Detection of Spotted Lanternfly (Lycorma delicatula) by Bats: A qPCR Approach to Forest Pest Surveillance

Invasive insect pests pose a significant threat to forest ecosystems. Effective pest management relies on detecting these pests, which can be challenging when populations are sparse, newly introduced, or not easily observable. The spotted lanternfly (Lycorma delicatula White), a recent invader to North America, has caused extensive damage across the eastern United States since its introduction in 2014. Conventional monitoring methods, such as traps or visual inspections, are limited in their spatial coverage and may not reliably attract or capture target species. In this study, we explored the potential of bat guano as an additional tool for invasive insect detection. We collected guano samples from five bat species across three forested sites in New Jersey, USA, between 2018 and 2022 and used species-specific quantitative PCR (qPCR) to detect spotted lanternfly DNA. Spotted lanternfly DNA was detected in guano from two bat species: big brown bats (Eptesicus fuscus) and eastern red bats (Lasiurus borealis). Detection probability was strongly influenced by spotted lanternfly phenology, with higher detection rates occurring during the adult life stage. The detection of spotted lanternfly DNA in bat guano demonstrates the feasibility of using guano analysis as a complementary tool for insect pest surveillance. Integrating guano-based monitoring with traditional methods could enhance insect pest detection efforts across diverse forested and agricultural landscapes.

Authors

Institutions

Publication Details

Journal
Forests
Published
2025-02-28
DOI
https://doi.org/10.3390/f16030443
Citations
1
Primary Topic
Fire effects on ecosystems
Type
article
Field-Weighted Citation Impact
1.11

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Detection of Spotted Lanternfly (Lycorma delicatula) by Bats: A qPCR Approach to Forest Pest Surveillance

Brooke Maslo, Kathleen Kerwin, Erin McHale, Christian Crosby et al.
1 citations
Forests
Fire effects on ecosystems
1.11
article

Detection of Spotted Lanternfly (Lycorma delicatula) by Bats: A qPCR Approach to Forest Pest Surveillance

Brooke Maslo, Kathleen Kerwin, Erin McHale, Christian Crosby, Kathleen Kyle, Robert Kwait
article en
1 citations

Abstract

Invasive insect pests pose a significant threat to forest ecosystems. Effective pest management relies on detecting these pests, which can be challenging when populations are sparse, newly introduced, or not easily observable. The spotted lanternfly (Lycorma delicatula White), a recent invader to North America, has caused extensive damage across the eastern United States since its introduction in 2014. Conventional monitoring methods, such as traps or visual inspections, are limited in their spatial coverage and may not reliably attract or capture target species. In this study, we explored the potential of bat guano as an additional tool for invasive insect detection. We collected guano samples from five bat species across three forested sites in New Jersey, USA, between 2018 and 2022 and used species-specific quantitative PCR (qPCR) to detect spotted lanternfly DNA. Spotted lanternfly DNA was detected in guano from two bat species: big brown bats (Eptesicus fuscus) and eastern red bats (Lasiurus borealis). Detection probability was strongly influenced by spotted lanternfly phenology, with higher detection rates occurring during the adult life stage. The detection of spotted lanternfly DNA in bat guano demonstrates the feasibility of using guano analysis as a complementary tool for insect pest surveillance. Integrating guano-based monitoring with traditional methods could enhance insect pest detection efforts across diverse forested and agricultural landscapes.

ForestsVol. 16(3)
Rutgers, The State University of New Jersey (US)
National Park Service
Openalex Percentile: Top 27%
Fire effects on ecosystems
1.11
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.