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1,074 results for “invasive species”
Invasive Species Mapping at Harvard Forest 2005
We are monitoring vegetation at the Harvard Forest for invasive plant populations with respect to land use history and other factors. Using our historical database for the Harvard Forest Prospect Hill tract, we have begun mapping the current distribution of non-native plants as a function of past land use. The 320 ha tract of Prospect Hill is mapped by parcels with known land-use history, soils, vegetation composition, and long-term vegetation dynamics. We plan to conduct annual vegetation surveys at Harvard Forest and the adjacent Quabbin Reservation to document six key non-native species currently present in the area: A. petiolata, the non-native shrubs B. thunbergii, Rhamnus cathartica, R. frangula, Lonicera spp. and the climbing vine, Celastrus orbiculatus. We will map the GPS coordinates and record cover estimates of each species and conduct spatial analyses on these data using our extensive records and GIS maps of land use histories at these locations. Detailed site histories will be determined certain species of interest, using field and archival records. Using similar techniques, we also plan to monitor invasive plant populations at key experimental plots (including the hemlock removal experiment at Simes Tract, and the "recovery phase" of the Chronic N addition plots). Together, these landscape-level studies will provide a novel historical context for understanding biological invasions in a historical context.
Eradication via destratification: whole-lake mixing to selectively remove rainbow smelt, a cold-water invasive species.
Rainbow smelt (Osmerus mordax) are an invasive species associated with several negative changes to lake ecosystems in northern Wisconsin. We combined empirically based bioenergetics models with empirically based hydrodynamic models to assess lake destratification as a potential rainbow smelt eradication method. The dataset reported here is the otolith data from 20 age 1plus individuals.
Native and invasive species abundance distributions in lakes at North Temperate Lakes LTER 1979-2010
These data were compiled from multiple sources. We collated data on the abundance or density of aquatic invasive and native species sampled in more than 20 sites using the same methods. To control for sampling methodology and allow comparisons among native and invasive species, we only included data where both invasive and native species from a taxonomic group were sampled using the same methods across multiple sites. Exceptions were made to include rusty crayfish (Orconectes rusticus) in its native range and zebra mussel (Dreissena polymorpha) data.
Invasion Biology WikiProject Scientific Papers: Text Data Mining and LLM-based Information Extraction of Species, Locations, Habitats, and Ecosystems
<p>This dataset contains the abstract and full-text for publication DOIs from the Invasion Biology WikiProject (DOI: <a href="https://www.doi.org/10.5281/zenodo.12518036">10.5281/zenodo.12518036</a>). The data was retrieved using the <a href="https://ask.orkg.org/">ask.orkg.org</a> <a href="https://api.ask.orkg.org/docs#tag/Semantic-Neural-Search/operation/explore_documents_index_explore_get">API</a>. For the <a href="https://github.com/jd-coderepos/invasion-biology-IE/blob/main/scripts/ask-doi-list-fulltext-search.py">script</a> used to obtain the data, refer to the accompanying GitHub repository: <a href="https://github.com/jd-coderepos/invasion-biology-IE/" target="_blank" rel="noopener">https://github.com/jd-coderepos/invasion-biology-IE/</a>.</p> <p>The resulting CSV file includes the following fields: <code>"ASK ID"</code>, <code>"DOI"</code>, <code>"Title"</code>, <code>"Abstract"</code>, and <code>"Full-text"</code>.</p> <p>Of the 49,438 queried DOIs, the ASK database provided:</p> <ul> <li><strong>Total DOIs processed:</strong> 12,636</li> <li><strong>DOIs with neither abstract nor full-text:</strong> 36 (abstract token count was less than 10)</li> <li><strong>DOIs with abstracts but no full-text:</strong> 12,636</li> <li><strong>DOIs with both abstract and full-text:</strong> 2,834</li> </ul> <p>The second part of the dataset contains structured information extracted from the publications using the GPT-4o Large Language Model. This structured data is included in the zipped folder <code>structured-publications.zip</code>.</p> <p>The accompanying GitHub repository provides access to the code and scripts used at various stages of the information extraction (IE) process.</p> <p><strong>Theme of the Study:</strong><br>"Mining for Species, Locations, Habitats, and Ecosystems from Scientific Papers in Invasion Biology: A Large-Scale Exploratory Study with Large Language Models."</p>
Impacts of invasive species on food web energy pathways and quality, St. Lawrence River, 2018-2021.
This dataset contains field measurements collected between 2018 and 2021 from three fluvial lakes in the Upper St. Lawrence River (Canada), including both invaded systems (with dreissenid mussels and round goby) and uninvaded reference sites. Data include georeferenced sampling information (site, lake, latitude, longitude, month, year), water chemistry (total phosphorus, µg/L; conductivity, µS/cm), and habitat descriptors (substrate). Biological records encompass seston, macroinvertebrates, and fish. Fish data comprise species identity, sex, total length (mm), weight (g), relative weight index (Wr), and detailed fatty acid composition expressed as relative proportions (%) and concentrations (µg/mg), including essential LC-PUFAs (EPA, DHA), n-3 and n-6 polyunsaturated fatty acids. Stable isotope data are provided, including carbon (δ13C) and nitrogen (δ15N) ratios, C:N ratios, and isotopic baselines from pelagic (δ13Cpel, δ15Npel) and benthic (δ13Cben, δ15Nben) sources. Derived variables, such as pelagic diet proportion and trophic position, were calculated using the two-source mixing model described by Post (2002) (DOI: https://doi.org/10.1890/0012-9658(2002)083[0703:USITET]2.0.CO;2). These data provide a comprehensive resource for examining food web structure, energy pathways, and the ecological impacts of invasive species in large river ecosystems.
Country Compendium of the Global Register of Introduced and Invasive Species. Dataset.
<p>The Country Compendium of the Global Register of Introduced and Invasive Species (GRIIS) is a collation of data across 196 individual country checklists of alien species, along with a designation of those species associated with evidence of impact at a country level. </p>
Supplementary Table S27.1: Animal species native to South Africa that have invasive populations elsewhere.
<p>Animal species native to South Africa that have invasive populations elsewhere. Sorted by expected chronological appearance in the first place they were recorded as alien species. Notes are made on whether the introduction is known to be (Y) or not (N) from South Africa (or unknown U). Pathways are according to the CBD pathway classification scheme (Harrower et al. 2017), along with an indication of whether the introduction was intentional or accidental. Species that have multi-continental distributions, and which may in addition have some introduced populations are shown at the end of the table.</p>
IPBES Invasive Alien Species Assessment, list of literature for Chapter 3
<p>This list of literature represents the literature reviewed for chapter 3 of IPBES thematic assessment of invasive alien species and their control. Please see respective data management report for more details.</p><p>For each data management report, please refer to below links:</p><p>3.2.1 Socio-cultural drivers and social values: <a href="http://doi.org/10.5281/zenodo.8031019">10.5281/zenodo.8031019</a></p><p>3.2.2.1 Regional and national changes in human population density: <a href="http://doi.org/10.5281/zenodo.8031519">10.5281/zenodo.8031519</a></p><p>3.2.2.2 Human migration: <a href="http://doi.org/10.5281/zenodo.8032105">10.5281/zenodo.8032105</a></p><p>3.2.2.3 International crises: armed conflict and humanitarian aid: <a href="http://doi.org/10.5281/zenodo.8032211">10.5281/zenodo.8032211</a></p><p>3.2.2.4 Urbanisation: <a href="http://doi.org/10.5281/zenodo.5553573">10.5281/zenodo.5553573</a></p><p>3.2.3.5 Externalities of negative impacts and cost: <a href="http://doi.org/10.5281/zenodo.8032327">10.5281/zenodo.8032327</a></p><p>3.2.4.1 Research: <a href="http://doi.org/10.5281/zenodo.5717444">10.5281/zenodo.5717444</a></p><p>3.2.4.2 Development of communication technology:<a href="http://doi.org/10.5281/zenodo.8035280">10.5281/zenodo.8035280</a></p><p>3.2.4.3 Breeding and genomic technologies: <a href="http://doi.org/10.5281/zenodo.5591058">10.5281/zenodo.5591058</a></p><p>3.2.5 Policies, governance, and institutions: <a href="http://doi.org/10.5281/zenodo.5717451">10.5281/zenodo.5717451</a></p><p>3.3.1.1 Introductions intentionally or accidentally from agriculture, forestry, fisheries, and aquaculture: <a href="http://doi.org/10.5281/zenodo.8035344">10.5281/zenodo.8035344</a></p><p>3.3.1.2 Fragmentation of ecosystems: <a href="http://doi.org/10.5281/zenodo.8035352">10.5281/zenodo.8035352</a></p><p>3.3.1.3 Creation of anthropogenic corridors: <a href="http://doi.org/10.5281/zenodo.5529361">10.5281/zenodo.5529361</a></p><p>3.3.1.5 Changes in landscape - seascape disturbance regimes (intensification and reduction): <a href="http://doi.org/10.5281/zenodo.8036425">10.5281/zenodo.8036425</a></p><p>3.3.1.6 Landscape and seascape degradation: <a href="http://doi.org/10.5281/zenodo.5533042">10.5281/zenodo.5533042</a></p><p>3.3.2.3 Mining (minerals, metal, oil, fossils fuels): <a href="http://doi.org/10.5281/zenodo.8036498">10.5281/zenodo.8036498</a></p><p>3.3.3.1 Eutrophication and nitrient deposition: <a href="http://doi.org/10.5281/zenodo.8036544">10.5281/zenodo.8036544</a></p><p>3.3.3.2 Other contaminants in water and soil: <a href="http://doi.org/10.5281/zenodo.5587987">10.5281/zenodo.5587987</a></p><p>3.3.3.3 Marine debris: <a href="http://doi.org/10.5281/zenodo.5588374">10.5281/zenodo.5588374</a></p><p>Box 3.8: <a href="http://doi.org/10.5281/zenodo.5588389">10.5281/zenodo.5588389</a></p><p>3.3.4.1 Temperature change: <a href="http://doi.org/10.5281/zenodo.8036828">10.5281/zenodo.8036828</a></p><p>3.3.4.2 Precipitation: <a href="http://doi.org/10.5281/zenodo.8036879">10.5281/zenodo.8036879</a></p><p>3.3.4.3 Climate extremes: <a href="http://doi.org/10.5281/zenodo.5533052">10.5281/zenodo.5533052</a></p><p>3.3.4.4 Carbon dioxide enrichment in air, water: <a href="http://doi.org/10.5281/zenodo.8037007">10.5281/zenodo.8037007</a></p><p>3.3.4.5 Fire regime changes: <a href="http://doi.org/10.5281/zenodo.5591070">10.5281/zenodo.5591070</a></p><p>3.3.4.6 sea level rise: <a href="http://doi.org/10.5281/zenodo.8037086">10.5281/zenodo.8037086</a></p><p>Box 3.9 Assisted colonisation: <a href="http://doi.org/10.5281/zenodo.5535113">10.5281/zenodo.5535113</a></p><p>3.3.5.1 Biotic facilitation: <a href="http://doi.org/10.5281/zenodo.5722695">10.5281/zenodo.5722695</a></p><p>3.3.5.2 Unintended consequences of management (including biological control): <a href="http://doi.org/10.5281/zenodo.8037235">10.5281/zenodo.8037235</a></p><p>3.4.1 Natural hazards: <a href="http://doi.org/10.5281/zenodo.5533488">10.5281/zenodo.5533488</a></p><p>3.5.4 Urbanisation and Pollution: <a href="http://doi.org/10.5281/zenodo.5588440">10.5281/zenodo.5588440</a></p><p>Figure 3.34: <a href="http://doi.org/10.5281/zenodo.7861162">10.5281/zenodo.7861162</a></p><p> </p>
Invasive grass litter suppresses a native grass species and promotes disease
Plant litter can alter ecosystems and promote plant invasions by altering resource availability, depositing phytotoxins, and transmitting microorganisms to living plants. Transmission of microorganisms from invasive plant litter to live plants may gain importance as invasive plants, which often escape pathogens upon introduction to a new range, acquire new pathogens over time. It is unclear, however, if invasive plant litter affects native plant communities by promoting disease. Microstegium vimineum is an invasive grass that suppresses native populations, in part through litter production, and has acquired new fungal leaf spot diseases since its introduction to the United States. In a greenhouse experiment, we evaluated how M. vimineum litter and its pathogens mediated competition with the native grass Elymus virginicus. Microstegium vimineum litter promoted disease on E. virginicus and suppressed establishment and biomass of both species. Litter had stronger negative effects on E. virginicus than M. vimineum, increasing the relative biomass of M. vimineum. Live plant competition reduced biomass of both species and live M. vimineum increased disease incidence on E. virginicus. Altogether, invasive grass litter suppressed both species, ultimately favoring the invasive species in competition, and increased disease incidence on the native species.
Mohonk Preserve Stream Water Quality Invasive Species and Macroinvertebrate Sampling in from 2017-Present
The mission of the Mohonk Preserve is to protect the Shawangunk Mountains region and inspire people to care for, enjoy, and explore their natural world. Among these 8,000 acres are the vernal pools, permanent springs, tributaries, Humpo Marsh, and the Humpo Kill, and parts of the Kleine Kill and Coxing Kill watersheds within the Hudson River Drainage Basin. Not only are the areas around the Shawangunks established habitats for New York State (NYS) protected species, including an Audubon-designated Important Bird Area, but the watershed also encapsulates more than one agricultural land use area, as well as Rondout Creek, which is an important waterway for the New York City water supply. A conservation plan must be implemented in these areas in particular, keeping in line with the Mohonk Preserves goal to conserve the Shawangunk region for both humans and the greater ecosystem within it. Recognizing the immediate and long-term conservation needs of the streams in this region by employing volunteer data collection will be a catalyst to the Preserves understanding of which environmental threats of this area should be prioritized. The StreamWatch citizen science program will be the newest addition to an array of volunteer research areas, which include collection of weather data, phenology observations, monitoring of peregrine falcon breeding activities, and monitoring of fall hawk migration. Using concise stream monitoring protocol designed for volunteer safety and maximum data accuracy, StreamWatch will evaluate water quality using an array of parameters. Following thorough observation and assessment (which will include analyzing appearance and smell of the water, shape of the stream, canopy cover, nearby land uses, recent weather, and presence of riparian vegetation including invasive species) water quality will be evaluated by means of temperature, dissolved oxygen, pH, and turbidity measurements, in addition to a macroinvertebrate count. Width and depth will also be
Global Register of Introduced and Invasive Species: GRIIS DwCA
Published via GBIF by the Invasive Species Specialist Group (ISSG). The Global Register of Introduced and Invasive Species (GRIIS) presents validated and verified checklists (inventories) of introduced (alien) and invasive alien species at the country, territory, and associated island level. Phase 1 of the project focused on developing validated and verified checklists of countries that are Party to the Convention on Biological Diversity (CBD). Phase 2 which is on-going, aims to achieve global coverage including non-party countries and all overseas territories of countries e.g. Netherlands, France and United Kingdom. Species belonging to all Kingdoms are covered as well as occurring in all Environment/systems. Country/ Territory/ Island checklists are reviewed and verified by networks of country or species experts. Verified checklists/ species records as well as those under review are presented on the online GRIIS website (www.griis.org). Individual species records are flagged with a __yes__ for verification. Only verified checklists/ species records are presented on the GBIF Portal. <p></p>https://www.gbif.org/dataset/search?publishing_org=cdef28b1-db4e-4c58-aa71-3c5238c2d0b5<p></p>
Country Compendium of the Global Register of Introduced and Invasive Species: Standardization to Records in World Flora Online or the World Checklist of Vascular Plants
<p>The <strong>Country Compendium of the Global Register of Introduced and Invasive Species (GRIIS)</strong> is a collation of data across 196 individual country checklists of alien species, along with a designation of those species associated with evidence of impact at a country level. This compendium is available via <a href="https://zenodo.org/records/6348164">Zenodo</a> and was described by Pagad et al. <a href="https://www.nature.com/articles/s41597-022-01514-z">2022</a>:</p><ul><li>Shyama Pagad, Stewart Bisset, & Melodie A. McGeoch. (2022). Country Compendium of the Global Register of Introduced and Invasive Species. Dataset. (V1_0) [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.6348164">https://doi.org/10.5281/zenodo.6348164</a></li><li>Pagad, S., Bisset, S., Genovesi, P. <i>et al.</i> Country Compendium of the Global Register of Introduced and Invasive Species. <i>Sci Data</i> <strong>9</strong>, 391 (2022). <a href="https://doi.org/10.1038/s41597-022-01514-z">https://doi.org/10.1038/s41597-022-01514-z</a></li></ul><p> </p><p>Here I provide direct and fuzzy matches for species listed for the Plantae Kingdom in GRIIS with accepted plant names in <strong>World Flora Online</strong> (<a href="https://www.worldfloraonline.org/downloadData">version 2023.03</a>; Borsch et al. <a href="https://doi.org/10.1002/tax.12373">2020</a>) or the <strong>World Checklist of Vascular Plants</strong> (<a href="https://doi.org/10.34885/nswv-8994">version 10</a>; Govaerts et al. <a href="https://www.nature.com/articles/s41597-021-00997-6">2021</a>). Matching was done in <i>R</i> through the <a href="https://cran.r-project.org/package=WorldFlora">WorldFlora</a> package (Kindt <a href="https://bsapubs.onlinelibrary.wiley.com/doi/full/10.1002/aps3.11388">2020</a>). The taxonomic standardization process was similar to the one completed <a href="https://www.worldagroforestry.org/output/agroforestry-species-switchboard-30">during the preparation of the third major release</a> of the <a href="https://apps.worldagroforestry.org/products/switchboard">Agroforestry Species Switchboard</a> and when preparing the <strong>GlobalUsefulNativeTrees database</strong> (GlobUNT; <a href="https://worldagroforestry.org/output/globalusefulnativetrees">https://worldagroforestry.org/output/globalusefulnativetrees</a>) .</p><p>Where a matching species was found in GlobUNT, the species name in the GlobUNT database has been shown. GlobUNT has been described in the following publication: Kindt et al. (<a href="https://www.nature.com/articles/s41598-023-39552-1">2023</a>) <strong>GlobalUsefulNativeTrees, a database of 14,014 tree species, supports synergies between biodiversity recovery and local livelihoods in restoration</strong>. <i>Sci Rep</i> <strong>13</strong>, 12640. <a href="https://doi.org/10.1038/s41598-023-39552-1">https://doi.org/10.1038/s41598-023-39552-1</a>.</p><p>The developments of this dataset and GlobUNT were supported by the Darwin Initiative to project DAREX001 of <a href="https://www.darwininitiative.org.uk/project/DAREX001/"><i>Developing a Global Biodiversity Standard certification for tree-planting and restoration</i></a> and by Norway's International Climate and Forest Initiative through the Royal Norwegian Embassy in Ethiopia to the <a href="https://www.worldagroforestry.org/project/provision-adequate-tree-seed-portfolio-ethiopia"><i>Provision of Adequate Tree Seed Portfolio</i></a> project in Ethiopia. </p>
Invasive snakes on islands: dataset and species vignettes
<p>This dataset describes known introductions of snakes to islands outside of their respective historical, native ranges as of May, 2022. It was created during the preparation of the chapter "Welcome to paradise: snake invasions on islands" for the upcoming book <em>Islands and Snakes</em>, Vol. II. Details for this accompanying summary text will be provided upon final publication.</p> <p>It contains a spreadsheet/database of individual documented introductions (Island_Snakes_data_cleaned), and vignettes organized by species that summarize introductions and provide references.</p> <p> </p> <p><em><strong>Island_Snakes_data_cleaned Database Details</strong></em></p> <p>The database contains several categories of information; categories are listed in bold below.</p> <ul> <li><strong>General Introduction information</strong></li> </ul> <p>Introduced Country = the country authority over the geographic location of introduction event</p> <p>Introduced to Island = the name of the island where a snake was introduced</p> <p>Island Group Name = the name of the island grouping, if any exists</p> <p>Introduced Ocean of Sea = the name of the body(ies) of water surrounding the island where a snake was introduced</p> <p>Native Range = a general description of where the snake is native to, if known</p> <p>Date Introduced Note = any details in addition to the year provided in Date Introduced column</p> <p>Date Introduced = the date a snake was considered or recorded as introduced to an island. These dates are often approximate of based on year of publication.</p> <p>Established = a binary variable where 1 indicates a snake has established a population on that island, and 0 indicates it has not established or there is not enough evidence to determine this status.</p> <p>Currently Present on island = a binary variable where 1 indicates a snake is present on that island, and 0 indicates it is not present or there is not enough evidence to determine this status.</p> <p> </p> <ul> <li><strong>Pathway information - </strong>these variables describe known pathways of introduction to an island. All variables are binary; 1 indicates the pathway likely contributed to the introduction of the snake, 0 indicates it likely did not or there is not evidence to support that pathway.</li> </ul> <p>Nursery Trade - introduced as a result of nursery or plant trade</p> <p>Cargo - introduced as a result of cargo that is not specifically associated with nursery or plant trade</p> <p>Pet Trade - introduced as a result of importation for eventual keeping as a pet or in captive hobby herpetoculture, or escape</p> <p>Intentional - introduced intentionally to the wild by a person intending to establish a population or releasing an animal for non-religious purposes</p> <p>Industrial - introduced as a result of an industry not described in other pathways; e.g. entertainment industry, skin trade</p> <p>Research - introduced as a result of escape or release from captive animals used for research purposes</p> <p>Medicinal - introduced as a result of medicinal trade in animals</p> <p>Food - introduced as a result animals traded or imported for consumption</p> <p>Pathway comment - additional details about the pathway associated with the introduction event</p> <p> </p> <ul> <li><strong>Introduced island characteristics - </strong>attributes of the ecology and geography where snakes have been introduced. Binary variables 1 indicate there is evidence for the category, 0 indicates there is not evidence for that category. *Note*: we did not consider fully-aquatic sea-snakes in our determination of island ecology characteristics</li> </ul> <p>introduced to historically snake-free - 1 indicates that prior to the snake's introduction, no other snakes were present on the island.</p> <p>introduced to island with native snakes already there - 1 indicates that prior to the snake's introduction, native snakes were already present</p> <p>introduced to island with ecologically similar snake - 1 indicates that prior to the snake's introduction, a snake with similar ecotype was already present (native or non-native).</p> <p>introduced island with same family - 1 indicates that prior to the snake's introduction, another snake of the same family was already present (native or non-native).</p> <p>introduced island with same genus - 1 indicates that prior to the snake's introduction, another snake of the same genus was already present (native or non-native).</p> <p>island area km2 - a rough estimate of the island's total geographic area in km<sup>2</sup></p> <p>nearest large landmass (>10000km2) - the name of the nearest landmass (greater than 10,000 km<sup>2 </sup>in area) to the island where a snake was introduced (as determined by linear distance).</p> <p>distance to nearest large landmass/mainland (km) - an estimate of the linear distance from the island where a snake was introduced to the nearest landmass greater than 10,000 km<sup>2 </sup> in area.</p> <p>distance to native origin (rough km) - a rough estimate of the linear distance from the snake's native range (and source of non-native introduction, if known) to the island where the snake has been introduced. </p> <p>Native_to_nearest_large_landmass - a binary variable where 1 indicates the snake is native to the nearest large landmass names in the nearest large landmass (>10000km2) column.</p> <p>island status comment - any additional information about the ecology of geography of the island where a snake was introduced.</p> <p> </p> <ul> <li><strong>Snake characteristics - </strong>Attributes associated with the ecotype and diet of the snakes introduced to islands. Binary variables indicate whether there is evidence to support a snake's membership to a specific category.</li> </ul> <p>Constrictor - 1 indicates the snake can be classified as a constrictor- using strangulation and squeezing to subdue prey.</p> <p>Venomous - 1 indicates the snake can be classified as venomous.</p> <p>Fossorial - 1 indicates the snake can be classified as fossorial; dwelling on ground in soil or leaf litter</p> <p>Terrestrial - 1 indicates the snake can be classified as terrestrial; living on the ground but generally not in soil or leaf litter</p> <p>Aquatic - 1 indicates the snake can be classified as aquatic, living at the water's edge or near the water.</p> <p>Arboreal - 1 indicates the snake can be classified as arboreal; living mostly in trees</p> <p>Cave-dwelling (troglodytic) - 1 indicates the snake can be classified as Cave-dwelling or troglodytic</p> <p>max SVL in mm (estimate) - the maximum snout-to-vent length recorded for the introduced snake species; this information may be derived from either native or introduced ranges</p> <p>Generalist - 1 indicates the snake can be classified as having a generalist diet</p> <p>Specialist - 1 indicates the snake can be classified as having a specialist diet</p> <p>Mammals - 1 indicates the snake is documented as consuming mammals</p> <p>Birds - 1 indicates the snake is documented as consuming birds</p> <p>Amphibs - 1 indicates the snake is documented as consuming amphibians</p> <p>Reptiles - 1 indicates the snake is documented as consuming reptiles</p> <p>Inverts - 1 indicates the snake is documented as consuming invertebrates</p> <p> </p> <ul> <li><strong>Impacts of introduction - </strong> a summary of any documented impacts associated with the introduction of the snake to the island. </li> </ul> <p>Ecological Impacts - 1 indicates there is documentation to support an impact of the snake's introduction to the island's ecology</p> <p>Health Impacts - 1 indicates there is documentation to support an impact of the snake's introduction to human health on the island</p> <p>Economic Impacts - 1 indicates there is documentation to support an impact of the snake's introduction to the local economy of the island</p> <p>Impacts not measured - 1 indicates there is no formal documentation of impacts of the snake to any of the previous categories</p> <p>Impact Comment - any details about impacts, or speculated impacts</p> <p> </p> <ul> <li><strong>Management </strong></li> </ul> <p>Previous eradication Efforts - 1 indicates there have been measures taken in the past to attempt to remove the snake species from the island</p> <p>Current eradication effort - 1 indicates that as of May 2022, attempts to remove the snake species from the island are ongoing.</p> <p> </p> <p>Cool Stuff! -<strong> </strong>a category with comments on introductions that do not fit neatly elsewhere</p> <p> </p> <p><em><strong>Vignette details</strong></em></p> <p>Vignettes are organized by species, using the most up-to-date accepted species name according to the Reptile Database in May, 2022. The vignette describes documented introductions to islands, which includes multiple locations for some species.</p> <p>All vignettes follow a similar format.</p> <p><em>Species name</em> and any relevant synonyms or colloquial names are given.<br> <em>Where native</em>- describes the native range of the snake, if known.<br> <em>Where introduced, when </em>- describes the islands where a snake has been documented as introduced, and the associated dates of introduction (if they differ from the publication date)</p> <p><em>Introduced Island characteristics - </em>gives any relevant information about the ecology or geography of the island(s) where the species has been introduced</p> <p><em>Pathways of introduction </em>- gives information about pathway(s) relevant to introductions</p> <p><em>Why successful introduction </em>- if the introduction was successful (i.e. established), what factors may have played a role in this success</p> <p><em>Any failed island introductions elsewhere, why?</em> - If introductions are recorded as not established or failed, any information that may help understand the failure of the introduction to establish.</p> <p><em>Documented impacts of introduction (Ecological, Economic, Social, Human Health)</em> - any impacts documented from the introduction of the species to the island(s)</p> <p><em>Speculated impacts</em> - any potential impacts of the species' introduction to the island(s), whether unrecorded, unexamined, or estimated to have a lag time before apparent</p> <p><em>References - </em>References cited within the vignette</p> <p> </p>
The InvL Dataset of Invasive Species from drones in a Land Environment
<p><strong>Summary</strong></p> <p>An original dataset for semantic segmentation, InvL, is introduced, which to the best of the authors' knowledge, is the first dataset of its kind with pixel-level annotations pertaining to invasive species (Himalayan balsam) in a land environment from drones with height 10-30 m (GSD 3-13 mm) using optical imaging and having diverse outdoor blur, noise and contrast.</p> <p><strong>Objectives</strong></p> <p>Automated detection and quantification of invasive species from drones would enable more efficient mapping using simple low-cost technologies. This would help to <em>remove invasive and later protect species. </em>However, it is difficult to distinguish invasive species from common ones from higher altitudes using drone images. Training a machine learning algorithm to accurately detect a given invasive species from images taken in the field requires a massive amount of human-generated training data.</p> <p>Objective is to encourage people to open share images that can be used to develop technology. We are interested expand database and add author for every 1 GB added to the new version InvL or every 200 hours spent to improve annotation quality or annotation type.</p> <p>Objective is to expand establish a reference dataset for automatic extraction using gold standard training sets to gain Intersection over Union (IoU) over 0.8 from drone height over 30 meters with least GSD using low cost drones.</p> <p><strong>Data description</strong></p> <p>This data set contains images of Himalayan balsam (Impatiens glandulifera) taken mostly with the DJI Mavic 2 PRO in Finland from heights 10, 15, 20 and 30 meters, low speed 1- 2 m/s, no filters, 90 degrees angle, still images, GSD varying from 3-13mm, image size ~15 MB, between July (usually no flowers) and August (flowers).</p> <p> </p> <p> </p> <p><strong><em>Table 1. Drone images of invasive species</em></strong></p> <table> <tbody> <tr> <td> <p><strong><em>Label</em></strong></p> </td> <td> <p><strong><em>Name of data file/set</em></strong></p> <p> </p> </td> <td> <p><strong>Dataset size (GB)</strong></p> </td> <td> <p><strong>File type (extension)</strong></p> <p> </p> </td> <td> <p><strong>Data repository and identifier</strong></p> </td> <td> <p><strong>IoU estimate </strong><strong>- model</strong></p> </td> <td> <p><strong>Comment</strong></p> </td> </tr> <tr> <td> <p><em>Himalayan_balsam</em></p> </td> <td> <p><em>InvL/Himalayan_balsam</em></p> <p><em>../ann – contains annotations</em></p> <p><em>…/ann/H10m_Lahti_Peitsikatu_H10m_10072020</em></p> <ul> <li><em>H10 = 10 m UAV heigth</em></li> <li><em>Lahti = city</em></li> <li><em>10072020 (last) = date of fligth</em></li> </ul> <p><em>…/original – orginal UAV images, folder structure same as for “ann”</em></p> </td> <td> <p>2</p> </td> <td> <p>InvL.zip (folder structure with annotations and original images)</p> <p> </p> </td> <td> <p> </p> </td> <td> <p><em>Himalayan balsam </em></p> <p><em>IoU = 0.53, FCN, 15 m with augmentation IoU=0.37, FCN, 30 m</em></p> </td> <td> <p><em>Himalayan balsam, green</em></p> <p><em>Elevation varies in area +- 5m, so actual UAV flight height varies</em></p> <p><em>Each image around 15 MB</em></p> </td> </tr> </tbody> </table> <p><strong>Limitations</strong></p> <p>Annotations do not indicate width or margins.</p> <ul> <li>There is no indication of confidence of annotations.</li> <li>Blur, noise or contrast values are not calculated.</li> <li>Mostly species are easily visible and images with bright sunlight have been removed in selection of images.</li> <li>Annotator needs good and tested instruction to annotate images. Annotator needs to do work for tens of hours with developed and tested instructions to guarantee good quality. After image annotator each image should be checked by an “expert” and reannotated if necessary (silver standard, if this is done twice it is gold standard). If expert is used each image should be annotated once (silver standard) and twice (gold standard).</li> <li>Annotation time for each 15 MB image should be around one hour.</li> <li>Image GSD should be around 5 mm and less for smaller species.</li> <li>In different field areas species color and size varies and mixed vegetation may cause problems.</li> <li>In images there are flowers and non-flowers.</li> </ul> <p><strong>Abbreviations</strong> FCN: a fully convolutional neural network.</p> <p> </p>
Supplementary material 2 from: Bayliss H, Stewart G, Wilcox A, Randall N (2013) A perceived gap between invasive species research and stakeholder priorities. NeoBiota 19: 67-82. https://doi.org/10.3897/neobiota.19.4897
Journal article classifications (doi: 10.3897/neobiota.19.4897.app2) File format: Comma Separated Value File (csv).:
Supplementary material 1 from: Bayliss H, Stewart G, Wilcox A, Randall N (2013) A perceived gap between invasive species research and stakeholder priorities. NeoBiota 19: 67-82. https://doi.org/10.3897/neobiota.19.4897
Stakeholder priorities. (doi: 10.3897/neobiota.19.4897.app1) File format: Micrisoft Comma Separated Value File (csv).:
Projected distribution of invasive plant species in the tropical Andes under climate change
<p>Distribution maps of 11 invasive species now and in the future (2040-70). The projections were the result of the assembly of three algorithms: Adaptive Boosting (AdaBoost), Boosted Regression Trees (BRT), and Extreme Gradient Boosting (XGBoost). Future projections were made for three global circulation models and three climate change scenarios, each with low (SSP126), medium (SSP370), and high (SSP585) levels of carbon emission.</p> <p>Habitat suitability and presence/absence maps are also included. The threshold for establishing a species as present was determined to be the value that maximized the TSS. </p> <p>For more information, see the article accompanying the dataset by González-Trujillo et al. Mapping the threat: Projecting invasive plant distribution in the tropical Andes under climate change</p> <p>List of modeled invasive plant species and their known impacts in the tropics.</p> <table> <tbody> <tr> <td> <p><strong>Species </strong></p> </td> <td> <p><strong>Biogeographic origin</strong></p> </td> <td> <p><strong>Impacts </strong></p> </td> <td> <p><strong>References</strong></p> </td> <td> <p><strong>GBIF data (DOIs)</strong></p> </td> </tr> <tr> <td> <p><em>Acacia decurrens </em></p> </td> <td> <p>Australian</p> </td> <td> <p>Create regular layers of litter on the ground, inhibit or redirect successional processes, inhibit the expression of seed banks, and limit resource supply, leading to displacement of native plants and animals and increasing the frequency of fires.</p> </td> <td> <p> (Cárdenas López et al., 2017; Le Maitre et al., 2011)</p> </td> <td> <p>https://doi.org/10.15468/dl.mjyxhw</p> </td> </tr> <tr> <td> <p><em>Acacia melanoxylon</em></p> </td> <td> <p>Australian</p> </td> <td> <p>Alter the structure and function of their ecosystems, thereby displacing their native flora. It also causes soil erosion and alters hydrological cycles, negatively affecting agriculture.</p> </td> <td> <p>(Kumschick and Jansen, 2023; Le Maitre et al., 2011)</p> <p> </p> </td> <td> <p>https://doi.org/10.15468/dl.4cugnk</p> </td> </tr> <tr> <td> <p><em>Arundo donax</em></p> <p><em> </em></p> </td> <td> <p>Holarctic</p> </td> <td> <p>Alter<em> </em>the natural vegetation structure, outcompete native plant species and diminish the diversity and abundance of animals such as arthropods and birds. It also drives out soil, fuels forest fires, displaces native species, and increases the invasion of ticks that affect livestock.</p> </td> <td> <p>(Cárdenas López et al., 2017; Girotto et al., 2021; Lambert et al., 2010)</p> </td> <td> <p>https://doi.org/10.15468/dl.bfep4t</p> </td> </tr> <tr> <td> <p><em>Genista monspessulana</em></p> </td> <td> <p>Holarctic</p> </td> <td> <p>Alter fire regime and nutrient cycling displace native species and decrease native diversity by forming dense monospecific stands. It also facilitates the establishment of other invasive species and produces seeds that are toxic to livestock and humans.</p> </td> <td> <p>(Cárdenas López et al., 2017; Herrera et al., 2016; Pauchard et al., 2008)</p> </td> <td> <p>https://doi.org/10.15468/dl.gyhnxh</p> </td> </tr> <tr> <td> <p><em>Hedychium coronarium </em></p> </td> <td> <p>Indo-Malesian</p> </td> <td> <p>Alter hydrological and nutrient cycles in soil. It forms thickets that suppress the successional and regeneration processes of native species, thus affecting the native flora and crops.</p> </td> <td> <p>(Cárdenas López et al., 2017; Costa et al., 2019)</p> </td> <td> <p>https://doi.org/10.15468/dl.6z2jgb</p> </td> </tr> <tr> <td> <p><em>Melinis minutiflora</em></p> </td> <td> <p>African</p> </td> <td> <p>Increases the occurrence of fires, displaces native species, and alters soil properties and decomposition. It also inhibits the growth of native species.</p> </td> <td> <p>(Cárdenas López et al., 2017; Nogueira et al., 2019; Sandoval et al., 2022)</p> </td> <td> <p>https://doi.org/10.15468/dl.fsqwsv</p> </td> </tr> <tr> <td> <p><em>Pteridium aquilinum</em></p> </td> <td> <p>Holarctic</p> </td> <td> <p>Alter vegetation success processes affect crops and cause livestock poisoning. It also produces acids that inhibit root growth in native and cultivated species.</p> </td> <td> <p> (Berget et al., 2015; Cárdenas López et al., 2017; Valdez-Ramírez et al., 2020)</p> <p> </p> </td> <td> <p>https://doi.org/10.15468/dl.sp4uuv</p> </td> </tr> <tr> <td> <p><em>Ricinus communis</em></p> </td> <td> <p>African</p> </td> <td> <p>Alter vegetation success processes affect crops and cause livestock poisoning. It also produces acids that inhibit root growth in native and cultivated species.</p> </td> <td> <p>(Cárdenas López et al., 2017; Sandoval et al., 2022; Silva and Fabricante, 2022)</p> </td> <td> <p>https://doi.org/10.15468/dl.dhbphb</p> </td> </tr> <tr> <td> <p><em>Senecio madagascariensis</em></p> </td> <td> <p>African</p> </td> <td> <p>Alter soil nutrient cycles, damage to agricultural crops, and outcompete native species. It also contains substances that are toxic to both animals and humans. </p> </td> <td> <p>(Wijayabandara et al., 2021)</p> </td> <td> <p>https://doi.org/10.15468/dl.7e8eyx</p> </td> </tr> <tr> <td> <p><em>Thunbergia alata</em></p> </td> <td> <p>African</p> </td> <td> <p>Displace native species and reduce habitat heterogeneity, thereby affecting the structure and function of native ecosystems.</p> </td> <td> <p>(Cárdenas López et al., 2017; Quijano-Abril et al., 2021)</p> </td> <td> <p>https://doi.org/10.15468/dl.g9zybc</p> </td> </tr> <tr> <td> <p><em>Ulex europeaus</em></p> </td> <td> <p>Holarctic</p> </td> <td> <p>Dry soil and increase the occurrence of fires. Inhibits vegetative growth, including pastures in agricultural and livestock lands.</p> </td> <td> <p>(Anderson and Anderson, 2009; Cárdenas López et al., 2017)</p> </td> <td> <p>https://doi.org/10.15468/dl.6642q9</p> </td> </tr> </tbody> </table>
Belgian baseline distribution of invasive alien species of Union concern (Regulation (EU) 1143/2014)
<p><strong>Aims and scope</strong></p> <p>The European Alien Species Information Network team (EASIN, http://easin.jrc.ec.europa.eu) of the Joint Research Centre (JRC) requests the European member states to provide and verify the baseline distribution data of invasive alien species of Union Concern (Tsiamis et al. 2017) as provided by the EASIN mapping system (Katsanevakis et al. 2012). These are species with documented biodiversity impacts sensu the European Union Regulation on the prevention and management of the introduction and spread of Invasive Alien Species in Europe (IAS Regulation No 1143/2014) (European Union 2014). The purpose of this baseline is to set a representative geographic account of the distribution of these species at (i) country and (ii) 10km<sup>2</sup> grid level before the entry into force of the Regulation (and the listing of species through implementing regulations). This distribution provides the baseline for subsequent reporting by the member states as required by the IAS Regulation.</p> <p>The dataset provides a shapefile on the baseline distribution of the invasive species of EU concern in Belgium based on an aggregated dataset (<em>ias_belgium_t0_xxxx</em>). Data were compiled from various datasets holding invasive species observations such as data from research institutes and research projects (76%), citizen science observatories (23%) and a range of other sources (1%) such as governmental agencies, water managers, invasive species control companies, angling and hunting organizations etc. Data were normalized using a custom mapping of the original data files to Darwin Core (Wieczorek et al. 2012) where possible. Species names were mapped to the GBIF Backbone Taxonomy (GBIF 2016) using the species API (http://www.gbif.org/developer/species). Appropriate selection of records was performed based on predefined cut-off dates (see data range) and record content validation (see validation procedure). Data were then joined with GRID10k layer Belgium based on GRID10k cellcodes (ETRS_1989_LAEA).</p> <p><strong>File description</strong></p> <p>The dataset contains two types of data:</p> <ol> <li> <p>Shapefiles (<em>ias_belgium_t0_2016.zip, ias_belgium_t0_2018.zip, ias_belgium_t0_2020.zip and ias_belgium_t0_2023.zip</em>) providing the presence of the species of EU concern at 10km<sup>2</sup> (European Terrestrial Reference System projection - 1989 ETRS_1989_LAEA) level (resp. for 1st, 2nd, 3rd and 4th batch of species added to the Union List). The attributes table field “ACCEPTED” provides coded information on the distribution validation: correct squares (Y) represent data overlapping between the collated baseline data for Belgium and the EASIN maps. Incorrect data (N) can represent records mapped on wrong 10km2 squares, non-validated records or records that fall outside of the date range applied. New squares (New) represent previously unpublished data that were absent from EASIN. The work was supervised and validated by the Belgian national scientific council on invasive alien species, an official consultative structure coordinating scientific input and data aggregation between Belgian regions and institutions with regards to technical implementation of the Regulation No 1143/2014 on invasive alien species.</p> </li> <li> <p>A geojson version of the same shapefiles (<em>ias_belgium_t0_2016.geojson, ias_belgium_t0_2018.geojson, ias_belgium_t0_2020.geojson, ias_belgium_t0_2023.geojson</em>), in WGS84 projection.</p> </li> </ol> <p><strong>Date range</strong></p> <p>The baseline distribution reflects the current status and situation of the IAS of Union concern in Belgium at 10km<sup>2</sup> grid level. Historical records were not taken into consideration for the baseline. The choice of cut-off date was based on an analysis of the relative contribution of a year in defining the total distribution of the species at 1km<sup>2</sup> grid level (calculated as [the sum of unique UTM 1km<sup>2</sup> grid squares year-1/total number of unique UTM 1km<sup>2</sup> grid squares for that species]) based on the complete dataset. </p> <p>The dataset comprises observations of Union List invasive species <strong>from 2000 <em>until the entry into force </em>for every species</strong>, hence between January 2000 (2000-01-01) and February 2016 (2016-01-31) for the species of the first batch (<em>ias_belgium_t0_2016.zip</em>), between January 2000 (2000-01-01) and August 2017 (2017-08-31) for the species of the first update of the Union List (<em>ias_belgium_t0_2018.zip</em>), between January 2000 (2000-01-01) and August 2019 (2019-08-31) for the species of the second update of the Union List (<em>ias_belgium_t0_2020.zip</em>), between January 2000 (2000-01-01) and August 2022 (2022-08-2) for the species of the third update (<em>ias_belgium_t0_2023.zip</em>). For raccoon dog (<em>Nyctereutes procyonoides), </em>included in the second update (<em>ias_belgium_t0_2020.zip</em>) the date cut-off is 01/01/2000 to 31/01/2019. Note that <em>Pistia stratiotes</em>, <em>Xenopus laevis </em>and <em>Fundulus heteroclitus </em>enter into force only as from 2 August 2024, <em>Celastrus orbiculatus </em>on 2 August 2027 because of prolonged transitionary measures. However, these species are already included in the baseline now with a cut-off date set on August 2022. The data include both casual records as well as established populations and also comprise data from eradicated populations for the period 2000-2022.</p> <p><strong>Validation procedure</strong></p> <p>Record validation was performed to exclude dubious records, wrong identifications etc. This was done based on the IdentificationVerificationStatus field (to which validation information from original data were mapped) if available. In general, non-validated data were not considered for ias_belgium_t0_xxxx. Data were validated in the original datasets based on evidence (e.g. pictures), on the observer’s experience, or based on a set of predefined rules (e.g. automated validation based on geographic filtering). Data from research institutes were generally considered validated. A few casual records of EU list species that were clearly planted were discarded manually. When the original dataset did not mention any validation status, records were not considered validated and therefore not taken into account for ias_belgium_t0_xxxx, unless for Chinese mitten crab <em>Eriocheir sinensis</em>, ruddy duck <em>Oxyura jamaicensis</em>, raccoon <em>Procyon lotor</em>, Siberian ground squirrel <em>Tamias sibiricus</em>, sacred ibis <em>Threskiornis aethiopicus</em>, and red-eared slider <em>Trachemys spp</em>. For these species, we assumed all records were correct as they originate from dedicated sampling (<em>E. sinensis</em>) within research projects or represent species that are readily recognizable by people in the field. Likewise, for the second batch species, all records of Egyptian goose <em>Alopochen aegyptiaca, </em>Himalayan balsam <em>Impatiens glandulifera</em>, giant hogweed <em>Heracleum mantegazzianum </em>and muskrat <em>Ondatra zibethicus</em> (mostly derived from public eradication services) were considered validated and taken into account. For the third batch species, records of the widespread tree of heaven <em>Ailanthus altissima </em>and pumpkinseed <em>Lepomis gibbosus </em>were also considered validated. For species with less than 10 records (<em>Salvinia molesta</em>, <em>Acridotheres tristis</em>), every record was manually checked.</p> <p>A visual check was performed on the resulting distribution maps by representatives of the Belgian scientific council on IAS and the Belgian Comittee on IAS, two official bodies created in response to the EU Regulation within the framework of a cooperation agreement between the Belgian regions and the Federal Authority. Data in the distribution maps provided by EASIN but not present in ias_belgium_t0_xxxx were carefully checked and kept/rejected accordingly.</p> <p><strong>Data providers</strong></p> <p>The providers of the invasive species data for this exercise (individuals and their respective organizations) are listed in the "data providers" section of the dataset metadata. Much of the primary occurrence data that formed the basis for this aggregated dataset will be published as open data on the Global Biodiversity Information Facility (GBIF) within the framework of the <strong>Tracking Invasive Alien Species project (TrIAS, https://osf.io/7dpgr/, 2017-2020)</strong>.</p>
Landuse/Landcover predictors for invasive species distribution modelling in Europe.
<p><strong>Description</strong></p> <p>This data set contains a set of predictors characterizing land use/land cover derived from the CORINE dataset, anthropogenic pressure from the global terrestrial human footprint dataset, and the distance to the nearest waterbody, for continental Europe. All have been aligned with the 1 km<sup>2</sup> EEA Reference Grid. The climate variables based on historical (1976-2005) and future (2040-2070) scenarios are available from De Troch et al., 2020 also via Zenodo. These rasters represent the habitat and anthropogenic predictors needed in the Tracking Invasive Alien Species (TrIAS) workflow for invasive species distribution modelling (wiSDM).</p> <p><strong>Geographic coverage</strong></p> <p>Europe</p> <p><strong>Methods</strong></p> <p>Land use classes were extracted from the CORINE06 100 m GeoTiff downloaded from Copernicus. The percentage of each 1 km<sup>2</sup> EEA Reference Grid cell occupied by coniferous forest, deciduous forest, wetlands, grasslands and agriculture was calculated. Multiple land use sub-classes were aggregated for the following categories: agriculture, wetlands, grasslands (Table 1). These data layers have been processed in R to replace all NAs that are within the European landmass, with zeros to distinguish them from the ocean, which remain NA, as in the CORINE dataset. In this context, a zero reflects the absence of a given land cover attribute. </p> <p>The mean anthropogenic pressure per 1km<sup>2 </sup>EEA Reference Grid cell was extracted from the global terrestrial human footprint dataset (Venter et al, 2016). Distance to the nearest waterbody within each 1km<sup>2</sup> EEA Reference Grid cell was calculated using the 2016 Surface Water Bodies shapefile available from the EEA (https://www.eea.europa.eu/data-and-maps/data/wise-wfd-spatial/surface-water-body). </p> <p> </p> <table> <tbody> <tr> <td>Land Use Class</td> <td>CORINE LABEL</td> </tr> <tr> <td>Agriculture</td> <td>Non-irrigated arable land (211), Rice fields (213),Vineyards (221),Fruit trees and berry plantations (222),Olive groves (223),Pastures (231),Annual crops associated with permanent crops (241),Complex cultivation patterns (242),Land principally occupied by agriculture, with significant areas of natural vegetation (243)</td> </tr> <tr> <td> </td> </tr> <tr> <td> </td> </tr> <tr> <td>Coniferous forest</td> <td>Coniferous forest (312)</td> </tr> <tr> <td>Deciduous forest</td> <td>Broad-leaved forest (311)</td> </tr> <tr> <td>Grassland</td> <td>Natural grasslands (321), Moors and heathland, (322) Sclerophyllous vegetation (323)</td> </tr> <tr> <td>Wetland</td> <td>Inland marshes (411), Peat bogs (412)</td> </tr> </tbody> </table> <p>Table 1. How the the original land use/land cover types as labelled in CORINE were combined (or not).</p> <p><strong>Files</strong></p> <p>distance2water_EEA_1km.tif (distance to nearest waterbody)</p> <p>ESM1000m.tif (mean anthropogenic pressure)</p> <p>corine_perAgriculture.tif</p> <p>corine_perWetland.tif</p> <p>corine_pergrass.tif</p> <p>corine_perdeciduous.tif</p> <p>corine_perConiferous.tif</p> <p> </p>
Distribution of invasive alien species of Union concern (Regulation (EU) 1143/2014) in Belgium for the reporting period 2015-2018
<p><strong>Aims and scope</strong></p> <p>Member State authorities are required to report on the distribution in their territory of each of the invasive alien species (IAS) of Union concern. These are species with documented biodiversity impacts sensu the European Union Regulation on the prevention and management of the introduction and spread of Invasive Alien Species in Europe (IAS Regulation No 1143/2014) (European Union 2014). This distribution represents the official reporting under Article 24(1) of R.1143/2014 on invasive alien species for the period 2015–2018. Baseline distribution of these species has previously been reported and published (Adriaens et al. 2018, ).</p> <p>Data were compiled from various datasets holding invasive species observations such as data from research institutes and research projects (9%), citizen science observatories (68%) and a range of other sources (23%) such as governmental agencies, water managers etc. More specifically the dataset includes:</p> <ul> <li>The citizen science recording portals www.waarnemingen.be and www.observation.be which has a specific alert system for IAS where nature volunteers can report their observations (Adriaens et al. 2018);</li> <li>Data from the Research Institute for Nature and Forest (INBO), the Flemish government institute that coordinates N2000, WFD and BIrd Directive and IAS monitoring in the terrestrial, estuarine and freshwater environment;</li> <li>Data from the Flemish Environment Agency which performs management of muskrat and invasive water plants in Flanders, gathered with a dedicated smartphone app since 2015;</li> <li>Data from the Flemish provinces and Rato vzw that manage water plants, muskrat, giant hogweed etc.;</li> <li>Some smaller datasets from cities;</li> <li>Data from the Brussels Capital Region from the Brussels Environment data portal;</li> <li>Plant inventories of the ‘contrats de rivière’ along watercourses in Wallonia, making use of a dedicated application to collect data directly from the field (fulcrum);</li> <li>The government reporting portals for IAS of the ‘Observatoire wallon de la flore, de la faune et des habitats (Service Public de Wallonie)’;</li> <li>Some validated data from specific datasets on gbif (iNaturalist, Natusfera, Naturgucker).</li> </ul> <p>Data were normalized using a custom mapping of the original data files to Darwin Core (Wieczorek et al. 2012) where possible. Species names were mapped to the GBIF Backbone Taxonomy (GBIF 2016) using the species API (http://www.gbif.org/developer/species). The mapping was assisted by dedicated software (SMARTIE) which was specifically written for the purpose of aggregating IAS data from various sources. Appropriate selection of records was performed based on the cut-off dates (see data range) and record content validation (see validation procedure). Data were then joined with GRID10k layer Belgium based on GRID10k cellcodes (ETRS_1989_LAEA). The technical format is in line with the <a href="http://cdr.eionet.europa.eu/help/ias_regulation/material/IAS-species-distribution-user-manual">guidelines</a> provided to the member states for the compilation of reports on Species Distribution (SD) of Invasive Alien Species of Union concern.</p> <p><strong>File description</strong></p> <p>The dataset contains a shapefiles (<em>T1_Belgium_Union_List_Species.shp</em>) with the distribution of the species of Union Concern at 10km<sup>2</sup> (European Terrestrial Reference System projection - 1989 ETRS_1989_LAEA) level. The attributes table contains <em>Cellcode </em>(ETRS<sup> </sup>grid cell code) and <em>Species </em>(scientific name + authority).</p> <p><strong>Date range</strong></p> <p>The data reflects the distribution of the IAS of Union concern in Belgium in the first reporting period for the EU Regulation hence comprises observations of Union List invasive species between January 2015 (2015-01-01) and December 2018 (2018-12-31). </p> <p><strong>Validation procedure</strong></p> <p>Record validation was performed to exclude dubious records, wrong identifications etc. This was done based on the IdentificationVerificationStatus field (to which validation information from original data were mapped) if available. In general, non-validated data were not considered. Data were validated in the original datasets based on evidence (e.g. pictures), on the observer’s experience, or based on a set of predefined rules (e.g. automated validation based on geographic filtering). Data from research institutes were generally considered validated. A few casual records of EU list species that were clearly planted were discarded manually. When the original dataset did not mention any validation status, records were not considered validated and therefore not taken into account unless for Chinese mitten crab <em>Eriocheir sinensis</em>, ruddy duck <em>Oxyura jamaicensis</em>, raccoon <em>Procyon lotor</em>, Siberian ground squirrel <em>Tamias sibiricus</em>, sacred ibis <em>Threskiornis aethiopicus</em>, Egyptian goose <em>Alopochen aegyptiaca, </em>Himalayan balsam <em>Impatiens glandulifera</em>, giant hogweed <em>Heracleum mantegazzianum, </em>muskrat <em>Ondatra zibethicus </em>and red-eared slider <em>Trachemys spp</em>. For these species, it was assumed all records were correct as they originate from dedicated sampling (<em>E. sinensis</em>) within research projects, were gathered by public bodies (e.g. muskrat), or represent species that are readily recognizable by people in the field. Data provided by EASIN in the care package and GBIF data were carefully checked.</p> <p>A visual check was performed on the resulting distribution maps by representatives of the Belgian national scientific council on invasive alien species, an official consultative structure coordinating scientific input and data aggregation between Belgian regions and institutions with regards to technical implementation of the Regulation No 1143/2014 on invasive alien species.</p> <p><strong>Data providers</strong></p> <p>The providers of the invasive species data for this exercise (individuals and their respective organizations) are listed in the "data providers" section of the dataset metadata. Much of the primary occurrence data that formed the basis for this aggregated dataset will be published as open data on the Global Biodiversity Information Facility (GBIF).</p>
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