Effects of mixing tree species and water availability on soil organic carbon stocks are depth dependent in a temperate podzol
Bibliographic record
Abstract
Abstract Mixing tree species is a forest management strategy put forward to increase and stabilize primary productivity. Yet, little is known about soil organic carbon (SOC) storage in mixed species forests, particularly under water shortage. In this study, we used a tree diversity experiment in southwestern France to assess the interactive effects of water availability (via irrigation) and mixing tree species (monocultures of pine ( Pinus pinaster ) and birch ( Betula pendula ) versus mixed plots of pine‐birch and pine‐birch‐oak ( Quercus robur )) on SOC stocks in the forest floor and across five mineral soil layers (0–5, 5–15, 15–30, 30–60 and 60–90 cm deep). We found that SOC stocks were negatively affected by irrigation in the forest floor due to an increase in decomposition rates. However, SOC stocks were positively influenced by both the mixing of tree species and irrigation in the mineral soil, particularly at the 15–30‐cm soil depth. This is because root niche partitioning in mixed plots and an increase in tree biomass in irrigated plots may have resulted in greater organic matter inputs through rhizodeposition and the incorporation of microbially‐derived compounds. These preliminary results indicate that SOC dynamics and its response to biotic and abiotic factors are strongly dependent on soil depth. Our data further highlight that the positive effect of mixing trees on SOC stocks was higher in irrigated plots, thereby contradicting the idea that tree mixture effects are expected to be greater when environmental conditions are harsher. We conclude that mixing tree species can increase SOC stocks in the short term in temperate forests, even if the exact mechanisms remain to be identified. Highlights Effects of mixing trees and increasing water availability on SOC are depth dependent. Increase in SOC stocks occurred mainly at the mid‐soil depth (15–30 cm). Effects of tree mixture on SOC were greater when soil water availability was high.
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.
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 | 0.000 | 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) | 0.001 | 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".