UFORE
Overview and Process
Overview & Process I
What is UFORE?
Science-based computer model that
quantifies urban forest structure, functions,
and values
Collection of analysis tools
Body of SAS code accessible through
USDA Forest Service in Syracuse
Specialized analysis for urban ecosystems
Overview & Process I
Ecosystem
“Functional units of interacting abiotic, biotic, and
cultural (anthropogenic) components”
Includes all trees
 Public/private
 Native/exotic/utopian
No systematic management of individuals, but we
can and--many believe--must manage the
population
Population contributes to common good at much
reduced cost/benefit ratio than street trees
Overview & Process II
Status of UFORE
Fully operational as program at Syracuse
running in SAS code
Being converted to desktop app for
Windows OS
 Conversion work will occupy next few years
Major advances for i-Tree:
 Data collection app
 Reporting mechanism
i-Tree 1.0
INPUT
UFORE
i-Tree 1.0
OUTPUT
Overview & Process III
Designed for ecosystem analysis
Calculates
 Structure, e.g.
 Leaf area and biomass
 Species and DBH distribution
 Function, e.g.
 VOC emissions
 Pollution removal
 Effect on building energy use
 Total carbon stored and net carbon sequestered annually
 Value based on structure, function
1 metric ton (“tonne”) = 1.10231131 US (short) ton
Overview & Process IV
What good is it?
Aid planning and management
Improve forest designs
Project future impacts
Assess impact of catastrophic events
Justify programs
Source: http://www.houstonregionalforest.org/Report/
Overview & Process V
How does it work?
Uses field data to calculate structure
Uses structure data to calculate function
Uses function data to calculate value
Uses value data to make recommendations
The Devil lurks, as always, in the details
3 questions
Ask when evaluating models:
Do I understand the numbers?
Can I trust the numbers?
Can I use the numbers?
I want to drill down one level in
an effort to answer these
questions
Overview & Process VI
Where do the numbers come from?
Let’s examine one relatively *simple*
set of calculations: CARBON
Start with allometric¹ equations
estimating above-ground biomass from
species and DBH
¹ = relation of the growth of a part of an
organism to the growth of the whole
Regression of DBH as predictor of biomass
Source: http://www.greenhouse.gov.au/ncas/reports/pubs/tr05afinal.pdf
Overview & Process VI
Convert with species-specific conversion
factor:
above-ground biomass  whole tree biomass
Adjust for 80% less biomass for open-grown
urban trees than computed
 Based on field measurements of 30 urban trees in
Chicago
 Nowak 1994 publication (Chicago study)
How much of biomass is carbon? Divide
biomass by 0.5 to derive stored carbon
(Chow and Rolfe 1989)
UFORE: SAS code segment
/*
ADJUST LEAF AREA OF TREES FOR OVERLAP
/*
OF CROWNS WITHIN CANOPY
/* Total the ground area of all the trees within each of the plots.
/* In addition, use ID option of the PROC MEANS to retain the
/* percent tree cover (P_TREE) of each of the plots.
PROC SORT DATA = NEWTREES;
BY PLOT LIVING TBM_TYPE;
RUN;
PROC MEANS SUM N DATA = NEWTREES NOPRINT;
BY PLOT LIVING;
VAR GRD_AREA LEAF_ARE TEMP_SH;
ID P_TREE PLT_AREA;
OUTPUT OUT = TARE_PLT SUM = TOT_CRWN TOT_LA TOT_SH N = TOT_NUM;
RUN;
Is this too MUCH??!!
http://tell.fll.purdue.edu/JapanProj/FLClipart/Adjectives/heavy.gif
Overview & Process VI
Use growth and mortality rates for annual
 Start with published and/or field data for
species and DBH class
 Adjust growth (C storage) for
 Site (e.g., park 1.78 times less growth than street)
 Growing season length
 Condition of tree
 Adjust mortality (C release) for
 % of condition class
 Rapid release (above ground, populated areas)
 Slow release (below ground, unpopulated areas)
Growth - Mortality  net annual C storage
Overview & Process VI
Value
Multiply net annual stored C by $20.30/tC
 Based on the estimated marginal social costs of
carbon dioxide emissions (Fankhauser, 1994).
 Stochastic model treats uncertainties in global
warming research/debate as random variables.
 Provides a distribution of outcomes from which
means can be calculated.
Rough order-of-magnitude assessment.
Does this help?!
Are
me?