Impact of weather variables and season on sporulation of <i>Phytophthora pluvialis</i> and <i>Phytophthora kernoviae</i>

Fraser, Stuart; Gómez-Gallego, Mireia; Gardner, J. F.; Bulman, L. S.; Denman, Sandra; Williams, N.

doi:10.1111/efp.12588

Cited by 11 publications

(32 citation statements)

References 34 publications

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“…In the latter, P. austrocedri was expected, but none were detected at this site. However, the detection of P. kernoviae close to a healthy Scots pine needs to be followed up, as recently, P. pluvialis and P. kernoviae have been associated with needle diseases of Pinus radiata in New Zealand [89], and this could be an emerging problem on pine.…”

Section: Discussionmentioning

confidence: 99%

Diversity of Phytophthora Species Detected in Disturbed and Undisturbed British Soils Using High-Throughput Sequencing Targeting ITS rRNA and COI mtDNA Regions

Landa

Arias-Giraldo

Henricot

et al. 2021

Forests

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Disease outbreaks caused by introduced Phytophthora species have been increasing in British forests and woodlands in recent years. A better knowledge of the Phytophthora communities already present in the UK is of great importance when developing management and mitigation strategies for these diseases. To do this, soils were sampled in “disturbed” sites, meaning sites frequently visited by the public, with recent and new plantings or soil disturbances versus more “natural” forest and woodland sites with little disturbance or management. Phytophthora diversity was assessed using high-throughput Illumina sequencing targeting the widely accepted barcoding Internal Transcribed Spacer 1 (ITS1) region of rRNA and comparing it with the mitochondrial cytochrome c oxidase I (COI) gene. Isolation of Phytophthora was run in parallel. Nothophytophthora spp. and Phytophthora spp. were detected in 79 and 41 of the 132 locations of the 14 studied sites when using ITS or COI, respectively. A total of 20 Phytophthora amplicon sequence variants (ASVs) were assigned to known Phytophthora species from eight clades (1a, 2, 2b, 3a, 5, 6b, 7a, 8b, 8c, 8d, 10a, and 10b) and 12 ASVs from six clades (1a, 2c, 3a, 3b, 6b, 7a, 8b, 8c, and 8d) when using ITS or COI, respectively. Only at two locations were the results in agreement for ITS, COI, and isolation. Additionally, 21 and 17 unknown Phytophthora phylotypes were detected using the ITS and COI, respectively. Several Phytophthora spp. within clades 7 and 8, including very important forest pathogens such as P. austrocedri and P. ramorum, were identified and found more frequently at “disturbed” sites. Additionally, eight ASVs identified as Nothophytophthora spp. were detected representing the first report of species within this new genus in Britain. Only three species not known to be present in Britain (P. castaneae, P. capsici, and P. fallax) were detected with the ITS primers and not with COI. To confirm the presence of these or any potential new Phytophthora species, sites should be re-sampled for confirmation. Additionally, there is a need to confirm if these species are a threat to British trees and try to establish any eradication measures required to mitigate Phytophthora spread in Britain.

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Section: Discussionmentioning

confidence: 99%

Diversity of Phytophthora Species Detected in Disturbed and Undisturbed British Soils Using High-Throughput Sequencing Targeting ITS rRNA and COI mtDNA Regions

Landa

Arias-Giraldo

Henricot

et al. 2021

Forests

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“…Peak abundance for both species was in late winter, approximately coincident with maximum disease expression nationally. Accordingly, probability of detection of inoculum was related to lower temperatures and periods of wet weather (Fraser et al 2020). Similarly, preliminary small-scale studies with potted grafted cuttings have revealed successful intermittent infection at least between July and October (mid-winter and mid-spring; Hood et al 2017).…”

Section: Introductionmentioning

confidence: 95%

“…In addition, field research has been conducted to determine the seasonal life cycles of both Phytophthora species. Between 2012 and 2014 spore traps consisting of freshly detached radiata pine fascicles floating on deionised or rainwater held in plastic containers were placed at fortnightly intervals beneath initially symptomatic radiata pine stands (Fraser et al 2020). In the laboratory, sections of the needle baits were plated onto selective isolation media to establish the presence and identity of trapped phytophthoras.…”

Section: Introductionmentioning

confidence: 99%

Infection periods of Phytophthora pluvialis and Phytophthora kernoviae in relation to weather variables and season in Pinus radiata forests in New Zealand

Hood¹,

Husheer²,

Gardner³

et al. 2022

NZJFS

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Background: Red needle cast caused by Phytophthora pluvialis Reeser, Sutton & E. Hansen, and less frequently P. kernoviae Brasier, Beales & S.A.Kirk, is an important foliar disease of Pinus radiata D.Don (radiata pine) in plantations throughout parts of New Zealand. Significant growth loss occurs following years when severe outbreaks occur. Aerial spraying with a copper-based fungicide has potential for disease control. Research is being carried out to optimise application timing, supported by complementary studies to understand RNC epidemiology. Methods: In order to determine the pathogen infection periods, a field trial was conducted over two years at two forests in the Central North Island of New Zealand. Batches of potted radiata pine seedlings were placed beneath diseased pine stands at fortnightly intervals, before returning them to an open nursery area for assessments of infection every two weeks (based on visual symptoms and qPCR) over a period of three months. A hybrid modelling approach was employed to establish relationships between the proportion of plants showing symptoms and weather conditions during the fortnight of exposure and previous fortnights. Gradient boosting machine learning analyses were used to identify the most important weather variables, followed by analysis of these by generalised mixed effects models, generalised least square models and ordinary least square models. Results: Development of RNC symptoms and detection of Phytophthora pluvialis and P. kernoviae on exchange seedlings was greatest for those exposed between April and September (Southern Hemisphere mid-autumn to early-spring). At this time, temperatures, solar radiation and evapotranspiration were lower, and rainfall and foliage wetness were plentiful. Modelling identified temperature and relative humidity several months before the date of exposure as the most important weather variables explaining infection. Conclusions: Because of autocorrelation, it was not possible to determine those variables that drive sporulation, dispersal, infection and symptom development. This will require more detailed exchange plant studies together with controlled environment inoculation experiments. Nevertheless, results of this and earlier work complement recent research indicating that it may be possible to manage RNC by fungicide applications made in late summer or autumn, early in the annual disease cycle.

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“…Yet another, “red needle cast,” has been associated mainly with Phytophthora pluvialis Reeser, Sutton & Hansen, and to a lesser extent with P . kernoviae (Fraser et al, 2020 ). Such weather, with temperatures allowing growth but with low insolation restricting photosynthesis, is likely to deplete the carbohydrate reserves that would help the host resist pathogens.…”

Section: Seasonal Phenologymentioning

confidence: 99%

Putative biotic drivers of plant phenology: With special reference to pathogens and deciduousness

Burdon

Bartlett

2022

Ecology and Evolution

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Plant phenology is not only manifested in the seasonal timing of vegetative and reproductive processes but also has ontogenetic aspects. The adaptive basis of seasonal phenology has been considered mainly in terms of climatic drivers. However, some biotic factors as likely evolutionary influences on plants’ phenology appear to have been under‐researched. Several specific cases of putative biotic factors driving plant phenology are outlined, involving both herbivores and pathogens. These illustrate the diversity of likely interactions rather than any systematic coverage or review. Emphasis is on woody perennials, in which phenology is often most multifaceted and complicated by the ontogenetic aspect. The complete seasonal leaf fall that characterizes deciduous plants may be a very important defense against some pathogens. Whether biotic influences drive acquisition or long‐term persistence of deciduousness is considered. In one case, of leaf rusts in poplars, countervailing influences of the rusts and climate suggest persistence. Often, however, biotic and environmental influences likely reinforce each other. The timing and duration of shoot flushing may in at least some cases contribute to defenses against herbivores, largely through brief periods of “predator satiation” when plant tissues have highest food value. Wide re‐examination of plant phenology, accommodating the roles of biotic factors and their interplays with environments as additional adaptive drivers, is advocated toward developing and applying hypotheses that are observationally or experimentally testable.

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Impact of weather variables and season on sporulation of Phytophthora pluvialis and Phytophthora kernoviae

Cited by 11 publications

References 34 publications

Diversity of Phytophthora Species Detected in Disturbed and Undisturbed British Soils Using High-Throughput Sequencing Targeting ITS rRNA and COI mtDNA Regions

Diversity of Phytophthora Species Detected in Disturbed and Undisturbed British Soils Using High-Throughput Sequencing Targeting ITS rRNA and COI mtDNA Regions

Infection periods of Phytophthora pluvialis and Phytophthora kernoviae in relation to weather variables and season in Pinus radiata forests in New Zealand

Putative biotic drivers of plant phenology: With special reference to pathogens and deciduousness

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