Plant Nutrition Requirements for an Installed Sedum-Vegetated Green Roof Module System: Effects of Fertilizer Rate and Type on Plant Growth and Leachate Nutrient Content
Bibliographic record
Abstract
The objectives of this study were to compare fertilizer rates and types to identify an optimum rate to maintain green roof vegetative coverage and encourage plant growth (i.e., plant performance) while minimizing the amount and concentration of nutrients leached from a green roof module system. Sedum-vegetated modules with no added fertilizer (control) were compared with modules fertilized with 5, 7.5, 10, 15, 20, 30, and 60 g·m −2 nitrogen (N) of 16N–2.6P–10K POLYON ® Homogenous NPK plus Minors, 5–6 month controlled-release fertilizer (CRF), 5 g·m −2 N of a 2.9N–2.2P–2.3K fly-larvae processed chicken manure fertilizer (5-Sus), or 5 g·m −2 N of 4N–4P–4K Gaia Green All Purpose organic fertilizer (5-OR). The total amount and concentration of aluminum (Al), calcium (Ca), cadmium (Cd), chromium (Cr), copper (Cu), iron (Fe), mercury (Hg), potassium (K), magnesium (Mg), sodium (Na), NH 4 + , nickel (Ni), NO 3 – , phosphorus (P), lead (Pb), sulfur (S), and zinc (Zn) in leachate as well as plant overall appearance, winter injury, vegetative coverage, shoot height, bloom duration, and leaf color of green roof modules were evaluated between July 2011 and Aug. 2012. A CRF fertilizer rate of 15 g·m −2 N maximized vegetative coverage and overall plant appearance while maintaining leachate quality within Ontario and Canadian guidelines for most of the measured elements. The amount of Zn in the CRF appeared to be higher than plant demand and the high amount and concentration of P in leachate was likely the result of release from the growing substrate. The 5-Sus fertilizer resulted in increased coverage the first spring and increased greenness soon after application compared with the same rate of CRF. Overall, 15 g·m −2 N of CRF was the best treatment based on vegetative coverage and plant growth in sedum-vegetated green roof modules.
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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".