A novel chorological data compilation for the main European tree and shrub species is presented. This dataset was produced by combining numerous and heterogeneous data collected from 20th century atlas monographs providing complete species distribution maps, and from more recent national to regional atlases, occurrence geodatabases and scientific literature. The dataset is composed of numerous species distribution maps available in geographical information system (GIS) format, created by compiling, evaluating and synthesizing data of all collected sources. The geometry of the individual datasets describes contiguous large areas of occupancy of each species as polygons and fragmented or isolated occurrences as points. Since this geodatabase is intended to provide a synthetic continental-scale overview of the species ranges, the maps represent the species’ general chorology and the presence/absence information should not be considered absolute in terms of geolocation. Errors and imprecisions arising from the interpretation and digitalization processes are likely to occur, especially in those areas where detailed information is scarce. As new information sources become available, these will be used to address current data gaps, implement corrections and updates of the chorology dataset as well as expanding it to comprise additional species.
Abstract. Forest ecosystems play a key role in the global carbon cycle. Spatially explicit data and assessments of forest biomass and carbon are therefore crucial for designing and implementing effective sustainable forest management options and forest related policies. In this contribution, we present European-wide maps of forest biomass and carbon stock spatially disaggregated at 1km x 1km. The maps originated from a spatialisation improvement of the IPCC methodology for estimating the forest biomass at IPCC Tier 1 level (IPCC-T1). Using a categorical map of ecological zones within the mapping technique may originate boundary effects between the ecological zones. This may induce undue artifacts in the outcomes, as evident in previously published maps generated with the IPCC-T1 methodology. Here we present a novel method for IPCC-T1 biomass mapping which mitigates these artifacts. We propose the use of a fuzzy similarity map of the FAO ecological zones computed by estimating the relative distance similarity (RDS) of each grid-cells climate and geography with respect to the FAO ecological zones. A robust ensemble approach was used to merge an array of simple models with spatially distributed fuzzy set-membership. This allowed the boundary artifacts to be reduced, while mitigating the impact of model semantic extrapolation. The chain of semantically enhanced data-transformations is described following the semantic array programming paradigm. Preliminary results obtained from the application of this novel approach are presented along with a discussion of its impact on the derived maps.
An updated series of distribution maps of more than 50 taxa, mainly of forest tree species, is presented along with the description of involved materials, inventory data and ancillary datasets, data-processing and modelling methods. Different methodologies are discussed and corresponding specific maps are presented for supporting the assessment on emerging plant pest risks. Updated maps of taxa habitat suitability are also presented. Maps, material and methods for supporting the risk assessment on Phytophthora ramorum for the European territory and for supporting the evaluation on Agrilus planipennis are provided. Maps, material and methods related to the assessment of the current spatial distribution of pine wilt nematode and of some of its main host plants, and also of relatively less investigated ones, have been presented at European and global scale. In this respect, four host taxa have been of particular interest: one species (Pinus pinea) and three genera (Juniperus, Chamaecyparis, Cryptomeria). The distribution of Monochamus at global scale has also been presented and its uncertainty has been discussed. A new XML based description of the subset of fields from the PRASSIS schema which are relevant in describing forest inventories is presented, along with a series of relevant metadata of forest inventories. A detailed analysis of plant biodiversity indicators, endangered/rare plant species and plant biodiversity related information is provided. The final design of the online pre-questionnaire regarding the definition of the spatial units for the questionnaire "Spatial information of forest practices in Europe" and the current stage of the actual excel-based questionnaire are presented. © Copyright 2011Copyright , 2012Copyright , 2013 European Union KEY WORDSService Level Agreement, exotic plant pests, forest tree species distribution, habitat suitability, biodiversity, indicators, forestry practices DISCLAIMERThe present document has been produced and adopted by the bodies identified above as author(s). This task has been carried out exclusively by the author(s) in the context of a contract between the European Food Safety Authority and the author(s) (Service Level Agreement between the European Community and the European Food Safety Authority SLA/EFSA-JRC/PLH/2010/01). The present document is published complying with the transparency principle to which the Authority is subject. It may not be considered as an output adopted by the Authority. The European Food Safety Authority reserves its rights, view and position as regards the issues addressed and the conclusions reached in the present document, without prejudice to the rights of the authors. The present document has been produced and adopted by the bodies identified above as author(s). This task has been carried out exclusively by the author(s) in the context of a contract between the European Food Safety Authority and the author(s) (Service Level Agreement between the European Community and the European Food Safety Authority SLA/EFSA-JRC/PLH/...
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.