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: Questions The study of naturally discontinuous forest systems could help further our understanding of the relative roles of abiotic factors and spatial connectivity in influencing species turnover and plant metacommunity structure compared to continuous forest formations where local communities are often arbitrarily defined and where ‘mass effects’ and source-sink dynamics tend to confound the roles of dispersal and environment. Here we study a tropical montane landscape where old-growth evergreen forest occurs as patchy formations in a matrix of natural grasslands, to test the influence of environment and connectivity on species turnover and woody plant metacommunity structure . Location The study area consists of the western and southern regions of the Upper Nilgiri Plateau in the Western Ghats of Southern India, a global biodiversity hotspot . Methods We sampled 85 vegetation plots located across a 600 km2 landscape, assembled environmental data, constructed contrasting spatial connectivity models, including models for the effects of topography on structural connectivity, and used RDA-based variation partitioning to assess the relative influence of environment and space on woody plant metacommunity structure . Results Considering several environmental and multi-scale spatial predictors, we could explain half the variation in plant community structure. Environmental and habitat factors such as precipitation, temperature seasonality, elevation, fragment size and landscape context play a dominant role and explain 42% of variation. Spatial predictors based on Euclidean distance performed better than those that accounted for topographical resistance. Spatial predictors accounted for only 9% of the variation in plant metacommunity structure . Conclusion Our results support the species sorting paradigm of metacommunity structure, as abiotic effects and biotic interactions play dominant roles in influencing community structure and species turnover in these old growth forests with a comparatively small influence of spatial connectivity. Effective management of woody species diversity would therefore require conservation of these forests across the range of environmental conditions under which they occur . This article is protected by copyright. All rights reserved.

Description: Questions As biodiversity losses increase due to global change and human-induced habitat destruction, the relationships between plant traits and ecosystem properties can provide a new level of understanding ecosystem complexity. Using a functional response–effect approach, we show that multiple components of the carbon cycle are determined by a few plant traits, which in turn are strongly affected by environmental conditions. Location Salt marshes, northwest Germany. Methods We explored responses of morphological, chemical and biomass-related plant traits to environmental drivers and examined their effects on carbon cycle properties, i.e. above-ground biomass, above-ground net primary productivity and decomposition. The combined analysis between environmental parameters, functional traits and ecosystem properties used structural equation modelling (SEM). Results Important response and effect traits were leaf dry matter content (LDMC) and below-ground dry mass (BDM, responding to groundwater level and salinity) and leaf C:N ratio (responding to inundation frequency). Inundation and salinity led to increased allocation to below-ground biomass and salt stress adaptation in leaves, which translated into increased decomposition rates. Release from these abiotic controls resulted in standing biomass accumulation, which was controlled by LDMC and canopy height as key traits. Conclusions These findings demonstrate the interacting effects of non-consumable environmental factors and soil resources on morphological, chemical and biomass traits, which affected carbon cycle properties. Loss of species from the community has the potential to change the relationships between environment and vegetation-based ecosystem properties and therefore elicit effects on the multifunctionality of the entire and adjacent ecosystems. Studying relationships between plant traits and ecosystem properties can provide new insight into ecosystem complexity. We ask how plant species traits respond to environmental conditions and how key effect traits determine carbon related ecosystem properties in salt marshes of NW-Germany. Our study reveals interacting effects of environmental factors on morphological, chemical and biomass traits and gives recommendations for conservation management.

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