985 resultados para Western Climate Initiative
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Geochemical and geochronological analyses of samples of surficial Acre Basin sediments and fossils indicate an extensive fluvial-lacustrine system, occupying this region, desiccated slowly during the last glacial cycle (LGC). This research documents direct evidence for aridity in western Amazonia during the LGC and is important in establishing boundary conditions for LGC climate models as well as in correlating marine and continental (LGC) climate conditions.
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The observation of non-random phylogenetic distribution of traits in communities provides evidence for niche-based community assembly. Environment may influence the phylogenetic structure of communities because traits determining how species respond to prevailing conditions can be phylogenetically conserved. In this study, we investigate the variation of butterfly species richness and of phylogenetic - and -diversities along temperature and plant species richness gradients. Our study indicates that butterfly richness is independently positively correlated to temperature and plant species richness in the study area. However, the variation of phylogenetic - and -diversities is only correlated to temperature. The significant phylogenetic clustering at high elevation suggests that cold temperature filters butterfly lineages, leading to communities mostly composed of closely related species adapted to those climatic conditions. These results suggest that in colder and more severe conditions at high elevations deterministic processes and not purely stochastic events drive the assemblage of butterfly communities.
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1 Insect pests, biological invasions and climate change are considered to representmajor threats to biodiversity, ecosystem functioning, agriculture and forestry.Deriving hypothesis of contemporary and/or future potential distributions of insectpests and invasive species is becoming an important tool for predicting the spatialstructure of potential threats.2 The western corn rootworm (WCR) Diabrotica virgifera virgifera LeConte is apest of maize in North America that has invaded Europe in recent years, resultingin economic costs in terms of maize yields in both continents. The present studyaimed to estimate the dynamics of potential areas of invasion by the WCR under aclimate change scenario in the Northern Hemisphere. The areas at risk under thisscenario were assessed by comparing, using complementary approaches, the spatialprojections of current and future areas of climatic favourability of the WCR. Spatialhypothesis were generated with respect to the presence records in the native rangeof the WCR and physiological thresholds from previous empirical studies.3 We used a previously developed protocol specifically designed to estimatethe climatic favourability of the WCR. We selected the most biologicallyrelevant climatic predictors and then used multidimensional envelope (MDE) andMahalanobis distances (MD) approaches to derive potential distributions for currentand future climatic conditions.4 The results obtained showed a northward advancement of the upper physiologicallimit as a result of climate change, which might increase the strength of outbreaksat higher latitudes. In addition, both MDE and MD outputs predict the stability ofclimatic favourability for the WCR in the core of the already invaded area in Europe,which suggests that this zone would continue to experience damage from this pestin Europe.
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Understanding the relative importance of historical and environmental processes in the structure and composition of communities is one of the longest quests in ecological research. Increasingly, researchers are relying on the functional and phylogenetic β-diversity of natural communities to provide concise explanations on the mechanistic basis of community assembly and the drivers of trait variation among species. The present study investigated how plant functional and phylogenetic β-diversity change along key environmental and spatial gradients in the Western Swiss Alps. Methods Using the quadratic diversity measure based on six functional traits: specific leaf area (SLA), leaf dry matter content (LDMC), plant height (H), leaf carbon content (C), leaf nitrogen content (N), and leaf carbon to nitrogen content (C/N) alongside a species-resolved phylogenetic tree, we relate variations in climate, spatial geographic, land use and soil gradients to plant functional and phylogenetic turnover in mountain communities of the Western Swiss Alps. Important findings Our study highlights two main points. First, climate and land use factors play an important role in mountain plant community turnover. Second, the overlap between plant functional and phylogenetic turnover along these gradients correlates with the low phylogenetic signal in traits, suggesting that in mountain landscapes, trait lability is likely an important factor in driving plant community assembly. Overall, we demonstrate the importance of climate and land use factors in plant functional and phylogenetic community turnover, and provide valuable complementary insights into understanding patterns of β-diversity along several ecological gradients.
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The late Early Cretaceous greenhouse climate has been studied intensively based on proxy data derived essentially from open marine archives. In contrast, information on continental climatic conditions and on the accompanying response of vegetation is relatively scarce, most notably owing to the stratigraphic uncertainties associated with many Lower Cretaceous terrestrial deposits. Here, we present a palynological record from Albian near-shore deposits of the Lusitanian Basin of W Portugal, which have been independently dated using Sr-isotope signals derived from low-Mg oyster shell calcite. Sr-87/Sr-86 values fluctuate between 0.707373 +/- 0.00002 and 0.707456 +/- 0.00003; absolute values and the overall stratigraphic trend match well with the global open marine seawater signature during Albian times. Based on the new Sr-isotope data, existing biostratigraphic assignments of the succession are corroborated and partly revised. Spore-pollen data provide information on the vegetation community structure and are flanked by sedimentological and clay mineralogical data used to infer the overall climatic conditions prevailing on the adjacent continent. Variations in the distribution of climate-sensitive pollen and spores indicate distinct changes in moisture availability across the studied succession with a pronounced increase in hygrophilous spores in late Early Albian times. Comparison with time-equivalent palynofloras from the Algarve Basin of southern Portugal shows pronounced differences in the xerophyte/hygrophyte ratio, interpreted to reflect the effect of a broad arid climate belt covering southern and southeastern Iberia during Early Albian times.
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Ecosystems are complex systems and changing one of their components can alter their whole functioning. Decomposition and biodiversity are two factors that play a role in this stability, and it is vital to study how these two factors are interrelated and how other factors, whether of human origin or not, can affect them. This study has tested different hypotheses regarding the effects of pesticides and invasive species on the biodiversity of the soil fauna and litter decomposition rate. Decomposition was measured using the litterbags technique. Our results indicate that pesticides had a negative effect on decomposition whereas invasive species increased decomposition rate. At the same time, the diversity of the soil biota was unaffected by either factor. These results allow us to better understand the response of important ecosystem functions to human‐induced alterations, in order to mitigate harmful effects or restore them wherever necessary.
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The Paratethys evolved as a marginal sea during the Alpine-Himalayan orogeny in the Oligo-Miocene. Sediments from the northern Alpine Molasse Basin, the Vienna, and the Pannonian Basins located in the western and central part of the Paratethys thus provide unique information on regional changes in climate and oceanography during a period of active Alpine uplift Oxygen isotope compositions of well-preserved phosphatic fossils recovered from the sediments support deposition under sub-tropical to warm-temperate climate with water temperatures of 14 to 28 degrees C for the Miocene. delta(18)O values of fossil shark teeth are similar to those reported for other Miocene marine sections and, using the best available estimates of their biostratigraphic age, show a variation until the end of the Badenian similar to that reported for composite global record. The (87)Sr/(86)Sr isotope ratios of the fossils follow the global Miocene seawater trend, albeit with a much larger scatter. The deviations of (87)Sr/(86)Sr in the samples from the well-constrained seawater curve are interpreted as due to local input of terrestrially-derived Sr. Contribution of local sources is also reflected in the epsilon(Nd) values, consistent with input from ancient crystalline rocks (e.g., Bohemian Massif and/or Mesozoic sediments with epsilon(Nd) < -9. On the other hand, there is evidence for input from areas with Neogene volcanism as suggested by samples with elevated epsilon(Nd) values >-7. Excluding samples showing local influence on the water column, an average epsilon(Nd) value of -7.9 +/- 0.5 may be inferred for the Miocene Paratethys. This value is indistinguishable from the epsilon(Nd) value of the contemporaneous Indian Ocean, supporting a dominant role of this ocean in the Western and Central Paratethys. (C) 2008 Elsevier B.V. All rights reserved.
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The thesis gives a general introduction about the topic include India, the spatial and temporal variation of the surface meteorological parameters are dealt in detail. The general pattern of the winds over the region in different seasons and the generation and movements of the thermally and dynamically originated local wind systems of Western Ghats region has been studied. The modification of the prevailing winds over region by the Palghat Gap and its effect on the mouth regions pf the gap is analysed in great depth. The thesis gives the information of climatic elements of the mountain region such as energy budgets, rainfall studies, evaporation and condensation and the variation in the heat fluxes over the region. The impact of orography is studied in a different approach. The type of hypothetical study gives more insight into the control of mountain on the distribution of meteorological parameter over the study region and helps to quantify the impact of the mountain in varying the weather climate of region. The detailed study of the hydro-meteorological aspects of the main river basins of the region also should be included to the climatic studies for the total understanding of the weather and climate over the region.
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Facing the double menace of climate change threats and water crisis, poor communities have now encountered ever more severe challenges in ensuring agricultural productivity and food security. Communities hence have to manage these challenges by adopting a comprehensive approach that not only enhances water resource management, but also adapts agricultural activities to climate variability. Implemented by the Global Environment Facility’s Small Grants Programme, the Community Water Initiative (CWI) has adopted a distinctive approach to support demand-driven, innovative, low cost and community-based water resource management for food security. Experiences from CWI showed that a comprehensive, locally adapted approach that integrates water resources management, poverty reduction, climate adaptation and community empowerment provides a good model for sustainable development in poor rural areas.
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The Asian monsoon system, including the western North Pacific (WNP), East Asian, and Indian monsoons, dominates the climate of the Asia-Indian Ocean-Pacific region, and plays a significant role in the global hydrological and energy cycles. The prediction of monsoons and associated climate features is a major challenge in seasonal time scale climate forecast. In this study, a comprehensive assessment of the interannual predictability of the WNP summer climate has been performed using the 1-month lead retrospective forecasts (hindcasts) of five state-of-the-art coupled models from ENSEMBLES for the period of 1960–2005. Spatial distribution of the temporal correlation coefficients shows that the interannual variation of precipitation is well predicted around the Maritime Continent and east of the Philippines. The high skills for the lower-tropospheric circulation and sea surface temperature (SST) spread over almost the whole WNP. These results indicate that the models in general successfully predict the interannual variation of the WNP summer climate. Two typical indices, the WNP summer precipitation index and the WNP lower-tropospheric circulation index (WNPMI), have been used to quantify the forecast skill. The correlation coefficient between five models’ multi-model ensemble (MME) mean prediction and observations for the WNP summer precipitation index reaches 0.66 during 1979–2005 while it is 0.68 for the WNPMI during 1960–2005. The WNPMI-regressed anomalies of lower-tropospheric winds, SSTs and precipitation are similar between observations and MME. Further analysis suggests that prediction reliability of the WNP summer climate mainly arises from the atmosphere–ocean interaction over the tropical Indian and the tropical Pacific Ocean, implying that continuing improvement in the representation of the air–sea interaction over these regions in CGCMs is a key for long-lead seasonal forecast over the WNP and East Asia. On the other hand, the prediction of the WNP summer climate anomalies exhibits a remarkable spread resulted from uncertainty in initial conditions. The summer anomalies related to the prediction spread, including the lower-tropospheric circulation, SST and precipitation anomalies, show a Pacific-Japan or East Asia-Pacific pattern in the meridional direction over the WNP. Our further investigations suggest that the WNPMI prediction spread arises mainly from the internal dynamics in air–sea interaction over the WNP and Indian Ocean, since the local relationships among the anomalous SST, circulation, and precipitation associated with the spread are similar to those associated with the interannual variation of the WNPMI in both observations and MME. However, the magnitudes of these anomalies related to the spread are weaker, ranging from one third to a half of those anomalies associated with the interannual variation of the WNPMI in MME over the tropical Indian Ocean and subtropical WNP. These results further support that the improvement in the representation of the air–sea interaction over the tropical Indian Ocean and subtropical WNP in CGCMs is a key for reducing the prediction spread and for improving the long-lead seasonal forecast over the WNP and East Asia.
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This study investigates the impacts of the transition of El Niño decaying phases on the western North Pacific anticyclone (WNPAC) anomalies in the subsequent summer with a coupled GCM. The modeling results suggest that the El Niños with short decaying phases lead to significant WNPAC anomalies in the following summer, which are contributed to mainly by the El Niños followed by La Niñas, in comparison with those not followed by La Niñas. In contrast, the long decaying cases are associated with the disappearance of WNPAC anomalies in the summer. These differences in the WNP circulation anomalies can be explained by the different configurations of simultaneous SSTs in the Indian Ocean and in the central and eastern tropical Pacific: positive SSTs in the former region and negative ones in the latter region constructively induce significant WNPAC anomalies for the short decaying cases, while the roles of positive SSTs in both regions for the long decaying cases work destructively and lead to weak WNP circulation anomalies. Further analysis indicates that the different lengths of El Niño decaying phases are predicted by the strength of Indian Ocean SSTs in the mature winter. The warmer wintertime Indian Ocean SSTs favor the anomalous easterly wind over the western and central equatorial Pacific in the subsequent summer, leading to a short decaying of El Niño. Thus, the strength of wintertime Indian Ocean SSTs is one of the important factors that affect the length of El Niño decaying phase and resultant WNPAC anomalies in the following summer.
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A statistical–dynamical regionalization approach is developed to assess possible changes in wind storm impacts. The method is applied to North Rhine-Westphalia (Western Germany) using the FOOT3DK mesoscale model for dynamical downscaling and ECHAM5/OM1 global circulation model climate projections. The method first classifies typical weather developments within the reanalysis period using K-means cluster algorithm. Most historical wind storms are associated with four weather developments (primary storm-clusters). Mesoscale simulations are performed for representative elements for all clusters to derive regional wind climatology. Additionally, 28 historical storms affecting Western Germany are simulated. Empirical functions are estimated to relate wind gust fields and insured losses. Transient ECHAM5/OM1 simulations show an enhanced frequency of primary storm-clusters and storms for 2060–2100 compared to 1960–2000. Accordingly, wind gusts increase over Western Germany, reaching locally +5% for 98th wind gust percentiles (A2-scenario). Consequently, storm losses are expected to increase substantially (+8% for A1B-scenario, +19% for A2-scenario). Regional patterns show larger changes over north-eastern parts of North Rhine-Westphalia than for western parts. For storms with return periods above 20 yr, loss expectations for Germany may increase by a factor of 2. These results document the method's functionality to assess future changes in loss potentials in regional terms.
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Observations of Earth from space have been made for over 40 years and have contributed to advances in many aspects of climate science. However, attempts to exploit this wealth of data are often hampered by a lack of homogeneity and continuity and by insufficient understanding of the products and their uncertainties. There is, therefore, a need to reassess and reprocess satellite datasets to maximize their usefulness for climate science. The European Space Agency has responded to this need by establishing the Climate Change Initiative (CCI). The CCI will create new climate data records for (currently) 13 essential climate variables (ECVs) and make these open and easily accessible to all. Each ECV project works closely with users to produce time series from the available satellite observations relevant to users' needs. A climate modeling users' group provides a climate system perspective and a forum to bring the data and modeling communities together. This paper presents the CCI program. It outlines its benefit and presents approaches and challenges for each ECV project, covering clouds, aerosols, ozone, greenhouse gases, sea surface temperature, ocean color, sea level, sea ice, land cover, fire, glaciers, soil moisture, and ice sheets. It also discusses how the CCI approach may contribute to defining and shaping future developments in Earth observation for climate science.
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We present a Bayesian image classification scheme for discriminating cloud, clear and sea-ice observations at high latitudes to improve identification of areas of clear-sky over ice-free ocean for SST retrieval. We validate the image classification against a manually classified dataset using Advanced Along Track Scanning Radiometer (AATSR) data. A three way classification scheme using a near-infrared textural feature improves classifier accuracy by 9.9 % over the nadir only version of the cloud clearing used in the ATSR Reprocessing for Climate (ARC) project in high latitude regions. The three way classification gives similar numbers of cloud and ice scenes misclassified as clear but significantly more clear-sky cases are correctly identified (89.9 % compared with 65 % for ARC). We also demonstrate the poetential of a Bayesian image classifier including information from the 0.6 micron channel to be used in sea-ice extent and ice surface temperature retrieval with 77.7 % of ice scenes correctly identified and an overall classifier accuracy of 96 %.