Environmental Management
T.T. Tran; Y.M.T. Nguyen; L.T. Pham; B.K. Veettil; S.N. Hoang; Q.X. Ngo
Abstract
The Lo Go-Xa Mat is a national park in the southeastern region of Vietnam, which has a particularly high biodiversity and it includes different wetlands which are unique diverse in species composition. It can be categorized into two types: temporarily-seasonally and permanently flooded wetlands. Ta Not ...
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The Lo Go-Xa Mat is a national park in the southeastern region of Vietnam, which has a particularly high biodiversity and it includes different wetlands which are unique diverse in species composition. It can be categorized into two types: temporarily-seasonally and permanently flooded wetlands. Ta Not grassy marsh is representative of the seasonally flooded wetland. Whilst the diversity and ecology of plants and mammals are well documented, little or no information of the benthic ecology in the seasonally flooded wetland exist. This study aims to provide a new database of the nematode’s structure in the seasonally flooded wetland and its relation with environmental variables as well as detection of the ecological quality, considering nematodes as bioindicators. This work is the first investigation on nematodes communities in associate with some environmental variables in the Ta Not grassy marsh. The results showed that free-living nematodes in the Ta Not seasonally flooded grassy marsh are characterized by the high density (ranged from 235.01 to 898.43 inds.10cm-2) but rather low diversity. More specifically, the genus richness (S) ranged from 8.20 to 8.60. The observed Margalef’s species richness (d) was ranging from 1.07 to 1.53 and the Shannon-Wiener index (H') was measured from 2.36 to 2.52. In addition, the Pielou's evenness (J′) ranged from 0.55 to 0.68 and the Hill indices indicated average values ranging between 5.46- 5.84 for N1, between 4.32-4.60 for N2, and between 2.64-2.86 for Ninf. Specifically, our results indicated that deep level, pH, and NH4+ showed a significant correlation with the nematode density and bio-indices. The sediment of the Ta Not grassy marsh was assessed as in good conditions in all stations based on the Maturity Index of nematodes.
Environmental Management
T.T. Tran; L.T. Pham; Q.X. Ngo
Abstract
Currently, the pandemic caused by a novel coronavirus, namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is one of the most serious issues worldwide. SARS-CoV-2 was first observed in Wuhan, China, on December 31, 2019; this disease has been rapidly spreading worldwide. Iran was the ...
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Currently, the pandemic caused by a novel coronavirus, namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is one of the most serious issues worldwide. SARS-CoV-2 was first observed in Wuhan, China, on December 31, 2019; this disease has been rapidly spreading worldwide. Iran was the first Middle East country to report a coronavirus death, it has been severely affected. Therefore, it is crucial to forecast the pandemic spread in Iran. This study aims to develop a prediction model for the daily total confirmed cases, total confirmed new cases, total deaths, total new deaths, growth rate in confirmed cases, and growth rate in deaths. The model utilizes SARS-CoV-2 daily data, which are mainly collected from the official website of the European Centre for Disease Prevention and Control from February 20 to May 04, 2020 and other appropriated references. Autoregressive integrated moving average (ARIMA) is employed to forecast the trend of the pandemic spread. The ARIMA model predicts that Iran can easily exhibit an increase in the daily total confirmed cases and the total deaths, while the daily total confirmed new cases, total new deaths, and growth rate in confirmed cases/deaths becomes stable in the near future. This study predicts that Iran can control the SARS-CoV-2 disease in the near future. The ARIMA model can rapidly aid in forecasting patients and rendering a better preparedness plan in Iran.