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Record W6992211089

Landscape heterogeneity impacts aphid suppression while adjacent habitats and aphid abundance impact predator movement in soybean

2022· dissertation· en· W6992211089 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMspace (University of Manitoba) · 2022
Typedissertation
Languageen
FieldEngineering
TopicNonlinear Optical Materials Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSoybean aphidAphidPredatorPredationPEST analysisAbundance (ecology)HabitatBiological pest control
DOInot available

Abstract

fetched live from OpenAlex

Landscape homogenization has resulted in the loss of crop and habitat diversity in agroecosystems, creating resource bottlenecks and higher rates of chemical inputs. This negatively impacts natural enemy communities and natural pest control. Landscape heterogeneity is thought to benefit predator populations (increased landscape complementation) and lower pest colonization (decreased resource concentration); however, few studies have investigated the relative contribution of these two processes in pest suppression. Habitats provide predators with differing floral and/or prey resources. Understanding how predators move between habitats during pest outbreaks is important for assessing how we can improve pest control in agricultural landscapes. My study investigates the direct and indirect impacts of landscape heterogeneity on sentinel soybean aphid populations open to and excluded from predation, in 23 soybean fields in Manitoba in 2017 and 2018 and aims to determine the role of adjacent habitats in predator movement in soybean during an aphid outbreak. Soybean fields were adjacent to alfalfa, canola, spring wheat, or woody vegetation. Five sticky traps were placed in soybean and the adjacent habitat to quantify predator abundance in 2017. Both years, bi-directional Malaise traps were used to quantify predator movement and sweep net samples and plant counts were conducted to quantify predator and aphid abundance in soybean. We found positive effects of crop diversity (1.5 km) on aphid abundance and indirect benefits to aphid suppression in the outbreak year, and positive effects of edge density (1.5 km) on aphid suppression during the low aphid year. Syrphids and coccinellids dominated all samples, were more abundant during the outbreak year, and their immigration was in response to aphid density. Syrphid movement was more impacted by the type of adjacent habitat than coccinellid movement, and wheat and canola were the main contributors of syrphids to soybean. Coccinellid abundance was highest in adjacent wheat. My study suggests planting wheat adjacent to soybean may benefit the early arrival of coccinellids and syrphids for aphid suppression and that landscape heterogeneity benefits aphid suppression through a reduction in resource concentration by crop diversification during outbreaks and through an increase in landscape complementation by edge density in low aphid years.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.356
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.010
GPT teacher head0.219
Teacher spread0.209 · 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