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Record W2907894628 · doi:10.1038/s42003-018-0257-6

Biological control of an agricultural pest protects tropical forests

2018· article· en· W2907894628 on OpenAlex
Kris A. G. Wyckhuys, Alice C. Hughes, C. Buamas, Anne C. Johnson, Liette Vasseur, Louis Reymondin, Jean‐Philippe Deguine, Douglas Sheil

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

VenueCommunications Biology · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBiological Control of Invasive Species
Canadian institutionsBrock University
Fundersnot available
KeywordsMealybugDeforestation (computer science)AgroforestryCroppingBiological pest controlAgricultureGeographyBiodiversityPest controlBiologyEcologyHemiptera

Abstract

fetched live from OpenAlex

Abstract Though often perceived as an environmentally-risky practice, biological control of invasive species can restore crop yields, ease land pressure and thus contribute to forest conservation. Here, we show how biological control against the mealybug Phenacoccus manihoti (Hemiptera) slows deforestation across Southeast Asia. In Thailand, this newly-arrived mealybug caused an 18% decline in cassava yields over 2009–2010 and an escalation in prices of cassava products. This spurred an expansion of cassava cropping in neighboring countries from 713,000 ha in 2009 to > 1 million ha by 2011: satellite imagery reveals 388%, 330%, 185% and 608% increases in peak deforestation rates in Cambodia, Lao PDR, Myanmar and Vietnam focused in cassava crop expansion areas. Following release of the host-specific parasitoid Anagyrus lopezi (Hymenoptera) in 2010, mealybug outbreaks were reduced, cropping area contracted and deforestation slowed by 31–95% in individual countries. Hence, when judiciously implemented, insect biological control can deliver substantial environmental benefits.

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)0.001
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 score0.882
Threshold uncertainty score0.731

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.064
GPT teacher head0.280
Teacher spread0.216 · 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