Reconstructing Spatial Distribution of Historical Cropland in China′s Traditional Cultivated Region: Methods and Case Study

As an important part of land use/cover change(LUCC), historical LUCC in long time series attracts much more attention from scholars. Currently, based on the view of combining the overall control of cropland area and ′top-down′ decision-making behaviors, here are two global historical land-use datasets, generally referred as the Sustainability and the Global Environment datasets(SAGE datasets) and History Database of the Global Environment datasets(HYDE datasets). However, at the regional level, these global datasets have coarse resolutions and inevitable errors. Considering various factors that influenced cropland distribution, including cropland connectivity and the limitation of natural and human factors, this study developed a reconstruction model of historical cropland based on constrained Cellular Automaton(CA) of ′bottom-up′. Then, an available labor force index is used as a proxy for the amount of cropland to inspect and calibrate these spatial patterns. Applied the reconstruction model to Shandong Province, we reconstructed its spatial distribution of cropland during 8 periods. The reconstructed results show that: 1) it is properly suitable for constrained CA to simulate and reconstruct the spatial distribution of cropland in traditional cultivated region of China; 2) compared with ′SAGE datasets′ and ′HYDE datasets′, this study have formed higher-resolution Boolean spatial distribution datasets of historical cropland with a more definitive concept of spatial pattern in terms of fractional format.

Calculation of Ecological Compensation Standards for the Kuancheng Traditional Chestnut Cultivation System

Kuancheng Traditional Chestnut Cultivation System is located in the Beijing-Tianjin-Hebei Water Containment Function Area.The Traditional Chestnut Cultivation System is characterized by agroforestry compound,and some studies have shown that the compound planting of chestnut has better ecological benefits than the single chestnut planting mode.However,most of the local farmers in Kuancheng are mainly engaged in single chestnut cultivation.Through ecological compensation,farmers are being encouraged to change their chestnut planting mode,which can achieve the purpose of inheriting China’s important agricultural heritage and improving the ecological benefits.This paper introduces preference coefficients to correct for opportunity costs,and through interviews and questionnaires,we obtained the input and output of the single chestnut cultivation,chestnut-maitake,chestnut-millet,and chestnut-chicken and the income of laborers working outside the home in the Kuancheng area.Through analysis and calculation,we obtained the following results:(1)Although the net income of the three chestnut composite modes is higher,their economic input is higher than that of a single chestnut planting mode,and the return on unit investment is lower.(2)The average income of young and middle-aged workers who work outside is higher than that of the local farming industry,so the local chestnut agroforestry plantation has a higher opportunity cost.(3)The final calculation shows that the chestnut-chicken agroforestry operation mode needs no compensation,the chestnut-maitake plantation mode is compensated at least 1608.5 USD ha^(-1) yr^(-1),and the minimum compensation for the chestnut-millet plantation mode is 198.3 USD ha^(-1) yr^(-1),which can guarantee that farmers receive the full value of their creations.Ultimately,farmers are incentivized to revive the traditional agroforestry production mode to achieve both economic and ecological benefits while inheriting agricultural heritage.

Comparisons of cropland area from multiple datasets over the past 300 years in the traditional cultivated region of China

Land use/cover change is an important parameter in the climate and ecological simulations. Although they had been widely used in the community, SAGE dataset and HYDE dataset, the two representative global historical land use datasets, were little assessed about their accuracies in regional scale. Here, we carried out some assessments for the traditional cultivated region of China （TCRC） over last 300 years, by comparing SAGE2010 and HYDE （v3.1） with Chinese Historical Cropland Dataset （CHCD）. The comparisons were performed at three spatial scales： entire study area, provincial area and 60 km by 60 km grid cell. The results show that （1） the cropland area from SAGE2010 was much more than that from CHCD moreover, the growth at a rate of 0.51% from 1700 to 1950 and -0.34% after 1950 were also inconsistent with that from CHCD. （2） HYDE dataset （v3.1） was closer to CHCD dataset than SAGE dataset on entire study area. However, the large biases could be detected at provincial scale and 60 km by 60 km grid cell scale. The percent of grid cells having biases greater than 70% （〈-70% or 〉70%） and 90% （〈-90% or 〉90%） accounted for 56%-63% and 40%-45% of the total grid cells respectively while those having biases range from -10% to 10% and from -30% to 30% account for only 5%-6% and 17% of the total grid cells respectively. （3） Using local historical archives to reconstruct historical dataset with high accuracy would be a valu- able way to improve the accuracy of climate and ecological simulation.

Gridded reconstruction of the population in the traditional cultivated region of China from 1776 to 1953

Using modern census and environmental factor data,this study first identified the environmental factors that significantly affect the population distribution through Geodetector analysis and then constructed a population spatial distribution model based on the random forest regression algorithm.Finally,with this model and historical population data that were examined and corrected by historians,gridded population distributions with a spatial resolution of 10 km by 10 km in the traditional cultivated region of China(TCRC,hereafter)were reconstructed for six time slices from 1776 to 1953.Using the reconstruction dataset,the spatiotemporal characteristics of the population distribution were depicted.The results showed that(1)the environmental factors that significantly affected the population density differences among counties in the TCRC mainly consisted of elevation,slope,relief amplitude,distances to the nearest prefectural and provincial capitals,distance to the nearest river and the climatology moisture index.(2)Using the census data of 1934 counties in the TCRC in 2000 and the abovementioned environmental factor data,a random forest regression algorithm-based population spatial distribution model was constructed.Its determination coefficient(R^(2))is 0.81.In 88.4%of the counties(districts),the relative errors of the model predictions were less than 50%.(3)From 1776 to 1953,the total population in the study area showed an uptrend.Prior to 1851,the population increased mainly in the Yangtze River Delta.During this period,the number of grid cells in which the population densities were greater than 500 persons per km^(2) increased from 292 to 683.From 1851 to 1953,the population increased extensively across the study area.In the North China Plain and the Pearl River Delta,the number of grid cells in which the population densities were greater than 500 persons per km^(2) increased from 36 to 88 and from 4 to 35,respectively.The spatial clustering pattern of the population distribution varied temporally.The potential reasons included the shifts in economic development hot spots,traditional beliefs,wars,famine,and immigration policies.(4)Between our reconstructions and the HYDE dataset,there are large differences in the data sources,selected environmental factors and modeling methods.As a consequence,in comparison to our reconstructions,there were fewer populations in the eastern area and more populations in the western area from 1776 to 1851 and more populations in urban areas and fewer populations in rural areas after 1851 in the HYDE dataset.