the Paired Land Use Experiments (PLUE) theory in driver identification of regional vegetation change

Vegetation change is one of the essential indices of global change. In the past 30 years, based on the remote sensing records, the whole world has shown an overall greening phenomenon, accompanied by regional browning. How to identify the drivers of regional-scale vegetation change, especially to distinguish between climate change and human activities remains a great challenge. Modeling studies show that the CO2 fertilization effect plays a dominant role, but the significant greening contribution of farmland areas at the global scale seems to indicate that human land management (LMC) activities have a huge impact. Methods can be divided into two categories: model and observation statistics. Models are easy to quantify contributions but lack descriptions of LMC processes, and regional-scale statistical methods are difficult to identify driving factors. This study proposes the theory of Paired Land Use Experiment (PLUE), which selects areas with large differences in land management and consistent climate change to achieve "control" of climate change and attribute the difference in vegetation change to on the LMC. The PLUE theory was applied in two selected regions around the world. First, the Khabur River plain on the border between Syria and Turkey was selected. The two countries occupy roughly the same area of the plain. The climate conditions on both sides are consistent with the changes, and the interannual time series correlation coefficient of the Enhanced Vegetation Index (EVI) after detrending exceeds 0.8 (p <0.01). For multi-year trends, this difference can be attributed to LMC. Combined with relevant reports on Syrian social development, social unrest has caused serious degradation of land management capabilities. Therefore, social unrest and occasional severe natural disasters have led to a continuous decline in land management capabilities in the region, further contributing to the "browning" of Syrian vegetation. Secondly, the Sanjiang Plain was selected. China and Russia roughly divided the plain into two, with farmland and temperate savannah as the main vegetation types on both sides. The temperature and precipitation changes in the two places were basically the same, and the leaf area index (LAI) showed a significant growth trend with the same magnitude. However, the seasonal characteristics of the LAI trend in the two regions are significantly different. Using the PLUE method, it can be seen that this difference is caused by land management, including the expansion of paddy fields and the increase in farmland management intensity (mechanization, pesticide and fertilizer application). At the same time, it is found that the climate residual method will give false conclusions in the attribution of interannual changes. In summary, the PLUE method can directly identify land management activities other than climate elements from observations at the regional scale, which is helpful for further research on the driving forces of long-term vegetation change trends.