Description: The field of ecoinformatics provides concepts, methods and standards to guide management and analysis of ecological data with particular emphasis on exploration of co-occurrences of organisms and their linkage to environmental conditions and taxon attributes. In this editorial, introducing the Special Feature ‘Ecoinformatics and global change’, we reflect on the development of ecoinformatics and explore its importance for future global change research with special focus on vegetation-plot data. We show how papers in this Special Feature illustrate important directions and approaches in this emerging field. We suggest that ecoinformatics has the potential to make profound contributions to pure and applied sciences, and that the analyses, databases, meta-databases, data exchange formats and analytical tools presented in this Special Feature advance this approach to vegetation science and illustrate and address important open questions. We conclude by describing important future directions for the development of the field including incentives for data sharing, creation of tools for more robust statistical analysis, utilities for integration of data that conform to divergent taxonomic standards, and databases that provide detailed plot-specific data so as to allow users to find and access data appropriate to their research needs.

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: Questions: What are the most likely environmental drivers for compositional herb layer changes as indicated by trait differences between winner and loser species? Location: Weser-Elbe region (NW Germany). Methods: We resurveyed the herb layer communities of ancient forest patches on base-rich sites of 175 semi-permanent plots. Species traits were tested for their ability to discriminate between winner and loser species using logistic regression analyses and deviance partitioning. Results: Of 115 species tested, 31 were identified as winner species and 30 as loser species. Winner species had higher seed longevity, flowered later in the season and more often had an oceanic distribution compared to loser species. Loser species tended to have a higher specific leaf area, were more susceptible to deer browsing and had a performance optimum at higher soil pH compared to winner species. The loser species also represented several ancient forest and threatened species. Deviance partitioning indicated that local drivers (i.e. disturbance due to forest management) were primarily responsible for the species shifts, while regional drivers (i.e. browsing pressure and acidification from atmospheric deposition) and global drivers (i.e. climate warming) had moderate effects. There was no evidence that canopy closure, drainage or eutrophication contributed to herb layer changes. Conclusions: The relative importance of the different drivers as indicated by the winner and loser species differs from that found in previous long-term studies. Relating species traits to species performance is a valuable tool that provides insight into the environmental drivers that are most likely responsible for herb layer changes.

Description: Tropical forests are biologically diverse ecosystems that play important roles in the carbon cycle and maintenance of global biodiversity. Understanding how tropical forests respond to environmental changes is important, as changes in carbon storage can modulate the rate and magnitude of climate change. Applying an ecoinformatics approach for managing long-term forest inventory plot data, where individual trees are tracked over time, facilitates regional and cross-continental forest research to evaluate changes in taxonomic composition, growth, recruitment and mortality rates, and carbon and biomass stocks. We developed ForestPlots.net as a secure, online inventory data repository and to facilitate data management of long-term tropical forest plots to promote scientific collaborations among independent researchers. The key novel features of the database are: (a) a design that efficiently deals with time-series data; (b) data management tools to assess potential errors; and (c) a query library to generate outputs (e.g. biomass and carbon stock changes over time).

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