A Management Strategy for Beech Bark Disease: Exploiting Native Resistance. Jennifer L. Koch, Mary E. Mason, Judy Loo, Dave W.

Transcription

1 A Management Strategy for Beech Bark Disease: Exploiting Native Resistance Jennifer L. Koch, Mary E. Mason, Judy Loo, Dave W. Carey

2 Beech Bark Disease: The Causal Complex Cryptococcus fagisuga: the beech scale insect. Sexual fruiting bodies, or perithecia Neonectria ditissima Neonectria faginata (photographs from David R. Houston and James T. O Brien FID Leaflet #75)

3 Beech Bark Disease: components and impacts Mortality rates of 50 % of mature beech (loss of millions of board feet of timber, canopy gaps, space for invasives?) Diseased trees susceptible to beech snap = hazard trees with costs associated with removal.

4 Beech Bark Disease: components and impacts Remaining trees are highly defective, little economic value Susceptible trees sprout into thickets Loss of beechnuts impact wildlife Prevents regeneration of other species or R beech trees Wildlife-provides food and habitat for over 40 species of birds and mammals (bear, hawk)

5 Still time to do something before BBD present across entire range of beech!

6 Beech Bark Disease-Resistant American Beech * Even in heavily infested areas, there are still American beech that remain free of scale. * It is estimated that between 1 and 5 percent of American beech trees are resistant. * Resistant trees are frequently found in clusters. Allegheny National Forest, PA Luddington State Park, MI

7 Germinating beech nuts Healthy Beech in mixed hardwoods stand Significant opportunities outside traditional tree improvement activities to influence genetic composition of residual stands during silvicultural operations.

8 Technique to artificially infest beech bark with the beech scale insect (Houston, DR, Res. Pap. NE-507) Eggs can then be collected easily and transferred to other trees to artificially "challenge" them. Foam pads provide a favorable environment for the scale. Repeated challenges of mature, scale-free beech failed to result in the establishment of a reproductive scale colony. Resistance was shown to be to the scale part of the causal complex. All parents used in crosses have been tested in this manner.

9 Using the Artificial Inoculation Technique to Screen Seedlings for Beech Scale Resistance Collect from an infested tree, or farming. Scale eggs are placed on foam and Beech scale egg-laden adults tied to the stems of & eggs. seedlings. Derived from D Houston 1982 Res. Paper NE-506) Eggs hatch & crawlers colonize susceptible trees.

10 Artificial Inoculation Technique: Date collected.adults (count on tree & foam), egg clusters (binary on tree, count on foam), juvy s (binary on tree, foam) First pads on in 2003, first data in 2004

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12 from Koch, Carey, Mason, and Nelson. Can J. For. Res 40: (2010).

13 Table 3. Model test of effects and family least-squares means for egg cluster number without adult count as a covariate. a. Type III tests of effects for scale egg cluster count. b. Family least-squares means and standard errors (SE) for egg cluster count. * means that share the same letter are not significantly different. Effect num df den. df F-vlaue p-value family <0.001 age <0.001 family*age from Koch, Carey, Mason, and Nelson. Can J. For. Res 40: (2010). Family Mean * SE Takes two R parents to produce an above average family 1510xOP a xOP a xOP a x ab x b MExOP b

14 Table 5. Repeatability estimates and standard error for each model. Trait model error dist. R SE Adult no covariate binomial Egg covariate = poisson adult Egg no covariate poisson Reasonable to support breeding as option. from Koch, Carey, Mason, and Nelson. Can J. For. Res 40: (2010).

15 Continued to improve the seedling screening method Screened additional families Screened parent grafts and seedling progeny in parallel

16 Total adult scale on tree and foam, one pad per tree, 2006 or 2009 test year. Some seedlings and some cultivars appear resistant to beech scale infestation. R

17 Overall proportion R is Fem/ma le DT (2) * NN02 DT05 DT02 NN07 DT (10) 0.0 (7) DT (12) DT04 Control 0.09 cross families Small numbers per family (11) TD (10) 0.4 (10) * * No pattern to suggest single gene action Shows need to screen larger family sizes 0.0 (12) 0.2 (10) Collaboration with Judy Loo, Canadian Forest Service, screen

18 Based on trees with 2 pads in 2009

19 Added more pads to trees 3-4 pads per seedling per year 5 pads per ramet, 3 ramets per genotype per year for grafts Often able to screen for just one year Screen IDa second n year mean if pads are SE(mea too variable n) (SE too high), or if tree too small to hold min. WV number of pads WV WV DN DN

20 Select putative R trees in field Graft to propagate for testing and replication Use confirmed R trees to establish Make crosses when grafts flower in the first (or regional later) years seed to produce orchards RxR families Test seedlings and use to refine understanding of genetics Use seedlings to develop deployment strategies for eventual seed orchard progeny

21 Cooperators and Partners select R trees Allegheny National Forest, PA

22 Cold Room Hot Callus Grafting Set-up Seedling grafts = 72 % success rate Mature scion = 60 % success rate Success varied by genotype & time of year Some genotypes had 90 % success rate

23 Containerized Greenhouse Seed Orchard flowers Developing burrs (2 seeds each)

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25 Selected parents from Michigan Ludington State Park, Upper Peninsula Pennsylvania Allegheny National Forest, Penn DNR lands West Virginia Monongahela National Forest Regional Seed orchards on Partner land Original target of 20 parents/orchard All screened after grafting to confirm R phenotype

26 New Families All confirmed resistant parents, screened in parallel Better family sizes, inc. 2 large reciprocal families Data collection finished July 2011, analysis soon!

27 Progeny test planting at Holden Arboretum

28 American Beech Genomics Project Collaborators: John Carlson Penn State University; Dave Neale UC Davis; Tom Kubisiak SRS USFS High Throughput Sequencing 150 million bases of sequence (Roche 454 platform) Six Resistant, Six Susceptible Trees Marker Development SNPs=1,536 (single nucleotide polymorphism) AACCTAA C TTGGATT G * AACTTAAC TTGAATTG SSR (N=96) (simple sequence repeat) AACCTAA C TTGGATT G AACCTAA C TTGGATT G Development of High Density Linkage Map Association Mapping

29 EACGxMCTG_264.1 EACGxMCTT_502 EACGxMCTT_503 EAAAxMCGT_208 EACGxMCTA_264 EACGxMCTR_503 EACAxMCTA_264 EAGGxMCTT_96.1 EAGGxMCTT_94 EAGGxMCTT_93 EACGxMCTR_502 EATCxMCCT_162 EACGxMCTR_132 EAAGxMCAG_246 EACGxMCTT_132.1 EACAxMCAG_117 EAAGxMCTT_132 EAATxMCTC_175 EATCxMCGG_211 EAACxMCTT_127 EACGxMCTG_226 EAACxMCGC_263 EAACxMCAC_316 EAAGxMCAG_245 EAATxMCTC_373 EAACxMCTT_102 EAGGxMCTT_237 EACCxMCCC_448 EAACxMCAT_320 EACAxMCTA_208.1 EACCxMCCC_179 EAATxMCTC_251 EAACxMCAC_104 EACAxMCTG_437 EACGxMCTC_99.2 EACAxMCTG_244 EAATxMCAG_140.1 EAAAxMCGT_178 EAACxMCTA_163.2 EAGAxMCGT_173 EAACxMCTA_256 EACAxMCTG_408 EAAAxMCGT_179 FS4-46_06 EATGxMCCA_91 EAACxMCAT_94 EAAAxMCGT_164 EACGxMCAT_203 EAAAxMCGT_172 EAACxMCTA_269 EAGAxMCGT_165 EAGAxMCGT_227 EAAAxMCGT_176 EAACxMCTA_254 EAAAxMCGT_166 EACAxMCTG_ EAACxMCAC_423 EAACxMCAC_422 EAACxMCAC_420 EATGxMCCA_139 EAGGxMCTA_148 EAACxMCTC_244 EAACxMCAT_185 EAAGxMCAT_130.1 EACGxMCTT_112 EAATxMCAG_268 EAGTxMCGA_247 EAACxMCTC_109 EATGxMCCG_260 EATGxMCCG_258 EACGxMCTT_125.2 EACCxMCCC_299 EACCxMCCC_301 EACCxMCCC_303 EACCxMCCC_305.1 EACCxMCCC_297 EAACxMCAT_80 EACAxMCAG_162 EACGxMCTA_96 EACAxMCTG_129 EAATxMCAG_127 EAAGxMCAT_215.2 EACAxMCTG_127 EACAxMCTG_128 EAACxMCTT_205 EAAGxMCTG_182 EACGxMCTA_463 EAAGxMCTA_379 EACGxMCTC_244 EAGGxMCTA_379 EAATxMCTC_182 EAACxMCAT_170 EAGGxMCGC_157 EACGxMCTT_134 EATAxMCCA_147 EATCxMCCT_256 EAGAxMCGT_183.2 EAACxMCTG_78 Linkage mapping and QTL s. comp_group_6b These markers predict the proper phenotype (R or S) between 82 and 86% of the time within this family useful for MAS of F2. M1_+b EAACxMCTT_126 **** K_10 m2p2 Dfg7 ** K_3.2 EAACxMCTA_270****K_8.8 u EggAvM1P1 AdAvM2P2 EATGxMCCA_140 - EAATxMCTC_237 - EAAGxMCTA_96 *******K_19 m1p1 EATCxMCGG_259- EAATxMCAG_86 ****** K_13.6Um1p2 EggAvM1P2 Ad&EggAvM1P1 AdAvM1P1 EggAvM1P2 94cM 75cM

30 10 Symptom-free trees 6 BBD diseased trees 8 Different stands 4 20 CM02d MS/MS sequencing to identify 11 spots are considered Robust Biomarker Candidates kDa 3 replicate gels of each Spot matching and quantification pi 250kDa 20 DT02

31 Current Lab Members: Jennifer Koch Dave Carey, Mary Mason, Mark Miller Charlotte Chan Judy Loo Bob Heyd Rich Mergener Tom Hall Dana Nelson Tom Kubisiak John Carlson Abdelai Barakat Dave Neale Acknowledgements Past Lab Members: Bill Sickinger, Jany Chan, Ian Chambers, Donna Wilburn, Ashley Papash Cooperators/Collaborators Holden Arboretum from. Canadian Forest Service Michigan Dept. of Natural Resources Michigan Dept. of Natural Resources Pennsylania Dept. of Cons. & Natural Resources Southern Institute of Forest Genetics form. Southern Institute of Forest Genetics Pennsylvania State University Pennsylvania State University UC Davis Funding for this work provided by the Special Technology Development Program, Forest Heath Protection, USDA FS; and the Evaluation Monitoring Program, Forest Health Protection, USDA FS