10 resultados para climate oscillation

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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The role of Pleistocene glacial cycles in forming the contemporary genetic structure of organisms has been well studied in China with a particular focus on the Tibetan Plateau. However, China has a complex topography and diversity of local climates, and how glacial cycles may have shaped the subtropical and tropical biota of the region remains mostly unaddressed. To investigate the factors that affected the phylogeography and population history of a widely distributed and nondeciduous forest species, we analysed morphological characters, mitochondrial DNA sequences and nuclear microsatellite loci in the Silver Pheasant (Lophura nycthemera). In a pattern generally consistent with phenotypic clusters, but not nominal subspecies, deeply divergent mitochondrial lineages restricted to different geographic regions were detected. Coalescent simulations indicated that the time of main divergence events corresponded to major glacial periods in the Pleistocene and gene flow was only partially lowered by drainage barriers between some populations. Intraspecific cytonuclear discordance was revealed in mitochondrial lineages from Hainan Island and the Sichuan Basin with evidence of nuclear gene flow from neighbouring populations into the latter. Unexpectedly, hybridization was revealed in Yingjiang between the Silver Pheasant and Kalij Pheasant (Lophura leucomelanos) with wide genetic introgression at both the mtDNA and nuclear levels. Our results highlight a novel phylogeographic pattern in a subtropical area generated from the combined effects of climate oscillation, partial drainage barriers and interspecific hybridization. Cytonuclear discordance combined with morphological differentiation implies that complex historical factors shaped the divergence process in this biodiversity hot spot area of southern China.

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Impacts of low-latitude, explosive volcanic eruptions on climate and the carbon cycle are quantified by forcing a comprehensive, fully coupled carbon cycle-climate model with pulse-like stratospheric aerosol optical depth changes. The model represents the radiative and dynamical response of the climate system to volcanic eruptions and simulates a decrease of global and regional atmospheric surface temperature, regionally distinct changes in precipitation, a positive phase of the North Atlantic Oscillation, and a decrease in atmospheric CO2 after volcanic eruptions. The volcanic-induced cooling reduces overturning rates in tropical soils, which dominates over reduced litter input due to soil moisture decrease, resulting in higher land carbon inventories for several decades. The perturbation in the ocean carbon inventory changes sign from an initial weak carbon sink to a carbon source. Positive carbon and negative temperature anomalies in subsurface waters last up to several decades. The multi-decadal decrease in atmospheric CO2 yields a small additional radiative forcing that amplifies the cooling and perturbs the Earth System on longer time scales than the atmospheric residence time of volcanic aerosols. In addition, century-scale global warming simulations with and without volcanic eruptions over the historical period show that the ocean integrates volcanic radiative cooling and responds for different physical and biogeochemical parameters such as steric sea level or dissolved oxygen. Results from a suite of sensitivity simulations with different magnitudes of stratospheric aerosol optical depth changes and from global warming simulations show that the carbon cycle-climate sensitivity γ, expressed as change in atmospheric CO2 per unit change in global mean surface temperature, depends on the magnitude and temporal evolution of the perturbation, and time scale of interest. On decadal time scales, modeled γ is several times larger for a Pinatubo-like eruption than for the industrial period and for a high emission, 21st century scenario.

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A lacustrine sediment core from Fiddaun, western Ireland was studied to reconstruct summer temperature changes during the Weichselian Lateglacial. This site is located close to the Atlantic Ocean; and so is potentially sensitive to climatic changes associated with changes in ocean circulation. The record, comprising the end of the Weichselian Pleniglacial to the early Holocene, was analysed for fossil chironomids, lithology, and oxygen and carbon isotopes in the sedimentary carbonates. These proxies clearly show rapid warming at the onset of the Lateglacial Interstadial, relatively high summer temperatures during the Interstadial, pronounced cooling during the Younger Dryas, and subsequent warming at the transition to the Holocene. Chironomid-inferred mean July air temperatures for the Interstadial are ~12.5–14.5 °C, ~7.5 °C for the Younger Dryas, and ~15.0 °C for the early Holocene. Furthermore, this research provides evidence for at least two cold events during the Interstadial. These more moderate temperature oscillations can be correlated to Greenland Interstadial events 1b and 1d, on the basis of the age-depth model for the Fiddaun sequence. Based on multiple proxies, the first cold oscillation (GI-1d) was the more severe of the two in Ireland.

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The interface between climate and ecosystem structure and function is incompletely understood, partly because few ecological records start before the recent warming phase. Here, we analyse an exceptional 100-yr long record of the great tit (Parus major) population in Switzerland in relation to climate and habitat phenology. Using structural equation analysis, we demonstrate an uninterrupted cascade of significant influences of the large-scale atmospheric circulation (North-Atlantic Oscillation, NAO, and North-sea – Caspian Pattern, NCP) on habitat and breeding phenology, and further on fitness-relevant life history traits within great tit populations. We then apply the relationships of this analysis to reconstruct the circulation-driven component of fluctuations in great tit breeding phenology and productivity on the basis of new seasonal NAO and NCP indices back to 1500 AD. According to the structural equation model, the multi-decadal oscillation of the atmospheric circulation likely led to substantial variation in habitat phenology, productivity and consequently, tit population fluctuations with minima during the "Maunder Minimum" (∼ 1650–1720) and the Little Ice Age Type Event I (1810–1850). The warming since 1975 was not only related with a quick shift towards earlier breeding, but also with the highest productivity since 1500, and thus, the impact of the NAO and NCP has contributed to an unprecedented increase of the population. A verification of the structural equation model against two independent data series (1970–2000 and 1750–1900) corroborates that the retrospective model reliably depicts the major long-term NAO/NCP impact on ecosystem parameters. The results suggest a complex cascade of climate effects beginning at a global scale and ending at the level of individual life histories. This sheds light on how large-scale climate conditions substantially affect major life history parameters within a population, and thus influence key ecosystem parameters at the scale of centuries.

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The past 1500 years provide a valuable opportunity to study the response of the climate system to external forcings. However, the integration of paleoclimate proxies with climate modeling is critical to improving the understanding of climate dynamics. In this paper, a climate system model and proxy records are therefore used to study the role of natural and anthropogenic forcings in driving the global climate. The inverse and forward approaches to paleoclimate data–model comparison are applied, and sources of uncertainty are identified and discussed. In the first of two case studies, the climate model simulations are compared with multiproxy temperature reconstructions. Robust solar and volcanic signals are detected in Southern Hemisphere temperatures, with a possible volcanic signal detected in the Northern Hemisphere. The anthropogenic signal dominates during the industrial period. It is also found that seasonal and geographical biases may cause multiproxy reconstructions to overestimate the magnitude of the long-term preindustrial cooling trend. In the second case study, the model simulations are compared with a coral δ18O record from the central Pacific Ocean. It is found that greenhouse gases, solar irradiance, and volcanic eruptions all influence the mean state of the central Pacific, but there is no evidence that natural or anthropogenic forcings have any systematic impact on El Niño–Southern Oscillation. The proxy climate relationship is found to change over time, challenging the assumption of stationarity that underlies the interpretation of paleoclimate proxies. These case studies demonstrate the value of paleoclimate data–model comparison but also highlight the limitations of current techniques and demonstrate the need to develop alternative approaches.

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Chrysophyte cysts are recognized as powerful proxies of cold-season temperatures. In this paper we use the relationship between chrysophyte assemblages and the number of days below 4 °C (DB4 °C) in the epilimnion of a lake in northern Poland to develop a transfer function and to reconstruct winter severity in Poland for the last millennium. DB4 °C is a climate variable related to the length of the winter. Multivariate ordination techniques were used to study the distribution of chrysophytes from sediment traps of 37 low-land lakes distributed along a variety of environmental and climatic gradients in northern Poland. Of all the environmental variables measured, stepwise variable selection and individual Redundancy analyses (RDA) identified DB4 °C as the most important variable for chrysophytes, explaining a portion of variance independent of variables related to water chemistry (conductivity, chlorides, K, sulfates), which were also important. A quantitative transfer function was created to estimate DB4 °C from sedimentary assemblages using partial least square regression (PLS). The two-component model (PLS-2) had a coefficient of determination of View the MathML sourceRcross2 = 0.58, with root mean squared error of prediction (RMSEP, based on leave-one-out) of 3.41 days. The resulting transfer function was applied to an annually-varved sediment core from Lake Żabińskie, providing a new sub-decadal quantitative reconstruction of DB4 °C with high chronological accuracy for the period AD 1000–2010. During Medieval Times (AD 1180–1440) winters were generally shorter (warmer) except for a decade with very long and severe winters around AD 1260–1270 (following the AD 1258 volcanic eruption). The 16th and 17th centuries and the beginning of the 19th century experienced very long severe winters. Comparison with other European cold-season reconstructions and atmospheric indices for this region indicates that large parts of the winter variability (reconstructed DB4 °C) is due to the interplay between the oscillations of the zonal flow controlled by the North Atlantic Oscillation (NAO) and the influence of continental anticyclonic systems (Siberian High, East Atlantic/Western Russia pattern). Differences with other European records are attributed to geographic climatological differences between Poland and Western Europe (Low Countries, Alps). Striking correspondence between the combined volcanic and solar forcing and the DB4 °C reconstruction prior to the 20th century suggests that winter climate in Poland responds mostly to natural forced variability (volcanic and solar) and the influence of unforced variability is low.

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We analyse the variability of the probability distribution of daily wind speed in wintertime over Northern and Central Europe in a series of global and regional climate simulations covering the last centuries, and in reanalysis products covering approximately the last 60 years. The focus of the study lies on identifying the link of the variations in the wind speed distribution to the regional near-surface temperature, to the meridional temperature gradient and to the North Atlantic Oscillation. Our main result is that the link between the daily wind distribution and the regional climate drivers is strongly model dependent. The global models tend to behave similarly, although they show some discrepancies. The two regional models also tend to behave similarly to each other, but surprisingly the results derived from each regional model strongly deviates from the results derived from its driving global model. In addition, considering multi-centennial timescales, we find in two global simulations a long-term tendency for the probability distribution of daily wind speed to widen through the last centuries. The cause for this widening is likely the effect of the deforestation prescribed in these simulations. We conclude that no clear systematic relationship between the mean temperature, the temperature gradient and/or the North Atlantic Oscillation, with the daily wind speed statistics can be inferred from these simulations. The understand- ing of past and future changes in the distribution of wind speeds, and thus of wind speed extremes, will require a detailed analysis of the representation of the interaction between large-scale and small-scale dynamics.