Effects of variable rate aerial application of Vision on moose (Alces alces) winter browsing and hardwood vegetation
Bibliographic record
Abstract
Experimental aerial treatment of 7 mixedwood areas in late summer for conifer \nrelease with Vision? at 0.80, 1.06, and 1.60 kg a.e./ha, decreased living hardwood stem densities \nafter ten months by 42, 61 and 42% respectively on treated plots, while controls increased by 13%. \nTwenty two months after treatment stem densities were reduced (from pre-spray levels) by 48, 65 and \n61%; controls increased 19%. Greatest numbers of stems occurred on moderately deep, fresh soils. \nAfter treatment, winter browsing rates decreased in both six and 18 months post spray on all plots \nand were consistently higher on controls when compared with treated sub-blocks. Decline was \nprogressive over two years after treatment on sprayed areas but recovered in the second year on \ncontrols. The two highest application rates had the lowest browsing levels. Conversely, winter \ntrack data showed no differences in moose use between sprayed areas and controls, nor any \ndifference among treatments. This suggested moose still traveled through sprayed areas, but did not \nstop to browse. In addition to stem density counts, cover (%) for both herbs \nand hardwoods were estimated to evaluate the effectiveness of Vision? as a conifer release. \nHardwood cover was reduced significantly by all application rates; differences among treatments \nwere not significant. Herbaceous ground cover was reduced approximately 20% on all treated areas \none season after spray but by next year these sprayed areas had recovered to equivalent levels as \ncontrols. Neither crop tree diameter \nnor height growth was affected by Vision? application at this early stage of the experiment. Moose \ndensities within these study areas appear to be low enough that food is not a limiting factor. \nThe small amount of spraying in Ontario (relative to the productive forest land base) is not \nexpected to affect moose populations. However, in areas with high concentrations of sprayed \ncutovers there should be concern. Results of this short term study suggest that 0.80 kg a.e./ha \ncontrolled hardwood and herbaceous competition as well as 1.06 & 1.60 kg a.e./ha. However, the \nlowest application rate showed signs of increased moose use two years post spray compared with the \ntwo higher rates. Consequently, when spray programs are concentrated in one management unit, the \n0.80 kg a.e./ha rate is recommended.
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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) | 0.000 | 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) | 0.000 | 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".