Viscum album in French forests: Distribution, environmental drivers and impacts on tree health and growth
Bibliographic record
Abstract
The European mistletoe ( Viscum album ) is represented in France by three subspecies and plays a dual role in ecosystems. While it provides essential food and habitat for numerous animal species, it also reduces the economic value of timber and weakens trees, making them more vulnerable to biotic and abiotic stressors. This study leveraged the French National Forest Inventory dataset, comprising observations from over 737,000 trees across more than 80,000 plots, to investigate the environmental factors shaping mistletoe distribution and assess its impacts on tree health and growth performance. Our findings revealed that mistletoe distribution is not random within the range of its host species but is significantly influenced by climate and soil conditions, as well as by the history of forest use. V . a . album was primarily constrained by soil properties, whereas V. a. abietis and V. a. austriacum were strongly affected by isothermality. Additionally, mistletoe was more frequently observed on trees with a higher crown dieback and, for Scots pine and silver fir, trees with a high level of infestation exhibited a growth reduction of 23–34 % compared to non-parasitized individuals. Fir and pine mistletoe occurrences were significantly lower in species-rich stands and in younger forests compared to older ones. With the ongoing impacts of climate change, implementing fine-scale monitoring of mistletoe populations could help foresters mitigate mistletoe-induced economic losses while simultaneously supporting biodiversity conservation efforts.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".