Green roof plant species diversity improves ecosystem multifunctionality
Bibliographic record
Abstract
Summary Constructed ecosystems such as green roofs often contain monocultures or low‐diversity plant communities, but adding more plant species to these systems can increase ecosystem service provisioning. Mixture advantage, when species‐rich treatments outperform the best monocultures, is desirable in constructed ecosystems due to the cost of increasing diversity. However, there have not been any studies in constructed ecosystems that have quantitatively compared mixtures with the best monocultures for multifunctionality, and there have been few studies that have examined how provision of ecosystem services changes over time as plant communities develop. In a green roof system, I predicted (i) that the mixture advantage would be stronger for ecosystem multifunctionality than for single ecosystem functions and (ii) that ecosystem service provisioning and complementarity in above‐ground biomass would increase over time. Fifteen monocultures of plant species from five life‐form groups (succulents, tall forbs, dwarf shrubs, creeping forbs, grasses) were compared with three‐species mixtures of the same life‐form and mixtures of species from three and five different life‐forms in a modular green roof system. Indicators of ecosystem services including above‐ground production, thermal regulation, stormwater retention, nutrient uptake and carbon sequestration and two indices of ecosystem multifunctionality were compared. Canopy density increased over time while substrate temperature decreased, suggesting higher provisioning of valuable ecosystem services. For single services, the positive relationship between planted species richness and ecosystem service grew stronger over time, but was consistently strong over time for multifunctionality. Quantile regression indicated a weak mixture advantage for several services including both multifunctionality indices. While the effects were small, different species optimized different functions, thus multifunctioning is enhanced in more diverse mixtures by combining species that maximize different functions. Tripartite partitioning of canopy density showed that overyielding and trait‐independent complementarity fluctuated between years in response to shifts in species abundances, but dominance and trait‐dependent complementarity increased over time. Synthesis and applications. This study provides the first evidence in a constructed ecosystem that mixtures can outperform the best monocultures for multiple ecosystem services. Mixtures of plant life‐forms can improve green roof performance. The biodiversity–ecosystem function relationships observed in natural ecosystems can also occur in novel and highly simplified engineered ecosystems.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".