Native American fire management at an ancient wildland–urban interface in the Southwest United States
Bibliographic record
Abstract
The intersection of expanding human development and wildland landscapes-the "wildland-urban interface" or WUI-is one of the most vexing contexts for fire management because it involves complex interacting systems of people and nature. Here, we document the dynamism and stability of an ancient WUI that was apparently sustainable for more than 500 y. We combine ethnography, archaeology, paleoecology, and ecological modeling to infer intensive wood and fire use by Native American ancestors of Jemez Pueblo and the consequences on fire size, fire-climate relationships, and fire intensity. Initial settlement of northern New Mexico by Jemez farmers increased fire activity within an already dynamic landscape that experienced frequent fires. Wood harvesting for domestic fuel and architectural uses and abundant, small, patchy fires created a landscape that burned often but only rarely burned extensively. Depopulation of the forested landscape due to Spanish colonial impacts resulted in a rebound of fuels accompanied by the return of widely spreading, frequent surface fires. The sequence of more than 500 y of perennial small fires and wood collecting followed by frequent "free-range" wildland surface fires made the landscape resistant to extreme fire behavior, even when climate was conducive and surface fires were large. The ancient Jemez WUI offers an alternative model for fire management in modern WUI in the western United States, and possibly other settings where local management of woody fuels through use (domestic wood collecting) coupled with small prescribed fires may make these communities both self-reliant and more resilient to wildfire hazards.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".