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Record W4403477011 · doi:10.1002/2688-8319.12391

Community science can inform invasive species management: <i>Melaleuca</i> (Myrtaceae) in South Africa

2024· article· en· W4403477011 on OpenAlex
Luke J. Potgieter, Michèle B. ter Huurne, David M. Richardson

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEcological Solutions and Evidence · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBotany, Ecology, and Taxonomy Studies
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaUniversiteit StellenboschAkademie Věd České Republiky
KeywordsMyrtaceaeMelaleucaGeographyAgroforestryBiologyEcology

Abstract

fetched live from OpenAlex

Abstract Community science initiatives are revolutionising our ability to detect and respond to biological invasions. Non‐native trees and shrubs are among the world's most damaging invasive species and community science data can be used to inform protocols for managing these invasions. This study explores the utility of iNaturalist in informing management practices for the widely cultivated and naturalised genus Melaleuca L. (Myrtaceae; here including the genus Callistemon ) in South Africa. We applied data from iNaturalist to assess the distribution and invasion ecology of Melaleuca species in South Africa. Melaleucas, first recorded in South Africa in 1882, have been widely used as garden ornamentals and street trees in the country for over 50 years. Naturalisation of melaleucas in South Africa was first reported in 1998 and the first records of naturalisation/invasiveness for other species are accumulating rapidly. Data on all Melaleuca species in South Africa were downloaded from iNaturalist and analysed using Geographic Information System software. In September 2023, iNaturalist had 3221 records of melaleucas across the country. After checking and filtering, and applying criteria to increase reliability, 2815 records remained, with confirmed identifications of 26 species. These species were recorded in a total of 138 quarter‐degree cells (QDCs) in South Africa (7% of the country); Research Grade (RG, wild‐growing) records occurred in 21 QDCs, records of cultivated plants in 75 QDCs, and 42 QDCs had records of both cultivated and wild‐growing plants. An Invasiveness Index was calculated for each species in the country, provinces, and municipalities, to show which species are already invasive or have substantial invasion debt. Thirty‐two percent of the filtered records were RG (naturalised). The municipality with the highest number of records is the City of Cape Town, with 43% RG records. iNaturalist provided useful information on the occurrence of five Melaleuca species for which no information was available before this study was undertaken. Case studies of invaded habitats highlight that melaleucas have the potential to alter ecosystems incurring substantial control costs. Practical implications : Our study highlights the value of community science data in the detection, monitoring, and management of invasive plant species.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.086
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.104
GPT teacher head0.250
Teacher spread0.146 · 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