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The invasive rust Austropuccina psidii was detected in the Hawaiian Islands in 2005 and has become widely established throughout the archipelago in both native and introduced species of Myrtaceae. Initial predictions about the impacts of the fungus on native ʽōhiʽa lehua (Metrosideros polymorpha), a keystone native tree, have not materialized, but there is ongoing concern that introductions of new genotypes of the fungus could lead to widespread mortality with catastrophic effects on native ecosystems. By contrast, two recently emergent Ascomycete pathogens, Ceratocystis lukuohia (Ceratocystis wilt of 'ōhi'a) and C. huliohia (Ceratocystis canker of 'ōhi'a), collectively known to cause Rapid ʽŌhiʽa Death (ROD), are causing significant mortality in native forests on Hawaiʻi and Kauaʻi Islands, but pathways of spread are still incompletely understood. We used a network of passive environmental samplers for collecting windblown urediniospores of Austropuccina to evaluate the effectiveness of environmental monitoring to detect seasonal and landscape-scale differences in airborne propagules of this rust on Hawai'i Island. The samplers were also used to determine if windborn ambrosia beetle frass or spores of Ceratocystis can spread long distances. We found frequent detections and regional and seasonal differences in numbers of samplers that were positive for urediniospores of Austropuccinia, but little evidence of long-distance airborne dispersal of the ROD-causing fungi. The simple, inexpensive platform for sampling airborne fungal spores that we used may have value as a monitoring tool for detecting spread of airborne fungal pathogens, evaluating habitats for suitability for restoration efforts, and for detecting new pathogen introductions, particularly new Austropuccinia genotypes both in Hawaiʻi and other parts of the world. [ABSTRACT FROM AUTHOR]

Diagnostic testing to detect forest pathogens requires the collection of physical samples from affected trees, which can be challenging in remote or rugged environments. As an alternative to traditional ground-based sampling at breast height by field crews, we examined the feasibility of aerially sampling and testing material collected from upper canopy branches using a small unoccupied aerial system (sUAS). The pathogen of interest in this study is Ceratocystis lukuohia, the fungal pathogen responsible for Ceratocystis wilt of ‘ōhi‘a, a vascular wilt disease which has caused widespread mortality to ‘ōhi‘a in native forests across the state of Hawai‘i. To characterize the minimum branch diameter needed to successfully detect the pathogen of interest in infected trees, we tested 63 branch samples (0.8–9.6 cm in diameter) collected from felled trees inoculated with C.lukuohia on Hawai‘i Island. Subsequently, we aerially sampled branches from ten symptomatic ‘ōhi‘a (Metrosideros polymorpha) trees using two different branch sampling systems, the Flying Tree Top Sampler from ETH Zurich and the new Kūkūau branch sampler system introduced in this work, producing 29 branch samples with a maximum diameter of 4.2 cm and length of >2 m. We successfully detected the target fungal pathogen from the collected branches and found that branch diameter, leaf presence and condition, as well as wood moisture content are important factors in pathogen detection in sampled branches. None of the smallest branch samples (those C.lukuohia, while 77% of the largest diameter branch samples (5–10 cm) produced positive results. The Kūkūau branch sampler system is capable of retrieving branches up to 7 cm diameter, providing important capacity for pathogenic research requiring larger diameter samples for successful diagnostic testing. Inconclusive and/or non-detection laboratory results were obtained from sample materials that were either too desiccated or from a branch with asymptomatic leaves, suggesting there is an optimal temporal window for sampling.

• Ceratocystis lukuohia is responsible for widespread mortality of 'ōhi'a on Hawai'i. • We projected the potential distribution of C. lukuohia across the Hawaiian Islands. • 63% of endangered plants have >50% of their range in areas suitable for C. lukuohia. • Protecting habitat by fencing reduces incidences of C. lukuohia. • A dynamic web portal hosts updated results online at http://hawaiirodresearch.org/. Hawai'i's most widespread native tree, 'ōhi'a lehua (Metrosideros polymorpha), has been dying across large areas of Hawai'i Island mainly due to two fungal pathogens (Ceratocystis lukuohia and Ceratocystis huliohia) that cause a disease collectively known as Rapid 'Ōhi'a Death (ROD). Here we examine patterns of positive detections of C. lukuohia as it has been linked to the larger mortality events across Hawai'i Island. Our analysis compares the environmental range of C. lukuohia and its spread over time through the known climatic range and distribution of 'ōhi'a. Analyses show this fungal pathogen generally encompassed the core, but not the extremes of the climatic range of 'ōhi'a. We further modeled the potential distribution of C. lukuohia across the Hawaiian Archipelago to estimate the risk of ROD to other islands. Given the potential for C. lukuohia to alter the structure of 'ōhi'a dominated forests, we used our projected potential distribution of C. lukuohia to assess the risk of ROD to threatened and endangered plant species across Hawai'i. Many native plants are likely vulnerable to these types of large 'ōhi'a mortality events: of 234 endangered native plant species considered, 147 (62.8%) have more than half of their range within current and expanding C. lukuohia suitable areas. We also found evidence that protecting habitat by fencing out introduced feral ungulates reduces the prevalence of the disease likely by reducing physical damage caused by these animals to 'ōhi'a trees, a precondition for Ceratocystis infection. Given the ongoing spread of C. lukuohia , we developed a dynamic web portal to host our results online, where models and analyses are updated with new lab-confirmed detections to provide managers with a useful tool to help monitor and assess the risk of C. lukuohia as it continues to spread. [ABSTRACT FROM AUTHOR]

The early detection of plant pathogens at the landscape scale holds great promise for better managing forest ecosystem threats. In Hawai‘i, two recently described fungal species are responsible for increasingly widespread mortality in ‘ōhi‘a Metrosideros polymorpha, a foundational tree species in Hawaiian native forests. In this study, we share work from repeat laboratory and field measurements to determine if visible near-infrared and optical remote sensing can detect pre-symptomatic trees infected with these pathogens. After generating a dense time series of laboratory spectral reflectance data and red green blue (RGB) images for inoculated ‘ōhi‘a seedlings, seedlings subjected to extreme drought, and control plants, we found few obvious spectral indicators that could be used for reliable pre-symptomatic detection in the inoculated seedlings, which quickly experienced complete and total wilting following stress onset. In the field, we found similar results when we collected repeat multispectral and RGB imagery over inoculated mature trees (sudden onset of symptoms with little advance warning). We found selected vegetation indices to be reliable indicators for detecting non-specific stress in ‘ōhi‘a trees, but never providing more than five days prior warning relative to visual detection in the laboratory trials. Finally, we generated a sequence of linear support vector machine classification models from the laboratory data at time steps ranging from pre-treatment to late-stage stress. Overall classification accuracies increased with stress stage maturity, but poor model performance prior to stress onset and the sudden onset of symptoms in infected trees suggest that early detection of rapid ‘ōhi‘a death over timescales helpful for land managers remains a challenge.

Effective forest management, particularly during forest disturbance events, requires timely and accurate monitoring information at appropriate spatial scales. In Hawai'i, widespread 'ōhi'a (Metrosideros polymorpha Gaud.) mortality associated with introduced fungal pathogens affects forest stands across the archipelago, further impacting native ecosystems already under threat from invasive species. Here, we share results from an integrated monitoring program based on high resolution (<5 cm) aerial imagery, field sampling, and confirmatory laboratory testing to detect and monitor 'ōhi'a mortality at the individual tree level across four representative sites on Hawai'i island. We developed a custom imaging system for helicopter operations to map thousands of hectares (ha) per flight, a more useful scale than the ten to hundreds of ha typically covered using small, unoccupied aerial systems. Based on collected imagery, we developed a rating system of canopy condition to identify 'ōhi'a trees suspected of infection by the fungal pathogens responsible for rapid 'ōhi'a death (ROD); we used this system to quickly generate and share suspect tree candidate locations with partner agencies to rapidly detect new mortality outbreaks and prioritize field sampling efforts. In three of the four sites, 98% of laboratory samples collected from suspect trees assigned a high confidence rating (n = 50) and 89% of those assigned a medium confidence rating (n = 117) returned positive detections for the fungal pathogens responsible for ROD. The fourth site, which has a history of unexplained 'ōhi'a mortality, exhibited much lower positive detection rates: only 6% of sampled trees assigned a high confidence rating (n = 16) and 0% of the sampled suspect trees assigned a medium confidence rating (n = 20) were found to be positive for the pathogen. The disparity in positive detection rates across study sites illustrates challenges to definitively determine the cause of 'ōhi'a mortality from aerial imagery alone. Spatial patterns of ROD-associated 'ōhi'a mortality were strongly affected by ungulate presence or absence as measured by the density of suspected ROD trees in fenced (i.e., ungulate-free) and unfenced (i.e., ungulate present) areas. Suspected ROD tree densities in neighboring areas containing ungulates were two to 69 times greater than those found in ungulate-free zones. In one study site, a fence line breach occurred during the study period, and feral ungulates entered an area that was previously ungulate-free. Following the breach, suspect ROD tree densities in this area rose from 0.02 to 2.78 suspect trees/ha, highlighting the need for ungulate control to protect 'ōhi'a stands from Ceratocystis-induced mortality and repeat monitoring to detect forest changes and resource threats. [ABSTRACT FROM AUTHOR]

The early detection of plant pathogens at the landscape scale holds great promise for better managing forest ecosystem threats. In Hawai'i, two recently described fungal species are responsible for increasingly widespread mortality in 'ōhi'a Metrosideros polymorpha, a foundational tree species in Hawaiian native forests. In this study, we share work from repeat laboratory and field measurements to determine if visible near-infrared and optical remote sensing can detect pre-symptomatic trees infected with these pathogens. After generating a dense time series of laboratory spectral reflectance data and red green blue (RGB) images for inoculated 'ōhi'a seedlings, seedlings subjected to extreme drought, and control plants, we found few obvious spectral indicators that could be used for reliable pre-symptomatic detection in the inoculated seedlings, which quickly experienced complete and total wilting following stress onset. In the field, we found similar results when we collected repeat multispectral and RGB imagery over inoculated mature trees (sudden onset of symptoms with little advance warning). We found selected vegetation indices to be reliable indicators for detecting non-specific stress in 'ōhi'a trees, but never providing more than five days prior warning relative to visual detection in the laboratory trials. Finally, we generated a sequence of linear support vector machine classification models from the laboratory data at time steps ranging from pre-treatment to late-stage stress. Overall classification accuracies increased with stress stage maturity, but poor model performance prior to stress onset and the sudden onset of symptoms in infected trees suggest that early detection of rapid 'ōhi'a death over timescales helpful for land managers remains a challenge. [ABSTRACT FROM AUTHOR]