Description:    Nitrous oxide (N 2 O) emissions from grazed grasslands are estimated to be approximately 28% of global anthropogenic N 2 O emissions. Estimating the N 2 O flux from grassland soils is difficult because of its episodic nature. This study aimed to quantify the N 2 O emissions, the annual N 2 O flux and the emission factor (EF), and also to investigate the influence of environmental and soil variables controlling N 2 O emissions from grazed grassland. Nitrous oxide emissions were measured using static chambers at eight different grasslands in the South of Ireland from September 2007 to August 2009. The instantaneous N 2 O flux values ranged from -186 to 885.6 μg N 2 O-N m −2  h −1 and the annual sum ranged from 2 ± 3.51 to 12.55 ± 2.83 kg N 2 O-N ha −1  y −1 for managed sites. The emission factor ranged from 1.3 to 3.4%. The overall EF of 1.81% is about 69% higher than the Intergovernmental Panel on Climate Change (IPCC) default EF value of 1.25% which is currently used by the Irish Environmental Protection Agency (EPA) to estimate N 2 O emission in Ireland. At an N applied of approximately 300 kg ha −1  y −1 , the N 2 O emissions are approximately 5.0 kg N 2 O-N ha −1 y −1 , whereas the N 2 O emissions double to approximately 10 kg N ha −1 for an N applied of 400 kg N ha −1  y −1 . The sites with higher fluxes were associated with intensive N-input and frequent cattle grazing. The N 2 O flux at 17°C was five times greater than that at 5°C. Similarly, the N 2 O emissions increased with increasing water filled pore space (WFPS) with maximum N 2 O emissions occurring at 60–80% WFPS. We conclude that N application below 300 kg ha −1  y −1 and restricted grazing on seasonally wet soils will reduce N 2 O emissions. Content Type Journal Article Pages 1-20 DOI 10.1007/s10021-011-9434-x Authors Rashad Rafique, Department of Civil and Environmental Engineering, Centre for Hydrology, Micrometeorology and Climate Change, University College Cork, Cork, Ireland Deirdre Hennessy, Department of Animals &, Grassland Science Research, Teagasc-Moorpark, Fermoy, Ireland Gerard Kiely, Department of Civil and Environmental Engineering, Centre for Hydrology, Micrometeorology and Climate Change, University College Cork, Cork, Ireland Journal Ecosystems Online ISSN 1435-0629 Print ISSN 1432-9840

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:    Agricultural drainage is thought to alter greenhouse gas emissions from temperate peatlands, with CH 4 emissions reduced in favor of greater CO 2 losses. Attention has largely focussed on C trace gases, and less is known about the impacts of agricultural conversion on N 2 O or global warming potential. We report greenhouse gas fluxes (CH 4 , CO 2 , N 2 O) from a drained peatland in the Sacramento-San Joaquin River Delta, California, USA currently managed as a rangeland (that is, pasture). This ecosystem was a net source of CH 4 (25.8 ± 1.4 mg CH 4 -C m −2  d −1 ) and N 2 O (6.4 ± 0.4 mg N 2 O-N m −2  d −1 ). Methane fluxes were comparable to those of other managed temperate peatlands, whereas N 2 O fluxes were very high; equivalent to fluxes from heavily fertilized agroecosystems and tropical forests. Ecosystem scale CH 4 fluxes were driven by “hotspots” (drainage ditches) that accounted for less than 5% of the land area but more than 84% of emissions. Methane fluxes were unresponsive to seasonal fluctuations in climate and showed minimal temporal variability. Nitrous oxide fluxes were more homogeneously distributed throughout the landscape and responded to fluctuations in environmental variables, especially soil moisture. Elevated CH 4 and N 2 O fluxes contributed to a high overall ecosystem global warming potential (531 g CO 2 -C equivalents m −2  y −1 ), with non-CO 2 trace gas fluxes offsetting the atmospheric “cooling” effects of photoassimilation. These data suggest that managed Delta peatlands are potentially large regional sources of greenhouse gases, with spatial heterogeneity in soil moisture modulating the relative importance of each gas for ecosystem global warming potential. Content Type Journal Article Pages 1-15 DOI 10.1007/s10021-011-9411-4 Authors Yit Arn Teh, Environmental Change Research Group, School of Geography & Geosciences, University of St Andrews, St Andrews, KY16 9 AL Scotland, UK Whendee L. Silver, Department of Environmental Science, Policy, and Management, University of California, Berkeley, California 94702, USA Oliver Sonnentag, Department of Environmental Science, Policy, and Management, University of California, Berkeley, California 94702, USA Matteo Detto, Department of Environmental Science, Policy, and Management, University of California, Berkeley, California 94702, USA Maggi Kelly, Department of Environmental Science, Policy, and Management, University of California, Berkeley, California 94702, USA Dennis D. Baldocchi, Department of Environmental Science, Policy, and Management, University of California, Berkeley, California 94702, USA Journal Ecosystems Online ISSN 1435-0629 Print ISSN 1432-9840

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