Human‐Climate Coupled Changes in Vegetation Community Complexity of China Since 1980s

Abstract

Vegetation community complexity is a critical factor influencing terrestrial ecosystem stability. China, the country leading the world in vegetation greening resulting from human activities, has experienced dramatic changes in vegetation community composition during the past 30 years. However, how China's vegetation community complexity varies spatially and temporally remains unclear. Here, we examined the spatial pattern of China's vegetation community complexity and its temporal changes from the 1980s to 2015 using two vegetation maps of China as well as more than half a million field samples. Spatially, China's vegetation community complexity distribution is primarily dominated by elevation, although temperature and precipitation can be locally more influential than elevation when they become the factors limiting plant growth. Temporally, China's vegetation community complexity shows a significant decreasing trend during the past 30 years, despite the observed vegetation greening trend. Prevailing climate warming across China exhibits a significant negative correlation with the decrease in vegetation community complexity, but this correlation varies with biogeographical regions. The intensity of human activities have an overall negative influence on vegetation community complexity, but vegetation conservation and restoration efforts can have a positive effect on maintaining vegetation composition complexity, informing the critical role of vegetation management policies in achieving the sustainable development goal.

Carbon storage through China’s planted forest expansion

“…For example, the classification of planted forest types over various periods with the same vegetation map may present a challenge to our study because vegetation types have the potential to change. However, our previous studies have indicated that vegetation types in China are stable 23 , 24 , justifying our use of the same vegetation map to classify planted forest types across different periods. Recognizing that C density changes with forest age, we constructed a C density database based on the national forest inventory data, considering age-dependent C density variations (see Methods).…”

“…For example, the classification of planted forest types over various periods with the same vegetation map may present a challenge to our study because vegetation types have the potential to change. However, our previous studies have indicated that vegetation types in China are stable 23,24 From 1990 to 2020, the increase in China's planted forests C storage due to area expansion exceeded 50% of the total C storage increment in China's planted forests (Figs. 2 and 3).…”

“…This expansion is a result of conducted government efforts to convert croplands, shrublands, and grasslands into planted forests 17,18,21,22 . This effort to grow the planted forest area not only increased China's total forest extent but also resulted in drastic changes in land use and land cover (LULC), impacting China's forests C storage capacity 5,11,[23][24][25][26] . Based on the National Forest Management Plan (2016-2050), China's forest area will continue to account for ~26% of China's total land area by 2050, requiring an additional conversion of over 2.8 million ha from other LULC to forests 20 .…”

3D Point Cloud Semantic Segmentation System Based on Lightweight FPConv

“…The purpose of segmentation is to divide a structure into multiple sets of neighboring points and to divide these points based on segmentation granularity through semantic segmentation (scene level), instance segmentation (target level), and partial segmentation (part level). Guo et al [4] discussed all available 3D point cloud semantic segmentation methods and divided these methods into projection-based, discretion-based, pointbased, and hybrid methods.…”

Synergistic Impact of Complex Topography and Climate Variability on the Loss of Microclimate Heterogeneity in Southeast Asia

“…The tropical and subtropical forest biomes of Southeast Asia are among the most imperiled regions of the planet's 36 biodiversity hotspots, with less than five percent of the natural ecosystems remaining intact (Buchadas et al., 2022; Hoang & Kanemoto, 2021; Pratzer et al., 2023; Su et al., 2022). Geographical shifts in species distribution have been observed (Early et al., 2016; Ruyn et al., 2014; Sunday et al., 2012), and it is expected that local species will accelerate their movement to higher elevations (Cazzolla Gatti et al., 2019; Elsen et al., 2021; Pecl et al., 2017).…”