954 resultados para Tunisia--Maps


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Abstract Hydrocarbons in surface sediments were studied quantitatively and qualitatively in 18 stations along the coastline of Gabes Gulf in Tunisia. The results show that the total hydrocarbon levels vary along a wide range from 90 to 1,800 ppm. The GC-MS profiles of aliphatic hydrocarbons vary according to the stations and show that the hydrocarbons were derived from various sources. A special feature prevalent in several stations was identified: aliphatic hydrocarbons with distinctive chemical features. This includes a high abundance of even-numbered n-alkanes (n-C14 - n-C26, maximizing at n-C18, n-C20 and n-C22) and n-alk-1-enes (n-C14:1 - n-C24:1, maximizing at n-C16:1, n-C18:1, n-C20:1 and n-C22:1). This unusual predominance of even-numbered n-alkanes/alkenes is reported for the first time in the Gulf of Gabes and it thus contributes to the information on the rare occurrence of such distributions in the geosphere.

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This study projects land cover probabilities under climate change for corn (maize), soybeans, spring and winter wheat, winter wheat-soybean double cropping, cotton, grassland and forest across 16 central U.S. states at a high spatial resolution, while also taking into account the influence of soil characteristics and topography. The scenarios span three oceanic-atmospheric global circulation models, three Representative Concentration Pathways, and three time periods (2040, 2070, 2100). As climate change intensifies, the suitable area for all six crops display large northward shifts. Total suitable area for spring wheat, followed by corn and soybeans, diminish. Suitable area for winter wheat and for winter wheat-soybean double-cropping expand northward, while cotton suitability migrates to new, more northerly, locations. Suitability for forest intensifies in the south while yielding to crops in the north; grassland intensifies in the western Great Plains as crop suitability diminishes. To maintain current broad geographic patterns of land use, large changes in the thermal response of crops such as corn would be required. A transition from corn-soybean to winter wheat-soybean doubling cropping is an alternative adaptation.

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Species distribution models (SDM) predict species occurrence based on statistical relationships with environmental conditions. The R-package biomod2 which includes 10 different SDM techniques and 10 different evaluation methods was used in this study. Macroalgae are the main biomass producers in Potter Cove, King George Island (Isla 25 de Mayo), Antarctica, and they are sensitive to climate change factors such as suspended particulate matter (SPM). Macroalgae presence and absence data were used to test SDMs suitability and, simultaneously, to assess the environmental response of macroalgae as well as to model four scenarios of distribution shifts by varying SPM conditions due to climate change. According to the averaged evaluation scores of Relative Operating Characteristics (ROC) and True scale statistics (TSS) by models, those methods based on a multitude of decision trees such as Random Forest and Classification Tree Analysis, reached the highest predictive power followed by generalized boosted models (GBM) and maximum-entropy approaches (Maxent). The final ensemble model used 135 of 200 calculated models (TSS > 0.7) and identified hard substrate and SPM as the most influencing parameters followed by distance to glacier, total organic carbon (TOC), bathymetry and slope. The climate change scenarios show an invasive reaction of the macroalgae in case of less SPM and a retreat of the macroalgae in case of higher assumed SPM values.

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[Vol. 1]: Report, tables, diagrams, appendices.--[Vol. 2]: Maps.

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Loose-leaf; reproduced from type-written copy.

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Reproduced from type-written copy.

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Reproduced from type-written copy.

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"The expansion of a course of lectures ... before graduate students of the Univesity of Virginia."--Foreword.

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Mode of access: Internet.

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Mode of access: Internet.

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"Classification, cataloging, and care of maps": p. 282-295; "Tentative map classification outline by subject": p. 297-308; "Map classification outline by areas": p. 309-311.