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Global Naturalized Alien Flora (GloNAF). Open access data to support research on understanding global plant invasions.
<p>This dataset is a snapshot of the Global Naturalized Alien Flora (GloNAF) database, version 2.02. GloNAF is a continuously updated, curated compilation of alien naturalized vascular plant inventories for geographic regions from around the world. The dataset has 16,429 unique taxa reported as naturalized or invasive and covers 1,343 regions (including 427 islands) from 336 data sources. For each region, the status (invasive, naturalized) is provided as listed in the original source. We provide the scientific names included with the original data source, and the matching accepted name or synonym of the taxon as given in the World Checklist of Vascular Plants (WCVP) Version 12. In addition, we provide an ESRI shapefile of polygons for each region. We also provide several variables that can be used to filter the data according to quality and completeness of alien taxon lists, which vary among the combinations of regions and data sources.</p> <p>The 'glonaf_flora2.csv' file lists the IDs ('taxon_wcvp_id') of all naturalized taxa contained in GloNAF and the regions they occur in. The 'glonaf_taxon_wcvp.csv' lists the original taxon names provided in the source data along with the corresponding accepted taxon name from the WCVP (version 12) for all alien taxa in GloNAF, regardless of their naturalization status. To link taxon names with naturalization records, join the 'id' column of the 'glonaf_taxon_wcvp.csv' file to the 'taxon_wcvp_id' column in 'glonaf_flora2.csv' . Additional information regarding the original source of the data ('glonaf_reference.csv'), specific attributes of the taxon lists ('glonaf_list.csv') and the region ('glonaf_region.csv') can also be joined similarly to 'glonaf_flora2.csv '. </p> <p> </p>
Citizen Science projects on Alien Species in Europe
<p><strong>Context</strong></p> <p>This survey relates to COST (European Cooperation in Science and Technology) Action CA17122 - Alien CSI - Increasing understanding of alien species through citizen science (see https://alien-csi.eu/). The main aim of this survey was to collect information on Citizen Science projects/initiatives involving alien species in European Member States and some neighbouring countries. The survey was performed using a google forms. Survey respondents/contributors are mentioned in this dataset as data collectors. </p> <p><strong>Definitions</strong></p> <p>We defined Citizen Science projects as project which actively involved citizens in scientific enquiry generating new knowledge or understanding on alien species. Citizens may act as contributors, collaborators, or as project leader and have a meaningful role in the project. 'Alien Species' are defined as any live specimen of a species, subspecies or lower taxon of animals, plants, fungi or micro-organisms introduced outside its natural range; it includes any part, gametes, seeds, eggs or propagules of such species, as well as any hybrids, varieties or breeds that might survive and subsequently reproduce. Alien Species thus includes both species that are invasive and species that are alien but not invasive. An 'Invasive Alien Species' is defined as an alien species whose introduction or spread has been found to threaten or adversely impact upon biodiversity and/or related ecosystem services.</p> <p><strong>Survey methodology</strong></p> <p>The survey was made available on Google Forms and disseminated online, collecting responses from June 27, 2019 to April 6, 2020. It was shared with all COST Action CA17122 participants and in each country one person coordinated contacts with existing citizen science projects involving alien and/or invasive species and requested that they complete the survey. Thus, all projects were active in EU member states and neighbouring countries, though some may also be active outside of Europe. To increase reach, the survey was also disseminated through the European Citizen Science Association (ECSA) newsletter and mailing list and respondents were asked to share it with colleagues and local networks via snowball sampling.</p> <p><strong>Questions and attribute values</strong></p> <p>Survey questions and attribute values were developed using JRC metadata standards for CS projects (Bio Innovation Service 2018) and the project metadata model of PPSR Core, a set of global, transdisciplinary data and metadata standards for Public Participation in Scientific Research (https://core.citizenscience.org/). The survey included 62 questions in nine sections:</p> <ol> <li>Contact information of the respondent;</li> <li>General characterization of the project, including a brief summary, geographical scope, time scale, hosting entities, funding, etc.; </li> <li>Information on project scope, including target audience, taxonomic and environmental scope, project aims, type of data collected, etc.;</li> <li>Policy-related information, namely if the project has policy relevance and inclusion of species listed in the EU IAS Regulation;</li> <li>Information on engagement, such as type of involvement of citizens in the design of the project, engagement methods and social media used, skills needed to participate and frequency of contributions;</li> <li>Information on feedback and support provided to participants by the project, e.g., if projects provide materials for species identification, guidelines, training activities, information on how data from the project are used, feedback mechanisms and support; </li> <li>Data quality and data management, namely validation mechanism for records, registration type, methods of recording, whether data are open and accessible to citizen scientists, data form used to store data, data standards and data licence used, whether a public data management plan was drafted for the project, and the vocabulary used with respect to biological invasions (origin, occurrence status, degree of establishment and pathway of introduction);</li> <li>Performance indicators of projects, namely, usage of apps, number of participants and number of records, whether learning is assessed, number and type of publications using data from the project; </li> <li>Notes and remarks.</li> </ol> <p><strong>Files</strong></p> <ul> <li><strong>raw_data.xlsx</strong>: includes the non-processed survey responses, supplemented with a project_ID. All GDPR sensitive data such as email addresses were omitted. Each row represents one project.</li> <li><strong>projects_excluded.csv: </strong>includes all projects that were omitted from the analysis and the specific criteria for this exclusion. </li> <li><strong>processed_data.csv</strong>: includes the cleaned, processed survey responses, used for analysis. The R code used for the analysis is available on <a href="https://github.com/alien-csi/inventory-analysis/blob/master/src/analysis.Rmd">this github repository</a>.</li> <li><strong>survey.pdf: </strong>a pdf extract from the original Google Forms, including all questions and their specifications. </li> <li><strong>analysis.Rmd</strong>: Rmarkdown script for statistical analysis. Also available on <a href="https://github.com/alien-csi/inventory-analysis/blob/master/src/analysis.Rmd">this github repository</a>.</li> </ul> <p> </p> <p> </p>
A list of newly (re)appearing alien species in Belgium in support of decision making
<h2><strong>Context</strong></h2> <p>Invasive alien species are an important driver of biodiversity loss. Policy responses are developed to address this threat and need to be based on the best available data, including information from alien species registries and occurrence data. The Tracking Invasive Alien Species (<a href="http://trias-project.be" target="_blank" rel="noopener">TrIAS</a>) project implemented a workflow based on FAIR principles to identify new species in Belgium. These are species that have been newly observed on the territory or that were newly added to a species registry or checklist. The workflow is built on the Global Biodiversity Information Facility (GBIF) and uses the Belgian Global Register of Introduced and Invasive Species (<a href="https://doi.org/10.15468/xoidmd" target="_blank" rel="noopener">GRIIS Belgium</a>) as a baseline for comparison. </p> <h2><strong>Description</strong></h2> <p>This dataset contains the outputs of the <a href="https://trias-project.github.io/indicators/06_occurrence_indicators_appearing_taxa.html" target="_blank" rel="noopener">pipeline</a> that generates a list of new alien species occurring in Belgium. This pipeline retrieves alien taxa from openly published species checklists or occurrence datasets on GBIF and compares this list with the <a href="https://doi.org/10.15468/xoidmd" target="_blank" rel="noopener">Global Register of Introduced and Invasive Species - Belgium</a> (GRIIS Belgium) which is published by the IUCN Invasive Species Specialist Group (ISSG). This register is based on the <a href="https://github.com/trias-project/unified-checklist" target="_blank" rel="noopener">unified checklist of alien species in Belgium</a> which was created by TrIAS in support of research and policy using an open and reproducible workflow. Appearing/reappearing species are defined as follows:</p> <ul> <li>Appearing: an alien species which newly occurs on the Belgian territory in the three years before the year of the GBIF download used for creating the <a href="../records/10527772" target="_blank" rel="noopener">occurrence cube for non-native taxa in Belgium</a>. We will refer to this 3 years period as <em>evaluation period</em>.</li> <li>Re-appearing: an alien species reappearing on the Belgian territory after a latency of 4 years or more. For example, we consider a taxon reappearing in 2022 if observations occur in 2022 and 2018 or before.</li> </ul> <h2><strong>Files</strong></h2> <ul> <li><code>appearing_taxa.tsv</code></li> <li><code>reappearing_taxa.tsv</code></li> </ul> <h2><strong>Field values</strong></h2> <p>Field values of <code>appearing_taxa.csv</code>: </p> <ul> <li><code>taxonKey</code>: GBIF taxonKey</li> <li><code>canonicalName</code>: scientific species name</li> <li><code>year</code>: year of appearance</li> <li><code>ncells_prot_areas</code>: number of 1x1km grid cells in protected areas</li> <li><code>ncells_BE</code>: number of 1x1km grid cells in Belgium</li> <li><code>in_prot_areas</code>: species occurs for the first time in protected areas of NATURA2000 in Belgium during the evaluation period (<code>TRUE</code>/<code>FALSE</code>)</li> <li><code>in_BE</code>: species occurs for the first time in Belgium during the evaluation period(<code>TRUE</code>/<code>FALSE</code>)</li> <li><code>class</code></li> <li><code>kingdom</code></li> <li><code>classKey</code></li> <li><code>kingdomKey</code></li> </ul> <p>Field values of <code>reappearing_taxa.csv</code>: </p> <ul> <li><code>taxonKey</code>: GBIF taxonKey</li> <li><code>canonicalName</code>: scientific species name</li> <li><code>year</code>: year of reappearance</li> <li><code>ncells_prot_areas</code>: number of 1x1km grid cells in protected areas</li> <li><code>ncells_BE</code>: number of 1x1km grid cells in Belgium</li> <li><code>in_prot_areas</code>: species reappears in protected areas of NATURA2000 in Belgium (<code>TRUE</code>/<code>FALSE</code>)</li> <li><code>in_BE</code>: species reappears in Belgium during the evaluation period (<code>TRUE</code>/<code>FALSE</code>)</li> <li><code>n_latent_years</code>: latency, in year, i.e. the number of years since last occurrence in Belgium</li> <li><code>class</code></li> <li><code>kingdom</code></li> <li><code>classKey</code></li> <li><code>kingdomKey</code></li> </ul> <h2><strong>Potential uses of the dataset</strong></h2> <p>The list of newly (re)appearing alien species in Belgium can be used for various purposes:</p> <ul> <li>to update the Belgian GRIIS checklist</li> <li>to flag the occurrence of new, regulated species on the territory (early warning)</li> <li>to develop a rapid response </li> <li>to select species for quick impact assessment</li> <li>to select species for risk assessment</li> <li>to draft alert lists</li> <li>for horizon scanning alien species</li> <li>to select species for risk assessment</li> <li>to identify new introduction patways</li> <li>...</li> </ul>
Prioritized lists of alien species in Belgium and its regions
<h2><strong>Context</strong></h2> <p>Invasive alien species are an important driver of biodiversity loss. Policy responses are developed to address this threat and need to be based on the best available data, including information from alien species registries and occurrence data. The Tracking Invasive Alien Species (<a href="http://trias-project.be" target="_blank" rel="noopener">TrIAS</a>) project implemented a <a href="https://trias-project.github.io/indicators/" target="_blank" rel="noopener">indicator workflow</a> based on FAIR principles to feed <strong>policy relevant indicators for biological invasions in Belgium</strong> from openly published checklist and occurrence data on GBIF. </p> <h2><strong>Description</strong></h2> <p>This dataset contains the outputs of the <a href="https://trias-project.github.io/indicators/08_ranking_emerging_status.html">pipeline</a> that prioritizes alien species based on their emergence status. This prioritization is built upon the information contained in:</p> <ul> <li> The <a href="https://doi.org/10.15468/xoidmd" target="_blank" rel="noopener">Global Register of Introduced and Invasive Species - Belgium</a> (GRIIS Belgium) which is published by the IUCN Invasive Species Specialist Group (ISSG) based on the <a href="https://github.com/trias-project/unified-checklist" target="_blank" rel="noopener">unified checklist of alien species in Belgium</a> which was created by TrIAS in support of research and policy using an open and reproducible workflow.</li> <li>The <a href="../records/10527772" target="_blank" rel="noopener">species occurrence cube for non-native taxa in Belgium</a>.</li> </ul> <p>We provide two different prioritization strategies: hierarchical ranking and point strategy.</p> <p>We do the prioritzation for both Belgium and its three regions separately: Flanders, Wallonia and Brussels. Only the prioritization for Belgium takes into account the emergence status (number of occurrences and observed occupancy) in Natura2000 protected areas.</p> <h3>Hierarchical ranking</h3> <p>The ranking is based on the highest emerging status. The following priority rules are applied, in order of importance:</p> <ol> <li>The more recent, the higher priority is.</li> <li>Emerging statuses in protected areas are more important than the ones defined over entire Belgium.</li> <li>Emerging statuses from occupancy are more important than the ones from occurrences.</li> <li>The higher average minimal guaranteed growth (#occs/year), the higher priority is.</li> </ol> <h3>Points strategy</h3> <p>The points strategy is based on applying gain factors to emerging statuses using the number of observations in 2020 in Belgium/region as reference (gain factor = 1). The gain factor tables for both Belgium and its regions are available in the <a title="pipeline" href="https://trias-project.github.io/indicators/08_ranking_emerging_status.html#42_Point_strategy">pipeline</a>.</p> <h2><strong>Files</strong></h2> <ul> <li><code>ranking_emerging_status_hierarchical_strategy_Belgium.tsv</code></li> <li><code>ranking_emerging_status_hierarchical_strategy_Flanders.tsv</code></li> <li><code>ranking_emerging_status_hierarchical_strategy_Wallonia.tsv</code></li> <li><code>ranking_emerging_status_hierarchical_strategy_Brussels.tsv</code></li> <li><code>ranking_emerging_status_points_strategy_Belgium.tsv</code></li> <li><code>ranking_emerging_status_points_strategy_Flanders.tsv</code></li> <li><code>ranking_emerging_status_points_strategy_Wallonia.tsv</code></li> <li><code>ranking_emerging_status_points_strategy_Brussels.tsv</code></li> </ul> <h2>Field values</h2> <p>Field values of <code>ranking_emerging_status_hierarchical_strategy_Belgium.tsv</code>: </p> <ul> <li><code>taxonKey</code>: GBIF taxonKey.</li> <li><code>canonicalName</code>: scientific species name.</li> <li><code>kingdom</code>: the kingdom the taxon belongs to.</li> <li><code>class</code>: the class the taxon belongs to.</li> <li><code>year_2022_em_status_occupancy_natura2000</code>: the emergence status of the observed occupancy in the Natura2000 protected areas of Belgium in 2022. A number between 0 and 3.</li> <li><code>year_2022_em_status_occs_natura2000</code>: the emergence status of the number of occurrences over the Natura2000 protected areas of Belgium in 2022. A number between 0 and 3.</li> <li><code>year_2022_em_status_occupancy_Belgium</code>: the emergence status of the observed occupancy over the entire Belgium in 2020. A number between 0 and 3.</li> <li><code>year_2022_em_status_occs_Belgium</code>: the emergence status of the number of occurrences over the entire Belgium in 2022. A number between 0 and 3.</li> <li><code>year_2021_em_status_occupancy_natura2000</code>: the emergence status of the observed occupancy in the Natura2000 protected areas of Belgium in 2021. A number between 0 and 3.</li> <li><code>year_2021_em_status_occs_natura2000</code>: the emergence status of the number of occurrences over the Natura2000 protected areas of Belgium in 2021. A number between 0 and 3.</li> <li><code>year_2021_em_status_occupancy_Belgium</code>: the emergence status of the observed occupancy over the entire Belgium in 2020. A number between 0 and 3.</li> <li><code>year_2021_em_status_occs_Belgium</code>: the emergence status of the number of occurrences over the entire Belgium in 2021. A number between 0 and 3.</li> <li><code>year_2020_em_status_occupancy_natura2000</code>: the emergence status of the observed occupancy in the Natura2000 protected areas of Belgium in 2020. A number between 0 and 3.</li> <li><code>year_2020_em_status_occs_natura2000</code>: the emergence status of the number of occurrences over the Natura2000 protected areas of Belgium in 2020. A number between 0 and 3.</li> <li><code>year_2020_em_status_occupancy_Belgium</code>: the emergence status of the observed occupancy over the entire Belgium in 2020. A number between 0 and 3.</li> <li><code>year_2020_em_status_occs_Belgium</code>: the emergence status of the number of occurrences over the entire Belgium in 2020. A number between 0 and 3.</li> <li><code>mean_growth</code>: the average minimal guaranteed growth of the number of occurrences calculated over the 3 year evaluation period.</li> <li><code>kingdomKey</code>: the GBIF kingdomKey, i.e. the GBIF taxonKey of the kingdom the taxon belongs to.</li> <li><code>classKey</code>: the GBIF classKey, i.e. the GBIF taxonKey of the class the taxon belongs to.</li> </ul> <p> </p> <p>Field values of <code>ranking_emerging_status_hierarchical_strategy_*<em>.tsv</em></code><em>, where <code>*</code></em> is one of: <code>Flanders</code>, <code>Wallonia</code>, <code>Brussels</code>:</p> <ul> <li><code>taxonKey</code>: GBIF taxonKey.</li> <li><code>canonicalName</code>: scientific species name.</li> <li><code>kingdom</code>: the kingdom the taxon belongs to.</li> <li><code>class</code>: the class the taxon belongs to.</li> <li><code>year_2022_em_status_occupancy_*</code>: the emergence status of the observed occupancy over the region * in 2020. A number between 0 and 3.</li> <li><code>year_2022_em_status_occs_*</code>: the emergence status of the number of occurrences over the region <strong>*</strong> in 2022. A number between 0 and 3.</li> <li><code>year_2021_em_status_occupancy_*</code>: the emergence status of the observed occupancy over the region <strong>*</strong> in 2020. A number between 0 and 3.</li> <li><code>year_2021_em_status_occs_*</code>: the emergence status of the number of occurrences over the region <strong>*</strong> in 2021. A number between 0 and 3.</li> <li><code>year_2020_em_status_occupancy_*</code>: the emergence status of the observed occupancy over the region <strong>*</strong> in 2020. A number between 0 and 3.</li> <li><code>year_2020_em_status_occs_*</code>: the emergence status of the number of occurrences over the region <strong>* </strong>in 2020. A number between 0 and 3.</li> <li><code>mean_growth</code>: the average minimal guaranteed growth of the number of occurrences calculated over the 3 year evaluation period.</li> <li><code>kingdomKey</code>: the GBIF kingdomKey, i.e. the GBIF taxonKey of the kingdom the taxon belongs to.</li> <li><code>classKey</code>: the GBIF classKey, i.e. the GBIF taxonKey of the class the taxon belongs to.</li> </ul> <p> </p> <p>Field values of <code>ranking_emerging_status_points_strategy_Belgium.tsv</code>: </p> <ul> <li><code>taxonKey</code>: GBIF taxonKey.</li> <li><code>canonicalName</code>: scientific species name.</li> <li><code>kingdom</code>: the kingdom the taxon belongs to.</li> <li><code>class</code>: the class the taxon belongs to.</li> <li><code>em_pts</code>: a number between 0 and 72</li> <li><code>mean_growth</code>: the average minimal guaranteed growth of the number of occurrences calculated over the 3 year evaluation period.</li> <li><code>year_2022_em_status_occupancy_natura2000</code>: the emergence status of the observed occupancy in the Natura2000 protected areas of Belgium in 2022. A number between 0 and 3.</li> <li><code>year_2022_em_status_occs_natura2000</code>: the emergence status of the number of occurrences over the Natura2000 protected areas of Belgium in 2022. A number between 0 and 3.</li> <li><code>year_2022_em_status_occupancy_Belgium</code>: the emergence status of the observed occupancy over the entire Belgium in 2020. A number between 0 and 3.</li> <li><code>year_2022_em_status_occs_Belgium</code>: the emergence status of the number of occurrences over the entire Belgium in 2022. A number between 0 and 3.</li> <li><code>year_2021_em_status_occupancy_natura2000</code>: the emergence status of the observed occupancy in the Natura2000 protected areas of Belgium in 2021. A number between 0 and 3.</li> <li><code>year_2021_em_status_occs_natura2000</code>: the emergence status of the number of occurrences over the Natura2000 protected areas of Belgium in 2021. A number between 0 and 3.</li> <li><code>year_2021_em_status_occupancy_Belgium</code>: the emergence status of the observed occupancy over the entire Belgium in 2020. A number between 0 and 3.</li> <li><code>year_2021_em_status_occs_Belgium</code>: the emergence status of the number of occurrences over the entire Belgium in 2021. A number between 0 and 3.</li> <li><code>year_2020_em_status_occupancy_natura2000</code>: the emergence status of the observed occupancy in the Natura2000 protected areas of Belgium in 2020. A number between 0 and 3.</li> <li><code>year_2020_em_status_occs_natura2000</code>: the emergence status of the number of occurrences over the Natura2000 protected areas of Belgium in 2020. A number between 0 and 3.</li> <li><code>year_2020_em_status_occupancy_Belgium</code>: the emergence status of the observed occupancy over the entire Belgium in 2020. A number between 0 and 3.</li> <li><code>year_2020_em_status_occs_Belgium</code>: the emergence status of the number of occurrences over the entire Belgium in 2020. A number between 0 and 3.</li> <li><code>kingdomKey</code>: the GBIF kingdomKey, i.e. the GBIF taxonKey of the kingdom the taxon belongs to.</li> <li><code>classKey</code>: the GBIF classKey, i.e. the GBIF taxonKey of the class the taxon belongs to.</li> </ul> <p> </p> <p>Field values of <code>ranking_emerging_status_points_strategy_*<em>.tsv</em></code><em>, where <code>*</code></em> is one of: <code>Flanders</code>, <code>Wallonia</code>, <code>Brussels</code>:</p> <ul> <li><code>taxonKey</code>: GBIF taxonKey.</li> <li><code>canonicalName</code>: scientific species name.</li> <li><code>kingdom</code>: the kingdom the taxon belongs to.</li> <li><code>class</code>: the class the taxon belongs to.</li> <li><code>em_pts</code>: a number between 0 and 31.5</li> <li><code>mean_growth</code>: the average minimal guaranteed growth of the number of occurrences calculated over the 3 year evaluation period.</li> <li><code>year_2022_em_status_occupancy_*</code>: the emergence status of the observed occupancy over the region <strong>*</strong> in 2020. A number between 0 and 3.</li> <li><code>year_2022_em_status_occs_*</code>: the emergence status of the number of occurrences over the region <strong>*</strong> in 2022. A number between 0 and 3.</li> <li><code>year_2021_em_status_occupancy_*</code>: the emergence status of the observed occupancy over the regin <strong>*</strong> in 2020. A number between 0 and 3.</li> <li><code>year_2021_em_status_occs_*</code>: the emergence status of the number of occurrences over the region <strong>*</strong> in 2021. A number between 0 and 3.</li> <li><code>year_2020_em_status_occupancy_*</code>: the emergence status of the observed occupancy over the region <strong>*</strong> in 2020. A number between 0 and 3.</li> <li><code>year_2020_em_status_occs_*</code>: the emergence status of the number of occurrences over the region <strong>*</strong> in 2020. A number between 0 and 3.</li> <li><code>mean_growth</code>: the average minimal guaranteed growth of the number of occurrences calculated over the 3 year evaluation period.</li> <li><code>kingdomKey</code>: the GBIF kingdomKey, i.e. the GBIF taxonKey of the kingdom the taxon belongs to.</li> <li><code>classKey</code>: the GBIF classKey, i.e. the GBIF taxonKey of the class the taxon belongs to.</li> </ul>
SInAS: A global dataset of native and alien distributions of alien species
<p>The SInAS dataset represents a collection of regional lists of alien (also called non-native or non-indigenous) species and includes information about their native ranges, alien ranges, invasion status for alien ranges, habitats and year of first record. This dataset has been generated by standardising and integrating large global databases of alien species occurrences using the SInAS workflow version 2.0. </p> <p>The SInAS dataset is described in more detail in the following scientific article, which need to be cited when using this dataset:</p> <p>Gómez-Suárez, M., Laeseke, P., and Seebens, H. (submitted) A global dataset of native and alien distributions of alien species </p> <p>The code to generate the dataset is stored on Github (https://github.com/hseebens/SInAS) with releases available on Zenodo (https://doi.org/10.5281/zenodo.3763221).</p>
Dataset containing binominal lexemes in Harakmbut (isolate, Peru), for "The derivational use of classifiers in Western Amazonia" and "When the alienability contrast fails to surface in adnominal possession: Bound nouns in Harakmbut"
<p>This is the dataset used, amongst others, in the paper: Van linden, An. Forthcoming. When the alienability contrast fails to surface in adnominal possession: Bound nouns in Harakmbut. Special Issue “Re-assessing the explanatory potential of alienability contrasts”, guest-edited by Françoise Rose & An Van linden. <em>Linguistics – An Interdisciplinary Journal of the Language Sciences</em>. [<a href="https://doi.org/10.1515/ling-2022-0039">https://doi.org/10.1515/ling-2022-0039</a>]</p> <p>For more details, see the ReadMe file.</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>
Distribution of alien tetrapods in the Iberian Peninsula
<p>We present a dataset that assembles occurrence records of alien tetrapods (amphibians, reptiles, birds and mammals) in the Iberian Peninsula, a coherent biogeographically unit where introductions of alien species have occurred for millennia. These data have important potential applications for ecological research and management, including the assessment of invasion risks, formulation of preventive and management plans, and research at the biological community level on alien species. This dataset summarizes inventories and data sources on the taxonomy and distribution of alien tetrapods in the Iberia Peninsula, comprising known locations from published literature, expert knowledge and citizen science platforms. An expert-based assessment process allowed the identification of unreliable records (misclassification or natural dispersion from native range), and the classification of species according to their status of reproduction in the wild. Distributional data was harmonized into a common area unit, the 10x10 km Universal Transverse Mercator (UTM) system (n=6,152 cells). The year of observation and/or year of publication were also assigned to the records. In total, we assembled 35,940 unique distribution records (UTM x species x Year) for 253 species (6 amphibians, 16 reptiles, 218 birds and 13 mammals), spanning between 1912 and 2020. The species with highest number of distribution records were the Mediterranean painted frog <em>Discoglossus pictus</em> (n=59 UTM), the pond slider <em>Trachemys scripta </em>(n=471), the common waxbill <em>Estrilda astrild</em> (n=1,275) and the house mouse <em>Mus musculus </em>(n=4,043), for amphibians, reptiles, birds and mammals, respectively. Most alien species recorded are native to Africa (33%), followed by South America (21%), Asia (19%), North America (12%) and Oceania (10%). Thirty-six species are classified by IUCN as threatened in their native range, namely 2 Critically Endangered (CR), 6 Endangered (EN), 8 Vulnerable (VU), and 20 species Near Threatened (NT). </p>
Coordinates and checklists of alien species populations as obtained from the DASCO workflow and the SInAS data set
<p>This data set contains coordinate records of alien (i.e., non-native) species populations worldwide and aggregated checklists of alien species for individual regions. The regions consists of non-overlapping polygons representing countries, sub-national or coastal marine ecoregions. </p><p>The data set was produced by applying the DASCO workflow (https://doi.org/10.5281/zenodo.5841930) using the SInAS database (version 2.5; https://doi.org/10.5281/zenodo.10038256). The workflow imports checklists of alien species such as those stored in SInAS, and extracts coordinates for the alien regions (according to SInAS) from GBIF and OBIS. After cleaning and thinning the coordinates, the workflow exports a list of coordinates of alien populations for all species included in SInAS and with records on GBIF or OBIS.</p><p>These files are part of a manuscript published in the journal Neobiota, where the workflow is described in detail (Seebens & Kaplan 2022, https://doi.org/10.3897/neobiota.74.81082).</p><p>DASCO_AlienCoordinates_SInAS_2.5.gz contains the coordinates of alien populations.</p><p>DASCO_AlienRegions_SInAS_2.5.csv contains the checklists of alien species per region. Note that this only includes species with GBIF and OBIS records. For more comprehensive checklists, other databases such as those listed here (https://doi.org/10.5281/zenodo.10038256) should be consulted.</p><p>OBIS_SpeciesKeys_SInAS_2.5.csv contains the species keys from OBIS.</p><p>GBIF_SpeciesKeys_SInAS_2.5.csv contains the species keys from GBIF.</p><p>DASCO_TaxonHabitats_SInAS_2.5.csv contains habitat information for individual species if available from WoRMS, Fishbase or Sealifebase (used to identify marine species).</p><p>The file DASCO_ListOriginalGBIFData_keys_SInAS_2.5.csv contains the DOIs of the originally downloaded files from GBIF, which provides the basis for the generation of the GBIF part (ie. the DASCO workflow was applied to these data sets from GBIF). Note that OBIS does not provide a DOI for downloads, and thus we cannot provide this.</p>
Alien CSI Akrotiri Bioblitz 2019
<p>The Akrotiri Bioblitz in Cyprus was a one-off event held as part of the Alien-CSI COST Action (CA17122). It took place for 24 hours between Wednesday, February 27 and Thursday, February 28, 2019. The aim of this bioblitz was to improve knowledge of the biodiversity of the Akrotiri Peninsula, identify potential risks to the biodiversity caused by invasive species and trial methods that could be used throughout Europe for this purpose. More information about the event can be found on these pages: <a href="https://osf.io/csvgz/wiki/home/">https://osf.io/csvgz/wiki/home/</a>. </p> <p> </p> <p>All bioblitz records can be found in the iNaturalist project <a href="https://www.inaturalist.org/projects/akrotiri-bioblitz-cyprus">akrotiri-bioblitz-cyprus</a> and in the GBIF dataset (Hadjikyriakou et al. 2019). At the time of writing, 396 species had obtained “research grade” status on iNaturalist and included also captive and cultivated organisms. These species were assigned native/alien status, a level of establishment using the categories described by Groom et al. (2019a) and their occurrence in Akrotiri and Cyprus was determined based on the Flora of Cyprus by Hand et al. (2021), the Cyprus Database of Alien Species (CyDAS) by Martinou et al. (2020), the Amphibians and Reptiles of Cyprus by Baier et al. (2013), Fauna Europaea (<a href="https://fauna-eu.org/">https://fauna-eu.org</a>), Sparrow and John (2016), Ridout (1983), Peterson et al. (2019), Guerrini et al. (2007), Englezou et al. (2018), Nahum et al. (2010), Christia et al. (2011), Jørgensen and Sørensen (2008), Can and Arap (2005), Haouas gharsallah et al. (2010), Flint (1997), Bouaziz-Yahiatene et al. (2017), Zogaris et al. (2012), Gözüaçık and Atay (2016), Groom et al. (2019b), Savvides et al. (2015) and Litterski & Mayrhofer (1998). In addition, we compared our bioblitz species checklist with the species present in the occurrence dataset on GBIF preceding the bioblitz (GBIF 2019). </p> <p>An overview of the establishment status of the recorded species during the Akrotiri bioblitz can be found in the csv file and summary table (pdf) included in this upload.</p>
Alien Futures Horizon Scanning dataset
<p>The data are the result of the Alien Futures Horizon Scanning project. They were collected through an open online survey (EnglishSurveyFinal.pdf) to poll specialists and stakeholders from around the world as to their opinion on the three most important issues that may affect the future global and local management of biological invasions in the next 20 to 50 years both globally and at their respective local working level.</p> <p>The dataset also contains the categorisation of these issues into topics conducted by the Alien Futures team and presented in:</p> <p>Dehnen-Schmutz, K., Boivin, T., Essl, F., Groom, Q. J., Harrison, L., Touza, J. M., Bayliss, H. (2018): Alien Futures: what is on the horizon for biological invasions?. <em>Diversity & Distributions </em>DOI:10.1111/ddi.12755</p> <p> </p>
First spectral Reflectance Dataset of Equisetum hyemale (Snake grass) Invasive Alien Plant
<p><em><span>This repository contains the first spectral reflectance dataset of <span>snakegrass</span> (Equisetum hyemale) invasive alien species recorded in South Africa. Spectral reflectance measurements were collected under lab conditions using the Spectral Evolution PSR-300 full-range spectrometer. Spectral pre-processing was performed in R statistical software to remove noisy spectra and regions and perform averaging per sample (code accessible: https://github.com/mkganyago/SpectralEvolutionFileReader).<br></span></em></p>
Dispersal of alien species in relation to the historic development of hydropower generation and navigation
<p>Dataset on dispersal of alien species in relation to the historic development of hydropower generation and Navigation along the River Danube.</p>
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>
A mapping of keywords from published papers on alien squirrels to biological invasion research themes
<p><strong>Context</strong></p> <p>This dataset was used to produce the worldl and the graphs in the editorial to the research topic <a href="https://www.frontiersin.org/research-topics/29270/ecology-impact-and-management-of-squirrel-invasions"><em>Ecology, impact and management of squirrel invasions</em></a> (La Morgia et al. 2023).</p> <p><strong>Contents of the dataset</strong></p> <p>The dataset contains the keywords of papers since 2000 harvested with a Web of Science search (performed on 29/05/2023) using the advanced search string TS=(invasive squirrel) OR TI=(invasive squirrel) OR AB=(invasive squirrel). We screened the search results, excluding papers irrelevant to alien squirrels, for example, papers on computer science or physiology, medical or other aspects without any bearing to conservation science. To do this, we checked the abstract and keywords of the papers. Out of the 401 initial papers, after this first screening, we kept 217 in this dataset. The keywords of these papers were manually assigned to alien squirrel research topics by the authors of this dataset (using an own categorisation) and then mapped to the seven broad themes of invasive alien species research of <a href="https://doi.org/10.1007/s10530-023-03067-7">Stevenson et al. (2023)</a>: </p> <ol> <li>Ecosystems: topics which discuss a specific region, or biome, or focused on a particular species strongly associated with one ecosystem type;</li> <li>Monitoring: topics regarding all aspects of monitoring, including detection, identification, and distributional mapping;</li> <li>Management and decision-making: topics discussing the management and socio-political aspects of invasion science, such as prevention, control, and policy;</li> <li>Interactions: topics discussing the interactions with native species, or the effects of those interactions</li> <li>Assessing change: topics focused on studying and analysing temporal and ecological change;</li> <li>Traits: topics that explored the characteristics of alien squirrels;</li> <li>Invasion mechanisms: topics discussing dispersal pathways and drivers of spread.</li> </ol> <p><strong>Dataset description</strong></p> <p>Every row (N = 1275) in the comma-separated .csv represents one original keyword with reference to the paper in which that keyword appears and mapped to the research topics on invasive squirrels and the broad themes in invasion biology research. The .csv contains the following fields:</p> <ul> <li>ID: a unique ID assigned to the combination of an original keyword and the corresponding paper harvested from the WoS search</li> <li>original_keyword: the original keywords associated with the paper (WoS search)</li> <li>keyword_topic: categorization of original keywords into topics related to invasive squirrel research by La Morgia et al. (2023)</li> <li>mapped_category: mapping to one of the seven broad themes of invasive alien species research of <a href="https://doi.org/10.1007/s10530-023-03067-7">Stevenson et al. (2023)</a> as listed and described above</li> <li>authors: author(s) of the paper (WoS search)</li> <li>year: publication year of paper (WoS search)</li> <li>title: title of the paper (WoS search)</li> <li>journal: full journal name (WoS search)</li> <li>doi: full doi of the paper (WoS search)</li> </ul> <p><strong>Potential applications of the dataset</strong></p> <p>This dataset can be used to reproduce the graphs in La Morgia et al. (2023) or to perform more in-depth review or analysis of the literature on alien squirrel invasions. For more information and graph code, we refer to <a href="https://github.com/Vale-LaMo/squirrels">this GitHub repository</a>.</p>
Alien Species First Records Database
<p>The Alien Species First Records data set contains years (first records) when an established alien species was first recorded in a region (mostly countries, but also sub-national units).</p><p>The first records were gathered in a collaborative effort involving >50 researchers worldwide from various sources consisting of online databases, scientific publications, reports and personal collections. A full list of data sources is provided in the data set and the data are described in more detail in the (compilation of data, list of data sources, delineation of continents, analyses etc.) in the following publication, which can be downloaded with free access:</p><p>Seebens, H., Blackburn, T. M., Dyer, E. E., Genovesi, P., Hulme, P. E., Jeschke, J. M., … Essl, F. (2017). No saturation in the accumulation of alien species worldwide. Nature Communications, 8(1), 14435. https://doi.org/10.1038/ncomms14435</p><p>The data set was revised and further extended in version 1.2, which was introduced by:</p><p>Seebens, H., Blackburn, T. M., Dyer, E. E., Genovesi, P., Hulme, P. E., Jeschke, J. M., … Essl, F. (2018). Global rise in emerging alien species results from increased accessibility of new source pools. Proceedings of the National Academy of Sciences, 115(10), E2264–E2273. https://doi.org/10.1073/pnas.1719429115</p><p>One of the above references needs to be cited in case of using the data set.</p><p>Note that single years of first records were generated from original records in cases latest years (e.g., '<1920', 'pre-1920') or ranges (e.g., '1920s', 1920-1930') were provided in the original document following these rules:</p><ul><li>If latest years were provided (e.g., '<1920'), this year was taken (e.g., '1920')</li><li>If ranges of years larger 20 years were provided in the original source, these records were removed.</li><li>If ranges of years equal or less than 20 years were provided in the original document, a random year was selected from this time period. This was done to avoid artificial peaks at e.g. the mean value or the first year of that period.</li></ul><p>Consequently, some records represent years randomly drawn from the original time period, which makes the column 'FirstRecord' different from the original data source. The original first record as provided in the source is provided in the column 'FirstRecord_orig' of the data set.</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>
Figure 3 in Population structure of a native and an alien species of snail in an urban area of the Atlantic Rainforest
Figure 3. Detectability probability (A), abundance (B) and recruitment (C) estimated for Achatina fulica during the study. The error bars show 90% confidence intervals.
Fig. 5. A in Two new species and ten new records of Heteroptera from Turkey, including the first record of the potential alien Campylomma miyamotoi in the Western Palaearctic
Fig. 5. A ‒ Phytocoris (Exophytocoris) carapezzai sp. nov., alive female attracted to UV light; B‒C ‒ Campylomma miyamotoi Yasunaga, 2001 (B ‒ male; C ‒ female). D ‒ Hallodapus concolor (Reuter, 1890), male; E ‒ Zanchius breviceps (Wagner, 1951), alive male on Ficus sp.; F ‒ Montandoniola moraguesi (Puton, 1896), alive male attracted to UV light; G ‒ Temnostethus (Temnostethus) gracilis Horváth, 1907, male; H ‒ Plinthisus (Isioscytus) minutissimus Fieber, 1864, female.
Fig. 2 in Two new species and ten new records of Heteroptera from Turkey, including the first record of the potential alien Campylomma miyamotoi in the Western Palaearctic
Fig. 2. Phytocoris (Exophytocoris) carapezzai sp. nov.: A ‒ male; B ‒ posterior leg; C‒D ‒ vesica in two different views; E ‒ left paramere; F ‒ right paramere. Scale bars: A, B ‒ 1 mm; C, D ‒ 0.1 mm; E, F ‒ 0.1 mm.
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