Climate and bark beetle effects on forest productivity — linking dendroecology with forest landscape modeling
Bibliographic record
Abstract
In forested systems throughout the world, climate influences tree growth and aboveground net primary productivity (ANPP). The effects of extreme climate events (i.e., drought) on ANPP can be compounded by biotic factors (e.g., insect outbreaks). Understanding the contribution of each of these influences on growth requires information at multiple spatial scales and is essential for understanding regional forest response to changing climate. The mixed conifer forests of the Lake Tahoe Basin, California and Nevada, provide an opportunity to analyze biotic and abiotic influences on ANPP. Our objective was to evaluate the influence of moisture stress (climatic water deficit, CWD) and bark beetles on basin-wide ANPP from 1987 to 2006, estimated through tree core increments and a landscape simulation model (LANDIS-II). Tree ring data revealed that ANPP increased throughout this period and had a nonlinear relationship to water demand. Simulation model results showed that despite increased complexity, simulations that include moderate moisture sensitivity and bark beetle outbreaks most closely approximated the field-derived ANPP∼CWD relationship. Although bark beetle outbreaks and episodic drought-induced mortality events are often correlated, decoupling them within a simulation model offers insight into assessing model performance, as well as examining how each contributes to total declines in productivity.
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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 | 0.001 |
| 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 | 0.001 |
| 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".