Description:    Climate change is an issue of great importance for human rights, public health, and socioeconomic equity because of its diverse consequences overall as well as its disproportionate impact on vulnerable and socially marginalized populations. Vulnerability to climate change is determined by a community’s ability to anticipate, cope with, resist, and recover from the impact of major weather events. Climate change will affect industrial and agricultural sectors, as well as transportation, health, and energy infrastructure. These shifts will have significant health and economic consequences for diverse communities throughout California. Without proactive policies to address these equity concerns, climate change will likely reinforce and amplify current as well as future socioeconomic disparities, leaving low-income, minority, and politically marginalized groups with fewer economic opportunities and more environmental and health burdens. This review explores the disproportionate impacts of climate change on vulnerable groups in California and investigates the costs and benefits of the climate change mitigation strategies specified for implementation in the California Global Warming Solutions Act of 2006 (AB 32). Lastly, knowledge gaps, future research priorities, and policy implications are identified. Content Type Journal Article Pages 1-19 DOI 10.1007/s10584-011-0310-7 Authors Seth B. Shonkoff, Department of Environmental Science, Policy, and Management, Division of Society and Environment, University of California, Berkeley, 137 Mulford Hall, MC 3144, Berkeley, CA 94720, USA Rachel Morello-Frosch, Department of Environmental Science, Policy and Management & School of Public Health, University of California, Berkeley, 137 Mulford Hall, MC 3114, Berkeley, CA 94720, USA Manuel Pastor, Departments of Geography and American Studies and Ethnicity, University of Southern California, 3620 S. Vermont Ave, KAP-462, Los Angeles, CA 90089-0255, USA James Sadd, Department of Environmental Science and Geology, Occidental College, 1600 Campus Rd., Los Angeles, CA 90041, USA Journal Climatic Change Online ISSN 1573-1480 Print ISSN 0165-0009

Description:    The tree species composition of a forested landscape may respond to climate change through two primary successional mechanisms: (1) colonization of suitable habitats and (2) competitive dynamics of established species. In this study, we assessed the relative importance of competition and colonization in forest landscape response (as measured by the forest type composition change) to global climatic change. Specifically, we simulated shifts in forest composition within the Boundary Waters Canoe Area of northern Minnesota during the period 2000–2400  AD . We coupled a forest ecosystem process model, PnET-II, and a spatially dynamic forest landscape model, LANDIS-II, to simulate landscape change. The relative ability of 13 tree species to colonize suitable habitat was represented by the probability of establishment or recruitment. The relative competitive ability was represented by the aboveground net primary production. Both competitive and colonization abilities changed over time in response to climatic change. Our results showed that, given only moderate-frequent windthrow (rotation period = 500 years) and fire disturbances (rotation period = 300 years), competition is relatively more important for the short-term (〈100 years) compositional response to climatic change. For longer-term forest landscape response (〉100 years), colonization became relatively more important. However, if more frequent fire disturbances were simulated, then colonization is the dominant process from the beginning of the simulations. Our results suggest that the disturbance regime will affect the relative strengths of successional drivers, the understanding of which is critical for future prediction of forest landscape response to global climatic change. Content Type Journal Article Pages 1-31 DOI 10.1007/s10584-011-0098-5 Authors Chonggang Xu, Division of Earth and Environmental Sciences, Los Alamos National Laboratory, Los Alamos, NM 87544, USA George Z. Gertner, Department of Natural Resources & Environmental Sciences, University of Illinois, W-523 Turner Hall, MC-047, 1102 South Goodwin Ave, Urbana, IL 61801, USA Robert M. Scheller, Environmental Science and Management, Portland State University, P.O. Box 751, Portland, OR 97207, USA Journal Climatic Change Online ISSN 1573-1480 Print ISSN 0165-0009

Description:    This paper explores two issues that have been receiving increasing attention in recent decades, climate change adaptation and natural disaster risk reduction. An examination of the similarities and differences between them reveals important linkages but also significant differences, including the spectrum of threats, time and spatial scales, the importance of local versus global processes, how risks are perceived, and degree of uncertainty. Using a risk perspective to analyze these issues, preferential strategies emerge related to choices of being proactive, reactive, or emphasizing risk management as opposed to the precautionary principle. The policy implications of this analysis are then explored, using Canada as a case study. Content Type Journal Article Pages 1-15 DOI 10.1007/s10584-011-0259-6 Authors David Etkin, Disaster and Emergency Management, Faculty of Liberal Arts and Professional Studies, York University, 4700 Keele St, Toronto, Ontario, Canada M3J 1P3 J. Medalye, Political Science, Faculty of Liberal Arts & Professional Studies, York University, Toronto, Ontario, Canada K. Higuchi, Faculty of Environmental Studies, York University, Toronto, Ontario, Canada Journal Climatic Change Online ISSN 1573-1480 Print ISSN 0165-0009

Description:    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

Description:    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

Description:    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

Description:    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

Description:    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

Description:    Although policymaking in response to the climate change threat is essentially a challenge of risk management, most studies of the relation of emissions targets to desired climate outcomes are either deterministic or subject to a limited representation of the underlying uncertainties. Monte Carlo simulation, applied to the MIT Integrated Global System Model (an integrated economic and earth system model of intermediate complexity), is used to analyze the uncertain outcomes that flow from a set of century-scale emissions paths developed originally for a study by the U.S. Climate Change Science Program. The resulting uncertainty in temperature change and other impacts under these targets is used to illustrate three insights not obtainable from deterministic analyses: that the reduction of extreme temperature changes under emissions constraints is greater than the reduction in the median reduction; that the incremental gain from tighter constraints is not linear and depends on the target to be avoided; and that comparing median results across models can greatly understate the uncertainty in any single model. Content Type Journal Article Pages 1-15 DOI 10.1007/s10584-011-0260-0 Authors Mort Webster, Joint Program on the Science and Policy of Global Change, Massachusetts Institute of Technology, Cambridge, MA, USA Andrei P. Sokolov, Joint Program on the Science and Policy of Global Change, Massachusetts Institute of Technology, Cambridge, MA, USA John M. Reilly, Joint Program on the Science and Policy of Global Change, Massachusetts Institute of Technology, Cambridge, MA, USA Chris E. Forest, Department of Meteorology, Pennsylvania State University, University Park, PA, USA Sergey Paltsev, Joint Program on the Science and Policy of Global Change, Massachusetts Institute of Technology, Cambridge, MA, USA Adam Schlosser, Joint Program on the Science and Policy of Global Change, Massachusetts Institute of Technology, Cambridge, MA, USA Chien Wang, Joint Program on the Science and Policy of Global Change, Massachusetts Institute of Technology, Cambridge, MA, USA David Kicklighter, The Ecosystems Center, Marine Biological Laboratory, Woods Hole, MA, USA Marcus Sarofim, AAAS Science and Technology Policy Fellow, U.S. Environmental Protection Agency, Washington DC, USA Jerry Melillo, The Ecosystems Center, Marine Biological Laboratory, Woods Hole, MA, USA Ronald G. Prinn, Joint Program on the Science and Policy of Global Change, Massachusetts Institute of Technology, Cambridge, MA, USA Henry D. Jacoby, Joint Program on the Science and Policy of Global Change, Massachusetts Institute of Technology, Cambridge, MA, USA Journal Climatic Change Online ISSN 1573-1480 Print ISSN 0165-0009

Description:    Wetland ecosystems are of global significance having productive, regulatory and informative function. These wetlands are crucial for the long-term protection of water sources, as well as the survival of its unique biodiversity. Most of the wetlands of Turkey are now facing serious threat from the anthropogenic sources and now near to the verge of extinction. This study has been carried out to monitor vegetation dynamics and ecological status of wetlands of Koyna basin at spatial and temporal scale. This study has involved MODerate-resolution Imaging Spectroradiometer (MODIS) images of the year 2000, 2004 and 2008 on daily basis with spatial resolution of 1 km. The MODIS 16 days composite NDVI time series products of 250-m spatial resolution from year 2000 to 2008 has been utilized to monitor the ecological status of the wetlands. The European Nature Information System habitat classification map, meteorological data (precipitation, temperature) coupled with field data has been utilized to validate NDVI values of nine habitats in the wetlands. The time series analyses of NDVI data values have been correlated with the groundwater level depth from 1996 to 2004. The overall analysis has shown a declining trend of NDVI over the year 2000 to 2008, indicated a degraded wetland condition in span of 9 years. Content Type Journal Article Pages 1-12 DOI 10.1007/s10113-011-0241-x Authors Jay Krishna Thakur, Department Hydrogeology and Environmental Geology, Institute of Geosciences, Martin Luther University, Von-Seckendorff-Platz 3, 06120 Halle (Saale), Germany P. K. Srivastava, Department of Civil Engineering, Water and Environment Management Research Center, University of Bristol, Bristol, BS8 1TR United Kingdom S. K. Singh, Centre of Atmospheric and Ocean Science, KBCAOS, IIDS, University of Allahabad, Allahabad, 211002 India Zoltán Vekerdy, Faculty of Geo-information Science and Earth Observation, Twente University, Hengelosestraat 99, 7514 AE Enschede, The Netherlands Journal Regional Environmental Change Online ISSN 1436-378X Print ISSN 1436-3798