17 resultados para Rabies in animals--South Carolina

em Chinese Academy of Sciences Institutional Repositories Grid Portal


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Investigating the interplay between continental weathering and erosion, climate, and atmospheric CO2 concentrations is significant in understanding the mechanisms that force the Cenozoic global cooling and predicting the future climatic and environmental response to increasing temperature and CO2 levels. The Miocene represents an ideal test case as it encompasses two distinct extreme climate periods, the Miocene Climatic Optimum (MCO) with the warmest time since 35 Ma in Earth's history and the transition to the Late Cenozoic icehouse mode with the establishment of the east Antarctic ice sheet. However the precise role of continental weathering during this period of major climate change is poorly understood. Here we show changes in the rates of Miocene continental chemical weathering and physical erosion, which we tracked using the chemical index of alteration ( CIA) and mass accumulation rate ( MAR) respectively from Ocean Drilling Program (ODP) Site 1146 and 1148 in the South China Sea. We found significantly increased CIA values and terrigenous MARs during the MCO (ca. 17-15 Ma) compared to earlier and later periods suggests extreme continental weathering and erosion at that time. Similar high rates were revealed in the early-middle Miocene of Asia, the European Alps, and offshore Angola. This suggests that rapid sedimentation during the MCO was a global erosion event triggered by climate rather than regional tectonic activity. The close coherence of our records with high temperature, strong precipitation, increased burial of organic carbon and elevated atmospheric CO2 concentration during the MCO argues for long-term, close coupling between continental silicate weathering, erosion, climate and atmospheric CO2 during the Miocene. Citation: Wan, S., W. M. Kurschner, P. D. Clift, A. Li, and T. Li (2009), Extreme weathering/ erosion during the Miocene Climatic Optimum: Evidence from sediment record in the South China Sea, Geophys. Res. Lett., 36, L19706, doi: 10.1029/2009GL040279.

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The onshore-offshore deep seismic experiment was carried out for the first time and filled the blankness of the seismic surveys in the transition area between South China and northeastern South China Sea. The seismic data were analyzed and processed. The different seismic phases were identified and their travel time arrivals were modeled by ray-tracing to study the P-wave velocity crustal structure of this area. The crustal structure of this area is the continental crust. The crust thickness is gradually decreasing southward along the on-shore-offshore seismic line. The low-velocity layer (5.5 similar to 5.9 km (.) s(-1)) exists generally in the middle crust (about 10.0 similar to 18.0km)with about 2.5 similar to 4.0 km thickness, which is also thinning seaward. No obvious high-velocity layer appears in the lower crust. The Binhai (littoral) fault zone is a low velocity zone, which is located about 35km southeast to the Nan'ao station and corresponding to the gradient belt of gravity & magnetism anomalies. The depth of the fault zone is close to the Moho discontinuity. The littoral fault zone is a boundary between the normal continental crust of South China and the thinned continental crust of the sea area.

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Characteristics and distribution patterns of elastic minerals (0.063 similar to 0.125 mm) in bottom sediments represent a significant indicator for the identification of the origin of sediment. One hundred and fourteen surface sediment samples, which were collected from the area near the Zhongsha Islands in the South China Sea, were analysed to identify the mineral suites and their distributions in the study area. The area can be divided into three mineral provinces: ( I) a province of biogenic minerals, which mainly originate from the Zhongsha Atoll; ( H) a province of volcanogenic minerals, which are mainly derived from local basaltic seamounts and small-scale volcanoes that are probably erupting, with some influences from the island-are volcanic region around the South China Sea; and (II) a mixed mineral province whose material source includes biogenic minerals, volcanogenic minerals and terrigenous minerals; the last province can be subdivided into a mixed mineral sub-province of the northeastern part of the study area, in which terrigenous minerals are mainly derived from China's Mainland and do not exceed 17 degrees N, and a mixed mineral sub-province of the southeastern part of the study area, in which terrigenous minerals are derived from Kalimantan and Indochina Peninsula and might be further transported into the deep sea basin through submarine canyons.

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128 samples from Ocean Drilling Program (ODP) Site 1143 in the southern South China Sea were analyzed for grain size, clay minerals, biogenic opal content and quartz in order to reconstruct changes in East Asian monsoon climate since 8.5 Ma. An abrupt change of terrigenous mass accumulation rate (MAR), clay mineral assemblage, median grain size and biogenic opal MAR about 5.2 Ma suggests that between 8.5-5.2 Ma the source of terrigenous sediment was mainly in the region of surface uplift and basaltic volcanism in southern Vietnam. A simple model of East Asian summer monsoon evolution was based on the clay/feldspar ratio, kaolinite/chlorite ratio and biogenic opal MAR. The summer monsoon has two periods of maximum strength at 8.5-7.6 Ma and 7.1-6.2 Ma. Subsequently, there was a relatively stable period at 6.2-3.5 Ma, continued intensification about 3.5-2.5 Ma, and gradually weakening after 2.5 Ma. Since I Ma the monsoon has intensified, with remarkable high-frequency and amplitude variability. Simultaneous increase in sedimentation rates at ODP Sites 1143, 1146 and 1148, as well as in MAR of terrigenous materials, quartz, feldspar and clay minerals at ODP Site 1143 at 3.5-2.5 Ma, may be the erosional response to both global climatic deterioration and the strengthening of the East Asian summer monsoon after about 3-4 Ma. (c) 2006 Elsevier B.V. All rights reserved.

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We used fifteen years (1993-2007) of altimetric data, combined from different missions (ERS-1/2, TOPEX/Poseidon, Jason-1, and Envisat), to analyze the variability of the eddy kinetic energy (EKE) in the South China Sea (SCS). We found that the EKE ranged from 64 cm(2)/s(2) to 1 390 cm(2)/s(2) with a mean value of 314 cm(2)/s(2). The highest EKE center was observed to the east of Vietnam (with a mean value of 509 cm(2)/s(2)) and the second highest EKE region was located to the southwest of Taiwan Island (with a mean value of 319 cm(2)/s(2)). We also found that the EKE structure is the consequence of the superposition of different variability components. First, interannual variability is important in the SCS. Spectral analysis of the EKE interannual signal (IA-EKE) shows that the main periodicities of the IA-EKE to the east of Vietnam, to the southwest of Taiwan Island, and in the SCS are 3.75, 1.87, and 3.75 years, respectively. It is to the south of Taiwan Island that the IA-EKE signal has the most obvious impact on EKE variability. In addition, the IA-EKE exhibit different trends in different regions. An obvious positive trend is observed along the east coast of Vietnam, while a negative trend is found to the southwest of Taiwan Island and in the east basin of Vietnam. Correlation analysis shows that the IA-EKE has an obvious negative correlation with the SSTA in Nio3 (5A degrees S-5A degrees N, 90A degrees W-150A degrees W). El Nio-Southern Oscillation (ENSO) affects the IA-EKE variability in the SCS through an atmospheric bridge-wind stress curl over the SCS. Second, the seasonal cycle is the most obvious timescale affecting EKE variability. The locations of the most remarkable EKE seasonal variabilities in the SCS are to the east of Vietnam, to the southwest of Taiwan, and to the west of Philippines. To the east of Vietnam, the seasonal cycle is the dominant mechanism controlling EKE variability, which is attributed primarily to the annual cycle there of wind stress curl. In this area, the maximum EKE is observed in autumn. To the southwest of Taiwan Island, the EKE is enlarged by the stronger SCS circulation, which is caused by the intrusion branch from the Kuroshio in winter. Finally, intra-annual and mesoscale variability, although less important than the former, cannot be neglected. The most obvious intra-annual and mesoscale variability, which may be the result of baroclinic instability of the background flow, are observed to the southwest of Taiwan Island. Sporadic events can have an important effect on EKE variability.

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The four leading tidal constituents M-2, S-2, K-1 and O-1 in the South China Sea are simulated by using POM. The model is forced with tide-generating potential and four leading tidal constituents at the open boundary. In order to simulate more exactly, TOPEX/Poseidon altimeter data are assimilated into the model and the open boundary is optimized. The computed co-tidal charts for M-2 and K-1 constituents are generally consistent with previous results in this region. The numerical simulation shows that energetic internal tides are generated over the bottom topography such as the Dongsha Islands, the Xisha Islands, the Zhongsha Islands, the Nansba Islands and the Luzon Strait.

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The principal tidal constituents M-2, S-2, K-1 and O-1 in the South China Sea, Gulf of Tonkin and Gulf of Thailand are simulated simultaneously using the numerical scheme of Kwok et al. (1995 Proceedings of the 1st Asian Computational Fluid Dynamics Conference, pp. 16-19). The average differences between the computed and observed harmonic constants are mostly within 5 cm and 10 degrees for amplitudes and phase-lags, respectively. The simulated tidal regimes in the present model are believed to be more accurate than the previous numerical results. Our studies confirm that a clockwise rotating M-2 amphidromic system lies in the southeast of the Gulf of Thailand and an S-2 amphidromic system at the near-shore area of the northeast South China Sea. The linear tidal energy equation developed by Garrett (1975 Deep-Sea Research 22, 23-35) is generalized to the nonlinear case. Based on the numerical results, the energy budgets in the South China Sea and its subareas, namely the Taiwan Strait, the Gulf of Tonkin, the Gulf of Thailand and the remaining area are investigated. The tidal motion in the Taiwan Strait is maintained mainly by the energy fluxes from the East China Sea for both semidiurnal and diurnal species and partially from the Luzon Strait for semidiurnal species. For the other parts of the South China Sea, the tidal motion is mainly maintained by the energy fluxes through the Luzon Strait. The energy inputs from the tide-generating force are negative for semidiurnal species and positive for diurnal species. (C) 1999 Elsevier Science Ltd. All rights reserved.

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We compared nonlinear principal component analysis (NLPCA) with linear principal component analysis (LPCA) with the data of sea surface wind anomalies (SWA), surface height anomalies (SSHA), and sea surface temperature anomalies (SSTA), taken in the South China Sea (SCS) between 1993 and 2003. The SCS monthly data for SWA, SSHA and SSTA (i.e., the anomalies with climatological seasonal cycle removed) were pre-filtered by LPCA, with only three leading modes retained. The first three modes of SWA, SSHA, and SSTA of LPCA explained 86%, 71%, and 94% of the total variance in the original data, respectively. Thus, the three associated time coefficient functions (TCFs) were used as the input data for NLPCA network. The NLPCA was made based on feed-forward neural network models. Compared with classical linear PCA, the first NLPCA mode could explain more variance than linear PCA for the above data. The nonlinearity of SWA and SSHA were stronger in most areas of the SCS. The first mode of the NLPCA on the SWA and SSHA accounted for 67.26% of the variance versus 54.7%, and 60.24% versus 50.43%, respectively for the first LPCA mode. Conversely, the nonlinear SSTA, localized in the northern SCS and southern continental shelf region, resulted in little improvement in the explanation of the variance for the first NLPCA.

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The mixed layer depth (MLD) in the upper ocean is an important physical parameter for describing the upper ocean mixed layer. We analyzed several major factors influencing the climatological mixed layer depth (CMLD), and established a numerical simulation in the South China Sea (SCS) using the Regional Ocean Model System (ROMS) with a high-resolution (1/12A degrees x1/12A degrees) grid nesting method and 50 vertical layers. Several ideal numerical experiments were tested by modifying the existing sea surface boundary conditions. Especially, we analyzed the sensitivity of the results simulated for the CMLD with factors of sea surface wind stress (SSWS), sea surface net heat flux (SSNHF), and the difference between evaporation and precipitation (DEP). The result shows that of the three factors that change the depth of the CMLD, SSWS is in the first place, when ignoring the impact of SSWS, CMLD will change by 26% on average, and its effect is always to deepen the CMLD; the next comes SSNHF (13%) for deepening the CMLD in October to January and shallowing the CMLD in February to September; and the DEP comes in the third (only 2%). Moreover, we analyzed the temporal and spatial characteristics of CMLD and compared the simulation result with the ARGO observational data. The results indicate that ROMS is applicable for studying CMLD in the SCS area.

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11-year satellite altimeter sea surface height (SSH) anomaly data from January 1993 to December 2003 are used to present the dominant spatial patterns and temporal variations of the South China Sea (SCS) surface circulation through Empirical Orthogonal Function (EOF) analysis. The first three EOF modes show the obvious seasonal variations of SSH in the SCS. EOF mode one is generally characterized by a basin-wide circulation. Mode two describes the double-cell basin scale circulation structure. The two cells were located off west of the Luzon Island and southeast of Vietnam, respectively. EOF mode three presents the mesoscale eddy structure in the western SCS, which develops into a strong cyclonic eddy rapidly from July to September. EOF mode one and mode three are also embedded with interannual signals, indicating that the SCS surface circulation variation is influenced by El Nino events prominently. The strong El Nino of 1997/98 obviously changed the SCS circulation structure. This study also shows that there existed a series of mesoscale eddies in the western SCS, and their temporal variation indicates intra-seasonal and interannual signals.

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To investigate the seasonal and interannual variations in biological productivity in the South China Sea (SCS), a Pacific basin-wide physical - biogeochemical model has been developed and used to estimate the biological productivity and export flux in the SCS. The Pacific circulation model, based on the Regional Ocean Model Systems (ROMS), is forced with daily air-sea fluxes derived from the NCEP (National Centers for Environmental Prediction) reanalysis between 1990 and 2004. The biogeochemical processes are simulated with a carbon, Si(OH)(4), and nitrogen ecosystem (CoSiNE) model consisting of silicate, nitrate, ammonium, two phytoplankton groups (small phytoplankton and large phytoplankton), two zooplankton grazers (small micrograzers and large mesozooplankton), and two detritus pools. The ROMS-CoSiNE model favourably reproduces many of the observed features, such as ChI a, nutrients, and primary production (PP) in the SCS. The modelled depth-integrated PP over the euphotic zone (0-125 m) varies seasonally, with the highest value of 386 mg C m (-2) d (-1) during winter and the lowest value of 156 mg C m (-2) d (-1) during early summer. The annual mean value is 196 mg C m (-2) d (-1). The model-integrated annual mean new production (uptake of nitrate), in carbon units, is 64.4 mg C m (-2) d (-1) which yields an f-ratio of 0.33 for the entire SCS. The modelled export ratio (e-ratio: the ratio of export to PP) is 0.24 for the basin-wide SCS. The year-to-year variation of biological productivity in the SCS is weaker than the seasonal variation. The large phytoplankton group tends to dominate over the smaller phytoplankton group, and likely plays an important role in determining the interannual variability of primary and new production.