Dendrogeomorphological analysis of a debris flow in the Monarch Butterfly Biosphere Reserve, central Mexico
Bibliographic record
Abstract
Abstract Debris flows are one of the most hazardous and frequent landslides in mountainous regions. In this research, we apply dendrogeomorphological techniques to analyze the debris flow that occurred in February 2010 in the Monarch Butterfly Biosphere Reserve in central Mexico. Firstly, analyzed precipitation data from two nearby meteorological stations has indicated that an extraordinary precipitation event accumulated 236.4 mm of rainfall over a 5-day period, from January 31st to February 4th, 2010. In addition, we generated a geomorphological cartography of the area at 1:600 scale by interpreting the images obtained using an Unmanned Aerial Vehicle. Subsequently, we carried out dendrochronological sampling on 98 Abies religiosa trees (125 cores); the cores were dated using cross-dating and the ring width was measured for generating a chronology, in which the years with growth disturbances as a result of the debris flow could be identified and characterized. We identified three types of growth anomalies in the tree ring series: (a) traumatic resin ducts, (b) growth suppression, and (c) growth releases, related to the 2010 debris flow event. We also estimated the debris flow intensity through the scar heights recorded in the trees, which allowed us to identify that the intensity of the debris flow was greater in the transport zone. These results highlight the benefit of the dendrogeomorphological technique used in the collection of spatio-temporal information on debris flow activity in intertropical montane environments, especially where information about mass movement processes is limited. Therefore, we demonstrate that dendrogeomorphological techniques, in combination with other parameters such as scar height on the trees, as well as a detailed geomorphological survey, allows for an understanding of the dynamics of debris flows, which, in the case of Mexico have not been previously evaluated using this approach.
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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 | 0.003 | 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) | 0.001 | 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".