Рудопроявление Суой Кун как пример потенциальной золото-сульфидной минерализации карлин-типа в северо-восточном Вьетнаме

The territory of the northeast of Vietnam is the most important region of the country in terms of metallogeny, especially for precious and non-ferrous metals. A large number of Au, Pb, Zn, Sb, Hg, and Ni-Cu-PGE deposits are located in this territory, regionally confined to the southwestern margin of the South China Block. This region is located northeast of the Red River Shear Zone, which marks the boundary between two large geoblocks. The Song Hien rift basin is an important metallogenic region of northeastern Vietnam and extends for more than 200 km in the NW-SE direction, up to the state border with China. On the adjacent territory of China, the Song Hien structure passes into the Youjiang rift basin, where a large number of gold deposits attributed to the Carlin formation are also known. The Suoi Cun deposit is located to the east and southeast of the Cao Bang city and the large Cu-Ni-Pt-bearing mafic-ultramafic Suoi Cun massif. The mineralization is hosted by the rhyolites of the Triassic Song Hien formation and represents by hydrothermal low-temperature veins and crushing zones with chalcedonic quartz. Ore minerals in quartz-vein and metasomatically altered rhyolites are represented by pyrite, marcasite, and arsenopyrite. The amount of ore minerals is not constant and varies in a wide range from poor dissemination to 30 %. Ore zones have a zonal structure. The outer zones, 50–100 meters wide, are represented by altered rhyolites. The central part of the ore bodies is ore breccia, the fragments of which are represented by both massive pyrite aggregates and differently altered and mineralized rhyolites. The cement of the breccias is different and depends on the spatial position in the section of the ore body. The outer part of the inner mineralized zone is cemented by quartz and, more rarely, by carbonate. According to the results of Ar-Ar dating, the calculated age of hydrothermal sericite from the axial part of the mineralized zone was 218 ± 1 Ma. The main geological and mineral characteristics of the Suoi Cun deposit include: (1) the confinement of mineralization to zones of crushing and multiple breccia formation in the rhyolites of the Song Hien Formation; (2) wide development of chalcedonic quartz and marcasite, indicating low temperatures of mineral formation; (3) chloritization, sericitization, silicification, and sulfidization as the dominant types of metasomatic transformation; (4) mineral association represented by pyrite, marcasite, arsenopyrite, and stibnite; (5) absence of native gold in ores, positive correlation between gold and Carlin group elements (As, Sb, Hg, Tl); (6) relation of mineral formation with regional tectonic events, lack of genetic relationship with magmatism. Using the critical characteristics for Carlin type deposits, we conclude that the Suoi Cun deposit is represented by this formation

Mangrove Mapping and Above-Ground Biomass Change Detection using Satellite Images in Coastal Areas of Thai Binh Province, Vietnam

Mangroves are recognized as a highly valuable resource due to their provision of multiple ecosystem services. Therefore, mangrove ecosystems mapping and monitoring is a crucial objective, especially for tropical regions. Thai Binh province is one of the most important mangrove ecosystems in Vietnam. The mangrove ecosystem in this province has faced threats of deforestation from urban development, land reclamation, tourism activities, and natural disasters. Recently, to maintain the fundamental functions of the ecosystems, a large mangrove area was planted in Thai Binh. The aim of this research is to detect the change in the mangrove areas and to create an aboveground biomass map for mangrove forests in Thai Binh province. Landsat and Sentinel-2 satellite images from 1998 to 2018 were analysed using the supervised classification method to detect mangrove area change. Mangrove Above-ground Biomass (AGB) was estimated using linear regression between vegetation indices and field AGB survey. The accuracy assessment for the classified images of 1998, 2003 and 2007, 2013 and 2018 are 93%, 86%, 96%, 94% and 91% respectively with kappa of 0.8881, 0.7953, 0.9357, 0.9114 and 0.8761. The mangrove cover in the study area was estimated at 5874.93 ha in 1998. This figure decreased significantly to 4433.85 ha in 2007, before recovery began to take place in the study area, which was estimated at 6587.88 ha in 2018. In 1998, the average AGB in this study area was 22.57 ton/ha, and in 2018 it was 37.74 ton/ha with a standard error of 12.41 ton/ha and the root mean square error (RMSE) was ±12.08 ton/ha

Modelling nitrous oxide (N2O) emission from rice field in impacts of farming practices: A case study in Duy Xuyen district, Quang Nam province (Central Vietnam)

Nitrous oxide (N2O) emisison from paddy soil via the soil nitrification and denitrification processes makes an important contribution to atmospheric greenhouse gas concentrations. The soil N2O emission processes are controlled not only by biological, physical and chemical factors but also by farming practices. In recent years, modeling approach has become popular to predict and estimate greenhouse gas fluxes from field studies. In this study, the DeNitrification–DeComposition (DNDC) model were calibrated and tested by incorporating experimental data with the local climate, soil properties and farming management, for its simulation applicability for the irrigated rice system in Duy Xuyen district, a delta lowland area of Vu Gia-Thu Bon River Basin regions. The revised DNDC was then used to quantitatively estimate N2O emissions from rice fields under a range of three management farming practices (water management, crop residue incorporation and nitrogen fertilizer application rate). Results from the simulations indicated that (1) N2O emissions were significantly affected by water management practices; (2) increases in temperature, total fertilizer N input substantially increased N2O emissions. Finally, five 50-year scenarios were simulated with DNDC to predict their long-term impacts on crop yield and N2O emissions. The modelled results suggested that implementation of manure amendment or crop residue incorporation instead of increased nitrogen fertilizer application rates would more efficiently mitigate N2O emissions from the tested rice-based system.Phát thải nitơ ôxít (N2O) từ canh tác lúa nước (thông qua quá trình nitrat hóa và phản nitrat hóa) đóng góp đáng kể vào tổng lượng khí nhà kính có nguồn gốc từ sản xuất nông nghiệp. Quá trình phát thải N2O là không chỉ phụ thuộc vào các yếu tố sinh-lý-hóa học mà còn phụ thuộc các phương pháp canh tác. Trong những năm gần đây, việc ứng dụng mô hình hóa nhằm tính toán và ước lượng sự phát thải khí nhà kính ngày càng trở lên phổ biến. Trong nghiên cứu này, số liệu quan trắc từ thí nghiệm đồng ruộng và dữ liệu về đất đai, khí hậu, biện pháp canh tác được sử dụng để kiểm nghiệm và phân tích độ nhạy của mô hình DNDC (mô hình sinh địa hóa). Sau đó, mô hình được sử dụng để tính toán lượng N2O phát thải trong canh tác lúa nước dưới các phương thức canh tác khác nhau (về chế độ tưới, mức độ vùi phụ phẩm, bón phân hữu cơ, phân đạm) tại huyện Duy Xuyên, thuộc vùng đồng bằng thấp của lưu vực sông Vu Gia-Thu Bồn. Kết quả kiểm định chỉ ra rằng (1) sự phát thải N2O bị ảnh hưởng đáng kể do sự thay đổi chế độ tưới; (2) nhiệt độ tăng và lượng phân bón N tăng sẽ làm tăng phát thải N2O. Kết quả mô phỏng về tác động lâu dài (trong 50 năm) của các yếu tố đến năng suất cây trồng và phát thải N2O cho thấy: Việc sử dụng phân hữu cơ và phụ phẩm nông nghiệp thay thế cho việc bón phân đạm sẽ giúp giảm phát thải N2O đáng kể

Logging intensity drives variability in carbon stocks in lowland forests in Vietnam

Forest degradation in the tropics is generating large carbon (C) emissions. In tropical Asia, logging is the main driver of forest degradation. For effective implementation of REDD+ projects in logged forests in Southeast Asia, the impacts of logging on forest C stocks need to be assessed. Here, we assess C stocks in logged lowland forests in central Vietnam and explore correlations between logging intensity, soil, topography and living aboveground carbon (AGC) stocks. We present an approach to estimate historical logging intensities for the prevalent situation when complete records on logging history are unavailable. Landsat analysis and participatory mapping were used to quantify the density of historical disturbances, used as a proxy of logging intensities in the area. Carbon in AGC, dead wood, belowground carbon (BGC) and soil (SOC) was measured in twenty-four 0.25 ha plots that vary in logging intensity, and data on recent logging, soil properties, elevation and slope were also collected. Heavily logged forests stored only half the amount of AGC of stems ≥10 cm dbh as lightly logged forests, mainly due to a reduction in the number of large (≥60 cm dbh) trees. Carbon in AGC of small trees (5–10 cm dbh), dead wood and BGC comprised only small fractions of total C stocks, while SOC in the topsoil of 0–30 cm depth stored ~50% of total C stocks. Combining logging intensities with soil and topographic data showed that logging intensity was the main factor explaining the variability in AGC. Our research shows large reductions in AGC in medium and heavily logged forests. It highlights the critical importance of conserving big trees to maintain high forest C stocks and accounting for SOC in total C stock estimates

CSA: Thực hành nông nghiệp thông minh với khí hậu ở Việt Nam

During the last five years, Vietnam has been one of the countries most affected by climate change. Severe typhoons, flooding, cold spells, salinity intrusion, and drought have affected agriculture production across the country, from upland to lowland regions. Fortunately for Vietnam, continuous work in developing climate-smart agriculture has been occurring in research organizations and among innovative farmers and entrepreneurs. Application of various CSA practices and technologies to adapt to the impact of climate change in agriculture production have been expanding. However, there is a need to accelerate the scaling process of these practices and technologies in order to ensure growth of agriculture production and food security, increase income of farmers, make farming climate resilient, and contribute to global climate change mitigation. This book aims to provide basic information to researchers, managers, and technicians and extentionists at different levels on what CSA practices and technologies can be up scaled in different locations in Vietnam

Interactions between climate change, urban infrastructure and mobility are driving dengue emergence in Vietnam.

Dengue is expanding globally, but how dengue emergence is shaped locally by interactions between climatic and socio-environmental factors is not well understood. Here, we investigate the drivers of dengue incidence and emergence in Vietnam, through analysing 23 years of district-level case data spanning a period of significant socioeconomic change (1998-2020). We show that urban infrastructure factors (sanitation, water supply, long-term urban growth) predict local spatial patterns of dengue incidence, while human mobility is a more influential driver in subtropical northern regions than the endemic south. Temperature is the dominant factor shaping dengue's distribution and dynamics, and using long-term reanalysis temperature data we show that warming since 1950 has expanded transmission risk throughout Vietnam, and most strongly in current dengue emergence hotspots (e.g., southern central regions, Ha Noi). In contrast, effects of hydrometeorology are complex, multi-scalar and dependent on local context: risk increases under either short-term precipitation excess or long-term drought, but improvements in water supply mitigate drought-associated risks except under extreme conditions. Our findings challenge the assumption that dengue is an urban disease, instead suggesting that incidence peaks in transitional landscapes with intermediate infrastructure provision, and provide evidence that interactions between recent climate change and mobility are contributing to dengue's expansion throughout Vietnam

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Socializing One Health: an innovative strategy to investigate social and behavioral risks of emerging viral threats

In an effort to strengthen global capacity to prevent, detect, and control infectious diseases in animals and people, the United States Agency for International Development’s (USAID) Emerging Pandemic Threats (EPT) PREDICT project funded development of regional, national, and local One Health capacities for early disease detection, rapid response, disease control, and risk reduction. From the outset, the EPT approach was inclusive of social science research methods designed to understand the contexts and behaviors of communities living and working at human-animal-environment interfaces considered high-risk for virus emergence. Using qualitative and quantitative approaches, PREDICT behavioral research aimed to identify and assess a range of socio-cultural behaviors that could be influential in zoonotic disease emergence, amplification, and transmission. This broad approach to behavioral risk characterization enabled us to identify and characterize human activities that could be linked to the transmission dynamics of new and emerging viruses. This paper provides a discussion of implementation of a social science approach within a zoonotic surveillance framework. We conducted in-depth ethnographic interviews and focus groups to better understand the individual- and community-level knowledge, attitudes, and practices that potentially put participants at risk for zoonotic disease transmission from the animals they live and work with, across 6 interface domains. When we asked highly-exposed individuals (ie. bushmeat hunters, wildlife or guano farmers) about the risk they perceived in their occupational activities, most did not perceive it to be risky, whether because it was normalized by years (or generations) of doing such an activity, or due to lack of information about potential risks. Integrating the social sciences allows investigations of the specific human activities that are hypothesized to drive disease emergence, amplification, and transmission, in order to better substantiate behavioral disease drivers, along with the social dimensions of infection and transmission dynamics. Understanding these dynamics is critical to achieving health security--the protection from threats to health-- which requires investments in both collective and individual health security. Involving behavioral sciences into zoonotic disease surveillance allowed us to push toward fuller community integration and engagement and toward dialogue and implementation of recommendations for disease prevention and improved health security