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Record W2890455962 · doi:10.1111/jbi.13408

Anthropogenic and environmental factors affect the tree line position of <i>Fagus sylvatica</i> along the Apennines (Italy)

2018· article· en· W2890455962 on OpenAlexaff
Giuliano Bonanomi, Angelo Rita, Emilia Allevato, Gaspare Cesarano, Luigi Saulino, Gaetano Di Pasquale, Marina Allegrezza, Simone Pesaresi, Marco Borghetti, Sergio Rossi, Antonio Saracino

Bibliographic record

VenueJournal of Biogeography · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsElevation (ballistics)Tree lineEcotoneFagus sylvaticaPhysical geographyPopulationClimate changeEnvironmental scienceEcologyGeographyClimatologyGeologyBiologyBeechHabitatDemographyMathematics

Abstract

fetched live from OpenAlex

Abstract Aim High‐elevation forest line or tree line is an ecological ecotone representing the upper elevation thermal limit for forest development. The current tree line position is the result of the past human activity interacting with climatic and topographic conditions. In this study, we investigate how climate, local topographic factors and anthropogenic disturbance currently affect tree line distribution. Location Apennine Mountains, 900 km latitudinal gradient along the Italian Peninsula. Methods Overall, 302 mountain peaks were studied, comprising 3,622 km of measured tree lines. The position of the Fagus sylvatica tree line in all peaks was assessed and correlated with 58 selected variables representing climate, topography and human disturbance. Results The mean tree line elevation was 1,589 m a.s.l., with considerable variability among peaks. Contrary to our expectations, the tree line elevation was lower in the warmer southerly exposed slopes compared to north‐facing aspects, where we found the highest tree line (2,141 m a.s.l.). Correlation analysis indicates that both climatic and human density variables are associated with tree line elevation, with the climate having more influence in high elevation mountains, while human impact plays a prominent role in low elevation mountain peaks. Specifically, we found negative correlations between density of the resident population around each peak and tree line elevation at all examined dates (1861, 1921, and 2011), suggesting a pervasive negative impact of human activity on tree lines. As regards climatic variables, tree line elevation showed a stronger negative correlation with winter and spring months temperature than with mean annual temperature. Noteworthy, climatic variables had stronger effect on high elevation peaks (&gt;1,900 m a.s.l.) compared with low elevation ones (&lt;1,900 m a.s.l.). Main Conclusion Our data provide evidence that the current position of the F. sylvatica tree line in the Apennines is heavily depressed as a result of a complex interaction between climatic factors and the past human pressure.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.006
Threshold uncertainty score0.315

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.010
GPT teacher head0.220
Teacher spread0.209 · 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 teacher head, 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

Citations37
Published2018
Admission routes1
Has abstractyes

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