Assessing Urban Tree Responses to Climate and Pollution: Implications for Environmental Monitoring and Management
Bibliographic record
Abstract
In the context of climate change, trees are increasingly used as tools to create healthier and more comfortable urban environments. However, the extent of their impact on urban settings is intricately tied to their physiological health, growth, and vitality. This study evaluates urban trees' physiological response to the urban climate's primary stressors, high temperatures, low precipitations, traffic emissions and environmental pollutants. We investigated tree growth and δ13C, δ18O, δ15N, radiocarbon (F14C) levels and heavy metals in tree rings by comparing periurban parks, urban parks, busy streets, and airport zones in two Italian cities, Firenze and Pisa with a focus on Pinus pinea.Our preliminary findings indicate that climatic conditions did not directly affect tree growth in urban parks. However, high temperatures and reduced precipitations influenced tree physiology more than pollution. In detail, carbon (δ13C) and oxygen (δ18O) stable isotopes revealed sensitivity to high temperatures and drought in urban parks, whereas the indicators of pollution investigated in this study (δ15N and F14C) did not exhibit pronounced differences between urban and periurban parks.The general hypothesis is that the other urban sites (busy streets and airport zones), characterized by environmental constraints such as water deficit and high temperatures, show a higher δ13C and a lower δ18O than the periurban area. Regarding the characterization of the 15N and 14C and environmental pollutant concentrations in the tree rings, we assume they are more evident in the urban neighbours than in periurban contexts.These findings underscore the importance of selecting tree species adapted to urban conditions to maximise the ecosystem services provided by trees. In addition, it is essential to study the effects of the urban environment on plant growth and physiology, as the urban environment—characterized by higher temperatures and lower precipitations—represents a model of future climate conditions. This setting provides an opportunity to investigate tree responses to climate change, offering insights that may inform urban forestry and resilience strategies. Ultimately, our data demonstrate the utility of tree rings as an effective tool for assessing air and environmental quality in urban compared to periurban sites.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".