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Agro-biodiversity has increased over a 95 year period at sub-regional and regional scales in southern Quebec, Canada

2016· article· en· W2563389714 on OpenAlexafffundabout
Delphine Renard, Elena M. Bennett, Jeanine M. Rhemtulla

Bibliographic record

VenueEnvironmental Research Letters · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Rural Development Research
Canadian institutionsUniversity of British ColumbiaMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiodiversityAgricultural biodiversityAgricultureGeographySustainabilityLivestockEcosystem servicesEcosystemCash cropAbundance (ecology)Ecosystem diversityEcologyAgroforestryEnvironmental scienceBiologyForestry

Abstract

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Decline in agricultural biodiversity (cultivated species and wild species used for food or that support agro-ecosystem functioning) at the farm scale has fueled concerns about potential negative effects of this biodiversity loss on the ecological and economic sustainability of agro-ecosystems. Despite these concerns, formal assessment of how agro-biodiversity has historically changed at scales larger than individual farms is fragmented. We quantified the changes in the abundance of 10 crop and livestock species, their overall diversity, and the way they were mixed in ‘baskets’ of agricultural products from 1911 to 2006, at a sub-regional (15 Regional County Municipalities) and regional scales. We found that the diversity of agricultural products increased at the regional scale. From 1911 to 1966, the region produced fodder, milk and maple, mixed in two low-diversity baskets. After 1966, the region provided a greater variety of baskets composed of newly introduced cash crops and high-value livestock. All baskets provided were themselves more diverse than historically and varied greatly in composition across space. Increasing regional diversity was related to changes in agricultural policy, while the variation in the composition of baskets produced was related to biophysical and socioeconomic characteristics. Our results indicate that agricultural transformations of the 21th century did not invariably lead to agro-biodiversity loss at large scales. We have also demonstrated that combining diversity measures at multiple scales with the analysis of compositional change of agricultural products over long time periods could improve research on the links between agro-biodiversity dynamics and resilience.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.590
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 studies0.0000.001
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 head0.023
GPT teacher head0.203
Teacher spread0.180 · 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

Citations12
Published2016
Admission routes3
Has abstractyes

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