Effects of past and present microclimates on northern and southern plant species in a managed forest landscape
Bibliographic record
Abstract
Abstract Questions Near‐ground temperatures can vary substantially over relatively short distances, enabling species with different temperature preferences and geographical distributions to co‐exist within a small area. In a forest landscape, the near‐ground temperatures may change due to management activities that alter forest density. As a result of such management activities, current species distributions and performances might not only be affected by current microclimates, but also by past conditions due to time‐lagged responses. Location Sweden. Methods We examined the effects of past and current microclimates on the distributions and performances of two northern, cold‐favoured, and two southern, warm‐favoured, plant species in 53 managed forest sites. Each pair was represented by one vascular plant and one bryophyte species. We used temperature logger data and predictions from microclimate models based on changes in basal area to relate patterns of occurrence, abundance, and reproduction to current and past microclimate. Results The two northern species were generally favoured by microclimates that were currently cold, characterised by later snowmelt and low accumulated heat over the growing season. In contrast, the two southern species were generally favoured by currently warm microclimates, characterised by high accumulated heat over the growing season. Species generally had higher abundance in sites with a preferred microclimate both in the past and present, and lower abundance than expected from current conditions, if the past microclimate had changed from warm to cold or vice versa, indicating time‐lags in abundance patterns of the species. Conclusions Our results show a potential importance of past and present microclimate heterogeneity for the co‐existence of species with different temperature preferences in the same landscape and highlight the possibility to manage microclimates to mitigate climate change impacts on forest biodiversity.
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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 | 0.001 | 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 | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".