Early detection of an invading nonindigenous plant species (NIS) may be critical for efficient and effective management. Adaptive survey sampling methods may provide unbiased sampling for best estimates of distribution of rare and spatially clustered populations of plants in the early stages of invasion. However, there are few examples of these methods being used for nonnative plant surveys in which travelling distances away from an initial or source patch, or away from a road or trail, can be time consuming due to the topography and vegetation. Nor is there guidance as to which of the many adaptive methods would be most appropriate as a basis for invasive plant mapping and subsequent management. Here we used an empirical complete census of four invader species in early to middle stages of invasion in a management area to assess the effectiveness and efficiency of three nonadaptive methods, four adaptive cluster methods, and four adaptive web sampling methods that all originated from transects. The adaptive methods generally sampled more NIS-occupied cells and patches than standard transect approaches. Sampling along roads only was time-efficient and effective, but only for species with restricted distribution along the roads. When populations were more patchy and dispersed over the landscape the adaptive cluster starting at the road generally proved to be the most time-efficient and effective NIS detection method.

Many land managers are faced with trying to optimize management of invasive plant species based on budget constraints and lack of knowledge of the true potential of the species. Generally, “early detection rapid response” (EDRR) is the assumed best management strategy and tends to drive management regardless of the invasion stage or possible variation in the invasion potential of the population. We created a simulation model to evaluate the optimal management strategy to reduce the rate of invasion of nonindigenous plant species. The strategies were specifically chosen to assess the value of information from monitoring populations. We compared four management strategies and a no-management control over a 20-yr period in the context of a management area: (1) managing a fixed number of populations at random each year (EDRR random), (2) managing an equivalent number of populations along a road each year (EDRR road), (3) managing half of the fixed populations that were determined by monitoring to be sources of new populations (monitoring every year), and (4) managing an equivalent set of source populations only on even years, leaving the odd years for monitoring (monitoring every other year). EDRR random location without regard to population invasion potential, and monitoring every year targeting management on populations determined to be invasive (sources for new populations), were the most successful strategies for reducing the increase in total number of populations. The model simulations suggest that managers could dedicate 50% of their management time to monitoring without risk of accelerating invasions or reducing the impact of their weed management program.