Deep Planting Has No Short- or Long-Term Effect on the Survival and Growth of White Spruce, Black Spruce, and Jack Pine
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
Abstract Although studies in the past have reported that the deeper planting of conifers has no effect on seedling performance, most planting guidelines in use today still recommend that seedlings be planted to the rootcollar. Past studies were mostly observational, used bareroot seedlings, and often reported early results from just one or two depths of planting treatments. Most of the results available regarding planting depth for boreal species are anecdotal, although they are planted by the hundreds of millions every year. The present study reports no short-term (1 year) or long-term (15 to 19 years) negative effect of planting depth on the survival and height and diameter growth of black spruce, white spruce, and jack pine seedlings over three large, replicated experiments in the boreal forest of eastern and northern Quebec (eastern Canada). Four different depth treatments were compared, from manual planting at the rootcollar to the deepest mechanical planting treatment at 10 cm or more, making this the largest, longest-lasting study of its kind. Although, as expected, important differences in growth were present between species, all three commonly planted conifers reacted similarly to the planting depth treatments (no effect). This result can in part be attributed to an almost perfect control of frost heaving in the deepest two treatments. Planting depth effects were assessed using analysis of variance, multiple Tukey honestly significant difference, and uncorrected pairwise one-tailed t-tests to increase the probability of detecting a negative effect. Absolute differences and effect sizes (generally small and often positive with greater depths) were also analyzed.
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 | 0.001 | 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 | 0.001 |
| 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 it