eDNA sampling detects early colonization of spotted lanternfly Lycorma delicatula better than in-person scouting in an urban landscape

Authors: KELSEY, DAIYANERA - The Ohio State University; LEE-RODRIGUEZ, JONATHAN - The Ohio State University; MICHEL, ANDREW - The Ohio State University; Ranger, Christopher; CANAS, LUIS - The Ohio State University; LEACH, ASHLEY - The Ohio State University

Submitted to: Environmental DNA
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/5/2025
Publication Date: 5/26/2025
Citation: Kelsey, D., Lee-Rodriguez, J., Michel, A., Ranger, C.M., Canas, L., Leach, A. 2025. eDNA sampling detects early colonization of spotted lanternfly Lycorma delicatula better than in-person scouting in an urban landscape. Environmental DNA. 7 Article e70123. https://doi.org/10.1002/edn3.70123.
DOI: https://doi.org/10.1002/edn3.70123

Interpretive Summary: The spotted lanternfly (SLF) is an invasive insect that is rapidly colonizing the Northeast and Midwest USA. As SLF spreads across the USA, monitoring this species is crucial to assess management techniques. Environmental DNA (eDNA) is DNA that organisms deposit and can be detected to indicate their presence or absence. Environmental DNA can give us an idea of the spread of SLF. SLF are often found in association with the tree-of-heaven, near rail lines, and in disturbed areas. Understanding the relationship of these factors to the detection of SLF can help us better detect and eliminate these pests. Our objectives were to monitor at-risk locations for SLF and compare the efficacy of visual and eDNA methods. We sampled for eDNA in Cleveland during 2022 and 2023. To collect eDNA, we used paint rollers that were sprayed with water and rolled randomly on trees within infested habitats. The water was filtered using membrane filters and later extracted using DNA extraction solutions. The samples were analyzed using real-time polymerase chain reaction. Our results demonstrated that detecting eDNA deposited by SLF outperformed visual detection of this insect. Our results also showed that tree-of-heaven, active rail lines, and landscape features did not influence the eDNA or visual detection of SLF. The findings of this study will help with management practices to control the spread of SLF.

Technical Abstract: The spotted lanternfly (SLF), Lycorma delicatula, is an invasive insect species rapidly colonizing the Northeast and Midwest USA. While a pest of certain agricultural commodities, one of SLF most significant impacts appears to be a nuisance for residents. SLF readily infests plants and trees in woodlots, parks, and other natural areas. Honeydew is also excreted during feeding, attracting stinging Hymenoptera and causing sooty mold to develop on plants. This creates hazards and nuisance for communities. As SLF spreads across the USA, monitoring this species is crucial in attempts to control the increasing populations. As we monitor the spread of SLF, environmental DNA (eDNA) detection can give us an idea of the spread and how early we can detect SLF. SLF are often found in association with the tree-of-heaven (Ailanthus altissima), near rail lines, and in disturbed areas. Understanding the relationship of these factors to the detection of SLF can help us better detect and eliminate these pests. Our objectives were to monitor at-risk locations for SLF and determine the efficacy of visual and eDNA methods. We hypothesized that eDNA would outperform in-person, visual scouting. We also hypothesized that active rail lines, tree-of-heaven density, and landscape features would correlate with our SLF detections. We sampled for eDNA in Cleveland during the years 2022 and 2023. To collect eDNA, we used paint rollers that were sprayed with water and rolled randomly on selected surrounding trees. The water was filtered using membrane filters and later extracted using DNA extraction solutions. The samples were analyzed using real-time polymerase chain reaction. Our results showed eDNA significantly outperformed visual detection. Our results also showed that tree-of-heaven, active rail lines, and landscape features did not significantly influence our detection of SLF. The findings of this study will help with management practices to control the spread of SLF.