Dataset Information

Chirosurveillance: The use of native bats to detect invasive agricultural pests.

ABSTRACT: Invasive insect pests cost the agricultural industry billions of dollars annually in crop losses. Timely detection of pests is critical for management efficiency. Innovative pest detection strategies, such as environmental DNA (eDNA) techniques, combined with efficient predators, maximize sampling resolution across space and time and may improve surveillance. We tested the hypothesis that temperate insectivorous bats can be important sentinels of agricultural insect pest surveillance. Specifically, we used a new high-sensitivity molecular assay for invasive brown marmorated stink bugs (Halyomorpha halys) to examine the extent to which big brown bats (Eptesicus fuscus) detect agricultural pests in the landscape. We documented consistent seasonal predation of stink bugs by big brown bats. Importantly, bats detected brown marmorated stink bugs 3-4 weeks earlier than the current standard monitoring tool, blacklight traps, across all sites. We highlight here the previously unrecognized potential ecosystem service of bats as agents of pest surveillance (or chirosurveillance). Additional studies examining interactions between other bat and insect pest species, coupled with comparisons of detectability among various conventional monitoring methods, are needed to verify the patterns extracted from this study. Ultimately, robust economic analyses will be needed to assess the cost-effectiveness of chirosurveillance as a standard strategy for integrated pest management.

SUBMITTER: Maslo B

PROVIDER: S-EPMC5371280 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Chirosurveillance: The use of native bats to detect invasive agricultural pests.

Maslo Brooke B Valentin Rafael R Leu Karen K Kerwin Kathleen K Hamilton George C GC Bevan Amanda A Fefferman Nina H NH Fonseca Dina M DM

PloS one 20170329 3

Invasive insect pests cost the agricultural industry billions of dollars annually in crop losses. Timely detection of pests is critical for management efficiency. Innovative pest detection strategies, such as environmental DNA (eDNA) techniques, combined with efficient predators, maximize sampling resolution across space and time and may improve surveillance. We tested the hypothesis that temperate insectivorous bats can be important sentinels of agricultural insect pest surveillance. Specifical ...[more]

PMID: 28355216

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Project description:BackgroundInter-regional relationships between landscape factors and biological responses in natural conditions are important but difficult to predict because of the differences in each landscape context and local environment. To examine the inter-regional variability in relation to landscape factors and the biological response of an insect pest of rice, Stenotus rubrovittatus, we extrapolated a damage prediction model (the 'original model' of our previous study) for rice using land-use data. The 'original model' comprised as fixed factors the area of source habitat (i.e. pastures and graminoid-dominated fallow fields), soybean fields, and rice paddies within 300-m radii with research years as the random intercept. We hypothesized that the original model would be applicable to new regions, but the predictive accuracy would be reduced. We predicted that fitting a new extended model, adjusting the parameter coefficients of identical fixed factors of the 'original model,' and adding regional random intercepts would improve model performance (the 'extended model'). A field experiment was conducted in two regions that had a similar landscape context with the original region, each in a different year of four years in total. The proportion of rice damage and surrounding land use within a 300-m radius was investigated, and the data were applied to the models and the applicability and accuracy of the models were examined.ResultsWhen the 'original model' was assigned to the combined data from the original and extrapolated regions, the relationship between the observed and the predicted values was statistically significant, suggesting that there was an inter-regional common relationship. The relationship was not statistically significant if the model was applied only to the new regions. The extended model accuracy improved by 14% compared with the original model and was applicable for unknown data within the examined regions as demonstrated by three-fold cross validation.ConclusionsThese results imply that in this pest-crop system, there is likely to be a common inter-regional biological response of arthropods because of landscape factors, although we need to consider local environmental factors. We should be able to apply such relationships to identify or prevent pest hazards by offering region-wide management options.

Dataset Information

Chirosurveillance: The use of native bats to detect invasive agricultural pests.

Publications

Chirosurveillance: The use of native bats to detect invasive agricultural pests.

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