Higher aboveground carbon stocks in mixed-species planted forests than monocultures – a meta-analysis
Bibliographic record
Abstract
Abstract Natural forest is declining globally as the area of planted forest increases. Planted forests are often monocultures, despite results suggesting that higher species richness improves ecosystem functioning and stability. To test if this is generally the case, we performed a meta-analysis of available results. We assessed aboveground carbon stocks in mixed-species planted forests vs (a) the average of constituent species monocultures, (b) the best constituent species monoculture, and (c) commercial species monocultures. We investigated whether any advantage of mixtures over monocultures was positively related to species richness, as well as potential mechanisms driving differences in carbon stocks between mixtures and monocultures. The meta-analysis dataset included 79 comparisons from 21 sites. Carbon stocks in mixed planted forests were higher than the average of stocks in monocultures of their constituent species, containing on average 70% more carbon. Mixed planted forests also out-performed commercial monocultures, containing on average 77% more carbon. There was c.25% more carbon in mixed planted forests relative to the best performing monocultures, although this difference was not statistically significant. Overyielding was highest in four-species mixtures (richness range 2-6 species). More data providing better coverage of richness and age gradients (study sites aged 3.5-28 years) is needed to increase confidence in these results. None of the potential mechanisms we examined (nitrogen-fixer present vs absent; native vs non-native/mixed origin; tree diversity experiment vs forestry plantation) consistently explained variation in the diversity effects. This suggests that our findings are driven by a combination of small (statistically insignificant) effects from these sources or further unidentified mechanisms or some combination of the two. We conclude that increasing tree species richness in planted forests can increase carbon stocks while bringing other potential benefits associated with diversification. However, implementation will depend on the balance of these benefits relative to the operational challenges and costs of diversification.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".