Effects of land use changes on the nonlinear trends of net primary productivity in arid and semiarid areas, China. (1st February 2021)

• Record Type: Journal Article
• Authors: Liu, Huiyu; Cao, Li; Jia, Junhe; Gong, Haibo; Qi, Xiangzhen; Xu, Xiaojuan
• Is Part Of: Land degradation & development. Volume 32:Number 6(2021)
• Page Start: 2183
• Page End: 2196
• Publication Date: 2021-02-01
• Subjects: arid and semiarid areas -- ensemble empirical mode decomposition (EEMD) method -- land use change -- net primary productivity -- nonlinear trend analysis; Land degradation -- Periodicals; Soil conservation -- Periodicals; Reclamation of land -- Periodicals; Land use -- Periodicals; Economic development -- Environmental aspects -- Periodicals; 333.7315
• DOI: 10.1002/ldr.3885
• Languages: English
• ISSNs: 1085-3278

Abstract

Abstract: Monitoring the nonlinear trend of net primary productivity (NPP) is essential for assessing the changes of ecosystems quality. Land use change caused by human activities is considered to be a key factor leading to vegetation changes. However, how land use change impacts the nonlinear trend of NPP has not yet been determined. This article analyzed the nonlinear trend of NPP in arid and semiarid areas of China during in the period 1982–2015 based on the ensemble empirical mode decomposition (EEMD) method and elucidated the effects of land use changes on the nonlinear trends of NPP. The results revealed that: (a) With the EEMD method, although monotonic increase was the main type of the trend of NPP (28.40 %), trend reversals from increase to decrease and from decrease to increase accounted for 13.52 and 20.90 % of the study area, respectively. (b) Although vegetation in most types of land use has been improved a lot, it has not been improved significantly in forest areas and changed from improvement to degradation in some forest and urban land areas. (c) Urbanization limited vegetation recovery but other land use changes generally favoured vegetation improvement. Although afforestation improved vegetation, there was a considerable area of the forest converted from nonforest threatened by the changes from improvement to degradation due to water limitation. Overall, nonlinear trend analysis can reveal the hidden trend reversals to prevent the overestimation or underestimation of the risk of vegetation degradation and is conducive to accurate assessment of the effects of land use changes on vegetation trends.