Beschreibung:    The emerging interest in the biological and conservation significance of locally rare species prompts a number of questions about their correspondence with other categories of biodiversity, especially global rarity. Here we present an analysis of the correspondence between the distributions of globally and locally rare plants. Using biological hotspots of rarity as our framework, we evaluate the extent to which conservation of globally rare plants will act as a surrogate for conservation of locally rare taxa. Subsequently, we aim to identify gaps between rarity hotspots and protected land to guide conservation planning. We compiled distribution data for globally and locally rare plants from botanically diverse Napa County, California into a geographic information system. We then generated richness maps highlighting hotspots of global and local rarity. Following this, we overlaid the distribution of these hotspots with the distribution of protected lands to identify conservation gaps. Based on occupancy of 1 km 2 grid cells, we found that over half of Napa County is occupied by at least one globally or locally rare plant. Hotspots of global and local rarity occurred in a substantially smaller portion of the county. Of these hotspots, less than 5% were classified as multi-scale hotspots, i.e. they were hotspots of global and local rarity. Although, several hotspots corresponded with the 483 km 2 of protected lands in Napa County, some of the richest areas did not. Thus, our results show that there are important conservation gaps in Napa County. Furthermore, if only hotspots of global rarity are preserved, only a subset of locally rare plants will be protected. Therefore, conservation of global, local, and multi-scale hotspots needs serious consideration if the goals are to protect a larger variety of biological attributes, prevent extinction, and limit extirpation in Napa County. Content Type Journal Article Category Original Paper Pages 1-12 DOI 10.1007/s10531-011-0137-6 Authors Benjamin J. Crain, Department of Biological Sciences, Humboldt State University, 1 Harpst Street, Arcata, CA 95521, USA Jeffrey W. White, Department of Biological Sciences, Humboldt State University, 1 Harpst Street, Arcata, CA 95521, USA Steven J. Steinberg, Department of Environmental Science and Management, Humboldt State University, 1 Harpst Street, Arcata, CA 95521, USA Journal Biodiversity and Conservation Online ISSN 1572-9710 Print ISSN 0960-3115

Beschreibung:    Severe water erosion is notorious for its harmful effects on land-water resources as well as local societies. The scale effects of water erosion, however, greatly exacerbate the difficulties of accurate erosion evaluation and hazard control in the real world. Analyzing the related scale issues is thus urgent for a better understanding of erosion variations as well as reducing such erosion. In this review article, water erosion dynamics across three spatial scales including plot, watershed, and regional scales were selected and discussed. For the study purposes and objectives, the advantages and disadvantages of these scales all demonstrate clear spatial-scale dependence. Plot scale studies are primarily focused on abundant data collection and mechanism discrimination of erosion generation, while watershed scale studies provide valuable information for watershed management and hazard control as well as the development of quantitatively distributed models. Regional studies concentrate more on large-scale erosion assessment, and serve policymakers and stakeholders in achieving the basis for regulatory policy for comprehensive land uses. The results of this study show that the driving forces and mechanisms of water erosion variations among the scales are quite different. As a result, several major aspects contributing to variations in water erosion across the scales are stressed: differences in the methodologies across various scales, different sink-source roles on water erosion processes, and diverse climatic zones and morphological regions. This variability becomes more complex in the context of accelerated global change. The changing climatic factors and earth surface features are considered the fourth key reason responsible for the increased variability of water erosion across spatial scales. Content Type Journal Article Pages 127-143 DOI 10.1007/s11769-012-0524-2 Authors Wei Wei, State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-environmental Sciences, Chinese Academy of Sciences, Beijing, 100085 China Liding Chen, State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-environmental Sciences, Chinese Academy of Sciences, Beijing, 100085 China Lei Yang, State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-environmental Sciences, Chinese Academy of Sciences, Beijing, 100085 China Bojie Fu, State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-environmental Sciences, Chinese Academy of Sciences, Beijing, 100085 China Ranhao Sun, State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-environmental Sciences, Chinese Academy of Sciences, Beijing, 100085 China Journal Chinese Geographical Science Online ISSN 1993-064X Print ISSN 1002-0063 Journal Volume Volume 22 Journal Issue Volume 22, Number 2

Beschreibung:    Soil carbon stocks and sequestration have been given a lot of attention recently in the study of terrestrial ecosystems and global climate change. This review focuses on the progress made on the estimation of the soil carbon stocks of China, and the characterization of carbon dynamics of croplands with regard to climate change, and addresses issues on the mineralization of soil organic carbon in relation to greenhouse gas emissions. By integrating existing research data, China’s total soil organic carbon (SOC) stock is estimated to be 90 Pg and its inorganic carbon (SIC) stock as 60 Pg, with SOC sequestration rates in the range of 20–25 Tg/a for the last two decades. An estimation of the biophysical potential of SOC sequestration has been generally agreed as being 2 Pg over the long term, of which only 1/3 could be attainable using contemporary agricultural technologies in all of China’s croplands. Thus, it is critical to enhance SOC sequestration and mitigate climate change to improve agricultural and land use management in China. There have been many instances where SOC accumulation may not induce an increased amount of decomposition under a warming scenario but instead favor improved cropland productivity and ecosystem functioning. Furthermore, unchanged or even decreased net global warming potential (GWP) from croplands with enhanced SOC has been reported by a number of case studies using life cycle analysis. Future studies on soil carbon stocks and the sequestration potential of China are expected to focus on: (1) Carbon stocks and the sequestration capacity of the earths’ surface systems at scales ranging from the plot to the watershed and (2) multiple interface processes and the synergies between carbon sequestration and ecosystem productivity and ecosystem functioning at scales from the molecular level to agro-ecosystems. Soil carbon science in China faces new challenges and opportunities to undertake integrated research applicable to many areas. Content Type Journal Article Category Review Pages 1-11 DOI 10.1007/s11434-011-4693-7 Authors JuFeng Zheng, Institute for Resource, Ecosystem and Environment of Agriculture, and Research Center of Agriculture and Climate Change, Nanjing Agricultural University, Nanjing, 210095 China Kun Cheng, Institute for Resource, Ecosystem and Environment of Agriculture, and Research Center of Agriculture and Climate Change, Nanjing Agricultural University, Nanjing, 210095 China GenXing Pan, Institute for Resource, Ecosystem and Environment of Agriculture, and Research Center of Agriculture and Climate Change, Nanjing Agricultural University, Nanjing, 210095 China Pete Smith, Institute of Biological and Environmental Sciences, School of Biological Sciences, University of Aberdeen, 23 St Machar Drive, Aberdeen, AB24 3UU UK LianQing Li, Institute for Resource, Ecosystem and Environment of Agriculture, and Research Center of Agriculture and Climate Change, Nanjing Agricultural University, Nanjing, 210095 China XuHui Zhang, Institute for Resource, Ecosystem and Environment of Agriculture, and Research Center of Agriculture and Climate Change, Nanjing Agricultural University, Nanjing, 210095 China JinWei Zheng, Institute for Resource, Ecosystem and Environment of Agriculture, and Research Center of Agriculture and Climate Change, Nanjing Agricultural University, Nanjing, 210095 China XiaoJun Han, Institute for Resource, Ecosystem and Environment of Agriculture, and Research Center of Agriculture and Climate Change, Nanjing Agricultural University, Nanjing, 210095 China YanLing Du, Institute for Resource, Ecosystem and Environment of Agriculture, and Research Center of Agriculture and Climate Change, Nanjing Agricultural University, Nanjing, 210095 China Journal Chinese Science Bulletin Online ISSN 1861-9541 Print ISSN 1001-6538

Beschreibung:    Since Westman (1977) and Ehrlich (1982) put forward the concepts of “the service of nature” and “ecosystem service functions”, respectively, methods for conducting value accounting for them, and their practical application have become the subjects of intense study. Based on an overview of available research findings, we discuss three scientific hypotheses. First, the terrestrial ecosystem offers both positive and negative service functions. Second, changes in terrestrial ecosystem service functions lie not only in the number of ecosystem types and the coverage area of each type, but also in their quality. Third, the value of terrestrial ecosystem service functions should be assessed both in terms of the value stocked and the value added. We collected land use data from China during the period 1999–2008, and Normalized Difference Vegetation Index data based on remote sensing images from the Global Inventory Modeling and Mapping Studies for the same period. We then calculated and analyzed spatial and temporal changes in China’s terrestrial ecosystem service values over the 10-year period. Considering temporal change, the total value (stocked) of China’s terrestrial ecosystem service functions decreased from 6.82 trillion Yuan RMB in 1999 to 6.57 trillion Yuan RMB in 2008. During that period, the positive value decreased by 240.17 billion Yuan RMB and the negative value increased by 8.85 billion Yuan RMB. The decrease in total value lies mainly in the humidity control, soil formation, and waste recycling functions. The total value (added) of China’s terrestrial ecosystem service functions increased by 4.31 billion Yuan RMB in 2000, but decreased by 0.13 billion Yuan RMB in 2008 (based on the constant price of China in 1999). The value (added) was a negative figure. From the perspective of spatial change, we can see that the supply of China’s terrestrial ecosystem service functions fell slightly over the past 10 years, mainly in Northeast and Southern China. As a result of human activities on ecosystems, the loss of ecosystem service functions’ value was relatively prominent in Shanxi and Gansu provinces, compared with an increase in value in Shaanxi Province. Terrestrial ecosystem service functions’ value per unit area was relatively high in mid- and East China, showing a prominent spatial change over the 10-year period, but low in Western China. Some conclusions are drawn after an in-depth analysis of the factors causing the spatial and temporal changes in China’s terrestrial ecosystem service functions, in the hope that our suggestions will be helpful for the management of China’s terrestrial ecosystems. Content Type Journal Article Category Article Pages 1-12 DOI 10.1007/s11434-012-4978-5 Authors Yao Shi, State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085 China RuSong Wang, State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085 China JinLou Huang, State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085 China WenRui Yang, Beijing Municipal Institute of City Planning and Design, Beijing, 100045 China Journal Chinese Science Bulletin Online ISSN 1861-9541 Print ISSN 1001-6538

Beschreibung:    In this paper, we proposed a framework for evaluating the performance of ecosystem strategies prepared for enhancing vulnerability reduction in the face of hazards due to climate change. The framework highlights the positive effects of human activities in the coupled human and natural system (CHANS) by introducing adaptive capacity as an evaluation criterion. A built-in regional vulnerability to a certain hazard was generated based upon interaction of three dimensions of vulnerability: exposure, sensitivity and adaptive capacity. We illustrated the application of this framework in the temperate farming-grazing transitional zone in the middle Inner Mongolia of the northern China, where drought hazard is the key threat to the CHANS. Specific indices were produced to translate such climate variance and social-economic differences into specific indicators. The results showed that the most exposed regions are the inner land areas, while counties located in the eastern part are potentially the most adaptive ones. Ordos City and Bayannur City are most frequently influenced by multiple climate variances, showing highest sensitivity. Analysis also indicated that differences in the ability to adapt to changes are the main causes of spatial differences. After depiction of the spatial differentiations and analysis of the reasons, climate zones were divided to depict the differences in facing to the drought threats. The climate zones were shown to be similar to vulnerability zones based on the quantitative structure of indexes drafted by a triangular map. Further analysis of the composition of the vulnerability index showed that the evaluation criteria were effective in validating the spatial differentiation but potentially ineffective because of their limited time scope. This research will be a demonstration of how to combine the three dimensions by quantitative methods and will thus provide a guide for government to vulnerability reduction management. Content Type Journal Article Pages 1-13 DOI 10.1007/s11769-012-0583-4 Authors Xiaoqian Liu, Laboratory for Earth Surface Processes, Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing, 100871 China Yanglin Wang, Laboratory for Earth Surface Processes, Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing, 100871 China Jian Peng, Laboratory for Earth Surface Processes, Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing, 100871 China K. Braimoh Ademola, Global Land Project, Sapporo Nodal Office, Hokkaido University, Sapporo, 060-0809 Japan He Yin, Geomatics Laboratory, Geography Department, Humboldt-Universität zu Berlin, Berlin, 10099 Germany Journal Chinese Geographical Science Online ISSN 1993-064X Print ISSN 1002-0063

Beschreibung:    Land use change and human population growth are accelerating the fragmentation and insularization of wildlife habitats worldwide. The conservation and management of wildlife in the resultant ‘island’ ecosystems in the context of global warming is challenging due to the isolation and reduced size of the ecosystems and hence the scale over which ecosystem processes can operate. We analyzed trends in numbers of nine large herbivores in Kenya’s Lake Nakuru National Park to understand how rainfall and temperature variability, surrounding land use changes, and boundary fencing affected wildlife population dynamics inside the park during 1970–2011. Buffalo, zebra and Thomson’s gazelle numbers increased persistently. Grant’s gazelle and impala increased initially then gradually declined. Waterbuck and warthog numbers progressively declined to levels that potentially threatened their local population persistence. The total biomass of ungulates tripled from 1970 to 2011, with buffalo replacing waterbuck as the predominant species in biomass. Increased competition from buffalo and zebra, heightened predation and illicit human harvests probably all contributed to the declines by waterbuck and warthog. Density-dependent limitation of population growth within the park confines was evident for buffalo, impala, eland, giraffe, Grant’s and Thomson’s gazelles. Fluctuations in the lake level related to varying rainfall affected changes in animal abundance through expansion of the lake area and flooding of grasslands bordering the lake. Unusually, the most stressful conditions were associated with high water levels following high rainfall. There was also evidence of carry-over effects from prior habitat conditions affecting all species. The relatively stable populations of all species except warthog and waterbuck demonstrate the remarkable capacity of this small, insularized park to retain viable populations of most of the large herbivores, without much management intervention. Content Type Journal Article Category Original Paper Pages 1-21 DOI 10.1007/s10531-012-0239-9 Authors Joseph O. Ogutu, International Livestock Research Institute, P.O. Box 30709, Nairobi, 00100 Kenya Norman Owen-Smith, Centre for African Ecology, School of Animal, Plant and Environmental Sciences, University of the Witwatersrand, Wits, 2050 South Africa Hans-Peter Piepho, Bioinformatics Unit, Institute for Crop Science, University of Hohenheim, Fruwirthstrasse 23, 70599 Stuttgart, Germany Bernard Kuloba, Kenya Wildlife Service, Lake Nakuru National Park, P.O. Box 539, Nakuru, Kenya Joseph Edebe, Kenya Wildlife Service, Lake Nakuru National Park, P.O. Box 539, Nakuru, Kenya Journal Biodiversity and Conservation Online ISSN 1572-9710 Print ISSN 0960-3115

Beschreibung:    Four wetland maps for all China have been produced, based on Landsat and CBERS-02B remote sensing data between 1978 and 2008 (1978, 1990, 2000 and 2008). These maps were mainly developed by manual interpretation and validated by substantial field investigation in 2009. Based on these maps, we analyzed the 2008 wetland distribution in China and discussed wetland changes and their drivers over the past 30 years. (i) There were about 324097 km 2 of wetlands in 2008, for which inland marshes or swamps were the most common wetland type (35%), with lakes (26%) second. Most of the wetlands were in Heilongjiang, Inner Mongolia, Qinghai and Tibet, occupying about 55% of the national wetland area. (ii) From 1978 to 2008, China’s wetland area continually and significantly decreased, by about 33% based on changes in the wetland map. This was in sharp contrast to the increase in artificial wetlands, which increased by about 122%. Inland marshes accounted for the main loss of total wetlands from 1978 to 2000. From 2000 through 2008, riverine and lacustrine wetlands constituted the main wetland loss. Fortunately however, the rate of wetland loss decreased from 5523 to 831 km 2 /a. (iii) The change ratio of lost natural wetlands (including inland and coastal wetlands) to non-wetlands has decreased slightly over the past 30 years. From 1978 to 1990, nearly all natural wetlands (98%) lost were transformed into non-wetlands. However, the ratio declined to 86% from 1990 to 2000, and to 77% from 2000 to 2008. (iv) All Chinese provinces were divided into three groups according to patterns of wetland changes, which could relate to the driving forces of such changes. Tibet was completely different from other provinces, as it was one representative example in which there was a net wetland increase, because of global warming and decreased human activity since 1990. Increased economic development caused considerable wetland loss in most eastern provinces, and artificial wetlands increased. Content Type Journal Article Category Article Pages 1-11 DOI 10.1007/s11434-012-5093-3 Authors ZhenGuo Niu, State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Institute of Remote Sensing Applications, Chinese Academy of Sciences and Beijing Normal University, Beijing, 100101 China HaiYing Zhang, State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Institute of Remote Sensing Applications, Chinese Academy of Sciences and Beijing Normal University, Beijing, 100101 China XianWei Wang, State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Institute of Remote Sensing Applications, Chinese Academy of Sciences and Beijing Normal University, Beijing, 100101 China WenBo Yao, Ministry of Education Key Laboratory for Earth System Modeling, Center for Earth System Science, Institute for Global Change Studies, Tsinghua University, Beijing, 100084 China DeMin Zhou, Resource Environment and Tourism, Capital Normal University, Beijing, 100037 China KuiYi Zhao, Northeast Institute of Geography and Agricultural Ecology, Chinese Academy of Sciences, Changchun, 130012 China Hui Zhao, State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Institute of Remote Sensing Applications, Chinese Academy of Sciences and Beijing Normal University, Beijing, 100101 China NaNa Li, State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Institute of Remote Sensing Applications, Chinese Academy of Sciences and Beijing Normal University, Beijing, 100101 China HuaBing Huang, State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Institute of Remote Sensing Applications, Chinese Academy of Sciences and Beijing Normal University, Beijing, 100101 China CongCong Li, Department of Geography and Remote Sensing, Beijing Normal University, Beijing, 100875 China Jun Yang, College of Forestry, Beijing Forestry University, Beijing, 100083 China CaiXia Liu, State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Institute of Remote Sensing Applications, Chinese Academy of Sciences and Beijing Normal University, Beijing, 100101 China Shuang Liu, State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Institute of Remote Sensing Applications, Chinese Academy of Sciences and Beijing Normal University, Beijing, 100101 China Lin Wang, State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Institute of Remote Sensing Applications, Chinese Academy of Sciences and Beijing Normal University, Beijing, 100101 China Zhan Li, State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Institute of Remote Sensing Applications, Chinese Academy of Sciences and Beijing Normal University, Beijing, 100101 China ZhenZhong Yang, Department of Geography and Remote Sensing, Beijing Normal University, Beijing, 100875 China Fei Qiao, State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Institute of Remote Sensing Applications, Chinese Academy of Sciences and Beijing Normal University, Beijing, 100101 China YaoMin Zheng, State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Institute of Remote Sensing Applications, Chinese Academy of Sciences and Beijing Normal University, Beijing, 100101 China YanLei Chen, Department of Environmental Science, Policy and Management, University of California, Berkeley, 94720 USA YongWei Sheng, Department of Geography, University of California, Los Angeles, 90095 USA XiaoHong Gao, Department of Life and Geographic Sciences, Qinghai Normal University, Xining, 810008 China WeiHong Zhu, Department of Geography, Yanbian University, Yanbian, 133002 China WenQing Wang, School of Environment and Ecology, Xiamen University, Xiamen, 361005 China Hong Wang, School of Geographical Information Science, Hohai University, Nanjing, 211100 China YongLing Weng, School of Surveying and Mapping Transportation Engineering, Southeast University, Nanjing, 210096 China DaFang Zhuang, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101 China JiYuan Liu, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101 China ZhiCai Luo, School of Surveying and Mapping, Wuhan University, Wuhan, 430079 China Xiao Cheng, Department of Geography and Remote Sensing, Beijing Normal University, Beijing, 100875 China ZiQi Guo, State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Institute of Remote Sensing Applications, Chinese Academy of Sciences and Beijing Normal University, Beijing, 100101 China Peng Gong, State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Institute of Remote Sensing Applications, Chinese Academy of Sciences and Beijing Normal University, Beijing, 100101 China Journal Chinese Science Bulletin Online ISSN 1861-9541 Print ISSN 1001-6538