Detection and assessment of Armillaria in young conifer plantations of northwestern Ontario and northeastern China
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Methods for detecting and evaluating Armillaria in plantations were compared in a series \nof studies. The purposes of the studies were to standardize the Armillaria trapping technique, \nand to determine if it could be used in practical forest management to monitor and evaluate \nArmillaria root rot hazard in plantations. Trapping involves burying a removable substrate in \nthe soil for infection by rhizomorphs (RMs). The fungus reacts to the trap by rapidly colonizing \nthe substrate. The distribution of Armillaria is then inferred from the locations of infected \ntraps. \nIn a study of entrapment methods, spruce [Picea sp.) and poplar [Populus sp.) trap logs \nwere compared with each other and with mesh bags filled with conifer bark. Potato tuber \n(Solarium tuberosum) traps were unsuccessful. Bark bags were the most successful traps in \nterms of sensitivity, clarity of infection, and ease of interpretation, but they were more difficult \nto prepare and install than trap logs. Both species of trap logs detected similar levels of Armillaria \nprevalence. However, the spruce logs were generally easier to evaluate. Some inconsistencies \nin detection may be resolved by further refinements in trap preparation. \nIn a study of young plantations on recent cutovers and one undisturbed, mature spruce \nstand, estimates of the distribution of Armillaria based on various indicators were compared. \nTrap logs detected Armillaria in all plots including the mature spruce plot which was mossy and \nwater-logged. The percentages of plot area subjected to Armillaria impact were estimated to be \n3-21% using dead trees, 16-54% using residual stand material, and 12-69% using positive trap \nlogs. A comparison of these estimates showed that Armillaria RMs were much more prevalent \nthan was indicated by the dead planted trees. These estimates plus a survey of healthy and \ninfected trees showed that stump presence alone was a poor indicator of potential damage from \nArmillaria root rot. Mortality surveys were used to augment the trap results. Although current \nlevels of mortality were high (4.8% spruce, 3.6% Larix sp.), it was suggested that the trees may \nhave been predisposed to Armillaria attack by stresses such as root deformity. \nTo determine the utility of the trapping technique by forest managers unfamiliar with it, \nthe trap bag technique was introduced to a forest management unit in northeastern China. The \ntraps tested in a Pinus koraiensis plantation were superior to soil samples for evaluating the \npresence of viable RMs. Persons with little or no experience in identifying Armillaria learned to \nrecognize the fresh, abundant RMs quickly and confidently. \nIt was concluded that the trap methods described can be used at the management level, \nbut that they should be used in association with sound advice regarding the role of Armillaria \nin overall plantation health.
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.
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) | 0.000 | 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) | 0.002 | 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 it