  Invasive species harm biodiversity and ecosystem services, with global
economic costs of invasions exceeding $40 billion annually. Widespread
invasions are a particular challenge because they involve large spatial scales
with many interacting components. In these contexts, typical optimization-based
approaches to management may fail due to computational or data constraints.
Here we evaluate an alternative solution that leverages network science,
representing the invasion as occurring across a network of connected sites and
using network metrics to prioritize sites for intervention. Such heuristic
network-guided methods require less data and are less computationally intensive
than optimization methods, yet network-guided approaches have not been
bench-marked against optimal solutions for real-world invasive species
management problems. We provide the first comparison of the performance of
network-guided management relative to optimal solutions for invasive species,
examining the placement of watercraft inspection stations for preventing spread
of invasive zebra mussels through recreational boat movement within 58
Minnesota counties in the United States. To additionally test the promise of
network-based approaches in limited data contexts, we evaluate their
performance when using only partial data on network structure and invaded
status. Metric-based approaches can achieve a median of 100% of optimal
performance with full data. Even with partial data, 80% of optimal performance
is achievable. Finally, we show that performance of metric-guided management
improves for counties with denser and larger networks, suggesting this approach
is viable for large-scale invasions. Together, our results suggest network
metrics are a promising approach to guiding management actions for large-scale
invasions.
