Oak trees decline; a sign of climate variability impacts in the west of Iran
Bibliographic record
Abstract
The Persian oak, Quercus brantii, trees in the Zagros region of Western Iran have been in decline since 2000. The decline is assumed to be highly connected with changes in meteorological parameters. Our objectives were to quantify the long-term trends in meteorological parameters and reference evapotranspiration (ET0) in the Zagros region and estimate ecohydrological parameters highly affected by climate variability and related to rainfall interception (I) process (i.e., canopy storage capacity (S), the ratio of mean evaporation rate from the wet canopy to the mean rainfall intensity (E/R), and the free throughfall coefficient (p)). Long-term (1961-2010) changes in air temperature (T), precipitation (P), and wind speed (WS) were obtained from six synoptic meteorological stations located in the region. Throughfall (TF) was measured using the sixteen rain gauges randomly located underneath the crown of the five individual trees. P was measured using rain gauges fixed in an open space nearby to the oak trees .I was computed as the difference between P and TF. From 2000 to 2010, meteorological parameters and ET0 changed slightly; T, WS, and ET0 increased (+0.6 ˚C, +0.4 m.s -1, +0.25 mm.day-1, respectively), while P decreased (-60 mm).When climate patterns between 1961-2010 were analyzed for 6 synoptic weather stations, P significantly decreased significantly at one station, whereas T significantly increased at two stations and significantly decreased at another. I was estimated to be 40% and 25% within in-leaf and leaf-less periods, respectively. During the in-leaf period, the mean values of S, E/R, and p were roughly estimated to be 1 mm, 0.22, and 0.23, respectively. Our results indicate that the Zagros region is getting warmer and oak trees will indisputably experience reduction in the available water because of increased evaporative loss.
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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 | 0.001 | 0.001 |
| 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".