3 resultados para Climatic classification


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The state of research on the evolution of marine bivalve taxonomic diversity of the Mediterranean Pliocene is analysed. The following assertions are discussed: 1) The Early Pliocene malacofauna is characterized by a high number of warm-water taxa and a high taxonomic diversity with respect to that of the present time. 2) The first appreciable extinction event in the Mediterranean Pliocene approximates or just follows the FO of Globorotalia bononiensis. 3) The second appreciable extinction event is between the LAD of Discoaster tamalis and the LAD of Discoaster surculus . 4) A third minor extinction event is penecontemporaneous with the FO of Globorotalia inflaia. Taking into account the available data on the Pliocene extinction events it has been possible to distinguish 4 different molluscan units with different climatic-oceanographic significance.

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Climatic changes that affected the Northeastern Atlantic frontage are analyzed on the basis of the evolution of faunas and floras from the late Oligocene onwards. The study deals with calcareous nannoplankton, marine micro- and macrofaunas, some terrestrial vertebrates and vegetal assemblages. The climate, first tropical, underwent a progressive cooling (North-South thermic gradient). Notable climatic deteriorations (withdrawal towards the South or disappearance of taxa indicative of warm climate and appearance of "cold" taxa) are evidenced mainly during the Middle Miocene and the late Pliocene. Faunas and floras of modern pattern have regained, after the Pleistocene glaciations, a new climatic ranging of a temperate type in the northern part.

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Grasslands in semi-arid regions, like Mongolian steppes, are facing desertification and degradation processes, due to climate change. Mongolia’s main economic activity consists on an extensive livestock production and, therefore, it is a concerning matter for the decision makers. Remote sensing and Geographic Information Systems provide the tools for advanced ecosystem management and have been widely used for monitoring and management of pasture resources. This study investigates which is the higher thematic detail that is possible to achieve through remote sensing, to map the steppe vegetation, using medium resolution earth observation imagery in three districts (soums) of Mongolia: Dzag, Buutsagaan and Khureemaral. After considering different thematic levels of detail for classifying the steppe vegetation, the existent pasture types within the steppe were chosen to be mapped. In order to investigate which combination of data sets yields the best results and which classification algorithm is more suitable for incorporating these data sets, a comparison between different classification methods were tested for the study area. Sixteen classifications were performed using different combinations of estimators, Landsat-8 (spectral bands and Landsat-8 NDVI-derived) and geophysical data (elevation, mean annual precipitation and mean annual temperature) using two classification algorithms, maximum likelihood and decision tree. Results showed that the best performing model was the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), using the decision tree. For maximum likelihood, the model that incorporated Landsat-8 bands with mean annual precipitation (Model 5) and the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), achieved the higher accuracies for this algorithm. The decision tree models consistently outperformed the maximum likelihood ones.