982 resultados para gallery forest fragments


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Background: A previous review showed that high stress increases the risk of occupational injury by three- to five-fold. However, most of the prior studies have relied on short follow-ups. In this prospective cohort study we examined the effect of stress on recorded hospitalised injuries in an 8-year follow-up.
Methods: A total of 16,385 employees of a Finnish forest company responded to the questionnaire. Perceived stress was measured with a validated single-item measure, and analysed in relation recorded hospitalised injuries from 1986 to 2008. We used Cox proportional hazard regression models to examine the prospective associations between work stress, injuries and confounding factors.
Results: Highly stressed participants were approximately 40% more likely to be hospitalised due to injury over the follow-up period than participants with low stress. This association remained significant after adjustment for age, gender, marital status, occupational status, educational level, and physical work environment.
Conclusions: High stress is associated with an increased risk of severe injury.

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The emerging tephrostratigraphy of NW Europe spanning the last termination (ca. 15–9 ka) provides the potential for synchronizing marine, ice-core and terrestrial records, but is currently compromised by stratigraphic complications, geochemical ambiguity and imprecise age estimates for some layers. Here we present new tephrostratigraphic, radiocarbon and chironomid-based
palaeotemperature data from Abernethy Forest, Scotland, that refine the ages and stratigraphic positions of the Borrobol and Penifiler tephras. The Borrobol Tephra (14.14–13.95 cal ka BP) was deposited in a relatively warm period equated with Greenland Interstadial sub-stage GI-1e. The younger Penifiler Tephra (14.09–13.65 cal ka BP) is closely associated with a cold oscillation equated with GI-
1d. We also present evidence for a previously undescribed tephra layer that has a major-element chemical signature identical to the Vedde Ash. It is associated with the warming trend at the end of the Younger Dryas, and dates between 11.79 and 11.20 cal ka BP.

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Fragments of chelonian carapace and plastral dermal plates are well-represented from archaeological sites in the world's dry and wet tropics. However, although these bones are easily identified at an element level, few archaeological reports have explored the potential of using features of form and surface sculpturing as a way to refine that identification to genus or species. The ability to achieve such a refinement would benefit environmental and human subsistence strategy models alike. The objective of the current paper was to isolate recurrent and readily visible surface characteristics on the dermal plates from a selection of commonly occurring Southeast Asian hard- and soft-shelled turtles. Using these criteria, analysis is made of the chelonian assemblage from pre- and post-Last Glacial Maximum (LGM) cultural deposits in the West Mouth of Niah Cave. Copyright (C) 2009 John Wiley & Sons, Ltd.

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Recent research in Europe, Africa, and Southeast Asia suggests that we can no longer assume a direct and exclusive link between anatomically modern humans and behavioral modernity (the 'human revolution'), and assume that the presence of either one implies the presence of the other: discussions of the emergence of cultural complexity have to proceed with greater scrutiny of the evidence on a site-by-site basis to establish secure associations between the archaeology present there and the hominins who created it. This paper presents one such case study: Niah Cave in Sarawak on the island of Borneo, famous for the discovery in 1958 in the West Mouth of the Great Cave of a modern human skull, the 'Deep Skull,' controversially associated with radiocarbon dates of ca. 40,000 years before the present. A new chronostratigraphy has been developed through a re-investigation of the lithostratigraphy left by the earlier excavations, AMS-dating using three different comparative pre-treatments including ABOX of charcoal, and U-series using the Diffusion-Absorption model applied to fragments of bones from the Deep Skull itself. Stratigraphic reasons for earlier uncertainties about the antiquity of the skull are examined, and it is shown not to be an `intrusive' artifact. It was probably excavated from fluvial-pond-desiccation deposits that accumulated episodically in a shallow basin immediately behind the cave entrance lip, in a climate that ranged from times of comparative aridity with complete desiccation, to episodes of greater surface wetness, changes attributed to regional climatic fluctuations. Vegetation outside the cave varied significantly over time, including wet lowland forest, montane forest, savannah, and grassland. The new dates and the lithostratigraphy relate the Deep Skull to evidence of episodes of human activity that range in date from ca. 46,000 to ca. 34,000 years ago. Initial investigations of sediment scorching, pollen, palynomorphs, phytoliths, plant macrofossils, and starch grains recovered from existing exposures, and of vertebrates from the current and the earlier excavations, suggest that human foraging during these times was marked by habitat-tailored hunting technologies, the collection and processing of toxic plants for consumption, and, perhaps, the use of fire at some forest-edges. The Niah evidence demonstrates the sophisticated nature of the subsistence behavior developed by modern humans to exploit the tropical environments that they encountered in Southeast Asia, including rainforest. (c) 2006 Elsevier Ltd. All rights reserved.

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Artificial neural network (ANN) methods are used to predict forest characteristics. The data source is the Southeast Alaska (SEAK) Grid Inventory, a ground survey compiled by the USDA Forest Service at several thousand sites. The main objective of this article is to predict characteristics at unsurveyed locations between grid sites. A secondary objective is to evaluate the relative performance of different ANNs. Data from the grid sites are used to train six ANNs: multilayer perceptron, fuzzy ARTMAP, probabilistic, generalized regression, radial basis function, and learning vector quantization. A classification and regression tree method is used for comparison. Topographic variables are used to construct models: latitude and longitude coordinates, elevation, slope, and aspect. The models classify three forest characteristics: crown closure, species land cover, and tree size/structure. Models are constructed using n-fold cross-validation. Predictive accuracy is calculated using a method that accounts for the influence of misclassification as well as measuring correct classifications. The probabilistic and generalized regression networks are found to be the most accurate. The predictions of the ANN models are compared with a classification of the Tongass national forest in southeast Alaska based on the interpretation of satellite imagery and are found to be of similar accuracy.