Assessing drivers of localized invasive spread to inform large‐scale management of a highly damaging insect pest

Abstract

Studies of biological invasions at the macroscale or across multiple scales can provide important insights for management, particularly when localized information about invasion dynamics or environmental contexts is unavailable. In this study, we performed a macroscale analysis of the roles of invasion drivers on the local scale dynamics of a high‐profile pest, Lymantria dispar dispar L., with the purpose of improving the prioritization of vulnerable areas for treatment. Specifically, we assessed the relative effects of various anthropogenic and environmental variables on the establishment rate of 8010 quadrats at a localized scale (5 × 5 km) across the entire L. dispar transition zone (the area encompassing the leading population edge, currently from Minnesota to North Carolina). We calculated the number of years from first detection of L. dispar in a quadrat to the year when probability of establishment of L. dispar was greater than 99% (i.e., waiting time to establishment after first detection). To assess the effects of environmental and anthropogenic variables on each quadrat's waiting time to establishment, we performed linear mixed‐effects regression models for the full transition zone and three subregions within the zone. Seasonal temperatures were found to be the primary drivers of local establishment rates. Winter temperatures had the strongest effects, especially in the northern parts of the transition zone. Furthermore, the effects of some factors on waiting times to establishment varied across subregions. Our findings contribute to identifying especially vulnerable areas to further L. dispar spread and informing region‐specific criteria by invasion managers for the prioritization of areas for treatment.

Forecasting the spread of an invasive forest‐defoliating insect

“…Given the wide range of variables that have been mechanistically or statistically related to population dynamics and spread of L. dispar (Bigsby et al, 2011;Epanchin-Niell et al, 2022;Nunez-Mir et al, 2022), we were surprised that our simplest model, which used a coarse representation of habitat suitability and a computationally sophisticated but highly generalized depiction of local-scale dispersal, performed at least as well as more complex models. In models that predict potential distributions of invasive species, there is increasing recognition that increasing complexity does not always translate into an increase in model performance (Gallien et al, 2010).…”

“…On the other hand, accidental transportation of life stages by humans can span much longer distances, for example, when egg masses are laid on firewood, vehicles, or household items (Bigsby et al., 2011). Across the invasion front, spatial and temporal variation in the rate of spread depends on temperature (Nunez‐Mir et al., 2022; Sharov et al., 1999; Walter, Meixler, et al., 2015), landscape structure (Nunez‐Mir et al., 2022; Walter et al., 2016), and the dynamics of established populations (Johnson et al., 2006; Walter, Johnson, et al., 2015). Specifically, the pulsed advance and retreat of the range boundary is associated with population outbreaks behind the invasion front, which likely yield an influx of immigrants to the leading edge of the invasion.…”

“…The combination of extensive knowledge of L. dispar ecology and unparalleled data on its distribution and abundance makes this species an ideal study system for developing and testing near‐term spread forecasting models. However, despite extensive prior research on the invasion process and factors regulating rates of L. dispar spread (Johnson et al., 2006; Liebhold et al., 1992; Nunez‐Mir et al., 2022), a large majority of these studies have focused on explanation of historical invasion dynamics, as opposed to prediction, and we are unaware of other studies forecasting L. dispar range dynamics on year‐to‐year or similar temporal scales.…”

Advances in understanding and predicting the spread of invading insect populations

“…Species with high dispersal capabilities but reduced growth rates might be diluted in space and may not readily establish, while species with rapid growth but low dispersal capabilities might spread slowly. Furthermore, waiting times between arrival and establishment can be affected by environmental and anthropogenic variables [21]. Modeling each mechanism individually (dispersal and growth), and describing spread at an integrated level, furthers our understanding of the factors that affect the spread of invading species (Fig.…”

Drivers of invasion by laurel wilt of redbay and sassafras in the southeastern US

“…There is substantial variation in spread rates within and among invasions by woodboring insects, as spread of Agrilus planipennis (Coleoptera: Buprestidae) varied through time from 13.8 to 55.7 km/yr (Ward et al 2020 ) and spread of Sirex noctilio (Hymenoptera: Siricidae) varied among regions of the southern hemisphere from 11.7 to 78.0 km/yr (Lantschner et al 2014 ). Variation in rates of spread might be driven by differences in life history traits and/or habitat features (Lantschner et al 2014 ; Fahrner and Aukema 2018 ; Nunez‐Mir et al 2022 ), but the patterns and drivers of spread for invading ambrosia beetles—some of which cause severe economic and environmental damage by vectoring pathogenic fungi (Hulcr and Dunn 2011 ; Ranger et al 2015 ; Coleman et al 2019 ; Gugliuzzo et al 2021 ; Olatinwo et al 2021 )—are not well understood.…”