Topography modulates near-ground microclimate in the Mediterranean Fagus sylvatica treeline
Bibliographic record
Abstract
Understanding processes controlling forest dynamics has become particularly important in the context of ongoing climate change, which is altering the ecological fitness and resilience of species worldwide. However, whether forest communities would be threatened by projected macroclimate change or unaffected due to the controlling effect of local site conditions is still a matter for debate. After all, forest canopy buffer climate extremes and promote microclimatic conditions, which matters for functional plant response, and act as refugia for understory species in a changing climate. Yet precisely how microclimatic conditions change in response to climate warming will depend on the extent to which vegetation structure and local topography shape air and soil temperature. In this study, we posited that forest microclimatic buffering is sensitive to local topographic conditions and canopy cover, and using meteorological stations equipped with data-loggers we measured this effect during 1 year across a climate gradient (considering aspect as a surrogate of local topography) in a Mediterranean beech treeline growing in contrasting aspects in southern Italy. During the growing season, the below-canopy near-ground temperatures were, on average, 2.4 and 1.0 °C cooler than open-field temperatures for south and north-west aspects, respectively. Overall, the temperature offset became more negative (that is, lower under-canopy temperatures at the treeline) as the open-field temperature increased, and more positive (that is, higher under-canopy temperatures at the treeline) as the open-field temperature decreased. The buffering effect was particularly evident for the treeline on the south-facing slope, where cooling of near-ground temperature was as high as 8.6 °C for the maximum temperature (in August the offset peaked at 10 °C) and as high as 2.5 °C for the average temperature. In addition, compared to the south-facing slope, the northern site exhibited less decoupling from free-air environment conditions and low variability in microclimate trends that closely track the free-air biophysical environment. Although such a decoupling effect cannot wholly isolate forest climatic conditions from macroclimate regional variability in the south-facing treeline, it has the potential to partly offset the regional macroclimatic warming experienced in the forest understory due to anthropogenic 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 | 0.000 | 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 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".