The Global Alien Species First Record Database represents a compilation of first records of alien species across taxonomic groups and regions.

A first record denotes the year of first observation of an alien species in a region. Note that this often differs from the date of first introduction. The database covers all regions (mostly countries and some islands) globally with particularly intense sampling in Europe, North America and Australasia. First records were gathered from various data sources including online databases, scientific publications, reports and personal collections by a team of >45 researchers. A full list of data sources, an analysis of global and continental trends and more details about the data can be found in our open access publication: Seebens et al. (2017) No saturation in the accumulation of alien species worldwide. Nature Communications 8, 14435.

Note that species names and first records may deviate from the original information, which was necessary to harmonise data files. Original information is provided in the most recent files.

Note that first records are sampled unevenly in space and time and across taxonomic groups, and thus first records are affected by sampling biases. From our experience, analyses on a continental or global scale are rather robust, while analyses on national levels should be interpreted carefully. For national analyses, we strongly recommend to consult the original data sources to check sampling methods, quality etc individually.

The first record database will be irregularly updated and the most recent version is indicated by the version number. _Newer Versions_ are accessible via Zenodo_: https://doi.org/10.5281/zenodo.10039630

Here, we provide several files: (1) The annual number of first records per taxonomic group and continent in an excel file, which represents the aggregated data used for most of the analyses in our paper (Seebens et al. Nat Comm). (2) The R code for the implementation of the invasion model used in the paper. (3) A more detailed data set with the first records of individual species in a region. This data set represents only a subset (~77%) of the full database as some data were not publicly accessible. This data set will be irregularly updated and may differ from the data set used in our paper. All data are free of use for non-commercial purposes with proper citation of Seebens et al. (2017) Nat Comm 8, 14435. (4) A substantially updated version of the First Record Database (vs 1.2) used in our second publication: Seebens et al. (2018) Global rise in emerging alien species results from increased accessibility of new source pools. PNAS 115(10), E2264-E2273.

Please, do not ask the contact person for data, but download it at Zenodo: https://doi.org/10.5281/zenodo.10039630 - Thanks!

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). 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: 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 The data set was revised and further extended in version 1.2, which was introduced by: 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 One of the above references needs to be cited in case of using the data set. 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:

If latest years were provided (e.g., '<1920'), this year was taken (e.g., '1920') If ranges of years larger 20 years were provided in the original source, these records were removed. 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. 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.

We developed the DAMA (Distribution of Alien MAmmals) database, a comprehensive source reporting the global distribution of the 230 species of mammals that have established, self-sustaining and free-ranging populations outside their native range due to direct or indirect human action. Every alien range is accompanied by information on its invasion stage, pathway, method of introduction and date of introduction. We collected information from 827 different sources (scientific literature, books, risk assessments, reports, online biodiversity databases and websites), and used it to draw alien range maps for these species following the IUCN mapping framework. DAMA comprises 2726 range polygons, covering 199 Countries, 2190 level 1 administrative areas and 11 zoogeographic realms for the period 21500 BC-AD 2017. The most represented orders among introduced mammal species are Rodentia (n=58, 25.22%), Cetartiodactyla (n=49 species, 21.30%), Carnivora (n=30 species, 13.04%), Diprotodontia (n=28, 12.17%) and Primates (n=26, 11.30%). Mammal species have been frequently introduced for hunting (n=100), pet trade (n=57), conservation (n=51) and fauna improvement (n=42). The majority of range polygons are placed on islands (n=2196, 80.56%), encompass populations that have moved beyond establishment and into the invasion stage (n=1655, 60.71%), and originated from 1500 AD to the present (n=1496, 54.88%). Despite inheriting literature biases towards more studied regions (e.g., developed Countries), DAMA is the most up-to-date picture of alien mammal global distribution and can be used to investigate their invasion ecology across different biogeographical regions.

The DAISIE - inventory of alien invasive species in Europe is a species checklist dataset published by the Research Institute for Nature and Forest (INBO) and the Centre for Ecology and Hydrology (CEH). It contains information on 12,104 taxa (mostly species and mostly introduced) occurring in the wild in Europe since 1500. It covers a broad taxonomic spectrum of terrestrial and aquatic free living and parasitic organisms. The collation of the alien species list is the result of the efforts of the DAISIE (http://www.europe-aliens.org/) project partners and more than 300 collaborators from Europe and neighbouring countries, involved in different fields of expertise and organisations. Here the DAISIE checklist is published as a standardized Darwin Core Archive and includes for each species: the scientific name, higher classification, and stable taxon identifier (in the taxon core), the vernacular names (in the vernacular names extension), the presence in a specific region, the year of the first introduction (first collection) and/or last assessment/observation in that region, as well as extra information (in the distribution extension), and the habitat, native range, and ecofunctional group (in the description extension). The DAISIE dataset is no longer maintained, but can be used as a historical archive for researching and managing alien plants or compiling regional and national registries of alien species. Issues with the dataset can be reported at https://github.com/trias-project/daisie-checklist

We have released this dataset under a Creative Commons Attribution license (CC-BY 4.0). We would appreciate it if you follow the GBIF citation guidelines (https://www.gbif.org/citation-guidelines) when using the data. If you have any questions regarding this dataset, don’t hesitate to contact us via the contact information provided in the metadata or via https://twitter.com/trias_project.

The publication of the checklist to GBIF was supported by the European Cooperation in Science and Technology (COST) action Alien CSI “CA17122 - Increasing understanding of alien species through citizen science” as a Short Term Scientific Mission “Publishing alien species checklist data for Europe through repeatable, open workflows”, with technical support provided by the Research Institute for Nature and Forest (INBO).

List of invasive species in Belgium following the HARMONIA system and the ISEIA protocol. Extracted from the content of the http://ias.biodiversity.be website in June 2011 by the Belgian Biodiversity Platform (http://www.biodiversity.be ) in the framework of the GBIF Taxon publication award. Detailed data available on http://ias.biodiversity.be but not published in this checklist include distribution information within Belgium, invasiveness data, impact on ecosystems and species, invasiveness status in neighboring countries, ... Detailed data available on http://ias.biodiversity.be but not published in this checklist include distribution information within Belgium, invasiveness data, impact on ecosystems and species, invasiveness status in adjoining countries, ...

This dataset contains comprehensive information about the global alien spread and distribution of macrofungi species during the last centuries (1753-2018)

The aim of this project was to develop a global indicator of biological invasion for the Convention on Biological Diversity's (CBD) 2010 target. In developing this indicator we created a database which lists all documented IAS in 57 randomly selected countries that are signatory to the CBD. In addition to this we investigated which alien species present on the Southern Ocean islands are IAS and we worked on a paper to test the global indicator of biological invasion at a national scale. All information for the above listed items are included in this collection.

The file contains native and alien ranges of 1380 species worldwide obtained from the Global Invasive Species Database (http://www.iucngisd.org/gisd/) and CABI Invasive Species Compendium (http://www.cabi.org/isc/). The data are used to produce the results shown in Seebens, Essl & Blasius: The intermediate distance hypothesis of biological invasions, which is accepted for publication in Ecology Letters. The file is in csv format containing six columns: Species name, life form, native range, alien range, distance (great circle distance between the centroids of the respective regions) and species weights. More details about the data and the analysis can be found in Seebens et al.

IAS Tracker is a project to get locations of Invasive Alien Species (IAS) from common citizens. This crowdsourced project consist in the Geoportal IASTracker (http://iastracker.ic5team.org/) (to manage, view and control user observations) and a mobile App to submit the IAS observations. IASTracker App takes advantage of Mobile high-end technology to provide quality data on IAS sightings. IASTracker aims to achieve any type of public, expert or not, with the common goal of helping to reduce the negative impacts of invasive species on biodiversity, health and economy of the affected areas.

The Global Invasive Species Database is a free, online searchable source of information about alien and invasive species that negatively impact biodiversity. The GISD aims to increase public awareness about invasive species and to facilitate effective prevention and management activities by disseminating specialist’s knowledge and experience to a broad global audience. It focuses on invasive alien species that threaten native biodiversity and natural areas and covers all taxonomic groups from micro-organisms to animals and plants. The Global Invasive Species Database (GISD) is managed by the Invasive Species Specialist Group (ISSG) of the IUCN Species Survival Commission. It was developed between 1998 and 2000 as part of the global initiative on invasive species led by the erstwhile Global Invasive Species Programme (GISP).

Database of invasive alien species (including plants, mammals, birds, fish and amphibians) present in 57 countries, with references for impact and spread information.

Dataset

This dataset was created by blunderfist

Contents

The GreekMarineICAS geodataset was created as part of the project ALAS: Aliens in the Aegean – A Sea Under Siege project (https://alas.edu.gr/), with the aim to assess the spatial extent and potential impacts of alien species in the Aegean Sea, and to improve our understanding of the mechanisms driving the impacts of invasive alien species on native marine ecosystems. Methodology of data compilation: Initially, an ICAS catalogue was created, including species classified as of high impact in the European Alien Species Information Network (EASIN), or as invasive or of high impact in recent review papers. A thorough search was conducted to look for information on the presence of these species in the Greek Seas. Georeferenced data, along with information on the reported date / year of sighting, depth range, abundance and habitat type were compiled using all available types of data sources, including published scientific literature, grey literature (e.g., theses, technical reports, and newspaper reports), offline databases (including records from past projects of universities, research institutes, the ELNAIS database, and citizen science initiatives), online scientific or citizen science databases (Algaebase, GBIF, OBIS, iNaturalist - only research-grade data), social networks (e.g., Instagram and Facebook), as well as through field work involving scientific diving and interviews with marine scientists, fishers and divers that were carried out during the ALAS project. In situ underwater sampling during the ALAS project was carried out in 2020 at 156 sites, and all sampling was conducted using non-destructive visual sampling techniques via SCUBA or free diving, down to a maximum of 20 m depth. Moreover, an unstructured interview approach was applied during the respective interviews with marine scientists, fishers and divers, while a photographic guide of the targeted ICAS was produced and provided during the interviews to enhance the species verification process. Information from social networks was specifically retrieved from the websites of diving centers, which were thoroughly checked for images of ICAS, and once relevant images were found the corresponding information was further validated through direct communication. All data were organized within an Excel spreadsheet and all duplicate records were deleted.

Context

Starting with 20 years data scrapped from NUFORC (from 97 to 2017), plus Mr. Ajayrana UFO report dataset (1949 to 2000), my idea was since the beginning to be able to predict, given sight data, which shape the UFO would be. Therefore, besides NUFORC data, I captured data from Wunderground related to those occurrences.

Content

First of all, I did some web scrapping over NUFORC website collecting data from 1997 to 2017, using R. Then I created another Python program running periodically (every 30 minutes) reading 10 rows at a time from Wunderground, but only for those cities, dates having sight records

Acknowledgements

Thanks to Wunderground for letting me capture small amounts of historical data every day. And thanks to Alura, one of the best online educating platforms I ever used, and for letting me host some of my courses about Big Data. Also, I must thank Mr. Ajayrana for his nice work

Inspiration

It is an ongoing work. Soon I will have more data and be able to create an awesome prediction model

Shapefiles representing regions in alien species databases.

1- Regions_shapefile_amphibians_reptiles - created based on the regional information available in "Capinha, C. et al. Diversity, biogeography and the global flows of alien amphibians and reptiles. Divers Distrib 23, 1313–1322 (2017)."

2- Regions_shapefile_ants_mammals - provided by "Guénard, B., Weiser, M. D., Gómez, K., Narula, N. & Economo, E. P. The Global Ant Biodiversity Informatics (GABI) database: synthesizing data on the geographic distribution of ant species (Hymenoptera: Formicidae). Myrmecological News 24, 83–89 (2017)."

3- Regions_shapefile_birds - created based on the regional information available in "Dyer, E. E., Redding, D. W. & Blackburn, T. M. The global avian invasions atlas, a database of alien bird distributions worldwide. Sci Data 4, 170041 (2017)."

4- Regions_shapefile_freshwater - provided by "Tedesco, P. A. et al. A global database on freshwater fish species occurrence in drainage basins. Sci Data 4, 170141 (2017)."

5- Regions_shapefile_macrofungi - created based on the regional information available in "Monteiro, M. et al. A database of the global distribution of alien macrofungi. Biodiversity Data Journal 8, e51459 (2020)."

6- Regions_shapefile_plants - provided by "Kleunen, M. et al. The Global Naturalised Alien Flora (GloNAF) database. Ecology 100, (2019)."

7- Regions_shapefile_spiders - created based on the regional information shared by co-author Wolfgang Nentwig

This comma-separated text file contains the 27,723 alien bird records that form the core of the Global AVian Invasions Atlas (GAVIA) project. These records represent 971 species, introduced to 230 countries and administrative areas across all eight biogeographical realms, spanning the period 6000 BCE – AD 2014. The data comprises taxonomic (species-level), spatial (geographic location, realm, land type) and temporal (dates of introduction and spread) components, as well as details relating to the introduction event (how and why the species was introduced, whether or not it is established). Each line of data consists of an individual record concerning a specific alien bird species introduced to a specific location. The data derives from both published and unpublished sources, including atlases, country species lists, peer-reviewed articles, websites and via correspondence with in-country experts.

Acknowledgements

Dyer, Ellie; Redding, David; Blackburn, Tim (2016): Data from: The Global Avian Invasions Atlas - A database of alien bird distributions worldwide. figshare.

1. Preventing the arrival of invasive alien species (IAS) is a major priority in managing biological invasions. However, information on introduction pathways is currently scattered across many databases that often use different categorisations to describe similar pathways. This hampers the identification and prioritisation of pathways in order to meet the main targets of recent environmental policies. 2. Therefore, we integrate pathway information from two major IAS databases, IUCN's Global Invasive Species Database (GISD) and the DAISIE European Invasive Alien Species Gateway, applying the new standard categorisation scheme recently adopted by the Convention on Biological Diversity (CBD). We describe the process of mapping pathways from the individual databases to the CBD scheme and provide, for the first time, detailed descriptions of the standard pathway categories. The combined dataset includes pathway information for 8323 species across major taxonomic groups (plants, vertebrates, invertebrates, algae, fungi, other) and environments (terrestrial, freshwater, marine). 3. We analyse the data for major patterns in the introduction pathways, highlighting that the specific research question and context determines whether the combined or an individual dataset is the better information source for such analyses. While the combined dataset provides an improved basis for direction-setting in invasion management policies on the global level, individual datasets often better reflect regional idiosyncrasies. The combined dataset should thus be considered in addition to, rather than replacing, existing individual datasets. 4. Pathway patterns derived from the combined and individual datasets show that the intentional pathways ‘Escape’ and ‘Release’ are most important for plants and vertebrates, while for invertebrates, algae, fungi and micro-organisms unintentional transport pathways prevail. Differences in pathway proportions among marine, freshwater and terrestrial environments are much less pronounced. The results also show that IAS with highest impacts in Europe are on average associated with a greater number of pathways than other alien species and are more frequently introduced both intentionally and unintentionally. 5. Synthesis and applications. Linking databases on invasive alien species by harmonising and consolidating their pathway information is essential to turn dispersed data into useful knowledge. The standard pathway categorisation scheme recently adopted by the Convention on Biological Diversity may be crucial to facilitate this process. Our study demonstrates the value of integrating major invasion databases to help managers and policymakers reach robust conclusions about patterns in introduction pathways and thus aid effective prevention and prioritisation in invasion management.

Deposited here are four datasets relating to the paper “The global spread and invasion capacities of alien ants” A description of each dataset follows. Dataset_1_alien_ant_species_records.csv This dataset contains the occurrence records (N=17,942) for 520 alien ant species across 525 geographic regions worldwide. It includes records of species in their native regions (“native”) as well as records of species in non-native regions, in three different categories: species recorded from border interceptions (“border.interception”), species recorded from indoor settings such as buildings and greenhouses (“established.indoors”), and species recorded in the wild (“established.outdoors”). The data was extracted on 15 June 2022 from the Global Ant Biodiversity Informatics (GABI) database (Guénard et al., 2017), which is regularly updated. Information on the literature and database sources corresponding to each record is available from GABI. Corresponding range maps for all species across all regions can be viewed at https://antmaps.org. Dataset_2_regions_and_realms.csv This dataset contains the geographic coordinates of the 525 geographic regions in the GABI database. It also provides a classification of the regions into 11 global zoogeographic realms as defined in Holt et al. (2013). Dataset_3_alien_ant_species_strata.csv This dataset contains information on the vertical habitat strata occupied by each alien ant species. Three different vertical habitat strata are listed, namely the arboreal (“arboreal”), ground-surface (“ground.surface”), and the litter-and-soil (“litter.soil”) strata (after Lucky et al., 2013). Dataset_4_ant_genera_richness_strata.csv This dataset contains information on the species richness of and vertical habitat strata occupied by each ant genus (updated from Lucky et al., 2013).

For additional information, please contact: markwong.research@outlook.com

Literature cited Guenard, B., Weiser, M. D., Gomez, K., Narula, N., and Economo, E. P. (2017). The Global Ant Biodiversity Informatics (GABI) database: synthesizing data on the geographic distribution of ant species (Hymenoptera: Formicidae). Myrmecol. News, 24, 83–89. 10.25849/myrmecol.news_024:083 Holt, B. G., Lessard, J. P., Borregaard, M. K., Fritz, S. A., Araújo, M. B., Dimitrov, D., Fabre, P., Graham, C., Graves, G., Jonsson, K. A., et al. (2013). An update of Wallace’s zoogeographic regions of the world. Science, 339, 74–78. 10.1126/science.1228282 Lucky, A., Trautwein, M. D., Guenard, B. S., Weiser, M. D., and Dunn, R. R. (2013). Tracing the rise of ants out of the ground. PLoS One, 8, e84012. 10.1371/journal.pone.0084012

Differences in the number of alien plant species in different locations may reflect climatic and other controls that similarly affect native species and/or propagule pressure accompanied by delayed spread from the point of introduction. We set out to examine these alternatives for Himalayan plants, in a phylogenetic framework. We build a database of alien plant distributions for the Himalayas. Focusing on the well-documented regions of Jammu & Kashmir (west) and Bhutan (east) we compare alien and native species for (1) richness patterns, (2) the degree of phylogenetic clustering, (3) the extent to which species-poor regions are subsets of species-rich regions and (4) continental and climatic affinities/source. We document 1470 alien species (at least 600 naturalised), which comprise ~14% of the vascular plants known from the Himalayas. Alien plant species with tropical affinities decline in richness with elevation and species at high elevations form a subset of those at lower elevations, supporting location of introduction as an important driver of alien plant richness patterns. Separately, elevations that are especially rich in native plant species are also rich in alien plant species, suggesting an important role for climate (high productivity) in determining both native and alien richness. We find no support for the proposition that variance in human disturbance or numbers of native species correlate with alien distributions. Results imply an ongoing expansion of alien species from low-elevation sources, some of which are highly invasive.

List of invasive species in Belgium following the HARMONIA system and the ISEIA protocol. Extracted from the content of the http://ias.biodiversity.be website in June 2011 by the Belgian Biodiversity Platform (http://www.biodiversity.be ) in the framework of the GBIF Taxon publication award.

Detailed data available on http://ias.biodiversity.be but not published in this checklist include distribution information within Belgium, invasiveness data, impact on ecosystems and species, invasiveness status in neighboring countries, ...

Detailed data available on http://ias.biodiversity.be but not published in this checklist include distribution information within Belgium, invasiveness data, impact on ecosystems and species, invasiveness status in adjoining countries, ...