Evaluating Fertilizer Influence on Overwintering Survival and Growth of Sedum Species in a Fall-installed Green Roof
Bibliographic record
Abstract
Vegetation success on green roofs in northern climates is challenged by extreme weather conditions, especially in winter, and is influenced by season of installation and substrate fertility. Appropriate fertilization with phosphorus (P) and potassium (K) can reduce winter injury for some plant species. The objectives of this study were to identify both the effect of P and K fertilizer rates on Sedum spp. survival over the first winter and the response of Sedum spp. growth to fertilizer rates when applied at installation. In a fall-installed extensive green roof system, survival, growth, and visual appearance of Sedum mats in non-fertilized plots (control) were compared with plots fertilized with 16–6–13 POLYON ® Homogenous NPK plus Minors 3-4 month controlled-release fertilizer at 20.0 g nitrogen (N)/m 2 either alone or with additional P to total 28.8, 54.4, or 80.0 g P/m 2 or K to total 32.5, 51.6, or 70.6 g K/m 2 . Sedum mats were installed on 8 Oct. 2010 and plants in all plots survived the winter and the next year. During the 2011 growing season, vegetative coverage was not significantly different among any individual fertilized treatments; however, vegetative coverage data combined for all fertilized treatments was larger than the control. Fertilized treatments also showed larger plant height and biomass after one year, taller S. acre and S. sexangulare inflorescences, increased leaf greenness, and higher visual appearance rankings compared with the control. For individual S edum species, S. album showed the greatest coverage in P-fertilized treatments, and effects on S. acre and S. sexangulare were treatment-dependent. Application of a controlled-release N–P–K fertilizer, without additional P or K, can be used to encourage vegetative coverage, plant growth, leaf greenness, inflorescence height, and visual appearance in fall-installed extensive Sedum green roof systems.
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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 | 0.000 |
| 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".