Investigating the Effect of a Mixed Mycorrhizal Inoculum on the Productivity of Biomass Plantation Willows Grown on Marginal Farm Land
Bibliographic record
Abstract
Inoculation with mycorrhizal fungi, proven mediators of soil fertility, has great potential in agricultural and silvicultural systems. This is particularly true in short-rotation coppices (SRCs), where questions of food displacement and fertilization are causes of concern for researchers and policy makers. We set out to thoroughly test if current inoculation methods, coupled with reduced fertilization, can demonstrate a growth benefit in SRC willows on marginal lands. Roughly 21,600 Salix miyabeana Seeman (‘SX61’ and ‘SX64’) were planted in a hierarchical design with inoculation treatments randomized first, cultivars randomized second, and fertilization treatments randomized third. This process was repeated across three fields of different marginal soil type (which, in our experiment, were given the descriptive names Sandy, Rocky, and Dry). The inoculum species, Rhizoglomus irregulare Błaszk., Wubet, Renker & Buscot Sieverd., G.A. Silva & Oehl and Hebeloma longicaudum (Pers.) P. Kumm., were chosen as they are most likely to be commercially available, and because they represent both arbuscular and ectomycorrhizal inoculum types. Growth was measured over 2.5 years, or three growing seasons. Fertilization treatment (75 kg/ha Nitrogen), however, was only applied during the second growing season. Our results conclusively showed no benefit from mycorrhizal inoculation across fields that exhibited significantly different growth rates, as well as significant differentiation from fertilization.
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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) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".