First evidence of genetic-based tolerance to red needle cast caused by Phytophthora pluvialis in radiata pine
© Dungey et al.; licensee Springer. 2014
Received: 10 May 2014
Accepted: 10 November 2014
Published: 31 December 2014
Red needle cast (RNC) is a new needle disease of Pinus radiata D. Don (radiata pine) in New Zealand that is causing significant, but as-yet un-quantified, loss of growth and productivity. This foliar disease has recently been attributed to the infection of the needles by Phytophthora pluvialis Reeser, Sutton & E Hansen. Genetic improvement is seen as a possible solution to mitigate the effects of this needle disease on forest productivity.
To quantify the ability of genetics to provide a solution, RNC was assessed on a single clones-within-families genetics trial using two methods: the percentage needle cast that was attributable to red needle cast symptoms; and the percentage needle cast where the causal agent was not clearly identifiable. Both needle cast assessment methods were found to be heritable (ĥ 2 0.21-0.31).
Selecting for tolerance to RNC is likely to deliver healthier trees. More assessments across a number of sites and seasons are required to confirm this result.
Red needle cast (RNC) is a new needle disease caused by Phytophthora pluvialis Reeser, Sutton & E Hansen that causes defoliation of Pinus radiata D. Don (radiata pine) under conditions favourable to the development of the disease (Dick et al. ; Hansen et al. ; Hood et al. ; Reeser et al. ). The disease has become well established in certain areas of New Zealand and has the potential to cause production loss through needle shed and reduced growth. Infection appears to be limited to needles of infected trees, with no recoveries of Phytophthora pluvialis having been made from the roots, stems or branches (Dick et al. ). The risk of any transfer on logs appears to be negligible (Hood et al. ). Past experience with other needle diseases such as Dothistroma needle blight suggest that such diseases can be managed in the medium-to-long term with tree breeding and appropriate silviculture. This study aimed at giving an early indication of the potential to select for better tolerance to RNC.
Forest tree species that have shown some differential tolerance or susceptibility to infection by Phytophthora pathogens
Chamaecyparis lawsoniana (A. Murray) Parl.
P. lateralis (Tucker & Milbrath)
Hansen et al. 
P. cinnamomi Rands
Green et al. 
Sniezko et al. 
Bower et al. 
Pinus echinata Mill.
Eucalyptus marginata Donn ex Sm.
McComb et al. 
Stukely and Crane 
Stukely et al. 
Eucalyptus regnans F.Muell.
Harris et al. 
Gully gum/blackbutt peppermint
Eucalyptus smithii R.T.Baker
Pinus radiata D. Don.
Butcher et al. 
Abies fraseri (Pursh) Poi
P. cactorum (Lebert &. Cohn) Schröt.
Frampton et al. 
Abies balsamea var. phanerolepis (Fern.)
Abies nordmanniana (Steven) Spach
P. drechsleri Tucker
subsp. equitrojani (Asch. & Sint. Ex Boiss.)
Abies bornmuelleriana Mattf.
Coast live oak
Quercus agrifolia Née
P. ramorum Werres, de Cock & Man in't Veld
Dodd et al. 
This study aimed to provide the first estimates of heritabilities from a clones-within-families genetics trial in order to determine whether tree breeding would help to mitigate the long-term effects of red needle cast disease on radiata pine in New Zealand.
Materials and methods
Trial design and establishment
One clones-within-families genetics trial was assessed at Wharerata forest on the east coast of New Zealand’s North Island (38°55'11.43"S 177°50'42.99"E).
The trial design comprised 15 clones from each of 100 families, with up to 6 ramets per clone. The trial was an incomplete block design, with 4 replicates and 32 incomplete blocks per replicate (128 blocks). The trial was established to test a wide range of families across the New Zealand radiata pine breeding population (Dungey et al. ). Tolerance to Dothistroma needle blight or other needle diseases was not considered at selection.
Allocation of genotypes to incomplete blocks was undertaken using software package ALPHA + V.2.3 (CSIRO Australia and Biometrics & Statistics Scotland). Incomplete blocks were 24 m × 24 m (6 trees × 8 rows) and genotypes were planted randomly in a single-tree plot layout within incomplete blocks. Initial stocking was 833 stems per hectare, equating to tree spacing of 4 m × 3 m.
Cuttings were set in 2004 from stool-beds established from seed sown in 2002. Three controls were incorporated: GF14 seedlot 94/10; GF19 seedlot 03/652; and GF25 comprising an equal mix of seedlots 99/62, 99/378, 99/188, 97/67 and 99/318.
Sites were surveyed and pegged during September 2005. Plants were lifted between 14/9/05 to 16/9/05. Planting was carried out from 20/9/2005 to 22/9/2005.
The trial was inspected for infection by RNC when the trees were six years of age from planting, in September 2011.
One week after inspection, the trial was subsequently assessed for two traits relating to damage to the crown caused by red needle cast. These were:
RNC – the percentage of crown that was clearly affected by red needle cast and distinguishable from other needle diseases such as Dothistroma needle blight (Carson ) and Cyclaneusma needle cast (Beets ; Dungey et al. ). This assessment was, therefore, based on the needles that were alive at that time.
NC – the percentage of crown that was lost overall due to needle cast, where the cause (i.e. type of disease) was no longer discernible. This assessment, therefore, included dead needles.
It is important to note that this trial had not yet reached crown closure, so this did not affect the scores. The trial was not assessed for growth rate, and there were no previous growth data available.
where 0 is a null matrix, and G and R are (co)variance matrices for effects in u and e, respectively.
Fixed terms in vector b included the overall mean, mu, and a factor with two levels to account for the effects of control seedlots versus pedigreed (genetic) material. Random terms in vector u included additive and non-additive genetic effects of individual genotypes within the ‘genetic’ material, the effects of replicates and the effects of incomplete blocks within replicates. All the effects in u were assumed to be mutually independent. Missing values were also fitted as a fixed effect.
The error process in vector e was partitioned into spatially correlated (ξ) and uncorrelated (η) residuals. The spatially correlated error (ξ) was modelled using a first-order separable autoregressive process in the row and column directions, as suggested by Gilmour et al. () for agricultural trials, as well as by Costa e Silva et al. (), Dungey et al. () and Dutkowski et al. () for forest genetic trials.
Significant differences between the fit of models (spatial and non-spatial) were estimated using a two-tailed likelihood ratio test (LRT) by comparing twice the difference between the log likelihood of the two models against the chi-square distribution with two degrees of freedom.
Individual narrow-sense heritability (ĥ 2 ) was estimated as the additive genetic variance divided by the sum of the additive genetic variance and the error variance. The clonal repeatability (Ĥ 2 ) was estimated as the sum of the additive and non-additive genetic variance divided by the sum of the additive, non-additive and the error variance. Dominance variance () was estimated as the non-additive variance divided by the sum of the additive, non-additive and the error variance.
The percentage of genetic gain available was estimated as the difference between the average of the top selections (20 or 100) and the average of the population, divided by the average of the population, multiplied by 100. Gains for clonal deployment assumed direct deployment of selections and that juvenile material was available for this to occur. Gains based on open-pollination assumed equal representation of selections established in grafted clonal seed orchards and that pollen contributions were unknown (i.e. gains were multiplied by 0.5). All gains were estimated using predicted breeding values of individual traits (i.e. RNC or NC) using spatial analyses.
There was a high level of infection in the area and a high level of infection throughout the trial. However, there was some variation among the experimental blocks, with some blocks higher up the slope having higher infection levels than those further down the slope.
Basic statistics for percentage needle loss for red needle cast (RNC) and for needle cast (NC) estimated from individual trees at the clones-within-families trial
Variance components, heritability and breeding values
Variance component estimates, narrow sense heritability and clonal repeatability estimates for RNC and NC
Spatial residual variance (units)
Narrow-sense heritability ĥ 2
0.21 ± 0.04
0.31 ± 0.04
Clonal repeatability Ĥ 2
0.23 ± 0.02
0.59 ± 0.02
0.02 ± 0.03
0.41 ± 0.04
Spatial residual variance (units)
Narrow-sense heritability ĥ 2
0.24 ± 0.02
0.31 ± 0.04
Clonal repeatability Ĥ 2
0.24 ± 0.02
0.59 ± 0.02
0.00 ± 0.00
0.42 ± 0.04
The spatial model also increased the estimate of dominance (, Table 3) from a negligible range to a moderate one (0.31-0.41) with spatial partitioning of the residual variance. This was not what was expected, and may mean that clonal selection and deployment will deliver the best gains. Again, more evidence will be needed before embarking on such a strategy.
The spatial model was a significantly better fit to the data for both the traits, RNC and NC (P < 0.0001, LRT). Fitting a spatial component to the error variance, as we have done here, has been found to give better fitting models for many forestry trials and traits than when modelling only replicate and block effects (Dutkowski et al. , ; Dungey et al. ). Modelling spatial error variance has not been found to be useful for traits that do not have strong auto-correlated spatial structures, for example stem counts, form or branching in various species (Eucalyptus globulus Labill., Picea abies (L.) Karst., Picea mariana (Mill.) Britton, Pinus pinaster Aiton, Pinus radiata, Picea sitchensis (Bong.) Carrière) and cypress canker in Cupressus lusitanica (Dungey et al. ).
Breeding values were estimated for individual trees and their parents. From these breeding values, it was clear that there were no individual tree breeding values that had very little damage resulting from the disease. This was in contradiction to the fact that assessment did find trees with very little damage (minimum of 0%, Table 2), but is likely to be a direct result of the BLUP methodology shrinking predictions towards the mean, particularly where there are only a few individual trees in this category. Clear differences were, however, evident between the worst affected (~40% damage) and the least affected trees (~7% damage; data not shown).
The heritability estimated here for red needle cast was comparable with heritability estimates for other diseases on radiata pine. These include examples of Dothistroma needle blight in New Zealand (0.17-0.40; Carson ; and Wilcox  family-mean heritability of 0.32). Dothistroma needle blight heritabilities in Australia have ranged from non-significant to 0.69 (median 0.35); (Ivković et al. ). Cyclaneusma needle cast heritabilties (0.44-0.68; from Beets ()) were slightly higher than the RNC heritabilities estimated here although estimates of individual narrow-sense heritabilities vary considerably between trial sites and are most frequently between 0.1 and 0.4 (Dungey et al. ).
Repeatable heritability estimates rely not only on a robust genetic trial, but on a level of infection that ensures differentiation between tolerant or resistant and susceptible genotypes (Dungey et al. ). Differences between sites can be due to genotype x environment interaction, real differences in infection levels and different stages of infection. The moderate-to-high infection rates in the well-designed clones-in-families trial assessed here should provide a reasonably robust heritability estimate. Long term, however, infection trials to screen a large number of genotypes under controlled conditions will provide the most reliable method of repeating damage assessments.
Gains of up to 48% were estimated from the top 20 selections using breeding values for RNC, and 39% for the top 100 assuming clonal deployment. Gains for NC were not as large (20-25% for the top 100 or 20 selections), again assuming clonal deployment. Gains assuming clonal deployment with selections limited to only one clone per family gave 40.5% for RNC and 25% for NC for the top 20 selections, and 27% and 16% for the top 100 selections respectively. Gains from open-pollination within a clonal seed orchard were half those where direct deployment was possible from selected clones.
Even when obtaining planting stock from open-pollination in a clonal seed orchard, these gains appear to be very good when compared with predicted gains for Dothistroma needle cast in the Dothistroma Resistant breed in New Zealand (6-7%; H. S. Dungey unpublished data) and other estimates in Australia. Using selection criteria, Ivković et al. () predicted that damage caused by Dothistroma septosporum (Dorog.) M. Morelet may be reduced by up to 7.7% while Ades and Simpson () estimated that selecting the best 10% of radiata pine clones would reduce infection levels by 12%.
The figures obtained here for predicted gain are high compared with the estimates for needle loss from Dothistroma needle cast, outlined above. This result is encouraging, and implies that breeding will be a useful tool to mitigate future damage to New Zealand P. radiata forests.
Long-term tolerance to Phytophthora spp.
This paper represents only one component of the approach we are taking to mitigate the effects of red needle cast. We intend to select for tolerance within a broad-based genetic collection within the current New Zealand radiata pine breeding population (Nari Williams pers. comm.). We will also be investigating the diversity and genetics of the pathogen (personal communication R. McDougal 2014) and taking a systems-biology approach to identify tolerant germplasm. Multiple approaches will be used, including field and in vitro screening, screening for several Phytophthora species and across several tree species. Putative resistant and susceptible trees will be genotyped in an attempt to identify genes, gene families or alleles that confer broad-spectrum tolerance to these pathogens in the host. In this way we hope to reduce the possibility of any tolerance being overcome.
Tolerance to needle loss due to red needle cast is heritable (ĥ 2 0.21-0.31) and selection for this trait will result in improved tree health. These genetic parameters are the first estimated for this trait in New Zealand, from one site at one time. These results must, therefore, be treated with caution, as rank changes with more information across more sites may occur. Nevertheless, genetic gain estimates imply that significant progress can be made through selection, up to 48%. Breeding for tolerance to Phytophthora pluvialis, therefore, appears to be an appropriate response to mitigate the effects of the introduction of RNC in New Zealand forests.
Future plans for this research include confirming these results with further field assessments and through future RNC inoculations under more controlled environmental conditions.
Thanks to the New Zealand Forest industry for providing access to trials, Lindsay Bulman and Rebecca Ganley for providing guidance on the disease. Thanks to Forest Protection and Forest Genetics staff at Scion who all helped determine the assessment methodology, including Margaret Dick, Judy Gardner, Ian Hood, Toby Stovold, Kane Fleet and Mark Miller. Thanks to Beccy Ganley and Stuart Kennedy for reviewing an earlier draft of the manuscript. This research was funded by Scion and by the Radiata Pine Breeding Company.
- Ades PK, Simpson JA: Clonal selection for resistance to Dothistroma needle blight in Pinus radiata . New Forests 1990,4(1):27–35. 10.1007/BF00119588View ArticleGoogle Scholar
- Beets PN, Oliver GR, Kimberley MO: Genotypic variation in symptoms of upper mid-crown yellowing and Cyclaneusma minus in a Pinus radiata stand. New Zealand Journal of Forestry Science 1997,27(1):69–75.Google Scholar
- Bower, AD, Casavan, K, Frank, C, Goheen, D, Hansen, E, Marshall, K, Sniezko, R, & Sutton, W. (2000). Screening Port-Orford-cedar for resistance to Phytophthora lateralis: results from 7000+ trees using a branch lesion test. Paper presented at the IUFRO Working Party 7.02.09, Phytophthora Diseases of Forest Trees, Proceedings from the First International Meeting on Phytophthoras in Forest and Wildland Ecosystems , Forest Research Laboratory, Oregon State University, Corvallis, Oregon, August 30 – September 3, 1999 (pp. 99–100). Oregon: Oregon State University.Google Scholar
- Brasier, C. (2000). The role of Phytophthora pathogens in forests and semi-natural communities in Europe and Africa. Paper presented at the IUFRO Working Party 7.02.09, Phytophthora Diseases of Forest Trees, Proceedings from the First International Meeting on Phytophthoras in Forest and Wildland Ecosystems , Forest Research Laboratory, Oregon State University, Corvallis, Oregon, August 30 – September 3, 1999 (pp. 6–13). Oregon: Oregon State University.Google Scholar
- Butcher TB, Stukely MJC, Chester GW: Genetic variation in resistance of Pinus radiata to Phytophthora cinnamomi . Forest Ecology and Management 1984,8(3–4):197–220. 10.1016/0378-1127(84)90053-7View ArticleGoogle Scholar
- Carson SD: Selecting Pinus radiata for resistance to Dothistroma needle blight. New Zealand Journal of Forestry Science 1989, 19: 3–21.Google Scholar
- Costa e Silva J, Dutkowski GW, Gilmour AR: Analysis of early tree height in forest genetic trials is enhanced by including a spatially correlated residual. Canadian Journal of Forest Research 2001,31(11):1887–1893. 10.1139/x01-123View ArticleGoogle Scholar
- Dick MA, Dobbie K, Cooke DE, Brasier CM: Phytophthora captiosa sp. nov. and P. fallax sp. nov. causing crown dieback of Eucalyptus in New Zealand. Mycological Research 2006,110(4):393–404. 10.1016/j.mycres.2006.01.008View ArticlePubMedGoogle Scholar
- Dick, MA, Williams, NM, Hood, IA, Bader, M. (2014). Pathogenicity of Phytophthora pluvialis on Pinus radiata and its relation with red needle cast disease in New Zealand. New Zealand Journal of Forestry Science, 44, 6.Google Scholar
- Dodd, RS, Huberli, D, Douhovnikoff, V, Harnik, TY, Afzal-Rafii, Z, Garbelotto, M (2005). Is variation in susceptibility to Phytophthora ramorum correlated with population genetic structure in coast live oak (Quercus agrifolia)? New Phytologist, 165(1), 203–214. doi:10.1111/j.1469–8137.2004.01200.x.Google Scholar
- Dungey, HS, Low, CB, Bulman, LS (2006). Needle cast in New Zealand – are there opportunities for improvement in plantation growth? Paper presented at the Breeding for success: diversity in action. Proceedings of the 13th Australasian Plant Breeding Conference, Christchurch, New Zealand, 18–21 April 2006. [CDROM].Google Scholar
- Dungey HS, Brawner JT, Burger F, Carson M, Henson M, Jefferson P, Matheson AC: A new breeding strategy for Pinus radiata in New Zealand and New South Wales. Silvae Genetica 2009, 58: 28–38.Google Scholar
- Dungey HS, Russell JH, Costa e Silva J, Low CB, Miller MA, Fleet KR, Stovold GT: The effectiveness of cloning for the genetic improvement of Mexican white cypress Cupressus lusitanica (Mill.). Tree Genetics and Genomes 2012, 9: 443–453. 10.1007/s11295-012-0565-9View ArticleGoogle Scholar
- Durán, A, Gryzenhout, M, Slippers, B, Ahumada, R, Rotella, A, Flores, F, Wingfield, BD, Wingfield, MJ. (2008). Phytophthora pinifolia sp nov associated with a serious needle disease of Pinus radiata in Chile. Plant Pathology, 57(4), 715–727. doi:10.1111/j.1365–3059.2008.01893.xGoogle Scholar
- Dutkowski GW, Costa e Silva J, Gilmour AR, Lopez GA: Spatial analysis methods for forest genetic trials. Canadian Journal of Forest Research 2002,32(12):2201–2214. 10.1139/x02-111View ArticleGoogle Scholar
- Dutkowski GW, Costa e Silva J, Gilmour AR, Wellendorf H, Aguiar A: Spatial analysis enhances modelling of a wide variety of traits in forest genetic trials. Canadian Journal of Forest Research 2006,36(7):1851–1870. 10.1139/x06-059View ArticleGoogle Scholar
- Frampton J, Isik F, Benson DM: Genetic variation in resistance to Phytophthora cinnamomi in seedlings of two Turkish Abies species. Tree Genetics and Genomes 2013,9(1):53–63. 10.1007/s11295-012-0529-0View ArticleGoogle Scholar
- Gilmour AR, Cullis BR, Verbyla AP: Accounting for natural and extraneous variation in the analysis of field experiments. Journal of Agricultural, Biological, and Environmental Statistics 1997,2(3):269–293. 10.2307/1400446View ArticleGoogle Scholar
- Gilmour AR, Gogel BJ, Cullis BR, Welham SJ, Thompson R: ASReml User Guide Release 3.0. Hemel Hempstead, HP1 1ES. VSN International, UK; 2010.Google Scholar
- Green S, Brasier CM, Schlenzig A, McCracken A, Macaskill GA, Wilson M, Webber JF: The destructive invasive pathogen Phytophthora lateralis found on Chamaecyparis lawsoniana across the UK. Forest Pathology 2013,43(1):19–28.Google Scholar
- Hansen EM, Hamm PB, Roth LF: Testing Port-Orford-Cedar for resistamce to Phytophthora . Plant Disease 1989,73(10):791–794. 10.1094/PD-73-0791View ArticleGoogle Scholar
- Hansen EM, Reeser PW, Davidson JM, Garbelotto M, Ivors K, Douhan L, Rizzo DM: Phytophthora nemorosa , a new species causing cankers and leaf blight of forest trees in California and Oregon, USA. Mycotaxon 2003, 88: 129–138.Google Scholar
- Hansen EM, Reeser PW, Sutton W: Phytophthora beyond agriculture. Annual Review of Phytopathology 2012, 50: 359–378. 10.1146/annurev-phyto-081211-172946View ArticlePubMedGoogle Scholar
- Harris JA, Kassaby FY, Smith IW: Variations in mortality in families of Eucalyptus regnans caused by Phytophthora cinnamomi . Australian Forest Research 1985, 15: 57–65.Google Scholar
- Hood, IA., Williams, NM, Dick, MA, Arhipova, N, Kimberley, M, Gardner, J. (2014). Decline in vitality of propagules of Phytophthora ‘pluvialis’ and P. kernoviae and their inability to survive on and contaminate or colonise bark of Pinus radiata. New Zealand Journal of Forestry Science, 44, 7Google Scholar
- Hoover BK: Susceptibility of fraser, canaan, and nordmann fir to root rot incited by Phytophthora cactorum and Phytophthora drechsleri . HortTechnology 2013,23(1):44–50.Google Scholar
- Ivković M, Baltunis B, Gapare W, Sasse J, Dutkowski G, Elms S, Wu H: Breeding against Dothistroma needle blight of radiata pine in Australia. Canadian Journal of Forest Research 2010,40(8):1653–1660. 10.1139/X10-097View ArticleGoogle Scholar
- McComb, JA, Bennett, IJ, Cahill, DM (1991). Selection and propagation of jarrah resistant to Phytophthora cinnamomi. Rural Industries Research and Development report (pp. 73). Perth, Western Australia: Murdoch School of Biological and Environmental Sciences, Murdoch University.Google Scholar
- Reeser, P, Sutton, W, Hansen, E. (2013). Phytophthora pluvialis, a new species from mixed tanoak-Douglas-fir forests of western Oregon, U.S.A. North American Fungi, 8(7). Corvallis, OR, U.S.A.: Department of Botany and Plant Pathology, Oregon State University. http://www.treesearch.fs.fed.us/pubs/44667., Reeser, P, Sutton, W, Hansen, E. (2013). Phytophthora pluvialis, a new species from mixed tanoak-Douglas-fir forests of western Oregon, U.S.A. North American Fungi, 8(7). Corvallis, OR, U.S.A.: Department of Botany and Plant Pathology, Oregon State University. . http://www.treesearch.fs.fed.us/pubs/44667
- Sniezko, RA, Hansen, EM, Bower, A, Goheen, D, Marshall, K, Casavan, K, & Sutton, W. (2000). Genetic resistance of Port-Orford-cedar (Chamaecyparis lawsoniana) to Phytophthora lateralis: results from early field trials. Paper presented at the IUFRO Working Party 7.02.09, Phytophthora Diseases of Forest Trees, Proceedings from the First International Meeting on Phytophthoras in Forest and Wildland Ecosystems, Forest Research Laboratory, Oregon State University, Corvallis, Oregon, August 30 – September 3, 1999 (pp. 138–140). Oregon: Oregon State University.Google Scholar
- Stukely MJC, Crane CE: Genetically Based Resistance of Eucalyptus marginata to Phytophthora cinnamomi M. Phytopatholgy 1994,84(6):650–656. 10.1094/Phyto-84-650View ArticleGoogle Scholar
- Stukely, MJC, Crane, CE, McComb, JA, Bennett, IJ. (2007). Field survival and growth of clonal, micropropagated Eucalyptus marginata selected for resistance to Phytophthora cinnamomi. Forest Ecology and Management, 238(1–3), 330–334, doi:10.1016/j.foreco.2006.10.028.Google Scholar
- Werres S, Marwitz R, In't M, Veld WA, De Cock AWAM, Bonants PJM, De Weerdt M, Themann K, Ilieva E, Baayen RP: Phytophthora ramorum sp. nov., a new pathogen on Rhododendron and Viburnum . Mycological Research 2001,105(10):1155–1165(2001). 10.1016/S0953-7562(08)61986-3View ArticleGoogle Scholar
- Wilcox MD: Genetic variance and inheritance of resistance to Dothistroma needle blight in Pinus radiata . New Zealand Journal of Forestry Science 1982, 12: 14–35.Google Scholar
- Zentmyer, GA. (1980). Phytophthroa cinnamomi and the diseases it causes (Vol. 10, Amer. Phytopathol. Soc. Monogr). St. Paul, Minn: American Phytopathological Society.Google Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.