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:    The area of study lies at the northeastern part of Nile Delta. Global shoreline regression and sea-level rise have their own-bearing on the groundwater salinization due to seawater intrusion. A new adopted approach for vulnerability mapping using the hydrochemical investigations, geographic information system and a weighted multi-criteria decision support system (WMCDSS) was developed to determine the trend of groundwater contamination by seawater intrusion. Six thematic layers were digitally integrated and assigned different weights and rates. These have been created to comprise the most decisive criteria used for the delineation of groundwater degradation due to seawater intrusion. These criteria are represented by the total dissolved solids, well discharge, sodium adsorption ratio, hydrochemical parameter (Cl/HCO 3 ), hydraulic conductivity and water types. The WMCDSS modeling was tried, where a groundwater vulnerability map with four classes ranging from very low to high vulnerability was gained. The map pinpointed the promising localities for groundwater protection, which are almost represented by the very low or low vulnerability areas (53.69 % of the total study area). The regions having high and moderate groundwater vulnerability occupy 46.31 % of total study area, which designate to a deteriorated territory of groundwater quality, and needs special treatment and cropping pattern before use. However, the moderate groundwater vulnerability class occupies an area of about 28.77 % of the total mapped area, which highlighted the need for certain management practices to prevent the saltwater intrusion from expanding further to the south. There was a good correlation of the constructed vulnerability map with the recently gathered water quality data and hydrochemical facies evolution. The plotting of water quality data on Piper trilinear diagram revealed the evolution of freshwater into the mixing and the saline zones as an impact of seawater intrusion, which validates the model results. Content Type Journal Article Category Original Article Pages 1-19 DOI 10.1007/s12665-012-1740-x Authors Hossam H. Elewa, National Authority for Remote Sensing and Space Sciences (NARSS), P.O. Box 1564, 23 Jozef Brows Tito St., El Nozha El-Gedida, Alf-Maskan, Cairo, 11769 Egypt Ragaa E. Shohaib, Chemistry Department, Faculty of Science, Zagazig University, Zagazig, Egypt Atef A. Qaddah, Geological Hazards Research Unit, Faculty of Earth Sciences, King Abdulaziz University, Jeddah, Saudi Arabia Ahmad M. Nousir, Geology Department, Faculty of Science, Zagazig University, Zagazig, Egypt Journal Environmental Earth Sciences Online ISSN 1866-6299 Print ISSN 1866-6280

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