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:    To quantitatively assess the effects of agricultural practices on methane (CH 4 ) emissions from rice fields, a two-year (2005/2006) field experiment with 2 3 factorial designs was conducted to assess the effects of three driving factors on CH 4 emissions in South China: continuously flooded (W0) and mid-season and final drainages (W2), straw (S1) and nitrogen fertilizer (N1) applications and their controls (S0, N0). Results showed that averaged across all the treatments about 75 % of the seasonal total CH 4 occurred between the rice transplanting and booting stage, while constituted only 33 % of the seasonal total rice biomass during the same period. Averaged across the treatments in 2006, CH 4 emissions were substantially decreased by mid-season drainage up to 60 % (15.6 vs. 39.0 g m −2 ). The decreased CH 4 emissions represented almost all of the decrease in the total global warming potentials. Without straw incorporation CH 4 emissions substantially decreased up to 59 % (15.9 vs. 38.7 g m −2 ). The stimulating effects of straw were significantly greater for W0 than W2 treatment, being also greater in the 2005 than in the 2006 season. A significant inter-annual difference in CH 4 emissions was found when averaged across straw incorporation and N fertilizer applications for the W2 treatment (42.8 and 15.4 g m −2 in 2005 and 2006, respectively). Moreover, N fertilization has no significant effect on CH 4 emissions in this study. Our results demonstrate that although straw effects varied greatly with specific management, both straw managements and water regimes are equally important driving factors and thus being the most promising measures attenuating CH 4 emissions while achieving sustainable rice production. Content Type Journal Article Category Original Article Pages 1-10 DOI 10.1007/s10705-012-9503-3 Authors Jinyang Wang, Jiangsu Key Laboratory of Low Carbon Agriculture and GHGs Mitigation, College of Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing, 210095 China Xiaolin Zhang, Jiangsu Key Laboratory of Low Carbon Agriculture and GHGs Mitigation, College of Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing, 210095 China Zhengqin Xiong, Jiangsu Key Laboratory of Low Carbon Agriculture and GHGs Mitigation, College of Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing, 210095 China M. A. K. Khalil, Department of Physics, Portland State University, P.O. Box 751, Portland, OR 97207, USA Xu Zhao, State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, 210008 China Yingxin Xie, National Engineering Research Center for Wheat, Henan Agricultural University, Zhengzhou, 450002 China Guangxi Xing, State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, 210008 China Journal Nutrient Cycling in Agroecosystems Online ISSN 1573-0867 Print ISSN 1385-1314

Description:    Persistently high activity concentrations of radioactive Cs-137 ( T 1/2  = 30.17 a) in various animals and fruits originating from Bavarian forest ecosystems suggest that the contamination of soils in these ecosystems is still critical even decades after the severe inputs following the Chernobyl nuclear accident. Aware of the fact, that such inputs are a global threat that can re-emerge at any time, a new monitoring network was established in cooperation with the Bavarian State Ministry of the Environment and Public Health, to enhance the value of long-term radioprotection strategies in forests. Based on the investigation of 48 forest sites throughout the entire state territory, the project delivers a total of 889 gamma spectrometric records and demonstrates the current Cs-137 contamination situation of Bavarian forest soils, providing a valuable update on the residual contamination levels and thus a comprehensive inventory for any future radioprotection management. First results of this project are presented hereby. The total Cs-137 areal activity densities in Bavarian forest soils currently vary between 640 and 61,166 Bq m − ², with the peak areal activity density of each profile being located in the uppermost, humus rich mineral A-horizon in 68 % of all cases. Moreover, the results detect a positive correlation of humus thickness and relative areal Cs-137 activity density in humus horizons ( R ² = 0.50), validating previous findings on that topic by means of a very comprehensive data set across 2.56 Mio ha forest stands by showing that humus bodies 〉7.5 cm still contain at least 50 % of the total areal topsoil activity density. Content Type Journal Article Category Original Paper Pages 1-15 DOI 10.1007/s10342-012-0626-5 Authors Jennifer Winkelbauer, Department of Geomorphology and Soil Science, Technische Universität München, Freising-Weihenstephan, Germany Jörg Völkel, Department of Geomorphology and Soil Science, Technische Universität München, Freising-Weihenstephan, Germany Matthias Leopold, Department of Geomorphology and Soil Science, Technische Universität München, Freising-Weihenstephan, Germany Kerstin Hürkamp, Institute of Radiation Protection, Helmholtz-Zentrum München, German Research Center for Environmental Health, München-Neuherberg, Germany Rudolf Dehos, Department of Radioprotection and Radioecology, Bavarian State Ministry of the Environment and Public Health, Munich, Germany Journal European Journal of Forest Research Online ISSN 1612-4677 Print ISSN 1612-4669

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