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ABSTRACT AimThe global, human‐mediated dispersal of invasive insects is a major driver of ecosystem change, biodiversity loss, crop damage and other effects. Trade flows and invasive species propagule pressure are correlated, and their relationship is essential for predicting and managing future invasions. Invaders do not disperse exclusively from the species' native range. Instead, the bridgehead effect, where established, non‐native populations act as secondary sources of propagule, is recognised as a major driver of global invasion. The resulting pattern of global spread arises from a mixture of global interactions between invasive species, their vectors and, their invaded ranges, which has yet to be fully characterised. LocationGlobal. Time Period1997–2020. Major Taxa StudiedInsects. MethodsWe analysed 319,283 border interception records of 514 insect species from a broad range of taxa from four national‐level phytosanitary organisations. We classified interceptions as coming from species native range or from bridgehead countries and examined taxonomic autocorrelation of global movement patterns between species. ResultsWhile 65% of interceptions originated from bridgehead countries, highlighting the importance of the bridgehead effect across taxa, patterns among individual species were highly variable and taxonomically correlated. Forty per cent of species originated almost exclusively from their native range, 28% almost exclusively from their non‐native range and 32% from a mix of source locations. These patterns of global dispersal were geographically widespread, temporally consistent, and taxonomically correlated. ConclusionsDispersal exclusively from bridgeheads represents an unrecognised pattern of global insect movement; these patterns emphasise the importance of the bridgehead effect and suggest that bridgeheads provide unique local conditions that allow invaders to proliferate differently than in their native range. We connect these patterns of global dispersal to the conditions during the human driven global dispersal of insects and provide recommendations for modellers and policymakers wishing to control the spread of future invasions.
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Forecasting global spread of invasive pests and pathogens through international trade
Abstract Non‐native plant pests and pathogens threaten biodiversity, ecosystem function, food security, and economic livelihoods. As new invasive populations establish, often as an unintended consequence of international trade, they can become additional sources of introductions, accelerating global spread through bridgehead effects. While the study of non‐native pest spread has used computational models to provide insights into drivers and dynamics of biological invasions and inform management, efforts have focused on local or regional scales and are challenged by complex transmission networks arising from bridgehead population establishment. This paper presents a flexible spatiotemporal stochastic network model called PoPS (Pest or Pathogen Spread) Global that couples international trade networks with core drivers of biological invasions—climate suitability, host availability, and propagule pressure—quantified through open, globally available databases to forecast the spread of non‐native plant pests. The modular design of the framework makes it adaptable for various pests capable of dispersing via human‐mediated pathways, supports proactive responses to emerging pests when limited data are available, and enables forecasts at different spatial and temporal resolutions. We demonstrate the framework using a case study of the invasive planthopper spotted lanternfly (Lycorma delicatula). The model was calibrated with historical, known spotted lanternfly introductions to identify potential bridgehead populations that may contribute to global spread. This global view of phytosanitary pandemics provides crucial information for anticipating biological invasions, quantifying transport pathways risk levels, and allocating resources to safeguard plant health, agriculture, and natural resources.
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- Award ID(s):
- 2200038
- PAR ID:
- 10527139
- Publisher / Repository:
- Wiley
- Date Published:
- Journal Name:
- Ecosphere
- Volume:
- 14
- Issue:
- 12
- ISSN:
- 2150-8925
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Models that are both spatially and temporally dynamic are needed to forecast where and when non-native pests and pathogens are likely to spread, to provide advance information for natural resource managers. The potential US range of the invasive spotted lanternfly (SLF, Lycorma delicatula ) has been modeled, but until now, when it could reach the West Coast’s multi-billion-dollar fruit industry has been unknown. We used process-based modeling to forecast the spread of SLF assuming no treatments to control populations occur. We found that SLF has a low probability of first reaching the grape-producing counties of California by 2027 and a high probability by 2033. Our study demonstrates the importance of spatio-temporal modeling for predicting the spread of invasive species to serve as an early alert for growers and other decision makers to prepare for impending risks of SLF invasion. It also provides a baseline for comparing future control options.more » « less
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Abstract AimEstablishments of non‐native forest pests (insects and pathogens) continue to increase worldwide with growing numbers of introductions and changes in invasion pathways. Quantifying spatio‐temporal patterns in establishment locations and subsequent invasion dynamics can provide insight into the underlying mechanisms driving invasions and assist biosecurity agencies with prioritizing areas for proactive surveillance and management. LocationUnited States of America. Time period1794–2018. Major taxa studiedInsecta, plant pathogens. MethodsUsing locations of first discovery and county‐level occurrence data for 101 non‐native pests across the contiguous USA, we (a) quantified spatial patterns in discovery points and county‐level species richness with spatial point process models and spatial hotspot analyses, respectively, and (b) identified potential proxies for propagule pressure (e.g., human population density) associated with these observed patterns. ResultsDiscovery points were highly aggregated in space and located in areas with high densities of ports and roads. Although concentrated in the north‐eastern USA, discovery points also occurred farther west and became less aggregated as time progressed. Invasion hotspots were more common in the north‐east. Geographic patterns of discovery points and hotspots varied substantially among pest origins (i.e., global region of pests’ native ranges) and pest feeding guilds. Significant variation in invasion richness was attributed to the patterns of first discovery locations. Data and shapefiles comprising analyses are provided. Main conclusionsUse of spatial point pattern analyses provided a quantitative characterization of the central role of human activities in establishment of non‐native pests. Moreover, the decreased aggregation of discovery points through time suggests that invasion pathways to certain areas in the USA have either been created or intensified by human activities. Overall, our results suggest that spatio‐temporal variability in the intensity of invasion pathways has resulted in marked geographic patterns of establishment and contributed to current macroscale patterns of pest invasion in the USA.more » « less
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1002/ecs2.4740
