  Complex socio-environmental interdependencies drive biological invasions,
causing damages across large spatial scales. For widespread invasions,
targeting of management activities based on optimization approaches may fail
due to computational or data constraints. Here we evaluate an alternative
approach that embraces complexity by representing the invasion as a network and
using network structure to inform management locations. We compare optimal
versus network-guided invasive species management at a landscape-scale,
considering siting of boat decontamination stations targeting 1.6 million
boater movements among 9,182 lakes in Minnesota, USA. Studying performance for
58 counties, we find that when full information is known on invasion status and
boater movements, the best-performing network-guided metric achieves a median
and lower quartile performance of 100% of optimal. We also find that
performance remains relatively high using different network metrics or with
less information (median above 80% and lower quartile above 60% of optimal for
most metrics), but is more variable, particularly at the lower quartile.
Additionally, performance is generally stable across counties with varying lake
counts, suggesting viability for large-scale invasion management.
