No evidence of foliar disease impact on crop root functional strategies and soil microbial communities: what does this mean for organic coffee?
Bibliographic record
Abstract
Global climate change is increasing pest and pathogen pressures on plant communities, deteriorating optimal plant functioning. In plant communities, root functional trait expression and microbial communities are important indicators of plant functioning belowground, and, when confronted with pathogens aboveground, can simultaneously reflect plant defence strategies. Yet, while research is continuing to emerge on the response of root functional traits and microbial processes to pathogens aboveground, little work has investigated these interactions in tree‐crops, or the role organic amendments play in moderating these relationships. The main objective of this study is to disentangle the dynamic effects of pathogens and amendments on root functional traits (i.e. specific root length and area, root diameter, root length density, root nitrogen and root carbon to nitrogen ratio) and root endophytic fungal communities. As a model, we use Coffea arabica (coffee) variety Caturra along a gradient of coffee leaf rust – a foliar disease prominent in coffee systems – under contrasting but widespread amendment regimes in biodiverse agroforestry systems. We found that root trait expression varies along established conservation and collaboration gradients, where fungal endophyte community composition varies significantly as a function of root traits. Belowground resource acquisition strategies do not change with foliar disease incidence, suggesting they may be decoupled. Rather, amendment regimes differentially shape root trait expression and microbial communities, where coffee plants under organic amendments, regardless of foliar disease incidence, expressed greater acquisitive traits and enhanced collaboration with symbiotic fungi. This is an important first step in disentangling the dynamic inter‐relationships between plant traits, endophytes and pathogens, generating new questions on the role of amendments in sustainable pathogen management in biodiverse agroecosystems.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".