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Record W4399094471 · doi:10.3897/bdj.12.e119539

Alien plant species distribution in Romania: a nationwide survey following the implementation of the EU Regulation on Invasive Alien Species

2024· article· en· W4399094471 on OpenAlexaffabout
Paulina Anastasiu, Iulia V. Miu, Athanasios Alexandru Gavrilidis, Cristina Preda, Laurenţiu Rozyłowicz, C. Sîrbu, Adrian Oprea, Mihaela Urziceanu, Petronela Camen-Comănescu, Eugenia Nagodă, Daniyar Memedemin, M.I. Bărbos, V. Boruz, Alina Georgiana Cîșlariu, Ioan Don, Marius Făgăraș, József Pál Frink, Ioana Mihaela Georgescu, Ovidiu Hâruţa, Bogdan‐Iuliu Hurdu, Attila Mátis, Sretco Milanovici, Sorana Muncaciu, A. Neacşu, Monica Neblea, A. L. Nicolin, M. Niculescu, Silvia Oroian, Oliviu Grigore Pop, Daniel Răduțoiu, Mihaela Sămărghițan, Ioana Simion, Liliana Cristina Soare, Corina Steiu, Emilia Stoianov, Daniela Strat, Anna Szabó, Paul Marian Szatmari, Corneliu Tănase, Marian D. Mirea, Nicolae Manta, Ioana-Minodora Sîrbu

Bibliographic record

VenueBiodiversity Data Journal · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsAlberta Conservation Association
FundersUniversitatea din BucureștiAutoritatea Natională pentru Cercetare Stiintifică
KeywordsAlienBiodiversityAlien speciesEuropean unionInvasive speciesChecklistGeographyDistribution (mathematics)Environmental resource managementChristian ministryIntroduced speciesEcologyEnvironmental planningBusinessPolitical scienceBiologyEnvironmental science

Abstract

fetched live from OpenAlex

Biological invasions pose an increasing risk to nature, social security and the economy, being ranked amongst the top five threats to biodiversity. Managing alien and invasive species is a priority for the European Union, as outlined in the EU Biodiversity Strategy for 2030 and the Kunming-Montreal Global Biodiversity Framework. Alien plant species are acknowledged to impact the economy and biodiversity; thus, analysing the distribution of such species provides valuable inputs for the management and decision-making processes. The database presented in the current study is the first consolidated checklist of alien plant species that are present in Romania, both of European Union concern and of national interest. This database complements a prior published distribution, based only on records from literature, bringing new information regarding the occurrence of alien plants in Romania, as revealed by a nationwide field survey. We consider this database a valuable instrument for managing biological invasions at both national and regional levels, as it can be utilised in further research studies and in drafting management and action plans, assisting stakeholders in making informed decisions and implementing management actions. We present the results of the first nationwide survey of alien plant species in Romania, conducted between 2019 and 2022, in the framework of a national project coordinated by the Ministry of Environment, Waters and Forests and the University of Bucharest. The present database complements and updates the database published by Sirbu et. al (2022), which included occurrence records published until 2019. The new database includes 98323 occurrence records for 396 alien plant species in 77 families, with most species belonging to the Asteraceae family. One alien plant species in our database, the black locust Robinia pseudoacacia L., had more than 10,000 occurrence records. The distribution database also includes information on newly-reported invasive alien plant species of European Union concern in Romania (i.e. the floating primrose-willow Ludwigia peploides (Kunth) P.H.Raven) and documents the presence of plants in 44 additional families compared to Sirbu et al. (2022). Each entry includes information on species taxonomy, location, year, person who recorded and identified the alien plant, geographical coordinates and taxon rank.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.124
GPT teacher head0.251
Teacher spread0.127 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2024
Admission routes2
Has abstractyes

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