Forest Disturbance in the Olympic Experimental State Forest

Item

Title: Eng Forest Disturbance in the Olympic Experimental State Forest
Date: 2018
Creator: Eng Buhler, Steven Paul
Subject: Eng Environmental Studies
extracted text: FOREST DISTURBANCE IN THE OLYMPIC EXPIERMENTAL
STATE FOREST

by
Steven Paul Buhler

A Thesis
Submitted in partial fulfillment
of the requirements for the degree
Master of Environmental Studies
The Evergreen State College
June 2018

© 2018 by Steven P. Buhler. All rights reserved

This Thesis for the Master of Environmental Studies Degree
by
Steven Paul Buhler

has been approved for
The Evergreen State College
by

________________________
John Withey, Ph. D.
Member of the Faculty

________________________
Date

ABSTRACT
Forest Disturbance in the Olympic Experimental State Forest
Steven Paul Buhler
The Olympic Experimental State Forest (OESF) is a Washington State Department of Natural
Resources (DNR) planning unit on the western Olympic Peninsula. The OESF includes 110,000
hectares of DNR-managed state trust land, as well as private, tribal, and federal lands, specifically
Olympic National Forest and Olympic National Park. Land management practices within the
OESF have changed over time among these different ownerships. Under the 1997 Habitat
Conservation Plan, DNR manages State trust lands on the OESF in a manner that integrates
revenue production with ecological values across the landscape. Natural disturbance regimes are
used as a reference in managing forest conditions; it therefore benefits DNR to understand the
spatial scales and frequencies of both natural and anthropogenic disturbances in the OESF.
Through remote sensing and the LandTrendr methodology, this study uses NASA/USGS Landsat
images from 1985 to 2012 to identify and compare forest disturbances among the major
landowners groups over time. The average rate of disturbance has stayed the same in the OESF
from 1985-2012:0.84% per year. On lands the DNR manages, the rate of disturbance decreased
from 1.0% annually during the time period of 1985-1998, to 0.54% annually from 1999-2012,
which shows that on DNR lands a reduced rate of disturbance coincides with the implementation
of the HCP.

Table of Contents
List of Figures ............................................................................................................................. viii
List of Tables .............................................................................................................................. viii
Acknowledgements ....................................................................................................................... x
Introduction ................................................................................................................................... 1
Research Questions ................................................................................................................... 4
Chapter 1-Literature Review ....................................................................................................... 5
Introduction ............................................................................................................................... 5
Ecological Disturbance ............................................................................................................. 6
Windthrow ...................................................................................................................................... 7
Fire .................................................................................................................................................. 8
History of the Forests on the Olympic Peninsula ................................................................. 10
Vegetation Types and Ecoregions .......................................................................................... 14
Human Caused Disturbance .................................................................................................. 15
Spatial Methods to Analyze Disturbance .............................................................................. 17
Landscape Disturbance rates in the Pacific Northwest ....................................................... 18
Disturbance Research in the OESF ....................................................................................... 20
Conclusion................................................................................................................................ 21
Figure 1-1- Map of DNR Managed OESF Lands (WA DNR 2016). ........................................... 22
Chapter 2-Methods ..................................................................................................................... 23
Figure 2-1-Map of the Olympic Experimental Forest and Landownership (OESF 2017). ........ 24
Figure 2-2- Percentage of Landowner’s Area in the OESF (WA DNR 2016). ............................ 24
The OESF Study Area ............................................................................................................ 25
Figure 2-3- Map of ECO Regions in OESF(US EPA, 2015) ....................................................... 27
Figure 2-4- Map of Vegetation Zones in the OESF (ECOSHARE, 2017) ................................... 27
Study Design ............................................................................................................................ 27
Figure 2-5 Flow chart of Study Design......................................................................................... 30
Table 2-1- Data Type Used in Study ............................................................................................ 30
Chapter 3- Results & Discussion ............................................................................................... 32
Question 1. What is the Disturbance Rate in the Forest Lands in the Olympic
Experimental State Forest (OESF)? ...................................................................................... 32
Table 3-1- Annual Disturbance Rates in OESF by Landownership Group .................................. 33
iv

Table 3-2 Summary of Piecewise Regression Results for Each Landownership Type ................ 33
Question 2. Has the Disturbance Rate Decreased in the DNR lands in the OESF since
1999, When the Habitat Conservation Plan (HCP) Was Implemented? ........................... 34
Question 3. What are Differences in Land Disturbance Rate between the Different
Landownership Groups in the Olympic Experimental State Forest? ................................ 35
Disturbance Rate in Federal Land Owners (ONP and ONF) ........................................................ 35
Private Lands ................................................................................................................................ 37
Tribal Lands .................................................................................................................................. 38
Figure 3-1- Graph of Disturbance Rate among Primary Landowners in OESF. .......................... 39
Question 4. What is the Disturbance Rate among the Different EPA Ecoregions in the
OESF? ...................................................................................................................................... 39
Table 3-3- Annual Disturbance Rate in OESF by EPA Level IV Ecoregions.............................. 41
Figure 3-2- Disturbance in Ecoregions in the OESF .................................................................... 41
Disturbance in the High Olympics Ecoregion .............................................................................. 41
Table 3-4- Yearly Disturbance Rates in the High Olympic Ecoregion ........................................ 42
Question 5-What is the Disturbance Rate among the Different Forest Vegetation Zones?
................................................................................................................................................... 43
Table 3-5- Annual Disturbance Rate by Different Vegetation Zones .......................................... 43
Figure 3-3-Disturbance in Primary Vegetation Zones .................................................................. 44
Conclusion ................................................................................................................................... 45
Appendix A- Maps ...................................................................................................................... 47
Figure A-1- Map of Disturbance in OESF .................................................................................... 47
Figure A-2- Map of Disturbance in the OESF by Two Year Groups (1985-98 and 1999-2012) . 48
Figure A-3- Map of Disturbance in DNR Lands in the OESF by YOD ....................................... 49
Figure A-4- Map of Disturbance in DNR lands in the OESF by Year Groups 1985-1998 and
1999-2012 ..................................................................................................................................... 50
Figure A-5- Map of Disturbance in ONP Lands in the OESF by YOD ....................................... 51
Figure A-6- Map of Disturbance in ONP Lands in the OESF by Year Groups 1985-1998 and
1999-2012 ..................................................................................................................................... 52
Figure A-7- Map of Disturbance in ONF Lands in the OESF by YOD ....................................... 53
Figure A-8- Map of Disturbance in ONF Lands in the OESF by Year Groups 1985-1998 and
1999-2012 ..................................................................................................................................... 54
Figure A-9- Map of Disturbance in Tribal Lands in the OESF by YOD ..................................... 55

v

Figure A-10- Map of Disturbance in Tribal Lands in the OESF by Year Groups 1985-1998 and
1999-2012 ..................................................................................................................................... 56
Figure A-11- Map of Disturbance in Private Lands in the OESF by YOD .................................. 57
Figure A-12- Map of Disturbance in Private Lands in the OESF by Year Groups 1985-1998 and
1999-2012 ..................................................................................................................................... 58
Figure A-13- Map of Disturbance in the High Olympics Ecoregion by YOD (Mount Olympus).
....................................................................................................................................................... 59
Appendix B- Line Graphs .......................................................................................................... 60
Figure B-1- Overall Annual Disturbance Rates in OESF ............................................................. 60
Figure B-2- DNR Annual Disturbance Rates in OESF ................................................................ 60
Figure B-3- Timber by Board Feet in Olympic Region by Landownership (Klallam County,
Jefferson County, and Quinault Reservation, Washington) (Derived From WA DNR, 2018.) ... 61
Figure B-4- Level IV Ecoregions in the OESF by Area ............................................................... 61
Figure B-5- Annual Disturbance Rate in Coastal Lowlands by Landownership ......................... 62
Figure B-6- Annual Disturbance Rate in Coastal Uplands Ecoregion by Landownership........... 62
Figure B-7- Disturbance in Low Olympics Ecoregion by Landownership .................................. 63
Figure B-8- Annual Disturbance Rate by High Olympic Ecoregion ............................................ 63
Figure B-9- Disturbance by Vegetation Zones in OESF .............................................................. 64
Figure B-10- Annual Disturbance Rate in Sitka Spruce Vegetation Zone by Landownership Type
....................................................................................................................................................... 64
Figure B-11- Annual Disturbance in Western Hemlock Vegetation Zone by Landownership Type
....................................................................................................................................................... 65
Figure B-12- Annual Disturbance in Silver Fir Vegetation Zone by Landownership Type ........ 65
Appendix C- Disturbance Date with Predicted Piecewise Regresission Analysis Regression
lines ............................................................................................................................................... 66
Table C-1 Table Summary of Piecewise Regression Results for Each Landownership Type
(Table 3-2 reproduced here as a reference for the Appendix C figures). ..................................... 66
Figure C-2- Overall Annual Disturbance Rates in the OESF with Piecewise Regression Analysis
Line ............................................................................................................................................... 67
Figure C-3- DNR Annual Disturbance Rates in the OESF with Piecewise Regression Analysis
Line ............................................................................................................................................... 67
Figure C-4- ONP Annual Disturbances Rates in the OESF with Piecewise Regression Analysis
Line ............................................................................................................................................... 67
Figure C-5 ONF Annual Disturbance Rates in OESF with piecewise Regression Analysis Line 68

vi

Figure C-6- Private Annual Disturbance Rates in the OESF with the Piecewise Regression
Analysis Line ................................................................................................................................ 68
Figure C-7- Tribal Annual Disturbance Rates in the OESF with the Piecewise Regression
Analysis Line ................................................................................................................................ 69
Appendix D- Tables .................................................................................................................... 70
Table D-1- Yearly Disturbance Rate in Coastal Lowlands Ecoregion ......................................... 70
Table D-2- Yearly Disturbance Rate among Coastal Uplands ..................................................... 70
Table D-3- Yearly Disturbance Rate among Low Olympic Ecoregion ........................................ 70
References .................................................................................................................................... 71

vii

List of Figures
Figure 1-1- Map of DNR Managed OESF Lands (WA DNR 2016). ........................................... 22
Figure 2-1-Map of the Olympic Experimental Forest and Landownership (OESF 2017). ........ 24
Figure 2-2- Percentage of Landowner’s Area in the OESF (WA DNR 2016). ............................ 24
Figure 2-3- Map of ECO Regions in OESF(US EPA, 2015) ....................................................... 27
Figure 2-4- Map of Vegetation Zones in the OESF (ECOSHARE, 2017) ................................... 27
Figure 2-5 Flow chart of Study Design......................................................................................... 30
Table 2-1- Data Type Used in Study ............................................................................................ 30
Table 3-1- Annual Disturbance Rates in OESF by Landownership Group .................................. 33
Table 3-2 Summary of Piecewise Regression Results for Each Landownership Type ................ 33
Figure 3-1- Graph of Disturbance Rate among Primary Landowners in OESF. .......................... 39
Table 3-3- Annual Disturbance Rate in OESF by EPA Level IV Ecoregions.............................. 41
Figure 3-2- Disturbance in Ecoregions in the OESF .................................................................... 41
Table 3-4- Yearly Disturbance Rates in the High Olympic Ecoregion ........................................ 42
Table 3-5- Annual Disturbance Rate by Different Vegetation Zones .......................................... 43
Figure 3-3-Disturbance in Primary Vegetation Zones .................................................................. 44
Figure A-1- Map of Disturbance in OESF .................................................................................... 47
Figure A-2- Map of Disturbance in the OESF by Two Year Groups (1985-98 and 1999-2012) . 48
Figure A-3- Map of Disturbance in DNR Lands in the OESF by YOD ....................................... 49
Figure A-4- Map of Disturbance in DNR lands in the OESF by Year Groups 1985-1998 and
1999-2012 ..................................................................................................................................... 50
Figure A-5- Map of Disturbance in ONP Lands in the OESF by YOD ....................................... 51
Figure A-6- Map of Disturbance in ONP Lands in the OESF by Year Groups 1985-1998 and
1999-2012 ..................................................................................................................................... 52
Figure A-7- Map of Disturbance in ONF Lands in the OESF by YOD ....................................... 53
Figure A-8- Map of Disturbance in ONF Lands in the OESF by Year Groups 1985-1998 and
1999-2012 ..................................................................................................................................... 54
Figure A-9- Map of Disturbance in Tribal Lands in the OESF by YOD ..................................... 55
Figure A-10- Map of Disturbance in Tribal Lands in the OESF by Year Groups 1985-1998 and
1999-2012 ..................................................................................................................................... 56
Figure A-11- Map of Disturbance in Private Lands in the OESF by YOD .................................. 57
Figure A-12- Map of Disturbance in Private Lands in the OESF by Year Groups 1985-1998 and
1999-2012 ..................................................................................................................................... 58
viii

Figure A-13- Map of Disturbance in the High Olympics Ecoregion by YOD (Mount Olympus).
....................................................................................................................................................... 59
Figure B-1- Overall Annual Disturbance Rates in OESF ............................................................. 60
Figure B-2- DNR Annual Disturbance Rates in OESF ................................................................ 60
Figure B-3- Timber by Board Feet in Olympic Region by Landownership (Klallam County,
Jefferson County, and Quinault Reservation, Washington) (Derived From WA DNR, 2018.) ... 61
Figure B-4- Level IV Ecoregions in the OESF by Area ............................................................... 61
Figure B-5- Annual Disturbance Rate in Coastal Lowlands by Landownership ......................... 62
Figure B-6- Annual Disturbance Rate in Coastal Uplands Ecoregion by Landownership........... 62
Figure B-7- Disturbance in Low Olympics Ecoregion by Landownership .................................. 63
Figure B-8- Annual Disturbance Rate by High Olympic Ecoregion ............................................ 63
Figure B-9- Disturbance by Vegetation Zones in OESF .............................................................. 64
Figure B-10- Annual Disturbance Rate in Sitka Spruce Vegetation Zone by Landownership Type
....................................................................................................................................................... 64
Figure B-11- Annual Disturbance in Western Hemlock Vegetation Zone by Landownership Type
....................................................................................................................................................... 65
Figure B-12- Annual Disturbance in Silver Fir Vegetation Zone by Landownership Type ........ 65
Table C-1 Table Summary of Piecewise Regression Results for Each Landownership Type
(Table 3-2 reproduced here as a reference for the Appendix C figures). ..................................... 66
Figure C-2- Overall Annual Disturbance Rates in the OESF with Piecewise Regression Analysis
Line ............................................................................................................................................... 67
Figure C-3- DNR Annual Disturbance Rates in the OESF with Piecewise Regression Analysis
Line ............................................................................................................................................... 67
Figure C-4- ONP Annual Disturbances Rates in the OESF with Piecewise Regression Analysis
Line ............................................................................................................................................... 67
Figure C-5 ONF Annual Disturbance Rates in OESF with piecewise Regression Analysis Line 68
Figure C-6- Private Annual Disturbance Rates in the OESF with the Piecewise Regression
Analysis Line ................................................................................................................................ 68
Figure C-7- Tribal Annual Disturbance Rates in the OESF with the Piecewise Regression
Analysis Line ................................................................................................................................ 69
Table D-1- Yearly Disturbance Rate in Coastal Lowlands Ecoregion ......................................... 70
Table D-2- Yearly Disturbance Rate among Coastal Uplands ..................................................... 70
Table D-3- Yearly Disturbance Rate among Low Olympic Ecoregion ........................................ 70

ix

List of Tables
Table 2-1- Data Type Used in Study ............................................................................................ 30
Table 3-1- Annual Disturbance Rates in OESF by Landownership Group .................................. 33
Table 3-2 Summary of Piecewise Regression Results for Each Landownership Type ................ 33
Table 3-3- Annual Disturbance Rate in OESF by EPA Level IV Ecoregions.............................. 41
Table 3-4- Yearly Disturbance Rates in the High Olympic Ecoregion ........................................ 42
Table 3-5- Annual Disturbance Rate by Different Vegetation Zones .......................................... 43
Table C-1 Table Summary of Piecewise Regression Results for Each Landownership Type
(Table 3-2 reproduced here as a reference for the Appendix C figures). ..................................... 66
Table D-1- Yearly Disturbance Rate in Coastal Lowlands Ecoregion ......................................... 70
Table D-2- Yearly Disturbance Rate among Coastal Uplands ..................................................... 70
Table D-3- Yearly Disturbance Rate among Low Olympic Ecoregion ........................................ 70

x

Acknowledgements
I wouldn’t have been able to finish this thesis without the help of the Washington State
Department of Natural Resources (DNR). Kyle Martens, Warren Devine, and Teodora Minkova,
Ph.D., helped me form a feasible hypothesis for the project. They also provided support and
advice for how to accomplish my thesis. I’d like to thank John Withey for his support as my
thesis adviser. He gave technical assistance with GIS and the statistics model associated with my
project. I’d like to thank the LandTrendr developers Dr. Robert Kennedy and Oregon State for
publishing the LandTrendr Northwest Forest Plan maps and granting permission to use their
data. I’d like to thank Katherine Copass from the Olympic National Park for providing practical
knowledge and technical assistance on LandTrendr. I’d like to finally thank my family for their
assistance and especially my sister Joy with her editorial support. My thesis paper would not
have been possible without the support of these people.

xi

Introduction
Disturbance is a widespread phenomenon in nature and is common in all ecosystems.
Disturbance is an important ecological process shaping ecosystems (Attiwill, 1994a; White &
Pickett, 1985). Disturbance can be defined as any event that changes the trajectory or spatial
extents of an ecosystem and is important in shaping ecosystem function and structure (White &
Pickett, 1985). Forest disturbance can be a natural processes like fire, windstorms, diseases, and
damage or mortality from insects. Disturbance can also stem from anthropogenic causes such as
timber harvests, road building, housing development, agriculture, and infrastructure building
projects. As a forest grows, a disturbance event can change a forest by a small event like a single
tree fall or a large event (for example-timber harvest and fires). Disturbance events can also
impact humans such as landslides damaging roads and windblown events damaging trees that
would be harvested at a later time. These disturbance events can cause economic and physical
harm to humans, their buildings, and infrastructure (roads, pipelines, power lines, etc.). These
natural events in forest ecosystems may reduce the profitability of timber harvest (Cliff Mass,
2005). Humans have historically changed disturbance regimes in forests across the United States
by fire suppression or timber production (Franklin & Johnson, 2012). Modern timber production
uses clearcutting techniques which consists of harvesting nearly all of the trees and this changes
the structure and species affected by the clearcutting.
Disturbance has been increasingly studied by ecologists because of the importance it has
in shaping forest ecosystems. Ecologists have recognized that disturbance regimes have been
greatly altered by humans in the last one hundred years. Temperate forests on the Pacific Coast
specifically face disturbances of infrequent large wildfires and large and small scale windstorms
that help achieve complex old growth forest ecosystems (Franklin & Johnson, 2012). These
1

forests have been historically logged and their primary economic purpose is timber production.
Natural disturbance events happen less frequently and on average a smaller scale than modern
timber harvests in the Pacific Northwest. Historical timber production provided poor habitat for
seral species and modern practices have changed historical disturbance regimes, which has
caused the function and structure of forests to change (White & Pickett, 1985). Ecologists
studying disturbances are alarmed because disturbance regimes across the planet are changing
rapidly due to anthropogenic climate change and the consequences of this is unknown.
Currently, the Western United States has experienced an increased frequency of large fires and
this is strongly associated with higher than historically normal temperatures (Halofsky et al.,
2011; Turner, 2010). Studying disturbances is important to better understand how future
disturbance will shape ecosystems.
An important method used to detect forest disturbances is remote sensing technology.
The 1960s and 1970s brought two technologies that have helped aid ecologists studying
disturbance; Landsat Imagery and Geographic Information Systems (GIS). The launch of
Landsat satellites enabled scientists to study the earth through satellite imagery. At the same
time, electronic computing lay the foundation for GIS software which could model and map
Earth. Scientists were able to use Landsat Imagery and GIS to model and study spatial and
temporal trends in ecosystems (Cohen & Goward, 2004). Since the implementation of both of
these technologies, computing power has increased exponentially and higher resolution of
Landsat imagery has increased the effectiveness of these remote sensing methods to analyze
disturbance patterns across the planet. These two technologies are used together and are used by
researchers to study landscape disturbance regimes and forest cover rates. Using GIS and
Landsat imagery has become an effective and common way of detecting trends and patterns of

2

disturbance over time. LandTrendr software is an algorithm that creates disturbance maps and
was developed by researchers at Oregon State University to detect disturbance in forests
landscapes (Kennedy et al., 2009).
The Olympic Peninsula in Western Washington State has large temperate rainforests and
various landowners who have different objectives in managing their forests. The Olympic
Peninsula encompasses the Olympic National Park (ONP), Olympic National Forest (ONF),
State lands (managed by Washington State Department of Natural Resources (DNR), Tribal
lands and private landowners (many are owner my commercial timber companies). Washington
State DNR established the Olympic Experimental State Forest (OESF) on the western half of the
Olympic forest (Figure 1-1- Map of DNR Managed OESF Lands (WA DNR 2016).. The state of
Washington approved a Habitat Conservation Plan (HCP) for multispecies habitat management
for Federally-listed endangered species on Washington state lands in 1997. The establishment of
the HCP was the state of Washington’s requirement to comply with the Federal Endangered
Species Act. The HCP’s objective is to protect habitat for endangered species in state lands
managed by DNR. The HCP designates the OESF as a state experimental forest and lays out its
unique purpose among Washington state managed lands. The purpose of the OESF is to research
natural phenomenon and to study natural processes in working forests. One of the objectives of
the OESF is to study how disturbance affects their forest and how these patterns can be applied
to other forests in Washington and the Pacific Northwest (WA DNR, 1997, 2016). This thesis
paper will use LandTrendr software to determine annual disturbance trends in the forest from
1985-2012. Management practices have changed in the OESF since the 1980s and this paper
will look at how disturbance has affected the OESF by answering these five questions:

3

Research Questions
1) What is the disturbance rate on forest lands in the Olympic Experimental State Forest
(OESF)?
2) Has the disturbance rate on the DNR lands in the OESF since 1999, when the Habitat
Conservation Plan was implemented?
3) What are differences in disturbance rates by different land ownership categories in the
Olympic Experimental State Forest?
4) What is the disturbance rate across the different ecoregions in the OESF?
5) What is the disturbance rate across the different forest vegetation zones?

4

Chapter 1-Literature Review
Introduction
Disturbance is an event that changes the spatial and temporal trajectory of an ecosystem
(Turner, 2010). For example, a temperate rain forest in Olympic Peninsula in Western
Washington can grow for hundreds of years and will eventually be dominated by Western
hemlock, its climax community. A climax community will hypothetically stay on the same
trajectory or stay in equilibrium until a disturbance event happens (for example, a windthrow
event that blows down trees and opens the forest canopy). These disturbance events create
heterogeneity in a forest (White & Pickett, 1985). Forest openings allow early successional
species that thrive in sunlight to germinate, grow, and reproduce (Peterson et al., 1997) A
disturbance can be small or large in spatial extent, and potentially change the structure and
species composition of the forest. Disturbances therefore shape a forest and have been
increasingly studied by ecologists. This literature review will examine what disturbance is, the
common terms used by ecologists and foresters, and existing disturbance research in forest
ecosystems.
The Olympic Experimental State Forest (OESF) was created on the Olympic Peninsula to
study to natural phenomenon in a working forest by the Washington State Department of Natural
Resources (DNF). The creation and the history of forestry practices in OESF will be examined
as will disturbance related research in the OESF and the Pacific Northwest. The paper will then
focus on remote sensing techniques and how disturbance is determined using remotes sensing
techniques. LandTrendr will be used as the primary methodology in this study and studies using
this software will be reviewed. The chief OESF researcher had a database compiled in 2011 that
attempted to include all disturbance related research in the OESF. The purpose of this
bibliography was to examine how disturbance has shaped the OESF and how to incorporate
5

disturbance’s spatial and temporal variability in the management standards of the OESF (Foster
et al., 2011).
Ecological Disturbance
White and Picket et al., (1985) describe disturbance as an event that changes the structure
of an ecosystem, resource availability, and the physical environment of the ecosystem. The
previously stated definition is often cited as the standard definition in most of the reviewed
literature. Disturbance affects all ecosystems through all range of scale and alter the state and
trajectory of an ecosystem (Turner, 2010; White & Pickett, 1985). Disturbances are a major
factor in development and function of forests and disturbance is widespread across all
ecosystems on the planet (Attiwill, 1994b; White & Pickett, 1985). Few communities exist in
equilibrium where disturbance does not happen. Biological and physical processes act as agents
of disturbance and the latter is most commonly associated with disturbance (Sousa, 1984).
Disturbance events can be hard for researchers to detect because they occur over a wide range of
size, frequency, seasons, and magnitude (Attiwill, 1994b). An example of a small scale
disturbance event is when a single tree falls, creating small forest gaps (Attiwill, 1994b).
After a disturbance event, the ability of an ecosystem to absorb the changes and return to
an equilibrium or previous state is called resilience. After a disturbance like a fire or windfall, a
forest will go through a period of community succession, with some species more adapted to
greater sunlight availability replacing others. In old growth forests in the Eastern United States,
disturbance was causing gaps in the forest at about 1% per year and these gaps were vital to
increase success of early successional species and other species that need more sunlight (Runkle,
1982).

6

Major sources of natural disturbances in forests across the world are fire, hurricanes or
typhoons, windstorms, mass movements, flooding, droughts, and biotic disturbances such as
pests and disease (Attiwill, 1994b; Wallin et al., 1996; White & Pickett, 1985). These were the
main disturbance agents in OESF before European settlement (WA DNR, 2016). Disturbance
can happen over different time periods, such as a windstorm that occurs over hours, or a pine
beetle infestation that can kill trees over a period of years (Turner 2010). Mass movement events
include landslides as well as debris flows or torrents (Copass & S., 2016). Debris flow is fast
moving event that is combination of debris and water. These events can scour river and stream
bed and also bury vegetation under sediment. Debris flow event in the Olympic can have effects
on riparian habitat for over one hundred years (Benda et al., 2003). The term ‘disturbance
regime’ describes how often a certain type of disturbance typically happens in an ecosystem.
Fire disturbance regime describes, on average, how often a forest experiences a forest fire. The
most common type of natural type of disturbance in the OESF are windstorms, landslides, fire,
and pests (Peterson et al., 1997; WA DNR, 2016)
Windthrow
Windthrow or windfall events are fairly common in the OESF. Windthrow events occur
from small to large spatial scales. A single tree could blow down from the wind because of
factors like decay and insects, whereas a hurricane or wind storm can cause a large percentage of
trees to blow down in a large area of forest (Attiwill, 1994b). Historically, windstorms typically
occur in the winter in the Pacific Northwest (Cliff Mass, 2005). Native Americans have legends
about strong windstorm including one from the Quillayute tribe (whose lands are in the OESF)
where Thunderbirds (a giant mythological bird) are the cause of these strong winds. The

7

Quillayute tribe would move to a sheltered area in the winter to protect themselves from the
storms (Mass, 2005).
The giant windfall of 1921 was a large-scale windthrow event and affected 20% of the
forests on the Olympic Peninsula (Cliff Mass, 2005). There has been at least fourteen storms
with hurricane strength winds on the Washington coast in the previous 200 years; two of these
fourteen storms recorded winds with over 150 miles per hour (Cole Mass, 2008). These events
have shaped the forest in the OESF and also cause timber productivity losses. Blowdowns on
the Olympic Peninsula can lead to complete stand or partial stand replacement in the Olympic
Peninsula. The common silvicultural practice for DNR in the OESF after windthrow events is to
salvage the fallen trees and then replant (WA DNR, 2016). There is concern that with climate
change there could be an increase in weather patterns that favor strong windstorms (Devine et
al., 2012; Halofsky, 2013). Climate change could also lead to more disturbance in the future and
this could lead to more insect and tree mortality, landslides, and fires (Halofsky, 2013).
Fire
Fire is often the most predominant disturbance type in many forests (Attiwill, 1994b).
Fire has been suppressed by modern societies since the early 20th century (Wallin et al., 1996).
Fire regimes varies across the Western United States and are dependent on vegetation and annual
precipitation rates. In the Douglas Fir (Pseudotsuga menziesii) forest type the average is around
230 years in the Pacific Northwest, though historically this type of forest wasn’t abundant in the
OESF (Agee, 1991, 1996). However, specifically in the western part of the Olympic Peninsula,
fire regimes for the Western hemlock (Tsuga hetrophylala) forest type are about once every
millennia and for Douglas fir forest types, about every 750 years (Agee 1991, 1996). These are
very long intervals compared to most fire regimes in the Western United States and is because of
8

the high rates of precipitation in the Olympic Peninsula. However, remote sensing data reveals
that fire has become a more common factor in the loss of old-growth forests since the
implementation of the Northwest Forest Plan (NWFP) in the 1990s, which could be linked to
climate change (Healey et al., 2008)
The size and intensity of forest fires in the Olympic Peninsula is less than in most other
parts of the Pacific Northwest, although large scale fire events of over thousands of acres have
occurred. There are stories of large fires among the Native American tribes that live in the
Coastal forest of the Pacific Northwest. The Quinault tribe has a legend of a massive fire in the
western Olympic Peninsula: the fire came down from the Olympic Mountains and drove the tribe
to the sea (Agee, 1991, 1996) Modern forest management has suppressed fire activity through
fire suppression and timber harvesting (Agee, 1996). Fir is crucial in the stand development and
species recruitment in northwestern forests and suppression and timber harvesting could change
the composition of these forests (Agee, 1991).
There has only been one large fire (over 100 acres burned) in the OESF since 1985 and
in was the Paradise fire. It was in the Hoh river drainage in the Olympic National Park. It was
2,798 acres and was caused by lightning in 2015 (WA DNR, 2018b). There has been a total of
seven large fires in the Olympic Peninsula (outside the OESF) according to WA DNR data from
1973-2016, and only the Paradise fire was in the boundaries of the OESF. Since 2008, the DNR
has recorded a total of 75 fires in the OESF region and all of were small fires (less than 100
acres). There may be missing data in the database because of the 75 fires only one is located in
the ONP, which is about a third of total area in the OESF. The total amount of acres burned in
these fires is 276 acres, this is quite small compared to other regions in the west that have large
fire disturbance regimes. Of the 75 fires, 28 were noted as caused by logging activities such as
9

deliberately burning debris from logging activities and one lightning caused fire (WA DNR,
2018b).
These data and other research suggest that the Olympics have a low rate of lightningcaused fire. Agee (1991) ran a simulation for lighting ignitions in four forests in the Pacific
Northwest: the Western Olympics and Wind River in Washington, and McKenzie River and
Siskiyou’s in Oregon. The western Olympics had the smallest ignition rate at 0.2 per year per
175,000-ha. This could be a possible reason that Olympics have a low-frequency fire regime.
History of the Forests on the Olympic Peninsula
The Olympic Peninsula has a high amount of biodiversity because of its geographical
location, mountains, and unique geological history (Peterson et al. 1997). The Olympic
Peninsula was not affected by the giant ice sheet of Fraser glaciation period from ~15,000 years
before present (Peterson, et al 1997). Because of this geologic history, seven of the eight plant
taxa endemic to the Olympics survived the Ice Age and contribute to the uniqueness of the area.
The coniferous forest within the Olympic Peninsula is an important producer of wood
products and the forests have been extensively harvest for timber in the last century. Washington
state law in 1948 mandated all logged forests had to be replanted. Laws in the 1970s and 1980s
further mandated how forests should be managed (WA DNR, 2018a). The harvest of virgin or
old growth forests led to tension between economies that relied on timber product and groups
that advocated for the existence of old growth forest that served as habitat for species such as the
marbled murrelet (Brachyramphus marmoratus) and the northern spotted owl (Strix occidentalis
caurina) (Kennedy et al., 2012; Moeur et al., 2011).

10

The northern spotted owl was listed as threatened under the Endangered Species Act in
1990 and this led to multiple lawsuits on how the federal government managed federally-owned
forests in the Pacific Northwest (Moeur et al., 2011).. The concern for the old growth forests led
to the Northwest Forest Plan (NWFP). The NWFP led to changes in timber harvest activities
and has reduced forest timber harvest and disturbance levels across the northwest in federal
lands. The purpose of the NWFP was to protect forests and the species that use them such as
northern spotted owls and marbled murrelets (Kennedy et al., 2012; WA DNR, 1997).
The Olympic National Forest (ONF) was established in 1897 as the Olympic Forest
Reserve, and as a National Forest in 1907, and encompasses over 256,400 acres on the Olympic
Peninsula (Halofsky et al., 2011; Lesher et al., 1989). Prior to the 1990s, ONF management
practices favored timber production in the forest. Timber harvest began in the 1920s and an
estimated 1/3 of the total forest was harvested by 1990. The NWFP directly led to management
change in the ONF in 1994. The NWFP shifted ONF management to ecosystem management.
The current ONF focus is on ecological restoration and has objectives that focus on the
protection and restoration of late successional or old growth forest (Halofsky et al., 2011).
Timber harvest activities have significantly reduced since the NWFP implementation and this
can be seen when reviewing Washington State timber harvest reports (WA DNR, 2017).
The Olympic National Park (ONP) was first established as a National Monument in 1909
under President Theodore Roosevelt (Lesher et al., 1989). The National Monument was
established primarily to protect its native elk species-Roosevelt elk (Cervus canadensis
roosevelti). The ONP was created out of the national monument in 1938. The park has
expanded multiple times from 680,000 acres to the current size of approximately 936,011 acres
(Halofsky et al., 2011; Lesher et al., 1989). One of the ONP expansions added a 110 km coastal
11

strip (which is entirely in the OESF). Most of the park is in relatively pristine condition
compared to lands outside of ONP, though there are some concentrated areas of human activity
by park visitors. The purpose of the ONP is to conserve the scenery, the natural objects, and
wildlife for the future (Halofsky et al., 2011).
The Olympic Experimental Forest (OESF) was created in 1992 by the Washington
Department of Natural Resources (DNR) in order to learn how to integrate revenue production
and ecological values in a working forest (WA DNR, 2016). The OESF is located on the
Northwest section of the Olympic Peninsula in Washington State (Figure 1-1). The OESF
mission statement only applies to DNR lands in the OESF, which are a part of Washington state
trust lands. The primary purpose of Washington State trust lands is to generate revenue for
public education for the state of Washington (WA DNR, 1997). The OESF has four other major
types of land ownership: private lands (whose primary purpose is typically timber production),
tribal lands, Olympic National Forest, and the Olympic National Park (WA DNR, 2016).
In 1997, Washington State created a Habitat Conservation Plan (HCP) for state trust
lands that details how the DNR will restore, maintain, and enhance habitat for endangered
species, which was authorized under the Endangered Species Act (ESA) to protect listed species
that occupy the OESF (WA DNR, 1997). The HCP describes the conservation strategies for how
the Washington Department of Natural Resources (DNR) will restore and enhance habitation for
listed species such as the northern spotted owl and marbled murrelet, in conjunction with using
best practices for timber harvest and activities on its forested lands. The HCP has four major
strategies: riparian (management strategies for aquatic species, including salmonids and others),
northern spotted owl, marbled murrelet (management strategies for restoring and maintaining
their habitat), and multispecies (habitat management for unlisted species and species that have
12

risk of local extinction). The HCP also describe how they will implement adaptive management
and research and monitoring in the OESF (WA DNR, 1997, 2016).
The 1997 Washington state trust lands HCP was established in coordination with the
Northwest Forest Plan of 1997 (WA DNR, 1997). Under the 1997 HCP, the DNR manages state
trust lands on the OESF in a manner that integrates revenue production with ecological values
across the landscape. One of the DNR’s conservation objectives is to study natural disturbance
regimes in the OESF. The DNR wants to study how scales and frequencies of both natural and
anthropogenic disturbances affect the OESF (WA DNR, 1997). DNR has determined there is
limited knowledge of what natural landscapes caused by disturbance looks like and DNR is
trying to learn how the spatial and natural variability of disturbance should be incorporated in the
management of their forest (Foster et al., 2011). DNR also set aside lands in the OESF that are
used by endangered species and provide protection for riparian habitat (WA DNR, 2016). In
2011, the OESF commissioned a bibliography to record all instances of disturbance and research
of disturbance in the OESF to establish a reference pool for future projects describing
disturbance in the OESF (Foster et al., 2011).
The DNR’s objectives to estimate and understand patterns in forest disturbances is the
reason for this project and the author is trying to determine how disturbance has affected
landscapes in the OESF. Disturbance is importance is natural ecosystems and are vital to the
diversity of forest ecosystems and is important in forest stand development (Franklin et al.,
2002). Large scale natural disturbances occur in the OESF, and have influenced the structure of
the forest and have long lasting impacts to landscape in the OESF (WA DNR, 2013). In the last
four decades silviculture practices have tried to use practices from disturbance ecology that are

13

more aligned to natural disturbance process (Attiwill, 1994b; Franklin et al., 2002; Franklin &
Forman, 1987).
Vegetation Types and Ecoregions
There are many different vegetation types in the OESF. A vegetation type is determined
by the most shade tolerant species in an ecosystem (Lesher et al., 1989). Vegetation types affect
the disturbance rate in area. The vegetation types in the OESF are Sitka spruce (Picea
sitchensis), Western hemlock (Tsuga heterophylla), Pacific silver fir (Abies amabilis), mountain
hemlock (Tsuga mertensiana), parkland, alpine, and subalpine fir (Abies lasiocarpa)
(ECOSHARE, 2017). Kennedy et al. (2012) studied disturbance using LandTrendr in ecoregions
across the OESF, but did not break out disturbance rates by vegetation types, so this is one of the
primary questions of this thesis.
Geographers have classified ecological communities that are similar as “ecoregions.”
Omernik (1987) developed this framework with federal agencies and other North American
countries, they mapped these ecoregions in North America (Omernik, 1987; US EPA, 2015).
The purpose of having ecoregions is to develop a common system for research, monitoring and
assessment of similar types of ecosystems. Ecoregions are hierarchal from I to IV, and there are
four types of level IV ecoregions in the OESF. The Coastal Lowlands consist of marine
estuaries, beaches, and lowland lands and western hemlock/Sitka spruce forests in the OESF
region (US EPA, 2015). This is the smallest ecoregion in the OESF, which is less than 3% of
total area. The Coastal Uplands consist of coastal headlands and higher gradient streams. The
main forest in the OESF consists of Western hemlock, Sitka spruce, Western red cedar (Thuja
plicata), and Douglas fir (Pseudotsuga menziesii) trees. The Low Olympic ecoregions consist of
low mountains and previously glaciated areas. The main forests are Western hemlock, western
14

red cedar, and Pacific silver fir. Low Olympics and Coastal Uplands is the most common
ecoregion in the OESF. The High Olympic ecoregion is only found in the ONP and consists of
glaciers, mountains, subalpine coniferous forests and meadow (US EPA, 2015).
Human Caused Disturbance
Disturbance caused by humans (timber harvest activities, dams, agriculture, and human
settlements) have about the same impact at a spatial scale, but not at the same temporal scale to
largest natural disturbance such as fire). Fire can be quite large across the landscape and usually
takes place in a period of days happens from days to months while large scale human disturbance
such as timber harvest takes place over years and does not progress as rapidly as a fire.
According to Peterson (1997) anthropogenic activities are more frequent and fragment the
landscape more than natural disturbance in the Pacific Northwest forest region. Human activities
could lead to less diversity and reduce the spatial and temporal scale of natural disturbances such
as fire (Peterson et al., 1997). Peterson (1997) noted that in clear-cuts caused by logging a lot of
early succession species exist and this could cause species that are more adapted to prevalent
disturbance.
High levels of disturbance has reduced connectivity between various habitats and this
could cause the loss of species and especially in lowland vegetation and wetlands due to future
climatic change. Peterson et al. (1997) concluded that by 1988 timber harvests had removed
over 75% of old growth forest in the ONF and almost all old growth forest in tribal, state, and
private lands. Species before human settlement that dominated the area such as Sitka spruce
(Picea sitchensis) and Low elevation Douglas fir (Pseudotsuga menziesii) has been reduced
drastically in the Olympic Peninsula. The forests in Olympic Peninsula get harvested at about
every 50-80 years (Peterson et al., 1997). After a forest gets logged it can be followed by slash
15

burning, this can somewhat mimic the disturbance of a fire, but is quite different as there is less
snags (standing dead trees) and more soil disturbance (Agee, 1991; Ruggiero, et al. 1991). This
has led to a simplification of a class in the forests through simplifying the structure and species
composition. Peterson (1997) studied clear cuts in the Olympic Peninsula and found a
proliferation of early successional and exotic species in clear cuts. They concluded that these
early successional species will be more abundant in areas with a high amount of disturbed areas
like in the Olympic Peninsula (Peterson et al., 1997).
Since the 1980s researchers have proposed that anthropogenic actions such as timber
harvest can be used to mimic natural disturbance events (Agee, 1991, 1996; Attiwill, 1994b;
Franklin et al., 2002; Franklin & Forman, 1987). Franklin (2002) looked at modern forest
methods and how they shape the forest and compared them to natural forest. Franklin noted that
structural development of forest is very complex and that disturbance processes contribute to
forest development and structure. Modern timber practices such as clearcutting are not based on
natural disturbance processes. Attiwill (1993) in a study of disturbances stated the greater the
magnitude of a disturbance, the less likely the forest will recover. Diversity, structure, and the
functions of forests are developed by natural disturbance that silviculture practices should be
based on natural disturbance process.
Silviculture practices traditionally did not try to replicate natural disturbance and
foresters simply tried to maximize production in the forest. Foresters currently use practices that
help resemble natural disturbance patterns that encourage different patterns of forest and retain
parts of the previous forest structure (Franklin et al., 2002). Current laws also regulate how
foresters have to leave gaps and leave undisturbed space in wetlands and riparian areas (WA
DNR, 2018a). DNR set areas in the OESF that are off limits to timber harvest activities to
16

protect species and watersheds by providing habitat buffers. Under the 1997 HCP, the DNR
reduces harvest on unstable slopes, restores and maintains habitat for northern spotted owls and
marbled murrelets. DNR also thins forest stands in different densities to maintain a diverse
forest structure. Current OESF forest practices managed by DNR leave standing and down
snags, some uncut trees to help improve the structure and diversity of their forest stands and they
also protect old growth forest stands from timber harvest where previous to HCP and other
management practices implemented in the 1990s, the policy was to harvest older and larger
forests (WA DNR, 1997, 2016).
Spatial Methods to Analyze Disturbance
Researchers often use remote sensing to help analyze disturbance in forests (Cohen et al.,
2017). Remote sensing helps researchers show connections between natural disturbances and
human disturbances. Land satellite (Landsat) data is a common remote sensing method for
monitoring disturbance in forests (Cohen et al., 2017). Land Satellite Time series (LTS) data has
been used over 40 years for remote sensing. Landsat data can be within 30 m range (Cohen et al.,
2017). Landsat data is obtained freely from NASA and includes Landsat Thematic Mapper
(TM) data. TM data has fine grain photos to detect small scale disturbance like patches in the
forest and roads and large scale event like a large fire (over a hundred acres). A limitation of TM
data is it only goes back to 1984 (Kennedy et al., 2012).
There are numerous software programs that use algorithms to analyze disturbance using
Landsat data. Cohen et al. (2017) conducted a study using six Landsat scenes to determine the
similarity and differences among seven different algorithms. The algorithm analyzes the pixel
data and determines which areas have been disturbed. All of the software programs, that were
reviewed, can detect long term disturbances (large scale insect kills, fires, clear cuts) and short
17

term disturbances (windstorms or timber clear cuts). The researchers noted that of the seven
algorithms, all were in general agreement about areas that had no disturbance but areas with
disturbance the algorithms had a great amount of variability in the magnitude of disturbance. As
in areas with low magnitude of disturbance (small insect kills, tree mortality, small scale wind
blow down), the different software reviewed showed high variability. Not all of the programs
agreed how large or scale of small magnitude disturbance. The researchers found agreement
among areas that showed high magnitude of disturbance (Cohen et al., 2017).
The algorithm from these disturbances I will use in these studies is LandTrendr
developed from Oregon State (Kennedy et al., 2010). The disturbance maps created from
LandTrendr is what I am using for this study to determine what the disturbance rates are in the
OESF. LandTrendr was developed in 2010 and is currently still being updated from Oregon State
(Kennedy et al., 2010). LandTrendr developers developed maps for the NWFP region
(Washington, Oregon, and California) to analyze how disturbance has shaped the NWFP, the.
The researchers published these maps online1 for public use.
Landscape Disturbance rates in the Pacific Northwest
Remote sensing technology has allowed researchers to study disturbance and land cover
rates in forests in the Pacific Northwest. Researchers have been study disturbance with remote
sensing technology at least since the 1990s. Turner et al. (1996) used the Landsat multiple
scanner imager to analyze forest cover in the Hoh River basin (which is in the OESF) and the
Dungeness River basin, Washington, and a river basin in Tennessee. The authors used formulae
that analyzed satellite imagery to determine how much forest cover existed in each area. Their

1

http://landtrendr.forestry.oregonstate.edu/content/download-data
18

analysis showed forest cover rates were higher in federally owned land than in state and private
lands in the Olympic Peninsula. Turner el al. (1996) also noticed that harvesting trends in private
lands owned by commercial timber lands in the Hoh River basin were influenced by economic
forces. They did not find the same trends in the Dungeness river basin, and attributed this to
more large commercial timber land in the Hoh basin than in the Dungeness (Turner et al. 1996).
The researchers noted that in when timber prices increased, disturbance increased in the Hoh
basin (Turner et al., 1996). This study was conducted when the primary purpose of DNR lands
was to generate revenue from timber harvesting and before the implementation of the HCP and
NWFP. During this time period, federal lands had lower rates of disturbance than state and
federal. Their primary conclusion was that land ownership has a strong effect on disturbance
patterns and forest cover rates in their study.
Kennedy et al. (2012) conducted a study using LandTrendr to analyze disturbance rates
in the Pacific Northwest, which they used LTS data from 1985 to 2008. Their goal of the study
was to determine if the NWFP of 1994 changed disturbance rates across the forests of the Pacific
Northwest and looked at land ownership. Kennedy used disturbance through the whole forest
instead of annual disturbance rates. They found a high level of disturbance in the Olympic
region compared to other areas (Kennedy et al., 2012). The models generated showed that the
predominance disturbance in the Olympic region is timber harvest compared to other regions
using the greatest disturbance map (Kennedy et al., 2012; Ohmann et al., 2012). Disturbance
rate on native lands increased after 1993. Disturbance on non-protected federal lands decreased
after implementation of the NWFP. Researchers noted that disturbance in state lands in
Washington decreased after the implementation of the NWFP.

19

Disturbance Research in the OESF
Disturbance has been studied in the OESF by many different researchers. The DNR
wanted to keep track of all disturbance related studies in the OESF and landscape that was
simpler and created a bibliography for all disturbance related research in 2011(Foster et al.,
2011). The bibliography also cites any disturbance related research to Olympic Peninsula.
National Park Service researchers used LandTrendr to study disturbance in the ONP and
the lands surrounding it on the Olympic Peninsula, Mount Rainer, and North Cascades National
Park. The National Park researchers worked with Dr. Kennedy, the lead developer of
LandTrendr. The researchers mapped the different types of disturbance in the ONP and
surrounding forests on the Olympic Peninsula from 1985-2010 (WA-DNR, 2017). The
researchers used LandTrendr disturbance patterns focused on land imagery to determine what
type of agent caused the disturbance. The researchers used the fast disturbance event by year
data from LandTrendr. The researchers labeled the disturbance event in their study area and
measured disturbance by total area disturbed by hectares. One of the most common types of
disturbance noticed inside and outside the ONP was wind throw events. In 2007, nine of the top
ten largest natural disturbance events in the ONP were wind throw events that ranged from 44 to
10 acres (Thompson et al., 2011). There was a large wind blow event in the Quinault and Queets
river valley in 2005. This wind blow event was noted by ONP researchers using LandTrendr.
This wind blow event was quite large and wide-spread and affected private lands, ONF, and
ONP. The most common natural events in the study area were wind throw, fires, riparian
disturbance, avalanche, winter ice events, defoliation, and mass movement. Outside ONP,
landscape clearing caused by timber harvest was the most dominant and common form of
disturbance and had high levels in the 1990s and 2000s. The study determined that private lands

20

had highest rate of timber harvest followed by Tribal and DNR lands, ONF, and lastly ONP.
(Copass & S., 2016) The challenges the researchers noticed in the study were that slow changes
like insect and disease were hard to detect using the fast disturbance map in LandTrendr.
Conclusion
The OESF was established as a working research forest (WA DNR, 2016). DNR is
studying how natural processes shape forest and how understand the process that shape
disturbance can be used to help establish sustainable practices for forestry on their lands. The
OESF has multiple landowner with different management objectives on their respective forest
lands (WA DNR, 1997). Multiple management objectives throughout the OESF have shaped the
structure and disturbance rate of the OESF (Turner et al., 1996). Disturbance is an important
influence on forest ecosystems (White & Pickett, 1985). Disturbance shapes the function,
structure, and diversity of the forest. The natural disturbance categories that affects the OESF
are wind, fire, landslides, insects, and disease. The OESF has a low fire regime compared to
many forests in the west, but has had large historical forest fires (over thousands of acres) in the
past. Windblown events are quite important in shaping the OESF and are quite common and can
range from very small to very large events.
Currently the largest disturbance agent in the OESF is timber harvest. Studies have
showed that clearcutting practices shape diversity and the function of the forest. Modern
methods use remote sensing to best detect disturbance. LandTrendr was developed to look at
disturbance and has been used many times to study disturbance rates and help determine what
caused the disturbance. LandTrendr has also been used to show Federal lands have reduced
disturbance levels since the implementation of the NWFP. Furthermore, Washington DNR lands
have reduced their disturbance levels since the 1990s.
21

Figure 1-1- Map of DNR Managed OESF Lands (WA DNR 2016).

22

Chapter 2-Methods
The maps and primary data for this thesis use the LandTrendr (Landsat-based detection
of Trends in Disturbance and Recovery) approach to extract spectral trajectories of land surface
change from yearly Landsat time-series stacks (LTS) and NASA Landsat imagery scenes (Cohen
et al., 2017; Kennedy et al., 2012; Kennedy, Yang, & Cohen, 2010). LandTrendr data from
1985-2015, that covers the NASA LTS scenes 48/26, 48/27, and 47/27, were used for this
analysis. LandTrendr was developed by Oregon State University as a method to analyze remote
sensing data (Kennedy et al., 2010). LandTrendr software can detect the magnitude, duration,
and detection of disturbance using land cover layers in ArcGIS. The LandTrendr output was
analyzed using ArcGIS to determine the amount and timing of forest disturbance in the Olympic
Experimental State Forest (OESF). The rates of disturbance will be compared by primary land
ownership types in the OESF, which includes Washington DNR Lands, Private, Tribal, Olympic
National Park (ONP), and Olympic National Forest (ONF). All disturbance in Olympic National
Park (ONP) is assumed as natural disturbance since they do not allow logging and other large
scale human disturbance. All the landowners have different primary goals for their lands, so we
expect to observe some differences in forest disturbance rates.

23

Figure 2-1-Map of the Olympic Experimental Forest and Landownership (OESF 2017).

Figure 2-2- Percentage of Landowner’s Area in the OESF (WA DNR 2016).
NPS (National Park Service), USFS (United States Forest Service), DNR (Washington State
Department of Natural Resources), Tribes (Makah Tribe, Quinault Indian Nation, Quileute
Tribe, and the Hoh Tribe.)
24

The OESF Study Area
The study area is the Olympic Experimental State Forest OES and lies in the northeast
section of the Olympic Peninsula in Washington State (Figure 1-1- Map of DNR Managed OESF
Lands (WA DNR 2016).; Figure 2-1-Map of the Olympic Experimental Forest and Landownership
(OESF 2017).). The study compared different disturbance rates across the five main landowner in

the OESF (from largest to smallest landownership group) - private, Olympic National Park
(ONP), and Olympic National Forest (ONF; Figure 2-2- Percentage of Landowner’s Area in the
OESF (WA DNR 2016).). The area has a total of 1.3 million acres with acres with DNR lands

consisting of 275,506 acres. The largest landownership group is private owners with about
370,000 acres, ONP is responsible for approximately 355,000 acres, ONF with about 158,00
acres, and tribal lands compose of about 133,300 acres There are four tribes with reservation and
tribal managed lands in the OESF; Quinault Indian Nation (92,734 acres), Makah Tribe (92,734
Acres), Quileute Tribe (1,859 acres) and the Hoh Tribe (1,009 acres) (WA DNR, 2018b).
The OESF lies in the temperate rainforest of the Olympic Peninsula from coastal wetland
to high alpine mountains and glaciers of the Olympic Mountains. The area has high amount of
rain fall with annual precipitation of 80 to 180 inches a year (WA DNR, 2016). The elevation
range is from sea level to 7980 feet. The DNR lands in the OESF comprise elevation from 12
feet to 3680 feet. The area lies within two level III EPA ecoregions (Coast range and North
Cascades). The 4 Level IV ecoregions are Coastal Lowlands, Coastal uplands, Low Olympics
and High Olympics (US EPA, 2015) (Figure 2-3- Map of ECO Regions in OESF(US EPA, 2015)).
The High Olympic Ecoregion will be excluded from the forest study area since most of this
terrain is alpine isand is protected in Olympic National Park.
The main forest disturbance in the OESF is timber harvest. The main natural disturbance
25

factors in the regions are fires, insects, wind blows, landslides, and floods (WA DNR, 2016).
The primary management objectives are different for the different landowners. The lands of the
OESF are managed for the benefit of the State trust. Private forest lands are operated by private
landowners who are supervised by state forest land regulations. The Forest Service lands are
managed by the U.S. Forest Service under the Northwest forest plans. The National Park lands
are protected from forest harvest activities (Halofsky et al., 2011). The tribal lands are managed
under the four different tribes with different objectives.
The main forest zones in the OESF are Sitka spruce (Picea sitchensis), Western hemlock
(Tsuga heterophylla), Pacific silver fir (Abies amabilis), mountain hemlock (Tsuga mertensiana),
parkland, alpine, and subalpine fir (Abies lasiocarpa,) (listed from most dominant to least)
(ECOSHARE, 2017; WA DNR, 1997, 2016). The Sitka spruce, western hemlock, and Pacific
silver fir are the predominant vegetation zone in the DNR lands in the OESF (Figure 2-4- Map of
Vegetation Zones in the OESF (ECOSHARE, 2017)).

26

Figure 2-3- Map of ECO Regions in OESF(US EPA, 2015)

Figure 2-4- Map of Vegetation Zones in the OESF (ECOSHARE, 2017)
Study Design
The LandTrendr output was brought into ArcGIS and mapped on to the Olympic
Experimental State forest. The disturbance data was sorted by year and landownership (State,
private, ONF, ONP, and tribal lands). The maps are pixel based and each pixel indicates a
disturbance. The data were sorted by year and magnitude. The magnitude is sorted by greatest
disturbance by year. There are a variety of LandTrendr maps that were created by disturbance
level (magnitude of disturbance) - greatest disturbance, second greatest disturbance, and third
greatest disturbance. The maps with the third greatest disturbance is quite small and researchers
27

suggest it isn’t very effective because of how little data there is in this map (Kennedy et al.,
2012; Ohmann et al., 2012). This study used greatest disturbance by year.
If a disturbance pixel was present on the map, it means there is disturbance detected by
the LandTrendr algorithm (Kennedy et al., 2010). Each pixel is nine square meters. Disturbance
rates were calculated by the total area of disturbance (indicated by disturbance pixels) divided by
total area. One of the problems with this LandTrendr data is that disturbances of less than 8
pixels are not very accurate and could reflect error. LandTrendr data was designed for to 3 x 3
pixel plots and not areas smaller than that (Kennedy et al., 2010). Thompson (2011) excluded
disturbances less than 8 pixels sizes in their study rea. I did not exclude disturbance less than 8
pixels but assumed that the rate of smaller than 8 pixels is constant. Another problem researchers
have notice using the algorithm is that the first and last year ran by the LandTrendr algorithm has
less disturbance than expected and this could be an error in the program (Copass & S., 2016). I
included this in my data because excluding it would reduce the amount of data in the study.
Each ownership group disturbance rate was determined using ArcGIS software and
exported into Excel Worksheets to plot the data. The yearly rates were compared by land
ownership, EPA Ecoregion, Vegetation Zones, Landownership and EPA Ecoregion,
Landownership and Vegetation zone (Figure 2-5 Flow chart of Study Design).
Two time periods were used to analyze whether disturbance rates have changed over
time. The Northwest Forest Plan (NWFP) and the Habitat Conservation Plan (HCP) were
implemented on DNR lands in 1999 (WA DNR, 2016), so annual disturbances were analyzed for
two time periods: 1985-1998 and 1999-2012. To determine if trends in disturbance rates were the
same or different across the two time periods, I used piecewise regression modeling, a type of
multiple linear regression. In this study, disturbance rate was the dependent variable (Y) and
28

‘year’ was the first independent variable (X1). For the piecewise regression (also known as
segmented or ‘broken-stick’ regression) I used a dummy variable, X2, to indicate whether data
are in the first or second time period (Oosterbaan, 1994). The equation for the piecewise
regression then uses the product of the dummy variable X2 and the term (X1 – 1998):
𝑌𝑖 = 𝛽0 + 𝛽1 𝑋𝑖1 + 𝛽2 (𝑋𝑖1 − 1998)𝑋𝑖2 + 𝜀𝑖
which can be expressed as:
𝑌𝑖 = 𝛽0 + 𝛽1 𝑋𝑖1 + 𝛽2 𝑋 ∗ 𝑖2 + 𝜀𝑖
where
Yi is the disturbance rate in year i,
Xi1 is the year,
Xi2 is the dummy variable (0 if Xi1 ≤ 1998 and 1 if Xi1 > 1998), and
X*i2 represents the product (Xi1 – 1998) Xi2
The results of the piecewise regression yields two separate linear functions, one (in the
context of this study) for the first time period of 1985-1998, and another for the second time
period of 1999-2012. The coefficient β1 is the slope of the first linear relationship, and the sum
of the two coefficients (β1 + β2) is the slope of the second linear relationship. If the coefficient
β2 is not significantly different than 0, that represents a similar linear trend during the two time
periods. I used JMP software to fit the piecewise regression model for disturbance rates in OESF
overall and by different landowners. I used an alpha of 0.05 to evaluate statistical significance.

29

Figure 2-5 Flow chart of Study Design

Table 2-1- Data Type Used in Study
Data Layer

Data Type

Source

LandTrendr Disturbance by
Year
EPA Ecoregions

Raster File

(Kennedy et al., 2012)

Shape File

(US EPA, 2015)

Vegetation Zones

Raster File

(ECOSHARE, 2017)

Landowners

Shape File

(WA DNR, 2018b)

I anticipated that forest disturbance rates would decrease on DNR lands during the
second time period because of the 1997 HCP and active measures to set aside land from logging.
I anticipated the ONF forest disturbance rate would decrease because the ONF reduced logging
on their land since 1999. I predicted rates of disturbance on tribal lands would have increased
because of previous research and the privately owned land disturbance rate would not change.
30

Forest disturbance is historically higher on state, tribal, and private lands than federally managed
lands (ONP and ONF) (Kennedy et al., 2012). I expected ONP annual disturbance rates to be
similar in both time periods. Forest disturbance in Olympic National Park can be assumed to be
from natural causes since logging and human disturbance is managed at a minimum. The annual
forest disturbance rate data was used to answer the questions posed in this thesis.

31

Chapter 3- Results & Discussion
Question 1. What is the Disturbance Rate in the Forest Lands in the Olympic Experimental
State Forest (OESF)?
The overall disturbance rates in the OESF were similar during the two designated time
periods of 1985-1998 and 1999-2012: 0.83% and 0.85%, respectively (Error! Reference source
not found.). However, within the data there was considerable variation, and the trends varied
within the two time periods (Table 3-2- Summary of Piecewise Regression Results for Each
Landownership Type; Figure C-2- Overall Annual Disturbance Rates in the OESF with Piecewise
Regression Analysis Line). The piecewise regression model explained 43% of the variation in

disturbance rates across all landownership types and was statistically significant (Table 3-2Summary of Piecewise Regression Results for Each Landownership Type). The highest overall

disturbance level in the OESF was in 1987 at 2% and the rate decreased every year thereafter
(Figure 3-1- Graph of Disturbance Rate among Primary Landowners in OESF.). The reason for the
decreasing disturbance level was most likely because of the multiple lawsuits to conserve old
growth successional forests and because two species (northern spotted owl and marbled
murrelet) that used them were listed on the ESA in 1992 (Moeur et al., 2011; WA DNR, 1997).
The period from the late 1980s to the implementation of the NWFP is nicknamed the ‘Timber
Wars,’ as lawsuits related to the listing of the northern spotted owl halted timber production in
the PNW region. Declining disturbance rates from 1985-1988 is most likely because of
decreased timber harvests on OESF lands, since the predominant mode of disturbance in OESF
is timber harvest (Kennedy et al., 2012; Ohmann et al., 2011). The 1985-1998 time period has a
steeper decline in disturbance compared to the 1999-2012 period (Figure C-2- Overall Annual
Disturbance Rates in the OESF with Piecewise Regression Analysis Line). The 1999-2012 yearly

disturbance data decreased at a slower rate than previous years and rates of disturbance are more
32

stable from year to year. The stability of the disturbance data could be because of fewer lawsuits
and the implementation of the NWFP, which focused more on old growth forest preservation
than previous OESF management plans.

Table 3-1- Annual Disturbance Rates in OESF by Landownership Group

Year
Group
85-98

DNR

Disturbance Rates
ONP
ONF
Private Tribal

1.01%

0.10%

0.63%

1.30%

0.98%

0.83%

99-12

0.54%

0.10%

0.15%

2.02%

0.77%

0.85%

Total

0.77%

0.10%

0.39%

1.66%

0.87%

0.84%

All

Table 3-2- Summary of Piecewise Regression Results for Each Landownership Type

33

Model

Year¹ (SE)

Product¹ (SE) Sum2

OESF (all
ownership)

-1.08‡(.23)

0.74‡ (.17)

DNR

-1.62‡(.32)

ONP

F-Ratio

P-Value

-0.34

Adj.
R²
.43

11.14

.0003

0.91‡ (.24)

-1.05

.53

16.07

<.0001

-0.112*(.05)

0.08*(.03)

-0.03

.096

2.44

.1079

ONF

-1.04‡(.17)

0.52‡ (.13)

-0.52

.67

28.06

<.0001

Private

-1.52**(.53)

1.31**(.41)

-0.21

.24

5.27

.012

Tribal

-0.91**(.29)

0.51*(.22)

-0.40

.29

6.44

.0055

¹coefficient values are shown x1000 for readability
2the sum of the ‘year’ and ‘product’ coefficients, which represents the slope of the linear
function in the second time period (see Methods)
*p<0.05, ** P<0.01, ‡P<0.001
Question 2. Has the Disturbance Rate Decreased in the DNR lands in the OESF since 1999,
When the Habitat Conservation Plan (HCP) Was Implemented?
The overall disturbance rate on DNR lands in the OESF decreased from 1.01% from
1985-1998, to 0.45% from 1999-2012 (Error! Reference source not found.). This shift was
expected because of the implementation of the HCP in 1999. The DNR had protected certain
lands in the OESF from timber harvest in the HCP and has tried to reduce logging on the lands
(WA DNR, 1997, 2016). Kennedy et al. (2012) have shown using LandTrendr data that
disturbance in Washington State DNR lands in the PNW Region has stabilized. The piecewise
regression model for DNR lands explained 53% of the variation in the disturbance rate, which
decreased at a greater rate from 1985-1998 compared to 1999-2012 (Table 3-2- Summary of
Piecewise Regression Results for Each Landownership Type; Figure C-3- DNR Annual Disturbance
Rates in the OESF with Piecewise Regression Analysis Line. The most likely explanation for this

difference is because of court cases reducing logging in the OESF (Kennedy et al., 2012; WA
DNR, 2016). The disturbance rate per year was the highest in the 1980s with the highest rate in
34

1987 and on a decreasing trend after that date (Figure 3-1- Graph of Disturbance Rate among
Primary Landowners in OESF.). The 1999-2012 data shows that the disturbance rate was more

stable year to year with a slight decreasing trend (Figure C-3). Since the implementation of the
HCP, large percentage of the lands are off limits to timber harvesting and this would cause a
decrease in overall disturbance rates since less land is available for timber harvest. This stability
is most likely because of the implantation of HCP and forestry practices that reduced the rates of
timber harvest.
Question 3. What are Differences in Land Disturbance Rate between the Different
Landownership Groups in the Olympic Experimental State Forest?
Disturbance Rate in Federal Land Owners (ONP and ONF)
The lowest disturbance rate among the landownership groups (Private, DNR, Tribal,
ONF, and ONP) were in the ONP (Table 3-1- Annual Disturbance Rates in OESF by Landownership
Group; Figure 3-1- Graph of Disturbance Rate among Primary Landowners in OESF.). This was

expected since their management policy is a natural regime. Currently very little human
development exists in the ONP compared to other landowner categories and this is because of
ONP policy (Halofsky et al., 2011). ONP policy is to allow natural processes to shape the forest
and landscape in the National park. ONP disturbance rates from 85-98 and 99-12 was the exact
same at 0.1%. This rate stayed relatively stable from year to year. The piecewise regression
model for the ONP showed no statistical difference in the1985-99 and 1999-2012 year groups
(Table 3-2- Summary of Piecewise Regression Results for Each Landownership Type). This
stability was expected because of the ONP management policy that does not allow logging.
The next lowest landownership disturbance rate was the ONF. On the ONF, disturbance
rates have declined since the 1990s (Table 3-1- Annual Disturbance Rates in OESF by Landownership
35

Group). The rate from 1985-1998 was decreasing and then stabilized from 1999-2012 (Figure 3-

1- Graph of Disturbance Rate among Primary Landowners in OESF.; Figure C-5 ONF Annual
Disturbance Rates in OESF with piecewise Regression Analysis Line). This trend in disturbance rate

was expected since the timber harvest production is minimal on the ONF and their land
management practices is to preserve old growth forest and was implemented in the mid-1990s
(Halofsky et al., 2011; Kennedy et al., 2012). In addition, there also hasn’t been any large fires
on the ONF and the ONP during the years studied, which could cause spikes in disturbance
rates, like the 2,798 acre Paradise fire in the ONP in 2015 (WA DNR, 2018b). The piecewise
regression model explained 67% of the variation in disturbance rates on ONF lands, the bestfitting model compared to other landownership types (Table 3-2- Summary of Piecewise
Regression Results for Each Landownership Type).
It is interesting to note that ONF annual disturbance rates dropped to around 0.15%
from 1999-2012, and the ONP disturbance rate is around 0.10%. This rate could be assumed as
the natural disturbance rate in the OESF, i.e. from 0.10% to 0.15% annual disturbance. The
disturbance rate in the ONP was consistent across both time periods (1985-98 and 1999-2012).
However, disturbance in the ONP could increase with climate change and it would be interesting
to determine if the rate has increased from 2012-2017. Halofsky (2011) projected that as the
climate warms, the disturbance regime will shift and increase because of stronger storms and
more frequent fires. Natural disturbance rates may also increase because of increasing
temperatures which lead to forest heat stress which could cause more of the forest to be
susceptible to diseases and insects. Trees could die because of insect infestation and diseases
(Chmura et al., 2011). The stronger storms could cause higher windstorms and higher

36

precipitation events which could increase the amount of landslides, fires, and wind throw events
leading to higher rates of disturbance.
Private Lands
Private land yearly disturbance rates increased from 1.30% in the 1985-1998 time period
to 2.02% in the 1999-2012 year group (Table 3-1- Annual Disturbance Rates in OESF by
Landownership Group). Private land disturbance rates were expected to be the highest disturbance

rates in the study area. The increase in private land disturbance is one of the reasons why
disturbance didn’t decrease across all of the OESF in the 1999-2012 time period. Previous
studies in Washington state showed that private landowners had the highest rate of disturbance in
the State but the disturbance rate on private lands stayed relatively the same from 1985-2008;
whereas, federal and state lands had decreased disturbance rates since the implementation of the
NWFP (Kennedy et al., 2012). The piecewise regression model supported different trends
during the two time periods, but only explained 24% variation in the data (Table 3-2- Summary of
Piecewise Regression Results for Each Landownership Type; Figure C-6- Private Annual Disturbance

Rates in the OESF with the Piecewise Regression Analysis Line).
Timber mill survey data was analyzed to see if timber mills received more lumber during
1999-2012 and overall, board feet has decreased compared to the 1985-1998 year group (WA
DNR, 2017). In addition, logging rates in the two counties in the OESF has decreased since the
1980s (Figure B-3- Timber by Board Feet in Olympic Region by Landownership (Klallam County,
Jefferson County, and Quinault Reservation, Washington)). However, this data is incomplete, since

DNR stopped tracking timber harvested from Native American tribal land in 2002. The data was
from Washington State DNR mill surveys and only includes county data, and not the specific
area origin of the timber harvest. The data is sorted by county where the lumber is harvested.
37

The OESF lies in three counties, Jefferson, Clallam, and Grays Harbor County. All of the
private lands in the OESF are in Jefferson and Clallam counties. These were the only counties
used in the mill surveys for private, state, and federal lands. The Grays Harbor portion of the
OESF is in the Quinault Indian Nation reservation. Timber production could have increased in
the OESF and decreased in other lands in the county, but further investigation is warranted.
Soulard et al. (2017) analyzed private timberlands using remote sensing in the Cascade
Mountains of Washington from 1985-2014 and concluded that the highest rates of disturbance
were from 2000-2007. They concluded this was because of the housing boom of the 2000s and
the rates dropped after the 2008 housing bust (Soulard, et al., 2017). The increasing disturbance
trend on private lands is similar to the trend in the annual disturbance in the OESF among private
lands (Figure 3-1- Graph of Disturbance Rate among Primary Landowners in OESF.).
Tribal Lands
The disturbance level on tribal lands decreased from the mid-1980s and had a lower
disturbance rate in the 1999-2012 year group than the 1985-1998 data set (Table 3-1- Annual
Disturbance Rates in OESF by Landownership Group; Figure 3-1- Graph of Disturbance Rate among
Primary Landowners in OESF.). Kennedy et al. (2012) in their study noted the increased yearly

disturbance rate in tribal lands in Washington State but this finding was not seen in the OESF.
The piecewise regression model explained 29% of the variability and showed a different slope in
the two time periods (Table 3-2- Summary of Piecewise Regression Results for Each Landownership
Type; Figure C-7- Tribal Annual Disturbance Rates in the OESF with the Piecewise Regression Analysis
Line). Because DNR stopped taking mill surveys from tribal lands in 2002, it is impossible to

determine if timber production increased on reservation lands (Figure B-3- Timber by Board Feet

38

in Olympic Region by Landownership (Klallam County, Jefferson County, and Quinault Reservation,
Washington)) (WA DNR, 2018).

DISTURBANCE RATE= DISTURBANCE/TOTAL AREA
OF LANDOWNER

4.50%

4.00%

3.50%

3.00%

2.50%

2.00%

1.50%

1.00%

0.50%

DNR

ONP

ONF

Private

Tribal

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

1996

1995

1994

1993

1992

1991

1990

1989

1988

1987

1986

1985

0.00%

All

Figure 3-1- Graph of Disturbance Rate among Primary Landowners in OESF.
Question 4. What is the Disturbance Rate among the Different EPA Ecoregions in the
OESF?
Each of the different EPA ecoregions have a different disturbance rate (
). The largest of the ecoregions are the low Olympics and coastal uplands. The high
Olympics (which is excluded because its extent is only within the ONP) and coastal lowlands are
the smallest ecoregions (Figure B-4- Level IV Ecoregions in the OESF by Area). The coastal
lowlands region is also excluded because this region is not in ONF lands. The coastal lowland
39

disturbance rate might not be accurate because of its small size, as acknowledged specifically by
the creators of LandTrendr (Kennedy et al., 2010) (Table 3-3- Annual Disturbance Rate in OESF by
EPA Level IV Ecoregions; Figure 3-2- Disturbance in Ecoregions in the OESF2). There are years where

there is no disturbance in this ecoregion which could reflect errors in the data.
The coastal uplands ecoregion has the highest yearly disturbance rate among the different
landowners, possibly reflecting its status as the most favorable ecoregion for timber production
in the OESF. This ecoregion also has the highest disturbance rate for DNR lands (

Table D-2- Yearly Disturbance Rate among Coastal Uplands). The disturbance rate in the
coastal uplands ecoregion among private lands doubled in the 1999-2012 year group from the
1985-1998 year group and this could be why the overall annual disturbance rate increased in the
coastal uplands (

Table D-2- Yearly Disturbance Rate among Coastal Uplands; Table D-3- 3). All the other
landowners’ disturbance rate decreased in the coastal uplands.
The low Olympic ecoregion experienced a decrease in overall disturbance in the 19992012 from 1985-98 year group (Table D-3- 3). The disturbance level in DNR lands decreased
from 1.01 to 0.44% in this time period (Table D-3- Yearly Disturbance Rate among Low Olympic
Ecoregion). The ONF yearly disturbance rate also decreased during the same time period. The

ONP disturbance rate stayed the same in the two different time periods. Tribal lands also
experienced a decrease in disturbance rates but private lands disturbance rate increased in the
1999-2012 year group in the low Olympic ecoregion.

40

Table 3-3- Annual Disturbance Rate in OESF by EPA Level IV Ecoregions

Year
Group
85-98

Low
Olympics
0.76%

Disturbance Rate
Coastal
Coastal
Uplands Lowlands
1.00%
0.44%

99-12

0.69%

1.19%

0.65%

0.85%

Total

0.73%

1.10%

0.55%

0.84%

All
0.83%

DISTURBANCE RATE= DISTURBANCE/
TOTAL AREA OF ECOREGION

4.00%
3.50%
3.00%

2.50%
2.00%
1.50%
1.00%
0.50%

1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012

0.00%

Low Olympics

Coastal Uplands

Coastal Lowlands

All

Figure 3-2- Disturbance in Ecoregions in the OESF
Disturbance in the High Olympics Ecoregion
Disturbance rates from the high Olympic ecoregion is excluded from this study because
this area is predominated by glaciers and non-forest area which is not the focus of LandTrendr.
However, the data shows an increase in disturbance rate and the disturbance patterns appear to be
41

retreating glaciers in the High Olympic region (Figure A-13- Map of Disturbance in the High
Olympics Ecoregion by YOD (Mount Olympus).). The disturbance rate has increased from 1999-2011

and the trend is increasing overall as from 1985-98 (
Table 3-4- Yearly Disturbance Rates in the High Olympic Ecoregion
Year

High Olympics
Disturbance Rate

; Figure B-8- Annual Disturbance Rate by High Olympic Ecoregion8). The effects of climate
change could result in further downstream disturbance in watersheds that have glaciers such as
the Hoh and Queets river drainage. Copass (2016) did not include High Olympic ecoregion in
their study because of the high variability of disturbance data from year to year and the data is
not very accurate. The algorithm is not reliable in alpine areas because of differences in yearly
snow depth in the high Olympics (Copass et al., 2016). The high Olympic ecoregion in the
OESF includes Mt Olympus, the highest and most glaciated peak in the Olympic Mountain
Range. Scientists have said climate change poses a high risk to glaciers in the Olympics and that
glaciers and snowfields are retreating (Halofsky et al., 2011). Retreating glaciers could increase
riparian disturbance and rivers banks shifting due to the changes in hydrology patterns (Halofsky
et al., 2011).
Table 3-4- Yearly Disturbance Rates in the High Olympic Ecoregion
Year

High Olympics
Disturbance Rate

1985-1998

0.49%

1999-2011*

0.68%

Total

0.58%

42

*There was no disturbance data in this ecoregion for 2012.
Question 5-What is the Disturbance Rate among the Different Forest Vegetation Zones?
There are eight vegetation zones in the OESF. Not all OESF landowners have all eight
vegetation zones on their lands and only the ONP contains all eight vegetation zones. The
primary vegetation zones in the OESF are Sitka Spruce, Western hemlock, and Pacific silver fir.
The primary vegetation zones are found with all the landowners in the OESF. The Western
hemlock and Sitka spruce is the vegetation zone where timber harvest primarily takes place in
the OESF and they have the highest rates of disturbance (Table 3-5- Annual Disturbance Rate by
Different Vegetation Zones; Figure 3-3-Disturbance in Primary Vegetation Zones ). Disturbance

rates in the Sitka spruce and Western hemlock vegetation zones mirrored the overall disturbance
rate (Figure 3-3-Disturbance in Primary Vegetation Zones ). This finding would be expected
because these zones have the most favorable trees for timber harvest (WA-DNR, 2017). Silver
Fir has a lower disturbance rate and this is also expected since this tree is not as favorable for
timber harvest as are trees in the Sitka spruce and Western hemlock vegetation zones (USDA
NRCS, 2017). The Pacific silver fir disturbance rate is close to vegetation zone’s rates where
there is no timber harvest and this could be a natural disturbance rate for Pacific silver fir
(Figure B-9- Disturbance by Vegetation Zones .
Table 3-5- Annual Disturbance Rate by Different Vegetation Zones
Disturbance Rate

Year
85-98

Low
Olympics
0.93%

Western Pacific
Hemlock Silver Fir
1.05%
0.46%

99-12

1.14%

1.09%

0.21%

Total

1.03%

1.07%

0.33%
43

Sitka Spruce
Western Hemlock
Pacific Silver Fir

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

1996

1995

1994

1993

1992

1991

1990

1989

1988

1987

1986

1985

Disturbance Rate = Disturbance/area of
Vegetation zone
3.00%

2.50%

2.00%

1.50%

1.00%

0.50%

0.00%

All

Figure 3-3-Disturbance in Primary Vegetation Zones

44

Conclusion
Using LandTrendr data, the overall disturbance rates in the OESF since the
implementation of the 1997 HCP did not change, which was unexpected (Table 3-1- Annual
Disturbance Rates in OESF by Landownership Group). However, this overall average hides

considerable variation by land ownership, ecoregion, vegetation type, and year-to-year changes.
On DNR managed lands, disturbance rates declined considerably from 1985-1998, and then
declined but at a slower rate during 1999-2012 (Table 3-5). The overall rates in OESF were
similar likely because of an increase in timber production on private lands in the OESF. The
yearly disturbance rate on private lands increased during the duration of this study (Table 3-1Annual Disturbance Rates in OESF by Landownership Group; Figure 3-1- Graph of Disturbance Rate
among Primary Landowners in OESF.). The landownership type is the biggest factor in determining

disturbance rates in the OESF and this has been shown in other studies (Kennedy et al., 2012;
Peterson et al., 1997) . Each landowners different objectives for their forest land. Private land
owner’s main objective is for profit from timber sales (Peterson et al., 1997). The ONF
objectives since the implementation of the PNW is to preserve old growth successional sorest
and this is seen in their reduced disturbance rate. The ONP Policy is to support natural
disturbance regimes and as a result, they have the least amount of disturbance. DNR’s
management in the OESF is to be ecological friendly and also incorporate revenues from timber
productions and as a result their disturbance rate is between private and Federal (ONP and ONF)
landownership types.
More research needs to be done to see what the natural disturbance rate is in the OESF.
This is partially being done by researchers at the ONP (Copass & S., 2016). Future research
needs to focus on whether this natural disturbance rate is increasing. Many studies suspect that
45

climate change could increase the natural disturbance rates because of stronger storms and more
fires. The increase of natural disturbance rates could have an effect on DNR lands in the OESF.
As more LandTrendr data becomes available, this data should be examined to see if the natural
disturbance levels on the OESF is increase or decreasing. Natural disturbance type can be sorted
and measured by how much it covers. Categorizing natural disturbance rates by size can further
help DNR determine how disturbance is shaping their forest and how they should best manage
their land.

46

Appendix A- Maps

Figure A-1- Map of Disturbance in OESF
47

Figure A-2- Map of Disturbance in the OESF by Two Year Groups (1985-98 and 19992012)

48

Figure A-3- Map of Disturbance in DNR Lands in the OESF by YOD

49

Figure A-4- Map of Disturbance in DNR lands in the OESF by Year Groups 1985-1998 and
1999-2012

50

Figure A-5- Map of Disturbance in ONP Lands in the OESF by YOD

51

Figure A-6- Map of Disturbance in ONP Lands in the OESF by Year Groups 1985-1998
and 1999-2012

52

Figure A-7- Map of Disturbance in ONF Lands in the OESF by YOD

53

Figure A-8- Map of Disturbance in ONF Lands in the OESF by Year Groups 1985-1998
and 1999-2012

54

Figure A-9- Map of Disturbance in Tribal Lands in the OESF by YOD

55

Figure A-10- Map of Disturbance in Tribal Lands in the OESF by Year Groups 1985-1998
and 1999-2012

56

Figure A-11- Map of Disturbance in Private Lands in the OESF by YOD

57

Figure A-12- Map of Disturbance in Private Lands in the OESF by Year Groups 1985-1998
and 1999-2012
58

Figure A-13- Map of Disturbance in the High Olympics Ecoregion by YOD (Mount
Olympus).

59

0.00%
2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

1996

1995

1994

1993

1992

1991

1990

1989

1988

1987

1986

1985

0.00%

1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012

Disturbance Rate per Year=
Disturbance/Total area
Disturbance Rate per Year=
Disturbance/Total Area

Appendix B- Line Graphs
2.50%

2.00%

1.50%

1.00%

0.50%

Figure B-1- Overall Annual Disturbance Rates in OESF

4.00%

3.50%

3.00%

2.50%

2.00%

1.50%

1.00%

0.50%

Figure B-2- DNR Annual Disturbance Rates in OESF

60

Thousand of Board Suare Feed of timber

1,200,000
1,000,000
800,000
600,000
400,000
200,000

1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012

0

Private

State

ONF

Tribal

All

Figure B-3- Timber by Board Feet in Olympic Region by Landownership (Klallam County,
Jefferson County, and Quinault Reservation, Washington) (Derived From WA DNR, 2018.)
*DNR stopped tracking data from Tribal lands in 2002
ECOROEGIONS BY AREA IN OESF
Coastal lowlands

Coastal uplands

Low Olympics

High Olympics

5% 3%

31%

61%

Figure B-4- Level IV Ecoregions in the OESF by Area

61

1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012

Disturbance Rate = Disturbance/area
of Ecoregion
Disturbance Rate = Disturbance/area of
Ecoregion
0.00%
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012

7.00%

6.00%

5.00%

4.00%

3.00%

2.00%

1.00%

DNR
ONP

DNR

ONF

ONP

Private

ONF

Private

Indian

Indian

All

Figure B-5- Annual Disturbance Rate in Coastal Lowlands by Landownership

5.00%

4.50%

4.00%

3.50%

3.00%

2.50%

2.00%

1.50%

1.00%

0.50%

0.00%

All

Figure B-6- Annual Disturbance Rate in Coastal Uplands Ecoregion by Landownership

62

0.000%

2011

2010

2009

Indian

2008

2007

2006

2005

Private

2004

2003

2002

2001

2000

1999

ONF

1998

1997

1996

1995

1994

ONP

1993

1992

1991

1990

1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012

Disturbance Rate = Disturbance/area
of
Ecoregion

DNR

1989

1988

1987

1986

1985

Disturbance Rate = Disturbance/area of
Ecorgegion

4.50%

4.00%

3.50%

3.00%

2.50%

2.00%

1.50%

1.00%

0.50%

0.00%

All

Figure B-7- Disturbance in Low Olympics Ecoregion by Landownership

0.030%

0.025%

0.020%

0.015%

0.010%

0.005%

Figure B-8- Annual Disturbance Rate by High Olympic Ecoregion

(High Olympic Ecoregion only exists in the ONP).

63

2.50%
2.00%
1.50%
1.00%
0.50%
0.00%

1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012

Disturbance Rate = Disturbance/area
of
Vegetation zone

3.00%

Sitka Spruce

Western Hemlock

Pacific Silver Fir

Mountain Hemlock

Subapline Fir

Parkland

Alpine

All

Figure B-9- Disturbance by Vegetation Zones in OESF

3.50%
3.00%
2.50%
2.00%
1.50%
1.00%
0.50%
0.00%

1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012

Disturbance Rate = Disturbance/area of
Vegetation zone

4.00%

DNR

ONP

ONF

Private

Indian

All

Figure B-10- Annual Disturbance Rate in Sitka Spruce Vegetation Zone by Landownership
Type

64

1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012

Disturbance Rate = Disturbance/area of
Vegetation zone
Disturbance Rate=Disturbance/area of
Vegetation zone
0.00%
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012

5.00%

4.50%

4.00%

3.50%

3.00%

2.50%

2.00%

1.50%

1.00%

0.50%

DNR

DNR

ONP
ONP

ONF
ONF

Figure B-11- Annual Disturbance in Western Hemlock Vegetation Zone by Landownership
Type
5.00%

4.50%

4.00%

3.50%

3.00%

2.50%

2.00%

1.50%

1.00%

0.50%

0.00%

Private

Indian

All

Figure B-12- Annual Disturbance in Silver Fir Vegetation Zone by Landownership Type

65

Appendix C- Disturbance Date with Predicted Piecewise Regresission
Analysis Regression lines
Table C-1 Table Summary of Piecewise Regression Results for Each Landownership Type
(Table 3-2 reproduced here as a reference for the Appendix C figures).
Model

Year¹ (SE)

Product¹ (SE)

Sum2

Adj. R²

F-Ratio

P-Value

OESF (all
ownership)

-1.08‡(.23)

0.74‡ (.17)

-0.34

.43

11.14

.0003

DNR

-1.62‡(.32)

0.91‡ (.24)

-1.05

.53

16.07

<.0001

ONP

-0.112*(.05)

0.08*(.03)

-0.03

.096

2.44

.1079

ONF

-1.04‡(.17)

0.52‡ (.13)

-0.52

.67

28.06

<.0001

Private

-1.52**(.53)

1.31**(.41)

-0.21

.24

5.27

.012

Tribal

-0.91**(.29)

0.51*(.22)

-0.40

.29

6.44

.0055

¹coefficient values are shown x1000 for readability
2
the sum of the ‘year’ and ‘product’ coefficients, which represents the slope of the linear function
in the second time period (see Methods)
*p<0.05, ** P<0.01, ‡P<0.001
This Table is in Chapter 3 and is placed here as a reference guide for the reader.

Annual Disturbance Rates

0.04
0.035
0.03
0.025
0.02

0.015
0.01
0.005
0

1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011

66

Figure C-2- Overall Annual Disturbance Rates in the OESF with Piecewise Regression
Analysis Line
0.04

Annual Disturbance Rates

0.035
0.03
0.025
0.02
0.015
0.01
0.005
0

1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011
Figure C-3- DNR Annual Disturbance Rates in the OESF with Piecewise Regression
Analysis Line
0.04

Annual Disturbance Rates

0.035
0.03
0.025
0.02
0.015
0.01
0.005
0

1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011
Figure C-4- ONP Annual Disturbances Rates in the OESF with Piecewise Regression
Analysis Line

67

0.04

Annual Disturbance Rates

0.035
0.03
0.025
0.02
0.015
0.01
0.005
0

1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011
Figure C-5 ONF Annual Disturbance Rates in OESF with piecewise Regression Analysis
Line

0.04

Annual Disturbance Rates

0.035
0.03
0.025
0.02
0.015
0.01
0.005

0

1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011
Figure C-6- Private Annual Disturbance Rates in the OESF with the Piecewise Regression
Analysis Line

68

Annual Disturbance Rates

0.04
0.035
0.03
0.025
0.02
0.015
0.01
0.005
0

1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011
Figure C-7- Tribal Annual Disturbance Rates in the OESF with the Piecewise Regression
Analysis Line

69

Appendix D- Tables
Table D-1- Yearly Disturbance Rate in Coastal Lowlands Ecoregion

Year
Group

DNR

Disturbance Rate
ONP
ONF
Private Tribal

85-98

0.36%

0.24%

0.00%

0.65%

0.47%

0.44%

99-12

1.18%

0.11%

0.00%

0.94%

0.95%

0.65%

Total

0.77%

0.18%

0.00%

0.79%

0.71%

0.55%

All

Table D-2- Yearly Disturbance Rate among Coastal Uplands

Year
Group

DNR

Disturbance Rate
ONP
ONF
Private Tribal

85-98

1.01%

0.32%

0.85%

1.11%

1.08%

1.00%

99-12

0.75%

0.27%

0.40%

2.07%

0.53%

1.19%

Total

0.88%

0.30%

0.62%

1.59%

0.81%

1.10%

All

Table D-3- Yearly Disturbance Rate among Low Olympic Ecoregion

Year
Group

DNR

Disturbance Rate
ONP
ONF
Private Tribal

85-98

1.01%

0.12%

0.61%

1.52%

0.88%

0.76%

99-12

0.44%

0.12%

0.13%

2.05%

1.51%

0.69%

Total

0.72%

0.12%

0.37%

1.78%

1.19%

0.73%

All

70

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