Dendroclimatic analysis of red pine affected by <i>Diplodia</i> shoot blight in different latitudinal regions in Michigan
Bibliographic record
Abstract
Drought and intraspecific competition in red pine (Pinus resinosa Ait.) stands in Michigan have been implicated as predisposing factors for increased shoot blight risk caused by Diplodia pinea Desm. The overall objective of this study is to examine the interactive effects of drought, other climatic factors, and biotic factors (intraspecific competition) on productivity and growth of red pine forests affected by Diplodia shoot blight. This study incorporates a dendroclimatic approach that allows the retrospective examination of past annual diameter growth in relation to historical climate and the assessment of the potential impacts of future climate change. A total of 20 red pine stands were sampled in two latitudinal regions (the Upper Peninsula (UP) and the Lower Peninsula (LP) regions) of Michigan across two levels of initial stand density (low vs. high) and two levels of forest health condition (healthy vs. D. pinea affected). The full dendroclimatic relationships revealed in this study indicated that other climatic factors, in addition to summer drought stress, impacted red pine radial growth. Overall, red pine radial growth was generally more affected by precipitation and moisture index than solely by temperature variables. The radial growth response to climate depended on latitudinal region: summer moisture stress was more influential in the LP; cold spring and early summer temperatures negatively impacted growth more in the UP; and the degree of winter harshness was more of a factor in the UP. Crown damage caused by winter damage may have predisposed red pine stands to D. pinea affection by providing an easier entry point for fungal infection. Negative relations with precipitation in D. pinea affected stands may be due to increased dispersal of spores in D. pinea affected stands with significant rain and any increased storm and wind activity. Projections of radial growth under future scenarios of climate change indicate that climate warming has the potential to increase growth mainly in red pine stands in the UP region where growth has historically been limited by cool temperatures early in the growing season. Under the moisture index model, growth of red pine under the drier (A2) climate change scenario, only the D. pinea impacted high-density stands in the LP region are projected to show a significant decrease in growth by the middle (2041–2070) and final (2071–2100) projection periods. Model-based projections of forest growth in Michigan generally do not account for forest health issues such as invasive pathogens. The current study therefore provides a new understanding of the role of forest pathogens under future climate change.
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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) | 0.001 | 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".