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Record W4321995435 · doi:10.5194/egusphere-egu23-9919

Dynamic Geodiversity, Geosystem Services, and Sustainable Development: Insights from Sesia Val Grande UNESCO Global Geopark

2023· preprint· en· W4321995435 on OpenAlexaboutno aff
Michele Guerini, Rasool Bux Khoso, Alizia Mantovani, Marco Giardino, Cristina Viani

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicGeotourism and Geoheritage Conservation
Canadian institutionsnot available
Fundersnot available
KeywordsGeodiversityEcosystem servicesGeographyGeoparkClimate changeBiodiversityEnvironmental resource managementSustainable developmentEnvironmental planningEcosystemEcologyEnvironmental scienceTourism

Abstract

fetched live from OpenAlex

Human activities and global factors have caused imbalances in mountain regions, leading to significant changes in these environments. One of the most visible impacts of rising temperatures is the melting of glaciers, which causes changes in the pressure on adjacent slopes and increases their instability, leading to mass movements (Chiarle et al., 2021). Other notable effects include the degradation of permafrost and increased erosion in previously glaciated areas (Savi et al., 2021). These changes affect the prevalence of natural hazards and result in the loss of geodiversity and ecosystem services, making it necessary to develop new conservation strategies to protect mountain regions and their geoheritage.To understand the impact of climate change and human activity on geoheritage and on the benefits that geodiversity provides to society, we conducted a study in the Alagna Valsesia municipality, a high-elevation mountain area in the Sesia Val Grande UGGp. We mapped geodiversity in that area using GIS data following a quali-quantitative approach. Then we identified geosites and evaluated their value to show their potential. We also assessed various abiotic ecosystem services, including regulating, provisioning, knowledge, cultural, and supporting services, and mapped them analysing the evolutionary relationship between humans and nature. By evaluating global drivers of change, we were able to understand the impact of these changes on identified services and to highlight the need for strong planning and management strategies for the Sesia Val Grande UGGp and for the sustainable development of vulnerable mountain regions.This approach helps us to understand the natural and human-induced threats to geodiversity and enables us to understand the importance of considering geoheritage in planning and management to promote sustainable development actions.ReferencesChiarle M, Geertsema M, Mortara G, Clague JJ. 2021. Relations between climate change and mass movement: Perspectives from the Canadian Cordillera and the European Alps. Global and Planetary Change 202: 103499;Savi S, Comiti F, Strecker MR. 2021. Pronounced increase in slope instability linked to global warming: A case study from the eastern European Alps. Earth Surface Processes and Landforms 46 : 1328–1347. DOI: 10.1002/ESP.5

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.012
GPT teacher head0.191
Teacher spread0.179 · 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.

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
Published2023
Admission routes1
Has abstractyes

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