1961—2010年中国气候生产潜力时空格局变化及其潜在可承载人口分析

以气温、降水格点数据为基础,采用Thornthwaite Memorial模型计算了中国气候生产潜力(CPP),并从气候的角度估算了耕地上气候资源潜在可承载的人口数,以便增强了解气候变化的影响及气候资源最大人口支撑能力。结果表明:1961—2010年中国CPP总体呈突变性增加趋势,1987年为突变点,年最低、最高及平均值分别为689. 18、814. 56和744. 05 g·m^-2·a^-1。空间上呈现出从西北向东南逐渐递增的带状分布,其中高值区主要分布在华南大部,最高值达2103. 56 g·m^-2·a^-1;低值区主要分布在西、北部地区,最低值为39. 28 g·m^-2·a^-1。2001—2010年中国大部分地区CPP年平均值相对于1961—2010年多年平均值变化幅度不大,变化比例高的地区基本上分布于中国西、北部,其中增加的区域达82%,主要分布在华东地区、新疆西部、西藏北部及青海大部,远大于缩减的区域(17%)。1995—2010年,基于公里网格的耕地气候潜在可承载人口为46—2180人·km^-2,全国平均值最低的年份为1130人·km^-2,对应的实际人口为0—49729人·km^-2,全国平均值均不高于137人·km^-2;全国实际总人口为11. 43—13. 04亿,耕地气候潜在可承载总人口为19. 72—20. 22亿,前后比值为58%—65%。这表明,中国耕地生产力未达到气候生产潜力,尚有一定的开发潜力;实际人口在中国大部分地区均没有超出气候资源潜在可承载的最大人口,然而在少数省市(如生态环境脆弱的青海省以及经济发达的大城市及沿海地区)已超出。     

Integration of remote sensing,county-level census,and machine learning for century-long regional cropland distribution data reconstruction

The Lower Mississippi Alluvial Valley (LMAV) was home to about ten million hectare bottomland hardwood (BLH) forests in the Southern U.S. It experienced over 80 % area loss of the BLH forests in the past centuries and large-scale afforestation in recent decades. Due to the lack of a high-resolution cropland dataset, impacts of land use change (LUC) on the LMAV ecosystem services have not been fully understood. In this study, we developed a novel framework by integrating the machine learning algorithm, county-level agricultural census, and satellite-based cropland products to reconstruct the LMAV cropland distribution during 1850–2018 at a 30-m resolution. Results showed that the LMAV cropland area increased from 0.78 × 10⁴ km² in 1850 to 6.64 × 10⁴ km² in 1980 and then decreased to 6.16 × 10⁴ km² in 2018. Cropland expansion rate was the largest in the 1960s (749 km² yr⁻¹) but decreased rapidly thereafter, whereas cropland abandonment rate increased substantially in recent decades with the largest rate of 514 km² yr⁻¹ in the 2010s. Our dataset has three notable features: (1) the depiction of fine spatial details, (2) the integration of the county-level census, and (3) the inclusion of a machine-learning algorithm trained by satellite-based land cover product. Most importantly, our dataset well captured the continuous increasing trend in cropland area from 1930–1960, which was misrepresented by other cropland datasets reconstructed from the state-level census. Our dataset would be important to accurately evaluate the impacts of historical deforestation and recent afforestation efforts on regional ecosystem services, attribute the observed hydrological changes to anthropogenic and natural driving factors, and investigate how the socioeconomic factors control regional LUC pattern. Our framework and dataset are crucial to developing managerial and policy strategies for conserving natural resources and enhancing ecosystem services in the LMAV.     

Converting Brazil's pastures to cropland: An alternative way to meet sugarcane demand and to spare forestlands

Brazil seeks to rapidly increase its agricultural production to meet future demands, especially for sugarcane, which is an agricultural commodity and a biofuel source. In this paper, we explore how to achieve this increase without compromising existing forestlands. We propose that it is possible to substantially expand sugarcane production in Brazil while avoiding further environmental losses and the indirect land use changes often associated with them, such as deforestation. This task could be accomplished by converting existing pasturelands with agricultural potential into cropland. A great deal of pastureland exists in Brazil. Thus, we addressed the following questions in this study: (1) where are the most suitable pasturelands for sugarcane located geographically and (2) what potential do these pasturelands have for sugarcane production regarding their physical suitability and other significant factors, such as infrastructure availability and socioeconomic factors. We conducted a land suitability analysis using a spatial location model based on multicriteria decision-making and geographic information systems (GIS) to identify the cultivated pasturelands most suitable for conversion to sugarcane production in Brazil. “What if” scenarios were built to determine how changes in the subjectively derived weights of the priority criteria would modify the spatial distribution of the suitability classes relative to the MCDA model and demonstrate the robustness of the crop suitability assessment. The most suitable pastureland areas for conversion to sugarcane production were predominantly located in Minas Gerais, São Paulo, Paraná, Goiás, Mato Grosso do Sul, Mato Grosso and Pará. These zones have large contiguous areas of pasture with moderate and high agricultural potentials for sugarcane production. The total estimated area of cultivated pasturelands with moderate or high suitability for sugarcane production was 50 million hectares, which is much larger than the area currently used for sugarcane production in Brazil.     

Global rain-fed,irrigated, and paddy croplands: A new high resolution map derived from remote sensing,crop inventories and climate data

Irrigation accounts for 70% of global water use by humans and 33–40% of global food production comes from irrigated croplands. Accurate and timely information related to global irrigation is therefore needed to manage increasingly scarce water resources and to improve food security in the face of yield gaps, climate change and extreme events such as droughts, floods, and heat waves. Unfortunately, this information is not available for many regions of the world. This study aims to improve characterization of global rain-fed, irrigated and paddy croplands by integrating information from national and sub-national surveys, remote sensing, and gridded climate data sets. To achieve this goal, we used supervised classification of remote sensing, climate, and agricultural inventory data to generate a global map of irrigated, rain-fed, and paddy croplands. We estimate that 314 million hectares (Mha) worldwide were irrigated circa 2005. This includes 66 Mha of irrigated paddy cropland and 249 Mha of irrigated non-paddy cropland. Additionally, we estimate that 1047 Mha of cropland are managed under rain-fed conditions, including 63 Mha of rain-fed paddy cropland and 985 Mha of rain-fed non-paddy cropland. More generally, our results show that global mapping of irrigated, rain-fed, and paddy croplands is possible by combining information from multiple data sources. However, regions with rapidly changing irrigation or complex mixtures of irrigated and non-irrigated crops present significant challenges and require more and better data to support high quality mapping of irrigation.     

Measuring land-use and land-cover change using the U.S. department of agriculture’s cropland data layer: Cautions and recommendations

Monitoring agricultural land is important for understanding and managing food production, environmental conservation efforts, and climate change. The United States Department of Agriculture's Cropland Data Layer (CDL), an annual satellite imagery-derived land cover map, has been increasingly used for this application since complete coverage of the conterminous United States became available in 2008. However, the CDL is designed and produced with the intent of mapping annual land cover rather than tracking changes over time, and as a result certain precautions are needed in multi-year change analyses to minimize error and misapplication. We highlight scenarios that require special considerations, suggest solutions to key challenges, and propose a set of recommended good practices and general guidelines for CDL-based land change estimation. We also characterize a problematic issue of crop area underestimation bias within the CDL that needs to be accounted for and corrected when calculating changes to crop and cropland areas. When used appropriately and in conjunction with related information, the CDL is a valuable and effective tool for detecting diverse trends in agriculture. By explicitly discussing the methods and techniques for post-classification measurement of land-cover and land-use change using the CDL, we aim to further stimulate the discourse and continued development of suitable methodologies. Recommendations generated here are intended specifically for the CDL but may be broadly applicable to additional remotely-sensed land cover datasets including the National Land Cover Database (NLCD), Moderate Resolution Imaging Spectroradiometer (MODIS)-based land cover products, and other regional, national, and global land cover classification maps.     

Monitoring agricultural cropping patterns across the Laurentian Great Lakes Basin using MODIS-NDVI data

The Moderate Resolution Imaging Spectrometer (MODIS) Normalized Difference Vegetation Index (NDVI) 16-day composite data product (MOD12Q) was used to develop annual cropland and crop-specific map products (corn, soybeans, and wheat) for the Laurentian Great Lakes Basin (GLB). The crop area distributions and changes in crop rotations were characterized by comparing annual crop map products for 2005, 2006, and 2007. The total acreages for corn and soybeans were relatively balanced for calendar years 2005 (31,462 km² and 31,283 km², respectively) and 2006 (30,766 km² and 30,972 km², respectively). Conversely, corn acreage increased approximately 21% from 2006 to 2007, while soybean and wheat acreage decreased approximately 9% and 21%, respectively. Two-year crop rotational change analyses were conducted for the 2005–2006 and 2006–2007 time periods. The large increase in corn acreages for 2007 introduced crop rotation changes across the GLB. Compared to 2005–2006, crop rotation patterns for 2006–2007 resulted in increased corn–corn, soybean–corn, and wheat–corn rotations. The increased corn acreages could have potential negative impacts on nutrient loadings, pesticide exposures, and sediment-mediated habitat degradation. Increased in US corn acreages in 2007 were related to new biofuel mandates, while Canadian increases were attributed to higher world-wide corn prices. Additional study is needed to determine the potential impacts of increases in corn-based ethanol agricultural production on watershed ecosystems and receiving waters.     

升温1.5℃和2.0℃情景下中亚地区干旱耕地暴露度研究

基于CMIP5中的5个全球气候模式统计降尺度的降水、最高和最低气温等数据,利用标准降水蒸发指数（SPEI）和强度-面积-持续时间（IAD）方法识别全球升温1.5℃与2.0℃情景下中亚地区干旱事件,结合30 m分辨率土地利用数据,探讨中亚干旱事件的演变及耕地暴露度变化。结果表明：相比基准期（1986—2005年),中亚地区的降水和潜在蒸发量均有所增加;全球升温1.5℃与2.0℃情景下,中亚地区的干旱事件频次、强度和面积均将增加,其中重旱和极旱事件的频次和影响面积大幅上升,而中旱事件的频次和影响面积持续下降;1986—2005年中亚地区年均干旱耕地暴露度约11.5万km2,全球升温1.5℃和2.0℃情景下,干旱耕地暴露度将分别上升到17.9万km2和28.6万km2,且暴露在极旱下的耕地面积增加最明显。全球升温1.5℃与2.0℃情景下,增加的干旱事件将会严重威胁当地农业生产和粮食安全,中亚地区需对干旱事件采取长期的减缓与适应措施。     

Population growth and loss of arable land

I discuss the loss of cropland in developing countries in connection with the ongoing land conversion caused by the growing population and socio-economic development, resulting in an increased demand for housing, industry, infrastructure, etc.Based on assumptions about the required space per capita for other purposes than agriculture, the portion of this area that is removed from presently used cropland, and the quality of the available land reserves, the required demand for land reserves has been calculated.The main conclusions are that during the next three decades (i) the loss of cropland is likely to be within the range 30–60 Mha, (ii) the reserve land utilized will be about 100–200 Mha, and (iii) the reserve land still in use after 30 years, about 50–100 Mha.     

SEDIMENT DAMAGES AND RECENT TRENDS IN THE UNITED STATES

lINTRODUCTIONWeoftenhavethepercepti0nthatsedimentisthebr0wnishoryell0wishcoloringinrunoffwater,thatlooksunpleasant,buteventually"g0esaway,"downstream,unseen.Butsedimentisn0tonlyaestheticallyunpleasant,itisalsoacarrierofpotentialchemicalc0ntaminants,fillsupwaterb0dies,andcausesphysicaldamaget0farmland,wildlife,andwatertreatmentsystemsandpowergenefat0rs.ThepurposeofthispaPeristoprovidean0verallperspectiveonthemagnitudeandtrendsofsedimelltasap0llutritintheUnitedStates.2CURRENTKNOWLEDG…     

Simulated effects of cropland expansion on seasonal temperatures over China

Human activities result in deforestation, expansion of cropland, grassland degradation, urbanization and other large-scale land use/cover change; among these, cropland expansion is one of the most important processes. To understand the effects of cropland expansion on seasonal temperatures over China, two 21-year simulations (spanning January 1, 1980–December 31, 2000), using the Regional Integrated Environmental Model System (RIEMS 2.0), were performed. The two simulations comprised current realistic land use/cover patterns and the previous vegetation cover without crop expansion, to investigate the impact of crop expansion on seasonal temperatures over China. The results showed that due to cropland expansion: (1) the most obvious changes occurred in the maximum temperatures, followed by the mean surface air temperatures, and the minimum temperatures were the least affected; (2) the summer mean maximum temperatures decreased in most parts of eastern China, and the temperatures changed significantly in most parts of northeast China, north China and central China (p < 0.05); (3) the surface air temperatures, maximum temperatures and minimum temperatures in summer decreased in the different regions by between −0.03 and −0.76 °C (the greatest temperature changes occurred in southwest China, and the smallest were in northeast China); (4) the net radiation flux and latent heat flux increased, while the sensible flux decreased, when semi-desert vegetation was replaced by dry land crops, in both summer and winter seasons, and the converse occurred when irrigated crops were replaced by dry land crops. In addition, the net radiation flux and sensible heat flux decreased, and the latent heat flux increased when short grass and tall grass were replaced dry land crops, as well as when dry land crops were replaced by irrigated crops.