Comparing Pre-settlement, Pre-treatment
and Post-treatment Stand Structure at
Lonetree Restoration Site:
Incorporating GIS into Restoration
By
Christine Brown & Michael Jow
Ecological Restoration Applications
November 30, 2004
More Lonetree!
• Data collected needs to be in a format where it
can be analyzed displayed and stored
– Including how it relates to the rest of the world
– Future monitoring needs to be incorporated in a
compatible format for comparison and analysis
• Average tree density and basal area don’t
provide the whole picture
– Spatial arrangement is important to reconstructing
proper structure
– Presettlement site utilization by overstory is difficult to
quantify and recreate
Objectives
1. Consolidate, store and organize project data
2. Spatially reference project area, treatment
units and plot boundaries
3. Visually display and compare pre-settlement,
pre-treatment and post-treatment stand
structures
4. Visualize and analyze outcome of various
prescriptions
Aerial View of the Lonetree Restoration Site
Treatment Areas
Project
Boundary
Treatment
Units
Plots
Methods
Project layout
• Boundaries and plot centers were plotted using a
Tremble Geoexplorer 2 GPS unit
• GPS data was and differentially corrected using USDA
FS base station data from Cedar City, Utah and brought
into an ESRI Arcmap project
• Plots were created using center points and plot direction
• Plot data was imported into Arcmap and linked to
corresponding features
• Pre- and post-treatment photos were hyperlinked to the
point location they were taken
• Features were overlaid on an aerial photo and topo map
Topographic View of the Lonetree Site
Methods (Continued)
Tree Data
• Trees were plotted in Arcmap using x-y data collected on
site and corresponding data attached to each tree
• Crown diameter was estimated using allometric
equations for ponderosa pine (McTague, 1988)
• Crowns of trees were projected and canopy closure was
estimated
• Tree density and basal area was calculated using plot
data
Formulas for Estimate Canopy from DBH
• When D > 20 in:
CST= (131.58 D - 1578.95) / {43.85exp (-333.54 / SD.99697))
+.012729 SD1.175 + 4.5}
S = Site Index (60)
D = Diameter in inches
• When D < 4 in:
CY = .426 + 1.317 D
• When 4 < D > 20:
C = (D – 4.0)[(CST, D=20) – 5.7] / 16.0 + 5.7
CST=Crown Diameter of Saw timber
CY=Crown Diameter of young trees
(McTague, 1988)
Assumptions
• Area of each plot was slope corrected for estimating tree
density and basal area
• Pre-settlement date used was 1870 (approximate time of fire
exclusion)
• Tree densities
– Pre-settlement – assumed pole density by including living presettlement trees in total tree density calculation
• Basal areas
– Pre-settlement were calculated using the DSH of remnant
stumps
– Living pre-settlement trees and pole basal area not included
• Crown closure
– Canopy only estimated within plot using allometric equations
– does not include canopy extending beyond plot boundaries or
the canopy of trees rooted outside plot
Need for Restoration
Average Basal Area
1400
1200
1000
800
600
400
200
0
Pre-settlement
Pre-treatment
Lonetree Site
Average tree density of all the
measured plots.
Basal Area (m 2/ha)
Tree Density (# trees/ha)
Average Tree Density
40
30
Pre-Settlement
20
Pre-treatment
10
0
Lonetree Site
Average basal area of all the measured
plots.
Pre-treatment tree density and basal area are significantly different than presettlement tree density and basal area. Restoration is needed to return to a healthy
forest similar to historical conditions.
Need for Restoration (cont.)
Diameter Distribution of 2000 Plots
Pre-settlement Diameter Distribution
25
1200
1000
Trees/hectare
Trees/hectare
20
15
10
5
800
600
400
200
0
0
10
10
20
30
40
50
DBH (cm)
60
70
20
30
40
50
60
70
80
DBH (cm)
Pre-settlement trees show a normal distribution around 40-50 cm DBH. The pretreatment trees show a logarithmic (reverse J) distribution.
80
Lonetree Restoration Project Plots
Tree Density (# trees/ha)
450
400
350
300
250
200
150
100
50
0
Pre-settlement
Pre-treatment
Post-treatment
NAU-99-2
NAU-99-2 Basal Areas
40
2
Pre-settlement, Pre and Post-treatment Canopy Covers
Basal Area (m /ha)
NAU-99-2
NAU-99-2 Tree Densities
35
30
25
Pre-settlement
20
Pre-treatment
15
Post-treatment
10
5
0
NAU-99-2
NAU-99-2 Crown Closure
90.0%
80.0%
70.0%
60.0%
50.0%
40.0%
30.0%
20.0%
10.0%
0.0%
Pre-settlement
Pre-treatment
Post-treatment
Plot NAU-99-2
NAU-99-2: POST-TREATMENT PICTURES (P2)
August 21, 2000
November 9, 2004
Tree Density (# trees/ha)
Pre-settlement and Pre-treatment Canopy Covers
3000
2500
2000
Pre-settlement
1500
Pre-treatment
1000
500
0
NAU-00-2
NAU-00-2 Basal Areas
2
Basal Area (m /ha)
NAU-00-2
NAU-00-2 Tree Densities
50
45
40
35
30
25
20
15
10
5
0
Pre-settlement
Pre-treatment
NAU-00-2
Crown Closure
80.0%
70.0%
60.0%
50.0%
Pre-settlement
40.0%
Pre-treatment
30.0%
20.0%
10.0%
0.0%
Plot NAU-00-2
NAU-00-2: PRE AND POST–TREATMENT
PICTURES (0P)
Pre-treatment. September 6, 2000.
Post-treatment. November 9, 2004.
Additional Analyses
• Location- find coordinates for any feature
• Measurements- distance, area, perimeter
• Spatial relationships- clumpiness,
connectivity, proximity
• Patterns- data visualization
• Trends- changes in data over time
• Modeling- predict outcomes of different
restoration alternatives
GIS to Visualize Restoration Prescriptions
10 m recruitment radius
Pre-settlement
Evidence
Pre-settlement
Live tree
Post-settlement Live Trees
Comparing Restoration Prescriptions
Possible treatment using a
1.5 to 1 replacement for presettlement evidence
Possible treatment using a
3 to 1 replacement for presettlement evidence
Conclusion
• ALL project data (maps, photos, plot data) can be stored,
organized and displayed in one GIS project
• Project data can utilize other GIS data for additional
analysis
• Pre-settlement canopy closure and spatial distribution
(i.e. “clumpiness”) can be reconstructed, analyzed and
displayed
• Spatial analysis can aid in selecting replacement/ leave
trees in restoration treatments
• Various prescriptions can be compared and visualized
prior to implementation
• Future monitoring information can easily be incorporated
and compared to previous data