plants, however, vigorous growing foliage co-exists with stressed or damaged foliage. 3. There was a negative correlation between branch growth ( vigour) and branch stress ( leaf chlorosis), with the most vigorous branches displaying little or no stress, and the most stressed branches achieving poor growth. There was a similar negative correlation between vigour and stress at the level of individual trees, which themselves represented a continuum in quality. 4. At the beginning of the season, E. betulae were intermittently more abundant on vigorous branches than on branches destined to become stressed, but aphids became significantly more abundant on stressed branches later in the season, when symptoms of stress became apparent. Similar patterns of aphid abundance were seen on vigorous and stressed trees in the following year. 5. Euceraphis betulae performance was generally enhanced when feeding on naturally stressed B. pendula leaves, but there was some evidence for elevated potential reproduction when feeding on vigorous leaves too. 6. Overall, plant stress probably influences E. betulae distribution more than plant vigour, but the temporal and spatial variability in plant quality suggests that plant vigour could play a role in aphid distribution early in the season.

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Temporal and spatial variability of aerosol optical depth (AOD) are examined using observations of direct solar radiation in the Eurasian Arctic for 1940-1990. AOD is estimated using empirical methods for 14 stations located between 66.2 degrees N and 80.6 degrees N, from the Kara Sea to the Chukchi Sea. While AOD exhibits a well-known springtime maximum and summertime minimum at all stations, atmospheric turbidity is higher in spring in the western (Kara-Laptev) part of the Eurasian Arctic. Between June and August, the eastern (East Siberian-Chukchi) sector experiences higher transparency than the western part. A statistically significant positive trend in AOD was observed in the Kara-Laptev sector between the late 1950s and the early 1930s predominantly in spring when pollution-derived aerosol dominates the Arctic atmosphere but not in the eastern sector. Although all stations are remote, those with positive trends are located closer to the anthropogenic sources of air pollution. By contrast, a widespread decline in AOD was observed between 1982 and 1990 in the eastern Arctic in spring but was limited to two sites in the western Arctic. These results suggest that the post-1982 decline in anthropogenic emissions in Europe and the former Soviet Union has had a limited effect on aerosol load in the Arctic. The post-1982 negative trends in AOD in summer, when marine aerosol is present in the atmosphere, were more common in the west. The relationships between AOD and atmospheric circulation are examined using a synoptic climatology approach. In spring, AOD depends primarily on the strength and direction of air flow. Thus strong westerly and northerly flows result in low AOD values in the East Siberian-Chukchi sector. By contrast, strong southerly flow associated with the passage of depressions results in high A OD in the Kara-Laptev sector and trajectory analysis points to the contribution of industrial regions of the sub-Arctic. In summer, low pressure gradient or anticyclonic conditions result in high atmospheric turbidity. The frequency of this weather type has declined significantly since the early 1980s in the Kara-Laptev sector, which partly explains the decline in summer AOD values. (c) 2004 Elsevier B.V. All rights reserved.

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Lake Kinneret (LK) is a relatively fresh water take situated in the Dead Sea Rift (DSR) Valley. The pore water (PW) in the sediments underlying LK pelagic zone have significantly higher salinity than that of the lake. The concentrations of major ion solutes (Cl, Br, Na, K, Mg) in PW from six 2.4 m to 5.1 m long sediment cores increase linearly with depth, indicating the occurrence of saline, deep seated brines. The upper part of the PW column is affected by the much fresher boundary with LK water and in most cores is characterized by gradually increasing Br/Cl and decreasing Na, Mg, K/Cl molar ratios, which tend to stabilize at about 2.0 m below the sediment surface. The 'stable' molar ratios in the deeper PW vary spatially and are supposed to represent the ratios in the deep underlying brines at each site. When plotted as Na/Cl vs. Br/Cl, the stable ratios of the northern and central part of the lake fall close to a straight line which characterizes many of the brines in the DSR Valley. However, the respective ratios in the southern part of the lake fall markedly off the DSR line. Moreover, Na/Cl and K/Cl molar ratios in the south are significantly higher than in the central and northern parts. delta Cl-37 measured in present LK water is ca. 0.0 parts per thousand. Along the PW column at the lake center, delta Cl-37 is becoming more positive with depth, reaching values of about +0.5 parts per thousand to +0.6 parts per thousand at 3 m depth. Even more positive values (+0.7 parts per thousand to +0.8 parts per thousand) are detected further north, in PW from deeper sediment layers. In contrast, in PW from the southeastern part of the lake, delta Cl-37 is becoming more negative with depth (-1.0 parts per thousand at similar to 2.6 m). It is suggested that these isotopic differences are also indicative of spatial variability in the PW brine sources. O-18 and D values in the PW of all 3 m long cores are similar and resemble the respective levels in LK. The source of H2O in 3 m deep, bed sediments is claimed to be the overlying lake water, and therefore water isotopes do not provide a clue regarding the original water isotopic composition in the underlying brines. PW from the southeast with higher K/Cl and Na/Cl but lower concentrations of these solutes, suggest leaching by meteoric water of sub-surface halite and post-halite salt formations, while the more saline PW from the northern and central parts, that have lower K/Cl and Na/Cl, and higher Br/Cl, are similar to DSR brines and represent underlying residual brines. (C) 2009 Elsevier B.V. All rights reserved.

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A study of the formation and propagation of volume anomalies in North Atlantic Mode Waters is presented, based on 100 yr of monthly mean fields taken from the control run of the Third Hadley Centre Coupled Ocean-Atmosphere GCM (HadCM3). Analysis of the temporal and. spatial variability in the thickness between pairs of isothermal surfaces bounding the central temperature of the three main North Atlantic subtropical mode waters shows that large-scale variability in formation occurs over time scales ranging from 5 to 20 yr. The largest formation anomalies are associated with a southward shift in the mixed layer isothermal distribution, possibly due to changes in the gyre dynamics and/or changes in the overlying wind field and air-sea heat fluxes. The persistence of these anomalies is shown to result from their subduction beneath the winter mixed layer base where they recirculate around the subtropical gyre in the background geostrophic flow. Anomalies in the warmest mode (18 degrees C) formed on the western side of the basin persist for up to 5 yr. They are removed by mixing transformation to warmer classes and are returned to the seasonal mixed layer near the Gulf Stream where the stored heat may be released to the atmosphere. Anomalies in the cooler modes (16 degrees and 14 degrees C) formed on the eastern side of the basin persist for up to 10 yr. There is no clear evidence of significant transformation of these cooler mode anomalies to adjacent classes. It has been proposed that the eastern anomalies are removed through a tropical-subtropical water mass exchange mechanism beneath the trade wind belt (south of 20 degrees N). The analysis shows that anomalous mode water formation plays a key role in the long-term storage of heat in the model, and that the release of heat associated with these anomalies suggests a predictable climate feedback mechanism.

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From 1997 onward, the strobilurin fungicide azoxystrobin was widely used in the main banana-production zone in Costa Rica against Mycosphaerella fijiensis var. difformis causing black Sigatoka of banana. By 2000, isolates of M. fijiensis with resistance to the quinolene oxidase inhibitor fungicides were common on some farms in the area. The cause was a single point mutation from glycine to alanine in the fungal target protein, cytochrome b gene. An amplification refractory mutation system Scorpion quantitative polymerase chain reaction assay was developed and used to determine the frequency of G 143A allele in samples of M. fijiensis. Two hierarchical surveys of spatial variability, in 2001 and 2002,found no significant variation in frequency on spatial scales <10 in. This allowed the frequency of G143A alleles on a farm to be estimated efficiently by averaging single samples taken at two fixed locations. The frequency of G 143A allele in bulk samples from I I farms throughout Costa Rica was determined at 2-month intervals. There was no direct relationship between the number of spray applications and the frequency of G143A on individual farms. Instead, the frequency converged toward regional averages, presumably due to the large-scale mixing of ascospores dispersed by wind. Using trap plants in an area remote from the main producing area, immigration of resistant ascospores was detected as far as 6 km away both with and against the prevailing wind.

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Rainfall can be modeled as a spatially correlated random field superimposed on a background mean value; therefore, geostatistical methods are appropriate for the analysis of rain gauge data. Nevertheless, there are certain typical features of these data that must be taken into account to produce useful results, including the generally non-Gaussian mixed distribution, the inhomogeneity and low density of observations, and the temporal and spatial variability of spatial correlation patterns. Many studies show that rigorous geostatistical analysis performs better than other available interpolation techniques for rain gauge data. Important elements are the use of climatological variograms and the appropriate treatment of rainy and nonrainy areas. Benefits of geostatistical analysis for rainfall include ease of estimating areal averages, estimation of uncertainties, and the possibility of using secondary information (e.g., topography). Geostatistical analysis also facilitates the generation of ensembles of rainfall fields that are consistent with a given set of observations, allowing for a more realistic exploration of errors and their propagation in downstream models, such as those used for agricultural or hydrological forecasting. This article provides a review of geostatistical methods used for kriging, exemplified where appropriate by daily rain gauge data from Ethiopia.

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A quarter of a century of daily rainfall data from the Global Telecommunications System are used to define the temporal and spatial variability of the start of the wet season over Africa and surrounding extreme south of Europe and parts of the Middle East. From 1978 to 2002, the start of the wet season arrived later in the year for the majority of the region, as time progressed. In some parts of the continent, there was an annual increase in the start date of up to 4 days per year. On average, the start of the wet season arrived 9–21 days later from 1978 to 2002, depending on the threshold used to define the start of the rains (varying from 10–30 mm over 2 days, with no dry period in the following 10 days). It is noted that the inter-annual variability of the start of the wet season is high with the range of start dates varying on average from 116 to 142 days dependent on the threshold used to determine the start date. These results may have important implications for agriculturists on all levels (from the individual farmer to those responsible for regional food supply), as knowledge of potential future climate changes starts to play an increasingly important role in the agricultural decision-making process, such as sowing and harvesting times.

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Self-pollination dominates in wheat , with a small level of out-crossing due to flowering asynchrony and male sterility. However, the timing and synchrony of male and female flowering in wheat is a crucial determinant of seed set and may be an important factor affecting gene flow and resilience to climate change. Here, a methodology is presented for assessing the timing and synchrony of flowering in wheat. From the onset of flowering until the end of anthesis, the anther and stigma activity of each floret was assessed on the first five developing ears in potted plants grown under ambient conditions and originating from cv Paragon or cvs Spark-Rialto backgrounds. At harvest maturity, seed presence, size and weight was recorded for each floret scored. The synchrony between pollen dehiscence and stigma collapse within a flower was dependent on its relative position in a spike and within a floret. Determined on the basis of synchrony within each flower, the level of pollination by pollen originating from other flowers reached approximately 30% and did not change throughout the duration of flowering. A modelling exercise parameterised by flowering observations indicated that the temporal and spatial variability of anther activity within and between spikes may influence the relative resilience of wheat to sudden, extreme climatic events which has direct relevance to predicted future climate scenarios in the UK.

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Long time series of ground-based plant phenology, as well as more than two decades of satellite-derived phenological metrics, are currently available to assess the impacts of climate variability and trends on terrestrial vegetation. Traditional plant phenology provides very accurate information on individual plant species, but with limited spatial coverage. Satellite phenology allows monitoring of terrestrial vegetation on a global scale and provides an integrative view at the landscape level. Linking the strengths of both methodologies has high potential value for climate impact studies. We compared a multispecies index from ground-observed spring phases with two types (maximum slope and threshold approach) of satellite-derived start-of-season (SOS) metrics. We focus on Switzerland from 1982 to 2001 and show that temporal and spatial variability of the multispecies index correspond well with the satellite-derived metrics. All phenological metrics correlate with temperature anomalies as expected. The slope approach proved to deviate strongly from the temporal development of the ground observations as well as from the threshold-defined SOS satellite measure. The slope spring indicator is considered to indicate a different stage in vegetation development and is therefore less suited as a SOS parameter for comparative studies in relation to ground-observed phenology. Satellite-derived metrics are, however, very susceptible to snow cover, and it is suggested that this snow cover should be better accounted for by the use of newer satellite sensors.

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Wine production is strongly affected by weather and climate and thus highly vulnerable to climate change. In Portugal, viticulture and wine production are an important economic activity. In the present study, current bioclimatic zoning in Portugal (1950–2000) and its projected changes under future climate conditions (2041–2070) are assessed through the analysis of an aggregated, categorized bioclimatic index (CatI) at a very high spatial resolution (near 1 km). CatI incorporates the most relevant bioclimatic characteristics of a given region, thus allowing the direct comparison between different regions. Future viticultural zoning is achieved using data from 13 climate model transient experiments following the A1B emission scenario. These data are downscaled using a two-step method of spatial pattern downscaling. This downscaling approach allows characterizing mesoclimatic influences on viticulture throughout Portugal. Results for the recent past depict the current spatial variability of Portuguese viticultural regions. Under future climate conditions, the current viticultural zoning is projected to undergo significant changes, which may represent important challenges for the Portuguese winemaking sector. The changes are quite robust across the different climate models. A lower bioclimatic diversity is also projected, resulting from a more homogeneous warm and dry climate in most of the wine regions. This will lead to changes in varietal suitability and wine characteristics of each region.

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The significance and cause of the decline in biomass burning across the Americas after AD 1500 is a topic of considerable debate. We synthesized charcoal records (a proxy for biomass burning) from the Americas and from the remainder of the globe over the past 2000 years, and compared these with paleoclimatic records and population reconstructions. A distinct post-AD 1500 decrease in biomass burning is evident, not only in the Americas, but also globally, and both are similar in duration and timing to ‘Little Ice Age’ climate change. There is temporal and spatial variability in the expression of the biomass-burning decline across the Americas but, at a regional–continental scale, ‘Little Ice Age’ climate change was likely more important than indigenous population collapse in driving this decline.

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Global NDVI data are routinely derived from the AVHRR, SPOT-VGT, and MODIS/Terra earth observation records for a range of applications from terrestrial vegetation monitoring to climate change modeling. This has led to a substantial interest in the harmonization of multisensor records. Most evaluations of the internal consistency and continuity of global multisensor NDVI products have focused on time-series harmonization in the spectral domain, often neglecting the spatial domain. We fill this void by applying variogram modeling (a) to evaluate the differences in spatial variability between 8-km AVHRR, 1-km SPOT-VGT, and 1-km, 500-m, and 250-m MODIS NDVI products over eight EOS (Earth Observing System) validation sites, and (b) to characterize the decay of spatial variability as a function of pixel size (i.e. data regularization) for spatially aggregated Landsat ETM+ NDVI products and a real multisensor dataset. First, we demonstrate that the conjunctive analysis of two variogram properties – the sill and the mean length scale metric – provides a robust assessment of the differences in spatial variability between multiscale NDVI products that are due to spatial (nominal pixel size, point spread function, and view angle) and non-spatial (sensor calibration, cloud clearing, atmospheric corrections, and length of multi-day compositing period) factors. Next, we show that as the nominal pixel size increases, the decay of spatial information content follows a logarithmic relationship with stronger fit value for the spatially aggregated NDVI products (R2 = 0.9321) than for the native-resolution AVHRR, SPOT-VGT, and MODIS NDVI products (R2 = 0.5064). This relationship serves as a reference for evaluation of the differences in spatial variability and length scales in multiscale datasets at native or aggregated spatial resolutions. The outcomes of this study suggest that multisensor NDVI records cannot be integrated into a long-term data record without proper consideration of all factors affecting their spatial consistency. Hence, we propose an approach for selecting the spatial resolution, at which differences in spatial variability between NDVI products from multiple sensors are minimized. This approach provides practical guidance for the harmonization of long-term multisensor datasets.

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We have compiled 223 sedimentary charcoal records from Australasia in order to examine the temporal and spatial variability of fire regimes during the Late Quaternary. While some of these records cover more than a full glacial cycle, here we focus on the last 70,000 years when the number of individual records in the compilation allows more robust conclusions. On orbital time scales, fire in Australasia predominantly reflects climate, with colder periods characterized by less and warmer intervals by more biomass burning. The composite record for the region also shows considerable millennial-scale variability during the last glacial interval (73.5–14.7 ka). Within the limits of the dating uncertainties of individual records, the variability shown by the composite charcoal record is more similar to the form, number and timing of Dansgaard–Oeschger cycles as observed in Greenland ice cores than to the variability expressed in the Antarctic ice-core record. The composite charcoal record suggests increased biomass burning in the Australasian region during Greenland Interstadials and reduced burning during Greenland Stadials. Millennial-scale variability is characteristic of the composite record of the sub-tropical high pressure belt during the past 21 ka, but the tropics show a somewhat simpler pattern of variability with major peaks in biomass burning around 15 ka and 8 ka. There is no distinct change in fire regime corresponding to the arrival of humans in Australia at 50 ± 10 ka and no correlation between archaeological evidence of increased human activity during the past 40 ka and the history of biomass burning. However, changes in biomass burning in the last 200 years may have been exacerbated or influenced by humans.

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How people live, work, move from place to place, consume and the technologies they use all affect heat emissions in a city which influences urban weather and climate. Here we document changes to a global anthropogenic heat flux (QF) model to enhance its spatial (30′′ × 30′′ to 0.5° × 0.5°) resolution and temporal coverage (historical, current and future). QF is estimated across Europe (1995–2015), considering changes in temperature, population and energy use. While on average QF is small (of the order 1.9–4.6 W m−2 across all the urban areas of Europe), significant spatial variability is documented (maximum 185 W m−2). Changes in energy consumption due to changes in climate are predicted to cause a 13% (11%) increase in QF on summer (winter) weekdays. The largest impact results from changes in temperature conditions which influences building energy use; for winter, with the coldest February on record, the mean flux for urban areas of Europe is 4.56 W m−2 and for summer (warmest July on record) is 2.23 W m−2. Detailed results from London highlight the spatial resolution used to model the QF is critical and must be appropriate for the application at hand, whether scientific understanding or decision making.

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To optimise the placement of small wind turbines in urban areas a detailed understanding of the spatial variability of the wind resource is required. At present, due to a lack of observations, the NOABL wind speed database is frequently used to estimate the wind resource at a potential site. However, recent work has shown that this tends to overestimate the wind speed in urban areas. This paper suggests a method for adjusting the predictions of the NOABL in urban areas by considering the impact of the underlying surface on a neighbourhood scale. In which, the nature of the surface is characterised on a 1 km2 resolution using an urban morphology database. The model was then used to estimate the variability of the annual mean wind speed across Greater London at a height typical of current small wind turbine installations. Initial validation of the results suggests that the predicted wind speeds are considerably more accurate than the NOABL values. The derived wind map therefore currently provides the best opportunity to identify the neighbourhoods in Greater London at which small wind turbines yield their highest energy production. The model does not consider street scale processes, however previously derived scaling factors can be applied to relate the neighbourhood wind speed to a value at a specific rooftop site. The results showed that the wind speed predicted across London is relatively low, exceeding 4 ms-1 at only 27% of the neighbourhoods in the city. Of these sites less than 10% are within 10 km of the city centre, with the majority over 20 km from the city centre. Consequently, it is predicted that small wind turbines tend to perform better towards the outskirts of the city, therefore for cities which fit the Burgess concentric ring model, such as Greater London, ‘distance from city centre’ is a useful parameter for siting small wind turbines. However, there are a number of neighbourhoods close to the city centre at which the wind speed is relatively high and these sites can only been identified with a detailed representation of the urban surface, such as that developed in this study.