The Role of Mycorrhizal Associations in Modulating Poplar Growth, Phytohormone Responses, and Mortality under Elevated CO2 and Temperature Conditions
Bibliographic record
Abstract
Climate change poses significant challenges to forests worldwide, particularly the Canadian boreal forest. Populus spp. are ecologically and economically important tree species that have had declining growth and survival due to elevated temperatures and droughts associated with climate change. Symbiotic microbes, such as mycorrhizal fungi, may increase plant growth under climate change conditions by altering tree metabolic profiles and increasing tree access to water and nutrients. My thesis explores the relationship between mycorrhizal fungi and a Populus hybrid (Populus x canadensis) grown under a range of future climate scenarios: ambient CO2 (400 ppm) or elevated CO2 (750 ppm) with either ambient temperatures or a +4 ˚C or +8˚C warming treatment. My primary objective is to assess how mycorrhizae influence growth, stress phytohormone concentrations, and stress tolerance of hybrid poplar under predicted future climatic scenarios. Additionally, I identify compounds exuded by mycorrhizal fungi and evaluate their potential to enhance plant growth. My findings reveal that different boreal mycorrhizal fungi produce similar profiles of phytohormones, amino acids, and organic acids in their exudates. The exudates of some mycorrhizal fungi enhanced plant growth, while others caused mortality. In my hybrid poplar growth study, the colonization of poplar roots by mycorrhizal fungi increased with elevated temperature and CO2. Inoculation with mycorrhizal fungi did not increase tree height or mass, with the exception of trees grown under +4 ˚C warming, where total biomass increased by ~15% compared to control trees. Unexpectedly, inoculation with mycorrhizal fungi almost always increased hybrid poplar mortality. To understand why mycorrhizal inoculation increased mortality but improved the growth of surviving hybrid poplars, I investigated the impacts of climate change and mycorrhizal inoculation on plant stress hormone concentrations. Mycorrhizal inoculation generally increased leaf concentrations of the stress hormone jasmonic acid, while the stress hormones salicylic acid and abscisic acid had reduced leaf concentrations across elevated temperature and CO2 treatments. Overall, my research contributes valuable insights into the intricate connections between mycorrhizal fungi, trees and climate change, offering a better understanding of forest ecosystem resilience in the face of environmental challenges.
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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 | 0.000 |
| 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 | 0.001 | 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 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".