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: 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: Publication date: Available online 1 September 2017 Source: The Egyptian Journal of Remote Sensing and Space Science Author(s): H.A. Bharath, M.C. Chandan, S. Vinay, T.V. Ramachandra Metropolitan cities in India are emerging as major economic hubs with an unprecedented land use changes and decline of environmental resources. Globalisation and consequent relaxations of Indian markets to global players has given impetus to rapid urbanisation process. Urbanisation being irreversible and rapid coupled with fast growth of population during the last century, contributed to serious ecological and environmental consequences. This necessitates monitoring and advance visualisation of spatial patterns of landscape dynamics for evolving appropriate management strategies towards sustainable development approaches. This study visualises the growth of Indian mega cities Delhi, Mumbai, Pune, Chennai and Coimbatore, through Cellular Automata Markov model considering the influence of agent(s) of urban growth through soft computing techniques. CA Markov model is considered to be one of most effective algorithm to visualise the growth of urban spatial structures. Prediction of growth using agent based modelling considering the spatial patterns of urbanisation during the past four decades has provided insights to the urban dynamics. The industrial, infrastructural, socio-economic factors significantly influence the urban growth compared to the biophysical factors. Visualisation of urban growth suggest agents driven growth in the cities and its surroundings with large land use transformations in urban corridors and upcoming Industrial and ear marked developmental zones. Integrating local agents of urban growth help in identifying specific regions of intense growth, likely challenges and provide opportunities for evolving appropriate management strategies towards sustainable cities during the 21st century.