First insights into the scale of invasions in African marine protected areas: leveraging global databases and citizen science data

399 First insights into the scale of invasions in African marine protected areas: leveraging global databases and citizen science data Sarah J. Ackland1, David M. Richardson1, Tamara B. Robinson1 1 Centre for Invasion Biology, Department of Botany and Zoology, Stellenbosch University, Matieland, 7609, South Africa Corresponding author: Tamara B. Robinson ([email protected]) Copyright: © Sarah J. Ackland et al. This is an open access article distributed under terms of the Creative Commons Attribution License (Attribution 4.0 International – CC BY 4.0). Research Article Abstract Up-to-date information on the distribution of alien species is essential for evidence-based management. However, routine monitoring is resource intensive. This has led to regional biases in the availability of information on invasions, with little understanding of invasions in many developing regions, including Africa. This knowledge gap, particularly problematic for marine protected areas (MPAs), challenges the ability of African states to meet their obligations under the Global Biodiversity Framework (GBF) Target 6. This study drew on freely available global databases (Protected Planet; World Register of Introduced Marine Species; World Register of Marine Species) and citizen science data (iNaturalist) to provide novel insights into marine alien species in African MPAs. A total of 27 species were recorded within 17 MPAs across seven countries. The potential threat posed to these MPAs was assessed using the EICAT and SEICAT impact schemes. Worryingly, species known to have impacts of massive or major magnitude were documented in nine MPAs (Table Mountain National Park, Robben Island, Sixteen Mile Beach, Langebaan Lagoon, Namaqua National Park – all in South Africa); Namibian Islands (Namibia); Ilhas Formosa, Nago and Tchedia (Urok) (Guinea-Bissau); Banc d’Arguin National Park (Mauritania); Massa (Morocco)). When used in conjunction with curated databases, iNaturalist offered cost-effective and verifiable records of some alien species in under-surveyed MPAs. By leveraging data from disparate databases, this study improves our knowledge of the scale of invasions in African MPAs and provides a foundation upon which States can prioritise monitoring within their MPA networks. Ultimately, these data could support the development of targeted routine monitoring programmes which could assist the management of marine invasions and the attainment of GBF Target 6. Key words: Africa, biological invasions, community science, data acquisition, impacts, iNaturalist, management, protected areas Introduction Biological invasions are a major driver of global environmental change (Ricciardi et al. 2021) and protected areas are not immune to the impacts of invasive alien species (Shackleton et al. 2019, 2020). The Kunming-Montreal Global Biodiversity Framework (GBF), developed under the Convention on Biological Diversity (CBD), proposes 23 targets to support and guide the achievement of the Sustainable Development Goals and the global vision to reduce anthropogenic impacts on biodiversity by 2030 (Robinson et al. 2025). Target 6 aims to reduce the rate of introductions and establishment of known or potentially invasive alien species by at least 50% by 2030 (CBD/COP/DEC/15/4). The aim of this target is to eliminate, Academic editor: Paula Chainho Received: 10 February 2025 Accepted: 3 June 2025 Published: 7 October 2025 Citation: Ackland SJ, Richardson DM, Robinson TB (2025) First insights into the scale of invasions in African marine protected areas: leveraging global databases and citizen science data. In: Anastácio P, Ribeiro F, Chainho P (Eds) Invasions in Aquatic Systems. NeoBiota 102: 399–418. https://doi.org/10.3897/ neobiota.102.149275 NeoBiota 102: 399–418 (2025) DOI: 10.3897/neobiota.102.149275 Advancing research on alien species and biological invasions A peer-reviewed open-access journal NeoBiota 400 NeoBiota 102: 399–418 (2025), DOI: 10.3897/neobiota.102.149275 Sarah J. Ackland et al.: Invasions in African MPAs minimise, reduce and mitigate the overall impacts of alien species on biodiversity and ecosystem services (CBD/COP/DEC/15/5). The target also requires the eradication or control of alien species in priority sites (e.g. protected areas) as these areas allow for conservation objectives to be met while providing economic, political and social benefits (Busch 2008). Although the availability of global data on alien species and their distribution has improved greatly over the last few decades (Pyšek et al. 2020), substantial geographical biases still remain, often reflecting the developmental and socioeconomical status of regions (Pyšek et al. 2008, 2020; Nuñez and Pauchard 2010). This can be seen, for example, in the focus of research effort in the Americas and Europe (Hulme et al. 2014). Inconsistencies in the availability of information across continents has also been highlighted. For example, as of 2006, work in South Africa accounted for approximately two-thirds of research effort on biological invasions on the African continent (Pyšek et al. 2008). Dedicated efforts to provide up-to-date alien species lists (e.g. Zengeya and Wilson (2023) for South Africa)) has improved the understanding of alien species in some countries, but many still lag behind. For example, there is a need for comprehensive invasive plant species lists for sub-Saharan Africa (Witt et al. 2018) and no data are available for many regions (Richardson et al. 2022). The same situation exists for other taxa. While the responsibility for the provision of such information usually falls on to researchers, the outputs of such studies are of practical use for managers (Ojaveer et al. 2015). The lack of foundational knowledge within understudied regions has the potential to perpetuate knowledge debt. This challenge is especially prevalent in developing regions where the management of alien taxa is already limited (Kumar Rai and Singh 2020). Global declines in marine biodiversity and threats posed by anthropogenic actions have led to the increasing implementation of marine protected areas (MPAs) (Ban et al. 2015; Chukwuka et al. 2025). Defined as geographical spaces dedicated to legally manage long-term conservation of ecosystem functions, services and cultural values (Day et al. 2012), MPAs are important marine conservation tools. Given the multitude of threats (including biological invasions) facing marine systems (Evariste et al. 2018; Horwitz et al. 2020; Pyšek et al. 2020; Renchen et al. 2021) and the fact that conservation agencies have limited resources (Delaney et al. 2008; Beric and MacIsaac 2015), managers must prioritise how and where to spend scarce resources. However, despite much effort, current management and conservation efforts are inadequate in most protected areas (Crain et al. 2009; Borja et al. 2016; Chukwuka et al. 2025). Marine protected areas serve a number of economic, ecological and societal aims, all of which are undermined by biological invasions. The need to address alien species and quantify the scale of invasions in MPAs is thus crucial to ensure that MPAs meet their intended purpose. Monitoring provides critical information on the changing scale of invasions and is crucial for evidence-based management (Lehtiniemi et al. 2020; Loureiro et al. 2021). When collected systematically over space and time, such information supports comprehensive databases that provide temporal and spatial insights into invasions (Delaney et al. 2008). However, monitoring is challenging in marine environments because of to their complex nature (D’Amen and Azzurro 2020). Their underwater landscapes and interconnectedness make invasions in the marine realm difficult to document and manage (Arndt et al. 2018). Additionally, largescale, long-term monitoring rarely occurs due to resource limitations (Delaney et 401 NeoBiota 102: 399–418 (2025), DOI: 10.3897/neobiota.102.149275 Sarah J. Ackland et al.: Invasions in African MPAs al. 2008; Beric and MacIsaac 2015). Cost-effective methods of monitoring are needed to bridge the gap between data requirements and scientific understanding (Lehtiniemi et al. 2020; Howard et al. 2022). One way of achieving this is to utilise crowd-sourced data provided by citizen science initiatives (Horwitz et al. 2020; Howard et al. 2022). The advancement of technology and the recent proliferation of online platforms has enhanced the potential for monitoring by using devices and smartphone applications (Daniels et al. 2022; Howard et al. 2022). Applications, such as iNaturalist, enable observers to upload photographic evidence of individual sightings and suggest taxonomic identifications (Pimm et al. 2015; Howard et al. 2022). Records collected by observers have the potential to provide a large volume of data over a wide area. If utilised with due attention to inherent limitations, citizen science offers a complementary source of data to support effective monitoring of alien species (Howard et al. 2022; Potgieter et al. 2024). iNaturalist has facilitated many useful insights within the marine realm, including improved understanding of reef fish species richness (Roberts et al. 2022), biodiversity patterns (Rocha et al. 2024) and invasions (Compagnone et al. 2024). For African countries to meet their obligations under GBF Target 6, better foundational knowledge on the presence of alien species within MPAs is essential. Underdeveloped regions are already experiencing a high economic burden which is exacerbated by the financial demands associated with managing invasive species (Bradshaw et al. 2024). The monitoring required to provide information for routine management of alien species has the potential to further intensify financial strain, challenging the acquisition of foundational knowledge and the implementation of effective management. Accordingly, this study aimed to: (1) provide insights into the scale of alien species in African MPAs through the use of global databases and citizen science data from iNaturalist; and (2) assess the potential environmental and socio-economic impacts posed by these taxa. Methods Marine protected areas (MPAs) along the African coast were identified using the open-access Protected Planet database (https://www.protectedplanet.net/en/thematic-areas/marine-protected-areas; accessed: 9 January 2024). This database, the most comprehensive and up-to-date source of data on protected areas, collates submissions from government agencies, non-governmental organisations and local communities. Marine Protected Areas were defined using the filters listed in Suppl. material 1. Data, extracted over a single day (9 January 2024), covered all African MPAs declared prior to January 2024. Records of all species reported as alien [i.e. species whose presence in a region is attributable to human actions enabling crossing of biogeographical barriers sensu Richardson et al. (2011)] along the African coast were extracted from the World Register of Introduced Marine Species (WRiMS; Costello et al. (2024); https:// www.marinespecies.org/introduced/aphia.php?p=checklist; accessed: 10 September 2024). Data included both occurrence records of alien species as well as records of established populations. This database was selected as it collates data from peer-reviewed articles to provide the most comprehensive and standardised global-scale database of marine introduced organisms (Costello et al. 2021). All species records that were extracted were inspected and a three-step cleaning procedure was applied. As data extracted from WRiMS include both accepted names and 402 NeoBiota 102: 399–418 (2025), DOI: 10.3897/neobiota.102.149275 Sarah J. Ackland et al.: Invasions in African MPAs synonyms with no option to filter out these redundancies, all taxonomic duplicates were checked and removed to avoid overestimations of the number of alien species. Scientific names were then updated according to the most recent nomenclature collated in the World Register of Marine Species (WoRMS; Ahyong et al. (2024); https://www.marinespecies.org; accessed: 10 September 2024). Since WRiMS contains both marine and estuarine data, all oligohaline species were inspected. Using current literature to investigate salinity tolerances, only species with a tolerance for marine environments were retained. To ensure that no published records of alien species were inadvertently excluded, a search was conducted on the ISI Web of Science on 10 September 2024. A systematic literature review was conducted using the following search string “marine” AND “alien” OR “invasive” OR “introduced” OR “nonnative” AND “country name”. As the terminology used to describe alien species is inconsistent and highly variable in the literature (Lockwood et al. 2013), broad search terms (i.e. “alien”, “invasive”, “nonnative” and “introduced”) were used to capture as much of the relevant literature as possible. As no additional records of marine alien species were detected in the literature search, the dataset extracted from WRiMS was accepted as complete. Utilising the explore page on iNaturalist (https://www.inaturalist.org; accessed: 18–19 September 2024), searches were made for each species listed as alien in any African country on WRiMS. Records for each species across all quality grades were extracted from iNaturalist for the period 1 April 2008 (the date of establishment of the iNaturalist platform) to 18 September 2024. Information on the species identification (scientific name and associated media), the date of observation, the date in which the observation was uploaded to the platform, the coordinates of the observations and positional accuracy were extracted for each observation. As some species may have a native range in one African country, but be alien in another, the native range of each species was confirmed using the World Register of Marine Species (WoRMS; Ahyong et al. (2024); https://www.marinespecies.org; accessed 20–21 September 2024) and published articles. To interrogate the geographic distribution of iNaturalist observations and ensure that the observations were, in fact, observed within an MPA, the coordinates for each observation were plotted using the Quantum Geographic Information System (QGIS; version 3.22 LTR). Each observation was plotted on to a map of Africa with the MPAs demarcated [MPA shapefiles from Protected Planet (https://www.protectedplanet.net/en/thematic-areas/marine-protected-areas; accessed: 9 January 2024]). All points were visually inspected and any records from outside MPAs were excluded from further analysis. iNaturalist observations occurring within the native range of a species were also excluded. To address uncertainty in iNaturalist data and improve its accuracy and reliability, confidence for each observation was scored following the protocol proposed by Ackland et al. (2024). This process included three steps: assessing the species, the image and geolocation of each record. Only records receiving medium or high confidence scores were retained for further analysis. A Kendall’s rank correlation was used to assess the relationship between the number of records of alien species as detected in African MPAs through time. Effort was quantified as the number of marine alien species records per 100 records within African MPAs. All statistical analyses were conducted in the R statistical environment (version 4.3.2 – “Eye Holes”, R Core Team (2023)). 403 NeoBiota 102: 399–418 (2025), DOI: 10.3897/neobiota.102.149275 Sarah J. Ackland et al.: Invasions in African MPAs To determine the threat that these species may pose to MPAs, a literature review was carried out using ISI Web of Science to identify all previously published reports of impact for each species at any global location. The search string “scientific name” AND “impact*” OR “effect*”, was applied along with each species name and all previous synonyms. Searches were completed between 25 and 27 September 2024. Environmental impact was categorised according to the mechanisms through which they manifest [i.e. (1) competition; (2) predation; (3) hybridisation; (4) disease transmission; (5) parasitism; (6) poisoning/toxicity; (7) bio-fouling; (8) grazing/herbivory/browsing; (9) chemical; (10) physical or (11) structural impact on an ecosystem; and (12) interaction with other alien species] using the Environmental Impact Classification for Alien Taxa scheme (EICAT; Blackburn et al. (2014)). Socio-economic impacts were classified according to the constituents of human well-being they affect [i.e. (1) safety; (2) material and immaterial assets; (3) health; and (4) social, spiritual and cultural relations] using the Socio-economic Impact Classification for Alien Taxa scheme (SEICAT; Bacher et al. (2017)). Lastly, the magnitude of impact (i.e. massive, major, moderate, minor, minimal or data deficient) reported previously in literature was assigned for each species. Classification of magnitude was based on the maximum impact noted for the species, regardless of location, following Kumschick et al. (2017). Results Seventy-nine African marine protected areas (MPAs) were identified across 14 countries (Fig. 1, Suppl. material 2: table S2). A total of 497 marine species were reported as alien in coastal African countries (Suppl. material 2: table S3) on the World Register of Introduced Species (WRiMS), with a total of 440 iNaturalist records for 34 of those species reported from within African MPAs. After excluding records that were not scorable and those with low confidence scores, 307 records (70%) of 27 species were retained for further analysis (Table 1, Suppl. material 2: table S4). Over two-thirds of these observations [211 records (72%)] received a maximum score for image clarity. Examples of such records are provided in Fig. 2. Of the 27 species recorded on iNaturalist, four were observed within countries with no previous records according to WRiMS. These species included the barnacle Balanus trigonus (Mauritania), the bryozoan Amathia verticillata (Mauritania and South Africa), the colonial tunicate Symplegma brakenhielmi (Senegal) and the crab Callinectes sapidus (Guinea-Bissau and Mauritania). A general trend of increased engagement on iNaturalist was observed, with records of marine alien species in African MPAs increasing significantly over time (Kendall’s rank correlation: τ = 0.51, p < 0.05; Fig. 3). Records were spread across 17 MPAs from seven countries (Fig. 4). Two MPAs accounted for 85.7% of all records (i.e. Table Mountain National Park MPA (South Africa) and Banc d’Arguin National Park (Mauritania)], with many other MPAs having fewer than five records. Table Mountain National Park MPA had the most records of alien taxa [i.e. 241 records (78.5%)] and the highest number of species detected on iNaturalist (15 species). The MPA with the second highest number of records was Banc d’Arguin National Park in Mauritania (22 records; 7.2%), the second highest number of species (8 species) was also detected in this MPA. Of the 27 alien species detected in African MPAs, environmental impact had been reported for 23 species and socio-economic impact for 14 species (Suppl. 404 NeoBiota 102: 399–418 (2025), DOI: 10.3897/neobiota.102.149275 Sarah J. Ackland et al.: Invasions in African MPAs material 2: table S5) and four species were listed as data deficient. Namibian Islands (Namibia) and Langebaan Lagoon (South Africa) were the only MPAs that supported species with massive (i.e. the oyster Magallana gigas and the Mediterranean mussel Mytilus galloprovincialis) and major impact (i.e. the mussel Semimytilus patagonicus, the ascidian Ciona robusta and the bryozoan Amathia verticillata). Table Mountain National Park MPA in South Africa had the highest number of species with previously documented impacts. This MPA had a single species known for massive impact (i.e. the Mediterranean mussel Mytilus galloprovincialis) and three species for which major impact had been reported (i.e. the European green crab Carcinus maenas, the mussel Semimytilus patagonicus and the ascidian Ciona robusta). Banc d’Arguin National Park in Mauritania had the second highest number of species with previously documented impacts. While some species displayed only environmental mechanisms of impact, a general pattern was that species that exerted environmental impact through multiple mechanisms also had many mechanisms of socio-economic impact and ultimately exerted high impacts (Pearson’s product-moment correlation: r = 0.79, p < 0.001; Fig. 5, Suppl. material 2: table S5). Three species had a high number of environmental and socio-economic mechanisms of impact (i.e. the oyster Magallana gigas and the mussels Mytilus galloprovincialis and Semimytilus patagonicus). The Pacific oyster, Magallana gigas, had the highest number of mechanisms through which it has caused environmental and socio-economic impacts. This species was only observed within Namibian Islands MPA in Namibia. Figure 1. Location of the 14 African countries and the number of marine protected areas declared within those countries on the Protected Planet database. Morocco Mauritania Senegal Guinea-Bissau Sierra-Leone Angola Namibia South Africa Tanzania Kenya Seychelles Egypt Sudan Eritrea 1 1 1 7 1 11 41 3 1 5 2 3 1 1 405 NeoBiota 102: 399–418 (2025), DOI: 10.3897/neobiota.102.149275 Sarah J. Ackland et al.: Invasions in African MPAs Discussion Invasive species are major drivers of global change (Pyšek et al. 2020) and invasions directly undermine the conservation objectives of protected areas (Ren et al. 2021). It is, therefore, critical to identify the protected areas that are most at risk to invasions and the species that may pose the greatest threat to them (Pyšek et al. 2020). However, the current lack of baseline data on alien species in MPAs hinders this task, since information on the scale of invasions in MPAs is lacking in most Table 1. The species detected on iNaturalist within African marine protected areas and the magnitude of their environmental impact (as per Blackburn et al. 2014) and socio-economic impact (as per Bacher et al. 2017). Marine protected area codes are as follows: iSimangaliso (iSi); Aliwal (Ali); Protea Banks (Pro); Amathole (Ama); Addo Elephant (Add); Betty’s Bay (Bet); Table Mountain National Park Marine Protected Area (Tmn); Robben Island (Rob); Sixteen Mile Beach (Smb); Langebaan Lagoon (Lan); Namaqua National Park (Nam); Namibian Islands (Nim); Namibe Marine (Nmc); Ihas Formosa, Nago & Tchedia (Iha); Gorée (Gor); Banc d’Arguin National Park (Ban) and Massa (Mas). Numbers (#) assigned to species correspond to the numbers in Figs 4, 5. # Scientific name Country Marine protected area Environmental impact Socio-economic impact Impact literature 1Ectopleura crocea South Africa Tmn Moderate Minor Fitridge and Keough 2013; Yan et al. 2021 2Obelia dichotoma South Africa Tmn Moderate Data deficient Wyatt et al. 2005 3Tridentata marginata Mauritania Ban Data deficient Data deficient 4Anisolabis maritima South Africa Tmn Data deficient Data deficient 5Amphibalanus venustus South Africa Ali; Ama Data deficient Data deficient 6Balanus glandula South Africa Ali; Tmn Moderate Data deficient Kado 2003; Vallarino and Elias 2008 7Balanus trigonus Angola Nmc Minimal Minimal Lozano-Cortès and Zapata 2014; Abelouah et al. 2024 Mauritania Ban 8Megabalanus tintinnabulum South Africa iSi, Tmn Moderate Data deficient Pfaff et al. 2022 9Callinectes sapidus Guinea-Bissau Iha Major Minor Clavero et al. 2022; Mancinelli et al. 2017 Mauritania Ban Morocco Mas 10 Carcinus maenas South Africa Tmn Major Minor Grosholz et al. 2011; Breen and Metaxas 2008 Whitlow 2010; de Rivera et al. 2011; Mabin et al. 2022 11 Amathia verticillata Mauritania Ban Major Minor McCann et al. 2015 South Africa Lan 12 Bugula neritina South Africa Bet Minor Minor Yu et al. 2007; Bae et al. 2022 13 Virididentula dentata South Africa iSi; Tmn Minimal Data deficient Micael et al. 2016 14 Watersipora subtorquata South Africa Add; Tmn Minor Minor Sellheim et al. 2010; McKenzie et al. 2011 15 Magallana gigas Namibia Nam Massive Major Troost 2010; Kelly et al. 2008 16 Mytilus galloprovincialis Mauritania Ban Massive Major Branch and Steffani 2004; Steffani and Branch 2005; Alexander et al. 2015 Namibia Nim South Africa Lan; Nam; Rob; Smb; Tmn 17 Semimytilus patagonicus Namibia Nam Major Major Skein et al. 2018 South Africa Lan; Tmn 18 Siphonaria pectinata Mauritania Ban Minor Data deficient Boukhicha et al. 2015 19 Thecacera pennigera South Africa Tmn Data deficient Data deficient 20 Ophiactis savignyi Guinea-Bissau Iha Minor Data deficient Çinar et al. 2019 South Africa Pro 21 Botryllus schlosseri South Africa Tmn Moderate Data deficient Wong and Vercaemer 2012 22 Ciona robusta South Africa Lan; Tmn Major Minor Robinson et al. 2017 23 Clavelina lepadiformis South Africa Tmn Minimal Data deficient Casso et al. 2018 24 Diplosoma listerianum South Africa Tmn Minor Minimal Aldred and Clare 2014 25 Symplegma brakenhielmi Senegal Gor Minor Minimal Spyksma et al. 2024 26 Acanthophora spicifera Mauritania Ban Moderate Data deficient Davidson et al. 2015 27 Hypnea musciformis Guinea-Bissau Iha Moderate Minimal Okuhata et al. 2023 Mauritania Ban Senegal Gor 406 NeoBiota 102: 399–418 (2025), DOI: 10.3897/neobiota.102.149275 Sarah J. Ackland et al.: Invasions in African MPAs (a) (b) (c) (d) © Lauren van Noort ©Terry Gosliner © Carel van der Colff © carolina_dlhs Figure 2. iNaturalist records that contributed towards the findings of this study. a. Clavelina lepadiformis (iNaturalist ID 152956163); b. Ciona robusta (iNaturalist ID 69033891); c. Thecacera pennigera (iNaturalist ID 23247918); d. Callinectes sapidus (iNaturalist ID 174999050). Figure 3. The number of alien species with records on iNaturalist in African marine protected areas (MPAs) over time. Numbers above bars indicate the number of alien species records per 100 records within African MPAs. 407 NeoBiota 102: 399–418 (2025), DOI: 10.3897/neobiota.102.149275 Sarah J. Ackland et al.: Invasions in African MPAs Figure 4. The number of marine alien species with records in iNaturalist across marine protected areas (MPAs) and the countries in which they occurred. Species are categorised according to the highest magnitude of impact noted for the species. Species codes (numbers in the boxes) are explained in Table 1. MPA names (below x axis): iSimangaliso (iSi); Aliwal (Ali); Protea Banks (Pro); Amathole (Ama); Addo Elephant (Add); Betty’s Bay (Bet); Table Mountain National Park Marine Protected Area (Tmn); Robben Island (Rob); Sixteen Mile Beach (Smb); Langebaan Lagoon (Lan); Namaqua National Park (Nam); Namibian Islands (Nim); Namibe Marine (Nmc); Ihas Formosa, Nago & Tchedia (Iha); Gorée (Gor); Banc d’Arguin National Park (Ban) and Massa (Mas). South Africa Namibia Angola Senegal Mauritania Morocco 13 8 5 6 20 5 14 12 22 4 6 21 10 23 24 1 8 16 17 2 14 19 13 2516 16 16 11 22 17 16 16 17 15 720 9 27 27 9 11 27 7 18 26 3 16 9 Figure 5. The relationship between the environmental and socio-economic mechanisms reported for each species recorded within an African marine protected area. The magnitude of impact for each species is indicated by the colours; the size of the points represents the number of species. 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The Open Database License (ODbL) is a license agreement intended to allow users to freely share, modify, and use this Dataset while maintaining this same freedom for others, provided that the original source and author(s) are credited. Link: https://doi.org/10.3897/neobiota.102.149275.suppl1 Supplementary material 2 Supplementary information Authors: Sarah J. Ackland, David M. Richardson, Tamara B. Robinson Data type: xlsx Explanation note: table S2. Marine protected areas identified from the Protected Planet database and the countries in which they have been declared. table S3. Marine alien species as identified on WRiMs and the countries in which they have been reported. table S4. Species reported within African marine protected areas on iNaturalist. table S5. The assessment of the magnitude of impact of species according to the EICAT (Blackburn et al. 2014) and SEICAT (Bacher et al. 2017) schemes. Copyright notice: This dataset is made available under the Open Database License (http://opendatacommons.org/licenses/odbl/1.0/). The Open Database License (ODbL) is a license agreement intended to allow users to freely share, modify, and use this Dataset while maintaining this same freedom for others, provided that the original source and author(s) are credited. Link: https://doi.org/10.3897/neobiota.102.149275.suppl2