Propagule pressure in the presence of uncertainty: extending the utility of proxy variables with hierarchical models
Bibliographic record
Abstract
Summary Species invasions depend on the abundance and rate at which organisms are introduced to new localities, known as propagule pressure. Due to the challenges of measuring propagule pressure, proxy variables are often used; however, untested proxy variables may obscure the role of propagule pressure vs. ecological factors that facilitate invasion, leading to uncertainty about the invasion process and confounding management response. To generate absolute estimates of propagule pressure and facilitate meaningful comparison among pathways of species introduction, we extend proxy variables by combining ecological and global trade data with hierarchical statistical models. We derive absolute propagule pressure with probability distribution functions (propagule size: the probability of introducingnpropagules per event; and overall propagule pressure: the probability of introducingnpropagules per year) and, based on these projections, evaluate the performance of ballast water volume (m3) as a common proxy variable. Hindcast accuracy of ballast water volume was low but strongly scale‐dependent, exhibiting poor accuracy (R2 = 0·058) at small scales and only marginal accuracy at large scales (overallR2 = 0·169). As a result, conclusions about propagule pressure are likely to be biased based on the ballast volume proxy, as may be conclusions about species invasion when ballast water volume has been used. Irrespective of geographic pathway, estimated propagule sizes demonstrated extreme leptokurtosis and long right tails, with maximum values between 131‐fold and 2966‐fold greater than median values. These characteristics signify a subset of introduction events involving extreme propagule abundance that may provide opportunity to overcome Allee thresholds or marginal environmental conditions. Developing meaningful propagule supply functions is critical to resolve the role of propagule pressure within the invasion process and test hypotheses about species colonization at landscape scales. By joining absolute propagule pressure with existing theory about species extinction, the expected ecological outcome of environmental policy to manage propagule pressure can be estimated within a statistical framework.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.072 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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 source (direct Gemma or distilled Codex), 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".