Global environmental change and the biology of arbuscular mycorrhizas: gaps and challenges
Bibliographic record
Abstract
Our ability to make predictions about the impact of global environmental change on arbuscular mycorrhizal (AM) fungi and on their role in regulating biotic response to such change is seriously hampered by our lack of knowledge of the basic biology of these ubiquitous organisms. Current information suggests that responses to elevated atmospheric CO 2 will be largely controlled by host-plant responses, but that AM fungi will respond directly to elevated soil temperature. Field studies, however, suggest that changes in vegetation in response to environmental change may play the largest role in determining the structure of the AM fungal community. Nevertheless, the direct response of AM fungi to temperature may have large implications for rates of C cycling. New evidence shows that AM fungal hyphae may be very short lived, potentially acting as a rapid route by which C may cycle back to the atmospohere; we need, therefore, to measure the impact of soil temperature on hyphal turnover. There is also an urgent need to discover the extent to which AM fungal species are differentially adapted to abiotic environmental factors, as they apparently are to plant hosts. If they do show such an adaptation, and if the number of species is much greater than the number currently described (150), as seems almost certain, then there is the potential for several new fields of study, including community ecology and biogeography of AM fungi, and these will give us new insights into the impacts of global environmental change on AM fungi in moderating the impacts of global environmental change on ecosystems.Key words: arbuscular mycorrhiza, temperature, diversity, community structure, ecosystem, carbon cycle.
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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 | 0.009 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.005 | 0.024 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.008 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".