Synergistic interactions: Population origin, chemical traits, and endophytic fungi shape white spruce adaptation across environments
Bibliographic record
Abstract
White spruce ( Picea glauca ), a dominant species in Canadian boreal forests, is increasingly threatened by climate change. Assisted migration, which involves relocating populations to areas with more suitable climates, has been proposed as a proactive management strategy to help vulnerable plant species in the face of climate change. However, it is not known whether assisted migration will impact the plant’s natural defence against herbivores. White spruce relies on toxic secondary metabolites, such as terpenes, along with symbiotic associations with endophytic fungi, to defend against many herbivores like the eastern spruce budworm. We explored if relocating to new climates, especially across long distances, influences chemical defences and fungal endophytes of white spruce. Our results showed that the population origin influenced terpene concentrations and the composition of endophytic fungi. In short-distance transplantations, population origin explained 31 % of the variation in terpene concentrations and 33 % of the variation in endophytic fungal communities. In long-distance transplantations, population origin explained 32 % of terpene variation and as much as 66 % of fungal community variation. Regression analyses further showed that, in short-distance transplantations, several terpene concentrations were significantly associated with elevation differences between origin and test sites as well as climatic variables from the source populations. In contrast, in long-distance transplantations, terpene concentrations were primarily associated with geographic differences (latitude and longitude) and mean annual precipitation (MAP). These findings highlight the ecological and genetic factors shaping white spruce adaptability to environmental changes. By elucidating the interactions between the population origin, chemical defence, and fungal endophytes, this study provides insights for developing forest management strategies that enhance the resilience and conservation of forest trees in response to climate change and pest pressures. • Terpene concentrations vary with geographic differences between sites and origins in assisted migration. • Terpene concentrations at short and long distances are shaped by different geographic and climatic factors. • Endophytic fungal communities are shaped by origin populations across transplant scales. • Terpenes and endophytes guide assisted migration and spruce management.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".