International Geosphere-Biosphere Programme Research Articles

Evaluation of the 2010 MODIS Collection 5.1 Land Cover Type Product over China

Although the MODIS Collection 5.1 Land Cover Type (MODIS v5.1 LCT) product is one of the most recent global land cover datasets and has the shortest updating cycle, evaluations regarding this collection have not been reported. Given the importance of evaluating global land cover data for producers and potential users, the 2010 MODIS v5.1 LCT product IGBP (International Geosphere-Biosphere Programme) layer was evaluated based on two grid maps at scales of 100-m and 500-m,which were derived by rasterizing the 2010 data from the national land use/cover database of China (NLUD-C). This comparison was conducted based on a new legend consisting of nine classes constructed based on the definitions of classes in the IGBP and NLUD-C legends. The overall accuracies of the aggregated classification data were 64.62% and 66.42% at the sub-pixel and pixel scales, respectively. These accuracies differed significantly in different regions. Specifically, high-quality data were obtained more easily for regions with a single land cover type, such as Xinjiang province and the northeast plain of China. The lowest accuracies were obtained for the middle of China, including Ningxia, Shaanxi, Chongqing, Yunnan and Guizhou. At the sub-pixel scale, relatively high producer and user accuracies were obtained for cropland, grass and barren regions; the highest producer accuracy was obtained for forests, and the highest user accuracy was obtained for water bodies. Shrublands and wetlands were associated with low producer and user accuracies at the sub-pixel and pixel scales, of less than 10%. Based on dominant-type reference data, the errors were classified as mixed-pixel errors and labeling errors. Labeling errors primarily originated from misclassification between grassland and barren lands. Mixed pixel errors increased as the pixel diversity increased and as the percentage of dominant-type sub-pixels decreased. Overall, mixed pixels were sources of error for most land cover types other than grassland and barren lands; whereas labeling errors were more prevalent than mixed pixel errors when considering all of the land cover data over China, due to the large amount of misclassification between the pure pixels of grassland and barren lands. Next, the accuracy of cropland/natural vegetation mosaics was assessed based on the qualitative (a mosaic of croplands, forests, shrublands, and grasslands) and quantitative (no single component composes more than 60% of the landscape) parts in the definition, which resulted in accuracies of 91.43% and less than 19.26%, respectively. These results are summarized with their implications for the development of the next generation of MCD12Q1 data and with suggestions for potential users of MCD12Q1 v5.1.

Was the Anthropocene anticipated?

Various authors have identified ‘precursors’ of the new concept of the Anthropocene, with most frequent reference made to Antonio Stoppani, Vladimir Vernadsky and Pierre Teilhard de Chardin. The effect, intended or otherwise, of finding forerunners is to deflate the significance of the proposed new geological epoch. We argue there were no precursors to the notion of the Anthropocene, and that there could not have been because the concept (put forward in the year 2000) is an outgrowth of the recent interdisciplinary understanding of the Earth as an evolving planet inaugurated in the 1980s by the International Geosphere-Biosphere Programme and Earth system science. Earlier scientists who commented on ‘the age of man’ did so in terms of human impact on the environment or ‘the face of the Earth’, not the Earth system. Moreover, earlier Western conceptions relied on a progressive and linear evolutionary understanding of the spread of humankind’s geographical and ecological influence, whereas the Anthropocene represents a radical rupture with all evolutionary ideas in human and Earth history, including the breakdown of any idea of advance to a higher stage (such as Teilhard’s ‘noösphere’).

Valuing map validation: The need for rigorous land cover map accuracy assessment in economic valuations of ecosystem services

Valuations of ecosystem services often use data on land cover class areal extent. Area estimates from land cover maps may be biased by misclassification error resulting in flawed assessments and inaccurate valuations. Adjustment for misclassification error is possible for maps subjected to a rigorous validation programme including an accuracy assessment. Unfortunately, validation is rare and/or poorly undertaken as often not regarded as a high priority. The benefit of map validation and hence its value is indicated with two maps. The International Geosphere Biosphere Programme's DISCover map was used to estimate wetland value globally. The latter changed from US$ 1.92trillionyr−1 to US$ 2.79trillionyr−1 when adjusted for misclassification bias. For the conterminous USA, ecosystem services value based on six land cover classes from the National Land Cover Database (2006) changed from US$ 1118billionyr−1 to US$ 600billionyr−1 after adjustment for misclassification bias. The effect of error-adjustment on the valuations indicates the value of map validation to rigorous evidence-based science and policy work in relation to aspects of natural capital. The benefit arising from validation was orders of magnitude larger than mapping costs and it is argued that validation should be a high priority in mapping programmes and inform valuations.

Narratives of the past for Future Earth: The historiography of global environmental change research

This paper analyses the auto-historiography of global environmental change research. It traces how participating researchers make sense of and rationalise research strategies through narratives of the history of global change and Earth System science. Our study draws on personal and programme accounts of Earth System science’s background related to the international global environmental change research programmes International Geosphere-Biosphere Programme (IGBP), the International Human Dimensions Programme on Global Environmental Change (IHDP), the World Climate Research Programme (WCRP), and Future Earth, from 1983 to 2013. The study finds three core narratives: the science history narrative motivates the future development of the programme by building on the successes of earlier international projects. The Earth System departs from an enhanced understanding of environmental change over time. Finally, the Anthropocene narrative underpins arguments for a science-based management of human–environment systems. We argue that including reflexive analytical perspectives in the history writing of Future Earth contributes to making environmental change research relevant and useful for democratic decision-making.

中国东部南北样带典型针叶林土壤酶活性分布格局研究

PDF HTML阅读 XML下载 导出引用 引用提醒 中国东部南北样带典型针叶林土壤酶活性分布格局 DOI: 10.5846/stxb201309272377 作者: 作者单位: 中国科学院地理科学与资源研究所生态网络观测与模拟重点实验室CERN综合研究中心,中国科学院地理科学与资源研究所生态网络观测与模拟重点实验室CERN综合研究中心,中国科学院大学,中国科学院地理科学与资源研究所生态网络观测与模拟重点实验室CERN综合研究中心,中国科学院地理科学与资源研究所生态网络观测与模拟重点实验室CERN综合研究中心 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金(31070435,31290222,31290221);国家重点基础研究发展计划项目(2012CB417103,2010CB833502);中国科学院地理科学与资源研究所"秉维"优秀青年人才基金(2011RC202);中国科学院战略性先导科技专项(XDA05050600) Pattern of enzyme activities of typical coniferous forest soils along the North-South Transect of Eastern China Author: Affiliation: Institute of Geographic Sciences and Natural Resources Research,,University of Chinese Academy of Sciences,, Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:选取中国东部南北样带不同气候区(寒温带、温带和亚热带)的针叶林作为研究对象,分析了多酚氧化酶、过氧化物酶、几丁质酶以及β-葡萄糖苷酶活性的变化。结果表明,土壤溶解性有机碳(DOC)、微生物生物量碳(MBC)、微生物生物量氮(MBN)含量从北到南依次减小,寒温带显著高于亚热带;土壤pH值在3个气候区差异显著,温带最高,亚热带最低。分解木质素的多酚氧化酶和过氧化物酶活性不存在显著性差异;而与氮循环密切相关的几丁质酶活性表现为温带显著高于寒温带和亚热带;与碳循环密切的β-葡萄糖苷酶活性在温带最高,并显著高于亚热带地区。逐步回归分析表明,土壤MBN与pH值影响土壤几丁质酶活性,而土壤β-葡萄糖苷酶活性主要受pH的控制。研究认为,在中国东部南北样带针叶林中,土壤几丁质酶和β-葡萄糖苷酶活性存在显著性差异,而pH与MBN可能是影响土壤酶活性的主要因素。 Abstract:Soil organic carbon (SOC) is the largest terrestrial pool of carbon, and the amount of carbon in soils represents about two thirds of total ecosystem. Therefore, any change in the size and turnover rate of SOC pools will potentially alter the atmospheric CO2 concentration and the subsequent global climate. Soil enzymes are involved in a series of catalyzing reactions and play pivotal roles in litter and soil organic matter decomposition as well as nutrient cycling in terrestrial ecosystems. Soil enzyme activity can be used as a proxy for plant and microbial substrate availability, the interference between soil ecosystem and external environment, and microbial community structure and metabolic capabilities. Therefore, the determination of soil enzyme activities is a powerful tool for understanding soil carbon and nitrogen biogeochemical processes and their responses to climate change. Soil enzyme activity has been a frontier of forest ecology research and has been widespread concern. Unfortunately, most of the studies to date have been limited to a single forest biome or a single forest site, and few studies concern the pattern and controlling factors of soil enzyme activity at a terrestrial transect scale. North-South Transect of Eastern China (NSTEC) is the fifteenth standard transect established by International Geosphere-Biosphere Program (IGBP) in 2005 and is mainly driven by heat, followed by precipitation. It covers almost all forest types from boreal forest to tropical rain forest, which provides an ideal tool to investigate the pattern and environmental control of soil enzyme activities in the boreal, temperate and tropical forest biomes. In the past decade, many studies were conducted to measure the main factors affecting the pattern of SOC storage and soil-atmosphere exchange of greenhouse gases in the typical forests along the NSTEC. However, little information is available on the pattern of soil enzyme activities involved in soil carbon and nitrogen cycles and they relate to soil microbial biomass at a large spatial scale. In this study, the typical coniferous forests distributed in the cold-temperate, temperate and subtropical climatic zones were selected along the NSTEC. The activities of polyphenol oxidase, peroxidase, chitinase and β-glucosaccharase, soil dissolved organic carbon (DOC), microbial biomass carbon (MBC) and microbial biomass nitrogen (MBN) as well as soil pH in the three coniferous forest soils were measured. The results showed that soil DOC, MBC, and MBN contents tended to decrease from north to south, and they were higher in the cold-temperate forest soils than in the subtropical forest soils. There was a significant difference in the soil pH values among the three coniferous forests, following the order cold-temperate > temperate > subtropical forests. Also, no significant differences were found in the soil polyphenol oxidase and peroxidase activities among the three typical coniferous forests. In contrast, the soil chitinase activity involved in soil nitrogen cycle was significantly higher in the temperate forest than in the cold-temperate and subtropical forests, and the soil β-glucosaccharase activity in the temperate forest was also significantly higher than that of the subtropical forest. Stepwise regression analysis showed that the soil chitinase activity was closely associated with soil MBN content and soil pH value, and the soil β-glucosaccharase activity was significantly and positively related to soil pH value. Our results suggest that soil cellulose- and chitin-degrading enzymes (i.e., chintinase and β-glucosaccharase) sensitively respond to climate zone. Soil MBN content and pH value are the main factors controlling soil enzyme activities of coniferous forests along the NSTEC. 参考文献 相似文献 引证文献

Multiscale climatological albedo look-up maps derived from moderate resolution imaging spectroradiometer BRDF/albedo products

Surface albedo determines radiative forcing and is a key parameter for driving Earth’s climate. Better characterization of surface albedo for individual land cover types can reduce the uncertainty in estimating changes to Earth’s radiation balance due to land cover change. This paper presents albedo look-up maps (LUMs) using a multiscale hierarchical approach based on moderate resolution imaging spectroradiometer (MODIS) bidirectional reflectance distribution function (BRDF)/albedo products and Landsat imagery. Ten years (2001 to 2011) of MODIS BRDF/albedo products were used to generate global albedo climatology. Albedo LUMs of land cover classes defined by the International Geosphere-Biosphere Programme (IGBP) at multiple spatial resolutions were generated. The albedo LUMs included monthly statistics of white-sky (diffuse) and black-sky (direct) albedo for each IGBP class for visible, near-infrared, and shortwave broadband under both snow-free and snow-covered conditions. The albedo LUMs were assessed by using the annual MODIS IGBP land cover map and the projected land use scenarios from the Intergovernmental Panel on Climate Change land-use harmonization project. The comparisons between the reconstructed albedo and the MODIS albedo data product show good agreement. The LUMs provide high temporal and spatial resolution global albedo statistics without gaps for investigating albedo variations under different land cover scenarios and could be used for land surface modeling.

The change of global terrestrial ecosystem net primary productivity (NPP) and its response to climate change in CMIP5

Using global terrestrial ecosystem observation and proxy data for net primary productivity (NPP), leaf area index (LAI), and climate data, we compared simulated NPP, LAI, and major climatic factors and explored the relationship between their variations in historical scenarios of ten Coupled Model Intercomparison Project (CMIP5) models. The results showed that global spatial patterns of the simulated terrestrial ecosystem and climate are consistent with proxy data, but the values have some differences for each model. Based on statistical analysis, the simulated climatic factors were found to be better than terrestrial ecosystem NPP and LAI, and the multi-model ensemble (MME) results were better than every single model. For the terrestrial ecosystem, air temperature (Ta) was found to be the major affecting factor, followed by precipitation, meaning the terrestrial ecosystem NPP and LAI are more related to Ta than precipitation. Meanwhile, surface downwelling shortwave radiation (Rsds) was found to inhibit the terrestrial ecosystem in almost all regions of the world. Between 1976 and 2005, precipitation had a slight increasing trend, Ta an obvious increasing trend, and Rsds a slight decreasing trend. The changes of precipitation, air temperature, and Rsds were favorable for the terrestrial ecosystem and for plant growth. Therefore, LAI and NPP showed an obvious increasing temporal trend, and the terrestrial ecosystem showed a positive response to climate change. All the model results showed NPP had an increasing temporal trend in the past 150 years, which also indicated that the terrestrial ecosystem has shown a positive response to climate change in that time period. In terms of the global average, the simulated NPP varied from 21.5 to 69.3 Pg C year−1, and the MME NPP is about 50.6, which was almost consistent with the International Geosphere Biosphere Program (IGBP) NPP result of 55.1 and Moderate Resolution Imaging Spectroradiometer (MODIS) NPP results of 60.5 Pg C year−1.

Observed and simulated changes in the water balance components over Malawi, during 1971–2000

Estimation of the spatial and temporal characteristics of key water balance components in data scarce regions is a large challenge worldwide. This paper presents the derivation of the 30-year surface water balance components (rainfall, temperature, potential and actual evapotranspiration (ETp and ETa) runoff). Monthly rainfall and mean temperature from 28 synoptic stations in Malawi during 1971–2000, together with soil moisture capacity extracted from the International Geosphere-Biosphere Programme Data Information Services (IGBP-DIS) Global Gridded Surfaces of Selected Soil Characteristics database at 0.5° × 0.5° grid resolution were used as model input. Ordinary Kriging was applied to examine the spatial distribution of the components using a 0.5° × 0.5° grid resolution. Temporal trends were investigated using the Mann–Kendall test at α = 0.05 significance level. The results showed: (1) an area of high rainfall, ETa and runoff areas located in the south east and north east highlands and decreasing westwards. Temperature and ETp were highest in the lower Shire River valley and along Lake Malawi; (2) Mann–Kendall trends suggested statistically significant positive trends in mean annual temperature and ETp and declines in annual rainfall, ETa and runoff, though their trends were not statistically significant. The contrasting trends ETp and ETa are a manifestation of the complementary relationship. The decline in rainfall coupled with temperature increase suggests that Malawi became more water-limited during 1971–2000.

The Application of GIS Spatial Analysis Method in Biomass and Carbon Storage Jatropha Curcas

It has become the international geosphere biosphere program, the world climate research programme and one of the core tasks of global change human factors plan that the global carbon cycle and curb greenhouse gas concentrations continue to rise , therefore, the existing biomass and carbon storage quantity of ecosystem research has important practical significance. We analyzed Jatropha curcas L biomass in Yunnan Simao district, basing on GPS location positioning, combining ARCGIS spatial analysis technology, selecting ecological factor such as altitude, slope, land use. Studies have shown that the Jatropha curcas L biomass under different land use types have significant differences by using the background data of these factors, with the help of space analysis method, combining with the measured data validation, respectively, it is: the most IS plantation, the second is cultivated land, the third is weeds, and the least is shrubbery. The research results can provide based data for Jatropha curcas L biomass and carbon storage calculation, also provide information for the decision-making department industry.

Models of L-Band Radar Backscattering Coefficients Over Global Terrain for Soil Moisture Retrieval

Physical models for radar backscattering coefficients are developed for the global land surface at L-band (1.26 GHz) and 40 ° incidence angle to apply to the soil moisture retrieval from the upcoming soil moisture active passive mission data. The simulation of land surface classes includes 12 vegetation types defined by the International Geosphere-Biosphere Programme scheme, and four major crops (wheat, corn, rice, and soybean). Backscattering coefficients for four polarizations (HH/VV/HV/350611873VH) are produced. In the physical models, three terms are considered within the framework of distorted Born approximation: surface scattering, double-bounce volume-surface interaction, and volume scattering. Numerical solutions of Maxwell equations as well as theoretical models are used for surface scattering, double-bounce reflectivity, and volume scattering of a single scatterer. To facilitate fast, real-time, and accurate inversion of soil moisture, the outputs of physical model are provided as lookup tables (with three axes; therefore called datacube). The three axes are the real part of the dielectric constant of soil, soil surface root mean square (RMS) height, and vegetation water content (VWC), each of, which covers the wide range of natural conditions. Datacubes for most of the classes are simulated using input parameters from in situ and airborne observations. This simulation results are found accurate to the co-pol RMS errors of to 3.4 dB (six woody vegetation types), 1.8 dB (grass), and 2.9 dB (corn) when compared with airborne data. Validated with independent spaceborne phased array type L-band synthetic aperture radars and field-based radar data, the datacube errors for the co-pols are within 3.4 dB (woody savanna and shrub) and 1.5 dB (bare surface). Assessed with spaceborne Aquarius scatterometer data, the mean differences range from ~ 1.5 to 2 dB. The datacubes allow direct inversion of sophisticated forward models without empirical parameters or formulae. This capability is evaluated using the time-series inversion algorithm over grass fields.

One Model to Fit All? The Pursuit of Integrated Earth System Models in GAIM and AIMES

Previous research connecting scientific knowledge production with governing of the global environment usually start in international climate change negotiations and related assessments. From that vantage point Earth system science and models are studied as an expansion of Global Circulation Models. By tracing of the history of the present Earth system outlook this thesis offers a reflection about how scientific knowledge produce and connects problems with descriptions of desired order of things and strategies to get there. Knowledge becomes a productive power by shaping fields of possible action in relation to the global environment. The interpreted empirical material consists of scientific discussions from the International global environmental change programmes and particularly the International Geosphere-Biosphere Programme (IGBP) and the International Human Dimensions Programme on global environmental change (IHDP). The studied period spans from the start of the planning of the IGBP in 1983 to the presentation of the new research programme Future Earth in 2013. The thesis is organised around the effects of the IGBP’s strategy to use predictive Earth system models as a tool to bring a broad range of scientific disciplines together. The results demonstrate the historicity of the present Earth system outlook by showing how ecosystems and human dimensions were attributed new and more important roles as drivers of global change. The thesis also argue for the need to approach the ‘Earth system’ as a result of a productive tension between top-down perspectives found in global modelling and bottom-up empirical research engaging with process interactions down to local scales.

Towards new-generation soil erosion modeling: Building a unified omnivorous model

S oil erosion is one of the greatest environmental issues affecting both agricultural and natural lands all over the world (Pimentel et al. 1995). Accordingly, modeling soil erosion is of paramount importance to understanding the processes governing soil degradation and resulting losses (De Vente and Poesen 2005), predicting runoff and soil erosion rates (Foster 1991; Laflen et al. 1991; Boardman 2006), identifying or choosing appropriate measures for erosion control and making decisions and planning in relation to public policy (Renschler and Harbor 2002), as well as coping with projected changes in erosion due to climate change and/or land use (Williams et al. 1996; Lee et al. 1999; Flanagan et al. 2007). As a result, improving the predictive capabilities for soil erosion under global change, by testing and validating several soil erosion models at the field and catchment scale through the Soil Erosion Network (Ingram et al. 1996), has become one of the core tasks in the Global Change and Terrestrial Ecosystem Core Project (GCTE) of the International Geosphere-Biosphere Program (IGBP) (De Roo and Jetten 1999; Jetten et al. 1999). However, until only recently, soil erosion modeling efforts, together with an understanding of the related soil erosion processes, have been mostly confined…

Translating land cover/land use classifications to habitat taxonomies for landscape monitoring: a Mediterranean assessment

Periodic monitoring of biodiversity changes at a landscape scale constitutes a key issue for conservation managers. Earth observation (EO) data offer a potential solution, through direct or indirect mapping of species or habitats. Most national and international programs rely on the use of land cover (LC) and/or land use (LU) classification systems. Yet, these are not as clearly relatable to biodiversity in comparison to habitat classifications, and provide less scope for monitoring. While a conversion from LC/LU classification to habitat classification can be of great utility, differences in definitions and criteria have so far limited the establishment of a unified approach for such translation between these two classification systems. Focusing on five Mediterranean NATURA 2000 sites, this paper considers the scope for three of the most commonly used global LC/LU taxonomies—CORINE Land Cover, the Food and Agricultural Organisation (FAO) land cover classification system (LCCS) and the International Geosphere-Biosphere Programme to be translated to habitat taxonomies. Through both quantitative and expert knowledge based qualitative analysis of selected taxonomies, FAO-LCCS turns out to be the best candidate to cope with the complexity of habitat description and provides a framework for EO and in situ data integration for habitat mapping, reducing uncertainties and class overlaps and bridging the gap between LC/LU and habitats domains for landscape monitoring—a major issue for conservation. This study also highlights the need to modify the FAO-LCCS hierarchical class description process to permit the addition of attributes based on class-specific expert knowledge to select multi-temporal (seasonal) EO data and improve classification. An application of LC/LU to habitat mapping is provided for a coastal Natura 2000 site with high classification accuracy as a result.

Preface "Earth observation for land-atmosphere interaction science"

iLEAPS International Project Office (iLEAPS IPO), Department of Physics, P.O. Box 48, 00014 University of Helsinki,FinlandCorrespondence to: D. Fernandez-Prieto (diego.fernandez@esa.int)´1 IntroductionLand–atmosphere interactions include a variety of complexprocesses and feedbacks between radiative, hydrological,and biogeochemical processes resulting in critical exchangesof energy and matter that influence the overall Earth systemand its climate. The observation, understanding and predic-tion of such processes from local to global scales represent amajor scientific challenge that requires multidisciplinary sci-entific effort and international coordination involving differ-ent scientific communities and technologies.The study of land–atmosphere interactions has been hin-dered in the past by the lack of suitable data at the requiredspatial and temporal scales. Over the last few years, Earthobservation (EO) data integrated with in situ networks andsuitable models have demonstrated the potential to becomea major tool for observing key variables and characterisingthe main processes governing land–atmosphere interactionsat global to local scales. In the next few years the capabilitiesof monitoring land surface and atmosphere will be furtherimproved by the increasing number of advanced EO mis-sions to be launched by space agencies. The full exploita-tion of such increasing multi-mission observational capacityrequires harmonised research efforts involving both EO andEarth system scientists, modellers, and institutions to developnovel observations and robust biophysical products to be ef-fectively integrated with in situ data and within appropriatecoupled models.In this context, in 2010, the European Space Agency(ESA), iLEAPS (the Integrated Land Ecosystem–Atmosphere Processes Study of the International Geosphere-Biosphere Programme, IGBP) and the European GeoscienceUnion (EGU) organised an international conference on EOfor Land–Atmosphere Interaction Science at the ESA centrein Frascati (Italy). The conference, attracting almost 200scientists worldwide, aimed at bringing together the EO andEarth system communities, as well as scientific institutionsand space agencies involved in the observation, characteri-sation and forecasting of land–atmosphere interactions andtheir impacts. In particular, the event presented a uniqueopportunity to facilitate the communications and scientificexchanges among these different communities in order toenhance the coordination of specific scientific efforts andadvocate for a common view of major scientific needs andpriority areas for the future.As a synthesis of these recent advances, this special issueentitled “Earth observation and land–atmosphere interactionsscience” collects some of the works presented at the aboveconference and gathers a number of scientific results demon-strating the potential and exploring the limits of EO tech-nology as a key tool to advance our current knowledge onland–atmosphere processes at different scales in space andtime.After an overview of the main scientific challenges inland–atmosphere interactions today (Sect. 2), the scientificadvances reported in the papers of this special issue will bebriefly summarised in Sect. 3. Section 4 will provide an out-look to future opportunities.Published by Copernicus Publications on behalf of the European Geosciences Union.

Finer resolution observation and monitoring of global land cover: first mapping results with Landsat TM and ETM+ data

We have produced the first 30 m resolution global land-cover maps using Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) data. We have classified over 6600 scenes of Landsat TM data after 2006, and over 2300 scenes of Landsat TM and ETM+ data before 2006, all selected from the green season. These images cover most of the world's land surface except Antarctica and Greenland. Most of these images came from the United States Geological Survey in level L1T (orthorectified). Four classifiers that were freely available were employed, including the conventional maximum likelihood classifier (MLC), J4.8 decision tree classifier, Random Forest (RF) classifier and support vector machine (SVM) classifier. A total of 91,433 training samples were collected by traversing each scene and finding the most representative and homogeneous samples. A total of 38,664 test samples were collected at preset, fixed locations based on a globally systematic unaligned sampling strategy. Two software tools, Global Analyst and Global Mapper developed by extending the functionality of Google Earth, were used in developing the training and test sample databases by referencing the Moderate Resolution Imaging Spectroradiometer enhanced vegetation index (MODIS EVI) time series for 2010 and high resolution images from Google Earth. A unique land-cover classification system was developed that can be crosswalked to the existing United Nations Food and Agriculture Organization (FAO) land-cover classification system as well as the International Geosphere-Biosphere Programme (IGBP) system. Using the four classification algorithms, we obtained the initial set of global land-cover maps. The SVM produced the highest overall classification accuracy (OCA) of 64.9% assessed with our test samples, with RF (59.8%), J4.8 (57.9%), and MLC (53.9%) ranked from the second to the fourth. We also estimated the OCAs using a subset of our test samples (8629) each of which represented a homogeneous area greater than 500 m × 500 m. Using this subset, we found the OCA for the SVM to be 71.5%. As a consistent source for estimating the coverage of global land-cover types in the world, estimation from the test samples shows that only 6.90% of the world is planted for agricultural production. The total area of cropland is 11.51% if unplanted croplands are included. The forests, grasslands, and shrublands cover 28.35%, 13.37%, and 11.49% of the world, respectively. The impervious surface covers only 0.66% of the world. Inland waterbodies, barren lands, and snow and ice cover 3.56%, 16.51%, and 12.81% of the world, respectively.

Assessing disagreement and tolerance of misclassification of satellite-derived land cover products used in WRF model applications

As more satellite-derived land cover products used in the study of global change, especially climate modeling, assessing their quality has become vitally important. In this study, we developed a distance metric based on the parameters used in weather research and forecasting (WRF) to characterize the degree of disagreement among land cover products and to identify the tolerance for misclassification within the International Geosphere Biosphere Programme (IGBP) classification scheme. We determined the spatial degree of disagreement and then created maps of misclassification of Moderate Resolution Imaging Spectoradiometer (MODIS) products, and we calculated overall and class-specific accuracy and fuzzy agreement in a WRF model. Our results show a high level of agreement and high tolerance of misclassification in the WRF model between large-scale homogeneous landscapes, while a low level of agreement and tolerance of misclassification appeared in heterogeneous landscapes. The degree of disagreement varied significantly among seven regions of China. The class-specific accuracy and fuzzy agreement in MODIS Collection 4 and 5 products varied significantly. High accuracy and fuzzy agreement occurred in the following classes: water, grassland, cropland, and barren or sparsely vegetated. Misclassification mainly occurred among specific classes with similar plant functional types and low discriminative spectro-temporal signals. Some classes need to be improved further; the quality of MODIS land cover products across China still does not meet the common requirements of climate modeling. Our findings may have important implications for improving land surface parameterization for simulating climate and for better understanding the influence of the land cover change on climate.

Rational Land Planning Utilization Structure Optimization Based on Multi-Objective Linear Programming Model of Foshan

Regional land use/cover change is one of the hot issues of the global research. Since the proposal of “land use/cover change” research program by the International Geosphere-Biosphere Program（IGBP）and International Human Dimensions Programme on Global Environmental Change（IHDP）in 1995, the research on the land use structure optimization has been increasingly important as the core issue of regional land use/cover change. The structural optimization of land use refers to the use of certain techniques and methods to make the regional future land use structure achieve the best economic, ecological and social benefits. Base on the multi-objective linear programming model and through the setting of 14 variables, this paper has proposed the land use structural optimization program for the rational land planning of Foshan, thus providing reference for the rational land planning of economically developed area.

Climate refugia: from the Last Glacial Maximum to the twenty‐first century

Climate refugia: from the Last Glacial Maximum to the twenty‐first century

American-Australian Scientific Expedition to Arnhem Land (1948): Its Long-Range Impact

The American-Australian Scientific Expedition to Arnhem Land in the Northern Territory of Australia was sponsored by the National Geographic Society and the Smithsonian Institution in the United States and the Commonwealth Government of Australia. During 1948, two anthropologists, an archaeologist, four biological scientists and three health and nutrition experts, with two photographers and three support staff, spent eight months studying the ecology of this infertile, monsoonal landscape to learn how the present-day Aborigines who had arrived between 3500 and 5000 years ago displacing the first hunter-gatherers, the Mimi, who arrived some 53,000 to 60,000 years before were able to survive throughout the year. The Gondwanan origins of the heathy flora of the sandstones, the grassy eucalypt forests and woodlands on the lateritic earths, the monsoonal rainforests, the wetland and coastal plant communities -with vegetation structures similar to those in southern Australia inspired long-term research on the physico-chemical processes (aerodynamic, water relations and mineral nutrition) that determine the structure, growth and biodiversity of plant formations throughout Australia. The cooperative research that was fostered between the United States and Australia during the 1948 Arnhem Land Expedition has continued over the last sixty years in the Fulbright Program, the UNESCO Arid Zone Research Programme, the International Biological Programme (especially in the Arid Zone Biome, the Grassland Biome, the Mediterranean-climate Biome, the Heathland Biome, the Wet-Dry Tropical Biome and Rainforest Biome Programs), the International Union for the Conservation of Nature and, since the 1990s, the International Geosphere-Biosphere Programme to tackle Global Warming.

Soil pH was the main controlling factor of the denitrification rates and N2/N2O emission ratios in forest and grassland soils along the Northeast China Transect (NECT)

The Northeast China Transect (NECT) is a mid-latitude terrestrial transect in the International Geosphere-Biosphere Programme. Its major environmental gradient is precipitation, which gradually decreases from the eastern mountainous region to the western pastoral area. In this investigation, a series of forest and grassland soils were sampled along the NECT, and the denitrification rate and nitrogen/nitrous oxide (N2/N2O) ratio were studied under laboratory conditions by the acetylene inhibition method. Forest soils were all acidic, with soil pH values ranging from 4.3 to 5.9 and soil organic carbon ranging from 32.0 to 54.7 g kg−1. Soil pH for grassland soils was approximately neutral, ranging from 6.1 to 7.8, while soil organic carbon ranged from 14.8 to 32.2 g kg−1. The highest denitrification rates (average 1.1 ± 0.2 mg N kg−1 h−1) were in grassland soils in the western part of the NECT, while the lowest were in forest soils (average 0.25 ± 0.1 mg N kg h−1) in the eastern part of the NECT. The denitrification rate increased linearly from east to west along the NECT (p < 0.01). Nitrous oxide was the main component of gas products of denitrification in forest soils, while N2 was the dominant denitrification product in grassland soils. The ratio of N2/N2O increased linearly from east to west along the NECT (p < 0.01). Soil pH was the best predictor of the denitrification rate and of the N2/N2O ratio in grassland and forest soils along the NECT.