Kauri forests are threatened by kauri dieback disease, caused by the microscopic soil-borne pathogen Phytophthora agathidicida (PA). Despite it being more than 15 years since the pathogen was discovered on the New Zealand mainland, there is still a paucity of information on the distribution of symptomatic trees and/or of the pathogen itself, which makes it challenging to understand where the infection foci are and how fast the pathogen is spreading. The considerable cost of surveillance for PA, as well as the risks associated with people walking between infected and non-infected sites, necessitates careful prioritisation of sites to be selected for surveillance. This task requires an understanding of which part of the landscape and how much of it needs to be surveyed to effectively detect the pathogen if present. We use information on the distribution of kauri trees with visible stress symptoms in the canopy to develop a baseline relative risk map depicting areas where PA is most likely to be present for three kauri forests in Northland, New Zealand. The relative risk map provides a simple, yet effective management tool to target trees for surveillance, monitoring, and protection. Using this insight, we demonstrate the application of a proof of absence statistical model to determine the surveillance effort required to be confident that if no PA is found during surveillance in selected priority sites, the pathogen can confidently be considered absent from these areas. Results from these analyses showed that many samples are needed to achieve 95% confidence in pathogen absence, but this varied between forests and sectors of each forest. However, these analyses are valuable to guide field efforts as well as to ensure realistic expectations among practitioners. The methods described here are applicable to many other pathogens affecting plants of cultural and/or ecological importance worldwide.
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