Climate change, non‐indigenous species and shipping: assessing the risk of species introduction to a high‐<scp>A</scp>rctic archipelago
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Aim Anticipated changes in the global ocean climate will affect the vulnerability of marine ecosystems to the negative effects of non‐indigenous species ( NIS ). In the A rctic, there is a need to better characterize present and future marine biological introduction patterns and processes. We use a vector‐based assessment to estimate changes in the vulnerability of a high‐ A rctic archipelago to marine NIS introduction and establishment. Location Global, with a case study of S valbard, N orway. Methods We base our assessment on the level of connectedness to global NIS pools through the regional shipping network and predicted changes in ocean climates. Environmental match of ports connected to S valbard was evaluated under present and future environmental conditions (2050 and 2100 predicted under the RCP 8.5 emissions scenario). Risk of NIS introduction was then estimated based on the potential for known NIS to be transported (in ballast water or as biofouling), environmental match, and a qualitative estimate of propagule pressure. Results We show that S valbard will become increasingly vulnerable to marine NIS introduction and establishment. Over the coming century, sea surface warming at high latitudes is estimated to increase the level of environmental match to nearly one‐third of ports previously visited by vessels travelling to S valbard in 2011 ( n = 136). The shipping network will then likely connect S valbard to a much greater pool of known NIS , under conditions more favourable for their establishment. Research and fishing vessels were estimated to pose the highest risk of NIS introduction through biofouling, while ballast water discharge is estimated to pose an increased risk by the end of the century. Main conclusions In the absence of focused preventative management, the risk of NIS introduction and establishment in S valbard, and the wider A rctic, will increase over coming decades, prompting a need to respond in policy and action.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it