Forecasting the potential distribution of the invasive tunicate <i>Didemnum vexillum</i>
Bibliographic record
Abstract
Summary Invasive species are a major threat to global biodiversity and their introduction can have significant economic consequences. The invasive tunicate Didemnum vexillum is a notorious invader with significant negative impacts on cultured shellfish and natural benthic communities, including commercially important ones. We conducted an expert survey, identifying the five most important transport vectors for D. vexillum along the west coast of North America. We determined the spatially explicit vector density for all vectors in order to identify introduction hotspots. Additionally, we developed an environmental niche model based on 46 occurrence points and nine environmental variables to identify areas suitable for D. vexillum . Spatial distribution of the most important transport vectors (slow‐moving vessels, aquaculture, fishing vessels, small vessels, and large commercial vessels) identified several hotspots with high vector densities. These proved to be a very good predictor of current D. vexillum occurrence in British Columbia (BC). Ecological niche modelling (Genetic Algorithm for Rule‐set Prediction) predicted suitable environments in southern BC, parts of central BC and along the east coast of the Queen Charlotte Islands. Independent validation of the model based on the current distribution in BC indicated good predictive accuracy. Additional analytical steps confirmed that no environmental variable dominated the predictions and we identified ranges of environmental conditions predicted suitable by the model. We identified areas of high establishment probability for D. vexillum by combining the vector model and environmental niche model. Parts of central BC, the west coast of Vancouver Island and the Strait of Georgia are areas where D. vexillum is most likely to establish. Synthesis and applications . Spatially explicit predictions of the potential distribution of biological invaders are crucial for informing risk assessments, development of management strategies, and resource allocation. While most studies only focus on one step in the invasion process, we successfully combined the likelihood of introduction and establishment. Results from this study are informing the canadian risk assessment of invasive tunicates, guiding current monitoring efforts, and providing a basis for potential intervention/mediation measures.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".