Search Results (5)

Studies of Phytophthora impact in forests generally focus on individual species without recognition that Phytophthora occur in multispecies communities. This study investigated community structure of Phytophthora species in the rhizosphere of Agathis australis (kauri) in Te Wao Nui o Tiriwa/Waitākere Ranges, New Zealand, in the context of kauri dieback disease expression. Soil sampling and tree monitoring were conducted on 767 randomly selected mature kauri trees. Phytophthora species were detected using both soil baiting and DNA metabarcoding of environmental DNA (eDNA). Four species were detected with soil baiting (P. agathidicida, P. cinnamomi, P. multivora, and P. pseudocryptogea/P. cryptogea) and an additional three species with metabarcoding (P. kernoviae, P. cactorum/P. aleatoria and an unknown clade 7 species). Phytophthora cinnamomi was the most abundant species and was distributed throughout the forest. Both P. multivora and P. agathidicida were limited to forest edges, suggesting more recent introductions. P. agathidicida presence was strongly correlated with declining canopy health, confirming its role as the main driver of kauri dieback. The limited distribution of P. agathidicida and infrequent detections (11.0% samples) suggests that that this species is spreading as an introduced invasive pathogen and provide hope that with strategic management (including track upgrades and closures, restricting access to uninfected areas, and continual monitoring) uninfected areas of the forest can be protected. The frequent detections of P. cinnamomi and P. multivora from symptomatic trees in the absence of P. agathidicida suggest more research is needed to understand their roles in kauri forest health. Full article

In Aotearoa/New Zealand, the soilborne pathogen Phytophthora agathidicida threatens the survival of the iconic kauri, and the ecosystem it supports. In 2011, a surveillance project to identify areas of kauri dieback caused by Phytophthora agathidicida within the Waitākere Ranges Regional Park (WRRP) highlighted the potential impact of the pathogen. A repeat of the surveillance in 2015/16 identified that approximately a quarter of the kauri area within the Regional Park was infected or possibly infected, an increase from previous surveys. The surveillance program mapped 344 distinct kauri areas and showed that 33.4% of the total kauri areas were affected or potentially affected by kauri dieback and over half (58.3%) of the substantial kauri areas (above 5 ha in size) were showing symptoms of kauri dieback. Proximity analysis showed 71% of kauri dieback zones to be within 50 m of the track network. Spatial analysis showed significantly higher proportions of disease presence along the track network compared to randomly generated theoretical track networks. Results suggest that human interaction is assisting the transfer of Phytophthora agathidicida within the area. The surveillance helped trigger the declaration of a cultural ban (rāhui) on recreational access. Te Kawerau ā Maki, the iwi of the area, placed a rāhui over the kauri forest eco-system of the Waitākere Forest (Te Wao Nui o Tiriwa) in December 2017. The purpose of the rāhui was to help prevent the anthropogenic spread of kauri dieback, to provide time for investment to be made into a degraded forest infrastructure and for research to be undertaken, and to help protect and support forest health (a concept encapsulated by the term mauri). Managing the spread and impact of the pathogen remains an urgent priority for this foundation species in the face of increasing pressures for recreational access. Complimentary quantitative and qualitative research programs into track utilization and ecologically sensitive design, collection of whakapapa seed from healthy and dying trees, and remedial phosphite treatments are part of the cross-cultural and community-enabled biosecurity initiatives to Kia Toitu He Kauri “Keep Kauri Standing”. Full article

New Zealand kauri trees are threatened by the kauri dieback disease (Phytophthora agathidicida (PA)). In this study, we investigate the use of pan-sharpened WorldView-2 (WV2) satellite and Light Detection and Ranging (LiDAR) data for detecting stress symptoms in the canopy of kauri trees. A total of 1089 reference crowns were located in the Waitakere Ranges west of Auckland and assessed by fieldwork and the interpretation of aerial images. Canopy stress symptoms were graded based on five basic stress levels and further refined for the first symptom stages. The crown polygons were manually edited on a LiDAR crown height model. Crowns with a mean diameter smaller than 4 m caused most outliers with the 1.8 m pixel size of the WV2 multispectral bands, especially at the more advanced stress levels of dying and dead trees. The exclusion of crowns with a diameter smaller than 4 m increased the correlation in an object-based random forest regression from 0.85 to 0.89 with only WV2 attributes (root mean squared error (RMSE) of 0.48, mean absolute error (MAE) of 0.34). Additional LiDAR attributes increased the correlation to 0.92 (RMSE of 0.43, MAE of 0.31). A red/near-infrared (NIR) normalised difference vegetation index (NDVI) and a ratio of the red and green bands were the most important indices for an assessment of the full range of stress symptoms. For detection of the first stress symptoms, an NDVI on the red-edge and green bands increased the performance. This study is the first to analyse the use of spaceborne images for monitoring canopy stress symptoms in native New Zealand kauri forest. The method presented shows promising results for a cost-efficient stress monitoring of kauri crowns over large areas. It will be tested in a full processing chain with automatic kauri identification and crown segmentation. Full article

The endemic New Zealand kauri trees (Agathis australis) are under threat by the deadly kauri dieback disease (Phytophthora agathidicida (PA)). This study aimed to identify spectral index combinations for characterising visible stress symptoms in the kauri canopy. The analysis is based on an aerial AISA hyperspectral image mosaic and 1258 reference crowns in three study sites in the Waitakere Ranges west of Auckland. A field-based assessment scheme for canopy stress symptoms (classes 1–5) was further optimised for use with RGB aerial images. A combination of four indices with six bands in the spectral range 450–1205 nm resulted in a correlation of 0.93 (mean absolute error 0.27, RMSE 0.48) for all crown sizes. Comparable results were achieved with five indices in the 450–970 nm region. A Random Forest (RF) regression gave the most accurate predictions while a M5P regression tree performed nearly as well and a linear regression resulted in slightly lower correlations. Normalised Difference Vegetation Indices (NDVI) in the near-infrared / red spectral range were the most important index combinations, followed by indices with bands in the near-infrared spectral range from 800 to 1205 nm. A test on different crown sizes revealed that stress symptoms in smaller crowns with denser foliage are best described in combination with pigment-sensitive indices that include bands in the green and blue spectral range. A stratified approach with individual models for pre-segmented low and high forest stands improved the overall performance. The regression models were also tested in a pixel-based analysis. A manual interpretation of the resulting raster map with stress symptom patterns observed in aerial imagery indicated a good match. With bandwidths of 10 nm and a maximum number of six bands, the selected index combinations can be used for large-area monitoring on an airborne multispectral sensor. This study establishes the base for a cost-efficient, objective monitoring method for stress symptoms in kauri canopies, suitable to cover large forest areas with an airborne multispectral sensor. Full article

The endemic New Zealand kauri trees (Agathis australis) are of major importance for the forests in the northern part of New Zealand. The mapping of kauri locations is required for the monitoring of the deadly kauri dieback disease (Phytophthora agathidicida (PTA)). In this study, we developed a method to identify kauri trees by optical remote sensing that can be applied in an area-wide campaign. Dead and dying trees were separated in one class and the remaining trees with no to medium stress symptoms were defined in the two classes “kauri” and “other”. The reference dataset covers a representative selection of 3165 precisely located crowns of kauri and 21 other canopy species in the Waitakere Ranges west of Auckland. The analysis is based on an airborne hyperspectral AISA Fenix image (437–2337 nm, 1 m² pixel resolution). The kauri spectra show characteristically steep reflectance and absorption features in the near-infrared (NIR) region with a distinct long descent at 1215 nm, which can be parameterised with a modified Normalised Water Index (mNDWI-Hyp). With a Jeffries–Matusita separability over 1.9, the kauri spectra can be well separated from 21 other canopy vegetation spectra. The Random Forest classifier performed slightly better than Support Vector Machine. A combination of the mNDWI-Hyp index with four additional spectral indices with three red to NIR bands resulted in an overall pixel-based accuracy (OA) of 91.7% for crowns larger 3 m diameter. While the user’s and producer’s accuracies for the class “kauri” with 94.6% and 94.8% are suitable for management purposes, the separation of “dead/dying trees” from “other” canopy vegetation poses the main challenge. The OA can be improved to 93.8% by combining “kauri” and “dead/dying” trees in one class, separate classifications for low and high forest stands and a binning to 10 nm bandwidths. Additional wavelengths and their respective indices only improved the OA up to 0.6%. The method developed in this study allows an accurate location of kauri trees for an area-wide mapping with a five-band multispectral sensor in a representative selection of forest ecosystems. Full article