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Emiliano Agrillo

Researcher at Sapienza University of Rome

Publications -  41
Citations -  1371

Emiliano Agrillo is an academic researcher from Sapienza University of Rome. The author has contributed to research in topics: Vegetation (pathology) & Vegetation. The author has an hindex of 14, co-authored 36 publications receiving 870 citations. Previous affiliations of Emiliano Agrillo include University of Pavia.

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European Vegetation Archive (EVA): an integrated database of European vegetation plots

Milan Chytrý, +96 more
TL;DR: The European Vegetation Archive (EVA) as mentioned in this paper is a database of European vegetation plots developed by the IAVS Working Group Europe Vegetation Survey (WGSVSS) since 2012 and made available for use in research projects in 2014.
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sPlot – A new tool for global vegetation analyses

Helge Bruelheide, +184 more
TL;DR: The sPlot database as mentioned in this paper contains 1,121,244 vegetation plots, which comprise 23,586,216 records of plant species and their relative cover or abundance in plots collected worldwide between 1885 and 2015.
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EUNIS Habitat Classification: expert system, characteristic species combinations and distribution maps of European habitats

Milan Chytrý, +107 more
TL;DR: This article developed the classification expert system EUNIS-ESy, which assigns vegetation plots to European habitats based on their species composition and geographic location. But the system is not suitable for outdoor gardening.
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A comparative framework for broad‐scale plot‐based vegetation classification

TL;DR: A framework to facilitate comparisons between broad-scale plot-based classification approaches, based on the distinction of four structural elements (plot record, vegetation type, consistent classification section and classification system) and two procedural elements (classification protocol and classification approach).
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History and environment shape species pools and community diversity in European beech forests

TL;DR: A framework of community assembly at a continental scale is used to test the relative influence of historical and environmental drivers, in combination with regional or local species pools, on community species richness and community completeness and empirically demonstrate how historical factors complement environmental gradients to provide a better understanding of biodiversity patterns across multiple regions.