Description:    High rates of urbanization, environmental degradation, and industrial development have affected all nations worldwide, but in disaster-prone areas, the impact is even greater serving to increase the extent of damage from natural catastrophes. As a result of the global nature of environmental change, modern economies have had to adapt, and sustainability is an extremely important issue. Clearly, natural disasters will affect the competitiveness of an enterprise. This study focuses on natural disaster management in an area in which the direct risks are posed by the physical effects of natural disasters such as floods, droughts, tsunamis, and rising sea levels. On a local level, the potential impact of a disaster on a company and how much damage (loss) it causes to facilities and future business are of concern. Each company must make plans to mitigate predictable risk. Risk assessments must be completed in a timely manner. Disaster management is also very important to national policy. Natural disaster management mechanisms can include strategies for disaster prevention, early warning (prediction) systems, disaster mitigation, preparedness and response, and human resource development. Both governmental administration (public) and private organizations should participate in these programs. Participation of the local community is especially important for successful disaster mitigation, preparation for, and the implementations of such measures. Our focus in this study is a preliminary proposal for developing an efficient probabilistic approach to facilitate design optimization that involves probabilistic constraints. Content Type Journal Article Pages 1-9 DOI 10.1007/s11069-011-9889-2 Authors Chun-Pin Tseng, Chung Shan Institute of Science and Technology, Armaments Bureau, Taoyuan, Taiwan Cheng-Wu Chen, Institute of Maritime Information and Technology, National Kaohsiung Marine University, Kaohsiung, 80543 Taiwan Journal Natural Hazards Online ISSN 1573-0840 Print ISSN 0921-030X

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:    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

Description:    This article explores how the causes and impacts of a flood event as perceived by local people shape immediate responses and future mitigation efforts in mountainous northwest Vietnam. Local flood perception is contrasted with scientific perspectives to determine whether a singular flood event will trigger adjustments in mitigation strategies in an otherwise rarely flood-affected area. We present findings from interdisciplinary research drawing on both socioeconomic and biophysical data. Evidence suggests that individual farmers’ willingness to engage in flood mitigation is curbed by the common perception that flooding is caused by the interplay of a bundle of external factors, with climatic factors and water management failures being the most prominent ones. Most farmers did not link the severity of flooding to existing land use systems, thus underlining the lack of a sense of personal responsibility among farmers for flood mitigation measures. We conclude that local governments cannot depend on there being a sufficient degree of intrinsic motivation among farmers to make them implement soil conservation techniques to mitigate future flooding. Policy makers will need to design measures to raise farmers’ awareness of the complex interplay between land use and hydrology and to enhance collective action in soil conservation by providing appropriate incentives and implementing coherent long-term strategies. Content Type Journal Article Category Original Paper Pages 1-21 DOI 10.1007/s11069-011-9992-4 Authors Iven Schad, Department of Social Sciences in Agriculture, Agricultural Communication and Extension, University of Hohenheim, Stuttgart, Germany Petra Schmitter, Department of Plant Production and Agro-Ecology in the Tropics and Subtropics, University of Hohenheim, Stuttgart, Germany Camille Saint-Macary, Department of Rural Development and Policy, University of Hohenheim, Stuttgart, Germany Andreas Neef, Resource Governance and Participatory Development, Graduate School of Global Environmental Studies, Kyoto University, Kyoto, Japan Marc Lamers, Department of Soil Science and Land Evaluation, Biogeophysics Section, University of Hohenheim, Stuttgart, Germany La Nguyen, Department of Soil Science and Land Evaluation, Biogeophysics Section, University of Hohenheim, Stuttgart, Germany Thomas Hilger, Department of Plant Production and Agro-Ecology in the Tropics and Subtropics, University of Hohenheim, Stuttgart, Germany Volker Hoffmann, Department of Social Sciences in Agriculture, Agricultural Communication and Extension, University of Hohenheim, Stuttgart, Germany Journal Natural Hazards Online ISSN 1573-0840 Print ISSN 0921-030X