Status of moose populations and challenges to moose management in Fennoscandia.
Why this work is in the frame
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Bibliographic record
Abstract
In the Fennoscandian countries, Norway, Sweden, and Finland, moose (Alces alces) populations began to increase rapidly in the 1960s and have since then been among the most productive and heavily harvested moose populations in the world. At the start of the 20th century, the total annual harvest was < 10,000 moose, whereas in 2000, the annual kill reached about 200,000. The winter population was estimated to be about 500,000. In Sweden and Finland, the highest harvest numbers (and presumably population density) were recorded in the first half of the 1980s and in Finland again in the late 1990s and during the beginning of the 2000s. In Norway, the 1990s was the decade of the highest harvest numbers. The current regional moose density during winter varies from < 0.2 to about 2 moose/km2 within Fennoscandia. Locally, the density may far exceed this level in typical wintering areas (e.g., 5-6 moose/km2). In general, the current densities are lower in the north than in the south and higher in Norway and Sweden than in Finland. The strong increase in harvest and the present high densities are explained by several factors. First, modern forestry clear-cutting practices have provided Fennoscandian moose with prime habitats in the form of early succession stages. Accordingly, the current carrying capacity is likely to be relatively high compared to the situation 50-100 years ago. The current trend, however, is towards less activity in the forest and a decreasing proportion of forests found at an early successional stage. This may increase the food limitation already seen in several populations; i.e., in all three countries, body mass and recruitment rates have been found to decrease with increasing density. Second, the introduction of sex and age-specific harvesting in the early 1970s has increased the general productivity of the populations. By focusing the harvest on calves, yearlings, and adult males, the proportion of productive females, the mean age of females, and the annual recruitment rate have increased. Simultaneously, the proportion and mean age of males have decreased, and in some populations, this has been associated with delayed parturition dates and lower fecundity; i.e., due to inadequate number of males for timely reproduction. Third, mortality other than hunting is low, and only near the eastern border of Finland with Russia has predation by wolves and bears had a notable effect on productivity figures. This situation is about to change with increasing populations of large carnivores in all of Fennoscandia during the 1990s. The management principles have been quite similar within Fennoscandia, although differences in legislation have resulted in national and regional differences in management performance. In general, moose managers take advantage of data collected by hunters during the hunting season (e.g., hunting statistics, number, sex, and age of moose observed) to monitor population development and determine hunting quotas. Moreover, in all three countries, the issues of traffic accidents and damage to forestry and agriculture play a central role in moose management and discussions concerning optimum population sizes. ALCES VOL. 39: 109-130 (2003)
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.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it