Shicheng Li

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 valuable way to improve the accuracy of climate and ecological simulation.

Reconstructed cropland in the mid-eleventh century in the traditional agricultural area of China: implications of comparisons among datasets

Reconstructions of historical cropland area and spatial distribution are necessary for studying human effects on the environment due to agricultural development. To understand the current status of reconstructions of cropland area and its spatial distribution in the mid-eleventh century in the traditional agricultural area of China, we compared three available datasets: the historic cropland inventories-based HE dataset, the population-based History Database of the Global Environment (HYDE) dataset, and the PJ dataset. The results indicate that the HYDE and PJ datasets estimated the regional mean cropland area fraction (a ratio of cropland area to total land area, hereafter, CAF) for the study area to be 0.12 and 0.09, respectively, both of which were lower than the HE estimation of 0.18. Moreover, both the HYDE and PJ datasets have a poor ability to capture the spatial distribution of the historical CAF. The HYDE dataset overestimated the cropland area in North China and underestimated the cropland area in the Yangtze River reach. The HYDE dataset also overestimated the cropland area along the great rivers in North China. The PJ dataset underestimated the cropland area in the old agricultural area and overestimated the cropland area in the relatively new agricultural area. These incorrect spatial distributions from the HYDE and PJ datasets mainly resulted from the underestimation of the historical population and an incorrect approach for the spatial allocation of cropland within China. The incorrect approach was mainly derived from a poor understanding of the historic spatial distribution of cropland. Using the expert knowledge of local historians may be an effective method to reduce the uncertainties in the global historic cropland reconstruction.

Reconstruction of cropland area and spatial distribution in the mid-Northern Song Dynasty (AD1004-1085)

To understand historical human-induced land cover change and its climatic effects, it is necessary to create historical land use datasets with explicit spatial information. Using the taxes-cropland area and number of families compiled from historical documents, we estimated the real cropland area and populations within each Lu (a province-level political region in the Northern Song Dynasty) in the mid-Northern Song Dynasty (AD1004-1085). The estimations were accomplished through analyzing the contemporary policies of tax, population and agricultural development. Then, we converted the political region-based cropland area to geographically explicit grid cell-based fractional cropland at the cell size of 60 km by 60 km. The conversion was based on calculating cultivation suitability of each grid cell using the topographic slope, altitude and population density as the independent variables. As a result, the total area of cropland within the Northern Song territory in the 1070s was estimated to be about 720 million mu (Chinese area unit, 1 mu = 666.7 m2), of which 40.1% and 59.9% occurred in the north and south respectively. The population was estimated to be about 87.2 million, of which 38.7% and 61.3% were in the north and south respectively, and per capita cropland area was about 8.2 mu. The national mean reclamation ratio (i.e. ratio of cropland area to total land area; RRA hereafter for short) was bout 16.6%. The plain areas, such as the North China Plain, the middle and lower reaches of the Yangtze River, Guanzhong Plain, plains surrounding the Dongting Lake and Poyang Lake and Sichuan Basin, had a higher RRA, being mostly over 40%; while the hilly and mountainous areas, such as south of Nanling Mountains, the southwest regions (excluding the Chengdu Plain), Loess Plateau and southeast coastal regions, had a lower RRA, being less than 20%. Moreover, RRA varied with topographic slope and altitude. In the areas of low altitude (⩽250 m), middle altitude (250–100 m) and high altitude (1000–3500 m), there were 443 million, 215 million and 64 million mu of cropland respectively and their regional mean RRAs were 27.5%, 12.6% and 7.2% respectively. In the areas of flat slope, gentle slope, medium slope and steep slope, there were 116 million, 456 million, 144 million and 2 million mu of cropland respectively and their regional mean RRAs were 34.6%, 20.7%, 8.5% and 2.3% respectively.

Combining the least cost path method with population genetic data and species distribution models to identify landscape connectivity during the late Quaternary in Himalayan hemlock

Abstract Himalayan hemlock (Tsuga dumosa) experienced a recolonization event during the Quaternary period; however, the specific dispersal routes are remain unknown. Recently, the least cost path (LCP) calculation coupled with population genetic data and species distribution models has been applied to reveal the landscape connectivity. In this study, we utilized the categorical LCP method, combining species distribution of three periods (the last interglacial, the last glacial maximum, and the current period) and locality with shared chloroplast, mitochondrial, and nuclear haplotypes, to identify the possible dispersal routes of T. dumosa in the late Quaternary. Then, both a coalescent estimate of migration rates among regional groups and establishment of genetic divergence pattern were conducted. After those analyses, we found that the species generally migrated along the southern slope of Himalaya across time periods and genomic makers, and higher degree of dispersal was in the present and mtDNA haplotype. Furthermore, the direction of range shifts and strong level of gene flow also imply the existence of Himalayan dispersal path, and low area of genetic divergence pattern suggests that there are not any obvious barriers against the dispersal pathway. Above all, we inferred that a dispersal route along the Himalaya Mountains could exist, which is an important supplement for the evolutionary history of T. dumosa. Finally, we believed that this integrative genetic and geospatial method would bring new implications for the evolutionary process and conservation priority of species in the Tibetan Plateau.

Crop cover reconstruction and its effects on sediment retention in the Tibetan Plateau for 1900–2000

Geographically explicit historical land use and land cover datasets are increasingly required in studies of climatic and ecological effects of human activities. In this study, using historical population data as a proxy, the provincial cropland areas of Qinghai province and the Tibet Autonomous Region (TAR) for 1900, 1930, and 1950 were estimated. The cropland areas of Qinghai and the TAR for 1980 and 2000 were obtained from published statistical data with revisions. Using a land suitability for cultivation model, the provincial cropland areas for the 20th century were converted into crop cover datasets with a resolution of 1 × 1 km. Finally, changes of sediment retention due to crop cover change were assessed using the sediment delivery ratio module of the Integrated Valuation of Ecosystem Services and Trade-offs (In- VEST) model (version 3.3.1). There were two main results. (1) For 1950–1980 the fractional cropland area increased from 0.32% to 0.48% and land use clearly intensified in the Tibetan Plateau (TP), especially in the Yellow River–Huangshui River Valley (YHRV) and the midstream of the Yarlung Zangbo River and its two tributaries valley (YRTT). For other periods of the 20th century, stability was the main trend. (2) For 1950–1980, sediment export increased rapidly in the Minhe autonomous county of the YHRV, and in the Nianchu River and Lhasa River basins of the YRTT, which means that sediment retention clearly decreased in these regions over this period. The results of this assessment provide scientific support for conservation planning, development planning, or restoration activities.

Comparison of changes in land use and land cover in China and the USA over the past 300 years

Comparative studies of changes in land use and land cover between different countries over a long time-scale are helpful in understanding the processes and driving forces of these changes in different situations. We compared and analyzed the temporal and spatial characteristics of cropland, forest and grassland between China’s mainland and the conterminous USA over the past 300 years. We found that, over the past 300 years, the area of cropland showed an overall increasing trend both in China and in the USA. In China, the area of cropland increased by about 79.46×104 km2 from 1661 to the 1980s, and the per capita cropland decreased from 0.37×104 m2 in 1685 to 0.10×104 m2 in 2000. For the USA, the area of cropland increased by 190.87×104 km2 between 1700 and 1950. The per capita cropland area of each time slice for the past 300 years was greater than 0.60×104 m2 and the maximum value was 2.01×104 m2 in 1890. As a result of the expansion in land reclamation, the forest and grassland areas of the USA have decreased by about 136.98×104 km2 and 136.98×104 km2, respectively, over the past 300 years; the corresponding values for China are about 89.73×104 km2 and 40.00×104 km2, respectively. In terms of the spatial patterns, the expansion in cropland in China mainly occurred in the border areas (including the northeast, southwest and Inner Mongolia) and in the hilly areas. Cropland expansion in the USA mainly occurred in the mid-west regions. In China, population growth is the most important driving factor in changes in land use and land cover, whereas in the USA, government policy plays the most significant role.

Spatiotemporal Patterns of Vegetation Greenness Change and Associated Climatic and Anthropogenic Drivers on the Tibetan Plateau during 2000–2015

Alpine vegetation on the Tibetan Plateau (TP) is known to be sensitive to both climate change and anthropogenic disturbance. However, the magnitude and patterns of alpine vegetation dynamics and the driving mechanisms behind their variation on the TP remains under debate. In this study, we used updated MODIS Collection 6 Normalized Difference Vegetation Index (NDVI) from the Terra satellite combined with linear regression and the Break for Additive Season and Trend model to reanalyze the spatiotemporal patterns of vegetation change on the TP during 2000–2015. We then quantified the responses of vegetation variation to climatic and anthropogenic factors by coupling climatic and human footprint datasets. Results show that growing season NDVI (GNDVI) values increased significantly overall (0.0011 year−1, p < 0.01) during 2000–2015 and that 70.37% of vegetated area on the TP (23.47% significantly with p < 0.05) exhibited greening trends with the exception of the southwest TP. However, vegetation greenness experienced trend shifts from greening to browning in half of the ecosystem zones occurred around 2010, likely induced by spatially heterogeneous temporal trends of climate variables. The vegetation changes in the northeastern and southwestern TP were water limited, the mid-eastern TP exhibited strong temperature responses, and the south of TP was driven by a combination of temperature and solar radiation. Furthermore, we found that, to some extent, anthropogenic disturbances offset climate-driven vegetation greening and aggravated vegetation browning induced by water deficit. These findings suggest that the impact of anthropogenic activities on vegetation change might not overwhelm that of climate change at the region scale.

Spatiotemporal changes in agricultural land cover in Nepal over the last 100 years

In order to advance land use and land cover change (LUCC) research in Nepal, it is essential to reconstruct both the spatiotemporal distribution of agricultural land cover as well as scenarios that can explain these changes at the national and regional levels. Because of rapid population growth, the status of agricultural land in Nepal has changed markedly over the last 100 years. Historical data is used in this study, encompassing soils, populations, climatic variables, and topography. Data were revised to a series of 30 m grid cells utilized for agricultural land suitability and allocation models and were analyzed using a suite of advanced geographical tools. Our reconstructions for the spatiotemporal distribution of agricultural land in Nepal reveal an increasing trend between 1910 and 2010 (from 151.2 × 102 km2 to 438.8 × 102 km2). This expanded rate of increase in agricultural land has varied between different eco, physiographic, and altitudinal regions of the country, significantly driven by population changes and policies over the period of this investigation. The historical dataset presented in this paper fills an existing gap in studies of agricultural land change and can be applied to other carbon cycle and climate modeling studies, as well as to impact assessments of agricultural land change in Nepal.