Microbial effects on plant phenology and fitness
Bibliographic record
Abstract
Plant development and the timing of developmental events (phenology) are tightly coupled with plant fitness. A variety of internal and external factors determine the timing and fitness consequences of these life-history transitions. Microbes interact with plants throughout their life history and impact host phenology. This review summarizes current mechanistic and theoretical knowledge surrounding microbe-driven changes in plant phenology. Overall, there are examples of microbes impacting every phenological transition. While most studies have focused on flowering time, microbial effects remain important for host survival and fitness across all phenological phases. Microbe-mediated changes in nutrient acquisition and phytohormone signaling can release plants from stressful conditions and alter plant stress responses inducing shifts in developmental events. The frequency and direction of phenological effects appear to be partly determined by the lifestyle and the underlying nature of a plant-microbe interaction (i.e., mutualistic or pathogenic), in addition to the taxonomic group of the microbe (fungi vs. bacteria). Finally, we highlight biases, gaps in knowledge, and future directions. This biotic source of plasticity for plant adaptation will serve an important role in sustaining plant biodiversity and managing agriculture under the pressures of 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) | 0.001 | 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 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".