Tree species versus regional controls on ecosystem properties and processes: an example using introduced <i>Pinus contorta</i> in Swedish boreal forests<sup>1</sup>This article is one of a selection of papers from the 7th International Conference on Disturbance Dynamics in Boreal Forests.
Bibliographic record
Abstract
When species are introduced into new regions, there is great uncertainty whether the trait differences of the introduced species or regional factors, such as climate or edaphic properties, will serve as the dominant control of ecosystem properties or processes. In this study, we examined whether the introduction of Pinus contorta Douglas ex Loudon into Sweden has altered forest floor properties and processes or whether these properties are more strongly controlled by regional factors. We compared forest floor pH, potential N mineralization rates, bulk density, litter and forest floor depths, C and N concentrations and pool sizes, C:N ratios, and soil microbial communities using substrate-induced respiration and phospholipid fatty acid analysis among stands of introduced P. contorta (SwPc), native Swedish Pinus sylvestris L. (SwPs), and native Canadian P. contorta (CaPc). For most forest floor properties (pH, net NH4+ mineralization, bulk density, N mass, and the microbial phospholipid fatty acid community structure), SwPc sites were more similar to SwPs than to CaPc, whereas litter and forest floor depth were significantly higher in SwPc than the two other forest types. Our findings suggest that regional factors exerted a stronger control on most forest floor properties and processes than did species differences between the two Pinus species for the regions we studied.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".