1 / 31

John Waldron, David Cairns, Charles Lafon, Maria Tchakerian, Robert Coulson, and Kier Klepzig

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. Why the Southern Pine Beetle?. SCENIC/ECOLOGICAL DAMAGE. HAZARDS. ECONOMIC DAMAGE.

jaimin
Download Presentation

John Waldron, David Cairns, Charles Lafon, Maria Tchakerian, Robert Coulson, and Kier Klepzig

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. 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

  2. Why the Southern Pine Beetle?

  3. SCENIC/ECOLOGICAL DAMAGE HAZARDS ECONOMIC DAMAGE

  4. 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.

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

  6. Southern Appalachians

  7. Range of Table Mountain pine

  8. Modeling Approach LANDIS 4.0 ● Raster (cell) based ● cell sizes ranging from 100 m2- 250,000 m2 ● 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. 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

  9. 13 14 15 16 17 18 18 Landtype Classes: Moisture & Elevation Gradient 7 8 9 10 11 12 1 2 3 4 5 6

  10. Not Actual Size Photo Credit: T. Waldrop

  11. Low Elevation Ridges & Peaks Fire No Disturbance SPB Fire + SPB

  12. Percent Contagion at Year 500

  13. Complexity of S. Appalachian Pine Ecosystems

  14. Pattern Process R. Coulson

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

  16. LANDIS-BDA: Biological Disturbance Agent module 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)

  17. 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)

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

  19. BDA Parameters

  20. 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

  21. 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

  22. 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

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

  24. 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.

  25. LANDIS runs • No fire, wind, or harvesting • BDA active to simulate SPB outbreaks • 150 year runs 13 14 15 16 17 18 7 8 9 10 11 12 1 2 3 4 5 6

  26. Sample Simulation

  27. Size and Timing of Outbreaks

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

  29. Infested Area vs. Aggregation p = 25%

  30. 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.

More Related