Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/265375 
Year of Publication: 
2022
Citation: 
[Journal:] Journal of Geophysical Research: Biogeosciences [ISSN:] 2169-8961 [Volume:] 127 [Issue:] 6 [Article No.:] e2021JG006659 [Publisher:] Wiley [Place:] Hoboken, NJ [Year:] 2022 [Pages:] 1-15
Publisher: 
Wiley, Hoboken, NJ
Abstract: 
The greening of the Earth over the last decades is predominantly indicated by the enhancements of leaf area index (LAI). Quantifying the relative contribution of multiple determinants, especially changes in climate and in land management changes (LMC), remains an arduous challenge. To solve this problem, we develop a simple yet novel data-driven method, called the Paired Land Use Experiment (PLUE), for mesoscale analysis. Using PLUE, we analyze vegetation development of the Sanjiang Plain, a transboundary plain between China and Russia, with roughly homogeneous climate but with distinct land management practices across the border-intensified agricultural development on China side (CNSP) versus largely little-disturbed natural vegetation on Russia side (RUSP). Both CNSP and RUSP LAI show significant trends (p < 0.05), with the annual variability reaching values of 9.8 × 10ˉ³ yrˉ¹ and 11.3 × 10ˉ³ yrˉ¹, respectively. However, in CNSP, the LAI increase is concentrated in the middle of the year, especially in five 8-day periods from 26 June to 28 July. During this period, the LAI trend of CNSP is much higher than that of RUSP, at 92.7 × 10ˉ³ yrˉ¹ (p < 0.01) and 43.8 × 10ˉ³ yrˉ¹ (p < 0.01), respectively. Meanwhile, LAI decreased in CNSP at the begging and end of the growing season. The results show that different LMC practices lead to notably different seasonal variability in vegetation changes. The PLUE method offers a new potential tool in driver identification of vegetation greenness change based on observations. We argue for the necessity of parameterizing these different LMC in Earth system models.
Subjects: 
Paired Land Use Experiment (PLUE)
land management
leaf area index (LAI)
cross-border plain
greening
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc-nd Logo
Document Type: 
Article
Document Version: 
Published Version

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