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The forest area of Tibet ranks among the top in China, and the forest resources in Tibet play an important role in water conservation and ecological service. Therefore, it is of great significance to assess the assets of forest natural resources in this region. However, existing products and statistical data related to forest cover fail to meet the demands for the assessment of forest natural resource assets in this region, and it is necessary to explore a fine - scale forest classification method suitable for this region. Based on the cloud computing platform Google Earth Engine ( GEE ), this study constructed the temporal, spatial, spectral, and auxiliary feature sets of the forest coverage in Motuo County using the Landsat8 remote sensing images of 2015 and 2020, as well as field survey data, and the basic geographic data. Then, it conducted forest classification using the random forest ( RF) and classification and regression tree ( CART) algorithms. As indicated by the accuracy evaluation of the assessment results obtained using the two algorithms, the forest classification results of 2015 and 2020 obtained using the RF algorithm had relatively high accuracy, with overall classification accuracy of 0. 88 and 0. 87, respectively and Kappa coefficients of both greater than 0.8. The analyses of the areal and spatio - temporal characteristics of forest classification results show that: 1 Motuo County had a total forest area of 34 000 km ² in 2015, with a forest cover rate of up to 84. 63%, which was 2% less than that in 2020; 2 The forest resources in Motuo County are dominated by broadleaved forests, which are mainly distributed in Yarlung Zangbo Grand Canyon and low - altitude areas and accounted for 72. 27% and 75. 37% of the total forest area in 2015 and 2020, respectively. Coniferous forests accounted for 25. 96% and 23. 19% of the total forest area in 2015 and 2020, respectively and are concentrated in high - altitude areas, such as the Namcha Barwa and Gyala Peri peaks. This study determined the spatio - temporal distribution of the forests in Motuo County in 2015 and 2020 by developing a spatio - temporal -spectral classification method. It can provide a reference method for calculating specific forest cover indices SDGs and fill the gap of forest data of smaH zones. The obtained monitoring data will provide data support for the natural asset assessment and ecological function evaluation in Motuo County. [ABSTRACT FROM AUTHOR]

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In this study? we examined the variation characteristics of leaf functional traits and the relationships between these traits and environmental factors in Abies georgei var. smithii forest? the dominant community of subalpine dark coniferous forests in southeastern Tibet. The results revealed that the leaf area[(0.57±0.20) cm2]? relative chlorophyll content(64.19±22.69)? volume [(0.029±0.011) cm³], and relative water content(83.76±11.98)% of A. georgei var. smithii were the highest at an altitude of 4 000 m? whereas leaf tissue density[(0.32±0.14) g??cm-3 ] was the lowest at this altitude. Compared with previously reported observations? we recorded lower specific leaf area[(66.81±17.48) cm².g-1] and higher leaf dry matter content[(0.41±0.05) g.g-¹] values for A. georgei var. smithii growing on Sejila mountain. Furthermore? we detected broad correlations among leaf traits? with more than half of the assessed relationships reaching a level of very high significance(P < 0.01). Soil physical and chemical properties were found to explain most of the observed variation in leaf functional traits(14.46%), whereas topographic factors such as altitude and slope appeared to have relatively little influence. Our findings indicate that A. georgei var. smithii trees growing on Sejila mountain adapt to changes in the external environment via a coordinated interaction of several functional characters? and compete for sunlight? water? and other resources in an alpine environment? thereby incorporating and conserving soil organic matter. [ABSTRACT FROM AUTHOR]

Orchidaceae resources census is the basis of mastering regional background data, and it is of great significance to the study of the geographical distribution and resource diversity of Orchids. Two newly recorded species of Orchidaceae, Bulbophyllum raskotii J. J. Verm., Schuit. & de Vogel and Panisea panchaseensis Subedi, are reported from southeastern Tibet, China for the first time. They grow on trees or rocks in evergreen broad-leaved forest at elevations of 2 000 m. Descriptions and photos for diagnostic characters are provided. Key to Panisea species occurring in China is provided. This study enriched the records of Orchidaceae in China, and provided basic data for studies of Orchidaceae diversity and conservation. [ABSTRACT FROM AUTHOR]

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Clarifying the characteristics of heat waves and their impacts on vegetation is essential for the development of industry and agriculture and the maintenance of the ecological environment. Based on the daily average temperature data of 712 meteorological stations in China and the normalized difference vegetation index (NDVI) data, the heat wave event is defined with the excess heat factor as an indicator, and four indexes like the number of heat waves, maximum duration, frequency, and amplitude are selected. The indexes analyze the temporal and spatial characteristics of heat wave events in 8 sub-regions of China from 1961 to 2017, and uses Spearman rank correlation analysis to explore the impact of heat wave events on vegetation finally. The results show that the four heat wave indexes have increased significantly and have undergone abrupt changes in the 1990s and early 21th century. The number, maximum duration and frequency of heat waves in the Qinghai-Tibet region, western region and eastern region have large mean values and changing trends over the years. The mean and changing trends of heat wave amplitude show the characteristics of spatial change of north high and south low. Heat wave events have a significant impact on the growth of vegetation. Heat wave events in the southeast coast, eastern Inner Mongolia and Xinjiang have an inhibitory effect on vegetation growth, while in the western region, Qinghai-Tibet region and southwest China heat wave events have a more obvious promotion effect on vegetation growth. [ABSTRACT FROM AUTHOR]

Copyright of Guihaia is the property of Guihaia Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)