Carbon emissions from oil palm induced forest and peatland conversion in sabah and Sarawak, Malaysia

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. The palm oil industry is one of the major producers of vegetable oil in the tropics. Palm oil is used extensively for the manufacture of a wide variety of products and its production is increasing by around 9% every year, prompted largely by the expanding biofuel markets. The rise in annual demand for biofuels and vegetable oil from importer countries has caused a dramatic increase in the conversion of forests and peatlands into oil palm plantations in Malaysia. This study assessed the area of forests and peatlands converted into oil palm plantations from 1990 to 2018 in the states of Sarawak and Sabah, Malaysia, and estimated the resulting carbon dioxide (CO2) emissions. To do so, we analyzed multitemporal 30-m resolution Landsat-5 and Landsat-8 images using a hybrid method that combined automatic image processing and manual analyses. We found that over the 28-year period, forest cover declined by 12.6% and 16.3%, and the peatland area declined by 20.5% and 19.1% in Sarawak and Sabah, respectively. In 2018, we found that these changes resulted in CO2 emissions of 0.01577 and 0.00086 Gt CO2-C yr−1, as compared to an annual forest CO2 uptake of 0.26464 and 0.15007 Gt CO2-C yr−1, in Sarawak and Sabah, respectively. Our assessment highlights that carbon impacts extend beyond lost standing stocks, and result in substantial direct emissions from the oil palm plantations themselves, with 2018 oil palm plantations in our study area emitting up to 4% of CO2 uptake by remaining forests. Limiting future climate change impacts requires enhanced economic incentives for land uses that neither convert standing forests nor result in substantial CO2 emissions

Role of Trace Elements in Alzheimer's Disease R > R > R . Multiple correlation coefficient in AD samples R > Keywords Alzheimer's Disease, Trace Elements, Flame Atomic Absorption, Multiple and Partial Correlation

Abstract Atomic absorption analysis involves measuring the absorption of light by vaporized ground state atoms and relating the absorption to concentration. The incident beam of light is attenuated by atomic vapour absorption according to Beer's Law. The estimation of trace elements shows a colorful presentation of different metals. It has been seen and found that the levels of zinc, calcium, magnesium, aluminum are lower in Alzheimer's disease samples in comparison to healthy controls. The elements such as copper, iron, potassium and sodium were found higher than controls. A statistical analysis has been applied and measured regression with correlation coefficients including multiple correlation coefficients between different trace elements like Na, K, Ca, Mg, Zn, Cu, Fe and Al in normal samples. A trend has been found in coefficient of correlation such as Ca.Mg r &gt

Global consortium for the classification of fungi and fungus-like taxa

International audienc