A tale of two forest types

Transcription

1 A tale of two forest types Benjamin Ramage 1, Alison Forrestel 1,2, Max Moritz 1, and Kevin O Hara 1 1 Dept. of Environmental Science, Policy, and Management UC Berkeley 2 Point Reyes National Seashore

2 The Basics of Sudden Oak Death Exotic pathogen of unknown origin (Phytophthora ramorum) Discovered in mid 90s in Santa Cruz and Marin Counties Sudden Oak Death = lethal trunk infection impacts several tree species native to California (e.g. some oaks, tanoak, madrone) Ramorum Blight = sub lethal foliar infection affects a huge number of species pathogen is likely to persist indefinitely 2

3 Distribution is very patchy in CA coast ranges The Basics of Sudden Oak Death Regional and local spread expected to continue (OakMapper web application; 2006) (Meentemeyer et al. 2004) 3

4 Tanoak (Notholithocarpus densiflorus syn. Lithocarpus densiflorus) Ecological Significance Prolific acorn production Extremely shade tolerant Very competitive in conifer forests Susceptibility Genetic Age/size classes Environmental tanoak could be heading towards (functional) extinction in CA s coastal conifer forests 4

5 5

6 Potential for Trophic Cascades 6

7 OBJECTIVES 1. Document and describe SOD disease progression in the redwood and Douglas fir forests of Point Reyes National Seashore 2. Determine which factors affect tanoak survival probabilities 3. Simulate tanoak mortality through 2025 (using three separate models) 4. Compare baseline conditions in redwood and Douglas fir forests 5. Integrate these findings to discuss differences in the likely overall impact of SOD in these two forest types 7

8 Figure 1. Plot Locations STUDY AREA Plots: 1/20 hectare circular (12.62 m radius), all in second growth redwood or Douglas fir forest 8

9 STUDY DESIGN GIS used to: stratify plots by forest type In field protocol used to: stratify plots by disease condition: Healthy (SOD symptoms scarce or non existent) Diseased (severely impacted) (using a variant of a randomized split plot design, which was made possible by the highly patchy local distribution of the disease) standardize tanoak basal area (to facilitate direct comparisons across forest types and disease conditions) H RP D 9

10 DATA COLLECTION & ANALYSIS FIELD MEASUREMENTS: (in 2007 and 2009) Location, DBH, and health status for all standing* trees > 3 cm DBH Cover classes of all vascular plant species (visual estimates) Tree regeneration tallies Fuel loading (with Brown s transects) * Recently fallen tanoaks were also recorded DATA ANALYSIS (for observational component): Generalized Linear Mixed Models each plot pair (Healthy and Diseased) was treated as a random effect error distribution varied with response variable model predictors were dependent upon the analysis (e.g. baseline comparison of forest types, effects of SOD) 10

11 RESULTS: Disease Progression RW: 3.2% DF: 10.1% RW: 8.2% DF: 26.2% RW: 4.8% DF: 22.3% RW: 7.1% DF: 73.6% 11

12 RESULTS: Disease Progression 12

13 RESULTS: Disease Progression 13

14

15

16 16

17 What factors are increasing disease severity? 1. Which variables are associated with mortality patches? (i.e. H vs. D in 2007) 2. Which variables are associated with higher observed mortality rates from 2007 to 2009? We tested (individually and in interactions with forest type): total stems, total BA, tanoak stems, tanoak BA mean tanoak DBH, mean DBH of all tree species California bay stems, California bay BA, richness of mature tree species slope, elevation, northness (variables that could have conceivably influenced disease development, but that were very unlikely to have been affected by SOD induced mortality) RESULTS: All non significant No pre existing plot level variables were related to disease severity However DBH, forest type, and 2007 plot level tanoak mortality were all significant predictors of mortality between 2007 and

18 Three different models, each of which represents a different hypothesis about disease progression slope p-value Simple Model Intercept Redwood Forest Type DBH (cm) <.0001 DBH^ Redwood*DBH Total Dead Model slope p-value Intercept Redwood Forest Type DBH (cm) <.0001 DBH^ Total Dead BA in 07 (m^2) Total Dead BA in 207^ Redwood*DBH slope p-value Recent Dead Model Intercept Redwood Forest Type DBH (cm) <.0001 DBH^ Recent Dead BA in 07 (m^2) Recent Dead BA in 07^ Redwood*DBH Recent Dead BA in 07*DBH

19 Simulation Methods Survival probabilities (fitted from 2007 to 2009) were used to project mortality forward in two year intervals to 2025 Three separate simulations one for each model / hypothesis One static simulation (simple model); two dynamic simulations (total dead and recent dead models) 500 runs for each simulation Some details Effects of dead tanoak basal area (total or recent) were constrained to the 90 th percentile of our original (2007) data (because our models suggested that saturation occurs at approximately this point) Random site effects (plot and block) were ignored when predicting future survival probabilities (although we accounted for the non independence of each tree when fitting models); as such, we assume that any differences in tree level survival probability between individual plots and blocks are transitory and do not reflect permanent characteristics And an important note: our projections assume that mortality rates between 2007 and 2009 were representative of longer term trends 19

20 35% 20% 40% 0% 20

21 20% 0% 20% 0% 21

22 35% 20% 40% 0% 22

23 20% 0% 5% 0% 20% 0% 5% 0% 23

24 Basal Area RW DF RESULTS Total, Tanoak, Conifer (RW or DF) Non-tanoak hardwood + California bay + Stem Counts Total, Tanoak Conifer ++ Non-tanoak hardwood + California bay + Regen (Individuals / Clumps) Total, Tanoak Conifer ++ Non-tanoak hardwood ++ California bay ++ Fuels 1-hr, 10-hr, 1000-hr, litter Duff + Litter and Duff + Total + Baseline differences between redwood and Douglas fir forests (comparison of healthy plots in 2007) 24

25 RW DF Cover Classes Shrub, Juv. Tree, Exotic Herb ++ Canopy ++ Richness Herb, Tree (Juv./Mature), Exotic Shrub ++ Total ( + ) Evenness Tree (Juv./Mature), Exotic, Total Herb + Shrub ( + ) Diversity Herb, Shrub, Juv. Tree, Exotic Mature Tree + Total + RESULTS Baseline differences between redwood and Douglas fir forests continued 25

26 Summary Mortality rate is much higher in Douglas fir forests for reasons that are not entirely clear: 1. greater stand level abundance of CA bay? 2. more conducive climatic conditions? 3. greater abundance of other hosts? 4. more susceptible tanoak genotypes? But Long term effects may be greater in redwood forests because: 1. pre SOD tanoak abundances were much higher in RW forest 2. there is less functional redundancy in RW forest IMPORTANT NOTE: these results do not necessarily apply to RW and DF forests outside of PRNS, But they do demonstrate that SOD induced tanoak mortality can occur very rapidly in some areas 26

27 Acknowledgements Point Reyes National Seashore (fieldwork funding and site access) Baker Bidwell Research Fellowship (funding of data analysis) Dave Rizzo and his students/staff [UC Davis] (for testing symptomatic samples and providing general guidance) And our many excellent field volunteers For more information, me at: