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Record W6911536431 · doi:10.5281/zenodo.11219138

Seminatural areas act as reservoirs of genetic diversity for crop pollinators and natural enemies across Europe

2024· article· en· W6911536431 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsAgriculture and Agri-Food Canada
FundersEuropean Commission
KeywordsGenetic diversityGene flowPopulationSpecies richnessBiodiversityCoccinella septempunctataPopulation geneticsPollinator

Abstract

fetched live from OpenAlex

Despite increasing recognition of the importance of the multiple dimensions of biodiversity, including functional or genetic diversity as well as species diversity, most conservation studies on ecosystem service-providing insects focus on simple diversity measures such as species richness and abundance. In contrast, relatively little is known about the genetic diversity and resilience of pollinators or natural enemies of crop pests to population fragmentation and local extinction. The genetic diversity and demographic dynamics of remnant populations of beneficial insects in agricultural areas can be a useful indicator proving additional insights into their conservation status, but this is rarely evaluated. Although gene flow between agricultural and semi-natural areas is key to maintaining genetic diversity, its extent and directionality remain largely unexplored. Here, we apply a pan-European sampling protocol to quantify genetic diversity and structure and assess gene flow between agricultural and nearby semi-natural landscapes in populations of two key ecosystem service-providing insect species, the lady beetle Coccinella septempunctata, an important predator of aphids and other crop pests, and the bee pollinator Andrena flavipes. We show that A. flavipes populations are genetically structured at the European level, whereas populations of C. septempunctata experience widespread gene flow across the continent and lack any defined genetic structure. In both species, we found that there is high genetic connectivity between populations established in croplands and nearby semi-natural areas and, as a consequence, they harbor similar levels of genetic diversity. Interestingly, demographic models for some regions support asymmetric gene flow from semi-natural areas to nearby agricultural landscapes. Collectively, our study demonstrates how semi-natural areas can serve as genetic reservoirs of both pollinators and natural enemies for nearby agricultural landscapes, acting as sources for recurrent recolonization and, potentially, contributing to enhancing ecosystem service and crop production resilience in the longer term.

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)0.001
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 score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.036
GPT teacher head0.238
Teacher spread0.202 · 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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