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Record W4200190395 · doi:10.3390/birds2040035

Avian Use of Dairy Farm Ponds and Landowners’ Perceptions of Their Management for Wildlife Conservation

2021· article· en· W4200190395 on OpenAlexaffabout
Luc Bélanger, Charles Maisonneuve, Jean‐Paul Rodrigue

Bibliographic record

VenueBirds · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsMinistère des Ressources naturelles et des ForêtsEnvironment and Climate Change Canada
Fundersnot available
KeywordsRiparian zoneHabitatWildlifeGeographySpecies richnessBiodiversityWetlandAbundance (ecology)AgroforestryWildlife conservationHuman–wildlife conflictEcologyEnvironmental scienceBiology

Abstract

fetched live from OpenAlex

Farm ponds are among the last remaining lentic wetland habitats in human-dominated agricultural and suburban landscapes. However, their wildlife value and farmers’ willingness to maintain them for the conservation of regionally declining biodiversity are often both poorly documented. The objectives of this study of 61 dairy farm ponds located in Southern Quebec (Canada) were to (1) describe their biophysical features and birds’ use, (2) determine habitat and landscape characteristics that influence the bird community, and (3) assess the willingness of farmers to support wildlife use. The studied ponds were small (0.17 ha) and had rectangular shape with rocky/muddy steeply slopes (21°), surrounded by 3 m wide riparian strips and pastures, hayfields, and fallows. They were located about 300 m from farmhouses, buildings, streams, and adjacent ponds. A total of 1963 individuals belonging to 46 bird species were observed. The abundance of all bird species, of species with declining populations, and of crop damaging species were positively related to the area of fallow land and to the width of riparian strips; the areas of cereals and of mixed-wood forest had a negative influence. Only two habitat variables had influence on species richness: the width of riparian strips (+) and the distance to the closest farm buildings (–). Most pond landowners (>80%) were in favour of increasing wildlife use if they were given access to associated financial support and logistical assistance. Wider riparian strips and adjacent uncultivated field margins are recommended.

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 score0.005
Threshold uncertainty score0.135

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 studies0.0000.000
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 head0.021
GPT teacher head0.244
Teacher spread0.222 · 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

Citations7
Published2021
Admission routes2
Has abstractyes

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