The Effect of Climate, Environment and Man on Variations in Wildlife Population Fluctuations in Greenland Over 200 Years
Bibliographic record
Abstract
The Effect of Climate, Environment and Man on Variations in Wildlife Population Fluctuations in Greenland Over 200 Years Moshøj, Charlotte The underlying factors of species fluctuating population dynamics has been the dominant focus of attention in population ecology throughout much of this century. In arctic regions where a severe climate with high seasonal and annual variability and simplistic ecosystems prevail, species of fish, birds and mammals display distinct population fluctuations of varying temporal and spatial scale. In Greenland, historical records, archaeological findings and oral accounts passed on from Inuit elders all document that the presence of wildlife species and their population sizes have undergone pronounced fluctuations throughout recordable historical time. The most detailed accounts are found for the species that were harvested or had economical value. While several recent studies from northern latitudes have shown the relative roles of climate, the exogenous and endogenous environment of species and man as factors driving species population dynamics, the relative contributions and potential interactions among these factors remains unsolved. In Greenland, these fluctuations in the harvests of individual species are believed to be related to changes in climate, as well as variations in hunting pressure. Dating back 200 years, these hunting records therefore represent a unique time series for retrospective modelling of annual and decadal fluctuations in relation to long-term climatic data, environmental factors and temporal variations in social and demographic parameters in the existing society. The results of this study model future predictions of wildlife populations under changing climate variables and human hunting pressure. View Presentation.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".