Hong S. He University of Missouri-Columbia

1. LANDIS 4.0, A New Generation Computer Simulation Modelfor Assessing Fuel Management Effects on Fire Risk in Eastern U.S. Forest Landscapes Hong S. He University of Missouri-Columbia

2. Acknowledgements • Original Design: David Mladenoff • LANDIS 4.0 Dynamic Design: Hong He • Succession/Dispersal Module • David Mladenoff, Hong He • Fire Module • Jian Yang, Hong He, Eric Gustafson • Wind Module • David Mladenoff, Hong He • Harvest Module • Eric Gustafson, Stephen Shifley, Kevin Nimerfro, David Mladenoff, Hong He • Fuel Module • Hong He, Bo Shang, Thomas Crow, Eric Gustafson, Stephen Shifley • Biological Disturbance Module • Brian Sturtevant, Eric Gustafson, Wei Li, Hong He • LANDIS 4.0 Programming • Vera W. Li, Jian Yang, Bo Shang, and Hong He • Funding Supports for LANDIS 4.0 Development • USFS North Central Research Station

3. Introduction See reviews by Keane et al (Ecol. Model. 179) and Mladenoff (Ecol. Model. 180, 2004)

4. LANDISLandscape Disturbance and Succession • ‘Stochastic cellular automaton’ • Raster-based • Complex spatial dynamics computationally possible • Infinite aggregation and dissolution of patches • Spatial Scales • Functional extent 100s ha – 107 ha • Functional resolution- cell size 10x10m - km2 • Temporal Scales • Current model time step is 10 yr, while a version of annual time step has been developed and is being used in Southern California. • LANDIS simulates multiple disturbance and management processes in combination with the simulation of succession dynamics at the tree species level.

5. Tree Species Establishment and Resprouting Species Level Competitive Succession and Dispersal LANDIS 4.0 Model Dynamics Longevity Shade tolerance Dispersal distance Background mortality Disturbance and Management Land type Species age/size susceptibility Wind (top down) Fire (bottom up) Disturbance and Harvest Related Mortality Insect/Disease (specie/age specific) Harvest (specie/age specific) Modify fine/coarse fuel Fuel (Accumulation/reduction) Modify Specie and Age Cohorts Modified from Mladenoff 2004 Ecological Modelling

6. LANDIS Operational Design processes model simulation Multiple fire regimes: Ignition, size, cycle, spread, intensity and severity fire model input Wind regimes: size, cycle, spread, intensity and severity wind Epicenter, frequency, size, Hosts, susceptibility, intensity, and severity climate zone soil map Insect/disease DEM Harvest prescriptions: stands, management units, rotation size, species, and methods harvest Fine, coarse and life fuel Accumulation/decomposition fuel Environmental boundaries and constrains multiple species and age input maps Land type Site and species interactions succession, seeding, disturbance history, and disturbance interaction output single species map output disturbances reclassified vegetation type species age Classes year 0 year n

7. I/O LANDIS 4.0 Software Design --Component-based User1 species name longevity internal design WIND FIRE SUCCESSION maturity mortality growth User2 sprouting 1/O I/O dispersal shade tolerance fire tolerance HARVEST BDA FUEL Usern I/O I/O I/O

8. Sites of LANDIS Applications Modified from Mladenoff 2004 Ecological Modelling

9. An Application in Missouri Central Hardwood Forests

10. Fuel and Fire Management Issues • Over half a century fire suppression • Increasing fire intensity • Need for fuel management • Currently prescribed burning 0.06% per year for fuel reduction • How extensive should fuel treatment be expanded, 0.6%, 1.2%, or 2.4% per year? • Should coarse woody debris reduction be employed? • What are the effects of the combinations of fuel treatment size and method?

11. Simulation Design • Factorial Design of Fuel Treatments Treatment Size (percentage /yr) 0.06 0.12 0.6 1.2 2.4 4.8 Treatment Method ABCD PB PB+ CWD EFG H

12. Simulation Design • Using existing data of species/age and land types • Current fire regime under suppression • Mean fire size 3.5=ha, SD=1.8 ha • Fire cycle 300 yrs on southwestern slopes and 450 yrs on northeastern land types • Harvest • Even/uneven aged harvesting on oldest forest (>100 yrs) and “thinning” on young forest (<30 yrs), 0.4% /yr

13. Statistical Analysis • Each treatment was simulated to 200 years with 10 replicates • Overall treatment effects were analyzed using multivariate analysis of variance (MANOVA) • Treatment pair comparisons was analyzed using ANOVA • Response variables: • percent pixels (% landscape) • simulated fire severity classes (1-5), with 4 severely stand damaging and 5 stand leveling fire • five age classes of four species group, black oak, white oak, shortleaf pine, and maple • Seedling, sapling, pole, sawlog, and old-growth

14. Results and DiscussionSimulated Fire and Species Dynamics

15. Results and DiscussionSimulated Fuel Dynamics

16. Simulated Fires at Different Severities 200 year means Stand leveling Severe damaging Medium damaging Low damaging Ground fire

17. Simulated Fires at Different Severities 200 Year Dynamics Fire Severity Class Proportions (%) Simulation Years

18. Effects of Fuel Treatments on Fire Severity Low damaging Ground fire H Landscape (%) H G G F F D E C E C D A B B A D C B A Landscape (%) A B A E E F C E D B C D Severe damaging F G H F G G H Medium damaging Stand leveling H

19. Simulated Age Class Compositions 200 year means Black oak Pine Maple White oak

20. Effects of Fuel Treatments on Species Age Compositions—Seedling/Sapling Landscape (%) A E B C D F G Black oak Pine H Landscape (%) A E B C H D F G F D G B A C E H White oak Maple

21. Effects of Fuel Treatments on Species Age Compositions—Old Growth Landscape (%) Black oak Pine H H G G F F D D E C A B C A B E White oak H Maple Landscape (%) G G H F F D D C E B C A B E A

22. Summaries • Low and mid severity fires will change to severe stand damaging (class 4) or stand leveling (class 5) fires under the situation of limited fuel treatment (e.g., 0.6%/yr) in central hardwood forests. • Fuel treatments reduce fire occurrence, prolong fire cycle, and reduce the high severity fires. • Fire cycles extend from current 300-450 years to over 1,000 years depending upon treatment methods. • Total sites burned by high severity fires are reduced from 11% to 1% of the study area. • Fuel treatment size exhibits threshold effects in the study area: • When treatment size is small (e.g., <0. 6% per year (treatment B), treatment methods have little effect in terms of reducing fire severity.

23. Summaries • CWD reduction in combination with prescribed burning is more effective in reducing fire severity. • The benefits of fuel treatment are not linearly related to the treatment effort. • Increasing treatment size from 1.2%/yr (F) to 2.4% /yr (G) reduces severe stand damaging fire from 2.4% to 0.5%. Further increasing treatment size to 4.8% (H) had only small effects (although statistically significant) on high severity fires. Thus planners and managers should consider a balanced approach in terms of treatment size and treatment effects. PB PB CWD Treatment effects Treatment D Treatment F

24. Summaries • Fuel treatment effects on species composition and age class are statistically significant, except when treatment size is too small (e.g., <0.6%). However, such effects are secondary to the effects of fire suppression on species composition and age structure (result not shown). • We showed that LANDIS is a effective model for evaluating long-term and large spatial effects for the identified scenarios. The actual future is only one realization of numerous possible scenarios that are beyond any simulation capacity. Thus LANDIS is not a predictive model. Nevertheless, the model is useful since the large-scale effects would otherwise be very difficult to assess.