Seedling Response to Simulated Browsing and Reduced Water Availability: Insights for Assisted Migration Plantations
Bibliographic record
Abstract
To facilitate forest transition to future climate conditions, managers can use adaptive silvicultural tools, for example the assisted translocation of tree species and genotypes to areas with suitable future climate conditions (i.e., assisted migration). Like traditional plantations, however, assisted migration plantations are at risk of failure because of browsing by ungulate herbivores. The ability of seedlings to tolerate browsing could also be hampered by low water availability, as is expected under climate change. Using a greenhouse experiment with five eastern North American tree species, we evaluated the effects of simulated winter browsing and reduced water availability on the growth (total biomass, shoot:root ratio), survival, and chemical composition (nitrogen, total phenolics, flavonoids) of seedlings. We compared seedlings from three geographic provenances representing three climate analogues, i.e., locations with a current climate similar to the climate predicted at the plantation site at a specific time (here: current, mid-century and end of the century). We hypothesized that seedlings would allocate resources to the system (shoots or roots) affected by the most limiting treatment (simulated browsing or reduced water availability). Additionally, we evaluated whether the combination of treatments would have an additive or non-additive effect on the growth, survival and chemical composition of the seedlings. Quercus rubra seedlings reacted only to the water reduction treatment (changes in biomass and N concentration, dependent on geographic provenance) while Pinus strobus reacted only to the simulated browsing treatment (biomass and chemical composition). We also observed non-additive effects of reduced water availability and simulated browsing on Prunus serotina, Acer saccharum and Thuja occidentalis. In general, shoot:root ratio and investment in chemical defense did not vary in response to treatments. The regrowth response observed in Q. rubra and A. saccharum suggests that these species could tolerate periodic browsing events, even when water availability is reduced. More information is required to understand their long-term tolerance to repeated browsing events and to harsher and more frequent water stress. We highlight the importance of species-specific growth and allocation responses that vary with geographic provenance, which should be considered by managers when planning climate-adapted strategies, such as assisted migration.
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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".