Effects of observed and experimental climate change on terrestrial ecosystems in northern Canada: results from the Canadian IPY program
Bibliographic record
Abstract
Tundra and taiga ecosystems comprise nearly 40 % of the terrestrial landscapes of Canada. These permafrost ecosystems have supported humans for more than 4500 years, and are currently home to ca. 115,000 people, the majority of whom are First Nations, Inuit and Métis. The responses of these ecosystems to the regional warming over the past 30–50 years were the focus of four Canadian IPY projects. Northern residents and researchers reported changes in climate and weather patterns and noted shifts in vegetation and other environmental variables. In forest-tundra areas tree growth and reproductive effort correlated with temperature, but seedling establishment was often hindered by other factors resulting in site-specific responses. Increased shrub cover has occurred in sites across the Arctic at the plot and landscape scale, and this was supported by results from experimental warming. Experimental warming increased vegetation cover and nutrient availability in most tundra soils; however, resistance to warming was also found. Soil microbial diversity in tundra was no different than in other biomes, although there were shifts in mycorrhizal diversity in warming experiments. All sites measured were sinks for carbon during the growing season, with expected seasonal and latitudinal patterns. Modeled responses of a mesic tundra system to climate change showed that the sink status will likely continue for the next 50–100 years, after which these tundra systems will likely become a net source of carbon dioxide to the atmosphere. These IPY studies were the first comprehensive assessment of the state and change in Canadian northern terrestrial ecosystems and showed that the inherent variability in these systems is reflected in their site-specific responses to changes in climate. They also showed the importance of using local traditional knowledge and science, and provided extensive data sets, sites and researchers needed to study and manage the inevitable changes in the Canadian North.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".