Geospatial Model of the Universal Soil Loss Equation for Fremont County, Colorado and the Universal Soil Loss Equation Applied to Fuels Reduction Treatments
A Master’s Thesis Presented to the Faculty of The College of Science and Mathematics Colorado State University-Pueblo Pueblo, Colorado
In Partial Fulfillment Of the Requirements for the
Master of Science in Applied Natural Science
By Annie Thayer Merriam Colorado State University-Pueblo May 2005
Certificate of Acceptance
This thesis presented in partial
fulfillment of the requirements for the degree of
Master of Science in Applied Natural Science
by
Annie Thayer Merriam
Has been accepted by the Graduate Faculty of the
College of Science and Mathematics
Colorado State University-Pueblo.
Approval of Thesis Committee:
Graduate Advisor (Dr. Brian Vanden Heuvel) Date
Committee Member (Dr. Neal Osborn) Date
Committee Member (Dr. Moussa Diawara) Date
Graduate Director (Dr. Mel Druelinger) Date
Dedication
For Butch, my nightlight in a strange house, For without you I would be sitting in the dark with a stubbed toe.
Acknowledgements
Foremost I would like to thank my supervisor at the Bureau of Land
Management, John Smeins. John is responsible for giving me the opportunity to
complete this research and he also helped refine my focus of this research to what it is
today. John has also taught the true definition of fuels reduction: “eliminating small,
weak, trees, so that, few, large, strong, ones may grow.” I would also like to thank
everyone else who supported me at BLM.
To my committee, the deepest thank you. To Dr. Neal Osborn who was the
first to show me the wonderful world of botany and is the reason I have the profession
that I do. He has also made me the botanist I am today. To Dr. Brian Vanden Heuvel
who became a part of my committee before he even started as a professor at Colorado
State University-Pueblo. He has greatly contributed to the efforts of this thesis and has over the past year made me a better teacher. To Dr. Moussa Diawara who has taught me a great deal about environmental management, toxicology and has been a
great mentor and foremost taught me that you can forget to bring a lot of things to
class, just don’t forget a sense of humor.
I would also like to acknowledge Jennifer Dillon who is one of my best
friends and someone who has been through thick and thin with me professionally and
personally. I will always remember the trials and tribulation of fieldwork and all the
good times. Because of you I still can’t look at a Cholla or Grandmother’s Peanut
Butter Cookies without laughing. Along with Jennifer I would like to thank Sara for
always being there.
iv I would like to thank everyone at the BLM who has contributed to this research and supported me as well as contributed. A special thank you goes to John
Shaw who performed numerous canopy calculations for me and without his work this thesis would not be the same.
Finally I would like to thank everyone else who made this work possible, my friends, my family and last but certainly not least Butch Berlemann. Who, after all this still wants to spend the rest of his life with me. Your support and patience still amazes me.
v Geospatial Model of the Universal Soil Loss Equation for Fremont County, Colorado and the Universal Soil Loss Equation Applied to Fuels Reduction Treatments
Annie Thayer Merriam Colorado State University-Pueblo, 2005
Fuels reduction treatments have been practiced by the Bureau of Land
Management, Royal Gorge Field Office since 1998 and have been monitored since
2002. The purpose of these treatments is to eliminate or reduce some of the unnatural fuel loading that has occurred in the west with over zealous fire suppression.
Currently fuels reduction treatment areas have been placed in the Urban/Wildland
Interface as directed by the United States congress. The goal of this research was to examine soil erosion by utilizing the Universal Soil Loss Equation (USLE) on fuels reduction treatments in, and create a geospatial model to qualitatively predict erosion risk of Fremont County to aid in further planning of fuels reduction treatments. It is hypothesized that certain soils will have an increase in erosion due to fuels reduction treatments. The results of this research show that only two soils of 17 studied had a significant difference in soil erosion from pre-treatment status to post-one-year and post-two-year status. It was found that in the two soils, the Bronell and Boyle series, there was a statistically significant decreased in soil erosion due to the reduction of fuels. The other soils indicated that erosion risk was improved but not significantly.
vi Table of Contents
Acknowledgements…………………………………………………………………...iv
Abstract……………………………………………………………………………….vi
List of Tables…………………………………………………………………..……..ix
List of Figures…………………………………………………………………..……..x
Introduction………………………………………………….……………..………….1
Background and Mission of the Bureau of Land Management………...……..1
Standards for Public Land Health……………………………………….…….2
National Fire Plan……………………………………………………………..4
Ecological Dynamics of Fremont County, Colorado…………………….……5
Historical Rangeland Improvements…………………………………….…….9
Current Fuels Reduction Management………………………………………11
Types of Soils………………………………………………………………..12
Types of Treatments…………………………………………………..……..17
Universal Soil Loss Equation (USLE)…………………………………...…..29
Objectives…………………………………………………………………....32
Materials and Methods……………………………………………………………….34
Sampling Methods…………………………………………………………...34
Understory Analysis and Species Diversity………………………………….35
Canopy Sampling…………………………………………………………….36
Photographic Points………………………………………………………….36
Universal Soil Loss Equation...………………………………………………36
vii Statistical Analysis…………………………………………………………...38
Geographical Information Systems Modeling……………………………….39
Data Storage Management…………………………………………………...41
Results………………………………………………………………………………..42
USLE of Fuel Reduction Projects by Soil Series…………………………….42
USLE Comparative Analysis of Treatment Type……………………………49
Geospatial Model of the USLE for Fremont County, Colorado……………..52
Discussion……………………………………………………………………………53
Review of Objectives………………………………………………………...53
USLE of Fuels Reduction Projects by Soil Series…………………………...53
USLE Comparative Analysis of Treatment Type……………………………55
Geospatial Model of the USLE of Fremont County, Colorado…………..….56
Conclusion………………………………………………………………………….. 57
Appendix A. Geographical Information System…………………………………….59
Appendix B. Universal Soil Loss Equation………………………………………….67
Appendix C. Tabular data for soils and monitoring plot information……………….95
Appendix D. Plot data………………………………………………………………104
References………………………………………………………………………..…303
viii List of Tables
Table 1: Calculations used to determine percent canopy………..………………….38
Table 2: Boyle Soil Series one-way ANOVA output……………………………….42
Table 3: Bronell Soil Series one-way ANOVA output……………………………...43
Table 4: Bundo Soil Series one-way ANOVA output……………………………….43
Table 5: Libeg Soil Series one-way ANOVA output………………………………..44
Table 6: Pendant Soil Series one-way ANOVA output……………………………...44
Table 7: Raleigh Soil Series one-way ANOVA output……………………………...45
Table 8: Resort Soil Series one-way ANOVA output……………………………….45
Table 9: Rogert Soil Series one-way ANOVA output……………………………….46
Table 10: Tolex Soil Series one-way ANOVA output……………………………....46
Table 11: Summary table of a one- way ANOVA analysis of statistical
significant differences between soil series……………………………..…….47
Table 12: Plot information that lacks sufficient data for statistical analysis………..48
Table 13: Pre Treatment Comparison one-way ANOVA output…………………….49
Table 14: Post One-Year Comparison one-way ANOVA output…………………....49
Table 15: Post Two-Year Comparison one-way ANOVA output…………………...50
Table 16: Summary table of a one- way ANOVA analysis of statistical
significant differences between treatment types and status of treatment…….51
ix List of Figures
Figure 1: Map depicting the location of Fremont County and Canon City,
Colorado……………………………………………………………………….6
Figure 2: Map demonstrating the area that the Royal Gorge Resource Area
manages in relation to Colorado……………………..……………….……….7
Figure 3: Map depicting the land status of Fremont County…………………………8
Figure 4: Schematic and photograph demonstrating the chaining technique………...9
Figure 5. Rollerchop at North Cotopaxi project. Photo by A. Merriam October
2002…………………………………………………………………………..20
Figure 6: Rills caused by Roller Chopper, North Cotopaxi project. BLM,
November 2002……………………………………………………..………..21
Figure 7: Photo illustrating the influx of exotic species, North Cotopaxi project.
Photo by A. Merriam, June 2004…………………………………………….21
Figure 8: Rollerchop project before treatment. BLM, July 2002…………………...22
Figure 9: Rollerchop project one year after treatment. A. Merriam, July 2003……..22
Figure 10: Rollerchop project two years after treatment. A. Merriam, June 2004….22
Figure 11. The mower type head of a Hydroaxe. BLM, North Cotopaxi, October
2002………………………………………………………………………….24
Figure 12. A Hydroaxe removing selected trees. BLM, North Cotopaxi October
2002…………………………………………………………….…………….24
Figure 13: Hydroaxe project before treatment. BLM, July 2002…………………..25
Figure 14: Hydroaxe project one-year post treatment. BLM, July 2003…………….25
x Figure 15: Hydroaxe project two years post treatment. A. Merriam June 2004…….25
Figure 16: Hand thinning with a chainsaw. BLM, Poverty Mountain September
2002…………………………………………………………………………..26
Figure 17: Hand Thinning and Pile Burning project. BLM, August 2002………….27
Figure 18: Hand Thinning and Pile Burning project one-year post treatment. BLM,
August 2002………………………………………………………………….27
Figure 19: Hand Thinning and Pile Burning project two years post treatment.
A. Merriam, July 2004……………………………………..………………...27
Figure 20. Prescribed burn. BLM, Deer Haven project October 2002……………..29
Figure 21. Schematic of monitoring plot……………………………………………35
Figure 22: Map illustrating the product of the Length/Slope calculation in
ArcGIS 8x……………………………………………………………………40
Figure 23: Enlarged view of Big Hole project to demonstrate the calculated
qualitative USLE. This map illustrates the final product using ArcGIS…….41
Figure 24: Comprehensive map demonstrating qualitatively the erosion potential
of Fremont County, Colorado using ArcGIS………………………………...52
xi Introduction
Fuels management has become a topic of interest over the past years due to wildfires that have had a profound effect on the western United States. Over the last century in most parts of North America, the emphasis shifted away from active fire use for vegetation management to active fire suppression, a shift symbolized by the creation and subsequent popularity of Smokey the Bear in the mid 1940’s (Yoder, 2004). The effect of over-suppression has resulted in unnatural fuel loading and a noted shift in the ecosystem’s dynamics. Forested land in many areas increasingly includes dense understory or smaller more numerous tree stems, and woody vegetation has encroached into what had been prairie grasslands (Yoder 2004). The fire season of 2000, which saw more then eight million acres burn in the western United States (Gantenbein, 2002), encouraged the federal government to do more than fund the firefighting actions. The Clinton administration committed $1.8 billion a year to project called the National Fire Plan (Gantenbein, 2002).
As a result, fuels reduction has been implemented into the Bureau of Land Management’s
(BLM) practices and other agencies both public and private. In the Royal Gorge Resource
Area (RGRA) fuels reduction treatments began in 1998 (Dillon, 2003) and continue to date in recognition of the need for healthy forest management and research.
Background and Mission of the Bureau of Land Management
According to the Bureau of Land Management (BLM) national website,
(www.blm.gov 2004) in 1946, the Grazing Service was merged with the General
Land Office to form the Bureau of Land Management within the Department of the
Interior (DOI). When the BLM was initially created, there were over 2,000 unrelated and often conflicting laws for managing the public lands. The BLM had no unified
1 legislative mandate until Congress enacted the Federal Land Policy and Management
Act (FLPMA) of 1976. FLPMA gave value to public lands and their ownership.
This led to the term “multiple use” which the BLM defines as "management of the
public lands and their various resource values so that they are utilized in the
combination that will best meet the present and future needs of the American people”
(www.blm.gov 2004).
It is the mission of the Bureau of Land Management to sustain the health,
diversity and productivity of the public lands for the use and enjoyment of present
and future generations. However, the BLM has had many challenges throughout its
half-century of management such as, droughts, over grazing, wild land fires, the
amount of land managed and the ever-present budget issues. BLM required
guidelines for management to make sure that the mission and purpose of the BLM
would remain and to maintain consistency.
Standards for Public Land Health
The Bureau of Land Management developed standards for public land health
to ensure that public lands remain healthy and functioning. Standards for public land
health was approved by the Secretary of the Interior on February 3, 1997 to describe
conditions needed to sustain public land health, and relate to all uses of the public
lands (www.co.blm.gov 2004). Standards are applied on a landscape scale and relate
to the potential of the landscape. The Standards for Public Land Health are as follows
and can be accessed at http://www.co.blm.gov/standguide.htm#guide.
Standard 1: Upland soils exhibit infiltration and permeability rates that are appropriate to soil type, climate, land form, and geologic processes. Adequate soil
2 infiltration and permeability allows for the accumulation of soil moisture necessary
for optimal plant growth and vigor, and minimizes surface runoff.
Standard 2: Riparian systems associated with both running and standing water function properly and have the ability to recover from major disturbance such as fire, severe grazing, or 100-year floods. Riparian vegetation captures sediment, and
provides forage, habitat and bio-diversity. Water quality is improved or maintained.
Stable soils store and release water slowly.
Standard 3: Healthy, productive plant and animal communities of native and other desirable species are maintained at viable population levels commensurate with the species and habitat's potential. Plants and animals at both the community and population level are productive, resilient, diverse, vigorous, and able to reproduce and sustain natural fluctuations, and ecological processes.
Standard 4: Special status, threatened and endangered species (federal and state), and other plants and animals officially designated by the BLM, and their habitats are maintained or enhanced by sustaining healthy, native plant and animal communities.
Standard 5: The water quality of all water bodies, including ground water where applicable, located on or influenced by BLM lands will achieve or exceed the
Water Quality Standards established by the State of Colorado. Water Quality
Standards for surface and ground waters include the designated beneficial uses, numeric criteria, narrative criteria, and anti-degradation requirements set forth under
State law as found in (5 CCR 1002-8), as required by Section 303(c) of the Clean
Water Act.
3 National Fire Plan
In addition to these standards, President Bush created the Healthy Forest
Initiative (HFI) in August of 2000 following the repercussion of a century of well- intended fire suppression practices that caused unnaturally extreme fires
(www.fireplan.gov 2004). The purpose of the HFI is to utilize the best science available and take measures to restore public lands to healthy conditions dictated by the Standards for Public Land Health (www.fireplan.gov 2004). The National Fire
Plan (NFP) was developed in August of 2000, following an extreme fire season and the HFI. According to the NFP, five key points are addressed. They are as follows:
1. Assuring that necessary firefighting resources and personnel are available to
respond to wildland fires that threaten lives and property.
2. Conducting emergency stabilization and rehabilitation activities on landscapes
and communities affected by wildland fires.
3. Reducing hazardous fuels (dry brush and trees that have accumulated and
increased the likelihood of unusually large fires) in the country’s forests and
rangelands.
4. Providing assistance to communities that have been or may be threatened by
wildland fire.
5. Committing to the Wildland Fire Leadership Council, an interagency team
created to set and maintain high standards for wildland fire management on
public lands.
4 Ecological Dynamics of Fremont County, Colorado
The Bureau of Land Management manages approximately 8.3 million surface acres in Colorado (www.co.blm.gov 2004). The RGRA manages approximately
71,000 acres (Figures 2, and 3)(Appendix A). This area is managed from the Royal
Gorge Field Office in Canon City, Colorado, which is located in the eastern portion of
Fremont County (Figure 1)(Appendix A). There are 98 different soil types
(Appendix A4) in Fremont County and within these soil types there are 32 different range sites (Appendix A6). A range site is the grouping of soil type by vegetation classification (Appendix A7). The diversity of Fremont County is great, with elevations ranging from 5,500 feet to over 13,000 feet and vegetation ranging from plains to alpine tundra. The lands in Fremont County being so diverse have many uses as well. Primary uses are recreation, mining, wildlife habitat and livestock grazing. To protect these areas the land must be managed for multipurpose and all interests accounted for.
5 Fremont County, Colorado Park
Chaffee Fremont Teller
Salida El Paso
US Hwy 50 Canon City Pueblo
Penrose
Florence
US Hwy 50
Legend
Colorado Custer
Fremont County
Highways Type - INTERSTATE PRINCIPAL ARTERIAL
Cities 0 2.5 5 10 15 20 Miles Figure 1: Map depicting the location of Fremont County and Canon City, Colorado.
6 Royal Gorge Resource Area Canon City Field Office
Legend
Colorado
Cities
RGRA
Highways Type Principal Arterial 0 30 60 120 180 240 Interstate Miles
Figure 2: Map demonstrating the area that the RGRA manages (shaded in blue) in relation to Colorado. -
7 Land Status of Fremont County, Colorado
CO Hwy 9
US Hwy 50 Canon City
US Hwy 50
Legend Land Status
Fremont County Private Lands Cities State Lands
Highways US Forest Service Type US Dept of Defense Interstate US Fish & Wildlife Service Principal Arterial
Major Collector Bureau of Land Management Minor Arterial City/County Govt 0 30 60 120 180 240 Miles National Park Service - Figure 3: Map depicting the land status of Fremont County.
8 Historical Rangeland Improvements
What is now called fuels reduction treatments was once known as rangeland improvements by chainings. Chaining is a method of tree and brush removal by taking a heavy, thick chain or cable and dragging it between two crawl tractors or bulldozers. This was commonly done in the 1960s and 1970s in Pinus edulis and
Juniperus sp. (Pinyon-Juniper) stands across the west.
Figure 4: Schematic and photograph demonstrating the chaining technique.
This would create a swath of torn trees and brush. This was, unlike current fuels reduction treatments, intended to increase livestock grazing lands by decreasing the amount of forested lands and convert them to grass lands. Chainings were not always successful at reducing the amount of trees. Schott and Pieper (1987) while researching the effects of mechanical disturbance on Pinus edulis and Juniperus sp.
9 (Pinyon-Juniper) communities noted that on deeper soils, grasses and forbs did
increase but after 25 years they had declined to near pre-treatment levels. Also the
slash left behind the wake of chainings was large and rough. This debris was at times
burned or left to rot on the ground. During the 1970s when firewood collecting hit a
high the debris was often scavenged for fuel.
Chainings also had to have periodic maintenance performed to keep the area
clear. At times the initial chaining did not kill the trees but only up-rooted them and
created deformed trees that would manage to still re-grow. These treatments usually required hand maintenance with chainsaws to remove these trees and prevent saplings from growing as well, or a fire regime was implemented.
The result of these chainings was, for the purpose intended, a success. The deforestation did create increased areas for livestock to graze. However, other issues have arisen as to whether or not this treatment type was ecologically sound. Today, in many of the chained areas, there are still the remains of down trees and logs that in the dry climate of the west have failed to decompose. Also because of the combination of chainings and grazing, monocultures of Bouteloua gracilis (Blue grama) have formed (pers. obs.).
Research done on conversion sites in southern Utah by Gifford et al. (1969) have demonstrated that infiltration and sediment from plot data indicated that areas cleared of Pinus edulis and Juniperus sp. (Pinyon-Juniper) trees and seeded to grass show no consistent decrease or increase in sediment yields of infiltration rates at a given point. Therefore, chainings have had little effect on infiltration rate, sediment
10 yield and consequently, erosion. However, ecologically this treatment has not been well accepted due to the rough debris and mangled trees left in the wake of this kind of treatment. There also was limited section of treatment areas and little research was preformed on these treatments. For the most part chainings have been discarded.
Current Fuels Reduction Management
Current fuels reduction management was dictated by congress in response to the Healthy Forest Imitative (HFI) and the National Fire Plan. This dictated that fuels reduction treatments be placed in the Urban/Wildland Interface (UWI) and in areas of heavy fuel loading. The Field Office chooses the selection of treatment type and all monitoring techniques. The RGRA selects areas for treatment that meet the requirements of congress as well as ecological soundness based on the judgments of the land managers involved. Treatment type is selected based on the vegetation, topology and other ecological factors that have effect fuels reduction treatments.
In the RGRA there are 20 total treatment projects in stages ranging from planning to post-treatment monitoring and re-treatment where necessary, with a total of a 101 monitoring plots. However the scope of this research is focused on 13 treatment projects, with 77 plots in a total of 17 different soil types and 9 different range sites all located in Fremont County (Appendix A7).
In the research conducted there are 17 different soils types examined
(Appendix C1, Appendix A4). Below is a description of each soil type (USDA,
1995) included in this research.
11 Types of Soils
Boyle series is a gravelly sand loam found on 10 to 40 percent slopes. This soil is shallow and very well drained and found in elevation ranging from 7,200 to
85,000 feet with the major vegetation being Pinus edulis and Juniperus sp. (Pinyon-
Juniper) forests. The surface layer is typically dark grayish brown with gravelly sand loam about three inches thick. Permeability is moderate, and available water capacity is very low, and the rooting depth is only 20 inches. Water erosion is high to very high and runoff can be very rapid. Thinning of the overstory can increase the understory reproduction and can promote grass and sapling growth. The thinning and seeding of grasses reduces the risk of soil erosion. Grazing should not be done on treated or thinned areas for two years to allow understory development and reduce erosion.
Bronell series consists of gravelly sand loam on slopes ranging from 2 to 15 percent. This soil is found between 6,000 and 7,800 feet in elevation and is primarily a Pinus edulis and Juniperus sp. (Pinyon-Juniper) ecosystem. The surface layer is about 16 inches thick and is a grayish brown gravelly sandy loam with rapid permeability and low water capacity. Thinning of the overstory can increase understory growth but as in the Boyel series, must be rested after treatment and re- seeding aids in erosion potential reduction.
Bundo series is a soil that is cobbly sandy loam on 30 to 60 percent northerly facing slopes. This soil is found in elevations ranging between 9,500 and 11,500 feet.
The major vegetation community is mainly Picea engelmannii (Engelmann spruce),
12 Pinus flexilis (Limber pine) and Pinus contorta (Lodegpole pine). Lower limits of
this soil support Pseudotsuga menziesii (Douglas-fir) with mixed Picea sp. (spruce)
communities. The erosion potential for this soil is high and minimizing erosion is
key. Roads should be well drained and disturbing the understory and the mat of litter
that can accumulate should be minimized.
Libeg series soils are comprised of well-drained glacial outwash areas, of extremely cobbly sandy loam ranging from 8,000 to 8,800 feet in elevation and on slopes from 10 to 20 percent. Permeability is moderate and water capacity is low with rooting depth approximately 60 inches or more with medium runoff and water erosion hazard moderate. This soil type is primary a rangeland with limited overstory and a diverse understory of native grasses. In the plots studied this soil type had an extremely high Quercus gambelii (Gambel oak) content.
Martinsdale soils are sandy loam that is deep and well drained, found on 3 to
12 percent slopes at 6,800 to 8,200 feet in elevation. Permeability is moderately slow and available water capacity is high with rooting up to 60 inches or more with slight to high water erosion depending on elevation and slope. This soil is primarily a grass and shrub mix. Where severe erosion of the topsoil occurs, Pinus edulis and
Juniperus sp. (Pinyon-Juniper) ecosystems can develop.
Mussel soils are found on slopes of 2 to 15 percent, with elevations ranging between 6,100 to 7,600 feet. Vegetation is open stands of Pinus edulis and Juniperus sp. (Pinyon-Juniper) with mainly grasses dominating. Bronell soils can mix and increase Pinyon-Juniper stands. Where soils are primarily Mussel grassy vegetation
13 is present with deep well drained surface that is about 22 inches thick. Water capacity is high and runoff is slow to rapid with erosion potential of slight to very high depending on slope and elevation.
Pendent soils are extremely gravelly loam at elevations between 7,100 to
7,400 feet on slopes of 10 to 40 percent. These soils are well drained and derived from limestone. The native vegetation is Pinus edulis and Juniperus sp. (Pinyon-
Juniper) stands with a shallow surface comprised of stones and is gravelly loam approximately seven inches thick. Chainings have occurred in most areas and the removal of the upperstory can yield a productive understory but seeding in conjunction with deferred grazing of two years is necessary to prevent and protect from erosion.
Raleigh soils are found on 15 to 40 percent slopes on mountainsides ranging in elevation of 8,600 to 9,200 that are shallow, somewhat excessively drained. The vegetation is mainly conifers with moderate to rapid permeability, low water capacity and rapid to very rapid runoff increasing erosion risk to high or very high. The potential plant community is ponderosa pine and some Pseudotsuga menziesii
(Douglas-fir). The areas of focus of this research have shallower slopes than the standard.
Resort soils are comprised of gravelly sand loam on slopes of 20 to 45 percent at 7,500 to 8,800 feet in elevation. The surface layer is approximately eight inches thick with some areas of very cobbly sandy loam. This creates a rapid permeably and low water capacity. Rooting is shallow and ranges from 10 to 20
14 inches with the primary vegetation community of Pinus edulis and Juniperus sp.
(Pinyon-Juniper) and a high shrub component. Thinning can increase understory but accompaniment of seeding and differed grazing reduces erosion risk.
Rogert soils are very gravelly sandy loam with an elevation of 8,500 to
10,000 feet on 15 to 40 percent slopes. The native vegetation is mostly grass with open or moderate stands of Pinus ponderosa (Ponderosa pine) that can support Abies sp. (fir) trees on north-facing slopes. Permeability is moderately rapid with low available water capacity and effective rooting of 10 to 20 inches and medium or rapid runoff. Thus the water erosion potential is high to very high. This soil should not be overly disturbed to prevent erosion.
Sedillo soils are found on 4 to 25 percent slopes that are comprised of cobbly sandy loam with primarily vegetation of grasses and scattered Pinus edulis and
Juniperus sp. (Pinyon-Juniper). Elevation is 5,700 to 6,800 feet with 10 to 50 percent of the surface covered with pebbles, cobbles and stones. Permeability is moderate, water capacity low and runoff is rapid with erosion risk ranging from slight to very high depending on slopes. The upperstory is scattered and open allowing for a diverse dense understory. Thinning can increase understory, seeding and differed grazing decreases erosion risk.
Seitz soils are fine gravelly sand loam sites with slopes ranging from 20 to 40 percent at elevations of 8,200 to 11,500 feet. Vegetation community is composed of conifers such as Pseudotsuga menziesii (Douglas-fir) and scattered Picea engelmannii
(Engelmann spruce), which creates a thin layer of partially decomposed needles,
15 leaves and twigs. Permeability is slow with moderate water capacity, rapid runoff
and very high water erosion hazard. Thinning of mature Pseudotsuga menziesii
(Douglas-fir) increases the growth rate of the rest of the stand and increases the
understory vegetation. Erosion risk is high and planning of roads and soils distortion
should be analyzed.
Swissvale soils are on 20 to 25 percent slopes that are found at elevations of
7,300 to 8,400 feet and are shallow and well drained. The dominant vegetation is
Pinus edulis and Juniperus sp. (Pinyon-Juniper) that has moderately rapid permeability, low water capacity, and shallow rooting capacity of 4 to 20 inches. The hazard of water erosion is high or very high and can be reduced by seeding after thinning and differed grazing.
Teaspoon soils are very gravelly sandy loam on slopes of 15 to 45 percent and are well drained with Pinus edulis and Juniperus sp. (Pinyon-Juniper) the dominant community. Water capacity is low, permeability is moderate and effective rooting is 8 to 20 inches with rapid runoff and high to very high erosion potential. If thinning of the upperstory occurs then grazing should be differed for two years and seeding should be done to minimize the erosion hazard.
Tolex soils are found on 25 to 50 percent slopes with native vegetation of scattered ponderosa pine and Quercus gambelii (Gambel oak). The elevation is 7,000 to 7,500 feet with moderate permeability, low water capacity, effective rooting of 10 to 20 inches and rapid runoff. Water erosion hazard is very high. Limiting ground
16 disturbances reduces erosion potential. The area of study has slopes less steep then
the standard Tolex soils.
Travessilla soils are shallow and well drained on slopes ranging from 5 to 20
percent at elevations of 5,300 to 6,800 feet. This soil is typically channery loam that
is moderately alkaline. Available water capacity is very low with moderate
permeability, rooting ranging from 6 to 20 inches; runoff ranging from medium to
rapid and the erosion risk is moderate to high. The major vegetation community is
Pinus edulis and Juniperus sp. (Pinyon-Juniper) with limited understory. These soils have been chained in the past and are dominated by monocultures of grass such as
Bouteloua gracilis (Blue grama).
Wages soils are found on shallow slopes of 2 to 9 percent and are deep well drained with a native vegetation of grasses. Elevation ranges from 6,000 to 6,800 feet with a shallow surface of loam five inches thick. Permeability is moderate, effective water capacity is high and runoff is slow to medium. Erosion hazard is slight to high.
It has been observed that Pinus edulis and Juniperus sp. (Pinyon-Juniper) stands are encroaching onto this soil site.
Types of Treatments Utilized
The BLM in the RGRA employs different types of fuels reduction techniques.
The vegetation community and access to the treatment area determines the type of techniques utilized and cost associated with the treatment. Treatment type is related to the ecosystem and vegetation type to yield the most functional outcome and to assimilate natural reduction.
17 In a Pinus ponderosa (Ponderosa pine) community, hand thinning and controlled burns are most often used. Fire is a common successional regime in such systems and hand thinning reduces the risk of a crown fire occurring since lower limbs are removed, thus reducing ladder fuels. This form of treatment creates an open canopy condition that improves overall forest health including understory and diminishes the risk of high intensity crown fires (Figures 17, 18 and 19).
Rollerchops or Drumchops (Figure 5), Hydroaxes (Figure 11 and 12) or other similar mastication methods are often used to treat Pinus edulis and Juniperus sp.
(Pinyon-Juniper) ecosystems. Pinyon-juniper systems are more often treated on a larger scale basis and therefore cost management must be factored. Rollerchops are less expensive than other treatment types with an average of $50-120 per acre (Dillon,
2003). Topology also is a factor in treating and forms of treating Pinyon-Juniper systems.
The soils associated with Pinyon-Juniper systems also have a reduced organic layer (O horizon) and A layer (A horizon), which is commonly called topsoil. Litter content of the O horizon does not need to be reduced by ground fires. Rollerchops and Hydroaxes can increase the O horizon and subsequently the A horizon of the soil by the amount of litter that is produced (Figures 8,9,10,13,14 and 15). Another major factor in selecting treatment type for a Pinyon-juniper ecosystem is the steepness and rock content. Topology of the area is important in determining if the equipment can reach the area and the effects of the treatment on the equipment its self.
18 Terrain that is steep in nature can be hand thinned, burned or a feller-buncher
can be used. A feller-buncher removes trees individually by cutting them at the base
while holding them with clamps on the front of the tractor or other heavy equipment.
The cut trees are then limbed and placed in piles. This allow for recovery of timber
for logs, chippings, or building materials. The limbs and debris on the forest floor are
often burned or chipped to reduce the biomass accumulation. The feller-buncher is
always used on soft tired machinery and therefore it can be used on steeper terrain.
All aspects of the treatment area are assessed in terms of vegetation
community, topology and access to select treatment type. With this research it is
hoped that treatment type, and treatment area can be better assessed with further
knowledge of erosion factors pertaining to soil.
Rollerchop or Drumchop
Rollerchop of Drumchop is a form of mechanical fuel reduction treatment that
is it is most often used in Pinus edulis and Juniperus sp. (Pinyon-Juniper) and shrubland communities. This treatment uses a bulldozer pulling a large drum with horizontal axe like blades encompassing the drum. A seed hopper can be placed on the back of the bulldozer and before the drum to aid in increasing understory return.
The drum can be filled with water up to 1000 gallons of water to increase weight, with a total weight of the equipment reaching 43,000 pounds (Dillon, 2003). A
Rollerchop can remove Pinyon and Junipers up to eight inches in diameter
(www.blm.gov).
19 Figure 5: Rollerchop at North Cotopaxi project. A. Merriam, October 2002.
The mechanism is for the bulldozer to lower the blade and knock the tree down and then the drum will be pulled over the debris to chop the woody material into smaller pieces ranging from 18” to 24”. This is, however, not always accomplished when woody material is pushed into the ground or otherwise remains whole. Other disadvantages to Rollerchops, includes the frequent ground disturbance that is often caused (Figure 6). This can increase the risk of erosion and increase the possibility for noxious weed induction. Since major ground disturbance can create a habitat for noxious weeds to enter the ecosystem, this effect must be closely monitored. Also Rollerchop treatments often look rather unsightly and rough (Figure
6). The debris and litter created is often large which can slow the rate of decomposition and nutrient return to the soil.
20 Figure 6: Rills caused by Rollerchopper, North Cotopaxi project. BLM, November 2002.
Figure 7: Photo illustrating the influx of exotic species, North Cotopaxi project. A.Merriam, June 2004.
21 Figure 8: Rollerchop project before treatment. BLM, July 2002.
Figure 9: Rollerchop project one year after treatment. A. Merriam, July 2003.
Figure 10: Rollerchop project two years after treatment. A. Merriam, June 2004.
22 Hydroaxe
Hydroaxe (Figure 11) or other mastication treatments are preferable
treatments in shrubland communities and Pinus edulis and Juniperus sp. (Pinyon-
Juniper) projects. The use of a Hydroaxe allows for the treatment to be very selective
since trees are removed one at a time, not in swaths with the Rollerchop method.
Because of this a more natural and visually appealing project can be accomplished.
The mechanism of the Hydroaxe is a tractor with a large mower head attached
to the front of the equipment (Figure 11). The mower head is then applied to the top
of the selected tree and moves down the tree, creating a mulching effect (Figure 12).
This effect is very much desired because it greatly reduces the risk of erosion by
applying and thin layer of litter over exposed soils (Figure 14). The mulch is also
finer compared to Rollerchop debris leading to more rapid decomposition and can
increase nutrient return in the soil. Ground disturbance is also reduced since the only
machinery touching the soil is a rubber-tired tractor. The disadvantage of the
Hydroaxe and other mulching methods is the cost, which averages from $119 to $220 per acre (Dillon, 2003).
23 Figure 11: The mower type head of a Hydroaxe. BLM, October 2002.
Figure 12: A Hydroaxe removing selected trees at North Cotopaxi project. BLM, October 2002.
24 Figure 13: Hydroaxe project before treatment. BLM, July 2002.
Figure 14: Hydroaxe project one-year post-treatment. BLM, July 2003.
Figure 15: Hydroaxe project two years post-treatment. A. Merriam June 2004.
25 Hand Thinning
Hand Thinning is a method that utilized axes, weedwackers, chainsaws and other mechanized methods to manually remove fuels. This form of treatment is high in manual labor and its associated costs at $90 to $355 per acre (Dillon, 2003).
However, the resulting effects are limited ground disturbance and a very selective method of fuels removal. The low ground disturbance allows for the understory to not withstand damage and the threat of noxious species introduction is limited. This treatment is most often used in Pinus ponderosa (Ponderosa pine) communities. The main focus of hand thinning is to reduce ladder fuels, which can result in crown fires and overall fuel loading, which can result in high intensity fires. Pile burning often follows this treatment (Figure 17,18 and 19).
Figure 16: Hand thinning with a chainsaw at Poverty Mountain project. BLM, September 2002.
26 Figure 17: Hand Thinning and Pile Burning project. BLM, August 2002.
Figure 18: Hand Thinning and Pile Burning project one year post-treatment. BLM, August 2002.
Figure 19: Hand Thinning and Pile Burning project two years post-treatment. A. Merriam July 2004.
27 Prescribed Fire
Prescribed fire or controlled burning is a fire that has been consciously set by qualified personnel to reduce fuels and improve land heath and functionality.
Prescribed fire is a land management tool that best reflects natural succession in comparison to other treatments. Prescribed fires are most often used in the Pinus ponderosa (Ponderosa pine), and shrubland ecosystems to mimic naturally occurring low intensity fires that can thin the forest, and reduce fuel loading of the understory.
Pile burning is also preformed in areas that have had other treatments such as hand thinning. The advantage of prescribed fire is the rapid return of nutrients to the soil, the low ground disturbance, and fire’s natural place in successional stages. Fire does have the ability to control noxious and invasive species. There is increased risk to personnel when fire is used. Precautions are taken to ensure the safety of both the environment and fire personnel. The cost on prescribed burning varies from project to project and is dependent on the type of burning done.
28 Figure 20: Prescribed burn at Deer Haven project. BLM, October 2002.
Universal Soil Loss Equation (USLE)
Research on the effects and causes of soil erosion began in agricultural areas
in the 1930s. During the 1940s and 150s, scientists began to develop a technique to
estimate soil loss in the Corn Belt of the United States. In 1954 the U.S. Department
of Agriculture established the National Runoff and Soil Loss Data Center with the
primary focus of gathering data from across the country on all available data
pertaining to erosion and soil loss. This yielded approximately 10,000 plot-years of basic research data (Haan et al. 1994). Wischmeier, Smith et al. developed the
Universal Soil Loss Equation with a description published in Agriculture Handbook
(No. 537) in 1965. The USLE was revised in 1978 for increased accuracy due to additional research and data collected. The USLE has widespread acceptance and has
29 been used as a major conservation tool not only in the United States but other countries around the world.
The USLE is intended to predict long-term average annual rate of erosion of an area based on rainfall, soil type, topography, the ecological system and the management practice used. The original purpose of the USLE was to predict erosion and runoff from agricultural land. To better suit the needs of forestland, using subfactors of certain factors of the USLE is necessary. As described by Haan et al.
(1994) undisturbed soils in forested areas tend to have infiltration rates greater than rainfall rates, meaning that the soil can sustain a greater water capacity than what normally occurs when it rains or runoff from snowmelt. Thus, bare soil areas become the primary source of sediment and runoff. A 0% cover in forest lands frequently results in zero sediment yield as a results of the root mass, whereas zero cover for agricultural land will normally have some sediment yield due to the fact that root mass is usually derogated because of agricultural practices (Haan et al., 1994). Thus the cover factor for forestland use is different from agricultural land uses and is described below.
The equation is A=RKLSCP where A is the average soil loss in tons/acre/year units. R is rainfall/runoff factor for a time period and determines units of A. This includes rainfall energy and runoff as well as accounts for snowmelt. The USLE utilizes thirty-year averages for all precipitation factors including rainfall, rainfall energy and snowmelt (Appendix B1).
30 K is the soil erodibility factor and determines units for A (Appendix B2). This factor
is taken from the Soil Survey of Fremont County. This factor is the rate of soil loss in
units of R under continuous fallow with up and down hill cultivation on a slope of 9%
with a slope length of 72.6 ft (Haan et al. 1994).
L is the slope length factor. This is a ration of soil loss from a defined slope
with the length of slope relative to that from a slope length of 72.6 ft. S is the slope
steepness factor in percent. This too is a ration of soil loss from a slope of defined
steepness relative to a slope of 9% steepness. Both L and S factors are calculated by
use of Geographical Information Systems (GIS). These factors when calculated in
tandem in GIS have a large impact on A because together L and S factors make up
one third of the entire equation and therefore have a great impact on the result
compared to other factors that stand alone.
C factor is cover and management practice. This is the ration of soil loss from
an area with known cover and the management relative to that from an identical area
that is untreated. For this factor, pre-treatment data is used to determine the C factor and serve as the identical area. Pre-treatment C factor and post-treatment C factor must be determined individually (Appendix B).
P is the supporting conservation practice faction, which is the ration of soil loss from a field with a conservation support practice such as contouring relative to that with straight row farming up and downhill (Haan et al. 1994)(Appendix B5).
When determining the USLE for woodlands, C or cover factor can be determined by using specified subfactors necessary to tailor the USLE for forestland
31 in substitute of agriculture land. C factor is determined to account for bare soil, fine
root matter, soil reconsolidation, canopy, steps, depression storage and contour
tillage. The method utilized for this research was determined on four plots and 34
watersheds. The correlation between predicted and observed values was 0.90, which
validates the use of the USLE.
Objectives
The Bureau of Land Management in the RGRA began monitoring the effects
of fuels reduction in 2002 (pers. obs.). Field data collected to date on fuels
monitoring plots is extensive, but the effects of fuels reduction treatments on soil
erosion are limited. The focus of this research will be on the susceptibility of soil
types to erosion because of the soil series type and the removal of canopy cover and
the conversion to litter, as part of a fuels treatment and the consequent decomposition
of that litter. The Universal Soil Loss Equation (USLE) will be implemented to
calculate and predict soil loss in fuels reduction treatments. The use of the USLE is
appropriate for the study of soil erosion on fuel reduction treatments because of the
long term aspects the USLE examines as well as the ability for the USLE to compare
pre-treatment and post-treatment status of fuels reduction treatments. Geospatial
modeling will be done to qualitatively assess erosion potential for fuels reduction
projects and for Fremont County as well. This model will demonstrate where erosion
is likely to occur and therefore land managers can best select optimal projects for
fuels reduction.
32 The objectives of this research are:
1. Examine the effects fuels reduction treatments have had on the
ecosystem specifically pertaining to soil type and erosion factors
utilizing the Universal Soil Loss Equation (USLE). It will be
determine if evidence exists that there is a significant difference
between soil type and treatment status using the USLE.
2. Perform a comparative analysis between the different treatment
types employed to determine if a difference exits between methods
utilized.
3. Create a geospatial model from the USLE to qualitatively define
areas of high and low erosion potential for Fremont County and
designated fuels reduction treatment areas.
4. Collect baseline and continuing vegetation data for short and long
term monitoring of the effects of fuels reduction on understory
communities.
It is hypothesized that certain soils will show an increase in erosion due to fuels reduction treatments. However, short-term erosion will be lessened because of the influx and increase of annual herbaceous species and the amount of litter produced by the process of a fuels reduction treatment. Due to the diversity of
Fremont County, individual soil types may respond in different ways to fuels treatments and a global affect may not be determined.
33 Materials and Methods
Sampling Methods
Fuels reduction monitoring plots which are 2000 feet squared (333.33 meters
squared) where designed by the Bureau of Land Management, Royal Gorge Field
Office to meet the regional needs of that resource area. Monitoring plots are placed
one per fifty acres of treated area. Controls are established in the same treatment area
but remain untreated. Plots are to be monitored prior to treatment then one, two, five
and ten years following treatment.
Navigation and establishment of plots are done using a Trimble GeoExplorer
III, differential correction using Pathfinder Office and projected in North American
Datum 83, Zone 13 North using Environmental Systems Research Institute (ESRI)
ArcView 3x and ArcGIS platforms as well as topographical maps and compass. Plot locations are recorded in Universal Transverse Mercator coordinates (UTM’s). Plots are chosen haphazardly within established treatment areas using ArcGIS then field checked for appropriate placement topographically. Plots are marked with permanent copper or aluminum caps that identify the plot ownership, project, plot identification, and date established. Monitoring plots are twenty feet wide and 100 feet long with the
line transect dissecting the center for a total of 2000 square feet (333.33 square
meters) (Figure 21).
Photos are taken of each site for time series analysis. Understory vegetation
cover is assessed to the species according to percent cover as well as rock, bare
ground and litter. Diversity of species is noted with an inventory of all present
34 species. Tree density and cover are sampled by species and diameter at breast height
(DBH, 4 ½ feet from ground). Soil erosion was assessed using the Universal Soil
Loss Equation (USLE).
Understory Analysis and Species Diversity
Understory is sampled using a line transect method. Understory vegetation cover is
evaluated with the line transect including rock, bare ground and litter categories. The
transect is a 100 foot tape placed in the center of the plot and is read by beginning at mark 0
and botanicals, rock, bare ground and litter intersecting the transect is recorded to the
nearest tenth of a foot. Understory is recorded by genus, species and Natural Resources
Conservation Service code (NRCS code). If a plant is unidentifiable then it is labeled by
growth form followed by unknown and numerically indexed. This method determines
percent cover of understory, rock, bare ground and litter composition.
Figure 21: Schematic of monitoring plot. The plot is 2000 feet square, being 20 feet wide by 100 feet long. The transect tape dissects the center of the plot and is marked by on each end for identification at a later date.
Species diversity is assessed with a complete botanical inventory of the monitoring plot. Plants are recorded according to genus, species and NRCS code. Unidentifiable
35 plants are recorded as above. Plants present but not intercepting the line transect are
considered to be less than one percent of the plot area.
Canopy Sampling
Tree density and cover is sampled by genus, species, Natural Resources
Conservation Service (NRCS) code and divided into Diameter at Breast Height
(DBH) classes. DBH is read with a 10-foot Diameter Tape (D-Tape) and placed into the following size classes: 0-1”, 1-3”, 3-6”, 6-12”, and 12”+. Trees whose base is greater then 50% falling inside the plot perimeter are counted as within the plot.
Photographic Points
Five Photo points of each site are taken with a digital camera facing all the magnetic cardinal directions; north, south, east, west and the ground at mark 0 on the transect tape. This data can be used for time series analysis and fuel loading. Photo points are also useful for locating plots.
Universal Soil Loss Equation (USLE)
The USLE is used to predict soil erosion and in this research the method used was developed by Wishmeier and Smith (1978). A combination of look up tables and
GIS was used to develop each factor the USLE. The equation of the USLE is
A=RKLSCP, where A is the average soil loss per unit of area and is expressed in tons/acre/year. In this research the USLE was calculated for each of the study plots and then GIS was used to calculate a general USLE for all of Fremont County.
The R factor was calculated by isoerodent lines of Colorado (Appendix B1), which for Fremont County is a factor of 20 in tons/acre/year. The K factor, which is
36 soil erodibility, was taken from Fremont County Soil Survey of 1995 (Appendix B2).
The LS factor, which is length slope factor, was derived using GIS and Digital
Elevation Model (DEMs) with 25-meter resolution. The C factor, or cover and management factor, was adapted from Wishmeier and Smith (1978) and assigned to each plot according to treatment type and vegetation community (Appendix B3, B4).
The final factor, the P factor, is determined by supporting conversation practice from
Wishmeier and Smith (1978) (Appendix B5).
For the scope of this research C will be determined by using Dissmeyer and
Foster (1984) method as described by Haan et al (1994). In order to calculate the C factor for the USLE canopy cover must be known. The fuels monitoring data collected (Appendix D) to date has not accounted for percent canopy. The only data collected on canopy was understory canopy from line transects and then trees per acre by species and DBH. In order to obtain percent canopy, data was sent to John Shaw of the Rocky Mountain Research Station, Forest Inventory and Analysis in Ogden,
Utah. The calculations where determined by using John Shaw’s crown width equations by ecoregion and by general equations developed for each species in cases where not enough data existed for section-specific equations (Figure 14). Complete data calculations can be found in Appendix B6.
37 Table 1: Calculations used to determine percent canopy by tree species and DBH. Developed by John Shaw, Rocky Mountain Research Station, Forest Inventory and Analysis in Ogden, Utah. NRCS Code ECOSEC Crown Width Equation DBH-DRC Equation ABCO M331F log(CW)=0.434+0.626*log(DBH) n/a JUMO 331I log(CW)=0.513+0.474*log(DRC) DRC=(DBH+2.6843)/1.0222 JUMO M331F log(CW)=-0.006+0.895*log(DRC)^0.769 DRC=(DBH+2.6843)/1.0222 JUMO M331I** log(CW)=0.154+0.773*log(DRC)^0.721 DRC=(DBH+2.6843)/1.0222 JUSC2 331I** log(CW)=0.072+0.910*log(DRC)^0.753 DRC=(DBH+2.6843)/1.0222 JUSC2 M331F** log(CW)=0.072+0.910*log(DRC)^0.753 DRC=(DBH+2.6843)/1.0222 JUSC2 M331I** log(CW)=0.072+0.910*log(DRC)^0.753 DRC=(DBH+2.6843)/1.0222 PIED 331I** log(CW)=0.215+0.834*log(DRC)^1.039 DRC=(DBH+1.1941)/0.9823 PIED M331F log(CW)=0.070+0.994*log(DRC) DRC=(DBH+1.1941)/0.9823 PIED M331I** log(CW)=0.215+0.834*log(DRC)^1.039 DRC=(DBH+1.1941)/0.9823 PIEN M331F log(CW)=0.424+0.633*log(DBH) n/a PIPO 331I** log(CW)=0.371+0.701*log(DBH)^1.161 n/a PIPO M331F log(CW)=0.391+0.669*log(DBH)^1.312 n/a PIPO M331I** log(CW)=0.371+0.701*log(DBH)^1.161 n/a POTR5 M331F log(CW)=0.383+0.743*log(DBH) n/a PSME M331F log(CW)=0.459+0.572*log(DBH) n/a PSME M331I log(CW)=0.666+0.495*log(DBH)^1.416 n/a *logs are base10 **no ecoregion equation; "generic" species equation used
Statistical Analysis
The primary calculation preformed was a one-way ANOVA calculated in
MiniTab version 13. This was chosen because it is best used in evaluating the statistical significance of differences between two or more sample means (Diekhoff,
1996). Fuels reduction data met the three criteria required for a one-way ANOVA.
The first being that the data be measured on an interval or ration scale, the second being samples should come from population that are normally distributed and lastly, samples being compared should have approximately equal variances (Diekhoff,
1996). The F-test or the Null and Alternative Hypothesis will be used to determine statistical significance between treatment years. Samples are concluded statistically
38 significant in difference if the F value that meets or exceeds the tabular value at the chosen level of significance.
Geographical Information Systems Modeling
The USLE was calculated qualitatively for all of Fremont County using
ArcGIS platforms as well as Arc Info prompt and the length slope factor (LS factor) for specific monitoring plots, which was derived from Digital Elevation Models
(DEMs) (Figure23). For R factor, data was assigned on a countywide basis. For K factor, soils data was assigned to feature classes. LS factor was determined by clipping a DEM to the study area and performing the following calculation.
m n LS(r) = (m+1) [ A(r) / a0 ] [ sin b(r) / b0 ]
Where A[m] is upslope contributing area per unit contour width, b [deg] is the slope, m and n are parameters, and a0 = 22.1m = 72.6ft is the length and b0 = 0.09 = 9% =
5.16 deg is the slope of the standard USLE plot. The expression: Pow([flowacc] * 25
/ 22.1, 0.6) * Pow(Sin([fremontslope] * 0.01745) / 0.09, 1.3)) is then calculated into raster calculator to yield the LS factor.
39 LS Factor of Big Hole and Portions of the Arkansas River
Legend Monitoring Plots Colorado Highways Type PRINCIPAL ARTERIAL LS Factor
5.2 - 12.6
12.7 - 20.2
20.3 - 27.7 Big Hole US Hwy 50 27.8 - 35.2 to Canon City 35.3 - 42.7
42.8 - 50.2
50.3 - 57.7
57.8 - 65.2
65.3 - 72.7
72.8 - 80.2
80.3 - 87.7
87.8 - 95.2
95.3 - 2,773.3 0 0.4 0.8 1.6 2.4 3.2 Miles - Figure 22: Map illustrating the product of the length slope (LS) calculation in ArcGIS 8x.
The product produced on a countywide basis is only a qualitative assessment.
To utilize the USLE on such a large scale requires using averages and constants that relatively depicts the area as a whole. This was accomplished by creating a layer of each of the factors of the USLE. These layers where then transformed from vector datasets into raster datasets and then combined in raster calculator to yield a raster dataset for all of Fremont County, Colorado (Figure 16).
40 Qualitative Calculated USLE of Big Hole
Big Hole US Hwy 50 to Canon City
Legend Monitoring Plots Colorado Highways Type PRINCIPAL ARTERIAL Calculated USLE Value High
Low 0 0.4 0.8 1.6 2.4 3.2 - Miles Figure 23: Magnified view of Big Hole project to demonstrate the calculated qualitative USLE. This map illustrates the final product using ArcGIS 8x.
Data Storage and Management
Data management in the digital age has become crucial. To ensure that data can be properly stored, analyzed and queried when necessary, a Microsoft Access database was established. Geographical data is managed in ArcGIS Geodatabases and linked to the Access database for advanced querying and storage. Photo points are linked to all geographical data and the Access database, so all photos are managed to where they where taken in regards to plot identification and magnetic direction and date.
41 Results
USLE of Fuel Reduction Projects by Soil Series
The A factor of the USLE of each plot was calculated by soil type to
determine if a statistical difference was found between pre-treatment status, post one- year treatment, and post two-year treatment status. All soils showed improvement of soil erosion risk having fuels reduction treatments performed. Only two soil types, the Bronell and Boyle soil series showed a statistically significant difference in improving erosion risk. A summary of all soil series can be found in Table 12. The
Boyle soil series one-way ANOVA preformed below shows statistical significance
for reducing soil erosion at the 0.01 level of significance (Table 2).
Table 2: Boyle Soil Series one-way ANOVA output. Analysis of Variance Boyle Series Source DF SS MS F P Factor 2 51.02 25.51 5.27 0.018 Error 15 72.55 4.84 Total 17 123.57 Individual 95% CIs For Mean Based on Pooled StDev Level N Mean StDev ------+------+------+------Pre Trea 6 4.085 3.720 (------*------) 1 Yr Pos 6 0.704 0.765 (------*------) 2 Yr Pos 6 0.350 0.292 (------*------) ------+------+------+------Pooled StDev = 2.199 0.0 2.5 5.0
The Boyle series shows no statistically significant difference at the 0.01 level
of significance, but does have significance at the 0.05 level of significance, between
pre-treatment, post one-year treatment and post two-year treatment. The tabular critical values for F at the 0.01 level of significance is 8.68 and at the 0.05 level of significance is 4.54. The Bronell soil series one-way ANOVA preformed below
42 shows statistical significance for reducing soil erosion at the 0.01 and 0.05 level of significance (Table 3).
Table 3: Bronell Soil Series one-way ANOVA output. Analysis of Variance Bronell series Source DF SS MS F P Factor 2 1.472 0.736 6.42 0.006 Error 24 2.752 0.115 Total 26 4.224 Individual 95% CIs For Mean Based on Pooled StDev Level N Mean StDev -----+------+------+------+- Pre Trea 10 0.6077 0.5373 (------*------) 1 Yr Pos 10 0.1184 0.0906 (------*------) 2 Yr Pos 7 0.1330 0.1158 (------*------) -----+------+------+------+- Pooled StDev = 0.3387 0.00 0.30 0.60 0.90
The Bronell series shows statistically significant difference at the 0.01 level of significance, between pre-treatment, post one-year treatment and post two-year treatment. The tabular critical values for F at the 0.01 level of significance is 5.61.
The Bundo soil series one-way ANOVA preformed below shows no statistical significance for reducing soil erosion at any level of significance (Table 4).
Table 4: Bundo Soil Series one-way ANOVA output. Analysis of Variance Bundo series Source DF SS MS F P Factor 2 0.5425 0.2712 3.87 0.148 Error 3 0.2101 0.0700 Total 5 0.7526 Individual 95% CIs For Mean Based on Pooled StDev Level N Mean StDev ------+------+------+------Pre Trea 2 0.8943 0.4527 (------*------) 1 Yr Pos 2 0.2701 0.0661 (------*------) 2 Yr Pos 2 0.2437 0.0288 (------*------) ------+------+------+------Pooled StDev = 0.2647 0.00 0.50 1.00
The Bundo series shows no statistically significant difference at the 0.01 level of significance, or at the 0.05 level of significance, between pre-treatment, post one- year treatment and post two-year treatment. The tabular critical values for F at the
0.01 level of significance is 30.81 and at the 0.05 level of significance is 9.55. The
43 Libeg soil series one-way ANOVA preformed below shows no statistical significance for reducing soil erosion at any level of significance (Table 5).
Table 5: Libeg Soil Series one-way ANOVA output. Analysis of Variance Libeg series Source DF SS MS F P Factor 2 0.63 0.32 0.24 0.787 Error 24 31.52 1.31 Total 26 32.15 Individual 95% CIs For Mean Based on Pooled StDev Level N Mean StDev ------+------+------+------Pre Trea 9 0.665 1.652 (------*------) 1 Yr Pos 9 0.344 0.777 (------*------) 2 Yr Pos 9 0.336 0.779 (------*------) ------+------+------+------Pooled StDev = 1.146 0.00 0.60 1.20
The Libeg series shows no statistically significant difference at the 0.01 level of significance, or at the 0.05 level of significance, between pre-treatment, post one- year treatment and post two-year treatment. The tabular critical values for F at the
0.01 level of significance is 5.61 and at the 0.05 level of significance is 3.40. The
Pendant soil series one-way ANOVA preformed below shows no statistical significance for reducing soil erosion at any level of significance (Table 6).
Table 6: Pendant Soil Series one-way ANOVA output. Analysis of Variance Pendant series Source DF SS MS F P Factor 2 10.69 5.34 1.88 0.195 Error 12 34.12 2.84 Total 14 44.81 Individual 95% CIs For Mean Based on Pooled StDev Level N Mean StDev ---+------+------+------+--- Pre Trea 7 1.715 2.384 (------*------) 1 Yr Pos 4 0.024 0.049 (------*------) 2 Yr Pos 4 0.021 0.042 (------*------) ---+------+------+------+--- Pooled StDev = 1.686 -1.5 0.0 1.5 3.0
The Pendant series shows no statistically significant difference at the 0.01 level of significance, or at the 0.05 level of significance, between pre-treatment, post one-year treatment and post two-year treatment. The tabular critical values for F at
44 the 0.01 level of significance is 6.93 and at the 0.05 level of significance is 3.88. The
Raleigh soil series one-way ANOVA preformed below shows no statistical significance for reducing soil erosion at any level of significance (Table 7).
Table 7: Raleigh Soil Series one-way ANOVA output. Analysis of Variance Raleigh series Source DF SS MS F P Factor 2 4.61 2.30 1.93 0.166 Error 26 31.07 1.19 Total 28 35.68 Individual 95% CIs For Mean Based on Pooled StDev Level N Mean StDev ------+------+------+------Pre Trea 19 1.210 1.300 (------*------) 1 Yr Pos 5 0.382 0.277 (------*------) 2 Yr Pos 5 0.361 0.298 (------*------) ------+------+------+------Pooled StDev = 1.093 0.00 0.70 1.40
The Raleigh series shows no statistically significant difference at the 0.01 level of significance, or at the 0.05 level of significance, between pre-treatment, post one-year treatment and post two-year treatment. The tabular critical values for F at the 0.01 level of significance is 5.53 and at the 0.05 level of significance is 3.37. The
Resort soil series one-way ANOVA preformed below shows no statistical significance for reducing soil erosion at any level of significance (Table 8).
Table 8: Resort Soil Series one-way ANOVA output. Analysis of Variance Resort series Source DF SS MS F P Factor 2 14.01 7.00 1.35 0.270 Error 37 191.27 5.17 Total 39 205.28 Individual 95% CIs For Mean Based on Pooled StDev Level N Mean StDev ------+------+------+------Pre Trea 16 1.829 3.333 (------*------) 1 Yr Pos 15 0.537 0.979 (------*------) 2 Yr Pos 9 0.810 1.185 (------*------) ------+------+------+------Pooled StDev = 2.274 0.0 1.2 2.4
The Resort series shows no statistically significant difference at the 0.01 level of significance, or at the 0.05 level of significance, between pre-treatment, post one-
45 year treatment and post two-year treatment. The tabular critical values for F at the
0.01 level of significance is 5.21 and at the 0.05 level of significance is 3.25. The
Rogert soil series one-way ANOVA preformed below shows no statistical significance for reducing soil erosion at any level of significance (Table 9).
Table 9: Rogert Soil Series one-way ANOVA output. Analysis of Variance Rogert series Source DF SS MS F P Factor 2 0.323 0.162 1.20 0.332 Error 14 1.893 0.135 Total 16 2.216 Individual 95% CIs For Mean Based on Pooled StDev Level N Mean StDev ------+------+------+------Pre Trea 7 0.3976 0.5465 (------*------) 1 Yr Pos 5 0.1175 0.1124 (------*------) 2 Yr Pos 5 0.1175 0.1124 (------*------) ------+------+------+------Pooled StDev = 0.3677 0.00 0.30 0.60
The Rogert series shows no statistically significant difference at the 0.01 level of significance, or at the 0.05 level of significance, between pre-treatment, post one- year treatment and post two-year treatment. The tabular critical values for F at the
0.01 level of significance is 6.51 and at the 0.05 level of significance is 3.74. The
Tolex soil series one-way ANOVA preformed below shows no statistical significance for reducing soil erosion at any level of significance (Table 10).
Table 10: Tolex Soil Series one-way ANOVA output. Analysis of Variance Tolex series Source DF SS MS F P Factor 2 0.252 0.126 0.32 0.743 Error 5 1.993 0.399 Total 7 2.245 Individual 95% CIs For Mean Based on Pooled StDev Level N Mean StDev ----+------+------+------+-- Pre Trea 4 0.5065 0.7672 (------*------) 1 Yr Pos 2 0.5331 0.4527 (------*------) 2 Yr Pos 2 0.1065 0.1506 (------*------) ----+------+------+------+-- Pooled StDev = 0.6314 -0.80 0.00 0.80 1.60
46 The Tolex series shows no statistically significant difference at the 0.01 level
of significance, or at the 0.05 level of significance, between pre-treatment, post one- year treatment and post two-year treatment. The tabular critical values for F at the
0.01 level of significance is 13.27 and at the 0.05 level of significance is 5.79.
The remaining soils series lack sufficient data to perform a one-way ANOVA.
Data is presented tabular. In all cases, soil erosion decreased but further data collection is necessary for statistical review (Table 12).
Table 11: Summary table of a one- way ANOVA analysis of statistical significant differences between soil series. Degrees Statistically Soil Level of Tabular Source of F Value Significant Series Significance F Value Freedom Difference Factor 2 0.01 8.68 No Boyle 5.27 Error 15 0.05 4.54 Yes Factor 2 0.01 5.61 Yes Bronell 6.42 Error 24 0.05 3.4 Yes Factor 2 0.01 30.81 No Bundo 3.87 Error 3 0.05 9.55 No Factor 2 0.01 5.61 No Libeg 0.24 Error 24 0.05 3.4 No Factor 2 0.01 6.93 No Pendant 1.88 Error 12 0.05 3.88 No Factor 2 0.01 5.53 No Raleigh 1.93 Error 26 0.05 3.37 No Factor 2 0.01 5.21 No Resort 1.35 Error 37 0.05 3.25 No Factor 2 0.01 6.51 No Rogert 1.2 Error 14 0.05 3.74 No Factor 2 0.01 13.27 No Tolex 0.32 Error 5 0.05 5.79 No
47 Table 12: Table containing all plot information that lacks sufficient data for statistical analysis of a one-way ANOVA. ID Project Name Plot ID Monitor Status Soil Type Range Site R K LS C P A t/ac/yr 151 North Cotopaxi NOCO14 Control Martinsdale Mountain Loam 13-18" 20 0.24 0 0.42 0.6 0.0000 205 North Cotopaxi NOCO14 Control Martinsdale Mountain Loam 13-18" 20 0.24 0 0.42 0.6 0.0000 149 North Howard NHOW4 1 year post-treatment Mussel Loamy Foothill 20 0.17 0 0.06 0.6 0.0000 188 North Howard NHOW4 2 year post-treatment Mussel Loamy Foothill 20 0.17 0 0.06 0.6 0.0000 52 North Howard NHOW4 Pre-treatment Mussel Loamy Foothill 20 0.17 0 0.39 0.6 0.0000 185 Dawson Ranch Dawson1 1 year post-treatment Sedillo Gravelly Foothill 20 0.15 1.89 0.07 0.5 0.1985 167 Dawson Ranch Dawson1 Pre-treatment Sedillo Gravelly Foothill 20 0.15 1.89 0.36 0.5 1.0206 141 Spruce Basin Sprucebasin3 1 year post-treatment Seitz Douglas Fir 20 0.10 2.6 0.06 0.8 0.2496 184 Spruce Basin Sprucebasin3 2 year post-treatment Seitz Douglas Fir 20 0.10 2.6 0.06 0.8 0.2496 77 Spruce Basin Sprucebasin3 Pre-treatment Seitz Douglas Fir 20 0.10 2.6 0.19 0.8 0.7904 94 Arkansas Mountain AM1 2 year pre-treatment Swissvale Pinyon-Juniper 20 0.05 2.76 0.42 0.5 0.5796 95 Arkansas Mountain AM2 2 year pre-treatment Swissvale Pinyon-Juniper 20 0.05 4.8 0.18 0.6 0.5184 234 Arkansas Mountain AM1 Other Swissvale Pinyon-Juniper 20 0.05 2.76 0.42 0.5 0.5796 240 Arkansas Mountain AM2 Other Swissvale Pinyon-Juniper 20 0.05 4.8 0.18 0.6 0.5184 1 Arkansas Mountain AM1 Pre-treatment Swissvale Pinyon-Juniper 20 0.05 2.76 0.42 0.5 0.5796 4 Arkansas Mountain AM2 Pre-treatment Swissvale Pinyon-Juniper 20 0.05 4.8 0.19 0.6 0.5472 126 North Cotopaxi NOCO7 1 year post-treatment Teaspoon Pinyon-Juniper 20 0.05 10.75 0.06 0.6 0.3870 239 North Cotopaxi NOCO7 2 year post-treatment Teaspoon Pinyon-Juniper 20 0.05 10.75 0.06 0.6 0.3870 97 Arkansas Mountain AM4 2 year pre-treatment Teaspoon Pinyon-Juniper 20 0.05 1.37 0.19 0.5 0.1302 242 Arkansas Mountain AM4 Other Teaspoon Pinyon-Juniper 20 0.05 1.37 0.19 0.5 0.1302 6 Arkansas Mountain AM4 Pre-treatment Teaspoon Pinyon-Juniper 20 0.05 1.37 0.19 0.5 0.1302 42 North Cotopaxi NOCO7 Pre-treatment Teaspoon Pinyon-Juniper 20 0.05 10.75 0.1 0.6 0.6450 65 Penrose PENROSE1 1 year post-treatment Travessilla Pinyon-Juniper 20 0.20 1.55 0.07 0.5 0.2170 66 Penrose PENROSE2 1 year post-treatment Travessilla Pinyon-Juniper 20 0.20 0 0.07 0.6 0.0000 146 Penrose PENROSE1 2 year post-treatment Travessilla Pinyon-Juniper 20 0.20 1.55 0.07 0.5 0.2170 145 Penrose PENROSE2 2 year post-treatment Travessilla Pinyon-Juniper 20 0.20 0 0.07 0.6 0.0000 117 Grand Canyon Hills GRCNYNHLS1 1 year post-treatment Wages Loamy Foothill 20 0.24 4.7 0.06 0.6 0.8122 253 Grand Canyon Hills GRCNYNHLS1 2 year post-treatment Wages Loamy Foothill 20 0.24 4.7 0.06 0.6 0.8122 21 Grand Canyon Hills GRCNYNHLS1 Pre-treatment Wages Loamy Foothill 20 0.24 4.7 0.19 0.6 2.5718
48 USLE Comparative Analysis of Treatment Type
The various treatment types, Hydroaxe, Rollerchop, Hand Thinning and
Prescribed Burning, where compared statistically by A factor of the USLE, regardless of soil type, to determine if a statistical difference was found between pre-treatment status, post one-year treatment, and post two-year treatment status. It was found that no statistically significant difference exists between fuels reduction treatment types.
Table 13: Pre-treatment Comparison one-way ANOVA output. Analysis of Variance Pre-treatment Source DF SS MS F P Factor 3 6.62 2.21 0.43 0.733 Error 73 375.33 5.14 Total 76 381.94 Individual 95% CIs For Mean Based on Pooled StDev Level N Mean StDev --+------+------+------+---- Hydroaxe 15 1.626 3.468 (------*------) Roller C 20 0.861 1.251 (------*------) Hand Thn 27 1.197 1.397 (------*------) Rx Burn 15 1.556 3.006 (------*------) --+------+------+------+---- Pooled StDev = 2.267 0.00 0.80 1.60 2.40
Pre-treatment data shows no statistically significant difference at the 0.01 level of significance, or at the 0.05 level of significance, between the different treatment types. The tabular critical values for F at the 0.01 level of significance is
4.08 and at the 0.05 level of significance is 2.74.
Table 14: Post One-Year Comparison one-way ANOVA output. Analysis of Variance Post One-year Source DF SS MS F P Factor 3 0.451 0.150 0.35 0.786 Error 48 20.358 0.424 Total 51 20.808 Individual 95% CIs For Mean Based on Pooled StDev Level N Mean StDev ------+------+------+------Hydroaxe 15 0.4307 0.9855 (------*------) Roller C 22 0.2862 0.5249 (------*------) Hand Thn 6 0.3135 0.2697 (------*------) Rx Burn 9 0.1537 0.2763 (------*------) ------+------+------+------Pooled StDev = 0.6512 0.00 0.35 0.70
49 Post one-year treatment data shows no statistically significant difference at the
0.01 level of significance, or at the 0.05 level of significance, between the different treatment types. The tabular critical values for F at the 0.01 level of significance is
4.22 and at the 0.05 level of significance is 2.80.
Table 15: Post Two-Year Comparison one-way ANOVA output. Analysis of Variance Post Two-year Source DF SS MS F P Factor 3 1.863 0.621 1.41 0.250 Error 53 23.351 0.441 Total 56 25.214 Individual 95% CIs For Mean Based on Pooled StDev Level N Mean StDev ------+------+------+------Hydroaxe 7 0.7386 1.4031 (------*------) Roller C 37 0.3234 0.5596 (---*----) Hand Thn 5 0.3762 0.2478 (------*------) Rx Burn 8 0.0371 0.0550 (------*------) ------+------+------+------Pooled StDev = 0.6638 0.00 0.50 1.00
Post two-year treatment data shows no statistically significant difference at the
0.01 level of significance, or at the 0.05 level of significance, between the different treatment types. The tabular critical values for F at the 0.01 level of significance is
4.16 and at the 0.05 level of significance is 2.78.
Overall there is not statistical difference between treatment statuses of the different treatment types utilized. However trends are noticed, as treatment status progresses over time, the treatment types begin to separate, and could possibly be considered statistically significantly different in the future (Table 16).
50 Table 16: Summary table of a one- way ANOVA analysis of statistical significant differences between treatment types and status of treatment. Statistically Treatment Degrees of Level of Tabular Source F Value Significant Status Freedom Significance F Value Difference Factor 3 0.01 4.08 No Pre-treatment 0.43 Error 73 0.05 2.74 No Factor 3 0.01 4.22 No Post One-year 0.35 Error 48 0.05 2.8 No Factor 3 0.01 4.16 No Post Two-year 1.41 Error 53 0.05 2.78 No
51 Geospatial Model of the USLE for Fremont County, Colorado
Qualitative Calculated USLE of Fremont County, Colorado
US Hwy 50 Canon City
US Hwy 50
Legend Colorado Highways Type PRINCIPAL ARTERIAL MINOR ARTERIAL Calculated USLE Value High
0 2.5 5 10 15 20 Low Miles - Figure 24: Comprehensive map demonstrating qualitatively the erosion potential of Fremont County, Colorado using ArcGIS 8x. Areas designated in red show high erosion potential; areas in blue show areas of low erosion potential.
52 Discussion
Review of Objectives
The first objective was to examine the effects fuels reduction treatments had in regards to soil erosion and soil type using the Universal Soil Loss Equation. This was accomplished and a one-way ANOVA analysis demonstrated that only two soils, of the 17 studied showed statistical significantly difference and that the fuels reduction at the two-year post-treatment status improved soil loss. The second objective was to compare statistically using a one-way ANOVA analysis to determine if a difference existed between treatment types in regards to treatment status following a fuels reduction treatment. This resulted in no statistically significant difference between treatment types. However trends where evident. The third objective was to create a geospatial model of the USLE for Fremont County,
Colorado to qualitatively demonstrate soil erosion potential (Figure 24). This raster dataset was created and now can be utilized to plan and implement future fuels reduction treatments with an improved and well-predicted outcome. The forth and last objective was to continue to collect vegetation data as well as baseline data for monitoring. This was accomplished and further results obtained in the future can be used to analyze the effects of fuels reduction treatments further.
USLE of Fuels Reduction Projects by Soil Series
The first objective was to examine the effects fuels reduction treatments had in regards to soil erosion and soil type using the Universal Soil Loss Equation. This was accomplished and a one-way ANOVA analysis demonstrated that only two soils,
53 Bronell and Boyle series, of the 17 studied showed statistical significantly difference
and that the fuels reduction at the two-year post-treatment status improved soil loss.
The one-way ANOVA analysis demonstrated that the only one soil showed a statistically significant difference between treatment years. The only portion that was significant was the comparison between pre-treatment and post-treatment of the
Bronell soil series. Treatment of this soil decreased the risk of soil erosion. The initial average rate of soil erosion was 0.60 tons/acre/year and the average post- treatment erosion rate was approximately 0.20 tons/acre/year. The Bronell soil series is found on relatively shallow slopes where erosion risk is low and also contains a deep O horizon of the soil making it capable of supporting a decedent understory.
The deep soils also allow for graminoids to become well established and reduce the risk of exotics species from infesting.
The Boyle soils series had moderate statistically significant difference between treatment statuses. The Boyle soil series was statistically significant but only at the 0.05 level of significance. For this soil series, treatment did lower the risk of erosion. This soil demonstrates mild slopes and moderate permeability to allow for water penetration instead of runoff. The O horizon can become shallow on sleep slopes and therefore increase erosion risk.
The remaining soils types where not statistically significant at any level for impacting fuels reduction treatment at pre-treatment or post-treatment status. The data does suggest that fuels reduction treatments have reduced erosion to some small extent. Further research should be conducted to determine if, as seen in other
54 research, the long-term effects of fuels reduction treatments on the site. It must also
be noted that the length slope factor is a key component of the USLE and all
treatments are done on relatively shallow slopes. Also further research will determine
that if perennials will replace the influx of annual exotic vegetation, and if so what the
diversity will be.
USLE Comparative Analysis of Treatment Type
Treatment types where compared to one another at pre-treatment, post one- year and post two-year intervals. There was no evidence that there was a statistical difference between the treatment types. It is known that hand thinning and prescribed burns create less ground disturbance than the Rollerchop or even the Hydoraxe on rubber tired equipment. However, the ground disturbance caused is negated in one to two years following treatment according to Haan et al. (1994). The concern with major ground disturbance is that it creates a niche for noxious weeds to invade.
This research concludes that the only reason to select different treatment types is dictated by the terrain of the landscape, rock content and access to the treatment area it’s self, as well as cost. It must also be noted that Rollerchops create rather unsightly scenery and this should be taken into consideration when implementing a fuels reduction treatment.
Trends where noticed between treatment types even if there is no evidence of statistical significant difference. Pre-treatment data shows that all areas are almost completely alike in variance (Table 13). However, in one-year and two-year monitoring, the treatment types begin to separate (Table 14 and 15). Here the
55 Rollerchop and Hydroaxe technique held constant on soil erosion while Hand
Thinning and Prescribed Fire began to move towards improving soil erosion. Five- year post-treatment monitoring will yield results as to whether this trend will become stronger or weaker.
Geospatial Model of the USLE for Fremont County, Colorado
The model calculating the USLE qualitatively for Fremont County, Colorado using ArcGIS to demonstrate where soil erosion potentially is the highest is a useful tool in the future planning of fuels reduction treatments. The vector data set has a resolution of 25 meters and it is lacking data for the Sangre De Cristo and Wet
Mountain ranges. Soil data was not available at this time to calculate the erosion risk for those areas. While creating this model and conducting this research, it was determined that the length slope factor plays one of the most crucial parts in soil erosion. The LS factor when calculated in tandem as it was done using GIS has a stronger impact because it comprises one third of the entire equation and therefore can have more influence then the other factors. Soil type and treatment type had minimal effect on erosion. For this reason it is concluded that to protect against soil erosion, treatment project areas should be kept on shallow slopes or if they are steep the slope length should be kept as short as possible.
56 Conclusion
Fuels reduction or rangeland improvements have been occurring in Fremont
County on public lands since the 1960s. The purpose of historical treatments was to maximize grazing lands. This was accomplished by chainings, which did serve the purpose of decreasing forested lands and increasing grasslands. However, these grasslands have been over grazed for many years and this has created a monoculture system, which, ecologically is not as stable and is a high risk for the dynamic to rapidly change. In regards to soil erosion, research has shown that following treatment or conversion to grasslands, there is not a drastic change in infiltration, runoff or sediment yield.
Current fuels reduction treatments are not as rough as the chainings. These treatments use Rollerchops, Hydroaxes, Hand Thinning or Prescribed Burning as primary mechanical tools and occasionally a Feller-Buncher is used. The treatments remove selected trees in all cases except the Rollerchop, which still utilizes swath methods. The purpose of these treatments is not to increase grazing land but to remove the heavy fuel loading that has occurred due to years of over fire suppression.
Consequently, fuels reduction treatments are bumping the successional stages of the ecosystem back to annual broadleaf and grass/forb communities.
This research has shown that there are no statistical difference between pre- treatment status and post-one and post-two-year treatment status for soil erosion among soil types with the exception of the Bronell and Boyle soil series. In these soil
57 series the risk of erosion was decreased. A general trend was noticed that overall erosion risk was reduced following a fuels reduction treatment.
Further research would determine the full effects of fuels reduction treatments. Currently only three years of data have been collected. It is also known that following a disturbance; succession will be an annual broadleaf community. This is the current stage in which fuels reduction treatments are. Five to ten-year monitoring will determine full effects since the successional stage will have moved beyond pioneer, annual broadleaf plant communities. When this occurs it will be clear if the soil type can sustain and robust and a large enough understory to compensate for the lack of litter that has subsequently decreased due to decomposition and the removal of the upperstory.
58 References
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Aro, R.S. Pinon-Juniper Woodland Manipulation with Mechanical Methods. 1975. Utah Agricultural Experiment Station, pp.67-75.
Blair, G.N. Soil Erosion on Chained and Unchained Slopes in the Garden Park Valley of South Central Colorado: A Comparative Analysis. 2004 University of Kansas, Department of Geography.
Bureau of Land Management. Decision Record and Finding of No Significant Impact: For Adoption of Standards for Public Land Health and Guidelines for Livestock Grazing Management in Colorado. January, 1997.
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305
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306 Appendix A. Geographical Information Systems This portion contains maps and tables relevant to all work done in regards to fuels reduction through the Bureau of Land Management, Royal Gorge Field Office.
Theses products are reproduced from geospatial information prepared by the U.S. Department of the Interior, Bureau of Land Management. GIS data and product accuracy may vary. They may be: developed from sources of differing accuracy, accurate only at certain scales, based on modeling or interpretation, incomplete while being created or revised, etc. Using GIS products for purposes other than those for which they are created may yield inaccurate or misleading results. The Bureau of Land Management reserves the right to correct, update, modify, or replace GIS products without notification. For more information contact the Royal Gorge Field Office, (719)269-8500
59 Map of Fremont County, Colorado
PARK
TELLER
EL PASO
CHAFFEE
US Hwy 50 CanonCanon City City FREMONT GUNNISON
US Hwy 50
Legend PUEBLO Cities
SAGUACHE
Fremont County CUSTER
Counties
Highways Interstates Principal Arterial HUERFANO
0 3.5 7 14 21 28 - Miles Appendix A2: Map depicting where Fremont County is located geographically in Colorado and the geographic location of Canon City within Fremont County.
60 Land Status of Fremont County, Colorado
CO Hwy 9
US Hwy 50 Canon City
US Hwy 50
Legend Land Status
Fremont County Private Lands Cities State Lands
Highways US Forest Service Type US Dept of Defense Interstate US Fish & Wildlife Service Principal Arterial
Major Collector Bureau of Land Management Minor Arterial City/County Govt 0 30 60 120 180 240 Miles National Park Service - Appendix A3: Map showing land status or land ownership of Fremont County.
61 Soil Types of Fremont County, Colorado CO Hwy 9
US Hwy 50 Canon City
US Hwy 50
Legend
BRONELL ESS LIBEG QUERIDA SHRINE Fremont County BRONELL VARIANT FORT COLLINS LIMON RA LEIGH SWISSVALE Ci ties BUNDO FORT COLLINS VARIANT LIMON, MODERATELY WET RE DCA MERON TEASPOON
BUSHVALLEY FORT COLLINS, COOL LIMON, SALINE RENTSAC TECOLOTE Colorado Highways MAJOR COLLECTOR CASCAJO GRANILE LOUVIE RS RENTSAC VARIANT TEL LURA
MINOR ARTERIAL CASCAJO VARIANT HAPLOBOROLLS MANVEL RE SORT TOLEX PRINCIPAL ARTERIAL CA SVA RE HE ATH MANVEL, SALINE RIVERWASH TOLEX, WARM CO Hwy 69 Soils CATHEDRAL HERAKLE MANZANOLA RIZOZO TRAVESSILLA
Soil Name CHITTUM, DRY HOODLE MARTINSDALE VARIANT ROGE RT USTIC TORRIORTHENTS
ADDERTON COALDALE JODERO MIDWAY ROGERT, WARM WAGES AMALIA COCHETOPA JODERO VARIANT MORSET ROYGORGE WAHATOYA AQUIC USTIFLUVENTS CORPENING KIM MUSSEL SAWFORK WANN - AQUOLLS CRYOBOROLLS KIM, COOL NEVILLE SEDILLO WATER
ARENTS CUMULIC CRYAQUOLLS KIM, MODERATELY WET NUNN SEITZ WESIX
BLOOM CURECANTI LAKEHELEN OTERO SHANTA WETMORE BOYLE CURECANTI VARIANT LARAND - PENDANT SHANTA, DRY WILEY 0 2.5 5 10 15 20 BOYLE, WARM DUMPS AND PITS LARKSON PENROSE SHINGLE WILEY, COOL
YOUGA Miles
Appendix A4: Map of Fremont County soils by name. Soil names determined by USGS.
62
Legend
BRONELL ESS LIBEG QUERIDA SHRINE Fremont County BRONELL VARIANT FORT COLLINS LIMON RALEIGH SWISSVALE Cities BUNDO FORT COLLINS VARIANT LIMON, MODERATELY WET REDCAMERON TEASPOON
BUSHVALLEY FORT COLLINS, COOL LIMON, SALINE RENTSAC TECOLOTE Colorado Highways MAJOR COLLECTOR CASCAJO GRANILE LOUVIERS RENTSAC VARIANT TELLURA
MINOR ARTERIAL CASCAJO VARIANT HAPLOBOROLLS MANVEL RESORT TOLEX PRINCIPAL ARTERIAL CASVARE HEATH MANVEL, SALINE RIVERWASH TOLEX, WARM
CATHEDRAL HERAKLE MANZANOLA CO HwyRIZOZO 69 TRAVESSILLA Soils
Soil Name CHITTUM, DRY HOODLE MARTINSDALE VARIANT ROGERT USTIC TORRIORTHENTS
ADDERTON COALDALE JODERO MIDWAY ROGERT, WARM WAGES
AMALIA COCHETOPA JODERO VARIANT MORSET ROYGORGE WAHATOYA
AQUIC USTIFLUVENTS CORPENING KIM MUSSEL SAWFORK WANN
AQUOLLS CRYOBOROLLS KIM, COOL NEVILLE SEDILLO WATER
ARENTS CUMULIC CRYAQUOLLS KIM, MODERATELY WET NUNN SEITZ WESIX
BLOOM CURECANTI LAKEHELEN OTERO SHANTA WETMORE BOYLE CURECANTI VARIANT LARAND - PENDANT SHANTA, DRY WILEY BOYLE, WARM DUMPS AND PITS LARKSON PENROSE SHINGLE WILEY, COOL
YOUGA
Appendix A5: Legend corresponding to Appendix A4. This represents the diversity of soil types in Fremont County.
63 Range Sites of Fremont County, Colorado CO Hwy 9
US Hwy 50 Canon City
US Hwy 50
Legend
Fremont County Soils DRY LOAM SLOPES LOAMY FOOTHILL OVERFLOW SANDY PLAINS
Appendix A6: Map illustrating the range sites of Fremont County.
64
Legend
Fremont County Soils DRY LOAM SLOPES LOAMY FOOTHILL OVERFLOW SANDY PLAINS
Appendix A7: Legend corresponding to Appendix A6. This represents the diversity range sites in Fremont County.
65 Fuels Reduction Monitoring Plots of Fremont County, by Soil Type
Co Hwy 9
US Hwy 50 Canon City
US Hwy 50
Legend
Soils BOYLE CATHEDRAL CURE CANTI VA RIANT HERAKLE LARAND MANZANOLA PENDANT RIZOZO SHANTA, DRY TRAVESSILLA Monitoring Plots
WILEY , COO L 0 2.5 5 10 15 20 YOUGA Miles - Appendix A7: Map illustrating the distribution of fuels reduction monitoring plots in Fremont County.
66 Appendix B. Universal Soil Loss Equation This dataset contains all tables and maps pertaining to the Universal Soil Loss Equation. Tables contain factors that equate to the USLE. Canopy calculation required for the C factor is present in its entirety as done by John Shaw.
67
Canon City, Colorado
Appendix B1: Isoerodent map of Colorado. The R-Factor for Fremont County is 20.
68
Appendix B2: Physical and Chemical Properties of Fremont County Soils adapted from the Soil Survey of Fremont County Area, Colorado 1995.
Physical and Chemical Properties of the Soils
Moist Available Salinity Shrink- Erosion Wind Organic Depth Clay Bulk Permeabil Water Soil Name Soil pH (mmho swell Factors Erodibility Matter (in) (Pct) Density ity (in/hr) Capacity s/cm) Poten. (K) Group (Pct) (g/cc) (in/hr)
Boyle 0-6 10-20 1.30-1.40 2.0-6.0 0.05-0.08 6.1-7.3 <2 Low 0.15 8 2-4 Bronell 0-6 10-18 1.25-1.35 2.0-6.0 0.6-.1 7.4-8.4 <2 Low 0.05 8 0.5-2 Bundo 0-27 12-20 1.25-1.40 2.0-6.0 0.06-0.09 5.6-6.5 <2 Low 0.1 1-2 Libeg 0-7 12-19 1.65-1.50 2.0-6.0 0.02-0.05 6.6-7.3 <2 Low 0.05 2-4 Martinsdale 0-5 15-20 1.30-1.50 0.6-2.0 0.14-0.16 6.6-7.8 <2 Low 0.24 3 2-4 Mussel 0-6 12-20 1.25-1.45 2.0-6.0 0.10-0.13 7.9-8.4 <2 Low 0.17 3 .5-2 Pendant 0-4 10-25 1.20-1.30 0.6-2.0 0.06-0.08 7.4-8.4 <2 Low 0.05 8 1-3 Raleigh 0-2 8-18 1.50-1.60 6.0-20 0.04-0.06 6.1-7.3 <2 Low 0.01 8 2-4 Resort 0-12 5-15 1.30-1.40 6.0-20 0.04-0.06 6.1-7.3 <2 Low 0.1 8 2-4 Rogert 0-5 10-18 1.35-1.45 2.0-6.0 0.04-0.08 6.1-7.3 <2 Low 0.05 8 2-4 Sedillo 0-5 10-20 1.30-1.40 2.0-6.0 0.08-0.1 6.6-7.8 <2 Low 0.15 7 .5-1 Sedillo 0-3 15-25 1.20-1.30 0.6-2.0 0.07-0.10 6.6-7.8 <2 Low 0.10 7 .5-1 Seitz 0-8 15-27 1.40-1.45 2.0-6.0 0.05-0.09 6.1-7.3 <2 Low 0.10 8 .5-1 Seitz 0-15 10-20 1.45-1.50 2.0-6.0 0.09-0.12 6.1-7.3 <2 Low 0.1 6 .5-1 Swissvale 0-2 10-18 1.25-1.35 2.0-6.0 0.05-0.08 6.6-7.8 <2 Low 0.05 8 .5-1 Teaspoon 0-4 13-18 1.25-1.35 2.0-6.0 0.05-0.08 6.1-7.8 <2 Low 0.05 8 2-4 Tolex 0-5 12-20 1.35-1.45 2.0-6.0 0.05-0.09 6.1-7.3 <2 Low 0.10 8 1-3 Travessilla 0-4 5-18 1.35-1.45 0.6-2.0 0.13-0.15 6.6-8.4 <2 Low 0.20 5 .5-2 Wages 0-5 15-27 1.30-1.40 0.6-2.0 0.16-0.18 6.6-7.8 <2 Low 0.24 5 2-4
69 Appendix B3: Table for calculating C factor for pre treatment areas.
C Factors for Permanent Pasture, Rangeland, Idle Land, and Grazed Woodlands Barfield et al. 1994 (after Wischmeier and Smith, 1978)* Vegetal Canopy Cover that contacts the surface, Percentage ground Canopy cover Type and height of Cover Type**** raised canopy** (%)*** 0 20 40 60 80 95-100 No appreciable G 0.450 0.200 0.100 0.042 0.013 0.003 canopy W 0.450 0.240 0.150 0.090 0.043 0.011
Canopy of tall weeds 25 G 0.360 0.170 0.038 0.038 0.012 0.003 or short brush (0.5-m W 0.360 0.200 0.082 0.082 0.041 0.011 fall height) 50 G 0.260 0.130 0.350 0.035 0.012 0.003 W 0.260 0.160 0.750 0.075 0.039 0.011 75 G 0.170 0.100 0.031 0.031 0.011 0.003 W 0.170 0.120 0.067 0.067 0.038 0.011
Appreciable brush or 25 G 0.400 0.180 0.090 0.040 0.013 0.003 bushes (2-m fall W 0.400 0.220 0.140 0.085 0.042 0.011 height) 50 G 0.340 0.160 0.085 0.038 0.012 0.003 W 0.340 0.190 0.130 0.081 0.041 0.011 75 G 0.280 0.140 0.080 0.036 0.012 0.033 W 0.280 0.170 0.120 0.077 0.040 0.011
Trees, but no 25 G 0.420 0.190 0.100 0.041 0.013 0.003 appreciable low brush W 0.420 0.230 0.140 0.087 0.042 0.011 (4-m fall height) 50 G 0.390 0.180 0.090 0.040 0.013 0.003 W 0.390 0.210 0.140 0.085 0.042 0.011 75 G 0.360 0.170 0.090 0.039 0.012 0.003 W 0.360 0.200 0.130 0.083 0.041 0.011
* All values shown assume: (1) random distribution of mulch or vegetation and (2) mulch of appreciable depth where it exists. Idle refers to land with undisturbed profiles for at least a period of 3 consecutive years. Also to be used for burned forest land and forest land that has been harvested less than 3 years ago. ** Average fall height of water drops from canopy to soil surface in meters. *** Portion of total surface area that would be hidden from view by canopy in a vertical projection. **** G, cover at surface is grass, glasslike plants, decaying compacted duff or litter at least 2 in. deep. W, cover at surface is mostly broadleaf herbaceous plants (as weeds with little lateral root network near the surface) and/or undecayed residue.
70 Appendix B4: Table for calculating C factor for post treatment areas.
C Factors for Mechanically Prepared Woodland Sites Barfield et al. 1994 (after Wischmeier and Smith, 1978) Percentage of soil covered Soil condition and weed cover*** with residue in contact Excellent Good Fair Poor with soil surface NC WC NC WC NC WC NC WC None A. Disked, or raked* 0.52 0.20 0.72 0.27 0.85 0.32 0.94 0.36 B. Burned** 0.25 0.10 0.26 0.10 0.31 0.12 0.45 0.17 C. Drum chopped** 0.16 0.07 0.17 0.07 0.20 0.08 0.29 0.11
10% cover A. Disked, or raked* 0.33 0.15 0.46 0.20 0.54 0.24 0.60 0.26 B. Burned** 0.23 0.10 0.24 0.10 0.26 0.11 0.36 0.16 C. Drum chopped** 0.15 0.07 0.16 0.07 0.17 0.08 0.23 0.10
20% cover A. Disked, or raked* 0.24 0.12 0.34 0.17 0.40 0.20 0.44 0.29 B. Burned** 0.19 0.10 0.19 0.10 0.21 0.11 0.27 0.14 C. Drum chopped** 0.12 0.06 0.12 0.06 0.14 0.07 0.18 0.09
40% cover A. Disked, or raked* 0.17 0.11 0.23 0.14 0.27 0.17 0.30 0.19 B. Burned** 0.14 0.09 0.14 0.09 0.15 0.09 0.17 0.11 C. Drum chopped** 0.09 0.06 0.09 0.06 0.10 0.06 0.11 0.07
60% cover A. Disked, or raked* 0.11 0.08 0.15 0.11 0.18 0.14 0.20 0.15 B. Burned** 0.08 0.06 0.09 0.07 0.10 0.08 0.11 0.08 C. Drum chopped** 0.06 0.05 0.06 0.05 0.07 0.05 0.07 0.05
80% cover A. Disked, or raked* 0.05 0.04 0.07 0.06 0.09 0.08 0.10 0.09 B. Burned** 0.04 0.04 0.05 0.04 0.05 0.04 0.06 0.05 C. Drum chopped** 0.03 0.03 0.03 0.03 0.03 0.03 0.04 0.04 * Multiply A values by following values to account fro surface roughness: 0.40, Very rough, major effect on runoff and sediment, storage depressions greater than 6 in.; 0.65, moderate; 0.90, smooth, minor surface sediment storage, depression less than 2 in. The C values for A are for the first year following treatment. For A-type sites 1 to 4 years old, multiply C value by 0.7 to account for again. For sites 4 to 8 years old, use Appendix B3.
*** The C values for areas are for the first 3 years following treatment. For sites treated 3 to 8 years ago, use Appendix B3. *** NC, no weed cover, WC, weed cover.
71
Appendix B5: Table for determining P factor. This table also notes maximum length for a slope and the corresponding slope percentage.
P Values and Slope Length Limits for Contouring Land Slope Maximum Length P Value Percentage (ft)* 1 to 2 0.6 400 3 to 5 0.5 300 6 to 8 0.5 200 9 to 12 0.6 120 13 to 16 0.7 80 17 to 20 0.8 60 21 to 25 0.9 50 26+ 1 <50
Appendix B5: Selected USLE P Factors (after Wischmeier and Smith, 1978) * Limit may be increased by 25% if residue covers after crop seedings will regularly exceed 50%.
72
Appendix B6: Percent Canopy calculations preformed by John Shaw.
Plot NRCS Class Class Class Class Class No Plot_ID Code 1 2 3 4 5 Trees/acre ECOSEC D10 62 PGSC10 ABCO 1 0 0 0 0 21.78 M331F 2.716439269 60 PGSC6 ABCO 0 0 0 0 1 21.78 M331F 2.716439269 83 PGSC6 ABCO 0 0 0 0 1 21.78 M331F 2.716439269 206 PGSC6 ABCO 0 0 0 0 1 21.78 M331F 2.716439269 75 Sprucebasin1 ABCO 13 3 1 0 0 370.26 M331F 2.716439269 139 Sprucebasin1 ABCO 2 0 0 0 0 43.56 M331F 2.716439269 181 Sprucebasin1 ABCO 2 0 0 0 0 43.56 M331F 2.716439269 76 Sprucebasin2 ABCO 80 9 0 0 0 1938.4 M331F 2.716439269 140 Sprucebasin2 ABCO 16 0 0 0 0 348.48 M331F 2.716439269 180 Sprucebasin2 ABCO 34 9 0 0 0 936.54 M331F 2.716439269 77 Sprucebasin3 ABCO 13 3 4 0 0 435.6 M331F 2.716439269 141 Sprucebasin3 ABCO 6 0 0 1 0 152.46 M331F 2.716439269 184 Sprucebasin3 ABCO 1 1 0 0 0 43.56 M331F 2.716439269 78 Sprucebasin4 ABCO 10 10 3 0 2 544.5 M331F 2.716439269 142 Sprucebasin4 ABCO 5 0 0 0 2 152.46 M331F 2.716439269 183 Sprucebasin4 ABCO 7 0 0 0 2 196.02 M331F 2.716439269 79 Sprucebasin5 ABCO 0 1 0 2 0 65.34 M331F 2.716439269 143 Sprucebasin5 ABCO 1 0 0 1 0 43.56 M331F 2.716439269 178 Sprucebasin5 ABCO 1 0 0 1 0 43.56 M331F 2.716439269 80 Sprucebasin6 ABCO 1 1 1 0 0 65.34 M331F 2.716439269 144 Sprucebasin6 ABCO 1 0 0 0 0 21.78 M331F 2.716439269 177 Sprucebasin6 ABCO 1 0 0 0 0 21.78 M331F 2.716439269 157 Sprucebasin7 ABCO 8 4 11 1 1 544.5 M331F 2.716439269 179 Sprucebasin7 ABCO 0 0 1 0 0 21.78 M331F 2.716439269 158 Sprucebasin8 ABCO 0 0 0 0 1 21.78 M331F 2.716439269 65 PENROSE1 JUMO 3 0 0 0 0 65.34 331I 5.983182609 146 PENROSE1 JUMO 3 0 1 0 0 87.12 331I 5.983182609 66 PENROSE2 JUMO 1 0 0 0 0 21.78 331I 5.983182609 145 PENROSE2 JUMO 3 0 0 0 0 65.34 331I 5.983182609 70 REDCR1 JUMO 8 2 2 1 0 283.14 331I 5.983182609 85 REDCR1 JUMO 4 0 0 0 0 87.12 331I 5.983182609 71 REDCR2 JUMO 16 6 1 0 0 500.94 331I 5.983182609 84 REDCR2 JUMO 14 0 0 0 0 304.92 331I 5.983182609 72 REDCR3 JUMO 10 0 0 0 0 217.8 331I 5.983182609 171 REDCR3 JUMO 2 0 0 0 0 43.56 331I 5.983182609 73 REDCR4 JUMO 33 1 0 0 0 740.52 331I 5.983182609 154 REDCR4 JUMO 20 0 0 0 0 435.6 331I 5.983182609 74 REDCR5 JUMO 21 5 2 0 0 609.84 331I 5.983182609 153 REDCR5 JUMO 25 0 0 0 0 544.5 331I 5.983182609 5 AM3 JUMO 4 2 2 0 1 196.02 M331F 3.668836128
73 6 AM4 JUMO 7 3 1 0 0 239.58 M331F 3.668836128 242 AM4 JUMO 8 3 1 0 0 261.36 M331F 3.668836128 150 BH1 JUMO 2 0 5 1 0 174.24 M331F 3.668836128 237 BH1 JUMO 2 0 4 1 0 152.46 M331F 3.668836128 238 BH2 JUMO 0 2 2 1 0 108.9 M331F 3.668836128 169 BH3 JUMO 0 3 0 0 0 65.34 M331F 3.668836128 236 BH3 JUMO 1 3 0 0 0 87.12 M331F 3.668836128 147 NHOW1 JUMO 7 0 0 0 0 152.46 M331F 3.668836128 191 NHOW1 JUMO 7 0 0 0 0 152.46 M331F 3.668836128 47 NOCO12 JUMO 1 1 1 0 0 65.34 M331F 3.668836128 151 NOCO14 JUMO 0 0 1 0 0 21.78 M331F 3.668836128 205 NOCO14 JUMO 0 0 1 0 0 21.78 M331F 3.668836128 152 NOCO15 JUMO 2 0 0 0 0 43.56 M331F 3.668836128 40 NOCO5 JUMO 3 0 0 0 0 65.34 M331F 3.668836128 43 NOCO8 JUMO 0 1 0 0 0 21.78 M331F 3.668836128 44 NOCO9 JUMO 2 1 0 0 0 65.34 M331F 3.668836128 81 PGSC1 JUMO 4 0 0 0 0 87.12 M331F 3.668836128 210 PGSC1 JUMO 4 0 0 0 0 87.12 M331F 3.668836128 67 POVERTY1 JUMO 0 0 1 0 0 21.78 M331F 3.668836128 136 POVERTY1 JUMO 1 0 0 0 0 21.78 M331F 3.668836128 68 POVERTY2 JUMO 28 3 0 0 0 675.18 M331F 3.668836128 137 POVERTY2 JUMO 27 0 0 0 0 588.06 M331F 3.668836128 251 POVERTY2 JUMO 28 0 0 0 0 609.84 M331F 3.668836128 69 POVERTY3 JUMO 1 2 3 0 0 130.68 M331F 3.668836128 255 POVERTY3 JUMO 1 0 0 0 0 21.78 M331F 3.668836128 161 Eightmile1 JUMO 0 0 1 0 0 21.78 M331I 4.579343695 166 Eightmile7 JUMO 0 2 0 0 0 43.56 M331I 4.579343695 21 GRCNYNHLS1 JUMO 1 1 0 0 0 43.56 M331I 4.579343695 22 HECLA1 JUMO 1 0 0 0 0 21.78 M331I 4.579343695 15 DH2 JUMO 0 1 0 0 0 21.78 M331I 4.579343695 16 DH3 JUMO 1 0 1 0 0 43.56 M331I 4.579343695 167 Dawson1 JUSC2 0 8 3 0 1 261.36 331I 4.545170712 185 Dawson1 JUSC2 1 0 0 0 0 21.78 331I 4.545170712 1 AM1 JUSC2 15 0 0 0 0 326.7 M331F 4.545170712 94 AM1 JUSC2 0 2 1 0 0 65.34 M331F 4.545170712 234 AM1 JUSC2 0 2 1 0 0 65.34 M331F 4.545170712 4 AM2 JUSC2 2 0 0 0 0 43.56 M331F 4.545170712 95 AM2 JUSC2 4 1 0 0 0 108.9 M331F 4.545170712 240 AM2 JUSC2 4 1 0 0 0 108.9 M331F 4.545170712 96 AM3 JUSC2 3 2 2 0 0 152.46 M331F 4.545170712 241 AM3 JUSC2 4 2 2 0 0 174.24 M331F 4.545170712 97 AM4 JUSC2 8 3 1 0 0 261.36 M331F 4.545170712 7 AM5 JUSC2 2 0 0 0 0 43.56 M331F 4.545170712 98 AM5 JUSC2 2 0 0 0 0 43.56 M331F 4.545170712 230 AM5 JUSC2 2 0 0 0 0 43.56 M331F 4.545170712 8 AM6 JUSC2 6 0 0 0 0 130.68 M331F 4.545170712 99 AM6 JUSC2 2 0 0 0 0 43.56 M331F 4.545170712
74 232 AM6 JUSC2 2 0 0 0 0 43.56 M331F 4.545170712 9 AM7 JUSC2 2 0 0 0 0 43.56 M331F 4.545170712 100 AM7 JUSC2 1 0 0 0 0 21.78 M331F 4.545170712 231 AM7 JUSC2 1 0 0 0 0 21.78 M331F 4.545170712 10 AM8 JUSC2 0 0 1 0 0 21.78 M331F 4.545170712 101 AM8 JUSC2 0 0 1 0 0 21.78 M331F 4.545170712 233 AM8 JUSC2 0 0 1 0 0 21.78 M331F 4.545170712 168 BH2 JUSC2 0 2 2 1 0 108.9 M331F 4.545170712 175 IM1 JUSC2 1 0 1 0 0 43.56 M331F 4.545170712 174 IM3 JUSC2 1 0 0 0 0 21.78 M331F 4.545170712 49 NHOW1 JUSC2 9 1 1 0 0 239.58 M331F 4.545170712 50 NHOW2 JUSC2 1 0 0 0 0 21.78 M331F 4.545170712 51 NHOW3 JUSC2 0 0 0 1 0 21.78 M331F 4.545170712 53 NHOW5 JUSC2 3 1 0 1 1 130.68 M331F 4.545170712 134 NHOW5 JUSC2 0 1 0 0 0 21.78 M331F 4.545170712 187 NHOW5 JUSC2 1 1 0 0 0 43.56 M331F 4.545170712 54 NHOW6 JUSC2 1 0 1 0 0 43.56 M331F 4.545170712 186 NHOW6 JUSC2 1 0 0 0 0 21.78 M331F 4.545170712 36 NOCO1 JUSC2 2 2 1 0 0 108.9 M331F 4.545170712 120 NOCO1 JUSC2 1 0 0 0 0 21.78 M331F 4.545170712 192 NOCO1 JUSC2 1 0 0 0 0 21.78 M331F 4.545170712 45 NOCO10 JUSC2 3 0 1 0 0 87.12 M331F 4.545170712 131 NOCO12 JUSC2 2 1 1 0 0 87.12 M331F 4.545170712 203 NOCO12 JUSC2 2 1 1 0 0 87.12 M331F 4.545170712 48 NOCO13 JUSC2 0 1 0 0 1 43.56 M331F 4.545170712 132 NOCO13 JUSC2 0 0 0 0 1 21.78 M331F 4.545170712 195 NOCO13 JUSC2 0 0 0 0 1 21.78 M331F 4.545170712 37 NOCO2 JUSC2 0 0 1 1 0 43.56 M331F 4.545170712 121 NOCO2 JUSC2 1 0 1 0 0 43.56 M331F 4.545170712 193 NOCO2 JUSC2 1 0 1 0 0 43.56 M331F 4.545170712 38 NOCO3 JUSC2 4 0 2 1 0 152.46 M331F 4.545170712 122 NOCO3 JUSC2 3 0 1 2 0 130.68 M331F 4.545170712 194 NOCO3 JUSC2 3 0 1 2 0 130.68 M331F 4.545170712 123 NOCO4 JUSC2 1 0 0 0 0 21.78 M331F 4.545170712 197 NOCO4 JUSC2 1 0 0 0 0 21.78 M331F 4.545170712 124 NOCO5 JUSC2 3 0 0 0 0 65.34 M331F 4.545170712 200 NOCO5 JUSC2 3 0 0 0 0 65.34 M331F 4.545170712 41 NOCO6 JUSC2 4 11 1 0 0 348.48 M331F 4.545170712 125 NOCO6 JUSC2 5 5 1 0 0 239.58 M331F 4.545170712 201 NOCO6 JUSC2 5 5 1 0 0 239.58 M331F 4.545170712 42 NOCO7 JUSC2 4 7 2 0 0 283.14 M331F 4.545170712 126 NOCO7 JUSC2 1 1 2 0 0 87.12 M331F 4.545170712 239 NOCO7 JUSC2 1 1 2 0 0 87.12 M331F 4.545170712 43 NOCO8 JUSC2 2 1 2 0 1 130.68 M331F 4.545170712 128 NOCO9 JUSC2 2 0 0 0 0 43.56 M331F 4.545170712 204 NOCO9 JUSC2 3 0 0 0 0 65.34 M331F 4.545170712
75 55 PGSC1 JUSC2 2 2 1 1 0 130.68 M331F 4.545170712 62 PGSC10 JUSC2 22 0 0 1 0 500.94 M331F 4.545170712 63 PGSC11 JUSC2 21 0 0 0 0 457.38 M331F 4.545170712 92 PGSC11 JUSC2 4 0 0 0 0 87.12 M331F 4.545170712 212 PGSC11 JUSC2 4 0 0 0 0 87.12 M331F 4.545170712 64 PGSC12 JUSC2 0 0 1 0 0 21.78 M331F 4.545170712 56 PGSC2 JUSC2 2 1 0 0 0 65.34 M331F 4.545170712 88 PGSC2 JUSC2 2 1 0 0 0 65.34 M331F 4.545170712 209 PGSC2 JUSC2 2 1 0 0 0 65.34 M331F 4.545170712 57 PGSC3 JUSC2 1 1 1 0 0 65.34 M331F 4.545170712 89 PGSC3 JUSC2 1 1 1 0 0 65.34 M331F 4.545170712 208 PGSC3 JUSC2 1 1 1 0 0 65.34 M331F 4.545170712 59 PGSC5 JUSC2 3 0 1 0 0 87.12 M331F 4.545170712 87 PGSC5 JUSC2 5 0 1 0 0 130.68 M331F 4.545170712 214 PGSC5 JUSC2 5 0 1 0 0 130.68 M331F 4.545170712 61 PGSC7 JUSC2 3 0 0 0 0 65.34 M331F 4.545170712 90 PGSC7 JUSC2 5 0 0 0 0 108.9 M331F 4.545170712 213 PGSC7 JUSC2 5 0 0 0 0 108.9 M331F 4.545170712 155 POVERTY4 JUSC2 15 2 0 2 0 413.82 M331F 4.545170712 254 POVERTY4 JUSC2 15 2 0 2 0 413.82 M331F 4.545170712 156 POVERTY5 JUSC2 11 2 2 1 0 348.48 M331F 4.545170712 252 POVERTY5 JUSC2 13 2 2 1 0 392.04 M331F 4.545170712 264 RdG1 JUSC2 3 0 0 0 0 65.34 M331F 4.545170712 265 RdG2 JUSC2 18 2 3 0 0 500.94 M331F 4.545170712 266 RdG3 JUSC2 6 1 1 0 0 174.24 M331F 4.545170712 75 Sprucebasin1 JUSC2 0 3 0 0 0 65.34 M331F 4.545170712 77 Sprucebasin3 JUSC2 0 3 0 0 0 65.34 M331F 4.545170712 141 Sprucebasin3 JUSC2 1 0 0 0 0 21.78 M331F 4.545170712 80 Sprucebasin6 JUSC2 0 2 0 0 0 43.56 M331F 4.545170712 158 Sprucebasin8 JUSC2 1 0 0 0 0 21.78 M331F 4.545170712 182 Sprucebasin8 JUSC2 1 0 0 0 0 21.78 M331F 4.545170712 243 Eightmile7 JUSC2 1 0 0 0 0 21.78 M331I 4.545170712
117 GRCNYNHLS1 JUSC2 1 1 0 0 0 43.56 M331I 4.545170712
253 GRCNYNHLS1 JUSC2 2 0 0 0 0 43.56 M331I 4.545170712 165 DH10 JUSC2 1 0 0 0 0 21.78 M331I 4.545170712 106 DH2 JUSC2 0 1 0 0 0 21.78 M331I 4.545170712 224 DH2 JUSC2 0 1 0 0 0 21.78 M331I 4.545170712 107 DH3 JUSC2 0 0 1 0 0 21.78 M331I 4.545170712 223 DH3 JUSC2 0 0 1 0 0 21.78 M331I 4.545170712 18 DH5 JUSC2 1 0 0 0 0 21.78 M331I 4.545170712 109 DH5 JUSC2 1 0 0 0 0 21.78 M331I 4.545170712 228 DH5 JUSC2 1 0 0 0 0 21.78 M331I 4.545170712 111 DH7 JUSC2 1 0 0 0 0 21.78 M331I 4.545170712 115 DH9 JUSC2 2 0 0 0 0 43.56 M331I 4.545170712 116 DH9 JUSC2 1 0 0 0 0 21.78 M331I 4.545170712
76 227 DH9 JUSC2 1 0 0 0 0 21.78 M331I 4.545170712 167 Dawson1 PIED 28 17 4 6 2 1241.5 331I 3.121537563 185 Dawson1 PIED 4 0 0 0 0 87.12 331I 3.121537563 172 Dawson2 PIED 25 4 6 4 0 849.42 331I 3.121537563 65 PENROSE1 PIED 4 0 0 0 0 87.12 331I 3.121537563 146 PENROSE1 PIED 2 0 0 0 0 43.56 331I 3.121537563 66 PENROSE2 PIED 1 0 0 0 0 21.78 331I 3.121537563 71 REDCR2 PIED 1 0 0 0 0 21.78 331I 3.121537563 84 REDCR2 PIED 1 0 0 0 0 21.78 331I 3.121537563 1 AM1 PIED 57 1 3 3 0 1393.9 M331F 2.611669395 94 AM1 PIED 84 0 5 4 0 2025.5 M331F 2.611669395 234 AM1 PIED 89 0 5 4 0 2134.4 M331F 2.611669395 4 AM2 PIED 9 14 4 5 0 696.96 M331F 2.611669395 95 AM2 PIED 16 10 5 6 0 805.86 M331F 2.611669395 240 AM2 PIED 17 10 5 6 0 827.64 M331F 2.611669395 5 AM3 PIED 16 0 1 3 0 435.6 M331F 2.611669395 96 AM3 PIED 26 0 0 3 0 631.62 M331F 2.611669395 241 AM3 PIED 26 0 0 0 0 566.28 M331F 2.611669395 6 AM4 PIED 14 2 0 0 0 348.48 M331F 2.611669395 97 AM4 PIED 18 2 0 0 0 435.6 M331F 2.611669395 242 AM4 PIED 19 2 0 0 0 457.38 M331F 2.611669395 7 AM5 PIED 2 1 0 0 0 65.34 M331F 2.611669395 98 AM5 PIED 0 1 0 0 0 21.78 M331F 2.611669395 230 AM5 PIED 0 1 0 0 0 21.78 M331F 2.611669395 9 AM7 PIED 2 0 0 0 0 43.56 M331F 2.611669395 10 AM8 PIED 2 0 0 0 0 43.56 M331F 2.611669395 101 AM8 PIED 1 0 0 0 0 21.78 M331F 2.611669395 233 AM8 PIED 1 0 0 0 0 21.78 M331F 2.611669395 150 BH1 PIED 7 0 3 1 0 239.58 M331F 2.611669395 237 BH1 PIED 7 0 3 1 0 239.58 M331F 2.611669395 168 BH2 PIED 3 9 10 1 0 500.94 M331F 2.611669395 238 BH2 PIED 3 9 10 1 0 500.94 M331F 2.611669395 169 BH3 PIED 11 1 1 4 0 370.26 M331F 2.611669395 236 BH3 PIED 12 1 0 3 0 348.48 M331F 2.611669395 49 NHOW1 PIED 48 9 3 2 0 1350.4 M331F 2.611669395 147 NHOW1 PIED 15 8 3 0 0 566.28 M331F 2.611669395 191 NHOW1 PIED 15 8 3 0 0 566.28 M331F 2.611669395 50 NHOW2 PIED 3 1 4 3 0 239.58 M331F 2.611669395 148 NHOW2 PIED 3 0 0 0 0 65.34 M331F 2.611669395 190 NHOW2 PIED 3 0 0 0 0 65.34 M331F 2.611669395 51 NHOW3 PIED 2 1 3 5 0 239.58 M331F 2.611669395 52 NHOW4 PIED 1 1 5 7 0 304.92 M331F 2.611669395 149 NHOW4 PIED 1 0 0 1 0 43.56 M331F 2.611669395 188 NHOW4 PIED 1 0 0 1 0 43.56 M331F 2.611669395 53 NHOW5 PIED 13 8 15 2 1 849.42 M331F 2.611669395 134 NHOW5 PIED 3 4 0 1 0 174.24 M331F 2.611669395 187 NHOW5 PIED 3 4 0 1 0 174.24 M331F 2.611669395
77 54 NHOW6 PIED 18 2 9 4 0 718.74 M331F 2.611669395 135 NHOW6 PIED 0 3 3 2 0 174.24 M331F 2.611669395 186 NHOW6 PIED 0 3 3 2 0 174.24 M331F 2.611669395 36 NOCO1 PIED 3 0 0 0 0 65.34 M331F 2.611669395 120 NOCO1 PIED 1 0 0 0 0 21.78 M331F 2.611669395 192 NOCO1 PIED 1 0 0 0 0 21.78 M331F 2.611669395 45 NOCO10 PIED 1 2 6 6 0 326.7 M331F 2.611669395 47 NOCO12 PIED 6 0 1 4 1 261.36 M331F 2.611669395 131 NOCO12 PIED 1 0 1 4 1 152.46 M331F 2.611669395 203 NOCO12 PIED 1 0 1 4 1 152.46 M331F 2.611669395 48 NOCO13 PIED 4 2 1 2 0 196.02 M331F 2.611669395 132 NOCO13 PIED 1 0 0 0 0 21.78 M331F 2.611669395 195 NOCO13 PIED 2 0 0 0 0 43.56 M331F 2.611669395 151 NOCO14 PIED 0 0 0 3 0 65.34 M331F 2.611669395 205 NOCO14 PIED 0 0 0 4 0 87.12 M331F 2.611669395 152 NOCO15 PIED 2 0 8 1 0 239.58 M331F 2.611669395 37 NOCO2 PIED 0 0 2 2 0 87.12 M331F 2.611669395 121 NOCO2 PIED 0 0 2 2 0 87.12 M331F 2.611669395 193 NOCO2 PIED 0 0 2 2 0 87.12 M331F 2.611669395 38 NOCO3 PIED 2 0 0 2 0 87.12 M331F 2.611669395 122 NOCO3 PIED 1 0 0 0 0 21.78 M331F 2.611669395 194 NOCO3 PIED 1 0 0 0 0 21.78 M331F 2.611669395 39 NOCO4 PIED 7 0 1 0 0 174.24 M331F 2.611669395 123 NOCO4 PIED 2 0 1 0 0 65.34 M331F 2.611669395 197 NOCO4 PIED 2 0 1 0 0 65.34 M331F 2.611669395 40 NOCO5 PIED 21 3 3 2 0 631.62 M331F 2.611669395 124 NOCO5 PIED 0 1 0 0 0 21.78 M331F 2.611669395 200 NOCO5 PIED 0 1 0 0 0 21.78 M331F 2.611669395 41 NOCO6 PIED 7 11 4 0 0 479.16 M331F 2.611669395 125 NOCO6 PIED 0 1 2 0 0 65.34 M331F 2.611669395 201 NOCO6 PIED 0 1 2 0 0 65.34 M331F 2.611669395 42 NOCO7 PIED 4 2 2 0 0 174.24 M331F 2.611669395 126 NOCO7 PIED 3 1 0 0 0 87.12 M331F 2.611669395 239 NOCO7 PIED 3 1 0 0 0 87.12 M331F 2.611669395 43 NOCO8 PIED 10 1 3 1 0 326.7 M331F 2.611669395 127 NOCO8 PIED 4 0 0 0 0 87.12 M331F 2.611669395 202 NOCO8 PIED 4 0 0 0 0 87.12 M331F 2.611669395 44 NOCO9 PIED 6 1 0 1 0 174.24 M331F 2.611669395 128 NOCO9 PIED 5 0 0 0 0 108.9 M331F 2.611669395 204 NOCO9 PIED 5 0 0 0 0 108.9 M331F 2.611669395 62 PGSC10 PIED 1 0 0 3 0 87.12 M331F 2.611669395 91 PGSC10 PIED 2 0 0 0 0 43.56 M331F 2.611669395 215 PGSC10 PIED 3 0 0 0 0 65.34 M331F 2.611669395 63 PGSC11 PIED 11 2 5 0 0 392.04 M331F 2.611669395 92 PGSC11 PIED 1 0 0 0 0 21.78 M331F 2.611669395 212 PGSC11 PIED 3 0 0 0 0 65.34 M331F 2.611669395 64 PGSC12 PIED 4 1 4 0 0 196.02 M331F 2.611669395
78 56 PGSC2 PIED 2 0 2 1 0 108.9 M331F 2.611669395 88 PGSC2 PIED 2 0 2 1 0 108.9 M331F 2.611669395 209 PGSC2 PIED 2 0 2 1 0 108.9 M331F 2.611669395 57 PGSC3 PIED 1 0 0 0 0 21.78 M331F 2.611669395 89 PGSC3 PIED 1 0 0 0 0 21.78 M331F 2.611669395 208 PGSC3 PIED 1 0 0 0 0 21.78 M331F 2.611669395 58 PGSC4 PIED 0 0 1 0 0 21.78 M331F 2.611669395 82 PGSC4 PIED 0 0 1 0 0 21.78 M331F 2.611669395 207 PGSC4 PIED 0 0 1 0 0 21.78 M331F 2.611669395 67 POVERTY1 PIED 8 3 4 2 0 370.26 M331F 2.611669395 136 POVERTY1 PIED 2 0 1 0 0 65.34 M331F 2.611669395 250 POVERTY1 PIED 3 0 1 0 0 87.12 M331F 2.611669395 68 POVERTY2 PIED 17 0 0 0 0 370.26 M331F 2.611669395 137 POVERTY2 PIED 3 0 0 0 0 65.34 M331F 2.611669395 251 POVERTY2 PIED 5 0 0 0 0 108.9 M331F 2.611669395 69 POVERTY3 PIED 5 6 17 5 0 718.74 M331F 2.611669395 138 POVERTY3 PIED 0 0 2 2 0 87.12 M331F 2.611669395 255 POVERTY3 PIED 2 0 2 2 0 130.68 M331F 2.611669395 155 POVERTY4 PIED 8 2 1 2 0 283.14 M331F 2.611669395 254 POVERTY4 PIED 9 2 1 0 0 261.36 M331F 2.611669395 156 POVERTY5 PIED 12 0 2 0 0 304.92 M331F 2.611669395 264 RdG1 PIED 3 2 3 3 2 283.14 M331F 2.611669395 265 RdG2 PIED 9 5 4 0 0 392.04 M331F 2.611669395 266 RdG3 PIED 25 1 0 0 0 566.28 M331F 2.611669395 256 CH1 PIED 2 9 8 4 0 500.94 M331I 3.121537563 257 CH2 PIED 3 2 7 4 1 370.26 M331I 3.121537563 258 CH3 PIED 9 6 4 2 0 457.38 M331I 3.121537563 161 Eightmile1 PIED 9 1 0 1 1 261.36 M331I 3.121537563 244 Eightmile1 PIED 1 0 0 0 1 43.56 M331I 3.121537563 160 Eightmile2 PIED 15 2 0 1 0 392.04 M331I 3.121537563 247 Eightmile2 PIED 3 0 0 0 0 65.34 M331I 3.121537563 159 Eightmile3 PIED 7 0 0 0 0 152.46 M331I 3.121537563 245 Eightmile3 PIED 4 0 0 0 0 87.12 M331I 3.121537563 163 Eightmile4 PIED 3 1 1 0 0 108.9 M331I 3.121537563 248 Eightmile4 PIED 1 0 0 0 0 21.78 M331I 3.121537563 164 Eightmile5 PIED 0 2 0 0 0 43.56 M331I 3.121537563 246 Eightmile5 PIED 1 0 0 0 0 21.78 M331I 3.121537563 162 Eightmile6 PIED 2 2 1 0 0 108.9 M331I 3.121537563 249 Eightmile6 PIED 1 0 0 0 0 21.78 M331I 3.121537563 166 Eightmile7 PIED 11 35 0 2 0 1045.4 M331I 3.121537563 243 Eightmile7 PIED 16 0 0 2 0 392.04 M331I 3.121537563 21 GRCNYNHLS1 PIED 53 1 0 0 0 1176.1 M331I 3.121537563 117 GRCNYNHLS1 PIED 22 0 0 0 0 479.16 M331I 3.121537563 253 GRCNYNHLS1 PIED 9 0 0 0 0 196.02 M331I 3.121537563 22 HECLA1 PIED 2 1 4 1 0 174.24 M331I 3.121537563 118 HECLA1 PIED 1 0 1 0 0 43.56 M331I 3.121537563 23 HECLA2 PIED 0 0 3 4 0 152.46 M331I 3.121537563
79 14 DH1 PIED 2 0 0 0 0 43.56 M331I 3.121537563 219 DH12 PIED 3 0 2 0 0 108.9 M331I 3.121537563 107 DH3 PIED 1 0 0 0 0 21.78 M331I 3.121537563 223 DH3 PIED 1 0 0 0 0 21.78 M331I 3.121537563 113 DH8 PIED 1 0 0 0 0 21.78 M331I 3.121537563 78 Sprucebasin4 PIEN 3 3 3 3 1 283.14 M331F 2.654605562 73 REDCR4 PIPO 2 0 0 0 0 43.56 331I 2.349632821 154 REDCR4 PIPO 2 0 0 0 0 43.56 331I 2.349632821 6 AM4 PIPO 10 6 0 0 1 370.26 M331F 2.460367604 97 AM4 PIPO 13 1 2 0 1 370.26 M331F 2.460367604 242 AM4 PIPO 13 1 2 0 1 370.26 M331F 2.460367604 7 AM5 PIPO 7 4 1 0 1 283.14 M331F 2.460367604 98 AM5 PIPO 5 4 1 0 2 261.36 M331F 2.460367604 230 AM5 PIPO 5 4 1 0 2 261.36 M331F 2.460367604 8 AM6 PIPO 9 1 1 2 2 326.7 M331F 2.460367604 99 AM6 PIPO 4 0 0 0 2 130.68 M331F 2.460367604 232 AM6 PIPO 4 0 0 0 0 87.12 M331F 2.460367604 9 AM7 PIPO 5 1 0 2 2 217.8 M331F 2.460367604 100 AM7 PIPO 4 1 0 2 2 196.02 M331F 2.460367604 231 AM7 PIPO 4 1 0 2 2 196.02 M331F 2.460367604 10 AM8 PIPO 3 3 0 0 0 130.68 M331F 2.460367604 101 AM8 PIPO 3 2 0 0 0 108.9 M331F 2.460367604 233 AM8 PIPO 3 2 0 0 0 108.9 M331F 2.460367604 152 NOCO15 PIPO 1 0 0 0 0 21.78 M331F 2.460367604 39 NOCO4 PIPO 0 1 0 0 0 21.78 M331F 2.460367604 123 NOCO4 PIPO 0 0 1 0 0 21.78 M331F 2.460367604 197 NOCO4 PIPO 0 0 1 0 0 21.78 M331F 2.460367604 40 NOCO5 PIPO 0 0 0 0 1 21.78 M331F 2.460367604 124 NOCO5 PIPO 0 0 0 0 1 21.78 M331F 2.460367604 200 NOCO5 PIPO 0 0 0 0 1 21.78 M331F 2.460367604 59 PGSC5 PIPO 0 1 0 1 0 43.56 M331F 2.460367604 87 PGSC5 PIPO 0 1 0 1 0 43.56 M331F 2.460367604 214 PGSC5 PIPO 0 1 1 0 0 43.56 M331F 2.460367604 61 PGSC7 PIPO 0 0 0 7 0 152.46 M331F 2.460367604 90 PGSC7 PIPO 0 0 0 5 0 108.9 M331F 2.460367604 213 PGSC7 PIPO 0 0 0 4 0 87.12 M331F 2.460367604 67 POVERTY1 PIPO 0 0 0 0 1 21.78 M331F 2.460367604 136 POVERTY1 PIPO 0 0 1 0 1 43.56 M331F 2.460367604 250 POVERTY1 PIPO 0 0 1 0 1 43.56 M331F 2.460367604 155 POVERTY4 PIPO 0 0 1 0 0 21.78 M331F 2.460367604 254 POVERTY4 PIPO 0 0 1 0 0 21.78 M331F 2.460367604 156 POVERTY5 PIPO 0 0 1 4 2 152.46 M331F 2.460367604 252 POVERTY5 PIPO 1 0 1 4 2 174.24 M331F 2.460367604 265 RdG2 PIPO 0 0 0 1 1 43.56 M331F 2.460367604 266 RdG3 PIPO 6 0 0 1 4 239.58 M331F 2.460367604 75 Sprucebasin1 PIPO 0 0 0 0 2 43.56 M331F 2.460367604 139 Sprucebasin1 PIPO 0 0 0 1 0 21.78 M331F 2.460367604
80 181 Sprucebasin1 PIPO 0 0 0 1 0 21.78 M331F 2.460367604 77 Sprucebasin3 PIPO 3 0 0 1 0 87.12 M331F 2.460367604 141 Sprucebasin3 PIPO 2 0 0 0 0 43.56 M331F 2.460367604 184 Sprucebasin3 PIPO 2 0 0 0 0 43.56 M331F 2.460367604 79 Sprucebasin5 PIPO 1 2 0 1 2 130.68 M331F 2.460367604 143 Sprucebasin5 PIPO 0 2 0 1 1 87.12 M331F 2.460367604 178 Sprucebasin5 PIPO 0 2 0 1 1 87.12 M331F 2.460367604 80 Sprucebasin6 PIPO 1 0 0 0 0 21.78 M331F 2.460367604 144 Sprucebasin6 PIPO 1 0 0 0 0 21.78 M331F 2.460367604 177 Sprucebasin6 PIPO 1 0 0 0 0 21.78 M331F 2.460367604 259 CM1 PIPO 3 11 2 1 0 370.26 M331I 2.349632821 260 CM2 PIPO 2 1 1 0 1 108.9 M331I 2.349632821 217 LM1 PIPO 25 7 2 1 0 762.3 M331I 2.349632821 216 LM2 PIPO 65 0 2 0 7 1611.7 M331I 2.349632821 14 DH1 PIPO 5 0 0 0 2 152.46 M331I 2.349632821 105 DH1 PIPO 2 0 0 0 2 87.12 M331I 2.349632821 225 DH1 PIPO 2 0 0 0 0 43.56 M331I 2.349632821 165 DH10 PIPO 0 0 0 2 1 65.34 M331I 2.349632821 229 DH10 PIPO 0 0 0 2 1 65.34 M331I 2.349632821 219 DH12 PIPO 0 1 1 1 0 65.34 M331I 2.349632821 15 DH2 PIPO 5 0 0 0 1 130.68 M331I 2.349632821 106 DH2 PIPO 4 0 0 0 0 87.12 M331I 2.349632821 224 DH2 PIPO 5 0 0 0 0 108.9 M331I 2.349632821 16 DH3 PIPO 1 0 0 0 4 108.9 M331I 2.349632821 107 DH3 PIPO 1 0 0 0 4 108.9 M331I 2.349632821 223 DH3 PIPO 1 0 0 0 4 108.9 M331I 2.349632821 17 DH4 PIPO 0 0 1 3 3 152.46 M331I 2.349632821 108 DH4 PIPO 0 0 0 2 4 130.68 M331I 2.349632821 220 DH4 PIPO 1 0 0 2 4 152.46 M331I 2.349632821 18 DH5 PIPO 0 0 0 0 1 21.78 M331I 2.349632821 109 DH5 PIPO 1 0 0 1 0 43.56 M331I 2.349632821 19 DH6 PIPO 5 0 5 5 0 326.7 M331I 2.349632821 110 DH6 PIPO 0 0 6 5 0 239.58 M331I 2.349632821 221 DH6 PIPO 0 0 0 6 5 239.58 M331I 2.349632821 111 DH7 PIPO 17 3 0 0 0 435.6 M331I 2.349632821 113 DH8 PIPO 12 0 1 0 0 283.14 M331I 2.349632821 114 DH8 PIPO 1 0 0 0 0 21.78 M331I 2.349632821 226 DH8 PIPO 1 0 0 0 0 21.78 M331I 2.349632821 115 DH9 PIPO 6 0 0 2 3 239.58 M331I 2.349632821 116 DH9 PIPO 2 0 0 2 4 174.24 M331I 2.349632821 227 DH9 PIPO 2 0 0 2 4 174.24 M331I 2.349632821 75 Sprucebasin1 POTR5 3 1 0 0 0 87.12 M331F 2.415460834 139 Sprucebasin1 POTR5 2 0 0 0 0 43.56 M331F 2.415460834 181 Sprucebasin1 POTR5 5 0 0 0 0 108.9 M331F 2.415460834 76 Sprucebasin2 POTR5 82 9 7 0 0 2134.4 M331F 2.415460834 140 Sprucebasin2 POTR5 50 0 4 2 0 1219.7 M331F 2.415460834 180 Sprucebasin2 POTR5 86 6 0 0 0 2003.8 M331F 2.415460834
81 77 Sprucebasin3 POTR5 34 8 2 2 0 1001.9 M331F 2.415460834 141 Sprucebasin3 POTR5 23 0 1 1 0 544.5 M331F 2.415460834 184 Sprucebasin3 POTR5 97 1 2 1 0 2199.8 M331F 2.415460834 78 Sprucebasin4 POTR5 2 0 0 1 0 65.34 M331F 2.415460834 142 Sprucebasin4 POTR5 5 0 1 1 0 152.46 M331F 2.415460834 183 Sprucebasin4 POTR5 12 0 1 1 0 304.92 M331F 2.415460834 79 Sprucebasin5 POTR5 30 1 0 0 0 675.18 M331F 2.415460834 143 Sprucebasin5 POTR5 24 1 0 0 0 544.5 M331F 2.415460834 178 Sprucebasin5 POTR5 28 1 0 0 0 631.62 M331F 2.415460834 80 Sprucebasin6 POTR5 27 6 1 0 0 740.52 M331F 2.415460834 144 Sprucebasin6 POTR5 22 3 1 0 0 566.28 M331F 2.415460834 177 Sprucebasin6 POTR5 24 3 1 0 0 609.84 M331F 2.415460834 157 Sprucebasin7 POTR5 5 4 1 2 0 261.36 M331F 2.415460834 179 Sprucebasin7 POTR5 9 0 0 2 0 239.58 M331F 2.415460834 158 Sprucebasin8 POTR5 12 0 0 5 0 370.26 M331F 2.415460834 182 Sprucebasin8 POTR5 13 0 0 5 0 392.04 M331F 2.415460834 1 AM1 PSME 15 0 0 0 0 326.7 M331F 2.877398415 94 AM1 PSME 6 0 0 0 0 130.68 M331F 2.877398415 234 AM1 PSME 5 0 0 0 0 108.9 M331F 2.877398415 95 AM2 PSME 3 0 0 0 0 65.34 M331F 2.877398415 240 AM2 PSME 4 0 0 0 0 87.12 M331F 2.877398415 5 AM3 PSME 37 0 0 1 3 892.98 M331F 2.877398415 96 AM3 PSME 28 0 0 1 2 675.18 M331F 2.877398415 241 AM3 PSME 29 0 0 1 2 696.96 M331F 2.877398415 6 AM4 PSME 2 1 0 1 0 87.12 M331F 2.877398415 97 AM4 PSME 0 1 0 1 1 65.34 M331F 2.877398415 7 AM5 PSME 16 1 3 1 1 479.16 M331F 2.877398415 98 AM5 PSME 18 2 3 2 0 544.5 M331F 2.877398415 230 AM5 PSME 18 2 3 2 0 544.5 M331F 2.877398415 8 AM6 PSME 28 2 1 0 0 675.18 M331F 2.877398415 99 AM6 PSME 28 2 1 2 0 718.74 M331F 2.877398415 232 AM6 PSME 28 2 1 2 0 718.74 M331F 2.877398415 9 AM7 PSME 1 0 0 0 0 21.78 M331F 2.877398415 100 AM7 PSME 1 0 0 0 0 21.78 M331F 2.877398415 231 AM7 PSME 1 0 0 0 0 21.78 M331F 2.877398415 10 AM8 PSME 0 0 0 1 0 21.78 M331F 2.877398415 101 AM8 PSME 0 0 0 1 0 21.78 M331F 2.877398415 233 AM8 PSME 0 0 0 1 0 21.78 M331F 2.877398415 45 NOCO10 PSME 1 0 0 0 0 21.78 M331F 2.877398415 68 POVERTY2 PSME 63 1 2 2 1 1502.8 M331F 2.877398415 137 POVERTY2 PSME 51 0 0 2 1 1176.1 M331F 2.877398415 251 POVERTY2 PSME 52 0 0 2 1 1197.9 M331F 2.877398415 155 POVERTY4 PSME 3 1 2 0 0 130.68 M331F 2.877398415 254 POVERTY4 PSME 3 1 2 0 0 130.68 M331F 2.877398415 156 POVERTY5 PSME 5 1 0 0 0 130.68 M331F 2.877398415 252 POVERTY5 PSME 6 1 0 0 0 152.46 M331F 2.877398415 75 Sprucebasin1 PSME 7 0 0 0 3 217.8 M331F 2.877398415
82 139 Sprucebasin1 PSME 1 0 0 0 3 87.12 M331F 2.877398415 181 Sprucebasin1 PSME 1 0 0 0 3 87.12 M331F 2.877398415 76 Sprucebasin2 PSME 34 6 0 0 0 871.2 M331F 2.877398415 140 Sprucebasin2 PSME 11 0 0 0 0 239.58 M331F 2.877398415 180 Sprucebasin2 PSME 82 9 7 0 0 2134.4 M331F 2.877398415 77 Sprucebasin3 PSME 8 3 0 0 0 239.58 M331F 2.877398415 141 Sprucebasin3 PSME 5 0 1 0 0 130.68 M331F 2.877398415 184 Sprucebasin3 PSME 1 0 0 0 0 21.78 M331F 2.877398415 78 Sprucebasin4 PSME 2 0 0 0 0 43.56 M331F 2.877398415 142 Sprucebasin4 PSME 0 0 0 1 1 43.56 M331F 2.877398415 183 Sprucebasin4 PSME 0 0 0 1 1 43.56 M331F 2.877398415 79 Sprucebasin5 PSME 0 1 0 0 0 21.78 M331F 2.877398415 80 Sprucebasin6 PSME 1 0 1 0 0 43.56 M331F 2.877398415 144 Sprucebasin6 PSME 1 0 0 0 0 21.78 M331F 2.877398415 177 Sprucebasin6 PSME 1 0 0 0 0 21.78 M331F 2.877398415 157 Sprucebasin7 PSME 1 1 0 2 0 87.12 M331F 2.877398415 179 Sprucebasin7 PSME 0 0 0 2 1 65.34 M331F 2.877398415 158 Sprucebasin8 PSME 2 0 0 0 2 87.12 M331F 2.877398415 182 Sprucebasin8 PSME 2 0 0 0 2 87.12 M331F 2.877398415 165 DH10 PSME 5 0 0 1 1 152.46 M331I 4.634469197 229 DH10 PSME 1 0 0 0 0 21.78 M331I 4.634469197 15 DH2 PSME 23 15 1 0 0 849.42 M331I 4.634469197 106 DH2 PSME 46 17 1 0 1 1415.7 M331I 4.634469197 224 DH2 PSME 46 17 1 0 1 1415.7 M331I 4.634469197 16 DH3 PSME 0 0 1 0 0 21.78 M331I 4.634469197 107 DH3 PSME 0 0 1 0 0 21.78 M331I 4.634469197 223 DH3 PSME 0 0 1 0 0 21.78 M331I 4.634469197 17 DH4 PSME 3 0 1 0 0 87.12 M331I 4.634469197 108 DH4 PSME 0 0 0 1 0 21.78 M331I 4.634469197 220 DH4 PSME 0 0 0 1 0 21.78 M331I 4.634469197 19 DH6 PSME 1 0 0 0 0 21.78 M331I 4.634469197 111 DH7 PSME 1 0 1 0 0 43.56 M331I 4.634469197 112 DH7 PSME 1 0 0 0 0 21.78 M331I 4.634469197 218 DH7 PSME 1 0 0 0 0 21.78 M331I 4.634469197
83
Tree Count * Crown Area Tree Count * Crown Area * 21.78
Plot No D05 D20 D45 D90 D15 D05 D20 D45 D90 D15 CCTot 62 1.4 0.0 0.0 0.0 0.0 31.6 0.0 0.0 0.0 0.0 31.6 60 0.0 0.0 0.0 0.0 172.0 0.0 0.0 0.0 0.0 3746.4 3746.4 83 0.0 0.0 0.0 0.0 172.0 0.0 0.0 0.0 0.0 3746.4 3746.4 206 0.0 0.0 0.0 0.0 172.0 0.0 0.0 0.0 0.0 3746.4 3746.4 75 18.8 41.4 38.1 0.0 0.0 410.2 901.9 829.8 0.0 0.0 2141.9 139 2.9 0.0 0.0 0.0 0.0 63.1 0.0 0.0 0.0 0.0 63.1 181 2.9 0.0 0.0 0.0 0.0 63.1 0.0 0.0 0.0 0.0 63.1 76 115.9 124.2 0.0 0.0 0.0 2524.5 2705.7 0.0 0.0 0.0 5230.2 140 23.2 0.0 0.0 0.0 0.0 504.9 0.0 0.0 0.0 0.0 504.9 180 49.3 124.2 0.0 0.0 0.0 1072.9 2705.7 0.0 0.0 0.0 3778.6 77 18.8 41.4 152.4 0.0 0.0 410.2 901.9 3319.2 0.0 0.0 4631.3 141 8.7 0.0 0.0 90.7 0.0 189.3 0.0 0.0 1976.3 0.0 2165.7 184 1.4 13.8 0.0 0.0 0.0 31.6 300.6 0.0 0.0 0.0 332.2 78 14.5 138.0 114.3 0.0 344.0 315.6 3006.3 2489.4 0.0 7492.8 13304.1 142 7.2 0.0 0.0 0.0 344.0 157.8 0.0 0.0 0.0 7492.8 7650.6 183 10.1 0.0 0.0 0.0 344.0 220.9 0.0 0.0 0.0 7492.8 7713.7 79 0.0 13.8 0.0 181.5 0.0 0.0 300.6 0.0 3952.7 0.0 4253.3 143 1.4 0.0 0.0 90.7 0.0 31.6 0.0 0.0 1976.3 0.0 2007.9 178 1.4 0.0 0.0 90.7 0.0 31.6 0.0 0.0 1976.3 0.0 2007.9 80 1.4 13.8 38.1 0.0 0.0 31.6 300.6 829.8 0.0 0.0 1162.0 144 1.4 0.0 0.0 0.0 0.0 31.6 0.0 0.0 0.0 0.0 31.6 177 1.4 0.0 0.0 0.0 0.0 31.6 0.0 0.0 0.0 0.0 31.6 157 11.6 55.2 419.1 90.7 172.0 252.5 1202.5 9127.7 1976.3 3746.4 16305.4 179 0.0 0.0 38.1 0.0 0.0 0.0 0.0 829.8 0.0 0.0 829.8 158 0.0 0.0 0.0 0.0 172.0 0.0 0.0 0.0 0.0 3746.4 3746.4 65 21.1 0.0 0.0 0.0 0.0 459.3 0.0 0.0 0.0 0.0 459.3 146 21.1 0.0 53.0 0.0 0.0 459.3 0.0 1153.3 0.0 0.0 1612.6 66 7.0 0.0 0.0 0.0 0.0 153.1 0.0 0.0 0.0 0.0 153.1 145 21.1 0.0 0.0 0.0 0.0 459.3 0.0 0.0 0.0 0.0 459.3 70 56.2 70.6 105.9 84.0 0.0 1224.7 1537.8 2306.7 1828.9 0.0 6898.2 85 28.1 0.0 0.0 0.0 0.0 612.4 0.0 0.0 0.0 0.0 612.4 71 112.5 211.8 53.0 0.0 0.0 2449.5 4613.5 1153.3 0.0 0.0 8216.3 84 98.4 0.0 0.0 0.0 0.0 2143.3 0.0 0.0 0.0 0.0 2143.3 72 70.3 0.0 0.0 0.0 0.0 1530.9 0.0 0.0 0.0 0.0 1530.9 171 14.1 0.0 0.0 0.0 0.0 306.2 0.0 0.0 0.0 0.0 306.2 73 232.0 35.3 0.0 0.0 0.0 5052.0 768.9 0.0 0.0 0.0 5820.9 154 140.6 0.0 0.0 0.0 0.0 3061.8 0.0 0.0 0.0 0.0 3061.8 74 147.6 176.5 105.9 0.0 0.0 3214.9 3844.6 2306.7 0.0 0.0 9366.2
84 153 175.7 0.0 0.0 0.0 0.0 3827.3 0.0 0.0 0.0 0.0 3827.3 5 10.6 30.6 57.5 0.0 98.3 230.3 667.2 1251.3 0.0 2140.9 4289.7 6 18.5 46.0 28.7 0.0 0.0 402.9 1000.8 625.7 0.0 0.0 2029.5 242 21.1 46.0 28.7 0.0 0.0 460.5 1000.8 625.7 0.0 0.0 2087.0 150 5.3 0.0 143.6 56.6 0.0 115.1 0.0 3128.4 1231.8 0.0 4475.3 237 5.3 0.0 114.9 56.6 0.0 115.1 0.0 2502.7 1231.8 0.0 3849.7 238 0.0 30.6 57.5 56.6 0.0 0.0 667.2 1251.3 1231.8 0.0 3150.4 169 0.0 46.0 0.0 0.0 0.0 0.0 1000.8 0.0 0.0 0.0 1000.8 236 2.6 46.0 0.0 0.0 0.0 57.6 1000.8 0.0 0.0 0.0 1058.4 147 18.5 0.0 0.0 0.0 0.0 402.9 0.0 0.0 0.0 0.0 402.9 191 18.5 0.0 0.0 0.0 0.0 402.9 0.0 0.0 0.0 0.0 402.9 47 2.6 15.3 28.7 0.0 0.0 57.6 333.6 625.7 0.0 0.0 1016.8 151 0.0 0.0 28.7 0.0 0.0 0.0 0.0 625.7 0.0 0.0 625.7 205 0.0 0.0 28.7 0.0 0.0 0.0 0.0 625.7 0.0 0.0 625.7 152 5.3 0.0 0.0 0.0 0.0 115.1 0.0 0.0 0.0 0.0 115.1 40 7.9 0.0 0.0 0.0 0.0 172.7 0.0 0.0 0.0 0.0 172.7 43 0.0 15.3 0.0 0.0 0.0 0.0 333.6 0.0 0.0 0.0 333.6 44 5.3 15.3 0.0 0.0 0.0 115.1 333.6 0.0 0.0 0.0 448.7 81 10.6 0.0 0.0 0.0 0.0 230.3 0.0 0.0 0.0 0.0 230.3 210 10.6 0.0 0.0 0.0 0.0 230.3 0.0 0.0 0.0 0.0 230.3 67 0.0 0.0 28.7 0.0 0.0 0.0 0.0 625.7 0.0 0.0 625.7 136 2.6 0.0 0.0 0.0 0.0 57.6 0.0 0.0 0.0 0.0 57.6 68 74.0 46.0 0.0 0.0 0.0 1611.8 1000.8 0.0 0.0 0.0 2612.6 137 71.4 0.0 0.0 0.0 0.0 1554.2 0.0 0.0 0.0 0.0 1554.2 251 74.0 0.0 0.0 0.0 0.0 1611.8 0.0 0.0 0.0 0.0 1611.8 69 2.6 30.6 86.2 0.0 0.0 57.6 667.2 1877.0 0.0 0.0 2601.8 255 2.6 0.0 0.0 0.0 0.0 57.6 0.0 0.0 0.0 0.0 57.6 161 0.0 0.0 37.5 0.0 0.0 0.0 0.0 817.6 0.0 0.0 817.6 166 0.0 44.8 0.0 0.0 0.0 0.0 975.8 0.0 0.0 0.0 975.8 21 4.1 22.4 0.0 0.0 0.0 89.7 487.9 0.0 0.0 0.0 577.6 22 4.1 0.0 0.0 0.0 0.0 89.7 0.0 0.0 0.0 0.0 89.7 15 0.0 22.4 0.0 0.0 0.0 0.0 487.9 0.0 0.0 0.0 487.9 16 4.1 0.0 37.5 0.0 0.0 89.7 0.0 817.6 0.0 0.0 907.3 167 0.0 188.3 132.5 0.0 150.2 0.0 4101.6 2884.9 0.0 3270.7 10257.2 185 4.1 0.0 0.0 0.0 0.0 88.3 0.0 0.0 0.0 0.0 88.3 1 60.8 0.0 0.0 0.0 0.0 1325.2 0.0 0.0 0.0 0.0 1325.2 94 0.0 47.1 44.2 0.0 0.0 0.0 1025.4 961.6 0.0 0.0 1987.0 234 0.0 47.1 44.2 0.0 0.0 0.0 1025.4 961.6 0.0 0.0 1987.0 4 8.1 0.0 0.0 0.0 0.0 176.7 0.0 0.0 0.0 0.0 176.7 95 16.2 23.5 0.0 0.0 0.0 353.4 512.7 0.0 0.0 0.0 866.1 240 16.2 23.5 0.0 0.0 0.0 353.4 512.7 0.0 0.0 0.0 866.1 96 12.2 47.1 88.3 0.0 0.0 265.0 1025.4 1923.3 0.0 0.0 3213.7 241 16.2 47.1 88.3 0.0 0.0 353.4 1025.4 1923.3 0.0 0.0 3302.1 97 32.5 70.6 44.2 0.0 0.0 706.8 1538.1 961.6 0.0 0.0 3206.5 7 8.1 0.0 0.0 0.0 0.0 176.7 0.0 0.0 0.0 0.0 176.7 98 8.1 0.0 0.0 0.0 0.0 176.7 0.0 0.0 0.0 0.0 176.7 230 8.1 0.0 0.0 0.0 0.0 176.7 0.0 0.0 0.0 0.0 176.7
85 8 24.3 0.0 0.0 0.0 0.0 530.1 0.0 0.0 0.0 0.0 530.1 99 8.1 0.0 0.0 0.0 0.0 176.7 0.0 0.0 0.0 0.0 176.7 232 8.1 0.0 0.0 0.0 0.0 176.7 0.0 0.0 0.0 0.0 176.7 9 8.1 0.0 0.0 0.0 0.0 176.7 0.0 0.0 0.0 0.0 176.7 100 4.1 0.0 0.0 0.0 0.0 88.3 0.0 0.0 0.0 0.0 88.3 231 4.1 0.0 0.0 0.0 0.0 88.3 0.0 0.0 0.0 0.0 88.3 10 0.0 0.0 44.2 0.0 0.0 0.0 0.0 961.6 0.0 0.0 961.6 101 0.0 0.0 44.2 0.0 0.0 0.0 0.0 961.6 0.0 0.0 961.6 233 0.0 0.0 44.2 0.0 0.0 0.0 0.0 961.6 0.0 0.0 961.6 168 0.0 47.1 88.3 86.7 0.0 0.0 1025.4 1923.3 1888.7 0.0 4837.4 175 4.1 0.0 44.2 0.0 0.0 88.3 0.0 961.6 0.0 0.0 1050.0 174 4.1 0.0 0.0 0.0 0.0 88.3 0.0 0.0 0.0 0.0 88.3 49 36.5 23.5 44.2 0.0 0.0 795.1 512.7 961.6 0.0 0.0 2269.5 50 4.1 0.0 0.0 0.0 0.0 88.3 0.0 0.0 0.0 0.0 88.3 51 0.0 0.0 0.0 86.7 0.0 0.0 0.0 0.0 1888.7 0.0 1888.7 53 12.2 23.5 0.0 86.7 150.2 265.0 512.7 0.0 1888.7 3270.7 5937.1 134 0.0 23.5 0.0 0.0 0.0 0.0 512.7 0.0 0.0 0.0 512.7 187 4.1 23.5 0.0 0.0 0.0 88.3 512.7 0.0 0.0 0.0 601.0 54 4.1 0.0 44.2 0.0 0.0 88.3 0.0 961.6 0.0 0.0 1050.0 186 4.1 0.0 0.0 0.0 0.0 88.3 0.0 0.0 0.0 0.0 88.3 36 8.1 47.1 44.2 0.0 0.0 176.7 1025.4 961.6 0.0 0.0 2163.7 120 4.1 0.0 0.0 0.0 0.0 88.3 0.0 0.0 0.0 0.0 88.3 192 4.1 0.0 0.0 0.0 0.0 88.3 0.0 0.0 0.0 0.0 88.3 45 12.2 0.0 44.2 0.0 0.0 265.0 0.0 961.6 0.0 0.0 1226.7 131 8.1 23.5 44.2 0.0 0.0 176.7 512.7 961.6 0.0 0.0 1651.0 203 8.1 23.5 44.2 0.0 0.0 176.7 512.7 961.6 0.0 0.0 1651.0 48 0.0 23.5 0.0 0.0 150.2 0.0 512.7 0.0 0.0 3270.7 3783.4 132 0.0 0.0 0.0 0.0 150.2 0.0 0.0 0.0 0.0 3270.7 3270.7 195 0.0 0.0 0.0 0.0 150.2 0.0 0.0 0.0 0.0 3270.7 3270.7 37 0.0 0.0 44.2 86.7 0.0 0.0 0.0 961.6 1888.7 0.0 2850.4 121 4.1 0.0 44.2 0.0 0.0 88.3 0.0 961.6 0.0 0.0 1050.0 193 4.1 0.0 44.2 0.0 0.0 88.3 0.0 961.6 0.0 0.0 1050.0 38 16.2 0.0 88.3 86.7 0.0 353.4 0.0 1923.3 1888.7 0.0 4165.4 122 12.2 0.0 44.2 173.4 0.0 265.0 0.0 961.6 3777.4 0.0 5004.1 194 12.2 0.0 44.2 173.4 0.0 265.0 0.0 961.6 3777.4 0.0 5004.1 123 4.1 0.0 0.0 0.0 0.0 88.3 0.0 0.0 0.0 0.0 88.3 197 4.1 0.0 0.0 0.0 0.0 88.3 0.0 0.0 0.0 0.0 88.3 124 12.2 0.0 0.0 0.0 0.0 265.0 0.0 0.0 0.0 0.0 265.0 200 12.2 0.0 0.0 0.0 0.0 265.0 0.0 0.0 0.0 0.0 265.0 41 16.2 258.9 44.2 0.0 0.0 353.4 5639.7 961.6 0.0 0.0 6954.7 125 20.3 117.7 44.2 0.0 0.0 441.7 2563.5 961.6 0.0 0.0 3966.9 201 20.3 117.7 44.2 0.0 0.0 441.7 2563.5 961.6 0.0 0.0 3966.9 42 16.2 164.8 88.3 0.0 0.0 353.4 3588.9 1923.3 0.0 0.0 5865.6 126 4.1 23.5 88.3 0.0 0.0 88.3 512.7 1923.3 0.0 0.0 2524.3 239 4.1 23.5 88.3 0.0 0.0 88.3 512.7 1923.3 0.0 0.0 2524.3 43 8.1 23.5 88.3 0.0 150.2 176.7 512.7 1923.3 0.0 3270.7 5883.3 128 8.1 0.0 0.0 0.0 0.0 176.7 0.0 0.0 0.0 0.0 176.7
86 204 12.2 0.0 0.0 0.0 0.0 265.0 0.0 0.0 0.0 0.0 265.0 55 8.1 47.1 44.2 86.7 0.0 176.7 1025.4 961.6 1888.7 0.0 4052.5 62 89.2 0.0 0.0 86.7 0.0 1943.6 0.0 0.0 1888.7 0.0 3832.3 63 85.2 0.0 0.0 0.0 0.0 1855.3 0.0 0.0 0.0 0.0 1855.3 92 16.2 0.0 0.0 0.0 0.0 353.4 0.0 0.0 0.0 0.0 353.4 212 16.2 0.0 0.0 0.0 0.0 353.4 0.0 0.0 0.0 0.0 353.4 64 0.0 0.0 44.2 0.0 0.0 0.0 0.0 961.6 0.0 0.0 961.6 56 8.1 23.5 0.0 0.0 0.0 176.7 512.7 0.0 0.0 0.0 689.4 88 8.1 23.5 0.0 0.0 0.0 176.7 512.7 0.0 0.0 0.0 689.4 209 8.1 23.5 0.0 0.0 0.0 176.7 512.7 0.0 0.0 0.0 689.4 57 4.1 23.5 44.2 0.0 0.0 88.3 512.7 961.6 0.0 0.0 1562.7 89 4.1 23.5 44.2 0.0 0.0 88.3 512.7 961.6 0.0 0.0 1562.7 208 4.1 23.5 44.2 0.0 0.0 88.3 512.7 961.6 0.0 0.0 1562.7 59 12.2 0.0 44.2 0.0 0.0 265.0 0.0 961.6 0.0 0.0 1226.7 87 20.3 0.0 44.2 0.0 0.0 441.7 0.0 961.6 0.0 0.0 1403.4 214 20.3 0.0 44.2 0.0 0.0 441.7 0.0 961.6 0.0 0.0 1403.4 61 12.2 0.0 0.0 0.0 0.0 265.0 0.0 0.0 0.0 0.0 265.0 90 20.3 0.0 0.0 0.0 0.0 441.7 0.0 0.0 0.0 0.0 441.7 213 20.3 0.0 0.0 0.0 0.0 441.7 0.0 0.0 0.0 0.0 441.7 155 60.8 47.1 0.0 173.4 0.0 1325.2 1025.4 0.0 3777.4 0.0 6128.0 254 60.8 47.1 0.0 173.4 0.0 1325.2 1025.4 0.0 3777.4 0.0 6128.0 156 44.6 47.1 88.3 86.7 0.0 971.8 1025.4 1923.3 1888.7 0.0 5809.2 252 52.7 47.1 88.3 86.7 0.0 1148.5 1025.4 1923.3 1888.7 0.0 5985.9 264 12.2 0.0 0.0 0.0 0.0 265.0 0.0 0.0 0.0 0.0 265.0 265 73.0 47.1 132.5 0.0 0.0 1590.2 1025.4 2884.9 0.0 0.0 5500.6 266 24.3 23.5 44.2 0.0 0.0 530.1 512.7 961.6 0.0 0.0 2004.4 75 0.0 70.6 0.0 0.0 0.0 0.0 1538.1 0.0 0.0 0.0 1538.1 77 0.0 70.6 0.0 0.0 0.0 0.0 1538.1 0.0 0.0 0.0 1538.1 141 4.1 0.0 0.0 0.0 0.0 88.3 0.0 0.0 0.0 0.0 88.3 80 0.0 47.1 0.0 0.0 0.0 0.0 1025.4 0.0 0.0 0.0 1025.4 158 4.1 0.0 0.0 0.0 0.0 88.3 0.0 0.0 0.0 0.0 88.3 182 4.1 0.0 0.0 0.0 0.0 88.3 0.0 0.0 0.0 0.0 88.3 243 4.1 0.0 0.0 0.0 0.0 88.3 0.0 0.0 0.0 0.0 88.3
117 4.1 23.5 0.0 0.0 0.0 88.3 512.7 0.0 0.0 0.0 601.0
253 8.1 0.0 0.0 0.0 0.0 176.7 0.0 0.0 0.0 0.0 176.7 165 4.1 0.0 0.0 0.0 0.0 88.3 0.0 0.0 0.0 0.0 88.3 106 0.0 23.5 0.0 0.0 0.0 0.0 512.7 0.0 0.0 0.0 512.7 224 0.0 23.5 0.0 0.0 0.0 0.0 512.7 0.0 0.0 0.0 512.7 107 0.0 0.0 44.2 0.0 0.0 0.0 0.0 961.6 0.0 0.0 961.6 223 0.0 0.0 44.2 0.0 0.0 0.0 0.0 961.6 0.0 0.0 961.6 18 4.1 0.0 0.0 0.0 0.0 88.3 0.0 0.0 0.0 0.0 88.3 109 4.1 0.0 0.0 0.0 0.0 88.3 0.0 0.0 0.0 0.0 88.3 228 4.1 0.0 0.0 0.0 0.0 88.3 0.0 0.0 0.0 0.0 88.3 111 4.1 0.0 0.0 0.0 0.0 88.3 0.0 0.0 0.0 0.0 88.3 115 8.1 0.0 0.0 0.0 0.0 176.7 0.0 0.0 0.0 0.0 176.7 116 4.1 0.0 0.0 0.0 0.0 88.3 0.0 0.0 0.0 0.0 88.3
87 227 4.1 0.0 0.0 0.0 0.0 88.3 0.0 0.0 0.0 0.0 88.3 167 53.6 244.2 153.7 629.7 469.8 1166.8 5318.4 3348.5 13715.7 10231.5 33780.8 185 7.7 0.0 0.0 0.0 0.0 166.7 0.0 0.0 0.0 0.0 166.7 172 47.8 57.5 230.6 419.8 0.0 1041.8 1251.4 5022.7 9143.8 0.0 16459.7 65 7.7 0.0 0.0 0.0 0.0 166.7 0.0 0.0 0.0 0.0 166.7 146 3.8 0.0 0.0 0.0 0.0 83.3 0.0 0.0 0.0 0.0 83.3 66 1.9 0.0 0.0 0.0 0.0 41.7 0.0 0.0 0.0 0.0 41.7 71 1.9 0.0 0.0 0.0 0.0 41.7 0.0 0.0 0.0 0.0 41.7 84 1.9 0.0 0.0 0.0 0.0 41.7 0.0 0.0 0.0 0.0 41.7 1 76.3 11.3 107.0 340.6 0.0 1662.6 246.2 2330.6 7418.0 0.0 11657.4 94 112.5 0.0 178.3 454.1 0.0 2450.2 0.0 3884.4 9890.6 0.0 16225.2 234 119.2 0.0 178.3 454.1 0.0 2596.1 0.0 3884.4 9890.6 0.0 16371.1 4 12.1 158.2 142.7 567.6 0.0 262.5 3446.2 3107.5 12363.3 0.0 19179.5 95 21.4 113.0 178.3 681.2 0.0 466.7 2461.6 3884.4 14835.9 0.0 21648.6 240 22.8 113.0 178.3 681.2 0.0 495.9 2461.6 3884.4 14835.9 0.0 21677.8 5 21.4 0.0 35.7 340.6 0.0 466.7 0.0 776.9 7418.0 0.0 8661.6 96 34.8 0.0 0.0 340.6 0.0 758.4 0.0 0.0 7418.0 0.0 8176.4 241 34.8 0.0 0.0 0.0 0.0 758.4 0.0 0.0 0.0 0.0 758.4 6 18.7 22.6 0.0 0.0 0.0 408.4 492.3 0.0 0.0 0.0 900.7 97 24.1 22.6 0.0 0.0 0.0 525.0 492.3 0.0 0.0 0.0 1017.4 242 25.4 22.6 0.0 0.0 0.0 554.2 492.3 0.0 0.0 0.0 1046.5 7 2.7 11.3 0.0 0.0 0.0 58.3 246.2 0.0 0.0 0.0 304.5 98 0.0 11.3 0.0 0.0 0.0 0.0 246.2 0.0 0.0 0.0 246.2 230 0.0 11.3 0.0 0.0 0.0 0.0 246.2 0.0 0.0 0.0 246.2 9 2.7 0.0 0.0 0.0 0.0 58.3 0.0 0.0 0.0 0.0 58.3 10 2.7 0.0 0.0 0.0 0.0 58.3 0.0 0.0 0.0 0.0 58.3 101 1.3 0.0 0.0 0.0 0.0 29.2 0.0 0.0 0.0 0.0 29.2 233 1.3 0.0 0.0 0.0 0.0 29.2 0.0 0.0 0.0 0.0 29.2 150 9.4 0.0 107.0 113.5 0.0 204.2 0.0 2330.6 2472.7 0.0 5007.5 237 9.4 0.0 107.0 113.5 0.0 204.2 0.0 2330.6 2472.7 0.0 5007.5 168 4.0 101.7 356.7 113.5 0.0 87.5 2215.4 7768.8 2472.7 0.0 12544.3 238 4.0 101.7 356.7 113.5 0.0 87.5 2215.4 7768.8 2472.7 0.0 12544.3 169 14.7 11.3 35.7 454.1 0.0 320.9 246.2 776.9 9890.6 0.0 11234.5 236 16.1 11.3 0.0 340.6 0.0 350.0 246.2 0.0 7418.0 0.0 8014.2 49 64.3 101.7 107.0 227.1 0.0 1400.1 2215.4 2330.6 4945.3 0.0 10891.5 147 20.1 90.4 107.0 0.0 0.0 437.5 1969.3 2330.6 0.0 0.0 4737.4 191 20.1 90.4 107.0 0.0 0.0 437.5 1969.3 2330.6 0.0 0.0 4737.4 50 4.0 11.3 142.7 340.6 0.0 87.5 246.2 3107.5 7418.0 0.0 10859.1 148 4.0 0.0 0.0 0.0 0.0 87.5 0.0 0.0 0.0 0.0 87.5 190 4.0 0.0 0.0 0.0 0.0 87.5 0.0 0.0 0.0 0.0 87.5 51 2.7 11.3 107.0 567.6 0.0 58.3 246.2 2330.6 12363.3 0.0 14998.4 52 1.3 11.3 178.3 794.7 0.0 29.2 246.2 3884.4 17308.6 0.0 21468.3 149 1.3 0.0 0.0 113.5 0.0 29.2 0.0 0.0 2472.7 0.0 2501.8 188 1.3 0.0 0.0 113.5 0.0 29.2 0.0 0.0 2472.7 0.0 2501.8 53 17.4 90.4 535.0 227.1 284.9 379.2 1969.3 11653.1 4945.3 6205.4 25152.3 134 4.0 45.2 0.0 113.5 0.0 87.5 984.6 0.0 2472.7 0.0 3544.8 187 4.0 45.2 0.0 113.5 0.0 87.5 984.6 0.0 2472.7 0.0 3544.8
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92 141 26.3 0.0 42.8 120.0 0.0 573.9 0.0 932.9 2613.1 0.0 4119.8 184 111.1 12.8 85.7 120.0 0.0 2420.2 279.6 1865.7 2613.1 0.0 7178.6 78 2.3 0.0 0.0 120.0 0.0 49.9 0.0 0.0 2613.1 0.0 2663.0 142 5.7 0.0 42.8 120.0 0.0 124.8 0.0 932.9 2613.1 0.0 3670.7 183 13.7 0.0 42.8 120.0 0.0 299.4 0.0 932.9 2613.1 0.0 3845.4 79 34.4 12.8 0.0 0.0 0.0 748.5 279.6 0.0 0.0 0.0 1028.1 143 27.5 12.8 0.0 0.0 0.0 598.8 279.6 0.0 0.0 0.0 878.4 178 32.1 12.8 0.0 0.0 0.0 698.6 279.6 0.0 0.0 0.0 978.2 80 30.9 77.0 42.8 0.0 0.0 673.7 1677.4 932.9 0.0 0.0 3283.9 144 25.2 38.5 42.8 0.0 0.0 548.9 838.7 932.9 0.0 0.0 2320.5 177 27.5 38.5 42.8 0.0 0.0 598.8 838.7 932.9 0.0 0.0 2370.4 157 5.7 51.3 42.8 240.0 0.0 124.8 1118.2 932.9 5226.2 0.0 7402.0 179 10.3 0.0 0.0 240.0 0.0 224.6 0.0 0.0 5226.2 0.0 5450.7 158 13.7 0.0 0.0 599.9 0.0 299.4 0.0 0.0 13065.4 0.0 13364.8 182 14.9 0.0 0.0 599.9 0.0 324.4 0.0 0.0 13065.4 0.0 13389.7 1 24.4 0.0 0.0 0.0 0.0 531.1 0.0 0.0 0.0 0.0 531.1 94 9.8 0.0 0.0 0.0 0.0 212.4 0.0 0.0 0.0 0.0 212.4 234 8.1 0.0 0.0 0.0 0.0 177.0 0.0 0.0 0.0 0.0 177.0 95 4.9 0.0 0.0 0.0 0.0 106.2 0.0 0.0 0.0 0.0 106.2 240 6.5 0.0 0.0 0.0 0.0 141.6 0.0 0.0 0.0 0.0 141.6 5 60.1 0.0 0.0 80.3 432.2 1310.1 0.0 0.0 1749.0 9412.8 12471.9 96 45.5 0.0 0.0 80.3 288.1 991.4 0.0 0.0 1749.0 6275.2 9015.6 241 47.1 0.0 0.0 80.3 288.1 1026.8 0.0 0.0 1749.0 6275.2 9051.0 6 3.3 14.4 0.0 80.3 0.0 70.8 313.0 0.0 1749.0 0.0 2132.8 97 0.0 14.4 0.0 80.3 144.1 0.0 313.0 0.0 1749.0 3137.6 5199.6 7 26.0 14.4 109.0 80.3 144.1 566.5 313.0 2374.3 1749.0 3137.6 8140.5 98 29.3 28.7 109.0 160.6 0.0 637.3 626.0 2374.3 3498.1 0.0 7135.7 230 29.3 28.7 109.0 160.6 0.0 637.3 626.0 2374.3 3498.1 0.0 7135.7 8 45.5 28.7 36.3 0.0 0.0 991.4 626.0 791.4 0.0 0.0 2408.8 99 45.5 28.7 36.3 160.6 0.0 991.4 626.0 791.4 3498.1 0.0 5906.9 232 45.5 28.7 36.3 160.6 0.0 991.4 626.0 791.4 3498.1 0.0 5906.9 9 1.6 0.0 0.0 0.0 0.0 35.4 0.0 0.0 0.0 0.0 35.4 100 1.6 0.0 0.0 0.0 0.0 35.4 0.0 0.0 0.0 0.0 35.4 231 1.6 0.0 0.0 0.0 0.0 35.4 0.0 0.0 0.0 0.0 35.4 10 0.0 0.0 0.0 80.3 0.0 0.0 0.0 0.0 1749.0 0.0 1749.0 101 0.0 0.0 0.0 80.3 0.0 0.0 0.0 0.0 1749.0 0.0 1749.0 233 0.0 0.0 0.0 80.3 0.0 0.0 0.0 0.0 1749.0 0.0 1749.0 45 1.6 0.0 0.0 0.0 0.0 35.4 0.0 0.0 0.0 0.0 35.4 68 102.4 14.4 72.7 160.6 144.1 2230.6 313.0 1582.9 3498.1 3137.6 10762.2 137 82.9 0.0 0.0 160.6 144.1 1805.8 0.0 0.0 3498.1 3137.6 8441.4 251 84.5 0.0 0.0 160.6 144.1 1841.2 0.0 0.0 3498.1 3137.6 8476.8 155 4.9 14.4 72.7 0.0 0.0 106.2 313.0 1582.9 0.0 0.0 2002.1 254 4.9 14.4 72.7 0.0 0.0 106.2 313.0 1582.9 0.0 0.0 2002.1 156 8.1 14.4 0.0 0.0 0.0 177.0 313.0 0.0 0.0 0.0 490.0 252 9.8 14.4 0.0 0.0 0.0 212.4 313.0 0.0 0.0 0.0 525.4 75 11.4 0.0 0.0 0.0 432.2 247.8 0.0 0.0 0.0 9412.8 9660.6 139 1.6 0.0 0.0 0.0 432.2 35.4 0.0 0.0 0.0 9412.8 9448.2
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94 Appendix C. Tabular data for soils and monitoring plot information These tables contain further information on the soils studied in this research in regards to expected vegetation community and geographical as well as support data on the monitoring plots established in Fremont County.
95 Appendix C1: Adapted from the Soil Survey of Fremont County Area, Colorado to demonstrate soils studied in this research. This also remarks on the expected vegetation per soil type as well as range site and expected composition percentage.
Rangeland and Woodland Understory Productivity and Characteristic Plant Communities Total Production Dry Range or Kind of Characteristic Composition Soil Name Weight Woodland Site Year Vegetation Pct Lb/Acre Boyle Pinyon-Juniper Favorable 500 Blue grama 15 Normal 400 Mountain muhly 10 Unfavorable 300 Sedge 10 Indian ricegrass 10 Gambel oak 10 Prarie junegrass 5 Mountain mahogany 5 Needle and Thread 5 Bronell Gravelly Favorable 700-850 Blue grama 10 Foothill #214 Normal 500-600 Scribner needlegrass 10 Unfavorable 300-400 Needle and Thread 10 Pinyon 10 Sideoats grama 5 Western wheatgrass 5 Indian ricegrass 5 Pinyon ricegrass 5 Mountain mahogany 5 Rocky Mtn juniper 5 Rubber rabbitbrush 5 Bundo Spruce-Fir Favorable 100 Elk sedge 10 Normal 50 Kentucky bluegrass 10 Unfavorable 25 Common juniper 10 Kinnikinnick 5 Lupine 5 Oregon grape 5 Snowberry 5 Libeg Loamy Glacial Favorable 1000 Arizona fescue 20 Outwash #291 Normal 800 Muttongrass 10 Unfavorable 600 Western wheatgrass 10 Mountain muhly 10 Blue grama 5 Little bluestem 5 Prarie junegrass 5 Elk sedge 5
96 Lupine 5 Bottlebrush squirreltail 5 Gable oak 5 Martinsdale Mountain Favorable 1000 Western wheatgrass 25 Loam, 13-18” PPT #226 Normal 750 Needle and Thread 25 Unfavorable 400 Blue grama 10 Fringed sagebrush 10 Prarie junegrass 5 Mussel Loamy Foothill Favorable 1500 Blue grama 30 #202 Normal 1100 Western wheatgrass 20 Unfavorable 800 Sideoats grama 15 Needle and Thread 15 Sand dropseed 5 Bottlebrush squirreltail 5 Prarie junegrass 5 Pendant Pinyon-Juniper Favorable 400 Sideoats grama 20 Normal 200 Blue grama 15 Unfavorable 100 Scribner needlegrass 10 Mountain muhly 10 Indian ricegrass 5 Needle and Thread 5 Bottlebrush squirreltail 5 Gambel oak 5 Raleigh Ponderosa Pine Favorable 1000 Gambel oak 25 Normal 600 Arizona fescue 15 Unfavorable 400 Mountain muhly 10 Muttongrass 5 Mountain mahogany 5 Prarie junegrass 5 Sedge 5 Buckwheat 5 Rabbitbursh 5 Resort Pinyon-Juniper Favorable 350 Mountain muhly 20 Normal 250 True moutain mahogany 16 Unfavorable 100 Gambel oak 10 Needle and Thread 5 Blue grama 5 Rabbitbursh 5 Rogert Dry Shallow Favorable 800 Mountain muhly 30 Pine #218 Normal 600 Blue grama 15 Unfavorable 400 Arizona fescue 10 Gambel oak 10 Muttongrass 5
97 Bottlebrush squirreltail 5 Mountain mahogany 5 Skunkbrush sumac 5 Pinyon 5 Pine dropseed 5 Rogert Dry Shallow Favorable 1000 Mountain muhly 35 Pine #240 Normal 800 Arizona fescue 20 Unfavorable 600 Parry oatgrass 10 Muttongrass 5 Prarie junegrass 5 Wax currant 5 Hairy goldenaster 5 Mountain mahogany 5 Gambel oak 5 Sedillo Gravelly Favorable 1000 Blue grama 10 Foothill #214 Normal 850 Needle and Thread 10 Unfavorable 400 Scribner needlegrass 10 Pinyon 10 Little bluestem 5 Sideoats grama 5 Western wheatgrass 5 Indian ricegrass 5 Pinyon ricegrass 5 Rocky Mountain juniper 5 Sedillo Pinyon-Juniper Favorable 700 Needle and Thread 30 Normal 400 Sideoats grama 25 Unfavorable 250 True moutain mahogany 10 Gambel oak 10 Blue grama 5 Scribner needlegrass 5 Seitz Douglas-Fir Favorable 300 Mountain muhly 45 Normal 250 Elk sedge 20 Unfavorable 200 entucky bluegrass 10 Common juniper 5 Buffaloberry 5 Seitz Ponderosa Pine Favorable 300 Mountain muhly 45 Normal 250 Elk sedge 20 Unfavorable 200 Arizona fescue 15 Pine dropseed 10 Prarie junegrass 5 Swissvale Pinyon-Juniper Favorable 500 Scribner needlegrass 20 Normal 350 Blue grama 20 Unfavorable 250 True moutain mahogany 15 Sideoats grama 5
98 Indian ricegrass 5 Teaspoon Pinyon-Juniper Favorable 300 Scribner needlegrass 25 Normal 200 Blue grama 20 Unfavorable 100 True moutain mahogany 10 Mountain muhly 5 Prarie junegrass 5 Bottlebrush squirreltail 5 Sedge 5 Pinyon 5 Sideoats grama 5 Tolex Ponderosa Pine Favorable 900-500 Sedge 15 Normal 500-300 Muttongrass 15 Unfavorable 300-200 Snowberry 10 Gambel oak 10 Mountain mahogany 10 Arizona fescue 10 Blue grama 5 Pine dropseed 5 Travessilla Pinyon-Juniper Favorable 800 Scribner needlegrass 25 Normal 700 Sideoats grama 15 Unfavorable 500 Blue grama 10 Little bluestem 5 Mountain mahogany 5 Gambel oak 5 Pinyon 5 Wages Loamy Foothill Favorable 1500 Blue grama 35 #202 Normal 1200 Western wheatgrass 20 Unfavorable 800 Needle and Thread 20 Prarie junegrass 5 Sedge 5
99 Appendix C2: Table taken from geospatial shape file of the monitoring plots in this research. Table demonstrates plot information associated with shapefile. 10 Plot ID Project Name North1 East1 Estb Aspct. Slope Elevation Treatment Soil Type 1 yr 2 yr 5 yr yr AM1 Arkansas Mountain 4253342 438302 8282002 E 10-28 7959 Hand thinning Swissvale 2003 2004 2007 2012 AM2 Arkansas Mountain 4253337 438383 8282002 S 10-29 7910 Hand thinning Swissvale 2003 2004 2007 2012 AM3 Arkansas Mountain 4254540 438116 9062002 E 15-20 7959 Hand thinning Pendant 2003 2004 2007 2012 AM4 Arkansas Mountain 4254897 438237 9062002 NW 5-31 7913 Hand thinning Teaspoon 2003 2004 2007 2012 AM5 Arkansas Mountain 4251843 436299 9302002 N 10-22 8635 Prescribed burn Raleigh 2003 2004 2007 2012 AM6 Arkansas Mountain 4252007 435928 9302002 NW 15-22 8615 Prescribed burn Raleigh 2003 2004 2007 2012 AM7 Arkansas Mountain 4251958 435836 9302002 NW 15-23 8615 Prescribed burn Raleigh 2003 2004 2007 2012 AM8 Arkansas Mountain 4251744 435973 9302002 NW 5-22 8671 Prescribed burn Raleigh 2003 2004 2007 2012 BH1 Big Hole 4259003 453029 8262003 S 0-5 7140 Rollerchop Bronel 2004 2005 2008 2013 BH2 Big Hole 4258705 451778 8262003 S 0-5 6880 Rollerchop Bronel 2004 2005 2008 2013 BH3 Big Hole 4260491 451689 8262003 S 0-5 7700 Rollerchop Bronel 2004 2005 2008 2013 BH4 Big Hole 4258848 452945 8032004 S 0-5 7080 Rollerchop Bronel 2005 2006 2010 2015 Dawson1 Dawson Ranch 4249663 475347 8032003 NE 5-30 6162 Hand thinning Sedillo 2004 2005 2008 2013 Dawson2 Dawson Ranch 4249101 475068 6032004 N 0-5 6996 Hydroaxe Bronel 2005 2006 2010 2015 DH1 Deer Haven 4273274 466967 8082002 NE 15-25 8481 Prescribed burn Rogert 2003 2004 2007 2012 DH10 Deer Haven 4274725 465271 6242003 N 10-15 8409 Hand thinning Tolex 2004 2005 2008 2013 DH11 Deer Haven 4274096 465590 9172003 N 10-15 8425 Hand thinning Rogert 2004 2005 2008 2013 DH12 Deer Haven 4275702 469701 7212004 NE 5-28 8625 Hand thinning Rogert 2005 5006 2009 2014 DH2 Deer Haven 4273818 465634 8082002 N 5-32 8583 Prescribed burn Tolex 2003 2004 2007 2012 DH3 Deer Haven 4274001 465770 8122002 W 20-27 8510 Prescribed burn Rogert 2003 2004 2007 2012 DH4 Deer Haven 4275117 466598 8122002 NE 10-23 8163 Hand thinning Raleigh 2003 2004 2007 2012 DH5 Deer Haven 4272248 466967 8132002 E 5-29 8478 Hand thinning Rogert 2003 2004 2007 2012 DH6 Deer Haven 4275019 466946 8132002 N 10-24 8081 Prescribed burn Raleigh 2003 2004 2007 2012 DH7 Deer Haven 4275000 466093 3262003 N 15-30 8271 Hand thinning Raleigh 2003 2004 2007 2012 DH8 Deer Haven 4275145 465855 3262003 NE 5-10 8287 Hand thinning Tolex 2003 2004 2007 2012
100 DH9 Deer Haven 4275022 465947 3262003 NE 10-15 8285 Hand thinning Raleigh 2003 2004 2007 2012 Eightmile1 Eightmile Mountain 4265235 470947 6092003 E 10-15 7500 Hydroaxe Raleigh 2004 2005 2008 2013 Eightmile2 Eightmile Mountain 4265292 471087 6092003 SE 0-5 7526 Hydroaxe Raleigh 2004 2005 2008 2013 Eightmile3 Eightmile Mountain 4265385 471033 6092003 NE 10-15 7530 Hydroaxe Raleigh 2004 2005 2008 2013 Eightmile4 Eightmile Mountain 4265256 471637 6112003 S 10-15 7572 Hydroaxe Raleigh 2004 2005 2008 2013 Eightmile5 Eightmile Mountain 4265131 471697 6112003 W 15-31 7500 Hydroaxe Raleigh 2004 2005 2008 2013 Eightmile6 Eightmile Mountain 4265102 471619 6112003 SW 10-15 7536 Hydroaxe Raleigh 2004 2005 2008 2013 Eightmile7 Eightmile Mountain 4264381 471822 8072003 NW 0-5 7565 Hydroaxe Raleigh 2004 2005 2008 2013 GRCNYNHLS1 Grand Canyon Hills 4253375 472965 1092002 N 10-31 6680 Hand thinning Wages 2003 2004 2007 2012 IM1 Iron Mountain 460171 4244597 6022002 E 10-15 7483 Wildfire Boyle 2003 2004 2007 2012 IM2 Iron Mountain 460305 4244240 6022002 E 10-15 7464 Wildfire Boyle 2003 2004 2007 2012 IM3 Iron Mountain 456419 4239313 7082002 SW 20-29 7831 Wildfire Boyle 2003 2004 2007 2012 IM4 Iron Mountain 456121 4239296 7082002 SW 15-27 7776 Wildfire Boyle 2003 2004 2007 2012 NHOW1 North Howard 4255613 424107 6062002 E 10-15 7296 Rollerchop Bronel 2003 2004 2007 2012 NHOW2 North Howard 4255575 424332 6062002 E 5-10 7251 Rollerchop Bronel 2003 2004 2007 2012 NHOW3 North Howard 4255727 424364 6062002 N 5-11 7228 Rollerchop Bronel 2003 2004 2007 2012 NHOW4 North Howard 4255861 424697 6062002 NE 0-5 7149 Rollerchop Mussel 2003 2004 2007 2012 NHOW5 North Howard 4256104 424919 6172002 NE 5-12 7083 Rollerchop Bronel 2003 2004 2007 2012 NHOW6 North Howard 4256368 424518 6172002 SE 20-25 7218 Rollerchop Bronel 2003 2004 2007 2012 NOCO1 North Cotopaxi 4257163 440686 7102002 SE 5-24 8327 Hydroaxe Raleigh 2003 2004 2007 2012 NOCO10 North Cotopaxi 4256805 439363 10212002 E 10-25 8045 Rollerchop Raleigh 2003 2004 2007 2012 NOCO11 North Cotopaxi 4257022 439583 10212002 SW 0-5 8061 Rollerchop Martinsdale 2003 2004 2007 2012 NOCO12 North Cotopaxi 4257835 438193 10252002 E 10-19 8136 Hydroaxe Pendant 2003 2004 2007 2012 NOCO13 North Cotopaxi 4254096 441202 10252002 SW 10-20 7638 Hydroaxe Pendant 2003 2004 2007 2012 NOCO14 North Cotopaxi 4256988 439393 6232003 E 0-5 8058 control Martinsdale 2004 2005 2008 2013 NOCO15 North Cotopaxi 4256045 439683 6232003 SE 5-10 7890 control Raleigh 2004 2005 2008 2013 NOCO2 North Cotopaxi 4254518 441017 7102002 SE 5-25 7710 Hydroaxe Raleigh 2003 2004 2007 2012 NOCO3 North Cotopaxi 4255237 441134 7102002 SW 15-24 7867 Hydroaxe Raleigh 2003 2004 2007 2012 NOCO4 North Cotopaxi 4256128 439600 7102002 NE 5-26 7933 Rollerchop Raleigh 2003 2004 2007 2012 NOCO5 North Cotopaxi 4255518 439735 7172002 E 5-27 7821 Rollerchop Raleigh 2003 2004 2007 2012
101 NOCO6 North Cotopaxi 4255605 438415 7222002 E 5-13 7900 Rollerchop Bronel 2003 2004 2007 2012 NOCO7 North Cotopaxi 4255466 438467 7222002 SE 10-30 7874 Rollerchop Teaspoon 2003 2004 2007 2012 NOCO8 North Cotopaxi 4257737 438045 7222002 E 10-21 8159 Hydroaxe Pendant 2003 2004 2007 2012 NOCO9 North Cotopaxi 4257908 438073 7222002 E 15-21 8176 Hydroaxe Pendant 2003 2004 2007 2012 PENROSE1 Penrose 4262550 496908 7252002 S 5-33 6158 Rollerchop Travessilla 2003 2004 2007 2012 PENROSE2 Penrose 4261945 497874 7252002 SW 0-5 6053 Rollerchop Travessilla 2003 2004 2007 2012 Palmer G./Sullivan PGSC1 Cr. 4239335 439687 6182002 N 5-15 7818 Prescribed burn Libeg 2003 2004 2007 2012 Palmer G./Sullivan PGSC10 Cr. 4239923 438353 7022002 N 5-16 7762 Rollerchop Libeg 2003 2004 2007 2012 Palmer G./Sullivan PGSC11 Cr. 4240752 437908 7052002 NW 20-26 7736 Rollerchop Libeg 2003 2004 2007 2012 Palmer G./Sullivan PGSC12 Cr. 4241184 438104 7052002 E 10-16 7598 Rollerchop Bronel 2003 2004 2007 2012 Palmer G./Sullivan PGSC2 Cr. 4239080 439378 6182002 N 5-17 7940 Prescribed burn Libeg 2003 2004 2007 2012 Palmer G./Sullivan PGSC3 Cr. 4239094 439366 6272002 N 5-18 7936 Prescribed burn Libeg 2003 2004 2007 2012 Palmer G./Sullivan PGSC4 Cr. 4238855 439276 6272002 N 5-19 8028 Prescribed burn Libeg 2003 2004 2007 2012 Palmer G./Sullivan PGSC5 Cr. 4239626 438310 7172002 NE 5-20 7841 Rollerchop Libeg 2003 2004 2007 2012 Palmer G./Sullivan PGSC6 Cr. 4238416 438998 6272002 N 10-18 8205 Prescribed burn Libeg 2003 2004 2007 2012 Palmer G./Sullivan PGSC7 Cr. 4239594 438349 7172002 NE 5-21 7844 Rollerchop Libeg 2003 2004 2007 2012 POVERTY1 Poverty Mountain 4250522 459015 8302002 SW 15-28 7897 Hand thinning Boyle 2003 2004 2007 2012 POVERTY2 Poverty Mountain 4251095 459164 8302002 N 10-26 7871 Hand thinning Resort 2003 2004 2007 2012 POVERTY3 Poverty Mountain 4250218 458391 8302002 NW 15-32 8077 Hand thinning Boyle 2003 2004 2007 2012 POVERTY4 Poverty Mountain 4250405 458543 5292003 NE 10-15 7936 Prescribed burn Boyle 2004 2005 2008 2013 POVERTY5 Poverty Mountain 4250723 458734 5292003 N 25-30 7851 Prescribed burn Boyle 2004 2005 2008 2013 Sprucebasin1 Spruce Basin 4261784 434361 6042002 W 10-27 9370 Feller Buncher Rogert 2003 2004 2007 2012
102 Sprucebasin2 Spruce Basin 4261718 434384 6042002 NW 10-17 9383 Feller Buncher Bundo 2003 2004 2007 2012 Sprucebasin3 Spruce Basin 4261322 434323 6052002 NW 15-26 9416 Feller Buncher Seitz 2003 2004 2007 2012 Sprucebasin4 Spruce Basin 4261525 434213 6052002 NW 5-14 9327 Feller Buncher Bundo 2003 2004 2007 2012 Sprucebasin5 Spruce Basin 4262079 434383 6052002 E 5-23 9383 Feller Buncher Raleigh 2003 2004 2007 2012 Sprucebasin6 Spruce Basin 4262155 434577 6052002 W 20-28 9485 Feller Buncher Rogert 2003 2004 2007 2012 Sprucebasin7 Spruce Basin 4259495 434257 6062003 SE 5-10 9537 Hand thinning Rogert 2004 2005 2008 2013 Sprucebasin8 Spruce Basin 4261584 433891 6062003 N 15-29 9278 control Raleigh 2004 2005 2008 2013
103 Appendix D: Plot data This appendix contains all information gathered on each plot in study area. Information was condensed for the purpose of this writing.
104