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Biometrics Working Group Meeting – New Orleans, LA. 04 March, 2009
Forest Inventory Components of Change (Growth, Removals & Mortality):
Christopher M. OswaltSouthern Research Station FIA
OutlineOutline
• Brief introduction of the topic
• Walk through the components of change
• Examples
• Recent regional trends
• Challenges
• Summary
IntroductionIntroduction
• Development informs utilization
• Of interest:– A population as recruitment occurs into,
through, and eventually exiting some expressed standard
Inventory Then
Inventory Now
G
RM
GG
M
G G
Conceptually Simple
GG
G
MG
G RR R
G G G
Operationally ComplexOperationally Complex
Private Timberland
0
500
1000
1500
2000
2500
3000
3500
4000
4500
5000
Select
white
oak
s
Select
red
oaks
Other
whit
e oa
ks
Other
red
oaks
Hickor
y
Yellow
birc
h
Hard
map
le
Soft m
aple
Beech
Sweetg
um
Tupelo
and
bla
ckgu
mAsh
Cotto
nwoo
d an
d as
pen
Bassw
ood
Yellow
-pop
lar
Black
walnu
t
Other
eas
tern
soft
hard
woods
Other
eas
tern
har
d ha
rdwoo
ds
Easte
rn n
onco
mm
ercia
l har
dwoo
ds
Mill
ion
tre
es (n
o.)
1990
2003
Components of ChangeComponents of Change
• Survivor growth• Ingrowth• Mortality• Cut• Reversions• Diversions• Cull increment
(minus)• Cull decrement
• Growth on ingrowth• Mortality growth• Cut growth• Reversion growth• Diversion growth• Cull increment growth• Cull decrement
growth
AssumptionsAssumptions
• Time of change is between then and now, but exactly when is unknown
• Time of change is estimated to be midway between t (time 1) and t+1 (time 2)
• Growth model is used to predict midpoint tree size– Usually based on past attributes
– Based on current attributes when there are no past attributes
T1 T2
Components of GRMComponents of GRM
• Survivor growth– Trees alive and measured time 1 and time 2– Diameter >= threshold (e.g. 5.0”) both times– No change in tree class (growing stock, cull,
etc.)– Contributes to G
Threshold DBH
Components of GRMComponents of GRM
• Ingrowth– Tree below threshold time 1 (may or may not
have been measured)– Tree grows across threshold before time 2– Contributes to G
Threshold DBH
Components of GRMComponents of GRM
• Mortality– Tree alive time 1– Tree dead time 2– Predicted midpoint diameter used to compute
volume– Contributes to M
Components of GRMComponents of GRM
• Cut– Tree alive time 1– Tree cut before time 2– Predicted midpoint diameter used to compute
volume– Contributes to R
Components of GRMComponents of GRM
• Cull increment– Growing stock time 1– Cull time 2– Predicted midpoint diameter used to compute
volume– Reduces G
Components of GRMComponents of GRM
• Cull decrement– Cull time 1– Growing stock time 2– Predicted midpoint diameter used to compute
volume– Contributes to G
Components of GRMComponents of GRM
• Reversion– Nonforest (or non-timberland) time 1– Forest (or timberland) time 2– Predicted midpoint diameter used to compute
volume– Contributes to G
Components of GRMComponents of GRM
• Diversion– Forest (or timberland) time 1– Nonforest (or non-timberland) time 2– Predicted midpoint diameter used to compute
volume– Contributes to R
GRM’s Defined (Scott et. al 2005)GRM’s Defined (Scott et. al 2005)
• Growth– Gross ingrowth = Ingrowth + Reversion– Gross growth = Gross ingrowth + accretion
• Accretion = GS+GI+GR+GM+GC+GD
– Net growth = Gross growth - mortality
• Removals– Cut stems and/or Diversions(forest – nonforest or timberland-reserved)
• Mortality– Death from natural causes
Growth & Removal TrendsGrowth & Removal Trends
Year
1940 1950 1960 1970 1980 1990 2000 2010
Ft3
(th
ousa
nds)
0
2000000
4000000
6000000
8000000
10000000
12000000
14000000
South
North
Pacific Coast
Rocky Mountain
Year
1940 1950 1960 1970 1980 1990 2000 2010
Ft3
(th
ousa
nds)
0
2000000
4000000
6000000
8000000
10000000
12000000
14000000
South
North
Pacific Coast
Rocky Mountain
Growing Stock on Timberland
Solid line - Growth Broken line - Removals
Growth & Removal TrendsGrowth & Removal Trends
Year
1970 1975 1980 1985 1990 1995 2000 2005 2010
G:R
0
1
2
3
4
5
NorthSouthRocky MountainPacific Coast
Year
1970 1975 1980 1985 1990 1995 2000 2005 2010
G:R
0
1
2
3
4
5
NorthSouthRocky MountainPacific Coast
Growing Stock on Timberland
ChallengesChallenges
• Historical reporting biases and naming conventions– Not all FIA reported removals reflect “removed” trees– Change and growth not the same thing
• Address through – additional tables or definitional changes?
• Historic variability in interpreting reserve status– GRM estimates are highly sensitive to changes in reserve status
• Address from what angle - data acquisition or compilation/processing?
• Not applicable on forest land
• Regional inconsistencies – Current estimation procedures– Mapped plot to mapped plot implementation
Additional DetailAdditional Detail
Total AAR – AAR(diversions) = More informative picture of actual removals
ChallengesChallenges
• Historical reporting biases– Not all FIA reported removals reflect “removed” trees
• Address through – additional tables or definitional changes?
• Historic variability in interpreting reserve status– GRM estimates are highly sensitive to changes in
reserve status• Address from what angle - data acquisition or
compilation/processing?• Not applicable on forest land
• Regional inconsistencies – Current estimation procedures– Mapped plot to mapped plot implementation
Currently… Not all there yet.Currently… Not all there yet.
SouthPrimarily annual to annual
NorthPrimarily annual to annual
Rocky MountainRemeasurement has not started
Pacific NorthwestTesting in California National Forests
Similar plot footprints (periodic to annual) in Alaska (testing)
ChallengesChallenges
• GRM labeling conventions to facilitate proper interpretation– FIDO II
• Tennessee: 2007 GRM - Tennessee (47) -- Mortality :: growing-stock on timberland by U.S. Counties and Major species group (in cuft/year)
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
ChallengesChallenges
• Lack of access to previous condition when using external data tools– Internal – uses previous condition (correct)
– External – uses current condition (wrong)
Source Total Large Medium Small Nonstocked
External 437.6 152.2 48.1 167.8 4.1
Internal(published)
437.6 341.1 85.8 10.3 .3
Absolute Difference
0 188.9 37.7 157.5 3.8
Million ft3 year-1
Example – TN(2007) – Removals of live trees on forest land by stand size class
SummarySummary
• GRM is conceptually simple• GRM analysis is complicated by the fact that the
same tree can contribute to different components of GRM
• GRM analysis will become simpler and more precise in the future
• Additional analytical techniques needed• Refinements in methodology potentially
necessary• Updates to some external tools needed
AcknowledgementsAcknowledgements
• Ray Sheffield
• Gary Brand
• Bill Burkman
• John Coulston