2. Relationships Between Landscape Structure & Southern Pine Beetle Outbreaks in the Southern Appalachians John Waldron, David Cairns, Charles Lafon, Maria Tchakerian, Robert Coulson, and Kier Klepzig

3. Why the Southern Pine Beetle?

4. HAZARDS SCENIC/ECOLOGICAL DAMAGE ECONOMIC DAMAGE

5. Why the Southern Pine Beetle? -Timber losses alone exceed $2.5 billion. The economic, social, and ecological impact of the SPB is catastrophic across the Southern US. Recent damage caused by SPB exceeds all historical records. -Ca. 89 million acres of forest land in the South are at risk The existing knowledge base for the insect is inadequate to explain the causes for the epidemic or provide insight into how it can be managed.

6. Geographic Range of Southern Pine Beetle (Dendroctonus frontalis)

7. Southern Appalachians

8. Range of Table Mountain pine

9. LANDIS was developed, and continues to be developed, by David Mladenoff & a team of researchers from the University of Wisconsin, the University of Missouri, & the USDA Forest Service Modeling Approach LANDIS 4.0 ● Raster (cell) based ● cell sizes ranging from 100 m 2 - 250,000 m 2 ● operates decadally ● simulates succession individualistically ● includes disturbances by wind, fire, insect/disease and harvesting ● determines species presence/absence in terms of 10-yr age cohorts.

10. 1 7810911 3456 12 131415161718 2 18 Landtype Classes: Moisture & Elevation Gradient

11. Photo Credit: T. Waldrop Not Actual Size

12. Low Elevation Ridges & Peaks No Disturbance Fire Fire + SPBSPB

13. Percent Contagion at Year 500

14. Complexity of S. Appalachian Pine Ecosystems

15. R. Coulson Pattern Process

17. Objectives Determine the impacts of SPB on landscape structure Determine the relative impact of landscape structure on SPB outbreak characteristics and pine persistence

18. Models Biological Disturbances (Disease & Insect) 4 Main Elements 1) Site Resource Dominance (SRD)- Indicates quality of food resources on a given site (cell) 2) Site Resource Modifiers- Adjust SRD to reflect variation in in food resources by land type and disturbance 3) Neighborhood Resource Dominance- distance-weighted average of SRD in all sites within a user-specified neighborhood. Combined with SRD to calculate Site Vulnerability, which dictates severity of Outbreak. 4) Temporal Disturbance Function- Determines temporal behavior of Biological Agent (chronic, cyclic, random) LANDIS-BDA: Biological Disturbance Agent module

19. What does the BDA do? Cell-based probability of infestation. –Site conditions (species and age structure) –Neighborhood conditions –Regional outbreak status Severity of individual outbreaks –Site conditions (species and age structure)

20. Outbreak Severity Calculations Species Age Cohort Resource Value Site Resource Dominance Site Vulnerability Outbreak? Outbreak Severity Class 1, 2 or 3 End Mortality?

21. BDA Parameters Resource ValueDisturbance Severity Host Age SpeciesMinorSecondaryPrimaryResistantTolerantVulnerable Acer rubrumNA Carya glabraNA Nyssa sylvaticaNA Oxydendrum arboreumNA Pinus pungens 204050204050 Quercus albaNA Quercus rubraNA Quercus coccineaNA Quercus prinusNA Quercus velutinaNA Robina pseudoacaciaNA

22. Populating the Landscapes Even Age Distribution: All trees in year 0 are 10 years old Host Trees –Table Mountain Pine: (Pinus pungens) Non-host species –11 species –Randomly placed in non-host cells

23. Landscape Creation RULE (Gardner 1999) 512 x 512 cells Binary (host / non-host) landscapes Variability in two parameters –Proportion of landscape as host –Fractal dimension

24. Experimental Design Factors Proportion of landscape in pine –2 Levels (0.25, 0.4) Fractal dimension of landscape –6 Levels of h (0, 0.1, 0.2, 0.3, 0.4, 0.5) Replications 50 Replicate landscapes Total of 600 different Landscapes

25. h = 0h = 0.1 h = 0.3 h = 0.4 h = 0.5 h = 0.2 LANDSCAPE STRUCTURE

26. Representation of Landscape Structure h can only be used for landscape creation, not landscape description. We used the Clumpiness Index in Fragstats to represent patch aggregation.

27. LANDIS runs No fire, wind, or harvesting BDA active to simulate SPB outbreaks 150 year runs 1 7810911 3456 12 131415161718 2

28. Sample Simulation

29. Size and Timing of Outbreaks

30. Persistence of Pine p = 25 %p = 40 %

31. Infested Area vs. Aggregation p = 25%

32. Conclusions Pine cover on the landscapes declines regardless of landscape characteristics. The proportion of the landscape in pine is less important than the aggregation of the elements for the persistence of pine. Pine landscapes become more fragmented over time. Highly aggregated landscapes are more likely to have larger and more severe infestations than are less aggregated landscapes. The proportion of old pines on the landscape influences the form of the response of infestation area to aggregation.