Evergreen shrubs dominate responses to experimental summer warming and fertilization in Canadian mesic low arctic tundra
Bibliographic record
Abstract
Summary Climate change in arctic tundra is projected to increase soil fertility, which may alter plant community composition and ecosystem processes by shifting niche space to favour particular species' life‐history strategies. The rate and magnitude of change in soil fertility may be critical to determining plant community responses, and so effects of slow increases in nutrient availability due to climate warming may differ substantially from those of chronic high‐level fertilizer additions. We investigated above‐ and below‐ground plant biomass responses to experimental summer warming and above‐ground responses to nutrient additions (low‐level N and factorial N and P) in a mesic birch hummock tundra community in the central Canadian Low Arctic after eight years of experimental treatment. Plant community biomass responses to experimental warming were fundamentally different from those of high‐level N and/or P additions, mainly due to opposing effects on the evergreen shrubs. Evergreen shrub above‐ground biomass increased 66% with greenhouse warming, but decreased on average 70% with high‐level N and/or P additions, driven by the strong responses of Rhododendron subarcticum . Because of this evergreen response, greenhouse‐warming increased total above‐ground biomass by 32% and total below‐ground biomass by 70%, but did not significantly change the total above‐ground/below‐ground biomass ratio. However, warming increased the shoot/root ratio of Betula glandulosa threefold. Increased soil fertility created interactions between N and P availability, whereby increased P availability led to a substantial increase in inorganic N availability. Meanwhile, the growth of several species that span a range of different functional groups was stimulated by the separate N and P additions. These factorial fertilization results highlight the importance of understanding climate warming impacts on availability of both of these nutrients in order to predict plant community responses. Synthesis . Our results strongly suggest that the trajectory of mesic tundra vegetation change with warming depends critically on the rate of increase in soil fertility. The relatively large greenhouse‐induced biomass increase in evergreen compared to deciduous shrubs suggests that carbon balance and albedo feedbacks to warming will be restricted in mesic tundra ecosystems, at least in their early responses to climate change.
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 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) | 0.002 | 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 teacher head, 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".