Atlas maps 96 invasive plant species across mainland Portugal

Invasive alien plants have been recorded in every municipality in mainland Portugal, but their distributions vary sharply: Lisbon, Coimbra, Sintra and Figueira da Foz contain the largest inventories, while many inland and northeastern municipalities have fewer recorded species. A national atlas assembled roughly 85,000 occurrence records for 96 listed invasive plants and used municipality-level mapping to identify where they occur. It also found significant statistical associations between the number of species in a municipality and municipality area, power-line density, proximity to the coast and travel time to the nearest city. The results provide a broad baseline for monitoring plant invasions, although they measure recorded richness rather than local abundance or ecological damage.

The study focused on the 278 municipalities of mainland Portugal and covered plants included in Portuguese Decree-Law No. 92/2019 or European Union Regulation No. 1143/2014, while excluding species relevant only to Portugal’s islands. The final mapping effort involved 96 species from 64 genera and 36 families. Most were terrestrial plants, accounting for 86% of the total, while 14% were aquatic or semi-aquatic. Grasses and herbs formed the largest growth-form category at 47%, followed by trees and shrubs at 29%, climbing plants at 5% and other forms at the remaining proportion. Asteraceae, Amaranthaceae, Fabaceae and Poaceae were the most represented families.

Occurrence data came from the Global Biodiversity Information Facility, the expert-led Flora-On project, research-grade iNaturalist observations, Pl@ntNet, scientific publications, postgraduate theses and unpublished records supplied by authors, collaborators and organizations involved in invasive-plant management. Information through May 2024 was included. Taxonomy was standardized using the GBIF Backbone Taxonomy; records referring only to the stored location of a specimen rather than its actual observation site were removed, as were records with spatial precision below 100 metres. Duplicate records for the same species within each municipality were collapsed so that richness represented the number of unique species recorded there.

The researchers used the 1-by-1-kilometre grid cells intersecting municipalities to estimate how extensively each species occupied the places where it had been detected. Oxalis pes-caprae had the highest mean occupancy, covering 7.53% of the relevant grid cells, followed by Arundo donax at 6.90% and Cortaderia selloana at 6.87%. Acacia longifolia and Arctotheca calendula ranked next, with mean occupancy of 5.58% and 5.88%, respectively, but were concentrated largely in coastal areas. A linear model found that the number of municipalities containing a species was significantly associated with its mean occupancy and accounted for 42% of the observed variation. This means national reach and the proportion of occupied cells within municipalities were related, but neither measure was a substitute for a direct assessment of abundance.

National coverage varied by species. Acacia dealbata had the broadest municipal distribution, appearing in 249 of the 278 municipalities, followed by Datura stramonium in 233, Arundo donax in 232, Phytolacca americana in 224, Oxalis pes-caprae in 213 and Cortaderia selloana in 208. Ailanthus altissima was recorded in 198 municipalities, Acacia melanoxylon in 190, Agave americana in 187 and Robinia pseudoacacia in 186. At the other end of the distribution, Alternanthera philoxeroides, Amaranthus hypochondriacus, Amaranthus muricatus and Baccharis halimifolia each appeared in only one municipality. Species with only a small number of records included a disproportionate share of aquatic or semi-aquatic plants, although the atlas alone could not determine whether a sparse record represented an emerging invasion or incomplete reporting.

To identify shared distribution patterns, the team characterized each species by the number of municipalities in which it occurred, the median and interquartile range of its distance from the coast, and the median and interquartile range of its latitude. Principal component analysis, with the first two components explaining 72.3% of the variance, was followed by k-means clustering, for which the elbow method was used to select the number of groups. Four clusters emerged. Twenty-six species were concentrated mainly in coastal areas, including Acacia saligna and Cotula coronopifolia. Fourteen had narrow ranges extending across no more than 33 municipalities and were generally found in central and northern areas, with Reynoutria japonica and Baccharis halimifolia as examples. Another 29 were moderately widespread, and the final 27 were mostly broadly distributed, averaging 145 municipalities each. A species such as Cortaderia selloana nevertheless remained relatively uncommon deep inland, illustrating how presence-only data at municipal scale can conceal finer geographic variation.

The mapped richness showed a clear coastal and urban concentration. Lisbon recorded 63 of the 96 species, narrowly ahead of Coimbra with 62, while Sintra had 58 and Figueira da Foz 55. Other relatively rich municipalities occurred around the Oporto metropolitan area, in cities including Viana do Castelo, and along the Algarve coast. Lower totals characterized parts of northeastern Portugal and some central and inland areas of Alentejo. Because Portugal’s population and economic activity are concentrated along the western and southern coasts, especially around Lisbon and Oporto, the geographic pattern is consistent with an important role for human activity and accessibility. The atlas measured association rather than causation, however, and did not experimentally test the processes responsible for the observed distribution.

A generalized least-squares model, fitted under an assumption of exponential spatial autocorrelation, explained 59% of the variation in municipality-level invasive-plant richness, expressed as a pseudo-R2. Four variables had statistically significant relationships at p < 0.05. Richness increased with municipality area, whose coefficient was 0.0478 with a standard error of 0.006, and with power-line density, whose coefficient was 0.4782 with a standard error of 0.231. It also increased as minimum distance to the coast decreased, with a coefficient of -0.0074 and standard error of 0.002, and as travel time to the nearest city shortened, with a coefficient of -0.0070 and standard error of 0.002. Larger municipalities can contain more habitats and a broader regional species pool, while the coastal and accessibility relationships align with the country’s concentration of people and economic activity. The role of linear infrastructure in facilitating plant invasion remains less well studied, and the significant power-line association does not establish that roads, railways or other transport corridors have the same effect.

Several tested variables were not significant in the final model. These included precipitation in the wettest month, the mean daily maximum air temperature of the warmest month, ruggedness, agricultural and forest cover, protected-area density, burnt area, soil pH, hydrographic-network density, railway density and several measures of sampling effort. The authors noted that averaging soil pH across heterogeneous soil types within a municipality may dilute local differences. They also observed that climate variables were weaker predictors than expected in this analysis, possibly reflecting the influence of human distribution and activity across mainland Portugal, although the observational model cannot establish which mechanisms produced the results. The inclusion of proxies for recording effort was intended to help distinguish biological patterns from differences in observation intensity, but those proxies cannot eliminate every sampling bias.

The atlas has important limitations. Its underlying records were assembled largely through opportunistic and citizen-science observation, so apparent absences may reflect low survey effort, restricted site access or poor detectability rather than true absence. Conspicuous species and well-visited urban areas may also be overrepresented. Most of the information came from presence records, and municipality-level richness does not show how many individuals are present, whether populations are expanding or how much ecological harm a species causes. The method also gives equal weight to every listed species even though their effects and management urgency can differ. A new record of one taxon may call for immediate investigation, while another may represent a geographically restricted occurrence; the richness map alone cannot make that distinction. The researchers therefore present it as a tool for locating potential invasion hotspots and identifying where field surveys are needed, not as a direct measure of invasion severity.

Despite these constraints, the database documents a national pattern that was previously fragmented among many sources. It shows that the 96 mapped species occur throughout mainland Portugal, with the highest recorded richness in coastal urban areas and the lowest totals in several inland regions. It also reveals sharply different national and municipal distribution profiles among individual taxa, from plants reported across most of the country to those represented by a single municipal record. For managers, those sparsely documented occurrences may justify targeted fieldwork to clarify whether they reflect early stages of invasion or gaps in observation. Continued systematic monitoring, collection of abundance data and species-specific risk assessments would be needed to turn the presence-based atlas into a more precise account of population size, ecological effects and management urgency.

Subject of Research: Spatial distribution and environmental correlates of invasive alien plant richness across mainland Portugal

Article Title: Diversity and distribution patterns of invasive alien plant species in mainland Portugal

Article References: Fernandes, R., Castro, A., Marchante, H., Marchante, E., & Capinha, C. (2025). Diversity and distribution patterns of invasive alien plant species in mainland Portugal. NeoBiota, 104, 139-162. https://doi.org/10.3897/neobiota.104.163291

Image Credits: AI Generated

DOI: 10.3897/neobiota.104.163291

Keywords: invasive plants, Portugal, biodiversity mapping, species richness, municipal distributions, occurrence records, coastal cities, power-line density, citizen science, plant invasions, Diversity, distribution