Spatially explicit reconstruction of cropland cover for China over the past millennium

Reconstructing historical land use and land cover change using explicit temporal,quantitative,and spatial information is not only the prerequisite for simulating long-term climate change and ecological effects but is also a scientific basis for comprehensively understanding the process and mechanism of anthropogenic land use alterations.Considering changes in historical borders and administrative divisions,a provincial cropland area dataset for China over the past millennium was created on the basis of existing estimations since the Song Dynasty.Land suitability for cultivation was then assessed by incorporating altitude,slope,soil texture,and the maximum potential productivity of climate.Subsequently,a gridding allocation model for cropland was constructed,and the provincial cropland area for 24 years over the past millennium was allocated into grids with a resolution of 10 km.The cropland area in China increased from 3.71×10^(7)ha in AD 1000 to 12.92×10^(7)ha in AD 1999,with a peak of 13.50×10^(7)ha in AD 1980.The total cropland area in China showed fluctuating increasing trends that can be divided into three phases:fluctuation without notable net change for AD 1000–1290,slow increase for AD 1290–1661,and rapid increase for AD 1661–1999.Spatially,cropland intensified in the middle-lower reaches of the Yellow and Yangtze Rivers and expanded to mountainous and frontier areas over the last millennium.Specifically,over the entire period,the fractional cropland areas(FCAs)in the middle-lower reaches of the Yellow and Yangtze Rivers increased by 1.4 and 0.8 times,respectively.Since the mid-Qing Dynasty,large-scale land reclamation expanded to areas of low reclamation in southwest and northeast China.The FCAs for southwest and northeast China increased from 2.13%and 0.55%in AD 1661 to 18.00%and 26.61%in AD 1999,respectively.For AD 1661–1999,the proportion of cropland increased by 55%in the hills and low mountains and 27%in the middle and high mountains.The comparison with remote sensing cropland data shows that the grid cells with absolute differences of 0–10%accounted for 70.35%of all grid cells,while grids with differences exceeding 60%accounted for only 0.83%.This finding indicates that the reconstruction method is feasible,and the reconstruction results objectively reveal the historical spatiotemporal changes in cropland.

Evaluating the accuracy of Chinese pasture data in global historical land use datasets

Global historical land use datasets are widely used in global environmental change studies; however, uncertainties in the included pasture data have not been evaluated. In this study, using trend, relative difference ratio(RDR), and spatial comparisons, we evaluated the accuracy of China pasture data in the HYDE(versions 3.1 and 3.2), SAGE, and PJ datasets using historical document-based reconstructions, including the land use datasets for China covering 1935–1997(hereafter Ge-dataset)and Northeast China covering the 1700 s–2000(hereafter Ye-dataset), and the satellite-based China's Land-Use/cover Datasets(CLUDs) for 1980–2015. Four important results were obtained.(1) China pasture area in the HYDE, SAGE, and PJ datasets and grassland area in the Ge-dataset, Ye-dataset, and CLUDs show both disparate trends and large differences in absolute values.(2)Spatially, 50.9%, 52.8%, and 63.0% pasture/grassland grids in 2000 had RDRs greater than 60% between HYDE3.1, HYDE3.2,and SAGE datasets, and CLUDs, respectively. The percentage of grids with RDRs less than 20% were 24.9%, 26.7%, and 16.0%,respectively.(3) Based on HYDE3.2, the spatial distribution of pasture in Northeast China over the last 300 year has expanded,which is in contrast to the results from the Ye-dataset, which shows the spatial distribution of grassland shrinking because of human reclamation activities.(4) The large contrasts between the global datasets and Chinese native datasets are due to differences in pasture/grassland definitions, land use practices, and spatial reconstruction methods.