Atmospheric change as a driver of change in the Canadian boreal zone<sup>1</sup>
Bibliographic record
Abstract
Global anthropogenic emissions of greenhouse gases and hazardous air pollutants have produced broad yet regionally disparate changes in climatic conditions and pollutant deposition in the Canadian boreal zone (the boreal). Adapting boreal resource management to atmospheric change requires a holistic understanding and awareness of the ongoing and future responses of terrestrial and freshwater ecosystems in this vast, heterogeneous landscape. To integrate existing knowledge of and generate new insights from the broad-scale impacts of atmospheric change, we first describe historical and present trends (∼1980–2015) in temperature, precipitation, deposition of hazardous air pollutants, and atmospheric-mediated natural disturbance regimes in this region. We then examine their associations with ecosystem condition and productivity, biological diversity, soil and water, and the carbon budget. These associations vary considerably among ecozones and likely undergo further changes under the emerging risks of atmospheric change. We highlight the urgent need to establish long-term, boreal-wide monitoring for many key components of freshwater ecosystems to better understand and project the influences of atmospheric change on boreal water resources. We also formulate three divergent future scenarios of boreal ecosystems in 2050. Our scenario analysis reveals multiple undesirable changes in boreal ecosystem structure and functioning with more variable atmospheric conditions and frequent land disturbances, while continuing business-as-usual management of natural resources. It is possible, though challenging, to reduce unwanted consequences to ecosystems through management regimes focussed on socio-ecological sustainability and developing resilient infrastructure and adaptive resource-management strategies. We emphasize the need for proactive actions and improved foresight for all sectors of society to collaborate, innovate, and invest in anticipation of impending global atmospheric change, without which the boreal zone will face a dim future.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".