PLoS ONE (2012) 7 (5 - e36533)

Soroush Parsa, Raul Ccanto, Edgar Olivera, Maria Scurrah, Jesus Alcazar and Jay A. Rosenheim (2012)
Explaining Andean potato weevils in relation to local and landscape features: A facilitated ecoinformatics approach
PLoS ONE 7 (5 - e36533)
Abstract:
Background
Pest impact on an agricultural field is jointly influenced by local and landscape features. Rarely, however, are these features studied together. The present study applies a "facilitated ecoinformatics" approach to jointly screen many local and landscape features of suspected importance to Andean potato weevils (Premnotrypes spp.), the most serious pests of potatoes in the high Andes.
Methodology/Principal Findings
We generated a comprehensive list of predictors of weevil damage, including both local and landscape features deemed important by farmers and researchers. To test their importance, we assembled an observational dataset measuring these features across 138 randomly-selected potato fields in Huancavelica, Peru. Data for local features were generated primarily by participating farmers who were trained to maintain records of their management operations. An information theoretic approach to modeling the data resulted in 131,071 models, the best of which explained 40.2-46.4% of the observed variance in infestations. The best model considering both local and landscape features strongly outperformed the best models considering them in isolation. Multi-model inferences confirmed many, but not all of the expected patterns, and suggested gaps in local knowledge for Andean potato weevils. The most important predictors were the field's perimeter-to-area ratio, the number of nearby potato storage units, the amount of potatoes planted in close proximity to the field, and the number of insecticide treatments made early in the season.
Conclusions/Significance
Results underscored the need to refine the timing of insecticide applications and to explore adjustments in potato hilling as potential control tactics for Andean weevils. We believe our study illustrates the potential of ecoinformatics research to help streamline IPM learning in agricultural learning collaboratives.
(The abstract is excluded from the Creative Commons licence and has been copied with permission by the publisher.)
Full text of article
Database assignments for author(s): Jay A. Rosenheim

Research topic(s) for pests/diseases/weeds:
environment - cropping system/rotation

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Pest and/or beneficial records:

Beneficial	Pest/Disease/Weed	Crop/Product	Country	Quarant.
	Premnotrypes (genus)	Potato (Solanum tuberosum)	Peru