Petit âge glaciaire

Résumé

Le petit âge glaciaire (parfois abrégé en PAG) est une période climatique froide principalement localisée sur l'Atlantique nord ayant approximativement eu lieu entre le début du s. Elle est caractérisée par une série d'hivers longs et froids. Elle porte plusieurs noms, dont « petit âge de glace », « petite période glaciaire » ou encore « petite glaciation ». Elle se caractérise par des périodes de crues glaciaires, auxquelles correspondent plusieurs minimums de températures moyennes très nets. Elle succède à l'optimum climatique médiéval (OCM), période plus chaude. Ce terme est introduit de manière informelle en 1939 par le géologue François E. Matthes pour désigner la période qu'il venait de vivre à la fin du . Cette expression « petit âge glaciaire » est aussi maintenant attribuée à la période qui a suivi les trois éruptions volcaniques massives de 536, 541 et 547 à l'échelle planétaire, éruptions mises en évidence au début du . Origine et persistance Paramèt

Source officielle

https://fr.wikipedia.org/wiki/Petit_%C3%A2ge_glaciaire

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Late Holocene climate: Natural or anthropogenic?

Jed Oliver Kaplan

For more than a decade, scientists have argued about the warmth of the current interglaciation. Was the warmth of the preindustrial late Holocene natural in origin, the result of orbital changes that had not yet driven the system into a new glacial state? Or was it in considerable degree the result of humans intervening in the climate system through greenhouse gas emissions from early agriculture? Here we summarize new evidence that moves this debate forward by testing both hypotheses. By comparing late Holocene responses to those that occurred during previous interglaciations (in section 2), we assess whether the late Holocene responses look different (and thus anthropogenic) or similar (and thus natural). This comparison reveals anomalous (anthropogenic) signals. In section 3, we review paleoecological and archaeological syntheses that provide ground truth evidence on early anthropogenic releases of greenhouse gases. The available data document large early anthropogenic emissions consistent with the anthropogenic ice core anomalies, but more information is needed to constrain their size. A final section compares natural and anthropogenic interpretations of the C-13 trend in ice core CO2.

Amer Geophysical Union2016

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Combined analysis of sedimentary facies, geochemistry and pollen from lake sediment records, and sedimentological and palynological studies from slope deposits allow the characterization of vegetation and lake level status during the Last Glacial (LGM) in the central Ebro valley (NE Spain). These records show the presence of phases of increased effective moisture, while regional vegetation was dominated by steppe species. The longest lake record comes from La Salineta, one of the saline lakes in the Los Monegros area; the other lake sequence comes from a sinkhole in the Gállego River floodplain. The slope deposit from Valmadrid is the only periglacial deposit found in the central Ebro valley. Our data indicate that, at least for some intervals during full glacial times, when cold steppe vegetation dominated the region, some lakes experienced more positive water balance than today, and run-off was also high. The data are coherent with the hypothesis that, at least for some periods, the ice-age climate of the western Mediterranean was characterized by cold winters, with relatively higher effective moisture (precipitation minus evaporation ratio) and summer droughts. Increased flow from the Pyrenean rivers during the early deglaciation could also have played a significant role in the paleohydrological cycle in the central Ebro valley. However, La Salineta records also show evidence for arid periods during glacial times, indicating the complex evolution of hydrology and moisture availability in the central Ebro valley during the LGM.

2004

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Multi-scale landscape genomic models

Kevin Leempoel

Environmental heterogeneity is one of the main actors of biodiversity and species adaptation as it exerts a selective pressure on observable characteristics of living organisms. Consequently, local adaptation favours certain genetic variants and, by doing so, leaves a footprint in the genetic heritage across populations. The identification of these adaptive genetic variations is the main objective of landscape genomics and allows, among other things, to study the role of specific regions of the genome in evolutionary processes. Landscape genomics studies also provide essential information for species conservation and for the prediction of migrations due to environmental changes. To identify these adaptations to the environment, it is necessary to define a study area where the populations are sampled. However, defining the scale of the study area is not a trivial task. In fact, whether the work is carried out at a local or at a broad scale determines the relevance of environmental factors and the type of signature of selection that will be observed. In addition, the concept of scale in ecology takes into account not only the extent of the study area but also the pattern and density of the geographic distribution of observations, and the spatial resolution of predictors (environmental variables), which is intrinsically linked to the extent. However, a priori indications about the relevance of any resolution over another are rare in the literature and it is therefore essential to question this issue. In this thesis, we propose a multi-scale landscape genomic framework to identify signatures of adaptation to the environment. This multidisciplinary framework lies at the interface between geographic information systems, spatial analysis, environmental modelling, population genetics and computer science. Specifically, we focus on the relevance of variables derived from Digital Elevation Models (DEMs) and on the application of multi-scale analysis aiming to detect signatures of selection. We applied this analytical framework to three case studies, comprising four species: Biscutella laevigata sampled at a local scale, Plantago major at a regional scale, sheep and goats at a large scale. In particular, the case of B. laevigata allowed us to evaluate the role of topographic features based on Very High Resolution DEMs and to include DEM-derived variables as predictors in association models to study the adaptation of species to their local environment. On the other hand, the case of Moroccan sheep and goats permitted to include for the first time whole genome sequence data within landscape genomic models. The results revealed several important findings. We showed that micro-climate variability is highly dependent on topographic factors at a local scale and that therefore, DEMs are relevant for understanding species adaptation to a mountainous environment. We also demonstrated that it is essential to consider the scale of spatial representativeness by assessing DEM-derived variables at various spatial resolutions. Indeed, two out of three case studies showed that the models involving topographic variables were sensitive to changes in resolution. In summary, we used several landscape genetics approaches to understand the role of environmental factors in the local adaptation of various species. Our findings mainly provide an important contribution to the understanding and use of scale in landscape genomics, also useful in landscape ecology.

EPFL2015

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Multi-scale landscape genomic models

Kevin Leempoel

EPFL2015