Pathogens and insects in a pristine forest ecosystem: the Sierra San Pedro Martir, Baja, Mexico
Bibliographic record
Abstract
We determined the incidence of pathogens and insects across mixed-conifer stands in the Sierra San Pedro Martir (SSPM) of northern Baja, Mexico, to assess the role of pests in a pristine forest ecosystem. We also determined the spatial distribution of the two most common pests, mistletoe, Phoradendron pauciflorum Torrey, and the fir engraver, Scolytus ventralis LeConte, of white fir (Abies concolor (Gord. & Glend.) Lindl.) across a 25-ha grid to assess spread and what host and pest variables were related. In these open parklike stands the mean tree density was 160 trees/ha, of which 58% were trees >20 cm diameter at breast height (DBH). In these low-density, mixed-aged stands we found that mixed-conifer species were well represented with no one species being completely dominant. Percent cumulative mortality for the SSPM was 12.7%, ranging from 2 to 24%, with the greatest amount of mortality occurring in the larger size classes, trees [Formula: see text]50 cm DBH. Multiple linear regression analysis showed that 78% of the mortality we observed was explained by pathogens and bark beetles (r2 = 0.78, P = 0.0001, F = 84). Mean pest incidence for Jeffrey pine (Pinus jeffreyi Grev. & Balf. in A. Murray), white fir, and sugar pine (Pinus lambertiana Dougl.) was 21, 88, and 2%, respectively. We found a number of relationships among host and pest variables, as well as a pathogen insect interaction, and across the SSPM we found that nonhost species may be interfering in certain hostpest interactions. Spatial patterns from the 25-ha grid survey revealed that both P. pauciflorum and S. ventralis incidence were widespread. Phoradendron pauciflorum showed no spatial structure across the 25 ha but S. ventralis showed some degree of spatial structuring across the survey area. We also found that mistletoe severity was negatively correlated with regeneration of white fir. In pristine forests, pathogens and insects influence mortality and regeneration success, affecting stand structure and composition.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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".