51 research outputs found

    Species–area relationships in continuous vegetation : evidence from Palaearctic grasslands

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    Aim: Species-area relationships (SARs) are fundamental scaling laws in ecology although their shape is still disputed. At larger areas power laws best represent SARs. Yet, it remains unclear whether SARs follow other shapes at finer spatial grains in continuous vegetation. We asked which function describes SARs best at small grains and explored how sampling methodology or the environment influence SAR shape. Location: Palaearctic grasslands and other non-forested habitats. Taxa: Vascular plants, bryophytes and lichens. Methods: We used the GrassPlot database, containing standardised vegetation-plot data from vascular plants, bryophytes, and lichens spanning a wide range of grassland types throughout the Palaearctic and including 2057 nested-plot series with at least seven grain sizes ranging from 1 cm2 to 1024 m². Using non-linear regression, we assessed the appropriateness of different SAR functions (power, power quadratic, power breakpoint, logarithmic, Michaelis-Menten). Based on AICc, we tested whether the ranking of functions differed among taxa, methodological settings, biomes or vegetation types. Results: The power function was the most suitable function across the studied taxonomic groups. The superiority of this function increased from lichens to bryophytes to vascular plants to all three taxonomic groups together. The sampling method was highly influential as rooted-presence sampling decreased the performance of the power function. By contrast, biome and vegetation type had practically no influence on the superiority of the power law. Main conclusions: We conclude that SARs of sessile organisms at smaller spatial grains are best approximated by a power function. This coincides with several other comprehensive studies of SARs at different grain sizes and for different taxa, thus supporting the general appropriateness of the power function for modelling species diversity over a wide range of grain sizes. The poor performance of the Michaelis-Menten function demonstrates that richness within plant communities generally does not approach any saturation, thus calling into question the concept of minimal area

    An operational definition of the biome for global change research

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    CITATION: Conradi, T. et al. 2020. An operational definition of the biome for global change research. New Phytologist, 227:1294–1306, doi:10.1111/nph.16580.The original publication is available at https://nph.onlinelibrary.wiley.comBiomes are constructs for organising knowledge on the structure and functioning of the world’s ecosystems, and serve as useful units for monitoring how the biosphere responds to anthropogenic drivers, including climate change. The current practice of delimiting biomes relies on expert knowledge. Recent studies have questioned the value of such biome maps for comparative ecology and global-change research, partly due to their subjective origin. Here we propose a flexible method for developing biome maps objectively. The method uses range modelling of several thousands of plant species to reveal spatial attractors for different growth-form assemblages that define biomes. The workflow is illustrated using distribution data from 23 500 African plant species. In an example application, we create a biome map for Africa and use the fitted species models to project biome shifts. In a second example, we map gradients of growth-form suitability that can be used to identify sites for comparative ecology. This method provides a flexible framework that (1) allows a range of biome types to be defined according to user needs and (2) enables projections of biome changes that emerge purely from the individualistic responses of plant species to environmental changes.Publisher's versio

    Fifteen emerging challenges and opportunities for vegetation science: A horizon scan by early career researchers

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    With the aim to identify future challenges and opportunities in vegetation science, we brought together a group of 22 early career vegetation scientists from diverse backgrounds to perform a horizon scan. In this contribution, we present a selection of 15 topics that were ranked by participants as the most emergent and impactful for vegetation science in the face of global change. We highlight methodological tools that we expect will play a critical role in resolving emerging issues by providing ways to unveil new aspects of plant community dynamics and structure. These tools include next generation sequencing, plant spectral imaging, process-based species distribution models, resurveying studies and permanent plots. Further, we stress the need to integrate long-term monitoring, the study of novel ecosystems, below-ground traits, pollination interactions and global networks of near-surface microclimate data at fine spatio-temporal resolutions to fully understand and predict the impacts of climate change on vegetation dynamics. We also emphasize the need to integrate traditional forms of knowledge and a diversity of stakeholders into research, teaching, management and policy-making to advance the field of vegetation science. The conclusions reached by this horizon scan naturally reflect the background, expertise and interests of a representative pool of early career vegetation scientists, which should serve as basis for future developments in the field

    FUSE – using artificial intelligence in the energy grid of tomorrow

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    The objective of Future Smart Energy (FUSE), a Finnish-German research and development project, is to develop methods based on artificial intelligence (AI) that will help to increase the resilience of future energy distribution grids. The use cases that are investigated include both condition monitoring/predictive maintenance, and distributed demand-side management in medium-voltage and low-voltage grids. The FUSE concept foresees a hierarchical infrastructure of sensing- and data processing nodes that use AI to transform raw data into information on asset and grid status and performance. FUSE supports the upward flow of data and aggregation of information into high-level visualisations for grid operators, as well as the downward flow of soft control signals that trigger the distributed self-control of assets. This study outlines the FUSE concept and presents the first results.This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)fi=vertaisarvioitu|en=peerReviewed

    An operational definition of the biome for global change research

    Get PDF
    CITATION: Conradi, T. et al. 2020. An operational definition of the biome for global change research. New Phytologist, 227:1294–1306, doi:10.1111/nph.16580.The original publication is available at https://nph.onlinelibrary.wiley.comBiomes are constructs for organising knowledge on the structure and functioning of the world’s ecosystems, and serve as useful units for monitoring how the biosphere responds to anthropogenic drivers, including climate change. The current practice of delimiting biomes relies on expert knowledge. Recent studies have questioned the value of such biome maps for comparative ecology and global-change research, partly due to their subjective origin. Here we propose a flexible method for developing biome maps objectively. The method uses range modelling of several thousands of plant species to reveal spatial attractors for different growth-form assemblages that define biomes. The workflow is illustrated using distribution data from 23 500 African plant species. In an example application, we create a biome map for Africa and use the fitted species models to project biome shifts. In a second example, we map gradients of growth-form suitability that can be used to identify sites for comparative ecology. This method provides a flexible framework that (1) allows a range of biome types to be defined according to user needs and (2) enables projections of biome changes that emerge purely from the individualistic responses of plant species to environmental changes.Publisher's versio

    GrassPlot : the database of multi-scale plant diversity in Palaearctic grasslands

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    Understanding patterns and drivers of phytodiversity as well as ecological scaling laws and assembly rules constitute core interests both of vegetation ecologists and macroecologists. To enhance our understanding of these issues, we compiled the new “Database of Scale-Dependent Phytodiversity Patterns in Palaearctic Grasslands” (GrassPlot; GIVD ID EU-00-003) within the framework of the Eurasian Dry Grassland Group (EDGG). GrassPlot contains high-quality plot observations (relevés) of eight standard grain sizes (0.0001; 0.001 … 1000 m²) as well as nested-plot series with at least four different grain sizes. The scope of GrassPlot are the grasslands as well as other herb- or cryptogam-dominated terrestrial and semi-terrestrial vegetation types from the whole Palaearctic biogeographic realm (Europe, North Africa, West, Central and North Asia)
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