888 resultados para seasonal and spatial trends


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Seasonal snow cover is of great environmental and socio-economic importance for the European Alps. Therefore a high priority has been assigned to quantifying its temporal and spatial variability. Complementary to land-based monitoring networks, optical satellite observations can be used to derive spatially comprehensive information on snow cover extent. For understanding long-term changes in alpine snow cover extent, the data acquired by the Advanced Very High Resolution Radiometer (AVHRR) sensors mounted onboard the National Oceanic and Atmospheric Association (NOAA) and Meteorological Operational satellite (MetOp) platforms offer a unique source of information. In this paper, we present the first space-borne 1 km snow extent climatology for the Alpine region derived from AVHRR data over the period 1985–2011. The objective of this study is twofold: first, to generate a new set of cloud-free satellite snow products using a specific cloud gap-filling technique and second, to examine the spatiotemporal distribution of snow cover in the European Alps over the last 27 yr from the satellite perspective. For this purpose, snow parameters such as snow onset day, snow cover duration (SCD), melt-out date and the snow cover area percentage (SCA) were employed to analyze spatiotemporal variability of snow cover over the course of three decades. On the regional scale, significant trends were found toward a shorter SCD at lower elevations in the south-east and south-west. However, our results do not show any significant trends in the monthly mean SCA over the last 27 yr. This is in agreement with other research findings and may indicate a deceleration of the decreasing snow trend in the Alpine region. Furthermore, such data may provide spatially and temporally homogeneous snow information for comprehensive use in related research fields (i.e., hydrologic and economic applications) or can serve as a reference for climate models.

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Mapping ecosystem services (ES) and their trade-offs is a key requirement for informed decision making for land use planning and management of natural resources that aim to move towards increasing the sustainability of landscapes. The negotiations of the purposes of landscapes and the services they should provide are difficult as there is an increasing number of stakeholders active at different levels with a variety of interests present on one particular landscape.Traditionally, land cover data is at the basis for mapping and spatial monitoring of ecosystem services. In light of complex landscapes it is however questionable whether land cover per se and as a spatial base unit is suitable for monitoring and management at the meso-scale. Often the characteristics of a landscape are defined by prevalence, composition and specific spatial and temporal patterns of different land cover types. The spatial delineation of shifting cultivation agriculture represents a prominent example of a land use system with its different land use intensities that requires alternative methodologies that go beyond the common remote sensing approaches of pixel-based land cover analysis due to the spatial and temporal dynamics of rotating cultivated and fallow fields.Against this background we advocate that adopting a landscape perspective to spatial planning and decision making offers new space for negotiation and collaboration, taking into account the needs of local resource users, and of the global community. For this purpose we introduce landscape mosaicsdefined as new spatial unit describing generalized land use types. Landscape mosaics have allowed us to chart different land use systems and land use intensities and permitted us to delineate changes in these land use systems based on changes of external claims on these landscapes. The underlying idea behindthe landscape mosaics is to use land cover data typically derived from remote sensing data and to analyse and classify spatial patterns of this land cover data using a moving window approach. We developed the landscape mosaics approach in tropical, forest dominated landscapesparticularly shifting cultivation areas and present examples ofour work from northern Laos, eastern Madagascarand Yunnan Province in China.

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Temporal dynamics create unique and often ephemeral conditions that can influence soil microbial biogeography at different spatial scales. This study investigated the relation between decimeter to meter spatial variability of soil microbial community structure, plant diversity, and soil properties at six dates from April through November. We also explored the robustness of these interactions over time. An historically unfertilized, unplowed grassland in southwest Germany was selected to characterize how seasonal variability in the composition of plant communities and substrate quality changed the biogeography of soil microorganisms at the plot scale (10 m x 10 m). Microbial community spatial structure was positively correlated with the local environment, i.e. physical and chemical soil properties, in spring and autumn, while the density and diversity of plants had an additional effect in the summer period. Spatial relationships among plant and microbial communities were detected only in the early summer and autumn periods when aboveground biomass increase was most rapid and its influence on soil microbial communities was greatest due to increased demand by plants for nutrients. Individual properties exhibited varying degrees of spatial structure over the season. Differential responses of Gram positive and Gram negative bacterial communities to seasonal shifts in soil nutrients were detected. We concluded that spatial distribution patterns of soil microorganisms change over a season and that chemical soil properties are more important controlling factors than plant density and diversity. Finer spatial resolution, such as the mm to cm scale, as well as taxonomic resolution of microbial groups, could help determine the importance of plant species density, composition, and growth stage in shaping microbial community composition and spatial patterns. (C) 2014 The Authors. Published by Elsevier Ltd. All rights reserved.

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As atmospheric emissions of S have declined in the Northern Hemisphere, there has been an expectation of increased pH and alkalinity in streams believed to have been acidified by excess S and N. Many streams and lakes have not recovered. Evidence from East Bear Brook in Maine, USA and modelling with the groundwater acid-base model MAGIC (Cosby et al. 1985a,b) indicate that seasonal and yearly variations in soil PCO2 are adequate to enhance or even reverse acid-base (alkalinity) changes anticipated from modest decreases of SO4 in surface waters. Alkalinity is generated in the soil by exchange of H+ from dissociation of H2CO3, which in turn is derived from the dissolving of soil CO2. The variation in soil PCO2 produces an alkalinity variation of up to 15 mu eq L-1 in stream water. Detecting and relating increases in alkalinity to decreases in stream SO4 are significantly more difficult in the short term because of this effect. For example, modelled alkalinity recovery at Bear Brook due to a decline of 20 mu eq SO4 L-1 in soil solution is compensated by a decline from 0.4 to 0.2% for soil air PCO2. This compensation ability decays over time as base saturation declines. Variable PCO2 has less effect in more acidic soils. Short-term decreases of PCO2 below the long-term average value produce short-term decreases in alkalinity, whereas short-term increases in PCO2 produce shortterm alkalization. Trend analysis for detecting recovery of streams and lakes from acidification after reduced atmospheric emissions will require a longer monitoring period for statistical significance than previously appreciated.

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The European Territorial Cohesion Policy has been the subject of numerous debates in recent years. Most contributions focus on understanding the term itself and figuring out what is behind it, or arguing for or against a stronger formal competence of the European Union in this field. This article will leave out these aspects and pay attention to (undefined and legally non-binding) conceptual elements of territorial cohesion, focusing on the challenge of linking it within spatial policies and organising the relations. Therefore, the theoretical approach of Cultural Theory and its concept of clumsy solution are applied to overcome the dilemma of typical dichotomies by adding a third and a fourth (but not a fifth) perspective. In doing so, normative contradictions between different rational approaches can be revealed, explained and approached with the concept of ‘clumsy solutions’. This contribution aims at discussing how this theoretical approach helps us explain and frame a coalition between the Territorial Cohesion Policy and spatial policies. This approach contributes to finding the best way of linking and organising policies, although the solution might be clumsy according to the different rationalities involved.

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The seasonal and annual representativeness of ionic aerosol proxies (among others, calcium, sodium, ammonium and nitrate) in various firn cores in the vicinity of the NEEM drill site in northwest Greenland have been assessed. Seasonal representativeness is very high as one core explains more than 60 % of the variability within the area. The inter-annual representativeness, however, can be substantially lower (depending on the species) making replicate coring indispensable to derive the atmospheric variability of aerosol species. A single core at the NEEM site records only 30 % of the inter-annual atmospheric variability in some species, while five replicate cores are already needed to cover approximately 70 % of the inter-annual atmospheric variability in all species. The spatial representativeness is very high within 60 cm, rapidly decorrelates within 10 m but does not diminish further within 3 km. We attribute this to wind reworking of the snow pack leading to sastrugi formation. Due to the high resolution and seasonal representativeness of the records we can derive accurate seasonalities of the measured species for modern (AD 1990–2010) times as well as for pre-industrial (AD 1623–1750) times. Sodium and calcium show similar seasonality (peaking in February and March respectively) for modern and pre-industrial times, whereas ammonium and nitrate are influenced by anthro pogenic activities. Nitrate and ammonium both peak in May during modern times, whereas during pre-industrial times ammonium peaked during July–August and nitrate during June–July.

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The time variable Earth’s gravity field contains information about the mass transport within the system Earth, i.e., the relationship between mass variations in the atmosphere, oceans, land hydrology, and ice sheets. For many years, satellite laser ranging (SLR) observations to geodetic satellites have provided valuable information of the low-degree coefficients of the Earth’s gravity field. Today, the Gravity Recovery and Climate Experiment (GRACE) mission is the major source of information for the time variable field of a high spatial resolution. We recover the low-degree coefficients of the time variable Earth’s gravity field using SLR observations up to nine geodetic satellites: LAGEOS-1, LAGEOS-2, Starlette, Stella, AJISAI, LARES, Larets, BLITS, and Beacon-C. We estimate monthly gravity field coefficients up to degree and order 10/10 for the time span 2003–2013 and we compare the results with the GRACE-derived gravity field coefficients. We show that not only degree-2 gravity field coefficients can be well determined from SLR, but also other coefficients up to degree 10 using the combination of short 1-day arcs for low orbiting satellites and 10-day arcs for LAGEOS-1/2. In this way, LAGEOS-1/2 allow recovering zonal terms, which are associated with long-term satellite orbit perturbations, whereas the tesseral and sectorial terms benefit most from low orbiting satellites, whose orbit modeling deficiencies are minimized due to short 1-day arcs. The amplitudes of the annual signal in the low-degree gravity field coefficients derived from SLR agree with GRACE K-band results at a level of 77 %. This implies that SLR has a great potential to fill the gap between the current GRACE and the future GRACE Follow-On mission for recovering of the seasonal variations and secular trends of the longest wavelengths in gravity field, which are associated with the large-scale mass transport in the system Earth.

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Mayer H. Segmentation and segregation patterns of women-owned high-tech firms in four metropolitan regions in the United States, Regional Studies. The number of women starting and owning a business has increased dramatically and female entrepreneurs are entering non-traditional sectors such as high technology, construction and manufacturing. This paper investigates the trends in high-tech entrepreneurship by women in four US metropolitan regions (Silicon Valley, California; Boston, Massachusetts; Washington, DC; and Portland, Oregon). The research examines the sectoral and spatial segmentation patterns of women-owned high-tech firms. Although women are entering non-traditional sectors, the research finds that women entrepreneurs tend to own businesses in female-typed high-tech sectors. In established high-tech regions like Silicon Valley and Boston, male-typed and female-typed women-owned high-tech firms differ significantly in terms of sectoral and spatial segmentation regardless of firm age. While differences between male-typed and female-typed firms are not significant at the regional level for Washington, DC, the analysis shows significant intra-metropolitan differences for the female-typed high-tech firms. The paper concludes that sectoral and spatial segmentation are powerful dynamics that shape business ownership by women in high technology.

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New pollen based reconstructions of summer (May-to-August) and winter (December-to-February) temperatures between 15 and 8 ka BP along a S-N transect in the Baltic-Belarus (BB) area display trends in temporal and spatial changes in climate variability. These results are completed by two chironomid-based July mean temperature reconstructions. The magnitude of change compared with modern temperatures was more prominent in the northern part of BB area. The 4 C degrees winter and 2 C degrees summer warming at the start of GI-1 was delayed in the BB area and Lateglacial maximum temperatures were reached at ca 13.6 ka BP, being 4 C degrees colder than the modern mean. The Younger Dryas cooling in the area was 5 C degrees colder than present, as inferred by all proxies. In addition, our analyses show an early Holocene divergence in winter temperature trends with modern values reaching 1 ka earlier (10 ka BP) in southern BB compared to the northern part of the region (9 ka BP).

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Characterization of spatial and temporal variation in grassland productivity and nutrition is crucial for a comprehensive understanding of ecosystem function. Although within-site heterogeneity in soil and plant properties has been shown to be relevant for plant community stability, spatiotemporal variability in these factors is still understudied in temperate grasslands. Our study aimed to detect if soil characteristics and plant diversity could explain observed small-scale spatial and temporal variability in grassland productivity, biomass nutrient concentrations, and nutrient limitation. Therefore, we sampled 360 plots of 20 cm × 20 cm each at six consecutive dates in an unfertilized grassland in Southern Germany. Nutrient limitation was estimated using nutrient ratios in plant biomass. Absolute values of, and spatial variability in, productivity, biomass nutrient concentrations, and nutrient limitation were strongly associated with sampling date. In April, spatial heterogeneity was high and most plots showed phosphorous deficiency, while later in the season nitrogen was the major limiting nutrient. Additionally, a small significant positive association between plant diversity and biomass phosphorus concentrations was observed, but should be tested in more detail. We discuss how low biological activity e.g., of soil microbial organisms might have influenced observed heterogeneity of plant nutrition in early spring in combination with reduced active acquisition of soil resources by plants. These early-season conditions are particularly relevant for future studies as they differ substantially from more thoroughly studied later season conditions. Our study underlines the importance of considering small spatial scales and temporal variability to better elucidate mechanisms of ecosystem functioning and plant community assembly.

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Beginning in the late 1980s, lobster (Homarus americanus) landings for the state of Maine and the Bay of Fundy increased to levels more than three times their previous 20-year means. Reduced predation may have permitted the expansion of lobsters into previously inhospitable territory, but we argue that in this region the spatial patterns of recruitment and the abundance of lobsters are substantially driven by events governing the earliest life history stages, including the abundance and distribution of planktonic stages and their initial settlement as Young-of-Year (YOY) lobsters. Settlement densities appear to be strongly driven by abundance of the pelagic postlarvae. Postlarvae and YOY show large-scale spatial patterns commensurate with coastal circulation, but also multi-year trends in abundance and abrupt shifts in abundance and spatial patterns that signal strong environmental forcing. The extent of the coastal shelf that defines the initial settlement grounds for lobsters is important to future population modeling. We address one part of this definition by examining patterns of settlement with depth, and discuss a modeling framework for the full life history of lobsters in the Gulf of Maine.

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This study was a descriptive analysis of 437 influenza A positive inpatients and outpatients during the five month period between September, 2009 and January, 2010. The objective of the study was to describe the epidemiological trends of the total influenza A positive population and more specifically the clinical features of patients hospitalized with influenza A at St. Luke's Episcopal Hospital in Houston, Texas from September 2009 through January 2010. Eligible cases were included if they tested positive for influenza A test using the rapid antigen test and/or rRT-PCR. Hospitalized cases were included based on the laboratory confirmation of influenza A as well as hospital admission for at least 24 hours. Data was collected from medical record abstraction and included patient demographics, clinical history and history of chronic disease. Clinical findings in the differential diagnosis that led to laboratory-confirmation of influenza A as well as course of treatment during the hospital admission were summarized. Finally, co-morbid conditions charted during the hospital visit were reviewed and evaluated for associations with influenza A complications. During the study period, forty-eight patients were included in the study of which 27 tested positive for the H1N1 subtype. Females were more likely to be hospitalized than men. The median age of all patients admitted to St. Luke's Episcopal Hospital with influenza A was 42. The distribution for admitted cases was 15 White, 15 Black, and 18 Hispanic. Patients with co-morbid disease constituted 81% of the admissions for Influenza A. The presence of an underlying medical condition remains a risk factor for both seasonal and H1N1 influenza. Although respiratory conditions such as asthma and COPD are commonly associated with complications of seasonal influenza, patients with metabolic disorders such as kidney disease and/or diabetes were admitted more frequently (58%) during the study period. The patients in the study also of a much younger age than the age that is usually associated with complications of influenza infection, i.e. no patients greater than 65 years of age were admitted with a diagnosis of influenza A. Lower infection rates among elderly populations were similarly reported in other studies of influenza during the same time period. Older patient populations may benefit from antibodies to previous H1N1 strains that have circulated during the twentieth century, whereas younger age groups lack these exposures.^

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Cardiovascular disease (CVD) is highly preventable, yet it is a leading cause of death among women in Texas. The primary goals of this research were to examine past and current trends of CVD, as well as identify whether there is an association between the insurance coverage and mortality from CVD among women aged 60–65 in Texas between 2000 and 2011. ^ The systematic review of the research is based on the guidelines and recommendations set by the Centre for Reviews and Dissemination for conducting reviews in health care. Over 47 citations of peer-reviewed articles from Ovid MEDLINE and PubMed databases and five websites were identified, of which 7 studies met inclusion criteria for the first systematic review to examine the trends of CVD in Texas. Ten citations of peer-reviewed articles from Ovid MEDLINE and PubMed databases and five web sites were reviewed for the second systematic review (to study the association between insurance coverage and cardiovascular health among Texas women 60–64 years of age), of which 3 studies met inclusion criteria and were included in the research. The results of the study highlighted key gaps in the existing literature and important areas for the further research, as well as determined directions for future public health CVD prevention programs in Texas. ^ Based on the conducted research, the major determinants of premature mortality among women attributed to cardiovascular disease are based on individual level characteristics, more specifically sex, age, race/ethnicity, and education. The results indicate that African American and non-Hispanic white women are more likely to have higher CVD mortality rates than Hispanic women due to higher prevalence of cardiac risk factors. The data also shows higher levels of mortality from CVD in the southeastern United States, with Texas ranking as the third state with the highest prevalence of CVD among women. According to the Texas Department of State Health Services, there are approximately 56,000 deaths caused by CVD annually in Texas, which represents about one death every ten minutes. Coronary artery disease and stroke were the causes of 31.2 percent of all female deaths in Texas in 2009, meaning that approximately 68 women die from any form of cardiac disease in Texas each day. ^ The data of the reviewed studies indicate that women' lack of health insurance was significantly associated with a higher prevalence of cardiovascular disease. The uninsured women were more likely to be unaware of their risk factors and more likely to have undiagnosed diabetes—a co-morbidity factor of CVD. One of the studies also reports strong correlation between state rates of uninsured and lower rates of preventive care. Given these strong correlations, those who were chronically uninsured were at a higher risk of mortality than the insured, due to prolonged periods of time without basic access to preventive and medical care. ^ Suggested recommendations to decrease CVD mortality rates in Texas are consistent with the existing literature and include state policy development that addresses elimination of health disparities, consideration of potential benefits of universal health coverage by the legislative policymakers, and maintenance of solid partnerships between public health agencies and hospitals to educate on, diagnose, and treat CVD among the female population in Texas. ^

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Scholars have found that socioeconomic status was one of the key factors that influenced early-stage lung cancer incidence rates in a variety of regions. This thesis examined the association between median household income and lung cancer incidence rates in Texas counties. A total of 254 individual counties in Texas with corresponding lung cancer incidence rates from 2004 to 2008 and median household incomes in 2006 were collected from the National Cancer Institute Surveillance System. A simple linear model and spatial linear models with two structures, Simultaneous Autoregressive Structure (SAR) and Conditional Autoregressive Structure (CAR), were used to link median household income and lung cancer incidence rates in Texas. The residuals of the spatial linear models were analyzed with Moran's I and Geary's C statistics, and the statistical results were used to detect similar lung cancer incidence rate clusters and disease patterns in Texas.^

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A population based ecological study was conducted to identify areas with a high number of TB and HIV new diagnoses in Harris County, Texas from 2009 through 2010 by applying Geographic Information Systems to determine whether distinguished spatial patterns exist at the census tract level through the use of exploratory mapping. As of 2010, Texas has the fourth highest occurrence of new diagnoses of HIV/AIDS and TB.[31] The Texas Department of State Health Services (DSHS) has identified HIV infected persons as a high risk population for TB in Harris County.[29] In order to explore this relationship further, GIS was utilized to identify spatial trends. ^ The specific aims were to map TB and HIV new diagnoses rates and spatially identify hotspots and high value clusters at the census tract level. The potential association between HIV and TB was analyzed using spatial autocorrelation and linear regression analysis. The spatial statistics used were ArcGIS 9.3 Hotspot Analysis and Cluster and Outlier Analysis. Spatial autocorrelation was determined through Global Moran's I and linear regression analysis. ^ Hotspots and clusters of TB and HIV are located within the same spatial areas of Harris County. The areas with high value clusters and hotspots for each infection are located within the central downtown area of the city of Houston. There is an additional hotspot area of TB located directly north of I-10 and a hotspot area of HIV northeast of Interstate 610. ^ The Moran's I Index of 0.17 (Z score = 3.6 standard deviations, p-value = 0.01) suggests that TB is statistically clustered with a less than 1% chance that this pattern is due to random chance. However, there were a high number of features with no neighbors which may invalidate the statistical properties of the test. Linear regression analysis indicated that HIV new diagnoses rates (β=−0.006, SE=0.147, p=0.970) and census tracts (β=0.000, SE=0.000, p=0.866) were not significant predictors of TB new diagnoses rates. ^ Mapping products indicate that census tracts with overlapping hotspots and high value clusters of TB and HIV should be a targeted focus for prevention efforts, most particularly within central Harris County. While the statistical association was not confirmed, evidence suggests that there is a relationship between HIV and TB within this two year period.^