This document discusses the value of forests and woodlands from both economic and ecological perspectives. It outlines how the UFORE model is used to quantify ecosystem services provided by urban forests, including examples from Prince William Forest Park. The document also addresses threats to forests like invasive pests and climate change, noting models predict most tree species in the park could experience unsuitable climates by the end of the century under higher emission scenarios. Land use change is also discussed as contributing to climate change and forest fragmentation.

1. Walking the Woods
Understanding our natural areas
and their value
Joe H. Sullivan, PhD
Department of Plant Science and Landscape Architecture
University of Maryland

2. Brief Outline
 Why do we values our trees and forests?
 How do we place a value on these in economic
terms?
 What are some of the threats to our woods?

3. What is the value of a forest or
woodland?
Real estate value – simple market value
Tourism value – aesthetics, fees, etc
Direct use – quantitative value, e.g. timber
Ecosystem services or non-use values – these are
difficult to quantify and frequently modeled
values.

4. What are the ecosystem services and
how do we value them?

5. Air quality
Timber production
Biodiversity Carbon
sequestration
Nutrient cycling
Carbon storage
Water Filtration
and Regulation

6. Placing a value on Ecosystem
Services?
 How do we value the ecosystem services?
 Apply some matrix in terms of environmental
accounting (e.g. Costanza) or energy consumption
(Odum), sometimes called Emergy.
 One model commonly used, particularly by urban
planners is the URFORE or ECO model.

7. The UFORE model
 Urban Forest Effects Model – USDA/FS, late
1990’s (recently renamed as ECO, and part of
the i-tree suite of forest assessment tools)
 UFORE has been used to assess services
provided by trees in U.S. cities including
Washington D.C., Baltimore, Philadelphia,
Minneapolis and San Francisco, natural areas
such as Prince William Forest Park (NPS) and
even the University of Maryland campus.
 UFORE outputs include ecological parameters
and ecosystem services

8. The i-TREE Suite
http://www.itreetools.org/
USDA Forest Service, 2006 plus revisions
“By understanding the local, tangible
ecosystem services that trees provide, i-
Tree users can link urban forest
management activities with
environmental quality and community
livability.”

9. Off-the shelf software OR design
Josh Nadler your own! Taylor Keen

10. i-Tree Analysis Tools
i-Tree Eco (UFORE) provides a broad picture
of the entire urban forest. It is designed to use
field data from complete inventories or
randomly located plots throughout a
community along with local hourly air
pollution and meteorological data to quantify
urban forest structure, environmental effects,
impacts of pest infestation and value to
communities.

11. OTHER TOOLS OF INTEREST
OFF THE I-TREE SUITE
i-Tree Vue allows you to use of national land cover data
maps to assess your community's land cover, including tree
canopy, and some of the ecosystem services provided by your
current urban forest.
i-Tree Streets (Stratum) focuses on the benefits provided by a
municipality's street trees.
i-Tree Hydro (beta) is a new application designed to simulate
the effects of changes in tree and impervious cover on stream
flow and water quality.
i-Tree Canopy offers a quick and easy way to produce a
statistically valid estimate of land cover types (e.g., tree
cover)

12. OTHER TOOLS OF INTEREST
OFF THE i-TREE SUITE
i-Tree Design (beta) is a simple online tool that provides a
platform for assessments of individual trees at the parcel level.
This tool links to Google Maps and allows you to see how tree
selection, tree size, and placement around your home effects
energy use and other benefits.
i-Tree Pest Detection Module is a portable, accessible and
standardized protocol for observing a tree for possible insect or
disease problems.
i-Tree Storm provides a method for a community to assess
widespread storm damage in a simple, credible, and efficient
manner immediately after a severe storm.

13. Example: Prince William Forest
Park
 Located just west of I-95, SW of Washington D.C., in Prince
William County, Virginia.
 National Park under National Park Service administration
since the 1930s.
 Previous uses include farmland, pyrite mines, social services
during the Great Depression, and training grounds for the
precursor to the CIA
 Mixture of Atlantic Coastal Plain and Piedmont regions.
 Naturally regenerating vegetation but in the urban “footprint”

14. Prince William County
Manassas
Prince William Forest Park

15. Sampling Methods
 100 random plots within the park, located via
GPS coordinates.
 Each plot 1/10 acre (approximately 37.2 feet in
radius).
 ID all woody species in the plot.
 Data include DBH, height, height to crown,
crown area, dieback, % of crown missing,
impervious surfaces and crown light exposure.
 Couple these data with weather and air quality
data.
 Estimates are provided by the model.

17. Summary Results
• Total number of trees surveyed 5099
• Total estimated trees in the park 5.7 X 106
• Mean trees/hectare 1126
• Mean trees per plot (total) 51
• Number of tree species surveyed 39
• Leaf Area Index 3.36
• Shannon-Weiner Diversity Index
2.45

18. Species Composition: all trees
15.6
22.2 American beech
Black tupelo
5.4 Red maple
Virginia pine
5.4
Flowering dogwood
Tulip tree
5.6
17.5 White oak
6.5 American holly
Other species
10.3 11.5

19. Proportion of all sampled trees (%)
10
20
30
40
50
60
0
2.5
-7
.62
7.6
3-
15
.2
15 4
.25
-22
.86
22
.87
-30
.48
30
.49
-38
38 .1
.11
-45
.72
45
.73
-53
.34
53
.35
-60
.96
60
DBH (cm)
.97
-68
.58
68
.59
-76
76 .2
.21
-83
.82
83
.83
-91
.44
91
.45
-99
99 .06
.07
-10
6.6
8
Size distribution

20. Forest Community Composition
Relative Relative
Leaf Area Importan
density Basal
Species Frequency Index (m2 ce Value
(% of Area (%
m-2) (I.V.)
total) of total)
American beech 90 24.6 11.0 0.86 125.6
Black gum 86 18.0 4.6 0.24 108.6
Red maple 83 11.8 9.3 0.41 104.1
White oak 62 5.3 15.1 0.32 82.4
Tulip poplar 61 5.7 16.5 0.49 73.2
Virginia pine 45 8.2 16.5 0.23 69.7

21. Changing Forest Composition?

22. Carbon in PWFP
Net Average Average
Sequestration Sequestration Total Storage Storage
(t yr-1) (t ha-1 yr-1) (t) (t ha-1 yr-1)
12,346 + 1,093 2.43 + 0.2 394,241 + 8,698 77.45 + 3.7
Value at $20 t-1 Value at $20 t-1 Value at $20 t-1 Value at $20 t-1
$246,920 $48.60 $7,884,820 $1549

23. Carbon
Carbon Storage
Sequestration
Carbon storage (10K metric tons) Estimated net carbon sequestration
0
1
2
3
4
5
6
7
2. (metric tons/year)
5-
7.
62
7.
63
1,000.00
1,500.00
2,000.00
2,500.00
3,000.00
-500.00
500.00
0.00
-1 2.
5. 5-
24 7.
62
15
.2 7.
5- 63
22 -1
.8 5.
6 24
22 15
.8 .2
7- 5-
30 22
.4 .8
8 6
22
30 .8
.4 7-
9- 30
38 .4
.1 8
30
38 .4
.1 9-
1- 38
45 .1
.7
2 38
.1
45 1-
.7 45
3- .7
53 2
.3 45
4 .7
3-
53 53
.3 .3
dbh class (cm)
5- 4
60 53
.9 .3
6 5-
dbh class (cm)
60 60
.9
.9
7- 6
68 60
.5 .9
8 7-
68
.5
68 8
.5 68
9-
76 .5
.2 9-
76
76 .2
.2 76
1-
83 .2
1-
.8 83
2 .8
99 99 2
.0 .0
7- 7-
10 10
Tree size and carbon dynamics
6. 6.
68 68

24. Tree Species and carbon dynamics

25. Carbon in PWFP – how does this
relate to other area??
PWFP DC- total DC – forest cover
Land area (ha) 5090 15900 4550
Sequestration 12,346 + 1,093 16,200 16,200
(t yr-1) ($247K) ($324K) ($324K)
Average 2.43 + 0.2 1.02 3.56
Sequestration
(t ha-1 yr-1)
Total Storage 394,241 + 8,698 526,000 526,000
(t) ($7.9M) ($10.5M) ($10.5M)
Average 77.45 + 3.7 33.08 115.60
Storage
(t ha-1 yr-1)

26. What are some of the threats to
our woods and what can we do
about them?

27. Risk from key insects.
Fraxinus pennsylvanica (green ash)

28. Fraxinus (ash) Trees
Emerald Ash Borer EAB
Fraxinus comprise 88 of 9000 Inventoried plants = ~1%
41 Fraxinus americana (white ash) @ UMD
47 Fraxinus pennsylvanica (green ash) @ UMD

29. 2008 UMD UFORE Study: Potential
Pest Impacts

30. Pest Damage in DC and UMD
Pest UMD % UMD DC % DC
Impacted Potential Impacted Potential
Loss ($) Loss ($)
Asian 27.3 14.7M 34.4 916M
longhorned
beetle
Gypsy moth 20.6 45.2M 13.8 1.39B
Dutch elm 2.1 376 T 2.4 112M
disease
Emerald ash 0.8 2.35M 2.1 72M
borer

31. Changes in Greenhouse Gasses

32. Changes in Temperature

33. Climate Change

34. Climate Change and Forests?

35. Projections of Future Forest
Composition

36. Some modeles for PWFP
The low-emission B2 scenario of the Intergovernmental Panel on
Climate Change predicts moderate increases in mean annual
global temperature by the end of the twenty-first century.
In the next 30 years, 35 out of 39 tree species in PWFP will
continue to experience optimal growth conditions.
By 2070, however, the model predicts that the number of species
that would find the Park optimal would decrease to ten, while
one species, witch-hazel (Hamamelis virginiana L.), would
experience a climate entirely unsuitable for growth
This model also predicts that 10 species would be extirpated
from the park by the end of this century and that all current
tree species would be in the fringe range or outside of optimal
conditions for growth.

37. What about the higher emission models??
By 2070 ALL species would be listed in the unfavorable climate
range!
Is this true??
What are current emission levels?
What does this mean?

38. Land Use and Fragmentation
Deforestation, urban sprawl, agriculture, and other human influences
have substantially altered and fragmented our landscape.
Such disturbance of the land can change the atmospheric
concentration of carbon dioxide, as well as affect local, regional, and
global climate by changing the energy balance on Earth's surface.
The extent to which land use changes have contributed to global
warming is controversial but may account for up to half of the
warming reported today.
This is only one of the affects of development and land use changes
on our environment. Dr. Neel will speak in more detail on this topic
in the next presentation.