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. K E Y W O R D Sarid and semiarid areas, ensemble empirical mode decomposition (EEMD) method, land use change, net primary productivity, nonlinear trend analysis

Five musk deer species (genus Moschus) are distributed in China, and the present estimated numbers in the wild are between 220 000 and 320 000. Population size of musk deer has dropped significantly due to historical over-hunting and loss or degradation of their habitat. Musk deer farming, therefore, has become one of the most appropriate ways to protect and utilize musk deer resources. In China, musk deer farming and extracting musk from the captive musk deer have been reasonably successful since the early 1950s. At present three species of musk deer, namely forest (Moschus Berezovskii), alpine (M. sifanicus) and Siberian (M. moschiferus) musk deer are farmed in China and, of these, the forest musk deer is the main captive population. The present patterns of musk deer farming in China, however, need to be improved and developed into more economic and scientific modes in order to improve the rate of survival and reproduction, and to increase the production of musk.

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Monitoring vegetation net primary productivity (NPP) is very important for evaluating ecosystem health. However, the nonlinear characteristics of the vegetation NPP remain unclear in the six provinces along the Maritime Silk Road in China. In this study, using NDVI and meteorological data from 1982 to 2015, NPP was estimated with the Carnegie-Ames-Stanford Approach (CASA) model based on vegetation type dynamics, and its nonlinear characteristics were explored through the ensemble empirical mode decomposition (EEMD) method. The results showed that: (1) The total NPP in the changed vegetation types caused by ecological engineering and urbanization increased but decreased in those caused by agricultural reclamation and vegetation destruction, (2) the vegetation NPP was dominated by interannual variations, mainly in the middle of the study area, while by long-term trends, mainly in the southwest and northeast, (3) for most of the vegetation types, NPP was dominated by the monotonically increasing trend. Although vegetation NPP in the urban land mainly showed a decreasing trend (monotonic decrease and decrease from increase), there were large areas in which NPP increased from decreasing. Although vegetation NPP in the farmland mainly showed increasing trends, there were large areas that faced the risk of NPP decreasing; (4) dynamical changes of vegetation type by agricultural reclamation and vegetation destruction made the NPP trend monotonically decrease in large areas, leading to ecosystem degradation, while those caused by urbanization and ecological engineering mainly made the NPP increase from decreasing, leading to later recovery from early degradation. Our results highlighted the importance of vegetation type dynamics for accurately estimating vegetation NPP, as well as for assessing their impacts, and the importance of nonlinear analysis for deepening our understanding of vegetation NPP changes.