Description:    The condition of many wetlands across Australia has deteriorated due to increased water regulation and the expansion and intensification of agriculture and increased urban and industrial expansion. Despite this situation, a comprehensive overview of the distribution and condition of wetlands across Australia is not available. Regional analyses exist and several exemplary mapping and monitoring exercises have been maintained to complement the more general information sets. It is expected that global climate change will exacerbate the pressures on inland wetlands, while sea level rises will adversely affect coastal wetlands. It is also expected that the exacerbation of these pressures will increase the potential for near-irreversible changes in the ecological state of some wetlands. Concerted institutional responses to such pressures have in the past proven difficult to sustain, although there is some evidence that a more balanced approach to water use and agriculture is being developed with the provision of increasing funds to purchase water for environmental flows being one example. We identify examples from around Australia that illustrate the impacts on wetlands of long-term climate change from palaeoecological records (south-eastern Australia); water allocation (Murray-Darling Basin); dryland salinisation (south-western Australia); and coastal salinisation (northern Australia). These are provided to illustrate both the extent of change in wetlands and the complexity of differentiating the specific effects of climate change. An appraisal of the main policy responses by government to climate change is provided as a basis for further considering the opportunities for mitigation and adaptation to climate change. Content Type Journal Article Category Effects of Climate Change on Wetlands Pages 1-21 DOI 10.1007/s00027-011-0232-5 Authors C. M. Finlayson, Institute for Land, Water and Society, Charles Sturt University, PO Box 789, Albury, NSW 2640, Australia J. A. Davis, School of Biological Sciences, Monash University, Clayton, VIC 3800, Australia P. A. Gell, Centre for Environmental Management, School of Science and Engineering, University of Ballarat, PO Box 663, Ballarat, VIC 3353, Australia R. T. Kingsford, Australian Rivers and Wetland Centre, University of New South Wales, Sydney, Australia K. A. Parton, Institute for Land, Water and Society, Charles Sturt University, PO Box 883, Orange, NSW 2800, Australia Journal Aquatic Sciences - Research Across Boundaries Online ISSN 1420-9055 Print ISSN 1015-1621

Description:    Gross primary productivity (GPP) is a major component of carbon exchange between the atmosphere and terrestrial ecosystems and a key component of the terrestrial carbon cycle. Because of the large spatial heterogeneity and temporal dynamics of ecosystems, it is a challenge to estimate GPP accurately at global or regional scales. The 8-day MODerate resolution Imaging Spectroradiometer (MODIS) GPP product provides a near real time estimate of global GPP. However, previous studies indicated that MODIS GPP has large uncertainties, partly caused by biases in parameterization and forcing data. In this study, MODIS GPP was validated using GPP derived from the eddy covariance flux measurements at five typical forest sites in East Asia. The validation indicated that MODIS GPP was seriously underestimated in these forest ecosystems of East Asia, especially at northern sites. With observed meteorological data, fraction of photosynthetically active radiation absorbed by the plant canopy (fPAR) calculated using smoothed MODIS leaf area index, and optimized maximum light use efficiency ( ε max ) to force the MOD17 algorithm, the agreement between predicted GPP and tower-based GPP was significantly improved. The errors of MODIS GPP in these forest ecosystems of East Asia were mainly caused by uncertainties in ε max , followed by those in fPAR and meteorological data. The separation of canopy into sunlit and shaded leaves, for which GPP is individually calculated, can improve GPP simulation significantly. Content Type Journal Article Category Special Feature: Original Article Pages 1-10 DOI 10.1007/s10310-012-0369-7 Authors Mingzhu He, Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, 901 Mengminwei Building, 22 Hankou Road, Nanjing, 210093 China Yanlian Zhou, School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing, 210093 China Weimin Ju, Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, 901 Mengminwei Building, 22 Hankou Road, Nanjing, 210093 China Jingming Chen, Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, 901 Mengminwei Building, 22 Hankou Road, Nanjing, 210093 China Li Zhang, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101 China Shaoqiang Wang, Qianyanzhou Ecological Experimental Station, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101 China Nobuko Saigusa, Center for Global Environmental Research, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, 305-8506 Japan Ryuichi Hirata, Center for Global Environmental Research, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, 305-8506 Japan Shohei Murayama, Research Institute for Environmental Management Technology, National Institute of Advanced Industrial Science and Technology (AIST), AIST Tsukuba West, 16-1 Onogawa, Tsukuba, 305-8569 Japan Yibo Liu, Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, 901 Mengminwei Building, 22 Hankou Road, Nanjing, 210093 China Journal Journal of Forest Research Online ISSN 1610-7403 Print ISSN 1341-6979

Description:    This review reports background information on wetlands in the Northeast Asia and High Asia areas, including wetland coverage and type, significance for local populations, and threats to their vitality and protection, with particular focus on the relationship of how global change influenced wetlands. Natural wetlands in these areas have been greatly depleted and degraded, largely due to global climate change, drainage and conversion to agriculture and silviculture, hydrologic alterations, exotics invasions, and misguided management policies. Global warming has caused wetland and ice-sheet loss in High Asia and permafrost thawing in tundra wetlands in Northeast Asia, and hence induced enormous reductions in water-storage sources in High Asia and carbon loss in Northeast Asia. This, in the long term, will exacerbate chronic water shortage and positively feed back global warming. Recently, better understanding of the vital role of healthy wetland ecosystems to Asia’s sustainable economic development has led to major efforts in wetland conservation and restoration. Nonetheless, collaborative efforts to restore and protect the wetlands must involve not only the countries of Northeast and High Asia but also international agencies. Research has been productive but the results should be more effectively integrated with policy-making and wetland restoration practices under future climatic scenarios. Content Type Journal Article Category Research Article Pages 1-9 DOI 10.1007/s00027-012-0281-4 Authors Shuqing An, The State Key Laboratory of Pollution Control and Resource Reuse, The Institute of Wetland Ecology, School of Life Science, Nanjing University, Nanjing, 210093 People’s Republic of China Ziqiang Tian, River and Coastal Environment Research Center, Chinese Research Academy of Environmental Sciences, Beijing, 100012 People’s Republic of China Ying Cai, The State Key Laboratory of Pollution Control and Resource Reuse, The Institute of Wetland Ecology, School of Life Science, Nanjing University, Nanjing, 210093 People’s Republic of China Teng Wen, The State Key Laboratory of Pollution Control and Resource Reuse, The Institute of Wetland Ecology, School of Life Science, Nanjing University, Nanjing, 210093 People’s Republic of China Delin Xu, The State Key Laboratory of Pollution Control and Resource Reuse, The Institute of Wetland Ecology, School of Life Science, Nanjing University, Nanjing, 210093 People’s Republic of China Hao Jiang, The State Key Laboratory of Pollution Control and Resource Reuse, The Institute of Wetland Ecology, School of Life Science, Nanjing University, Nanjing, 210093 People’s Republic of China Zhigang Yao, The Wetland Management Station, Jiangsu Administrate of Forestry, Nanjing, 210036 People’s Republic of China Baohua Guan, The Institute of Geography and Limnology, China Academy of Science, Nanjing, 210008 People’s Republic of China Sheng Sheng, The State Key Laboratory of Pollution Control and Resource Reuse, The Institute of Wetland Ecology, School of Life Science, Nanjing University, Nanjing, 210093 People’s Republic of China Yan Ouyang, The State Key Laboratory of Pollution Control and Resource Reuse, The Institute of Wetland Ecology, School of Life Science, Nanjing University, Nanjing, 210093 People’s Republic of China Xiaoli Cheng, Key Laboratory of Aquatic Botany and Watershed Ecology, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, 430074 People’s Republic of China Journal Aquatic Sciences - Research Across Boundaries Online ISSN 1420-9055 Print ISSN 1015-1621

Description:    A method for obtaining a relative deer population density index with low cost and effort is urgently needed in wildlife protection areas that need their own deer management guidelines. We recorded the number of deer sighted during our daily trips on forest roads by car in Ashiu Forest at Kyoto University, Japan, beginning in 2006. We used generalized additive mixed models (GAMMs) to estimate among-year trends in the number of deer sighted. We applied models for the total number of deer (TND), number of adults (NA), and number of fawns (NF) sighted, which included both current-year and 1-year-old fawns. Full models included the terms of year (2007, 2008, 2009, and 2010), weather (fine, cloudy, and rain/snow), and nonlinear effects of season (date) and time (time). The optimal GAMMs for TND, NA, and NF did not include the effect of weather but included those of time, date, and year. The detected among-year trends in deer population may be influenced by differences in snow environments among the years. The modeling of road count data using GAMM quantitatively determined among-year variation in the number of deer sighted. This trend was similar to that of the population density estimated using a block count survey conducted in Ashiu Forest. Content Type Journal Article Category Original Article Pages 1-7 DOI 10.1007/s10310-012-0379-5 Authors Inoue Mizuki, Laboratory of Forest Science, Faculty of Bioresource Sciences, Akita Prefectural University, Akita, 010-0195 Japan Shota Sakaguchi, Laboratory of Forest Biology, Graduate School of Agriculture, Kyoto University, Kyoto, Japan Keitaro Fukushima, Field Science Education and Research Center, Kyoto University, Kyoto, Japan Masaru Sakai, Graduate School of Global Environmental Studies, Kyoto University, Kyoto, Japan Atsushi Takayanagi, Laboratory of Forest Biology, Graduate School of Agriculture, Kyoto University, Kyoto, Japan Daisuke Fujiki, Institute of Natural and Environment Science, University of Hyogo, Tanba, Japan Michimasa Yamasaki, Laboratory of Forest Biology, Graduate School of Agriculture, Kyoto University, Kyoto, Japan Journal Journal of Forest Research Online ISSN 1610-7403 Print ISSN 1341-6979