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:    Agroforestry systems are widely practiced in tropical forests to recover degraded and deforested areas and also to balance the global carbon budget. However, our understanding of difference in soil respiration rates between agroforestry and natural forest systems is very limited. This study compared the seasonal variations in soil respiration rates in relation to fine root biomass, microbial biomass, and soil organic carbon between a secondary forest and two agroforestry systems dominated by Gmelina arborea and Dipterocarps in the Philippines during the dry and the wet seasons. The secondary forest had significantly higher ( p  〈 0.05) soil respiration rate, fine root biomass and soil organic matter than the agroforestry systems in the dry season. However, in the wet season, soil respiration and soil organic matter in the G. arborea dominated agroforestry system were as high as in the secondary forest. Whereas soil respiration was generally higher in the wet than in the dry season, there were no differences in fine root biomass, microbial biomass and soil organic matter between the two seasons. Soil respiration rate correlated positively and significantly with fine root biomass, microbial biomass, and soil organic C in all three sites. The results of this study indicate, to some degree, that different land use management practices have different effects on fine root biomass, microbial biomass and soil organic C which may affect soil respiration as well. Therefore, when introducing agroforestry system, a proper choice of species and management techniques which are similar to natural forest is recommended. Content Type Journal Article Pages 1-9 DOI 10.1007/s10457-012-9530-8 Authors Kikang Bae, Department of Forest and Natural Resources Management, SUNY College of Environmental Science and Forestry, Syracuse, NY 13210, USA Don Koo Lee, Department of Forest Science, Seoul National University, Seoul, 151-742 Korea Timothy J. Fahey, Department of Natural Resources, Cornell University, Ithaca, NY 14853, USA Soo Young Woo, Department of Environmental Horticulture, University of Seoul, Seoul, 130-743 Republic of Korea Amos K. Quaye, Department of Forest and Natural Resources Management, SUNY College of Environmental Science and Forestry, Syracuse, NY 13210, USA Yong-Kwon Lee, Korea Forest Service, Government Complex-Daejeon, Bldg 1, 189 Cheongsa-ro, Seo-gu, Daejeon, 302-701 Republic of Korea Journal Agroforestry Systems Online ISSN 1572-9680 Print ISSN 0167-4366

Description:    Participatory research methods have helped scientists to understand how farmers experiment and to seek partnerships with farmers in developing technologies with enhanced relevance and adoption. This paper reports on the development of a participatory methodology to systematize long-term experimentation with agroforestry systems carried out in a hotspot of biodiversity by non-governmental organizations and local farmers. A methodological guide for systematization and techniques used for Participatory Rural Appraisal formed the basis of our work. We propose an analytical framework that recognizes systems of reflexive and learning interactions, in order to make the learned lessons explicit. At the process level, the main lessons and recommendations are as follows. It is important to establish partnerships to conduct innovative and complex experimentation with agroforest. Participatory systematization allows us to improve the methodological aspects of design, implementation and management of on-farm participatory experimentation. It also serves to synthesize the main findings and to extract lessons from agroforestry systems experiments. It fosters the technical improvement of agroforestry systems. It creates possibilities for reflection on agroforestry systems by farmers, extensionists and researchers, as well as their learning with respect to management of such systems. The findings are placed in the context of current theory on participatory experimentation in agriculture. Extractive and interactive approaches help to produce rich insights of mutual interest through collaboration by identifying local, regional and global convergences, complementarities, and conflicts of interest; which affect the advance of new eco-friendly technologies, to both improve the livelihoods and to reverse biodiversity loss and environmental degradation. Content Type Journal Article Pages 1-16 DOI 10.1007/s10457-012-9498-4 Authors Helton Nonato de Souza, Department of Soil Quality, Wageningen University, Wageningen, The Netherlands Irene Maria Cardoso, Soil Science Department, Federal University of Viçosa, Viçosa, Brazil Eduardo de Sá Mendonça, Plant Production Department, Federal University of Espírito Santo, Alegre, ES 29500-000, Brazil Anôr Fiorini Carvalho, Soil Science Department, Federal University of Viçosa, Viçosa, Brazil Gustavo Bediaga de Oliveira, Centre of Alternative Technologies of Zona da Mata (CTA-ZM), Sitio Alfa Violeira, Zona Rural, Caixa Postal 128, Cep, Viçosa, MG 36570 000, Brazil Davi Feital Gjorup, Centre of Alternative Technologies of Zona da Mata (CTA-ZM), Sitio Alfa Violeira, Zona Rural, Caixa Postal 128, Cep, Viçosa, MG 36570 000, Brazil Verônica Rocha Bonfim, Centre of Alternative Technologies of Zona da Mata (CTA-ZM), Sitio Alfa Violeira, Zona Rural, Caixa Postal 128, Cep, Viçosa, MG 36570 000, Brazil Journal Agroforestry Systems Online ISSN 1572-9680 Print ISSN 0167-4366

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