Effect of forest canopy composition on soil nutrients and dynamics of the understorey: mixed canopies serve neither vascular nor bryophyte strata
Bibliographic record
Abstract
Question: The effect of overstorey composition on above-ground dynamics of understorey vegetation is poorly understood. This study examines the understorey biomass, production and turnover rates of vascular and non-vascular plants along a conifer–broadleaf gradient of resource availability and heterogeneity. Location: Canadian boreal forests of northwest Quebec and Ontario. Methods: We sampled mature stands containing various proportions of black spruce (Picea mariana (Mill.) BSP), trembling aspen (Populus tremuloides Michx.) and jack pine (Pinus banksiana Lamb.). Above-ground biomass of the understorey vegetation was assessed through harvesting; annual growth rates were calculated as the differences between biomass in 2007 and 2008, as estimated by allometric relationships, and turnover rates were estimated as net primary production divided by the biomass in 2007. Results: Higher aspen presence, linked to greater nutrient availability in the forest floor, was generally associated with higher vascular biomass and production in the understorey. This effect was less pronounced in sites of high intrinsic fertility. In contrast, bryophyte biomass was positively associated with conifer abundance, particularly in wet sites of the Quebec study area. Non-linear responses resulted in total understorey biomass being lower under mixed canopies than under pure aspen or pure conifer canopies. Turnover rates did not differ with overstorey composition. Conclusions: While resource availability is a main driver of understorey productivity, resources as drivers appear to differ with differences in understorey strata components, i.e. vascular versus non-vascular plants. Resource heterogeneity induced by a mixed canopy had overall negative effects on understorey above-ground productivity, as this productivity seemed to rely on species adapted to the specific conditions induced by a pure canopy.
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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 | 0.001 |
| 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 | 0.001 | 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 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".