Plant size traits are key contributors in the spatial variation of net primary productivity across terrestrial biomes in China

生物群落 初级生产 非生物成分 空间变异性 空间生态学 陆地生态系统 生态学 冻土带 植物群落 环境科学 生物 生态系统 生态演替 数学 统计
作者
Nannan An,Nan Lü,Mengyu Wang,Yongzhe Chen,Fuzhong Wu,Bojie Fu
出处
期刊:Science of The Total Environment [Elsevier BV]
卷期号:923: 171412-171412 被引量:1
标识
DOI:10.1016/j.scitotenv.2024.171412
摘要

Understanding the spatial variability of ecosystem functions is an important step forward in predicting changes in ecosystems under global transformations. Plant functional traits are important drivers of ecosystem functions such as net primary productivity (NPP). Although trait-based approaches have advanced rapidly, the extent to which specific plant functional traits are linked to the spatial diversity of NPP at a regional scale remains uncertain. Here, we used structural equation models (SEMs) to disentangle the relative effects of abiotic variables (i.e., climate, soil, nitrogen deposition, and human footprint) and biotic variables (i.e., plant functional traits and community structure) on the spatial variation of NPP across China and its eight biomes. Additionally, we investigated the indirect influence of climate and soil on the spatial variation of NPP by directly affecting plant functional traits. Abiotic and biotic variables collectively explained 62.6 % of the spatial differences of NPP within China, and 28.0 %-69.4 % across the eight distinct biomes. The most important abiotic factors, temperature and precipitation, had positive effects for NPP spatial variation. Interestingly, plant functional traits associated with the size of plant organs (i.e., plant height, leaf area, seed mass, and wood density) were the primary biotic drivers, and their positive effects were independent of biome type. Incorporating plant functional traits improved predictions of NPP by 6.7 %-50.2 %, except for the alpine tundra on the Qinghai-Tibet Plateau. Our study identifies the principal factors regulating NPP spatial variation and highlights the importance of plant size traits in predictions of NPP variation at a large scale. These results provide new insights for involving plant size traits in carbon process models.
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