基于MODIS数据设计的中国土地覆盖分类系统与应用研究

该文阐述了国内外主要土地覆盖分类系统及其土地覆盖产品在中国的表现,依据中国植被编码体系在MODIS数据试验的基础上,对现有国内土地覆盖分类系统进行了重新设计,包括7大类22个二级类别,并利用2001～2002年MODIS1km时间序列NDVI数据和多波段反射率光谱数据对中国区域进行了土地覆盖分类,结果显示分类产品能较为准确地描述中国区域土地覆盖的实际情况。     

Modelling soil erodibility in mountain rangelands of southern Kyrgyzstan

Soil erosion in mountain rangelands in Kyrgyzstan is an emerging problem due to vegetation loss caused by overgrazing. It is further exacerbated by mountain terrain and high precipitation values in Fergana range in the south of Kyrgyzstan. The main objective of this study was to map soil erodibility in the mountainous rangelands of Kyrgyzstan. The results of this effort are expected to contribute to the development of soil erodibility modelling approaches for mountainous areas. In this study, we mapped soil erodibility at two sites, both representing grazing rangelands in the mountains of Kyrgyzstan and having potentially different levels of grazing pressure. We collected a total of 232 soil samples evenly distributed in geographical space and feature space. Then we analyzed the samples in laboratory for grain size distribution and calculated soil erodibility values from these data using the Revised Universal Soil Loss Equation (RUSLE) K-factor formula. After that, we derived different terrain indices and ratios of frequency bands from ASTER GDEM and LANDSAT images to use as auxiliary data because they are among the main soil forming factors and widely used for prediction of various soil properties. Soil erodibility was significantly correlated with channel network base level (geographically extrapolated altitude of water channels), remotely sensed indices of short-wave infrared spectral bands, exposition, and slope degree. We applied multiple regression analysis to predict soil erodibility from spatially explicit terrain and remotely sensed indices. The final soil erodibility model was developed using the spatially explicit predictors and the regression equation and then improved by adding the residuals. The spatial resolution of the model was 30 m, and the estimated mean adjusted coefficient of determination was 0.47. The two sites indicated different estimated and predicted means of soil erodibility values (0.035 and 0.039) with a 0.05 significance level, which is attributed mainly to the considerable difference in elevation.     

A new approach and case study for estimating extent and rates of habitat loss for ecological communities

The pace and magnitude of biodiversity loss has led to wide recognition that efforts to conserve individual species must be complemented by assessment and planning at community and ecosystem levels. Emerging protocols for assessing the conservation status of communities include as central criteria the current extent, historical reduction and contemporary rate of decline in geographic distribution. Estimation of these parameters is confronted by methodological challenges, data limitations and uncertainties that may vary from case to case. We describe an approach to these issues comprising five steps: (1) classification of the community using an analysis of data from systematic ground surveys; (2) mapping to produce a contemporary baseline distribution (1980s); (3) interpolation to produce a historical distribution (pre-European settlement); (4) interpretation of satellite imagery to update the distribution (various dates up to 2004) and (5) assessment of change in extent over historical and contemporary time scales incorporating plausible bounds of uncertainty around best estimates. The bounds can be based on areas for which image interpretation produces uncertain diagnosis of clearing and differences between credible alternative base maps of the same area. We demonstrated the approach using a case study of Coolibah-Black Box Woodland, a declining semi-arid woodland community in Australia and found that 61% (plausible range 50-67%) of the woodland community had been cleared since European settlement and that during 1998-2004 the community continued to decline on average by 135.3(±21.7) km² each year, or 1.7(±0.3)% of each previous year’s distribution, apparently accelerating in recent years. Strengths of the approach include the use of biological data (cf. remote sensing) to distinguish the target assemblage from others, the use of historical and contemporary base lines to examine change over different time scales, and the use of bounded estimates to incorporate uncertainty into the assessment.     

Soil risk maps – Interpreting soils data for policy makers,agencies and industry

Surface runoff, erosion, compaction and the leaching of potential pollutants from land can degrade the soil resource and damage the water environment, reducing crop yields, causing loss of valuable nutrients and organic matter, together with increasing flood risk. Increasingly, it is recognized that scientific information must be translated into practical tools to change practices and protect the soil and water resource. Working alongside agencies in Scotland, we applied a suite of simple, transparent, rule-based models to identify areas most at risk of exporting sediment and pollutants that may degrade water quality based on field-scale (1:25,000) soil maps. The maps have been used by Scottish Environment Protection Agency, Scottish Water and Scottish Government to assess soil risks to waters from field to regional scale. The work brought scientists together with policy makers, agencies and the water industry to pool their knowledge to apply these practical tools for decision-making. It highlights the need to apply existing knowledge to answer salient questions. All three examples described show that providing the right type of information, which is based on fundamental soils data, can directly influence the implementation of policies, investment and monitoring decisions and provide evidence in support of government. However, this requires both researchers and agency scientists to develop skills as knowledge brokers and to normalize the use of soil data in everyday agency settings.     

基于样点的数字土壤属性制图方法及样点设计综述

土壤剖面数据与土壤类型图按照某种原则进行连接是目前获取土壤属性空间分布信息的主要方法,这种传统的土壤属性制图方法以土壤专家的“经验”和手工描绘为基础,耗费资本高、生产周期长.数字土壤制图通过借鉴先进的空间信息处理技术和高分辨率地形数据的优势,能够快速地获取高精度、高分辨率的土壤属性空间变化信息,是一种精细、高效、经济的土壤属性制图技术.本文详细介绍了基于样点进行数字土壤属性制图的3种方法:①基于空间自相关的方法:②基于空间自相关和土壤-环境关系混合相关的方法:③基于土壤-环境关系的方法.同时,为保证样点能够全面地捕捉到研究区内土壤属性空间变异特征,以上3种方法都对样点的数量、分布或典型性提出了较为严格的要求,即样点应具有全局代表性.因此,如何设计样点成为数字土壤属性制图中的一个重要问题.依据样点设计过程中是否能够整合已有样点,本文将样点设计方案分为采样设计方案和补样设计方案两种,并对其分别进行了详细的综述.     

一个水稻金黄色颖壳与节间基因的定位

在粳稻品种浙粳88种子经60Co γ射线辐照的后代中,筛选得到1个金黄色颖壳与节间基因突变体,将该突变体命名为浙粳88GH,该突变体的颖壳和茎间与野生型浙粳88相比具较明显的金黄色。遗传分析表明,该突变体性状受1对隐性核基因控制,暂将该突变基因命名为gold hull 6(gh6)。以该突变体与籼稻珍汕97B杂交的F₂作为定位群体,采用SSR分子标记和隐性群体分析法,将gh6基因初步定位在第2号染色体短臂端的分子标记RM3732和RM6378之间,遗传距离分别为21.2cM和28cM。然后,进一步扩大F₂群体将gh6基因定位在分子标记Indel3和Indel4之间约90kb内。     

水稻早衰突变体els-R7954的遗传分析和初步定位

为了深入研究水稻早衰机理,找到有效消除和延缓植株早衰的方法,本研究通过350Gy60Co-γ射线辐照水稻浙恢7954干种子,获得1份特异性水稻早衰突变体。观察该突变体生物学性状,发现苗期生长正常,分蘖末期叶片出现早衰现象,灌浆期整个植株枯黄,早衰现象非常明显,将其暂名为elsR7954(early leaf senescence)。遗传分析和基因定位发现,els-R7954受单隐性核基因控制,位于第2染色体SSR标记RM530和RM3774之间,距RM530约5.0c M。为进一步克隆该基因,丰富叶片早衰的分子机制奠定了一定基础,也为研究水稻早衰,最终提高产量和品质提供可能。     

小麦7D染色体数量性状基因定位和效应估计的研究

综合应用方差分析法、区间定位法和联合定位法将控制抽穗期、有效穗数、小穗数、５０粒重和单穗产量等５个性状的６个数量性状基因座（ＱＴＬ）定位在小麦７Ｄ染色体上。其中控制粒重的ＱＴＬ有２个。这些ＱＴＬ集中分布在着丝粒附近和染色体长臂的末端两个区域。效应估计结果表明多数ＱＴＬ的效应是微效的，控制同一个性状（粒重）的两个ＱＴＬ的效应几乎相等。比较３种ＱＴＬ定位法的分析结果，方差分析简单有效，且当染色体上只有     

Genetic and cytogenetic studies with a male sterile mutant of common wheat (Triticum aestivum)

Summary Genetic and cytogenetic studies were done on a male sterile mutant of the wheat variety Probus. Association of the 4A chromosome carrying the ms gene was studied in the F₁ of the male sterile Probus with Chinese Spring ditelo 4AS, with Transec and with line T4AS-DRS respectively. The presumption that the genetic male sterility of the mutant was due to a terminal deletion of the short arm of chromosome 4A could be confirmed.Linkage studies showed that the ms gene was at 17 map units from the dwarfing gene (Rht3) of Minister dwarf. This allows selection of short male sterile plants at the seedling stage.     

玉米籽粒突变体dek101的表型分析和精细定位

As the storage organ of maize, kernel development and accumulation of storage production directly determines maize yield and quality. In this study, a stable defective kernel mutant, named as defective kernel 101 (dek101), was identified during the development of double haploid (DH) lines in maize. The dek101 kernels displayed severely shrunk kernel appearance, significantly reduced kernel weight, lethal embryo, defective endosperm and were incapable of germinating. The dek101 showed obvious developmental abnormalities at 12 days after pollination (DAP). The fresh weight, dry weight and volume of the kernels were no longer increased after 21 DAP. Scanning electron microscopy (SEM) observation revealed that the starch granules of dek101 were significantly smaller compared with wild-type kernels. Genetic analysis demonstrated that the mutant trait was controlled by a recessive single gene. Using 441 F₂ individuals and 1648 F₃ individuals, dek101 was narrowed down to a genomic region of about 300 kb between the InDel marker IDP2182 and IDP4600 on chromosome 1, which contains five predicted genes. These results laid the foundation for mining functional genes related to maize kernel development and deciphering the mechanism of grain development.