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:    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

Description:    A 108-year (1901–2008) downscaling of the twentieth-century reanalysis (20CR) using the Regional Spectral Model (RSM) has been conducted for the southeastern United States (SEUS) at a horizontal grid resolution of 10 km. This 108-year product, named as the Florida Climate Institute-Florida State University Land–Atmosphere Reanalysis for the southeastern United States at 10-km resolution version 1.0 [FLAReS1.0], has primarily been developed for anticipated application studies in hydrology, crop management, ecology, and other interdisciplinary fields in the SEUS. The analysis of this downscaled product reveals that it ameliorates the issue of artificial discontinuity in the precipitation time series of the 20CR from the variations inherent to RSM. This centennial scale product allows us to begin examining decadal scale variations of the regional features of the SEUS. The fidelity of the low-frequency variations of the winter rainfall associated with the Atlantic Multi-decadal Oscillation (AMO) and the Pacific Decadal Oscillation is reasonably well captured in FLAReS1.0. In fact, the modulation of the El Niño-Southern Oscillation (ENSO) teleconnection with the SEUS rainfall by AMO in the downscaled product is also validated with observations. The ENSO-associated variations of accumulated rainfall from landfalling hurricanes in the SEUS are also well simulated in the downscaled climate simulation. It is to be noted that the success of this dynamical downscaling is also because the global reanalysis of 20CR showed comparable fidelity in these low-frequency variations of the SEUS climate. This method of dynamic downscaling global reanalysis with inclusion of spectral nudging at large wavelengths (in this case ≥500 km) toward the driving global reanalysis (20CR) is sometimes referred as a form of regional reanalysis. Content Type Journal Article Category Original Article Pages 1-9 DOI 10.1007/s10113-012-0372-8 Authors V. Misra, Department of Earth, Ocean and Atmospheric Science, Florida State University, P.O. Box 3064520, Tallahassee, FL 32306-4520, USA S. M. DiNapoli, Center for Ocean-Atmospheric Prediction Studies, Florida State University, 2035 E. Paul Dirac Dr., 200 RM Johnson Bldg, Tallahassee, FL 32306-2840, USA S. Bastola, Center for Ocean-Atmospheric Prediction Studies, Florida State University, 2035 E. Paul Dirac Dr., 200 RM Johnson Bldg, Tallahassee, FL 32306-2840, USA Journal Regional Environmental Change Online ISSN 1436-378X Print ISSN 1436-3798

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