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Record W4392662885 · doi:10.5194/egusphere-egu24-22109

Plant facilitation and soil microbiome modulate treeline advancement across the Apennines

2024· preprint· en· W4392662885 on OpenAlexaff
Giulio Tesei, Angelo Rita, Maurizio Zotti, Luigi Saulino, Marina Allegrezza, Antonio Saracino, Sergio Rossi, Emilia Allevato, Mohamed Idbella, Giuliano Bonanomi

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsFacilitationMicrobiomeEcologyEnvironmental scienceGeographyBiologyNeuroscienceBioinformatics

Abstract

fetched live from OpenAlex

Elevational treelines are expected to shift upwards in response to warming climate. Nevertheless, the global inconsistency in the upward shifts of treelines implies that factors such as topography, edaphic properties, disturbance, and the presence of competing vegetation may override the positive effect of cold stress alleviation. We report here the results of our research regarding the impact of climate warming and land abandonment on F. sylvatica at the treeline in Apennines. The underlying hypothesis was that in the Apennines, where historical human activities have significantly depressed the current altitudinal treeline position, shrubs act as nurse plants, promoting the upward shift of Fagus sylvatica. To test this hypothesis, nine treeline sites, along 500–km-long latitudinal gradient in Apennines, with different elevations, rock substrates, and physiognomic types including Juniperus communis, Pinus mugo, Vaccinium myrtillus shrublands, and grasslands were selected. In these sites, 68 transects were collected and analysed spatially fine-scale distribution data of F. sylvatica individuals with relation to both their age and their position associated or not to shrub. To evaluate the correlation between the above- and below-ground ecosystem components and to investigate the facilitation mechanisms more thoroughly, the soil microbiota was analysed within the different physiognomic types. The results showed that F. sylvatica regeneration is rare in open secondary grasslands at 1.600-2.100 m a.s.l., highlighting a bottleneck in the regeneration phase of this species. On the contrary, a strong association between shrubs and F. sylvatica individuals was observed. Compared with the adjacent grassland, F. sylvatica regeneration was 58.3 times higher under P. mugo, 131.5 higher under J. communis and 102.4 higher under V. myrtillus. Results concerning soil microbial communities showed a high diversity between open grassland and shrubs and comparable between different shrub species. Age-structure of F. sylvatica population indicates that, in the last 50 years, recruitment under shrubs is continuous, while episodic in grassland. In conclusion our study reveals that above the existing treeline in the Apennines, the development of F. sylvatica individuals is contingent upon the presence of shrubs, which function as nurse species. Shrubs are a necessary condition for F. sylvatica re-colonization of the high-altitude open areas affected, in the last centuries, by intense human land use.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.009
GPT teacher head0.232
Teacher spread0.223 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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