APPENDIX B TIMBER / SILVICULTURE

Transcription

1 APPENDIX B TIMBER / SILVICULTURE Appendix B-1. INFORMS Model Used for Landscape Discussion and HRV TFSR Salvage Vegetation Data Preparation The Shake Table Fire Complex started in the late summer of 2006 and the TFSR project proposes to salvage a portion of that fire. The following documents the procedures used to assemble vegetation data for use by the IDT team for effects analysis. The Malheur National Forest uses an analytical tool called the Integrated Forest Resource Management System (INFORMS Version 1.3). It is used on the forest to support planning analysis of forest vegetation at the project level. This is a tool developed by the Natural Resource Information (NRIS) Tools group of the USDA Forest Service. It is essentially a Graphical User Interface (GUI) created in ORACLE that formats data entered or obtained form corporate data sources that can be used in growth and yield programs such as the Forest Vegetation Simulator (FVS) and displayed in a Geographic Information System (GIS) software package such as Arcview. INFORMS can be used to develop alternatives and contains some canned analytical tools to display effects of treatments over time. For the TFSR Project INFORMS was used to assemble available data the forest has in the Field Sampled Vegetation (FSVeg) database which stores all stand exams the forest has taken over the years and formats it to be used with FVS. Since the area to be analyzed was not 100 percent examined prior to the fire, a tool called Most Similar Neighbor (MSN) (Crookston Moeur and Renner, 2002) is incorporated into INFORMS and used to populate any non-sampled forested polygon with data from polygons that are sampled or stand examined. Once all forest polygons are populated with data FVS grows the stands up to the planned implementation date which was set at 6/1/2007. The tool also provides ways for us to describe both pre and post fire conditions. The Following steps were used to create the dataset. These steps are completely documented in Performing Analysis with INFORMS (Twombly 2005). In this document there are 9 steps. For this project INFORMS was used thru step 8 to create pre and post fire conditions. No treatment alternatives were modeled in INFORMS. All documentation for INFORMS can be obtained from the Forest Service Intranet website : 1. Step 1 thru 3. These steps essentially set up the project and make available the National tools to be used in creating the pre and post fire conditions. It involves entering project specific data like implementation date, user access and roles and assignment of optional tools to use. In this case all national tools were assigned and used 2. Step 4. INFORMS at this time uses ARCVIEW 3.3 and ARC/INFO as its primary spatial tool. The project is opened in ARCVIEW and the boundary of the analysis area is imported and selected. This boundary is then used to clip a polygon layer called EVG, which contains all the current vegetation delineated polygons. In this step the tool clips the forest wide coverage EVG to the analysis boundary and extracts from the FSVeg database any exam data that is identified in the database as a useable exam for this area. It formats the data so it can be read by the FVS growth and yield program. At the completion of the program a cover is created called FSVEG_data that FEIS Appendices - 23

2 identifies which polygons are forested, non-forested and non-vegetated. It furthers identifies which polygons have stand exams on them. A discussion of analysis boundary used is needed. The size of the area to analyze is determined by what is needed to analyze snag levels. In normal projects a sub watershed or 6 field Hydrologic Unit Code (HUC) is adequate. Region 6 uses a tool called DECAID Advisor for snag and down woody analysis. It is recommended by the authors of the advisor that for fire salvage projects, an area 5 times the size of the fire or larger is needed when analyzing snag levels. The Shake Table complex was approximately 14,000 acres so a minimum of 70,000 acres is needed for analysis. The area was enlarged to include all of or parts of sub-watersheds (6th Field HUC) that were inside the National Forest proclaimed boundary that the fire had influenced. Private land in-holdings inside the proclaimed boundary were included. The following map shows the boundary and sub-watersheds affected. Total analysis area is approximately 88,043 acres. 3. Step 5- Essentially is a verification step to make sure that stands identified as examined are truly correct and that they can represent the current forested vegetation of the polygon they were done in.. 4. Step 6: This step runs a series of programs provided by the developers of INFORMS. The programs are national tools that upon successful completion of all the tools the entire landscape is populated with exam information or tree lists that can be modeled with the FVS model a. MSN_NF_DATA_ENT. In this step non-forested examined information is entered. At this point in time there are no national protocols for non-forest data that can be incorporated automatically. INFORMS provides a way to enter various non-forest attributes such as Fuel model and percent crown cover of trees, shrubs and grass, which can be used in the non-forest MSN imputations. To date there is no data available to be used. b. MSN_NF_INT_PREP. This step prepares the Non-forest data entered in the previous step to be used with the MSN tool. This step was NOT done. Non forest information was incorporated later from Photo Interpreted data of off :12000 air photography. c. MSN_FV_INT_PREP. This step grows all the examined stands to the year of the Landsat satellite scene used in the later MSN step. The most current Landsat Scene the forest has was from d. MSN_EXT_PREP. This tool prepares the data created in the previous step for use with the MSN tool e. MSN. This process uses Landsat satellite imagery, and a digital elevation model to impute data from inventoried polygons to polygons that have no inventory. It does this by finding the most similar neighbor polygon that has a similar signature from the Landsat scene and other digital elevation model attributes like aspect slope, solar insolation etc. For more information see the INFORMS documentation or the Users Guide to the Most Similar Neighbor Imputation Program Version 2. (Crookston, Moeur, Renner) f. MSN_REPORT. These are the results of the run. It provides information on the validity of the run and the error around the mean one can expect for certain attributes like basal area, Stand Density Index, percent crown cover, height, and volume. It also provides the number of variates used in the algorithms of the MSN run and the r squared value used for goodness of fit of the FEIS Appendices - 24

3 algorithms. It is recommended that for EA or EIS defense a minimum of 4 variates need to be used and a the r squared vale is greater than or equal to.8. If it is not then more stand-exam information needs to be collected. For the TFSR Project the run meets those minimums. g. MSN_FOR_USE_LOAD. This step adds additional attributes into the FSVEG_DATA cover discussed earlier and identifies which stands were used as the most similar neighbor. In this cover a field is created and called USE1_GIS_LINK. This field identifies the stand that was used to represent the polygon It also provides an estimate of which MSN imputed polygons are imputed as OK or POOR.. 5. Step 7 Creates a default no Action alternative. A tool called VEG_DATA_PREP is now run which grows all the forested stands up to the implementation date in the FVS model. The date was set at June 1,2007 in the setup steps.. Once completed the CREATE_VEG_COVER is run and it creates a cover called base_fvs_veg for each of 5 decades into the future starting with 2007 and ending in It includes most of the attributes in the FSVEG_DATA cover plus stand density index, basal area, quadratic mean diameter, over story DBH, Species and volume of the three most abundant species. The tool called FARSITE_PREP was also run and creates a cover called stand-fire for each of the decades identified above. This tool adds attributes to the FSVEG_DATA cover that are useful for specialists concerned with fire risk. 6. Step 8. Creates a No Action plus alternative. There were two alternatives created. The first is the Pre Fire Existing Conditions and the second was Post Fire Conditions. The base FVS model does not incorporate the most recent information on density management. Mortality is based on a density model where at the point where the density is above 55 percent of the maximum level possible for that stand natural mortality begins to increase at a faster rate as time goes on. The default maximums in the model are set using the Plant Association code assigned to that stand when it is extracted from the database. However these maximums are generally set to high for stands that are mostly in the mixed conifer Plant Associations. This assumption is based on a research note done in 1994 that Suggested Stocking Levels for Forest Stands in the Blue Mountains of Northeastern Oregon and Southeastern Washington Cochran and Others 1994). In this research note they suggested ways to calculate upper and lower management zones by Plant Association. David Powell Silviculturist of the Umatilla National Forest in 1999 took this research and published a document called Suggested Stocking Levels for Forest Stands in Northeastern Oregon and Southeastern Washington: An Implementation Guide for the Umatilla National Forest. This guide is also applicable to the Malheur National Forest and provides information necessary to calculate Maximum Stand Density Index (MAXSDI) that the model uses. To adjust MAXSDI a cover was created for each forested polygon and the plant association code extracted from FSVEG database for the sampled stands and then assigned to each forested polygon that each of the 270 sampled stands was used on. These assignments were then manually adjusted to reflect local and personal knowledge of the area where dry forest types were assigned by the imputation process and were changed to a moist forest type. Keyword sets were created for each of the plant associations that changed MAXSDI. Keyword sets were also created to calculated structure class using the STRCLASS keyword and a forest developed set of keywords using a TPA by diameter and a series of IF Ten Statements to assigns another estimate of structural stage. Other keywords were also applied to calculate additional variables that the forest generally finds useful. FVS provides ways of importing any calculated variables into a database or spreadsheet which then can be attached to the covers describer earlier. FEIS Appendices - 25

4 In INFORMS prescriptions are created by using activities or a series of activities that point to keyword sets used by FVS. Prescriptions are then assigned using a prescription assignment tools. In this case the GIS cover assignment tool was used to assign MAXSDI, calculation of structure stage, snag levels for the DECAID advisor, and other calculated variables. The Pre Fire Condition or Alternative in INFORMS was then created using this prescription assignment. The Post-Fire condition was created by copying the Pre-Fire Condition and then assignment of keyword sets that killed trees based on estimated mortality caused by intensity of the burn. To do this, a mortality map was created by using the burn intensity map used in the Burn Area Emergency Recovery plan (BAER) and overlaying it on Digital Globe s Quickbird Satellite Imagery acquired immediately after the fire. This imagery is high resolution and provides up to 1/2 meter resolution in true color, panchromatic and infrared bands. Keyword sets were developed to estimate Very High, High, Moderate and Low mortality. Upon completion of the above steps the base_fvs_veg and stand_fire covers were imported as feature classes into a geodatabase feature dataset for each of the 5 decades. This then became the primary vegetation description of pre and post fire conditions used in further project analysis Results As discussed in the introduction INFORMS is a tool that helps gather available data in corporate sources and structures that are specific to the project analysis area. It then formats that data for uses in growth and yield modeling programs like FVS. In a perfect world with unlimited budgets and time the ideal situation would be to have 100 percent of the polygons with a stand exam. This is generally not possible for most projects. In the past pure remote sensing was used quite often to do analysis either by human air photo interpretation or computer aided pixel analysis. This was quick way to get information for extremely large area but only could give you general estimates of species densities and sizes. None of these sources of vegetation data could be used in growth and yield models and was generally useless at stand levels or landscapes below a watersheds 5th field HUC. In most cases then people would then go out and walk through stands and make general interpretations of what they saw and combined it with the remote sensing product for project implementation analysis. In many cases they also had stand exam information and would identify stands that were not examined but were similar enough to the examined one and use that data for all unexamined ones. Advantages In 2002 the process called MSN was developed and combined both remote sensing techniques and stand level information. The technique essentially populates every stand polygon in the project area using a systematic and repeatable method with tree list information that can be read in to the FVS growth and yield model. This is the basic advantage of INFORMS it incorporates MSN and provides a systematic method of assignment of tree lists to stands with no inventory. The other advantage is that now one has tree list information that can be summarized in traditional expressions of densities and sizes, such as basal area, trees per acre, diameter, volumes, stand density index, structural stages, stand heights along with almost any other attribute that can be arithmetically arrived at. Accuracies and Problems The general goal for any project is to accurately predict for each stand what is there on the ground. In this ideal situation you could display spatially various attributes like structural stages, snag levels, basal area and so on over the landscape. Obviously then the closer to 100 percent inventory one had the more dependable the maps produced would be. However it is impractical and very expensive to FEIS Appendices - 26

5 100 percent inventory every stand and in many instances we have to use what is available especially in salvage projects. Therefore at a minimum, it is recommended that 10 percent of the stands be inventoried in a project area, to derive a reasonable estimate of landscape averages with the MSN process. In practice it has been somewhat lower around 7 or 8 percent on this forest. The exams need to be distributed in most if not all the forest types and sizes. At the minimum number of stands for a project the overall averages or percentages of acres in various groupings have been dependable and users on the Malheur have been happy with the results and believe it is giving an accurate description. It also has helped narrow down what stands that need to be treated or identify stands that may qualify as late seral stages. However at this level it only has been dependable on a stand by stand basis 60 to 70 percent of the time when hey field visit a stand of interest. In some cases it is even less accurate for example Plant Association calls. Therefore it is estimated that when 30 percent to 50 percent of the stands are inventoried, the MSN process will begin provide estimates that accurately depict characteristics at the stand level. For the TFSR Project, 270 stands were examined of the 3545 stands clipped out of the vegetation polygon coverage called EVG. This represents approximately 8 percent of the stands. The exams are fairly well distributed in most of the forest types except for juniper dominated areas and unmanaged moist forest stands. The data provided through MSN and INFORMS for this project is best used when aggregated up to a higher level of grouping. For example each stand was given a Plant Association call and I indicated above that it predicts this attribute poorly on a stand by stand basis when inventoried stands are at this level. However when each stand is placed into the Potential Vegetation Groupings (PVG) of Moist, Dry and or Cold forests using a crosswalk the three blue mountain forests have agreed to for each Plant Association code, it reflects what is on the ground. In the TFSR project area the north aspects at the highest elevations are dominated by grand fir and Douglas-fir moist forest with little ponderosa pine and as one progresses lower in elevation the stands increase in dominance of ponderosa pine and classify as dry forest but are still mixed conifer forests of pine Douglas-fir and some grand-fir. The MSN and INFORMS created data sets support this local knowledge. Likewise on the south aspects there is no moist forest and the highest elevations are primarily mixed conifer ponderosa pine dominated dry forest and at the lower elevations become pure ponderosa pine with some juniper. The datasets created by INFORMS and MSN for this project when displayed in Arcview also support this local knowledge. Submitted: Edward H. Uebler Forest Analyst April, 2007 FEIS Appendices - 27

6 Appendix 1a MSN Report INFORMS Condensed MSN Summary Report Name: msn_report.txt Report Path: /msn Date Created: Tue Dec 12 08:34: Created By: ehuebler Project Name: PC_THORN Report for Forested Vegetation MSN Run Information: Number of variates used is 5 The threshold value is There were 5 notably large distances among reference observations. This represents 1.9 percent of the 270 references. There were 232 notably large distances between reference and target observations. This represents 7.1 percent of the 3247 imputations. Canonical R Squared of 1st variate is: Average Attribute Difference Basal Area 41 Stand Density Index 78 Stand Height 9 QMD 2.9 Total CuFt Volume 1236 Canopy Cover 11 Total number of reference stands: 270 The average difference is the absolute difference between all the observed and imputed values. The absolute difference between the observed and imputed value is calculated for each stand and then these differences are totaled. This total is divided by the total number of reference stands to obtain the average listed above. Note: The actual values with all the decimal places are used in the Calculations. A rounded value is displayed in the report except for QMD FEIS Appendices - 28

7 Appendix B-2. Modeling Assumptions and Process Table B-2-1. Silv App 1 Model inputs to FVS to simulate sample stand attributes over time. ALTERNATIVE 1 WARM-DRY MOIST LOW SEVERITY All distances from edges establish 300 PP nats at age 10, then 50 PP tpa every third cycle, beginning cycle 5 establish 300 (200 pp, 100 df) nats at age 10, then 50 (25pp, 25df) tpa every third cycle, beginning cycle 5 MODERATE SEVERITY Less than 200 feet from seedwall establish 300 PP nats at age 10, then 50 PP tpa every third cycle, beginning cycle 5 establish 300 (200 pp, 100 df) nats at age 10, then 50 (25pp, 25df) tpa every third cycle, beginning cycle 5 HIGH SEVERITY Greater than 200 feet from seedwall VERY HIGH SEVERITY Greater than 200 feet from seedwall ALTERNATIVES 2, 3 and 4 WARM-DRY LOW SEVERITY All distances from edges MODERATE SEVERITY Less than 200 feet from seedwall HIGH SEVERITY Greater than 200 feet from seedwall VERY HIGH SEVERITY Greater than 200 feet from seedwall establish 300 pp nats at age 40, then 50 (25df. 25pp) tpa every third cycle, beginning cycle 7 establish 300 pp nats at age 60, then 50 (25df. 25pp) tpa every third cycle, beginning cycle 8 Salvage as prescribed, establish 100 pp nats at age 10, then 50 tpa pp every third cycle, beginning cycle 5 Salvage as prescribed, plant as described (300 pp, 40 percent survival), establish 100 pp nats at age 10 then 50 pp tpa every third cycle Salvage as prescribed, plant as described (300 pp, 40 percent survival), establish 100 pp nats at age 40 then 50 pp tpa every third cycle beginning cycle 7 Salvage as prescribed, plant as described (300 pp, 40 percent survival), establish 100 pp nats at age 60 then 50 pp tpa every third cycle beginning cycle 8 establish 300 (200 pp, 100df) nats at age 40, then 50 (25 pp 25 df) tpa every third cycle beginning cycle 7 establish 300 (200 pp, 100df) nats at age 60, then 50 (25 pp 25 df) tpa every third cycle beginning cycle 8 MOIST No salvage. establish 300 (200pp, 100df)nats at age 10, then 50 tpa (25 pp, 25 df) every third cycle beginning cycle 5 No salvage. Plant as described (230 pp, 120 df, 60 percent survival), establish 100 (75pp, 25 df) nats at age 10 then 50 tpa (25 p, 25 df) every third cycle beginning cycle 5 No salvage. Plant as described (230 pp, 120 df, 60 percent survival), establish 300 (200pp,100df) nats at age 40 then 50 tpa (25 p, 25 df) every third cycle beginning cycle 7 No salvage. Plant as described (230 pp, 120 df, 60 percent survival), establish 300 (200pp,100df) nats at age 60 then 50 tpa (25 p, 25 df) every third cycle beginning cycle 8 TFSR FVS modeling process for Forested Vegetation Section Effects The primary uses for FVS modeling are to compare the relative differences through time, of structure stage development, snag densities, and fuel conditions Representative stands will be selected for each PAG (warm-dry, and cool-moist), and for each burn severity; very high, high, moderate, low and unburned. Stand selections will be from the stands inside the project area, and will include, where available, measured stands, but to reach about six stands in each condition, imputed stands may be included. INFORMS keyword.kcp files will be used as a basis for each simulation, because they were developed to simulate conditions immediately after the fire. With that basic simulation, salvage will be added to the simulation and regeneration will be added to the simulation to show the effects of those activities on future stand development. Both planting and natural keywords will be used to simulate regeneration at the assumed densities, timing and species (described in Analysis Methods in Silviculture specialist report). Note that results from this process will not be directly comparable to the results from initial INFORMS runs for pre- and post-fire. This is because INFORMS assigns attributes to each site in the entire area, while the FVS used to simulate future conditions uses representative stands, and FEIS Appendices - 29

8 average per-acre conditions, which are then proportioned across the project or cumulative area. The FVS modeling will be used to look at relative proportions of structural stages in the future, and may not compare well with INFORMS existing conditions. The process steps include: 1. select representative stands 2. bring to common starting year (done by informs keywords) 3. increase the number of cycles to Alts 2, 3 and 4: planting; use 2009, because it is at the mid-point of the 4-year planting period (both PAGs) 5. Alt 1 and to model the stands in Alts 2, 3 and 4 that will regen on their own. naturals established at year 10 for low severity burns 6. Alt 1: naturals established at year 20 for moderate burns 7. Alt 1: naturals established at year 40 for high severity burns 8. Alt 1: naturals established at year 60 for very high severity burns 9. Alts 2, 3 and 4: invoke salvage keyword at year 2007 for the Warm-Dry PAG. Moist types are not included in the Proposed Action or Alternative 3 or 4, model removal of 95 percent of dead trees, used diameters from 9.0 to 999 inches. Leave 5 percent as down material 10. Alts 2, 3 and 4: Do not model salvage in moist PAG, but do model planting 11. Plant/Naturals keyword: Plant as appropriate. Establish naturals at 10 years for Low, 20 years for Mod, 40 years for High and 60 years for Very High. 12. Actual keyword sets, and outputs, are available in the project record files. FEIS Appendices - 30

9 Appendix B-3. Map of Vegetation Burn Severity FEIS Appendices - 31

10 Appendix B-4. Map of Insect and Disease Aerial Detection FEIS Appendices - 32

11 Appendix B-5. Map of Estimated Natural Regeneration in 10 years Alternative 1. FEIS Appendices - 33

12 Appendix B-6. Map of Estimated Natural Regeneration in 20-years Alternative 1. FEIS Appendices - 34

13 Appendix B-7. Vegetation Structural Stage Model Results Vegetation Structural Stage Proportional Assessments for each alternative, for 1.) Project area, and 2.) Vegetation section cumulative effects analysis area. Alternative 1 Percent Structural Stage by PAG and Decade for the Project Area PAG DECADE %OFMS %OFSS %SECC %SEOC %SI %UR %YFMS Moist WarmDry FEIS Appendices - 35

14 Alternative 2 Percent Structural Stage by PAG and Decade for the Project Area PAG DECADE %OFMS %OFSS %SECC %SEOC %SI %UR %YFMS Moist Warm Dry FEIS Appendices - 36

15 Alternative 3 Percent Structural Stage by PAG and Decade for the Project Area PAG DECADE %OFMS %OFSS %SECC %SEOC %SI %UR %YFMS Moist Warm Dry FEIS Appendices - 37

16 Alternative 4 Percent Structural Stage by PAG and Decade for the Project Area PAG DECADE %OFMS %OFSS %SECC %SEOC %SI %UR %YFMS Moist Warm Dry FEIS Appendices - 38

17 Alternative 1 Percent Structural Stage by PAG and Decade for the Vegetation Cumulative Effects Area PAG DECADE % OFMS %OFSS %SECC %SEOC %SI %UR %YFMS Moist Warm Dry FEIS Appendices - 39

18 Alternative 2 Percent Structural Stage by PAG and Decade for the Vegetation Cumulative Effects Area PAG DECADE %OFMS %OFSS %SECC %SEOC %SI %UR %YFMS Moist Warm Dry FEIS Appendices - 40

19 Alternative 3 Percent Structural Stage by PAG and Decade for the Vegetation Cumulative Effects Area PAG DECADE %OFMS %OFSS %SECC %SEOC %SI %UR %YFMS Moist Warm Dry FEIS Appendices - 41

20 Alternative 4 Percent Structural Stage by PAG and Decade for the Vegetation Cumulative Effects Area PAG DECADE %OFMS %OFSS %SECC %SEOC %SI %UR %YFMS Moist Warm Dry FEIS Appendices - 42

21 Appendix B-8. Salvage Unit List Alternative 2 Unit # Logging Salvage Slash Reforestation System Prescription Treatment Prescription Acres 1 GB Leave any Green LS Plant 46 2 GB Leave any Green LS Plant H Leave any Green LS Plant 4 4 H Leave any Green LS Plant 9 5 H Leave any Green LS Plant 24 6 GB Scott Guidelines YT Natural 116 Plant 7 9 H Scott Guidelines LS Natural 2 11 H Scott Guidelines LS Natural 47 Plant H Scott Guidelines LS Natural H Scott Guidelines LS Natural 31 Plant H Scott Guidelines LS Plant H Scott Guidelines LS Plant 4 19 H Scott Guidelines LS Natural 24 Plant H Scott Guidelines LS Natural 8 21 H Scott Guidelines LS Natural 27 Plant GB Scott Guidelines YT Natural H Scott Guidelines LS Natural 19 Plant 2 26 H Scott Guidelines LS Natural 7 27 H Scott Guidelines LS Natural H Scott Guidelines LS Natural 3 Plant 4 29 H Scott Guidelines LS Natural 35 Plant H Scott Guidelines LS Plant H Scott Guidelines LS Natural 1 Plant GB Scott Guidelines YT Natural 5 Plant 9 33 H Leave any Green LS Plant 5 36 H Scott Guidelines LS Plant H Scott Guidelines LS Natural 72 Plant H Leave any Green LS Plant 4 39 GB Leave any Green LS Plant 5 40 GB Leave any Green LS Plant 6 41 GB Leave any Green LS Plant 2 FEIS Appendices - 43

22 Alternative 2 Unit # Logging Salvage Slash Reforestation System Prescription Treatment Prescription Acres 42 GB Leave any Green LS Plant 2 43 GB Leave any Green LS Plant H Leave any Green LS Plant H Leave any Green LS Plant H Leave any Green LS Plant H Leave any Green LS Natural 17 Plant H Leave any Green LS Plant H Scott Guidelines LS Plant H Scott Guidelines LS Natural H Scott Guidelines LS Natural 12 Plant H Scott Guidelines LS Natural 12 Plant GB Leave any Green LS Plant H Leave any Green LS Plant H Scott Guidelines LS Natural 24 Plant H Scott Guidelines LS Natural H Scott Guidelines LS Plant H Scott Guidelines LS Natural 7 Plant 6 79 H Scott Guidelines LS Natural H Scott Guidelines LS Natural 3 81 H Leave any Green LS Natural 0 Plant GB Leave any Green LS Plant GB Leave any Green LS Plant 5 85 H Leave any Green LS Plant 196 GB Leave any Green LS Plant H Leave any Green LS Plant 8 88 GB Leave any Green LS Plant H Leave any Green LS Plant H Leave any Green LS Plant H Leave any Green LS Natural 0 Plant H Leave any Green LS Plant H Scott Guidelines LS Natural H Scott Guidelines LS Natural 13 Total 3668 Alternative 3 Unit # Logging Salvage Slash Reforestation System Prescription Treatment Prescription Acres 1 GB Leave any Green LS Plant 46 2 GB Leave any Green LS Plant 103 FEIS Appendices - 44

23 Alternative 3 Unit # Logging Salvage Slash Reforestation System Prescription Treatment Prescription Acres 3 H Leave any Green LS Plant 4 4 H Leave any Green LS Plant 9 5 H Leave any Green LS Plant 24 6 GB Scott Guidelines YT Natural 116 Plant 7 9 H Scott Guidelines LS Natural 2 11 H Scott Guidelines LS Natural 47 Plant H Scott Guidelines LS Natural H Scott Guidelines LS Natural 31 Plant H Scott Guidelines LS Plant H Scott Guidelines LS Plant 4 19 H Scott Guidelines LS Natural 24 Plant H Scott Guidelines LS Natural 8 21 H Scott Guidelines LS Natural 27 Plant GB Scott Guidelines YT Natural H Scott Guidelines LS Natural 19 Plant 2 26 H Scott Guidelines LS Natural 7 27 H Scott Guidelines LS Natural H Scott Guidelines LS Natural 3 Plant 4 29 H Scott Guidelines LS Natural 35 Plant H Scott Guidelines LS Plant H Scott Guidelines LS Natural 1 Plant GB Scott Guidelines YT Natural 5 Plant 9 33 H Leave any Green LS Plant 5 36 H Scott Guidelines LS Plant H Scott Guidelines LS Natural 72 Plant H Leave any Green LS Plant 4 39 GB Leave any Green LS Plant 5 40 GB Leave any Green LS Plant 6 41 GB Leave any Green LS Plant 2 42 GB Leave any Green LS Plant 2 43 GB Leave any Green LS Plant H Leave any Green LS Plant H Leave any Green LS Plant H Leave any Green LS Plant H Leave any Green LS Natural 17 FEIS Appendices - 45

24 Alternative 3 Unit # Logging Salvage Slash Reforestation System Prescription Treatment Prescription Acres Plant H Leave any Green LS Plant H Scott Guidelines LS Plant H Scott Guidelines LS Natural H Scott Guidelines LS Natural 12 Plant H Scott Guidelines LS Natural 12 Plant GB Leave any Green LS Plant H Leave any Green LS Plant 17 Total 2529 Alternative 4 Unit # Logging Salvage Slash Reforestation System Prescription Treatment Prescription Acres 6 GB Scott Guidelines YT Natural 105 Plant 7 9 H Scott Guidelines LS Natural 2 11 H Scott Guidelines LS Natural 47 Plant H Scott Guidelines LS Natural H Scott Guidelines LS Natural 31 Plant H Scott Guidelines LS Plant H Scott Guidelines LS Plant 4 19 H Scott Guidelines LS Natural 24 Plant H Scott Guidelines LS Natural 8 21 H Scott Guidelines LS Natural 27 Plant GB Scott Guidelines YT Natural H Scott Guidelines LS Natural 19 Plant 2 26 H Scott Guidelines LS Natural 7 27 H Scott Guidelines LS Natural H Scott Guidelines LS Natural 3 Plant 4 29 H Scott Guidelines LS Natural 35 Plant H Scott Guidelines LS Plant H Scott Guidelines LS Natural 1 Plant GB Scott Guidelines YT Natural 5 Plant 9 33 H Leave any Green LS Plant 5 36 H Scott Guidelines LS Plant 142 FEIS Appendices - 46

25 Alternative 4 Unit # Logging Salvage Slash Reforestation System Prescription Treatment Prescription Acres 37 H Scott Guidelines LS Natural 72 Plant H Leave any Green LS Plant 4 39 GB Leave any Green LS Plant 5 40 GB Leave any Green LS Plant 6 41 GB Leave any Green LS Plant 2 42 GB Leave any Green LS Plant 2 43 GB Leave any Green LS Plant H Leave any Green LS Plant H Leave any Green LS Plant H Leave any Green LS Plant H Leave any Green LS Plant H Scott Guidelines LS Natural 12 Plant H Scott Guidelines LS Natural 12 Plant GB Leave any Green LS Plant H Leave any Green LS Plant 17 Total 1624 GB=Ground Based, H=Helicopter, LS=Lop and scatter, YT= Yard tops FEIS Appendices - 47

26 Appendix B-9. Salvage Harvest Tree-Marking Guidelines The purpose of these marking guides is to implement the salvage harvest prescriptions for the TFSR Project. The objectives of the salvage harvest prescription are to remove merchantable trees killed by fire, or by secondary effects, including bark beetles. Most of the time it will not be difficult to determine if an individual tree would be considered dead. Blackened boles and the complete absence of needles, or with crowns having all brown needles, or with crowns having fading or dry-appearing (offcolor) green needles throughout the crown are considered dead trees. At other times, a series of estimations will be needed to determine the survivability of fire-injured trees with partially or completely green crowns. To determine a survival prediction for fire-injured trees, the Rating Guide for Tree Survival section is included below. Snag management and retention criteria are included in the project design features, and are included in these marking guidelines by reference. Three salvage prescriptions are applicable to this project: Salvage of dead trees with no green needles applies to units or parts of units mapped in the very high burn severity category only. Any tree with any green needles will be retained, regardless of its likelihood of survival. Snag retention requirements apply here as in all other units. Salvage dead trees as indicated in the rating guides for tree survival (low probability of survival) applies to units or parts of units mapped in the high, moderate and low burn severity category. Marking guidelines include the use of tree survival guidelines to include trees to be removed that are not likely to survive. Danger tree removal applies to all roadside danger tree units and applies the danger tree identification guidelines incorporated by reference. PREDICTING TREE SURVIVAL The tree survival scoring guide described below is adapted from a report entitled Factors Affecting Survival of Fire Injured Trees: A Rating System for Determining Relative Probability of Survival of Conifers in the Blue and Wallowa Mountains (Scott et al. 2002). This report, and its associated amendments are referred to as the Scott Guidelines. Use the Scoring Guide for Rating Tree Survival for the TFSR Project to determine a probability for tree survival. SCORING GUIDE FOR RATING TREE SURVIVAL FOR THE TFSR Project. Young and Immature Ponderosa Pine (Small Trees < 16 in. dbh) High Probability of Tree Surviving = Composite Rating Score 3-8 Moderate Probability of Tree Surviving = Composite Rating Score Low Probability of Tree Surviving = Composite Rating Score Young and Immature Ponderosa Pine (Large Trees > 16 in. dbh) FEIS Appendices - 48

27 High Probability of Tree Surviving = Composite Rating Score 3-9 Moderate Probability of Tree Surviving = Composite Rating Score Low Probability of Tree Surviving = Composite Rating Score Mature and Overmature Ponderosa Pine High Probability of Tree Surviving = Composite Rating Score 3-6 Moderate Probability of Tree Surviving = Composite Rating Score 7-12 Low Probability of Tree Surviving = Composite Rating Score Young and Immature Douglas-fir High Probability of Tree Surviving = Composite Rating Score 3-6 Moderate Probability of Tree Surviving = Composite Rating Score 8-16 Low Probability of Tree Surviving = Composite Rating Score Mature and Overmature Douglas-fir High Probability of Tree Surviving = Composite Rating Score 3-10 Moderate Probability of Tree Surviving = Composite Rating Score Low Probability of Tree Surviving = Composite Rating Score All Size Classes of Lodgepole Pine High Probability of Tree Surviving = Composite Rating Score 2-5 Moderate Probability of Tree Surviving = Composite Rating Score 6-10 Low Probability of Tree Surviving = Composite Rating Score All Size Classes of Western Larch High Probability of Tree Surviving = Composite Rating Score 3-6 Moderate Probability of Tree Surviving = Composite Rating Score 7-13 Low Probability of Tree Surviving = Composite Rating Score Grand Fir and White Fir (Young and Immature Trees <30 in. DBH) High Probability of Tree Surviving = Composite Rating Score 3-4 Moderate Probability of Tree Surviving = Composite Rating Score 5-10 Low Probability of Tree Surviving = Composite Rating Score Grand Fir and White Fir (Mature and Overmature Trees >30 in. DBH) FEIS Appendices - 49

28 High Probability of Tree Surviving = Composite Rating Score 2-12 Moderate Probability of Tree Surviving = Composite Rating Score Low Probability of Tree Surviving = Composite Rating Score Additional tree mortality might occur after marking, but prior to the salvage timber harvest. If the additional mortality is in excess of snag requirements, it is acceptable to remove it. MARKING PROCEDURE Determine the number of snags needed for the unit being marked. Consult the proposed harvest unit data table to determine acres and number of snags to be left. Also, determine the score from part A of the survival guidelines that would apply to all trees being considered in the unit. Direction will be provided on using orange (leave tree) or blue (cut tree) marking paint to designate trees for retention or removal in each unit. For units with leave-tree marking, all merchantable trees that are not marked with orange paint are designated for removal. For units with cut-tree marking, all merchantable trees that are marked with blue paint are designated for removal. Merchantability standards are >9 inches DBH for all species on all units. The Scoring Guide for Rating Tree Survival for the TFSR Project in the Predicting Tree Survival section shows how the composite rating score will be interpreted as a survival probability rating (low, moderate or high). Then use the following criteria to make a final determination about whether the tree is expected to survive over the next few years. Important Note: If it is between the low and moderate probability to survive categories, assign the moderate category. Cover the remainder of the unit, designating all trees predicted to survive and additional snags as required. Distribute the snags across the unit, leaving no areas larger than approximately three acres devoid of snags. If no snags greater than 21 inches DBH are present, then leave the next largest size class. Spacing of multiple diameter snags would be preferable to just retaining large-diameter snags in one limited area. Tally the number of trees by live and dead categories (including trees predicted to die using the survival guidelines) and by size classes: 9-21 inches DBH, and greater than 21 inches DBH. FEIS Appendices - 50

29 APPENDIX B-10. BEST SCIENCE CONSIDERATIONS. TIMBER SALVAGE Several responses to scoping requested the Forest to consider a number of reports, papers, and opinion pieces. Following are discussions on these papers. Beschta et al. Reports The original Beschta Report (Beschta et al. 1995) was commissioned by Pacific Rivers Council. Apparently, it was neither peer-reviewed nor published in a credible source. A similar version (Beschta et al. 2004) was subsequently published in the peer-reviewed journal Conservation Biology. This version was peer reviewed and is available from a credible source. Although the second Beschta report (Beschta et al. 2004) cited more literature than the first report to support the authors points of view, it is considered to be an editorial or opinion piece. The Beschta reports are often mentioned during public scoping. The Beschta report respondents generally advocate that natural recovery of burned landscapes, with little or no human intervention, is the optimal policy for public forests, and that this policy is supported by other literature such as American Lands Alliance (2005), DellaSala et al. (2006), Donato et al. (2006), Lindenmayer et al. (2004), and McIver and Starr (2000, 2001a). Some respondents believe that recovering economic value from dead trees is an inappropriate objective, particularly for public lands such as national forests, or that other values associated with dead trees (wildlife habitat, etc.) provide more net public benefit than revenue and related socioeconomic benefits (employment, income) derived from recovering the salvaged timber. When US Forest Service research scientists reviewed the original Beschta report, they concluded that it was biased toward a custodial (hands off) approach (Everett 1995), and that it is generally accepted in the science community that limiting post-fire management to just a single approach (whether custodial or commodity) is inappropriate because forest sites encompass a wide range of variability, and this variability points to the need for site-specific plans addressing each salvage situation on a case-by-case basis (Everett 1995, McIver and Starr 2001b). The Everett response (Everett 1995) to the original Beschta report (Beschta et al. 1995) was apparently not peer-reviewed or published in a credible source. The TFSR Project includes an alternative that would react to the burned forest in a manner similar to what is recommended by Beschta et al. (1995, 2004) the No Action Alternative. Specifically, the No Action Alternative would satisfy most or all of the Beschta et al. (1995, 2004) recommendations because it would not harvest trees in areas with steep slopes, sensitive soils, or severe fire intensity; it would not harvest trees in riparian areas; it would not build roads (whether temporary or permanent) to access harvest units; it would not harvest live trees (regardless of how tree mortality was determined); and it would not reforest burned sites. With these Beschta et al. (1995, 2004) limitations in place, most of the salvage timber harvest units in the proposed action would not be available for harvest, which means that the purpose and need for economic recovery of dead and dying trees would not be achieved. FEIS Appendices - 51

30 A lack of agreement between the Beschta et al. (1995, 2004) recommendations and the TFSR Project proposed action is not surprising because the Beschta reports address ecosystem restoration goals, while the TFSR Project focuses on recovery of economic value and rapid establishment of forest cover. American Lands Alliance After the Fires Report The objective of the American Lands Alliance (ALA) report (American Lands Alliance 2005) is to raise awareness among policy makers about the short- and long-term adverse ecological and economic impacts of post-fire logging. It draws extensively from the recent Beschta et al. (2004) article in Conservation Biology. The ALA report provides an extensive list of individuals and organizations that helped to produce it. However, the ALA report does not appear to be peer-reviewed (or credit for peer review was not claimed) and it was not published in a credible source. The American Lands Alliance After the Fires report is considered to be an editorial or opinion piece. The Forest Service prepared a response to the ALA report. It concluded that ALA makes highly selective use of the scientific information that addresses this complex topic [logging after fires], ignores the legal mandates placed on the agency by Congress, and downplays the effects of inaction on public forests and local communities (USDA Forest Service 2005). The US Forest Service response to the ALA report was apparently not peer-reviewed or published in a credible source. The TFSR Project includes an alternative that would react to the burned forest in a manner similar to what is recommended by the American Lands Alliance (2005) the No Action Alternative. Our discussion about the Beschta et al. (1995, 2004) reports and their relevance to the TFSR Project, specifically the No Action Alternative, also pertains to the ALA report. McIver and Starr Salvage Logging Literature Synthesis and Review The McIver and Starr report is entitled Environmental effects of post-fire logging: literature review and annotated bibliography (McIver and Starr 2000). The acknowledgments section of this report indicates that it was peer reviewed before being published by the Pacific Northwest Research Station in Portland, Oregon. Results from the original General Technical Report (McIver and Starr 2000) were also reported in the Western Journal of Applied Forestry (McIver and Starr 2001a), and this journal is a credible source. The McIver and Starr report reviews the existing body of scientific literature about logging (timber harvest) following wildfire. Twenty-one post-fire logging studies were reviewed and interpreted. McIver and Starr concluded that while the practice of salvage logging after fires is controversial, the debate is conducted without the benefit of much scientific information (McIver and Starr 2000, 2001a). They also concluded that the immediate environmental effects of post-fire logging are extremely variable and dependent on a wide variety of factors such as fire severity, slope steepness, soil texture and composition, the presence of preexisting roads, construction of new roads, timber harvest systems, and post-fire weather conditions (McIver and Starr 2000, 2001a). FEIS Appendices - 52