Invaders at the doorstep: Using species distribution modeling to enhance invasive plant watch lists
Watch lists of invasive species that threaten a particular land management unit are useful tools because they can draw attention to invasive species at the very early stages of invasion when early detection and rapid response efforts are often most successful. However, watch lists typically rely on the subjective selection of invasive species by experts or on the use of spotty occurrence records. Further, incomplete records of invasive plant occurrences bias these watch lists towards the inclusion of invasive plant species that may already be present in a land management unit, because the occurrences have not been formally integrated into publicly accessible biodiversity databases. However, these problems may be overcome by an iterative approach that guides more complete detection and compilation of invasive plant species records within land management units. To address issues from unobserved or unrecorded occurrences, we combined predicted suitable habitat from species distribution models and aggregated invasive plant occurrence records to develop ranked watch lists of 146 priority invasive plant species on >4000 land management units from five different administrative types within the United States. Based on this analysis, we determined that on average 84% of priority invasive plants with suitable habitat within a given land management unit were as yet unobserved, and that 41% of those were ‘doorstep species’ – found within 50 miles of the unit boundary yet not detected within the unit. Two case studies, developed in collaboration with staff at U.S. Fish and Wildlife Service Refuges, showed that by combining both habitat suitability models and invasive plant occurrence records, we could identify additional problematic invasive plants that had been previously overlooked. Model-based watch lists of ‘doorstep species’ are useful tools because they can objectively alert land managers to threats from invasive plants with high likelihood of establishment.
Citation Information
Publication Year | 2023 |
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Title | Invaders at the doorstep: Using species distribution modeling to enhance invasive plant watch lists |
DOI | 10.1016/j.ecoinf.2023.101997 |
Authors | Catherine S. Jarnevich, Peder Engelstad, Jillian LaRoe, Brandon Hays, Terri Hogan, Jeremy Jirak, Ian Pearse, Janet S. Prevéy, Jennifer Sieraki, Annie Simpson, Jess Wenick, Nicholas Young, Helen Sofaer |
Publication Type | Article |
Publication Subtype | Journal Article |
Series Title | Ecological Informatics |
Index ID | 70240339 |
Record Source | USGS Publications Warehouse |
USGS Organization | Core Science Analytics and Synthesis; Fort Collins Science Center |