Post on 21-Feb-2020
Developing a General Understanding of the
Decomposition Process: Results of a Network Experiment
Mark E. HarmonRichardson Chair and ProfessorDepartment of Forest Science
Oregon State University
Thanks to!
• Becky Fasth, Jay Sexton, and many, many others throughout the LTER network for their help in
installing and maintaining the experiments
• The NCEAS Decomposition Working Group
• NSF-LTER, LTRB, Ecosystems, NCEAS for funding
Decomposition is an important process to understand
• Controls accumulation of organic matter• Carbon dynamics of ecosystems
– Present and future• Nutrient release for plants• Decomposed material influences soil
properties• Ecosystem indicator of pollution
Compared to production we know little about decomposition
• Relatively few studies on decomposition• Few global views of process-studies
generally local• Few global models of process• Few databases to drive global
calculations• Uncertainty about long-term dynamics
LIDET: Long-term IntersiteDecomposition Experiment Team
To what degree does climate versus substrate quality control:
The rate of decomposition? Hypothesis: they interact
The formation of stable organic material? Hypothesis: no effect of either, a constant 15%
Lignin (%)
k
AET = 797 mm
AET = 343 mm
Climate-Substrate Quality Interaction-Meentemeyer (1978)
Background
• 1988 Wood’s Hole workshop at Marine Biological Laboratory– LIDET; DIRT experiments designed
• 1989 Litter collected, bags filled• 1990-91 Litter placed in field• 2002 field work completed• 2003-2006 NCEAS working group
Location of LIDET sites
Existing North American Networks
• LIDET: Long-term IntersiteDecomposition Experiment Team
• CIDET: Canadian IntersiteDecomposition Experiment
-10
-5
0
5
10
15
20
25
30
0 1000 2000 3000 4000 5000
Annual Precipitation (mm)
Annu
al T
empe
ratu
re (C
)
LIDETsites
Climatic Fields-LIDET
-15
-10
-5
0
5
10
15
20
25
30
0 1000 2000 3000 4000 5000
Annual Precipitation (mm)
Annu
al T
empe
ratu
re (C
)
LIDET
CIDET
Climatic Fields-LIDET & CIDET
0
0.5
1
1.5
2
2.5
0 10 20 30 40
Lignin (%)
Nitr
ogen
(%)
CIDET
LIDET
Substrate Quality: Lignin v. Nitrogen
Steps Involved• Collection of litter as selected sites• Preparation of litterbags; data set built• Sent to 28 sites• Site periodically send data and litter back• Initial Quality control checks, data entry,
preliminary analysis• Lab analysis
Litter bags20X20 cmOn surface
Root bags20X20 cmBuried ~10 cm
Models ExaminedMt=M0 exp[-kt]
Single exponential
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 2 4 6 8 10Time (years)
Mas
s re
mai
ning
Single exponential
0.001
0.01
0.1
10 2 4 6 8 10
Time (years)M
ass
rem
aini
ng
Models ExaminedMt=Mf0 exp[-kft]+Ms0 exp[-kst]
Dual Exponential
00.10.20.30.40.50.60.70.80.9
1
0 2 4 6 8 10Time (years)
Mas
s re
mai
ning
Dual Exponential
0.01
0.1
10 2 4 6 8 10
Time (years)
Mas
s re
mai
ning
Models ExaminedMt=Mf0 exp[-kft]+Mstable
Asymptotic
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 2 4 6 8 10Time (years)
Mas
s re
mai
ning
Asymptotic
0.1
10 2 4 6 8 10
Time (years)
Mas
s re
mai
ning
Acsa
0.00
20.00
40.00
60.00
80.00
100.00
120.00
0.00 2.00 4.00 6.00 8.00 10.00 12.00
Time (years)
Mas
s re
mai
ning
(%)
observedsingle expdual exp
Drgl
0.00
20.00
40.00
60.00
80.00
100.00
120.00
0.00 2.00 4.00 6.00 8.00 10.00 12.00
Time (years)
Mas
s re
mai
ning
(%)
observedsingle expdual exp
Pire
0.00
20.00
40.00
60.00
80.00
100.00
120.00
0.00 2.00 4.00 6.00 8.00 10.00 12.00
Time (years)
Mas
s re
mai
ning
(%)
observedsingle expdual exp
Qupr
0.00
20.00
40.00
60.00
80.00
100.00
120.00
0.00 2.00 4.00 6.00 8.00 10.00 12.00
Time (years)
Mas
s re
mai
ning
(%) observed
single expdual exp
Ange-roots
0.00
20.00
40.00
60.00
80.00
100.00
120.00
0.00 2.00 4.00 6.00 8.00 10.00 12.00
Time (years)
Mas
s re
mai
ning
(%)
observedsingle expdual exp
Drgl roots
0.00
20.00
40.00
60.00
80.00
100.00
120.00
0.00 2.00 4.00 6.00 8.00 10.00 12.00
Time (years)
Mas
s re
mai
ning
(%)
observedsingle expdual exp
Piel roots
0.00
20.00
40.00
60.00
80.00
100.00
120.00
0.00 2.00 4.00 6.00 8.00 10.00 12.00
Time (years)
Mas
s re
mai
ning
(%)
observedsingle expdual exp
Single exponential-Pine leaves
Pire L
0
20
40
60
80
100
120
140
160
0 20 40 60 80 100
Observed (PMR)
Mod
el 1
Pre
dict
ed (P
MR
)
Single exponential-Drypetes leaves
Drgl L
0
20
40
60
80
100
120
140
160
0 20 40 60 80 100
Observed (PMR)
Mod
el 1
pre
dict
ed (P
RM
)
Double exponential-pine leaves
Pire L
0102030405060708090
100
0 20 40 60 80 100
Observed (PMR)
Mod
el 5
pre
dict
ed (P
MR
)
Double exponential-Drypetes leaves
Drgl L
0102030405060708090
100
0 20 40 60 80 100
Observed (PMR)
Mod
el 5
pre
dict
ed (P
MR
)
Asymptotic-pine leavesPire L
0
20
40
60
80
100
120
0 20 40 60 80 100
Observed (PMR)
Mod
el 3
Pre
dict
ed (P
MR
)
Asymptotic-Drypetes leaves
Drgl L
0
20
40
60
80
100
120
0 20 40 60 80 100
Observed (PMR)
Mod
el 3
pre
dict
ed (P
MR
)
Which model is best?
0 20 40 60 80 100
Single exponential
Doubleexponential
Asymptotic
Mod
el
Matches (%)
Dual Exponential v AsymptoticAll sites and species
-20
0
20
40
60
80
100
0 20 40 60 80 100
Model 4 prediction (PMR)
Mod
el 5
pre
dict
ion
(PM
R)
Decomposition Rate-constants of Fast Phase
0
2
4
6
8
10
12
14
16
Andrews Luquillo
Site
Fast
rate
-con
stan
t (pe
r yea
r)
Time
Accumulated carbon in forest floor, Sweden
R2 = 0.993p<0.01
2984 yrs2081 yrs120 yrs 1106 yrs
7.8 tons
72 tons
173 tons
245 tons
After Wardle et al
Decomposition rate-constant of slow fraction
0
0.2
0.4
0.6
0.8
1
1.2
1.4
Andrews LuquilloSite
Rat
e-co
nsta
nt (p
er y
ear) Drypetes
Pinus
What is the Decomposition Rate?
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
0 2 4 6 8 10Time (years)
K pe
r yea
r
0
1
2
3
4
5
6
7
8
0 5 10 15 20 25
Time (years)
Sto
re
year 1
year 2
year 3
year 4
year 10
year 5
year 6
year 7year 8
year 9
Total litter
Overall Decomposition rate-constant: method
Year whatever
K=Input/Store
Example of calculation of integrated k
0
20
40
60
80
100
120
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31Time (years)
Mas
s re
mai
ning
(%)
species 1species 2
Species 1 2Store 624 617Input 100 100K 0.160 0.162
Integrated v. 1st year k
0.000
0.500
1.000
1.500
2.000
2.500
3.000
3.500
4.000
4.500
5.000
0.000 1.000 2.000 3.000 4.000 5.000
First-year k (per year)
Inte
grat
ed k
(per
yea
r)
observations1:1 lineregression
Y=0.75 XR2=0.59
Integrated v. 1st year k
0.00
1.00
2.00
3.00
4.00
5.00
6.00
7.00
0.000 1.000 2.000 3.000 4.000 5.000 6.000
1st year k (per year)
Inte
grat
ed: 1
st y
ear k
ratio
82% cases1st year k>integrated k
After Parton et al 2007
Open Sites
After Parton et al 2007
Short-termrelationships1st yeardecompositionrate-constants and Climate
ANGE roots, lignin = 10.5
kS
0.5
1.0
1.5
2.0
2.5
DRGL foliage, lignin = 10.9
ACSA foliage, lignin = 15.9
kS
0.5
1.0
1.5
2.0
2.5
DRGL roots, lignin = 16.1
TRAE foliage, lignin = 16.2
kS
0.5
1.0
1.5
2.0
2.5
PIRE foliage, lignin = 19.2
PIEL foliage, lignin = 21.4
kS
0.5
1.0
1.5
2.0
2.5
QUPR foliage, lignin = 23.5
THPL foliage, lignin = 26.7
0.0 0.2 0.4 0.6 0.8 1.0
kS
0.5
1.0
1.5
2.0
2.5
PIEL roots, lignin = 34.9
0.2 0.4 0.6 0.8 1.0Climatic Decomposition Index (CDI)
Currie et al in prep
Long-termrelationships10 year averagedecompositionrate-constants and Climate
ANGE roots, lignin = 10.5
kI
0.25
0.50
0.75
1.00
DRGL foliage, lignin = 10.9
ACSA foliage, lignin = 15.9
kI
0.25
0.50
0.75
1.00
DRGL roots, lignin = 16.1
TRAE foliage, lignin = 16.2
kI
0.25
0.50
0.75
1.00
PIRE foliage, lignin = 19.2
PIEL foliage, lignin = 21.4
kI
0.25
0.50
0.75
1.00
QUPR foliage, lignin = 23.5
THPL foliage, lignin = 26.7
0.0 0.2 0.4 0.6 0.8 1.0
kI
0.25
0.50
0.75
1.00
PIEL roots, lignin = 34.9
0.2 0.4 0.6 0.8 1.0Climatic Decomposition Index (CDI)
Currie et al in prep
Regression RelationshipsDependent
variable
Climate alone Litter quality alone AET and lignin only
Best independent variable r2 p Best independent
variables‡ r2 p r2 p
kS CDI 0.46 < 0.001 lignin:N 0.14 < 0.001 0.48 < 0.001
kH CDI 0.45 0.048 lignin:N, ascarb, ws 0.11 0.001 0.41 0.001
kD CDI 0.30 0.034 lignin:N, ascarb 0.09 0.014 0.28 < 0.001
MD CDI 0.11 < 0.001 tnn, acid 0.10 < 0.001 0.16 < 0.001
kI AET 0.07 < 0.001 tex, ascarb 0.06 < 0.001 0.13 < 0.001
Climatic Effects: Dowel Results
Single exponential model
0.000
0.200
0.400
0.600
0.800
1.000
1.200
1.400
1.600
1.800
0.000 0.100 0.200 0.300 0.400 0.500 0.600
Aboveground k1 (per year)
Belo
wgr
ound
k1
(per
yea
r) observed1:1 line
Above- v Belowground
CDI v Single exponential (k1)
0.000
0.200
0.400
0.600
0.800
1.000
1.200
1.400
1.600
1.800
0 0.2 0.4 0.6 0.8 1CDI (dimensionless)
k1 (p
er y
ear)
Below meshAboveBelow exposed
Climate Decomposition Index
Arid/AnnualGrassland
0102030405060708090100Biomass Remaining (%)
0.0
0.5
1.0
1.5
Initi
al N
Rem
aini
ng (%
)
TropicalForest
Humid Grassland
DeciduousForest
ConiferForest
Tundra
Drypetes glauca
Andropogon gerardi and, Pinus elliottii
020406080100Biomass Remaining (%)
0.0
0.5
1.0
1.5
Initi
al N
Rem
aini
ng (%
)Long-term Nitrogen Dynamics-fine roots-Parton et al 2007
01020304050607080901000.00.51.01.52.02.5
Initi
al N
Rem
aini
ng (%
)
01020304050607080901000.00.51.01.52.02.5
01020304050607080901000.00.51.01.52.02.5
0102030405060708090100Biomass Remaining (%)
0.00.51.01.52.02.5
1.97 % N
1.02 % N
0.58-0.81 % N
0.38 % N
TropicalForest
Annual Grassland
Humid Grassland
DeciduousForest
ConiferForest
Tundra
Long-term Nitrogen Dynamics-Initial Nitrogen Content-Parton et al 2007
0102030405060708090100Biomass Remaining (%)
0.00.51.01.52.02.5
01020304050607080901000.00.51.01.52.02.5
01020304050607080901000.00.51.01.52.02.5
01020304050607080901000.00.51.01.52.02.5
AridGrassland
Humid Grassland
Initi
al N
Rem
aini
ng (%
)1.98 % N
1.02 % N
0.58-0.80 % N
0.38 % N
Figure 4 e-h
Website slide
Future Experiments
Fill out range of environments: Tropical-subtropical; hydric
Better Understanding of MicroclimateInfluence of organisms
Decomposition rate of the slow phase materialDoes mass of slow phase depend on formation
rate or decomposition rate?