Human-connected wild lands: How network analysis can inform invasive species management

Abstract

Wild landscapes are critical strongholds for biodiversity, yet even in the remotest parts of the globe, increasing human use and development are leading to an influx of biodiversity threats including invasive species. Natural resource management agencies, and those that rely on public lands, need a better understanding of the long-distance dispersal pathways in which invasive species are introduced to remote locations. Pathway information is essential for targeting prevention and early detection across vast landscapes, but it is often challenged by information gaps and high surveillance costs. Data-driven approaches centered around a participating public can help resource managers and biosecurity professionals to better prioritize prevention and early detection activities to minimize incipient and secondary invasions. This study employed surveys with resource users to integrate and analyze multiple human-mediated dispersal networks for aquatic invasive species (AIS) across Alaska's part of the North American Boreal Forest. Specifically, it applied network analysis to further inform management priorities that so far were only based on a single pathway and different metrics. Results underline the vulnerability of remote wild freshwater systems to the introduction of AIS and provide a waterbody-specific tool for prioritizing monitoring and inform pathway-specific interventions that were unavailable through past research. The study compares the prioritization of waterbodies under newly derived network topology metrics accounting for multiple generic pathways with the existing single- species and single-pathway prediction model. Advantages of a more comprehensive multi-pathway network topology are discussed in the context of various invasion stages, multiple invasive taxa, and resource constraint conservation management systems.