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SIMulating Patterns and Processes at Landscape scaLEs HISTORIC RANGE of VARIABILITY.

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Presentation on theme: "SIMulating Patterns and Processes at Landscape scaLEs HISTORIC RANGE of VARIABILITY."— Presentation transcript:

1 SIMulating Patterns and Processes at Landscape scaLEs HISTORIC RANGE of VARIABILITY

2 Landres, P.B., Morgan, P., and Swanson, F.J. 1999. Overview of the use of natural variability concepts in managing ecological systems. Ecol Appl. 9: 1179 - 1188 Swetnam, T.W., Allen, C.D., and Betancourt, J.L. 1999. Applied historical ecology: using the past to manage for the future. Ecol Appl. 9: 1189-1260

3 “Applying natural variability concepts require multiple sources of information, ranging from site-specific data and simulation models to expert opinion and judgement”. “Creating static reproductions of past ecosystems is --- not desired.”. Landres et al. 1999

4 “… it may be misguided and fruitless to chose a single fixed point or period of time”. Swetnam et al. 1999

5 HRV using SIMPPLLE Starting with the current landscape make a long-term simulation (500 years) without fire suppression. The resulting landscape can be saved and multiple simulations made with it. The length of the simulation should be long enough to observe cycles in processes and vegetation conditions. Higher fire ignition probabilities can be used to account for Impact of Native Americans Different pathways can be used if processes such as insect or diseases did not exist historically.

6 Questions concerned with using SIMPPLLE to represent “Historic Range of Variability” are: what size area is used? what time frame is represented? do we modify the current landscape before starting? (example - adding back in species that are completely absence increasing fire occurrences to reflect native american ignitions)

7 Examples taken from: Eastside Region One Assessment (Pintler Ranger District) Bitterroot face, Bitterroot National Forest Salmon River Canyon, Idaho Watershed size analysis – Eastside Region One Assessmetn Beaverhead-Deerlodge National Forest SIMPPLLE – possible states (pathways) – current vs historic

8 Gallatin Custer Deerlodge Beaverhead Helena Lewis and Clark National Forest and “geographic areas” for Eastside Region One assessment

9 Missoula Butte Deerlodge Anaconda Hamilton Geographic Area #8 from East Side Assessment 1,500,291 acres

10 Forested habitat types Extreme levels of stand replacing fire occur at intervals greater than 5 decades. A 5 decade representation of historic conditions could provide too small to quantify the range of variability.

11 Forested habitat types Extremes of mixed severity fire levels sometimes coincide with the stand replacing fire, but tend to occur more frequently.

12 Forested habitat types

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14 Historic cycles in mountain pine beetle (mpb) are at low levels, only very infrequently does a very significant outbreak occur because of fire cycles that keep susceptible lodgepole at a minimum.

15 Forested habitat types Changing the scale of the figure makes it easier to see the frequency of lower levels of mountain pine beetle activity

16 Forested habitat types The conditions that are conducive to an extreme mountain pine beetle outbreak occur after decades of fire exclusion. The fuels created by the outbreak can contribute to extremes levels of stand replacing fire. mpb outbreak

17 Forested Habitat Types High, low, and median values from 5, 5-decade simulations for current conditions and 5, 10-decade simulations for historic conditions.

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19 Current mesic shrubs are below the range of what existed historically. Mesic Shrubs on forested habitat types varied with fire cycles.

20 Forested Habitat Types High, low, and median values from 5, 5-decade simulations for current conditions and 5, 10-decade simulations for historic conditions.

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23 Forested Habitat Types High, low, and median values from 5, 5-decade simulations for current conditions and 5, 10-decade simulations for historic conditions.

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25 Historic Conditions Probability of lodgepole pine

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29 Historic conditions Occurrence of quaking aspen

30 Forested Habitat Types High, low, and median values from 5, 5-decade simulations for current conditions and 5, 10-decade simulations for historic conditions.

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33 Forested Habitat Types High, low, and median values from 5, 5-decade simulations for current conditions and 5, 10-decade simulations for historic conditions.

34 Multiple simulations, without fire suppression were used to develop a frequency of fire return This data set used the nonforest from tsmrs and agriculture designations – neither of which were modeled to “burn” - thus a Unrealistic frequency of > 100 years in these areas Fire return frequency in years Bitterroot Face – fire return frequency Stevensville Hamilton Darby

35 Probability of Mixed-Severity-Fire Historic landscape Current landscape Process probability

36 Salmon River Canyon - examples

37 Fire Risk – Salmon River Canyon Current vegetation conditions probability stand replacing fire Historic vegetation conditions probability stand replacing fire Probability percent Simulations display historic stand replacing fire probability was much lower than current conditions.

38 Fire Risk – Salmon River Canyon Probability percent Current vegetation conditions probability mixed severity fire Historic vegetation conditions probability mixed severity fire Simulations display historic mixed severity fire probability was much higher than current conditions.

39 Fire Risk – Salmon River Canyon Simulations display historic light severity fire probability was much higher than current conditions.

40 Eight fifth-code watersheds, in two different areas, bounded by exterior basins (i.e. the surrounding landscape) were modeled in two ways: –1) in isolation from other watersheds, and –2) in context of the surrounding landscape Geographic Area 8 Geographic Area 17 (From analysis by Robert Ahl, graduate student, University of Montana) What size watershed do we model to characterize both historic and current trends?

41 Geographic Area 8 Geographic Area 17 Very distinct boundaries between watersheds. Watershed boundaries are less distinct and tend to be forested.

42 Simulation Comparisons “Not different” means there is no statistical difference in the level of the simulated process when simulated as a single watershed vs. as part of the larger landscape. There is a difference for all processes for GA 17 while only one is different for GA 8

43 GA 8: Stand-Replacing Fire For stand-replacing-fire there is little difference between the means of multiple simulations because the processes does not easily spread across watershed boundaries in this type of landscape.

44 GA 17: Stand-Replacing Fire For stand-replacing-fire there is a difference between the means of multiple simulations because the processes easily spread across watershed boundaries in this type of landscape. In this case simulating as a separate watershed would significantly underestimate the amount of stand replacing fire.

45 Originated Spread Geographic Area 8 origin and spread taken from one simulation Notice how watershed boundaries restrict spread

46 Originated Spread Geographic Area 17 origin and spread from one simulation Notice how watershed boundaries do not restrict spread

47 Beaverhead – Deerlodge Forest - examples “special areas” represented in the SIMPPLLE data set for the entire B-D The smaller the area, the greater the variability in conditions

48 279,711 acres (108,158 acres of forested habitat types) 535,834 acres (156,405 acres of forested habitat types)

49 888,949acres (486,118 acres of forested habitat types) 1,194,247 acres (542,359 acres of forested habitat types)

50 8,311,038 acres –(3,142,265 acres of forested habitat types)

51 Pathways – current vs historic disturbance processes Whitepine blister rust was not identified as a process to be modeled. The decision was made to include it within the current pathways since it is so “established”. To make “historic” simulations we need pathways that have blister rust removed.

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53 “Applying natural variability concepts require multiple sources of information, ranging from site-specific data and simulation models to expert opinion and judgement”. Landres et al. 1999 SIMPPLLE

54 SIMulating Patterns and Processes at Landscape scaLEs


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