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Record W4294252978 · doi:10.1017/s1742170522000229

What are farmers' perceptions about farmland landbirds? A Galapagos Islands perspective

2022· article· en· W4294252978 on OpenAlexaff
Ilke Geladi, Pierre‐Yves Henry, Paulina Couenberg, Rick Welsh, Birgit Feßl

Bibliographic record

VenueRenewable Agriculture and Food Systems · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsUniversity of British Columbia
FundersGalapagos Conservancy
KeywordsBiodiversityAgricultureLivestockGeographyAgroforestryEcologyBiologyForestry

Abstract

fetched live from OpenAlex

Abstract Conservation practices in agricultural landscapes can greatly mitigate biodiversity loss. However, agricultural landscapes are embedded in complex, social-ecological systems and therefore require a strong social-ecological approach for effective conservation measures. The Galapagos Islands are globally recognized for their high levels of biodiversity. Nevertheless, in recent years, Galapagos landbirds have suffered rapid declines, specifically in the agricultural zone. Our study is the first to examine the farmers’ perception of landbirds in the agricultural zone of Santa Cruz, Galapagos Islands. We conducted semi-structured interviews with 38 farmers to characterize the relationship between farmers and landbirds including how landbirds affect farmers and farmers’ perceptions of landbirds. The interviewed farmers managed a diverse array of farm types including coffee in agroforestry settings (23.7%), small-scale fruit and vegetable (60.5%) and livestock production (15.8%). We found that 86.9% of farmers had a positive or neutral perception of birds despite 52.6% of farmers finding finches bothersome. The most common techniques farmers employed to deter birds were putting out food and water, using nets to protect seedbeds and crops and using protective tubes around young plants. Our results suggest a positive potential for future conservation work targeted on farmland biodiversity. Future conservation projects should also address disservices and the mitigation of crop raiding by landbirds, the uninformed use of pesticides and other pest issues such as ants and rats.

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 score0.230
Threshold uncertainty score0.617

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 communication0.0000.000
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 head0.008
GPT teacher head0.200
Teacher spread0.192 · 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

Citations8
Published2022
Admission routes1
Has abstractyes

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