vayreda
TRANSCRIPT
Recent climate changes interact
with stand structure and management
to determine changes in tree carbon stocks
in Spanish forests
Javier Retana, Jordi Vayreda,
Jordi Martínez-Vilalta & Marc Gracia
Remedia workshop. Bilbao, 8-9 Marzo 2012
Carbon stock change of Spanish forests. . Remedia workshop 2012Remedia workshop 2012 # #22
Houghton, AREPS 2007
INTRODUCTION (i):
1) NPP is a major driver of
the global C balance and of
the interannual growth rate
of atmospheric CO2.
Carbon stock change of Spanish forests. . Remedia workshop 2012Remedia workshop 2012 # #33
INTRODUCTION (ii):
2a) Most temperate forests are accumulating C;
2b) And are expected to continue doing so.
Carbon sink and sources (Pg C yr-1) in the word’s forests. Pan et al 2011
Carbon stock change of Spanish forests. . Remedia workshop 2012Remedia workshop 2012 # #44
Zhao & Running, Science 2010
Carnicer et al. PNAS 2011
INTRODUCTION (iii):
3) The trends in C
accumulation are less clear
(and less studied) in water
limited systems.
Carbon stock change of Spanish forests. . Remedia workshop 2012Remedia workshop 2012 # #55
OBJECTIVES of the study:
(1) to analyze the factors determining the spatial patterns
of tree C stock change of forests and its components
(i.e., growth and mortality) in Spanish forests;
(2) to evaluate how the recent trends in climate have
affected C stock changes along a water availability
gradient; and
(3) to determine whether or not forest management has
contributed to mitigate the effects of recent warming.
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Advantages of the study system:
• Spain has a wide range of climatic conditions.• Most forests in Spain are Mediterranean (and limited by water).• The climate is getting warmer (and drier) [over a 30 yr period]:
Temperature trend (ºC)
[0.00, 0.33)
[0.33, 0.67)
[0.67, 1.00)
[1.00, 1.33)
[1.33, 1.67)
[1.67, 2.00]
Relative precipitation trend (%)
[-21.0, -17.5)
[-17.5, -14.0)
[-14.0, -10.5)
[-10.5, -7.0)
[-7.0, -3.5)
[-3.5, 0.0]
TEMPERATURE TREND RAINFALL TREND
Significant in < 5% of cells
Significant in 92% of cells
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DATA SOURCES:
• Climate. Digital Climatic Atlas of the Iberian Peninsula (Ninyerola et al. 2005).
• Climate trends. Center for Climatic Research, University of Delaware
(Matsuura & Willmott 2009).
• Forest structure and C stock change. National Forest Inventory of Spain
(IFN2 & IFN3; Villaescusa & Díaz, 1998; Villanueva 2005):
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METHODS:
• Scheme including ~ 90,000 circular plots (ca. 1 plot/km2 of forest).
• Plots surveyed in 1986-1996 (IFN2) and resurveyed 1997-2008 (IFN3).
• Not included: - Crops and species used exclusively for wood production
- Plots with signs of disturbances (e.g., fire) or management
• Final dataset included 22,477 resampled plots.
Using GLM and GLZ, as a function of climate and forest structure
(1) Increment due to tree growth and ingrowth
(2) Decrease due to mortality C stock change
Above- and belowground(allometric equations from
Montero et al. 2005)
Statistical modelling
Calculation of C stock change
National Forest Inventory of Spain
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RESULTS. Distribution of growth and mortality (in Mg C ha-1 yr-1):
Growth rate
[0.0, 0.5)
[0.5, 1.0)
[1.0, 1.5)
[1.5, 2.0)
[2.0, 2.5)
[2.5, 3.0)
[3.0, 3.5)
[3.5, 4.0]
Mortality rate
[0.0, 0.1)
[0.1, 0.2)
[0.2, 0.3)
[0.3, 0.4)
[0.4, 0.5)
[0.5, 0.6)
[0.6, 0.7)
[0.7, 0.8]
GROWTH RATE MORTALITY RATE
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RESULTS. Distribution of tree C stock change (in Mg C ha-1 yr-1):
Carbon stock change
[-1.0, -0.5)
[-0.5, 0.0)
[0.0, 0.5)
[0.5, 1.0)
[1.0, 1.5)
[1.5, 2.0)
[2.0, 2.5)
[2.5, 3.0]
Overall average: Overall average: 1.4 Mg C ha1.4 Mg C ha-1-1 yr yr-1-1
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RESULTS. Determinants of C stock change:
0
1
2
3
4
5
50
100
150
5001000
15002000
2500
C s
tock
cha
nge
(Mg
C h
a-1 y
r-1)
Car
bon
stoc
k (M
g C
ha
-1 )
Tree density (trees ha-1)
A
0
1
2
3
-100
-50
0
50
100
0.0
0.51.0
C s
tock
cha
nge
(Mg
C h
a-1 y
r-1)
Wat
er a
vaila
bilit
y (%
)
Temperature trend (ºC)
B
CARBONACCUMULATION
C stock Tree density
Management
Wateravailability
Temperaturetrend
+ +
+
+
-
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RESULTS. Effects of previous forest management:
A
Temperature trend (ºC)
0.5 1.0 1.5 2.0
Gro
wth
rat
e (M
g C
ha-1
yr-1
)
1.0
1.2
1.4
1.6
1.8
UnmanagedManaged
B
Temperature trend (ºC)
0.5 1.0 1.5 2.0C s
tock
cha
nge
(Mg
C h
a-1 y
r-1)
1.0
1.2
1.4
1.6
1.8
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CONCLUSIONS:
(1) Spanish forests are accumulating C at a rate of 1.4 Mg C ha-1 yr-1.
(2) Forest structural variables are the main determinants of forest
growth and tree C stock change.
(3) Spatial variation in mortality (in terms of C loss) was mostly driven by
differences in growth rate, and was consistent with self-thinning
dynamics related to the recent abandonment of forest management.
(4) Water availability was positively related to growth and C
accumulation.
(5) Recent warming has reduced growth rate and C accumulation,
especially in wet areas.
(6) The negative effect of warming on forest C accumulation disappears if
only managed stands are considered, emphasizing the potential of
forest management to mitigate the effects of climate change.
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Thank you! & questions?Thank you! & questions?
Table 1. Summary of the best model (in terms of BIC) of growth rate (Mg C ha-1 yr-1; log transformed) as a function of plot variables (all forest types combined)
Effects Estimate T-value Pr(>|t|) Sign.
Intercept -6.29E+00 ± 1.26E-01 -49.840 <0.001 ***
Management( = true) - - - - n.s.
ln(C stock (Mg C ha-1)) 1.07E+00 ± 3.68E-02 28.956 <0.001 ***
ln(Tree density (trees ha-1) 8.80E-01 ± 2.06E-02 42.655 <0.001 ***
Water availability 1.00E-02 ± 3.80E-04 26.354 <0.001 ***
Temperature trend (ºC) -1.90E-01 ± 1.64E-02 -11.575 <0.001 ***
ln(C stock) X ln(Tree density) -1.12E-01 ± 5.90E-03 -19.004 <0.001 ***
Water availability X Temperature trend -5.21E-03 ± 3.64E-04 -14.329 <0.001 ***
Management (=true) X Temperature trend 9.88E-02 ± 2.29E-02 4.314 <0.001 ***
Degrees of freedom 22468
BIC 37794
Adjusted-R² 0.622
F-value 4627
p-value <0.001
Significant. codes: ‘***’ 0.001; ‘**’ 0.01; n.s. not significant.
Table 2. Summary of the best models (in terms of BIC) of (a) mortality occurrence (dichotomic) and (b) mortality rate (Mg C ha-1 yr-1; log transformed) as a
function of plot variables (all forest types combined).
(a)
Effects Estimate Z-value Pr(>|t|)
Sign.
Intercept -1.44E+00 ± 5.99E-02 -24.088 <0.001 ***
Management( = true) - - - - n.s.
C stock (Mg C ha-1) 1.81E-02 ± 6.63E-04 27.288 <0.001 ***
Tree density (trees ha-1) 3.01E-04 ± 2.92E-05 10.286 <0.001 ***
Water availability 6.91E-03 ± 5.49E-04 12.584 <0.001 ***
Temperature trend (ºC) -1.83E-01 ± 4.74E-02 -3.854 <0.001 ***
C stock X Tree density - - - - n.s.
Water availability X Temperature trend - - - - n.s.
Management (=true) X Temperature trend - - - - n.s.
Degrees of freedom 20020
BIC 22001
AIC 21969
Deviance explained 0.102
(b)
Effects Estimate T-value Pr(>|t|) Sign.
Intercept - - - - n.s.
Management( = true) - - - - n.s.
ln(C stock (Mg C ha-1)) - - - - n.s.
Table 3. Summary of the best model (in terms of BIC) of C stock change (Mg C ha-1 yr-1) as a
function of plot variables (all forest types combined)
Effects Estimate T-value Pr(>|t|) Sign.
Intercept 6.55E-01 ± 3.51E-02 18.644 <0.001 ***
Management( = true) - - - - n.s.
C stock (Mg C ha-1) 1.15E-02 ± 3.78E-04 30.499 <0.001 ***
Tree density (trees ha-1) 1.39E-03 ± 2.24E-05 61.920 <0.001 ***
Water availability 1.48E-02 ± 6.82E-04 21.781 <0.001 ***
Temperature trend (ºC) -2.91E-01 ± 2.96E-02 -9.823 <0.001 ***
C stock X Tree density -6.18E-06 ± 3.41E-07 -18.146 <0.001 ***
Water availability X Temperature trend -7.59E-03 ± 6.54E-04 -11.600 <0.001 ***
Management (=true) X Temperature trend 1.18E-01 ± 4.13E-02 2.847 <0.01 **
Degrees of freedom 22468
BIC 64326
Adjusted-R² 0.4062
F-value 1923
p-value <0.001
Significant. codes: ‘***’ 0.001; ‘**’ 0.01; n.s. not significant.