Transcript Forest successional dynamics in the eastern

Reduced ecosystem functions
associated with species loss and climate
change
Han Y. H. Chen
Faculty of Natural Resources Management
Lakehead University
Research in Chen’s lab
Diversity
Function
Why plants co-exist
Biomass (C), production,
Nutrients
Disturbance
Species interaction
Climate change
Dynamics
Succession, disturbance
regimes
Why understanding diversity
function
relationships is important?
 Continuous loss of biodiversity at the global scale
 “Earth loses more than three-quarters of its species in a
geologically short interval (1k years), as has happened only five
times in the past 540 million years… a sixth mass extinction
may be under way, given the known species losses over the
past few centuries and millennia” Barnosky et al. 2011, Nature
471:51-57
Drought
Urbanization
Agriculture
Forestry
Fundamental question in BEF
• How might loss of the world's
biodiversity alter ecological function?
• Net primary production
• Nutrient cycling
• Outbreaks of insects and diseases?
The original
hypothesis
 Darwin’s (1859): the
presence of a “divergence of
characters” is essential for
reduced interspecific
competition as a result of
different demands for
resources, and in turn,
improves productivity
Tilman et al. (1997)
Science 277:1300-1302
Diversity and productivity relationships
• Despite being the most published topic in ecology
• Debate persists about diversity effects in natural vs. planted
grasslands (Adler et al. 2011, Science 333, 1750-1753)
• Evenness
• Heterogeneity of life-history traits
• The impacts of these factors on DPRs in forest
ecosystems are more poorly understood
Hypotheses
 Richness & evenness
 The extent of life-history variation
 Biomes
 Stand origin
.
 Stand age
Methods
Tropical
Temperate
Boreal
22
19
13
Each selected original study was designed to test
diversity effects, i.e., similar sites and disturbance
history
Net diversity effect, effect size (ES)
ESij 
Pij
Pij = the observed productivity of
the jth observation in the ith study
Mi
M i = the mean productivity of
monocultures
Evenness
H'
J'
ln(S )
Pielou (1969)
H’ = observed Shannon’s index
S = species richness
Trait-based approach
Contrasting
shade tolerance
Contrasting
nitrogen-fixing
Fast-slow growth
10
Statistical analysis
Boosted regression trees
Regression trees + boosting
Machine learning
Model averaging
De’ath 2007
Elith et al. 2008
Global average effect of diversity
 Ln(ES) = 0.213
 ES = 1.24
 At a global scale, the polycultures have 24%
higher productivity than monocultures
Predicted
ln(ES)
Predicted ln(ES)
a
c
b
0.3
0.3
0.3
0.2
0.2
0.2
0.1
0.1
0.1
13%
34%
0.0
0.0
0 2 4 6 8 10 12 14 16
0.0
0.2
0.4
Richness
Predicted ln(ES)
0.3
0.3
d
0.8
0
1.0
<3%
0.2
20 40 60 80 100 120
Stand age (years)
0.3
e
0.2
f
<2%
0.2
0.1
0.1
0.1
0.0
29%
0.0
Absence
Presence
0.3
<2%
0.2
Presence
Contrasting N-fixation
0.3
g
0.0
Absence
Contrasting shade tolerance
Predicted ln(ES)
0.6
Evenness
-0.1
Zhang et al. 2012. J Ecol
15%
h
<2%
0.2
0.1
0.1
0.0
0.0
Bo
Te
Biome
Tr
N
P
Stand origin
Absence
Presence
Contrasting growth habit
Known mechanisms for positive DPRs
 Niche differentiation/partitioning and/or
facilitation
 Grasslands (Tilman and many others)
 Algae in fresh water systems
(Cardinale BJ, 2011. Biodiversity
improves water quality through niche
partitioning, Nature 472, 86-89)
 Reduced Janzen–Connell effects
 Positive diversity effects on
productivity are realized by reduced
plant disease (Schnitzer et al. 2011,
Ecology 92, 296-303)
Diversity effects in belowground
 Few studies examined diversity effects on
belowground productivity of forest ecosystems
(although belowground accounts for ≈ 50% of total NPP; fine
roots, <2 mm in diameter alone accounts for 33% of total
NPP)
 Potential mechanisms are poorly understood in
natural environment
 Greater soil volume filling in natural environments?
Methods
 Pb+Late-successional
Picea mariana, Picea
glauca, and Abies
balsamea
(LSC)=Pb+LSC
deep- vs. shallow-rooted conifers
 Pinus banksiana (Pb)
 Populus tremuloides (Pt)
 Pb + Pt
gymnosperm vs. angiosperm
Seasonal biomass variation
Pb
Pt
Pb+LSC
Pb+Pt
4
3
2
1
Se
t
pt
em
be
r
O
ct
ob
er
Au
gu
s
ly
Ju
Ju
ne
0
M
ay
-1
Fine root biomass (Mg ha )
5
Brassard et al. 2013. J. Ecol.
Ingrowth
Fine root
production
MaxMin
MaxMin
3
b
Pb and Pb+LSC
Matrix
c
Pb, Pt and Pb+Pt
2
Pb +LSC
Pb
Pt
Pb+Pt
4
-1
-1
Fine root production (Mg ha year )
-1
-1
Annual fine root production (Mg ha year )
1
0.075
3
0.047
0.181
0.160
0.104
0.116
0.144
2
0.035
1
0
MaxMin
MaxMin
e
f
g
h
i
2
1
0
2
1
0
0
Ingrowth
d
Matrix
2
•
19% to 83% higher in mixedspecies stands than singlespecies stands
1
0
2
3
4
Tree species richness
5
0.0
0.2
0.4
0.6
0.8
Tree species evenness
1.0
Vertical distribution of fine roots
Pb+LSC
Pb
Pt
Pb+Pt
FF
May
MS1
MS2
FF
June
MS1
MS2
FF
July
MS1
MS2
FF
Aug
MS1
MS2
FF
Sept
MS1
MS2
FF
Oct
MS1
MS2
0
1
2
3
0
1
2
3
0
1
2
3
0
1
-1
Fine root biomass and necromass (Mg ha )
Pinus banksiana
Non-tree
Picea spp. and Abies balsamea
Necromass
Populus tremuloides and Betula papyrifera
2
3
4
3
3
2
2
Seasonal biomass heterogeneity
1
1
1 SD of biomass among 3 layers
1 SD of biomass among 7 cores
Summer
Summer
0
0
d
c
1.5
1.5
1.0
1.0
0.5
0.5
Summer
Summer
0.0
Sampling date
tob
er
Oc
be
r
Se
pte
m
Au
gu
st
ly
Ju
ne
Ju
Ma
y
er
tob
Oc
be
r
t
Se
pte
m
Au
gu
s
Ju
ly
Ju
ne
0.0
Ma
y
Horizontal heterogeneity
2.0
Fine root necromass (Mg ha -1)
4
Vertical heterogeneity
-1
Fine root biomass (Mg ha )
Pb+LSC
Pb+Pt
Relationships between fine root biomass
and heterogeneity
Pb
Pt
Pb+LSC
Pb+Pt
a
b
5
-1
Fine root biomass (Mg ha )
5
4
4
3
3
2
2
1
May
June
July
August
September
October
1
0.4
0.6
0.8
1.0
1.2
1.4
Horizontal heterogeneity
1.6
0.0
0.3
0.6
0.9
1.2
Vertical heterogeneity
1.5
Conclusion
 Evenness and trait
diversity increase
productivity both aboveand belowground
 Exploiting resources
more completely in
space and time
 Implications
 Conserving species and
trait diversity
 Diversity effects are
more pronounced in old
forests
Research in Chen’s lab
Diversity
Function
Plants
Biomass (C), production, N
& P resorption
Disturbance
Species interaction
Climate change
Dynamics
Succession, disturbance
regimes
Climate change and forest dynamics
 Biome shift
 Reduced ecosystem function, NPP, carbon
sink to source
 Forest compositional change
Widespread temporal
increases in tree
mortality have been
attributed to climate
change
 Studied 76 old-growth (>200
years old) stands
 Assume an equilibrium state,
thus all changes in mortality are
exogenous (climate change)
Studied 96 old stands
(>80 years old)
Two underlying assumptions:
1. Endogenous effects on
tree mortality in old
forests are weak, and
thus temporal variation in
tree mortality can be
solely attributed to
climate change
2. Climate change effects
are the same in young
and old forests
 Connell and Slatyer
(1977):
"We have found no example
of a community of sexually
reproducing individuals……
reached a steady-state
equilibrium"
Others attributed temporal
increases in mortality to stand
development
 Competition
 Negative density
dependence
 Tree ageing
 Thorpe & Daniels. 2012. Can.
J. For. Res. 42:1687-1696.
 Luo & Chen. 2011. J. Ecol.
99:1470-1480.
 Lutz & Halpern. 2006. Ecol.
Monogr. 76:257-275.
Unsuitable statistical methods that marginalize either climate or
non-climate drivers for longitudinal data in which these drivers are
highly correlated (Brown et al. 2011. GCB: 17: 3697)
 887 plots
 Measured: 1958-2007
 Stand age: 17 to 243 yr
Use Bayesian logistic models
 Endogenous mechanisms
 Asymmetric competition
 Stand crowding
 Interspecific interaction
 Tree ageing
 Exogenous mechanisms
 Year or Annual temperature anomaly or Drought
index (PDSI or CMI)
What is Bayesian statistics?
--vs. frequentist statistics
 Frequentist
 Parameters are fixed
quantities
 Bayesian
 The true value of a
parameter is thought of
as being a random
variable to which we
assign a probability
distribution, known
specifically as prior
information
Analyzed by young forests (≤ 80 years)
and old (>80 years)
Year effect on logit (p)
a
Sensitivity score
b
Populus tremuloides
Populus balsamifera
Pinus banksiana
Picea mariana
Picea glauca
0.07
0.06
0.05
0.04
0.03
0.02
NS
Without endogenous factors
With endogenous factors
0.01
0.00
0.06
Endogenous factors
Exogenous factors
Interaction terms
0.05
0.04
0.03
0.02
0.01
0.00
All
Young
Old
All
Young
Old
All
Young
Old
Luo and Chen. 2013. Nature Comm. 4:1655
All
Young
Old
All
Young
Old
Tree mortality in young and old forests
0.06
Populus balsamifera
Populus tremuloides
0.05
Annual mortality probability
0.04
Young forests
Old forests
0.03
0.02
0.01
0.00
0.06
Pinus banksiana
Picea glauca
Picea mariana
0.05
0.04
0.03
0.02
0.01
0.00
1960
1970
1980
1990
2000 1960
1970
1980
1990
Year
Luo and Chen. 2013. Nature Comm. 4:1655
2000 1960
1970
1980
1990
2000
Multiple climate change drivers
Higher growth rates
Higher NPP
Higher turnover rates
= high mortality?
Alternatively, more
food (CO2) improves
tree health, thus low
mortality?
Surface temperature anomalies relative to 1951–1980 from surface air measurements at
meteorological stations and ship and satellite SST measurements.
Hansen J et al. PNAS 2006;103:14288-14293
©2006 by National Academy of Sciences
Spatially heterogeneous N
deposition
Recay et al. 2008. Nat Geosci 7:430
Global drought trends for past 60 years
Sheffied et al. 2012. Nature 491: 435
1.5
ATA (ºC)
1.0
a
0.5
0.0
-0.5
 Increased mortality is
-1.0
positively associated
with temperature
anomaly
 Negatively associated
with drought index
(ACMIA)
-1.5
GPA (mm)
100
b
50
0
-50
-100
ACMIA (cm)
10
c
5
0
-5
-10
-15
1960
1970
1980
Year
1990
2000
Climate change effects on tree mortality
 The increased mortality is also higher in
 Pure than mixed forests
 More crowded forests
 Among species
 Higher for Populus balsamifera among pioneers
 Higher Picea spp. than Populus tremuloides and Pinus
banksiana
Undergoing forest compositional shift that is independent of
endogenous forest succession
—an important conservation challenge!
Current and future research in Chen’s lab
Biogeography of diversity and
function of Canada’s forest
Function
Diversity
Why/how species
co-exist?
Disturbance
Species interaction
Climate change
Productivity &
stability
Dynamics
• Long-(>8,000 years) and short-term fire
regime and forest dynamics
Acknowledgements
 Funding
 NSERC Discovery Grant
 NSERC Strategic Project
 National Centre of Excellence Network of Sustainable Forest
Management
 Ontario Early Research Award program
 Northern Ontario Heritage Fund Cooperation
 Partners and collaborators
 Resolute Inc.
 Tembec Inc.
 Louisiana-Pacific Canada Ltd.
 Ontario Forest Ecosystem Science Co-operative Inc.
 Provincial Governments
 Canadian Forest Service