STARFIRE CASE STUDY. Wildfire Analysis (WF): A case study at Big Cypress National Preserve

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STARFIRE CASE STUDY Wildfire Analysis (WF): A case study at Big Cypress National Preserve 11/7/2011

1 WILDFIRE ANALYSIS (WF) CASE STUDY AT BIG CYPRESS NATIONAL PRESERVE In this case study, we explore the results of the STARFire Wildfire Analysis (WF) at Big Cypress National Preserve. Figure CS.1 shows the administrative boundary of Big Cypress (black outline) in southern Florida. The flat topography, complex values and unique features of the preserve make the Big Cypress planning unit a valuable example for highlighting the features and interpretations available in a WF analysis. Figure CS.1: Big Cypress National Preserve study area http://warnercnr.colostate.edu/starfire-home/ 2

Two areas of interest at Big Cypress are highlighted by blue boxes in Figure CS.2. These cover an area with expected negative net benefit due to fires (red cells in box A) and an area with expected positive net benefit due to fires (dark green cells in box B). We will use these examples to show you how to interpret the net benefits displayed on the WF map. We will also compare the outputs of the original baseline analysis against other WF playbook pages to illustrate how different wind scenarios can change WF outputs. Big Cypress was selected as a case study area specifically to illustrate how wind changes can modify the WF outputs because the flat topography permits us to isolate wind effects on net benefit from topographic effects. Figure CS.2: The Big Cypress WF map showing areas of positive (green) and negative (red) net benefits of fires 1.1 NEGATIVE NET BENEFIT OF A FIRE AREA A Big Cypress supplied the following wind information for their baseline STARFire run: Direction: 40 degrees from north Speed: 7 mph Each red cell in Figure CS.3 indicates an overall negative net benefit for a fire starting in that cell. Although the WF analysis ignites every burnable cell on the landscape, we ll just evaluate an ignition for a single cell a indicated by the black outlined cell in Figure CS.3. Recall that probabilistic fire footprints are determined by the wind information http://warnercnr.colostate.edu/starfire-home/ 3

supplied by the planning unit and fire behavior calculations from FlamMap (for more information, see the WF Gear Head document). Cell a s probabilistic fire footprint is shown by the outlined area spreading to the south-southwest of cell a. The locations of fire management resources identified in the valuation process for Area A are shown in Figure CS.4. Wind Direction 40 deg, 7mph Figure CS.3: Area A with ignition in cell a (cell a outlined in black). Red indicates a negative net benefit from fires; green indicates a positive net benefit. Wind Direction 40 deg, 7mph Figure CS.4: Fire management resources for Area A http://warnercnr.colostate.edu/starfire-home/ 4

Figures CS.5 and CS.6 show that the cells in the fire footprint of cell a have predominately high intensity fires (pink cells in Figure CS.5) under an ecosystem maintenance condition (green cells in Figure CS.6). We can use information like this (high intensity, maintenance) to look up the corresponding protection or enhancement values from Table CST.1. Six of the eight resources present in cell a s footprint for high intensity/maintenance fires have negative values indicating these resources are harmed by fire. The other two resources at this intensity and condition (Prairie and Scrub Cypress) have positive values indicating that they are enhanced by fire. Relative values for other combinations, such as low intensity (tan cells in Figure CS.5) and ecosystem restoration (pink cells in Figure CS.6) would be determined using the appropriate column(s) in Table CST.1. Wind Direction 40 deg, Figure CS.5: Flame length calculated by FlamMap; used to divide landscape into low and high intensity fires. The map uses a flame length breakpoint supplied by Big Cypress: less than 7 foot flame length is low intensity fire; 7 foot or greater is high intensity. Figure CS.6: Ecosystem condition set by managers at Big Cypress using policy definitions for restoration (pink) and maintenance (green). http://warnercnr.colostate.edu/starfire-home/ 5

Table CST.1: Relative protection and improvement values from the valuation process for Big Cypress. Highlighted boxes in the table are for high intensity/ maintenance cells found in Area A. The expected value of burning each cell is calculated by multiplying the protection or enhancement value for a cell by the conditional probability that that cell will burn (burn probabilities are determined internally by STARFire). The final, overall expected net benefit of a fire starting in cell a is the sum of the expected values of burning for all cells within a s fire footprint. Looking at Figure CS.3 we see that cell a is pale red. This tells us that the balance between the negative and positive expected values of burning for the cells inside a s footprint leans toward the negative. This may be interpreted by saying a fire starting in cell a would cause relatively more harm than benefit to the landscape. 1.2 POSITIVE NET BENEFIT OF A FIRE AREA B To understand how a positive net benefit is generated for cells in the WF analysis we examine the WF results for Area B (Figure CS.7). Cell b and its probabilistic footprint for the baseline wind condition are shown by black outlines. Habitat Restoration is the predominant fire management resource in the area with smaller amounts of Prairie, http://warnercnr.colostate.edu/starfire-home/ 6

Scrub Cypress and Cypress strands, domes, marsh and swamp forest (Figure CS.8). A majority of the area is expected to have low intensity fires (Figure CS.9) and is currently in a maintenance condition (Figure CS.10). Wind Direction: 40 deg, 7mph b) Figure CS.7: WF analysis highlighting a positive net benefit for a fire starting in cell b (cell b is green) Wind Direction: d h b) Figure CS.8: Fire management resources for Area B http://warnercnr.colostate.edu/starfire-home/ 7

Wind Direction: 40 deg, 7mph b) Figure CS.9: Flame length calculated by FlamMap; used to divide landscape into low and high intensity fires. The map uses a flame length breakpoint supplied by Big Cypress: less than 7 foot flame length is low intensity fire; 7 foot or greater is high intensity. Wind Direction: 40 deg, 7mph b) Figure CS.10: Ecosystem condition set by managers at Big Cypress using policy definitions for restoration (pink) and maintenance (green). If we look up the corresponding low intensity/ maintenance values for Habitat Restoration, Prairie, Scrub Cypress and Cypress strands in Table CST.2 the values are 0.20, 0.30, 0.30 and 0.30, respectively. The overall positive net benefit from fires for this area is apparent (dark green cells in Figure CS.7) even though there are several single cells with negative (protection) fire values (All Buildings & Ceremonial Sites, Red cockaded woodpecker clusters, Above ground infrastructure). To understand why these areas do not appear red in the map, imagine igniting cell b (outlined cell in Figure CS.7). Although the ignition cell covers an attribute (All Buildings ) with a high negative value http://warnercnr.colostate.edu/starfire-home/ 8

(-1.00) the sum of the expected values of burning for all cells in the footprint results in an overall net positive value for a fire starting in cell b. Cell b shows a positive net benefit from fire because we expect high benefits from nearby cells burning, even though cell b by itself is negative when burned. The other cells in the footprint offset cell b s negative value. Table CST.2: Relative protection and improvement values from process. Highlighted boxes in the table are for low intensity/maintenance cells found in Area B valuation 1.3 COMPARING WEATHER SCENARIOS Because the topography is flat, the wind scenario selected for Big Cypress has a major effect on the probabilistic fire footprints. Figure CS.11 depicts the WF analysis results for the baseline wind scenario we used in our previous examples (wind direction 40 degrees from north; wind speed 7mph). If we model the wind from the opposite direction (220 degrees) and same speed the results look quite different (Figure CS.14). http://warnercnr.colostate.edu/starfire-home/ 9

Figure CS.11: WF analysis with a wind direction of 40 degrees from north and wind speed 7 mph Figure CS.12: WF analysis with a wind direction of 220 degrees from north and wind speed 7mph Comparing the net benefits from the different wind directions in Figures CS.11 and CS.12, we observe that some of the red cells in the center of Area A change from negative (red) at 40 degrees from north to positive (green) at 220 from north. Other cells, particularly in the southwest portion of Area A and the southeast portion of Area B change from a positive net benefit (at 40 degrees) to a negative net benefit (at 220 degrees). For both wind directions the management resources, ecosystem condition and fire intensity remains distributed the same way on the landscape (wind direction does not affect fire intensity in FlamMap). Why do the maps in Figures CS.11 and CS.12 look different? Why did some of the cells change color? http://warnercnr.colostate.edu/starfire-home/ 10

Recall the logic that provides a cell with its color (red for negative net benefit or green for positive net benefit): cell color is determined by the sum of the expected values of burning for the entire collection of cells in the probabilistic fire footprint. If we change the wind direction, an ignition cell will have an entirely new footprint (new shape, direction and size) and will therefore incorporate a different collection of cells. Because the new fire footprint is oriented differently, the footprint cells will have different fire management resources (and values), intensities, landscape conditions and different probabilities of burning. In short, a change in the wind direction will produce an entirely different fire for every cell on the landscape and therefore we expect to have a different cell colors and a different WF map. 1.4 THE PLAYBOOK AND THE WF ANALYSIS Numerous wind directions were assessed at Big Cypress because of the major influence that wind has on fire behavior and fire effects for the planning unit. These runs are collected together to form a playbook from which managers can select a page that matches the wind scenario for a given fire event. Figure CS.15 depicts WF analysis playbook pages for different wind directions at Big Cypress. One area of interest that exhibits dramatic changes in net benefits from fires with changes in wind direction is Alligator Alley (Interstate 75) in the northern part of Big Cypress. Starting in the upper left panel of Figure CS.15 the wind shifts from the northeast, through east, south, west and finishes from the north in the final panels. For all wind directions, the east and west boundaries of the preserve along Alligator Alley indicate negative net benefits (and a potential need for protection from fire) as illustrated by the red cells. The expected net benefits for fires near Alligator Alley in the interior of the preserve, however, change with changes in wind direction. The eastern portion of the highway is particularly affected by winds from the southwest and west (playbook pages for wind directions 220 and 265) with the darker red cells indicating a high value for protecting the highway corridor in the event of a fire under those wind conditions. http://warnercnr.colostate.edu/starfire-home/ 11

Wind Direction: 40 degrees Wind Direction: 85 degrees Wind Direction: 130 degrees Wind direction: 175 degrees Wind direction: 220 degrees Wind direction: 265 degrees Wind direction: 310 degrees Wind Direction: 365 degrees Figure CS.15: Playbook pages from WF analysis for Big Cypress: wind speed is 7 mph; wind direction varies by page http://warnercnr.colostate.edu/starfire-home/ 12

1.5 SUMMARY This case study reviewed the results of the STARFire Wildfire Analysis (WF) at Big Cypress National Preserve in Florida. We covered three topics of interest: how STARFire uses information from the planning unit to calculate expected net benefits from wildfires, how changes in an input (such as wind direction) can change expected net benefits from wildfires, and how we can use the STARFire WF analysis to develop a playbook that allows fire managers a quick glance to see how changes in an input can change net benefit all across the landscape. This case study only covers some of the strengths of the WF analysis. We hope that you will explore the WF analysis more thoroughly and find other ways to apply it to your specific fire management and planning needs. http://warnercnr.colostate.edu/starfire-home/ 13