Paul Barber

Corymbia calophylla (marri), an iconic keystone species in the northern jarrah forest of southwestern Australia, is suffering from a stem canker disease caused by an endemic fungus, Quambalaria coyrecup . It is unusual for an endemic pathogen to have such a detrimental effect on a co‐evolved host, unless host defence mechanisms have been compromised. This study investigated the role of Phytophthora cinnamomi root infection and water shortage in predisposing C. calophylla to this canker disease, and whether these two stresses work synergistically to intensify the effect of the canker pathogen on C. calophylla . The roots of two‐year‐old C. calophylla plants were inoculated with P. cinnamomi in pot infestation trials, and 8 weeks later in the stems with the canker pathogen Q. coyrecup . Half of the plants were exposed to a water shortage treatment for the duration of the trial. Biophysical variables related to plant responses to the treatments were measured at harvesting. Reflectance spectroscopy measurements with a portable high‐resolution spectroradiometer were also taken weekly. The normalised difference spectral index (NDSI) was calculated for every combination of reflectance values between 350 nm and 2500 nm for all time points, correlated with treatment effects, and displayed as heat maps. Fifty‐seven vegetation indices (VIs), using wavelengths from different regions in the electromagnetic spectrum, were also calculated from the spectral data. Neither P. cinnamomi nor the water shortage treatments exacerbated the effect of the canker pathogen on the plants. The canker treatment increased plant stem diameter and canker volume significantly ( p < 0.001). The NDSI heat maps indicated that wavelengths in the electromagnetic spectrum's visible and shortwave infrared portions displayed the strongest correlations with the P. cinnamomi and water shortage treatments. For the canker treatment, it was the shortwave infrared portion. Six of the VIs responded significantly to the water shortage treatment: Carter index 1 ( p < 0.001), renormalised difference vegetation index ( p < 0.001), normalised difference water index ( p = 0.012), normalised phaeophytinization index ( p < 0.001), photochemical reflectance index ( p < 0.001) and red‐green ratio index ( p = 0.018). The renormalised difference vegetation index was also sensitive to the canker treatment ( p < 0.001), and the Carter index 1 to the P. cinnamomi treatment ( p < 0.001). Reflectance spectroscopy was able to track biochemical changes in C. calophylla leaves due to inoculation with P. cinnamomi , Q. coyrecup, and the water shortage treatment. However, more work must be done to identify optimum wavelengths specific to C. calophylla and its responses to pathogens.

Seagrasses provide critical ecosystem services but cumulative human pressure on coastal environments has seen a global decline in their health and extent. Key processes of anthropogenic disturbance can operate at local spatio-temporal scales that are not captured by conventional satellite imaging. Seagrass management strategies to prevent longer-term loss and ensure successful restoration require effective methods for monitoring these fine-scale changes. Current seagrass monitoring methods involve resource-intensive fieldwork or recurrent image classification. This study presents an alternative method using iteratively reweighted multivariate alteration detection (IR-MAD), an unsupervised change detection technique originally developed for satellite images. We investigate the application of IR-MAD to image data acquired using an unoccupied aerial vehicle (UAV). UAV images were captured at a 14-week interval over two seagrass beds in Brisbane Water, NSW, Australia using a 10-band Micasense RedEdge-MX Dual camera system. To guide sensor selection, a further three band subsets representing simpler sensor configurations (6, 5 and 3 bands) were also analysed using eight categories of seagrass change. The ability of the IR-MAD method, and for the four different sensor configurations, to distinguish the categories of change were compared using the Jeffreys-Matusita (JM) distance measure of spectral separability. IR-MAD based on the full 10-band sensor images produced the highest separability values indicating that human disturbances (propeller scars and other seagrass damage) were distinguishable from all other change categories. IR-MAD results for the 6-band and 5-band sensors also distinguished key seagrass change features. The IR-MAD results for the simplest 3-band sensor (an RGB camera) detected change features, but change categories were not strongly separable from each other. Analysis of IR-MAD weights indicated that additional visible bands, including a coastal blue band and a second red band, improve change detection. IR-MAD is an effective method for seagrass monitoring, and this study demonstrates the potential for multispectral sensors with additional visible bands to improve seagrass change detection.

Urban and peri-urban trees in major cities provide a gateway for exotic pests and diseases (hereafter “pests”) to establish and spread into new countries. Consequently, they can be used as sentinels for early detection of exotic pests that could threaten commercial, environmental and amenity forests. Biosecurity surveillance for exotic forest pests relies on monitoring of host trees — or sentinel trees — around high-risk sites, such as airports and seaports. There are few publicly available spatial databases of urban street and park trees, so locating and mapping host trees is conducted via ground surveys. This is time-consuming and resource-intensive, and generally does not provide complete coverage. Advances in remote sensing technologies and machine learning provide an opportunity for semi-automation of tree species mapping to assist in biosecurity surveillance. In this study, we obtained high resolution (≥12 cm), 10-band, multispectral imagery using the ArborCam™ system mounted to a fixed-wing aircraft over Sydney, Australia. We mapped 630 Pinus trees and 439 Platanus trees on-foot, validating their exact location on the airborne imagery using an in-field mapping app. Using a machine learning, convolutional neural network workflow, we were able to classify the two target genera with a high level of accuracy in a complex urban landscape. Overall accuracy was 92.1% for Pinus and 95.2% for Platanus, precision (user’s accuracy) ranged from 61.3% to 77.6%, sensitivity (producer’s accuracy) ranged from 92.7% to 95.2%, and F1-score ranged from 74.6% to 84.4%. Our study validates the potential for using multispectral imagery and machine learning to increase efficiencies in tree biosecurity surveillance. We encourage biosecurity agencies to consider greater use of this technology.

Species in the genus Phytophthora cause significant economic losses in crops and damage to forests and natural ecosystems worldwide. Currently, phosphite is the most effective chemical for disease management, but excessive phosphite concentrations can result in phytotoxicity in plants and the development of tolerance by the pathogen. Two newly developed metal chelates and phosphite (alone and in combination) were tested for their in vitro and in planta efficacy against Phytophthora cinnamomi. In glasshouse trials, 0.25% and 0.5% of each chemical treatment (phosphite, Ca chelate, Zn chelate) and Ca chelate + phosphite were used as a foliar application on 3-month-old seedlings of Banksia grandis (experiment not repeated) and Eucalyptus marginata, prior to inoculation with P. cinnamomi. All noninoculated control plants remained healthy, while significant root damage and reduction of dry root weights were observed for inoculated untreated plants. Individually, phosphite and Ca chelate significantly reduced root lesion development of P. cinnamomi compared to the control, with Ca chelate attaining superior results to phosphite at the same concentration. In combination, Ca chelate + phosphite had the largest reduction in root lesion development in both plant species; however, this result has not yet been replicated but did reflect previous in vitro results. The Zn chelate applications were not effective. Ca chelate has the potential to be developed as a fungicide to control Phytophthora species.

Increased heat in urban environments, from the combined effects of climate change and land use/land cover change, is one of the most severe problems confronting cities and urban residents worldwide, and requires urgent resolution. While large urban green spaces such as parks and nature reserves are widely recognized for their benefits in mitigating urban heat islands (UHIs), the benefit of urban golf courses is less established. This is the first study to combine remote sensing of golf courses with Morphological Spatial Pattern Analysis (MSPA) of vegetation cover. Using ArborCamTM multispectral, high-resolution airborne imagery (0.3 × 0.3 m), this study develops an approach that assesses the role of golf courses in reducing urban land surface temperature (LST) relative to other urban land-uses in Perth, Australia, and identifies factors that influence cooling. The study revealed that urban golf courses had the second lowest LST (around 31 °C) after conservation land (30 °C), compared to industrial, residential, and main road land uses, which ranged from 35 to 37 °C. They thus have a strong capacity for summer urban heat mitigation. Within the golf courses, distance to water bodies and vegetation structure are important factors contributing to cooling effects. Green spaces comprising tall trees (>10 m) and large vegetation patches have strong effects in reducing LST. This suggests that increasing the proportion of large trees, and increasing vegetation connectivity within golf courses and with other local green spaces, can decrease urban LST, thus providing benefits for urban residents. Moreover, as golf courses are useful for biodiversity conservation, planning for new golf course development should embrace the retention of native vegetation and linkages to conservation corridors.

Seagrass ecosystems sequester carbon at disproportionately high rates compared to terrestrial ecosystems and represent a powerful potential contributor to climate change mitigation and adaptation projects. However, at a local scale, rich heterogeneity in seagrass ecosystems may lead to variability in carbon sequestration. Differences in carbon sequestration rates, both within and between seagrass meadows, are related to a wide range of interrelated biophysical and environmental variables that are difficult to measure holistically using traditional field surveys. Improved methods for producing robust, spatially explicit estimates of seagrass carbon storage across large areas would be highly valuable, but must capture complex biophysical heterogeneity and variability to be accurate and useful. Here, we review the current and emerging literature on biophysical processes which shape carbon storage in seagrass beds, alongside studies that map seagrass characteristics using satellite remote sensing data, to create a blueprint for the development of remote sensing-enabled proxies for seagrass carbon stock and sequestration. Applications of satellite remote sensing included measuring seagrass meadow extent, estimating above-ground biomass, mapping species composition, quantifying patchiness and patch connectivity, determining broader landscape environmental contexts, and characterising seagrass life cycles. All of these characteristics may contribute to variability in seagrass carbon storage. As such, remote sensing methods are uniquely placed to enable proxy-based estimates of seagrass carbon stock by capturing their biophysical characteristics, in addition to the spatiotemporal heterogeneity and variability of these characteristics. Though the outlined approach is complex, it is suitable for accurately and efficiently producing a full picture of seagrass carbon stock. This review has drawn links between the processes of seagrass carbon sequestration and the capabilities of remote sensing to detect and characterise these processes. These links will facilitate the development of remote sensing-enabled proxies and support spatially explicit estimates of carbon stock, ensuring climate change mitigation and adaptation projects involving seagrass are accounted for with increased accuracy and reliability.

Urban forests are important for ameliorating urban heat loads and the urban microclimate may have an impact on tree phenology. Understanding these interactions is important to urban planners to select suitable trees for the urban forest. For one year we tracked leaf cover, flowers and fruit of 22 tree species in Bang Kachao Peninsula and explored correlations between phenology and climatic factors. Tropical lowland trees, with exception of mangroves, had reduced leaf cover in the dry season. Mangroves flowered and fruited throughout the year as compared to 1-3 times a year for tropical lowland forests. Positive correlations were found between flowering of Diospyros decandra with temperature; flowering of Aglaia cucullata and Elaeocarpus hygrophilus with rainfall; and fruiting of Dillenia indica and Diospyros malabarica with rainfall and relative humidity. We intend to apply tree phenology results to urban forest restoration and to monitor any adaptation to climate change for future mitigation strategies in tropical urban forests in Thailand.

The health of Corymbia calophylla (marri), a keystone tree species in the native forests of southwest Western Australia, has been in decline for the past few decades. Phytophthora root disease and waterlogging have often been cited as contributing to this decline. Traditional methods (i.e., field surveys and sampling) of mapping Phytophthora root infection in the field are time-consuming and expensive; thus, the potential of reflectance spectroscopy to characterize marri response to Phytophthora and waterlogging stress was investigated. Twelve-month old marri plants were infected with either P. cinnamomi or P. multivora in two glasshouse trials and waterlogged for 24 h each fortnight. Spectral measurements with a portable high-resolution spectroradiometer were taken weekly. Plant biophysical measurements were taken at harvest time. Normalized difference spectral index (NDSI) was calculated for every combination of reflectance values between 400 and 2500 nm for all time points, correlated with the treatment effects and displayed as heat maps. Narrowband vegetation indices (VIs), utilizing different wavelengths of the electromagnetic spectrum, were also calculated from the spectral data. The Phytophthora treatments did not cause significant differences with the biophysical measurements in both trials. In the second trial, the waterlogging treatment significantly lowered plant top dry weight (P = 0.016) and diameter (P = 0.044). Reflectance values plotted against wavelength displayed differences between treatments as well as a seasonal trend. The NDSI heat maps indicated that the Phytophthora and waterlogging treatment effects were strongest correlated with bandwidths in the visible and near-infrared portions of the electromagnetic spectrum (538–558 nm and 701–709 nm). Six of the VIs (normalized difference nitrogen index 2, anthocyanin reflectance index 1, photochemical reflectance index, Carter index 1, Vogelman index 3 and water band index) were able to track the biochemical changes in the leaves over the 10 weeks, confirming the seasonal trend. The interaction effect between P. cinnamomi, waterlogging and elapsed time in the first trial was significant for water band index (P = 0.010). This study demonstrates that reflectance spectroscopy holds promise for characterizing marri response but more work needs to be done to identify the optimum wavelengths for identifying Phytophthora and waterlogging stress with marri.

Among the most economically relevant and environmentally devastating diseases globally are those caused by Phytophthora species. In Australia, production losses in agriculture and forestry results from several well-known cosmopolitan Phytophthora species and infestation of natural ecosystems by Phytophthora cinnamomi have caused irretrievable loss to biodiversity, especially in proteaceous dominated heathlands. For this review, all available records of Phytophthora in Australia were collated and curated, resulting in a database of 7869 records, of which 2957 have associated molecular data. Australian databases hold records for 99 species, of which 20 are undescribed. Eight species have no records linked to molecular data, and their presence in Australia is considered doubtful. The 99 species reside in 10 of the 12 clades recognised within the complete phylogeny of Phytophthora. The review includes discussion on each of these species? status and additional information provided for another 29 species of concern. The first species reported in Australia in 1900 was Phytophthora infestans. By 2000, 27 species were known, predominantly from agriculture. The significant increase in species reported in the subsequent 20 years has coincided with extensive surveys in natural ecosystems coupled with molecular taxonomy and the recognition of numerous new phylogenetically distinct but morphologically similar species. Routine and targeted surveys within Australian natural ecosystems have resulted in the description of 27 species since 2009. Due to the new species descriptions over the last 20 years, many older records have been reclassified based on molecular identification. The distribution of records is skewed toward regions with considerable activity in high productivity agriculture, horticulture and forestry, and native vegetation at risk from P. cinnamomi. Native and exotic hosts of different Phytophthora species are found throughout the phylogeny; however, species from clades 1, 7 and 8 are more likely to be associated with exotic hosts. One of the most difficult challenges to overcome when establishing a pest status is a lack of reliable data on the current state of a species in any given country or location. The database compiled here for Australia and the information provided for each species overcomes this challenge. This review will aid federal and state governments in risk assessments and trade negotiations by providing a comprehensive resource on the current status of Phytophthora species in Australia.

Among the most economically relevant and environmentally devastating diseases globally are those caused by Phytophthora species. In Australia, production losses in agriculture and forestry results from several well-known cosmopolitan Phytophthora species and infestation of natural ecosystems by Phytophthora cinnamomi have caused irretrievable loss to biodiversity, especially in proteaceous dominated heathlands. For this review, all available records of Phytophthora in Australia were collated and curated, resulting in a database of 7869 records, of which 2957 have associated molecular data. Australian databases hold records for 99 species, of which 20 are undescribed. Eight species have no records linked to molecular data, and their presence in Australia is considered doubtful. The 99 species reside in 10 of the 12 clades recognised within the complete phylogeny of Phytophthora. The review includes discussion on each of these species? status and additional information provided for another 29 species of concern. The first species reported in Australia in 1900 was Phytophthora infestans. By 2000, 27 species were known, predominantly from agriculture. The significant increase in species reported in the subsequent 20 years has coincided with extensive surveys in natural ecosystems coupled with molecular taxonomy and the recognition of numerous new phylogenetically distinct but morphologically similar species. Routine and targeted surveys within Australian natural ecosystems have resulted in the description of 27 species since 2009. Due to the new species descriptions over the last 20 years, many older records have been reclassified based on molecular identification. The distribution of records is skewed toward regions with considerable activity in high productivity agriculture, horticulture and forestry, and native vegetation at risk from P. cinnamomi. Native and exotic hosts of different Phytophthora species are found throughout the phylogeny; however, species from clades 1, 7 and 8 are more likely to be associated with exotic hosts. One of the most difficult challenges to overcome when establishing a pest status is a lack of reliable data on the current state of a species in any given country or location. The database compiled here for Australia and the information provided for each species overcomes this challenge. This review will aid federal and state governments in risk assessments and trade negotiations by providing a comprehensive resource on the current status of Phytophthora species in Australia.