<b>The implications of climate change for New Zealand’s freshwater fish</b>
Bibliographic record
Abstract
Data from:Canning, Zammit, Death. (2024). The implications of climate change for New Zealand’s freshwater fish. Canadian Journal of Fisheries and Aquatic Sciences.Abstract:Climate change is poised to reshape ecological communities globally by driving species into new environments and altering interactions between species. Conservation efforts should not only address current pressures but also plan for future pressures, such as sensitive species moving into degraded environments or arising problematic trophic interactions. This study sought to assess how climate change may affect the end-of-century distributions of New Zealand’s native and non-native freshwater fish, including consequences for the overlap between trout (a non-native sports fish) and native species vulnerable to trout predation. Random forest modelling was used to predict end-of-century distributions for New Zealand’s freshwater fish based on six hydrologically downscaled global climate models across four representative concentration pathways. Severe climate change impacts could drive nine native fish species to extinction or near-extinction and cause substantial declines in another eight native species. Seven non-natives are also predicted to decline substantially, including a 30-40% reduction in the extent of trout. To avert these potential extinctions, it is crucial to mitigate climate change severity and improve land use impacting freshwater ecosystems.Word Document: 'cjfas-2024-0127' suppla contains Supplementary material A.Excel file: 'cjfas-2024-0127supplb' contains Supplementary material Bcsv file: 'Optimal_Thresholds' contains the probability thresholds that maximised the Kappa statistic when determining presence from probability of occurrence.csv file: 'All preds RF wide' contains the probability of occurrence for all species at all river reaches modelled. Data is in wide format with columns representing individual species, along with a 'Scenario' column indicating the RCP climate, 'Model' column indicating the global circulation model used, and 'nzsegment' indicating the river reach as defined in the New Zealand River Environment Classification system v2.4.csv file: 'All preds binary RF wide' contains the presence (1) or background (0) classification for all species at all river reaches modelled. Data is in wide format with columns representing individual species, along with a 'Scenario' column indicating the RCP climate, 'Model' column indicating the global circulation model used, and 'nzsegment' indicating the river reach as defined in the New Zealand River Environment Classification system v2.4.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.275 | 0.059 |
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".