Fishery catch is affected by geographic expansion, fishing down food webs and climate change in Aotearoa, New Zealand
Bibliographic record
Abstract
Historical fishing effort has resulted, in many parts of the ocean, in increasing catches of smaller, lower trophic level species once larger higher trophic level species have been depleted. Concurrently, changes in the geographic distribution of marine species have been observed as species track their thermal affinity in line with ocean warming. However, geographic shifts in fisheries, including to deeper waters, may conceal the phenomenon of fishing down the food web and effects of climate warming on fish stocks. Fisheries-catch weighted metrics such as the Mean Trophic Level (MTL) and Mean Temperature of the Catch (MTC) are used to investigate these phenomena, although apparent trends of these metrics can be masked by the aforementioned geographic expansion and deepening of fisheries catch across large areas and time periods. We investigated instances of both fishing down trophic levels and climate-driven changes in the geographic distribution of fished species in New Zealand waters from 1950-2019, using the MTL and MTC. Thereafter, we corrected for the masking effect of the geographic expansion of fisheries within these indices by using the Fishing-in-Balance (FiB) index and the adapted Mean Trophic Level (aMTL) index. Our results document the offshore expansion of fisheries across the New Zealand Exclusive Economic Zone (EEZ) from 1950-2019, as well as the pervasiveness of fishing down within nearshore fishing stock assemblages. We also revealed the warming of the MTC for pelagic-associated fisheries, trends that were otherwise masked by the depth- and geographic expansion of New Zealand fisheries across the study period.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".