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Agrobiodiversity dynamics in a French wine-growing region

2022· article· en· W4310271554 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueOENO One · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicHorticultural and Viticultural Research
Canadian institutionsCanada Research ChairsUniversity of Toronto
FundersInstitut National de Recherche pour l'Agriculture, l'Alimentation et l'EnvironnementAgence Nationale de la Recherche
KeywordsAgricultural biodiversityVineyardGeographySpecies richnessAgricultureLivelihoodBiodiversityAgroforestryCash cropNatural resource economicsEcologyEconomicsBiology

Abstract

fetched live from OpenAlex

Agrobiodiversity is a promising nature-based solution in the pursuit of sustainable agriculture. In wine-growing systems, commercial pressure and varietal regulations have narrowed agrobiodiversity in vineyards despite higher diversity being an important buffer against the effects of climate change. If drivers of grape diversity change are well-understood at national to global scales, little is known about the local, past or anticipated trajectories that drive agrobiodiversity dynamics depending on growers’ cultural values, practices and choices. We combined quantitative agricultural census data and qualitative ethnographic approaches to characterise changes in the diversity of grape varieties from 1960 to 2020 at the communal and vineyard levels in a French wine-growing region, and to decipher the drivers of change. We highlight that vineyards have drastically changed in 60 years, with a decline in planted area and in farm number. We outline that despite a loss of varietal richness across both vineyard and communal scales, varietal richness remains high and evenness have increased across geographic scales in 2020. Ethnographic field observations emphasize that growers account for external drivers (e.g., market changes, regulation and policy, technology, environmental), but also cultural values when they choose which grape varieties to plant. Grape diversity was maintained despite market integration as an insurance to spread production risk, mitigate market volatility and address environmental uncertainties. Securing livelihoods in the midst of market changes has been a major concern for growers over the last six decades and remains so. Despite a pessimistic future vision of the vineyard shared by most growers, the Gaillac region has a cultural heritage that values diversity and that thereby supports adaptation to climate change. We expect that environmental factors may play a more important role in grape selection and planting sites in the future under the influence of climate change and pesticide reduction policies. In order to expand individual initiatives resulting in diversified grape selection, growers need to be better connected with stakeholders at a variety of institutional levels.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.759
Threshold uncertainty score0.885

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.042
GPT teacher head0.227
Teacher spread0.185 · 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