The effect of environmental changes on the photosynthesis and transpiration of rates of evergreen and deciduous trees during the summer, autumn, and winter periods
Bibliographic record
Abstract
By analyzing the seasonal changes in the photosynthesis (CO₂ uptake and fixation) and transpiration (water loss) rates of evergreen and deciduous trees, we can determine which trees should be promoted for future plantation projects, to develop a greener and more sustainable future. Trees exhibiting higher photosynthesis rates under various environmental conditions and growing seasons could reduce the rapidly increasing concentration of CO₂ in our atmosphere, and global warming. Evergreen and deciduous trees differ in their leaf senescence patterns through seasonal variations. Photosynthesis and transpiration rates were measured using the LI-COR LI-6200 Portable Photosynthesis System. Samples of evergreen and deciduous leaves under study were taken from 4 different tree species; 2 Evergreen Species: Thuja plicata (Western Red Cedar), Chamaecyparis lawsoniana (Lawson Cypress), and 2 Deciduous Species: Acer rubrum (Red Maple), Quercus rubra (Red Oak) on UBC's Sustainability Street, for a span of 9 months including summer, autumn, and winter (July 2010 - February 2011). Environmental factors such as light intensity, temperature, and the amount of precipitation were also recorded with observational data provided from Environment Canada's Historical Weather Database. Results showed higher photosynthetic and transpiration rates amongst the evergreen species during the fall/winter period, when compared to the deciduous species, as deciduous leaves undergo a senescence process due to environmental changes. Furthermore, specific protein gel analysis data through SDS-PAGE profiling and Western Blotting also showed higher levels of key photosynthesis proteins, light harvesting complex of photosystem II (LHCIIB), and the ribulose-1,5 bisphosphate carboxylase/oxygenase (RUBISCO) in evergreen species when compared to deciduous ones during the fall/winter. Photosynthesis and transpiration data will be discussed in relation to environmental parameters such as light intensity, temperature, and the amount of precipitation. The findings of this study will contribute to our knowledge about the role of these trees in CO₂ absorption and sustainable development. Disclaimer: “UBC SEEDS provides students with the opportunity to share the findings of their studies, as well as their opinions, conclusions and recommendations with the UBC community. The reader should bear in mind that this is a student project/report and is not an official document of UBC. Furthermore readers should bear in mind that these reports may not reflect the current status of activities at UBC. We urge you to contact the research persons mentioned in a report or the SEEDS Coordinator about the current status of the subject matter of a project/report.”
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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) | 0.000 | 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".