Predicting spread of invasive macrophytes in New Zealand lakes using indirect measures of human accessibility

1. Models predicting invasive macrophyte spread between lakes provide an important tool for focusing proactive management efforts to lakes deemed susceptible to invasion. However, challenges to forecasting macrophyte spread include wide physiological tolerances of invasive macrophytes and a lack of information on the relative importance of the various human vectors (e.g. boating traffic). In New Zealand, three invasive species that reproduce vegetatively, Ceratophyllum demersum, Lagarosiphon major, Egeria densa, and a single species that reproduces sexually, Utricularia gibba, are currently spreading across the lake landscape at a great cost to the local ecology and economy. 2. In this study, we first examined whether variables that indirectly describe weed spread via human access and use, as well as a lake’s position in the landscape, could describe the distribution of these four species using a boosted regression trees (BRT) modelling approach. Then, as these invasive species have not reached their full invasion potential, we examined how giving more influence to infected lakes at the edge of the invasion front, and including all lakes across New Zealand as background samples, simulating ‘absences beyond the invasion front’, influenced our ability to forecast the potential for new lakes to be invaded. 3. The BRT models identified that variables characterising human access and use, as well as lake position, were associated with the occurrence of the three vegetatively reproducing macrophytes. Weed occurrence was more likely when there was a highway in the vicinity, human population density was high and if the lake was large (c. 55 km²). But in the single case of U. gibba, temperature was the variable that best explained occurrence. This is consistent with the suggestion that U. gibba is predominantly dispersed by waterbirds, rather than human activity. 4. But for all four species, the BRT models based on the recorded observations alone predicted observed invasions with low prediction probabilities and did not forecast further spread. By contrast, when observations at the edge of the invasion front were upweighted, and additional background lakes implemented into the model, recorded observations were predicted and additional lakes were forecast to be at risk, suggesting that these models better captured the current and potential distribution of these macrophyte species. 5. The use of variables that characterise weed spread could provide similar insights into other systems where survey information on the nature, strength and direction of invasion vectors is lacking. Furthermore, when weighting the data, many lakes across New Zealand were forecasted to be at risk of invasion. The advantage of weighing the presence data was that insights into the potential for a species to spread were obtained. The probabilistic estimates of risk, as derived from the models, together with other information for prioritising lakes, can be used to focus surveillance and protection efforts.