Bibliographic record
Abstract
This is the OBIS extraction of the Ocean Tracking Network and Norwegian University of Science and Technology (NTNU) Greenland Arctic Charr, consisting of the release tagging metadata, i.e. the location and date when the tagged animal was released, and summarized detection events of tagged individuals. If readers are interested in the source dataset they may also inquire with the project PIs as listed here or on the OTN web site (https://members.oceantrack.org/project?ccode=V2LGAC2).Abstract:The Arctic charr is a partial migratory species, where some individuals migrate to sea every summer for feeding, while others remain in freshwater their entire life. Since migration is an adaptive response to particular conditions, environmental changes will potentially alter the selective pressures on movement behavior. The changes may also interfere with, or disrupt, a species’ ability to migrate. In either case, environmental changes could lead to the reduction or total loss of a migration with harmful impacts on fish populations. Yet we have little understanding of when to expect these outcomes to occur. Climatic changes are most pronounced in Arctic and subarctic areas, where increases in temperature and precipitation exceed global averages, resulting in changes to the annual growth period . The changes increase favorable temperatures for growth, but stratification in marine fjords may reduce productivity and limit food and hence prolong the marine feeding migration. Hence, it can be expected that changes in migratory phenologies and behavior may be among the first observed response to climate change. Especially, retreating glaciers will initially increase inflow of freshwaters to fjords due to increased melting, but later then the glacier is gone, freshwater run off will be reduced. Consequently, climate change may significantly have an impact on the marine ecosystem used by Arctic during their feeding migration. A recent study from three watercourses in South-western Greenland suggested that the local populations of Arctic charr consisted of a mixture of trophic groups; one group of marine specialists, an estuarine group that may have short and local marine migrations, and two resident morphs from the freshwater habitats. Hence there is a clear potential for a rapid adaptation by the species to changed climatic conditions although the mix of trophic groups may change. To reveal if changed climate may affect migratory behavior and trophic niche use, we will combine acoustic telemetry, physiological sampling techniques, sampling for stable isotopes (SIA) and genomics to examine charr populations in two neighboring fjord systems in Southwestern Greenland. One of the sites receives influx from glacial runoff whereas the other does not. The aim is to quantify variation in migratory tactics and the extent of marine habitat use of anadromous Arctic charr between the two ecologically very different fjord systems, and link distributions to important environmental variables like temperature, salinity and marine productivity. The current lack of knowledge regarding migratory tendencies makes it impossible for resource managers to ensure that different migratory behaviour types are protected, thus ensuring a portfolio of migration strategies are present within a given river system to deal with impending climate change. Knowledge from sites with limited other anthropogenic impacts will be crucial in providing this understanding.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.049 | 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".