Strategies to mitigate shifts in red oak (<i>Quercus</i> sect. <i>Lobatae</i>) distribution under a changing climate
Bibliographic record
Abstract
Red oaks (Quercus sect. Lobatae) are a taxonomic group of hardwood trees, which occur in swamp forests, subtropical chaparral and savannahs from Columbia to Canada. They cover a wide range of ecological niches, and many species are thought to be able to cope with current trends in climate change. Genus Quercus encompasses ca. 500 species, of which ca. 80 make up sect. Lobatae. Species diversity is greatest within the southeastern USA and within the northern and eastern regions of Mexico. This review discusses the weak reproductive barriers between species of red oaks and the effects this has on speciation and niche range. Distribution and diversity have been shaped by drought adaptations common to the species of sect. Lobatae, which enable them to fill various xeric niches across the continent. Drought adaptive traits of this taxonomic group include deciduousness, deep tap roots, ring-porous xylem, regenerative stump sprouting, greater leaf thickness and smaller stomata. The complex interplay between these anatomical and morphological traits has given red oaks features of drought tolerance and avoidance. Here, we discuss physiological and genetic components of these adaptations to address how many species of sect. Lobatae reside within xeric sites and/or sustain normal metabolic function during drought. Although extensive drought adaptation appears to give sect. Lobatae a resilience to climate change, aging tree stands, oak life history traits and the current genetic structures place many red oak species at risk. Furthermore, oak decline, a complex interaction between abiotic and biotic agents, has severe effects on red oaks and is likely to accelerate species decline and fragmentation. We suggest that assisted migration can be used to avoid species fragmentation and increase climate change resilience of sect. Lobatae.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".