Abstract
Invasive species pose a significant threat to biodiversity and ecosystem stability worldwide, challenging resource managers to develop strategies that maximize effective control measures with limited resources. While understanding connectivity is foundational to managing and conserving populations, the same network dynamics that sustain native communities can be exploited to manage invasive species. Here, we combined biophysical larval dispersal modeling, network analysis, and population modeling to optimize lionfish control within a network of 17 offshore banks in Flower Garden Banks National Marine Sanctuary, a marine protected area extending over 400 km2 in the Gulf of Mexico. Dispersal simulations revealed seasonal shifts in circulation dynamics, with winter and spring favoring connectivity among banks within the sanctuary and summer and fall promoting long-distance dispersal outside of the sanctuary through enhanced loop-current eddy activity. By increasing lionfish removal efforts during months of naturally low larval connectivity within the sanctuary, we were able to shift the modeled lionfish population from growing to declining with minimal effort. Network analysis further characterized the structure of larval connectivity in the sanctuary, identifying banks where removals would have a greater impact on population persistence versus locations where removals would only be impactful locally. This study illustrates how linking oceanographic processes, network theory, and population modeling can guide efficient and scalable interventions for invasive species control.
Subjects
- Ecology
- Ocean sciences
Acknowledgements
Funding for this project was provided by NOAA’s National Ocean Service, National Centers for Coastal Ocean Science, Center for Sponsored Coastal Ocean Research Coastal Ocean Program NA21NOS4780151. We want to thank LSU Seascape Ecology Lab members (Gaby Carpenter and Hannah Craft) and FGBNMS staff for project support throughout this study. Computing resources were conducted using high performance computing resources provided by Louisiana State University (http://www.hpc.lsu.edu). ChatGPT 4.0 was used in drafting and editing of code used to analyze data in this manuscript.
Funding
Funding for this project was provided by NOAA’s National Ocean Service, National Centers for Coastal Ocean Science, Center for Sponsored Coastal Ocean Research Coastal Ocean Program NA21NOS4780151. We want to thank the staff at FGBNMS and Lionfish Invitational Inc for project support throughout this study. Computing resources were conducted using high performance computing resources provided by Louisiana State University (http://www.hpc.lsu.edu). ChatGPT 4.0 was used in drafting and editing of code used to analyze data in this manuscript.
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Marissa F. Nuttall was employed by Flower Garden Banks National Marine Sanctuary. All authors were financially supported by through a cooperative agreement with NOAA’s National Ocean Service, National Centers for Coastal Ocean Science, Center for Sponsored Coastal Ocean Research Coastal Ocean Program.
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Nuttall, M.F., Rooker, J.R., Dance, M.A. et al. Exploiting network connectivity to enhance management of invasive species: a case study on lionfish in a marine protected area.
Sci Rep (2026). https://doi.org/10.1038/s41598-026-64508-6
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DOI: https://doi.org/10.1038/s41598-026-64508-6
Keywords
- Biophysical modeling
- Larval connectivity
- Network-based management
- Invasive species management
Source: Ecology - nature.com
