Ontogenetic spatial constraints of sub‐arctic marine fish species
Bibliographic record
Abstract
Abstract Marine species may respond and adapt to climate change through shifting spatial distributions, but options may be limited by the occupancy of essential habitats which are anchored in space. Limited knowledge of when spatial constraints are most likely to occur in marine fish life cycles has impeded the development of realistic distribution forecasts. In this study, we develop and implement analytical techniques to identify spatial constraints, defined by both the consistency through which a particular geographic area is used year after year, and by the extent of such area with respect to the entire population range. This approach is applied to simulated data and to ten case‐studies including six groundfish species from three subarctic marine systems. Our analyses illustrate that the early phase of the species’ life cycle is more spatially constrained than older life stages. We detected significant species‐specific variability in both the degree to which species are anchored in space throughout their life cycle, and the ontogenetic changes in the geographic association. There is an indication that this variability can be explained by the species life history strategy, highlighting the need to extend similar analyses to other species and regions. The presence of ontogenetic spatial constraints, particularly during early life stages, indicates restrictions exist to changes in spatial distribution and questions the assertion that global warming will uniformly result in an increase in abundance and harvest at higher latitudes and decreases at lower latitudes. Our study develops ecological and analytical insights that are critical for accurate projections of species distributions under different climate change scenarios.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".