Potential risks of future herbicide-resistant weeds in New Zealand revealed through machine learning

New Zealand has fewer numbers of herbicide-resistant crop weeds than many other highly developed economies, yet these numbers are likely to increase in the future. A clear indication of the scale of this risk can be derived from the predictable structure in the global occurrence of herbicide-resistant weeds that results from similarities in agronomic and environmental conditions. Hierarchical cluster analysis was used to identify groups of countries with similar herbicide-resistant weed assemblages to New Zealand. A distinct cluster of 11 European countries with strong climatic and agronomic affinities to New Zealand was identified. The combined assemblage of herbicide-resistant weeds within this cluster consisted of 27 species and the potential risk of a species evolving herbicide resistance was calculated as its frequency among these European countries. Species with potential to become herbicide resistant in New Zealand included established crop weeds (e.g. Senecio vulgaris, Tripleurospermum inodorum) as well as species only encountered as contaminants of seed imports (e.g. Alopecurus myosuroides, Apera spica-venti). All eight species already known to be herbicide-resistant in New Zealand were found in the high-risk assemblage and this indicates that the analysis provided a realistic measure of future risk.

Automated summary

New Zealand currently has fewer herbicide-resistant crop weeds compared to other developed economies, but these numbers are expected to rise in the future due to similarities in agronomic and environmental conditions. A cluster analysis revealed a group of 11 European countries with similar herbicide-resistant weed assemblages, indicating a potential risk for New Zealand. The analysis identified 27 species of herbicide-resistant weeds within this cluster, including both established crop weeds and species found in seed imports. All eight known herbicide-resistant species in New Zealand were found in this high-risk cluster, confirming the accuracy of the analysis in assessing future risk.