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Record W6948496260 · doi:10.5061/dryad.8cz8w9gt3

Data from: A multifaceted ecological assessment reveals the invasion of the freshwater red macroalga Montagnia macrospora (Batrachospermales, Rhodophyta) in Taiwan

2024· dataset· en· W6948496260 on OpenAlexaff

Bibliographic record

VenueDRYAD · 2024
Typedataset
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSingle-cell and spatial transcriptomics
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsRange (aeronautics)Generalist and specialist speciesPopulationFreshwater ecosystemInvasive speciesBiodiversity

Abstract

fetched live from OpenAlex

Invasive freshwater macroalgae are rarely described. Montagnia macrospora is a freshwater red alga introduced from South America to East Asia via the global aquarium trade. The earliest occurrence record of this alga in Taiwan is dated 2005. To determine whether M. macrospora has become invasive in Taiwan and to understand the traits that facilitated its invasion, we took a multifaceted approach that combines examination of ecological background and population genetic analysis. Our island-wide survey showed that M. macrospora is widespread in the field across Taiwan, where the climate greatly differs from that of South America, and can self-sustain for nearly a decade. Our population genetic analysis revealed a lack of genetic diversity of M. macrospora in Taiwan, consistent with the hypothesis that the alga expanded through asexual reproduction. Moreover, during our long-term ecological assessments and field surveys, we observed thatM. macrospora is an ecological generalist that can survive in a wide range of temperature, pH, illumination, and nutrient enrichment. Taken together, our data suggest that M. macrospora has successfully invaded the freshwater ecosystems ofTaiwan, likely due to its ability to disperse asexually and to grow under broad environmental conditions. We hope that our study brings attention to invasive freshwater algae, which have been overlooked in conservation planning and management.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.131
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0010.001
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 head0.035
GPT teacher head0.292
Teacher spread0.257 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2024
Admission routes1
Has abstractyes

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