Journal of
Plant Ecology
VOLUME 4, NUMBER 1–2,
PAGES 91–99
MARCH 2011
doi: 10.1093/jpe/rtq039
available online at
www.jpe.oxfordjournals.org
Impact of two different types of El
Niño events on the Amazon climate
and ecosystem productivity
Wenhong Li1,*, Pengfei Zhang2, Jiansheng Ye3, Laifang Li1 and
Paul A. Baker1
1
Earth and Ocean Sciences, Nicholas School of the Environment, Duke University, Durham, NC 27708, USA
College of Atmospheric Sciences and Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, Chengdu
University of Information Technology, No.24, Block 1, Xuefu Road, Chengdu, Sichuan, 610225, P. R. China
3
MOE Key Laboratory of Arid and Grassland Ecology, School of Life Science, Lanzhou University, No.222 Tianshui South
Road, Lanzhou, 730000, P. R. China
*Correspondence address. Earth and Ocean Sciences, Nicholas School of the Environment, Duke University, 321C
Old Chem Building, PO Box 90227, Durham, NC 27708, USA. Tel: 919-684-5015; Fax: 919-684-5833;
E-mail: [email protected]
2
Abstract
Aims
The Amazon basin plays an important role in the global carbon
budget. Interannual climate variability associated with El Niño
can affect the Amazon ecosystem carbon balance. In recent years,
studies have suggested that there are two different types of El Ninos:
eastern-Pacific (EP) El Niño and central-Pacific (CP) El Niño. The
impacts of two types of El Niño on the Amazon climate and Amazon
ecosystem are analyzed in the study.
Methods
A composite method has been applied to highlight the common features for the EP- and CP-El Niño events using observational data,
IPCC-AR4 model output. Potential impacts of the two different types
of El Niño on ecosystem carbon sequestration over the Amazon have
been investigated using a process-based biogeochemical model, the
Biome–BioGeochemical Cycles model (Biome–BGC).
Important Findings
Below-normal rainfall is observed year round in northern, central
and eastern Amazonia during EP-El Niño years. During CP-El Niño
years, negative rainfall anomalies are observed in most of the Amazon during the austral summer wet season, while there is average or
above-average precipitation in other seasons. EP- and CP-El Niño
events produce strikingly different precipitation anomaly pattern
in the tropical and subtropical Andes during the austral fall season:
wetter conditions prevail during EP-El Niño years and drier condi-
INTRODUCTION
The Amazon rainforest is Earth’s most biodiverse ecosystems
and contributes about 15% of the global photosynthesis (Field
tions during CP-El Niño years. Temperatures are above-average year
round throughout tropical South America during EP-El Niño events,
especially during austral summer. During CP-El Niño events, average
or slightly above-average temperatures prevail in the tropics, but
these temperatures are less extreme than EP year’s temperature
except in austral fall. These precipitation and temperature anomalies
influence ecosystem productivity and carbon sequestration throughout the Amazon. Using the Biome–BGC model, we find that net ecosystem production (NEP) in the EP-El Niño years is below average, in
agreement with most previous studies; such results indicate that the
Amazon region acts as a net carbon source to the atmosphere during
EP-El Niño years. In the CP-El Niño years, NEP does not differ significantly from its climatological value, suggesting that the Amazon
forest remains a carbon sink for the atmosphere. Thus, even if CP-El
Niño events increase in frequency or amplitude under global warming climate as predicted in some Global Climate Models, the Amazon rainforest may remain a carbon sink to the atmosphere during El
Niño years in the near future.
Keywords: EP-El Niño d CP-El Niño d Amazon
climate d Amazon ecosystem d Amazon carbon sequestration
Received: 16 July 2010 Revised: 8 December 2010
Accepted: 9 December 2010
et al. 1998). Consequently, the Amazon region significantly
affects global atmospheric CO2 concentration (Bosquet et al.
2000). Rainfall and temperature anomalies associated with
occurrence of the El Niño-Southern Oscillation (ENSO) events
Ó The Author 2011. Published by Oxford University Press on behalf of the Institute of Botany, Chinese Academy of Sciences and the Botanical Society of China.
All rights reserved. For permissions, please email: [email protected]
92
have been suggested to impact forest primary productivity (e.g.
Asner et al. 2000; Foley et al. 2002; Kindermann et al. 1996;
Malhi and Wright 2004; Potter et al. 2001; Prentice and Lloyd
1998; Tian et al. 1998). A decline in rainfall may reduce the
rates of carbon assimilation and growth of trees and of CO2 efflux
from the soil over the Amazon; higher temperatures may
increase respiration rates in plants and soil (Meir and Grace
2005) and rates of CO2 efflux from the soil. In El Niño years,
the Amazon ecosystem is generally observed to be a net carbon
source to the atmosphere due to hot and dry climate (Foley et al.
2002; Tian et al. 1998), although some studies suggested the possibility that the lower cloudiness in the El Niño years could result
in higher productivity (Graham et al. 2003; Huete et al. 2006).
ENSO is a coupled ocean–atmosphere phenomenon occurring across the tropical Pacific, characterized by irregular fluctuations between warm (El Niño) and cold (La Niña) phases
with a periodicity ranging from 2 to 7 years. Because ENSO
is a major source of interannual climate variability over much
of South America, its impact on Amazon climate has been well
studied (e.g. Aceituno 1988; Foley et al. 2002; Garreaud et al.
2008; Kiladis and Diaz 1989; Marengo 1992; Ropelewski and
Halpert 1987). During the canonical El Niño year, temperature
is warmer than normal over tropical and subtropical latitudes;
below-normal precipitation is observed over most of tropical
South America and above-normal precipitation occurs over
the southeastern portion of the continent and central Chile.
In recent years, many studies have suggested that there are
two types of El Niño events: eastern-Pacific (EP) El Niño and
central-Pacific (CP) El Niño (Ashok et al. 2007; Kao and Yu
2009; Larkin and Harrison 2005; Yeh et al. 2009; Yu et al.
2010). The EP-El Niño is manifested by maximum sea surface
temperature anomalies (SSTAs) located over the Niño 3 region
(5°N–5°S, 150°W–90°W). The evolution of the EP-El Niño is
similar to the traditional El Niño event and it has a mean duration of 15 months (Mo 2010). On the other hand, the CP-El
Niño has warmer SSTAs in the Niño 4 region (5°N–5°S,
160°E–150°W). Its evolution is related more to local processes
(Kug et al. 2009; Yu et al. 2010) and it has a shorter duration
(usually 8 months). Because of the different convection patterns and atmospheric responses for the EP-El Niño and CPEl Niño, impacts of the two types of El Niño on regional climate
are quite different. For example, Mo (2010) studied the influence of the two types of El Niño on atmospheric temperature
and precipitation over the United States. Atmospheric
responses to the CP-type ENSO show a Pacific–North American pattern with a west–east contrast in temperature and
increased winter rainfall over the Southwest US. By contrast,
during the boreal winter season of the classical EP-El Niño, the
atmospheric response resembles a tropical northern hemisphere pattern with a north–south temperature contrast with
greater winter precipitation over the Ohio River Valley (Mo
2010). How these two types of El Niño influence Amazon climate, and how the Amazon ecosystem responds to the climate
variables produced by the two different events has not been
previously investigated.
Journal of Plant Ecology
During the late 20th century, EP-El Niños have been
observed less frequently and CP-El Niños have become more
common (Kao and Yu 2009; Yeh et al. 2009). Recent studies
further suggest that in a warming climate, CP-El Niño events
will become much more frequent than their EP-counterpart
(Yeh et al. 2009; Yu et al. 2010). How such climate changes
impact Amazon climate, the Amazon ecosystem and thus
the global atmospheric CO2 concentration will be discussed
in the study.
DATA, METHODS AND MODEL
Data and methods
In tropical South America, El Niño events have been observed
to influence temperature and precipitation (Grimm 2003), the
two climatological variables most important to the Amazon
ecosystem (Foley et al. 2002; Lewis et al. 2004; Williamson
et al. 2000). Increasing temperatures and decreasing precipitation lead to increased moisture stress (Li et al. 2008) and cause
shifts in vegetation over the Amazon during El Niño years (e.g.
Foley et al. 2002; Phillips et al. 1998; Tian et al. 1998). These
observations motivate our study of the different changes of
precipitation and surface air temperature over the Amazon
that are associated with the two different types of El Niño
events.
Long-term observational precipitation in the study is
obtained from 0.5° 3 0.5° Monthly Analysis of Global Land
Precipitation (Precl_land, Chen et al. 2002) and temperature
from the University of East Anglia Climatic Research Unit
(CRU) Global 0.5° Monthly Time Series, Version 3.0 (CRU
TS 3.0). The Precl_land and CRU TS 2.1 data (Mitchell and
Jones 2005) have been shown to best represent the Amazon
water budget as well as capture the seasonal cycle of precipitation and temperature over the Amazon (Fernandes et al.
2008; Foley et al. 2002; Negrón Juárez et al. 2009). The CRU
TS 3.0 dataset is produced in a similar way as CRU TS 2.1 without homogenization (CRU TS 3.0—Knowledgebase at http://
badc.nerc.ac.uk/data/cru/faq.html) and has shown similar
results over the Amazon during the overlapping period
(1948–2002) (not shown). The present study period is
1948–2006 due to the availability of both precipitation and
temperature data. Seasonal means of each parameter are
obtained by averaging over 3 months, i.e. austral summer,
December, January and February (DJF), and austral winter
over June, July, and August (JJA).
The two types of El Niño have been identified in Yeh et al.
(2009). In order to include more cases of the El Niño events,
the Coupled Model Intercomparison Project phase 3 multimodel data (CMIP3) under the scenario 20C3M has been
employed as in Yeh et al. (2009). Among the five CMIP3 models with the best representation of the 20th-century ratio of
CP-El Niño to EP-El Niño listed in van Oldenborgh et al.
(2005) and Mo (2010), we choose the UKMO-HadCM3 model,
which reasonably simulates seasonality of precipitation over
the Amazon in the 20th century (Li et al. 2006). During the
Li et al.
|
Impact of two El Niño events on Amazon climate and ecosystem
20th century, there are 14 EP-El Niño and six CP-El Niño
events in the model. A composite method has been applied
to highlight the common features for the EP- and CP-El Niño
events (Mo 2010). The seasonal composite starts in JJA and ends
in March, April and May (MAM) of the following year based on
the life cycle of a general El Niño event (Trenberth 1997). The
Monte Carlo technique was used to test for the statistical significance of the composites (e.g. Wilks 1995). Table 1 lists the
observed EP-El Niño and CP-El Niño years since 1948 as in
Yeh et al. (2009).
Ecosystem model
Net ecosystem production (NEP), representing the net carbon
exchange between the ecosystem and the atmosphere, can be
used as a measure of whether an ecosystem acts as a carbon
sink or source. NEP is the difference between net primary production (NPP) and microbial respiration (Rh) in the soil. Previous studies have suggested that NEP is generally lower in El
Niño years than in normal years (e.g. Tian et al. 1998). Here we
evaluate potential impacts of the two different types of El Niño
on ecosystem carbon sequestration over the Amazon using a
process-based biogeochemical model, the Biome–BioGeochemical Cycles model (Biome–BGC, White et al. 2000).
NEP for the tropical forest has been estimated near Manaus
(3°6#48S, 60°1#31W) in the central Amazon based on the climate variables for the two types of El Niño. The study site,
Ducke Reserve, is about 25 km from Manaus. The forest site
was chosen because of (i) the availability of daily environmental data for a relatively long period (1980–2005), (ii) site characteristics provided by previous studies and (iii) availability of
NEP and NPP observations for a few years that allow model
validation.
The Biome–BGC model simulates carbon fluxes in the forest
site. Given daily weather conditions, vegetation ecophysiology
and physical characteristics such as soil type, site elevation and
slope, the model estimates the daily fluxes of carbon, nitrogen
and water between the atmosphere, plant, litter and soil
(Thornton et al. 2002). Daily atmospheric data are the fundamental drivers for the Biome–BGC model. The Mountain-Climate Simulator (Glassy and Running 1994) was applied to
estimate daily near-surface meteorological parameters such
as solar radiation and vapor pressure deficit from the nearby
weather station at Manaus. Biome–BGC requires a static
description of ecophysiological characteristics of the vegetation
at a simulation site. Physical characteristics, vegetation types
and dominant species at Ducke Reserve are given in Table
2. Ecophysiological parameters of evergreen broadleaf forest
used in the study are the same as in previous studies (Ichii
et al. 2005, 2007). Process descriptions of the Biome–BGC
model are available in Hunt et al.(1996) and Thornton et al.
(2002). Details of parameterization of the model are available
in White et al. (2000).
We first generated a steady state soil carbon condition by
conducting a spin-up run using 1980–2006 climatic data
and a CO2 concentration fixed at the level of 1980. Then
93
Table 1: the EP-El Niño and CP-El Niño years using detrended
SSTs from 1948
EP-El Niño years
CP-El Niño years
1951,
1969,
1982,
1997,
1968, 1977, 1990, 1994,
2002, 2004
1957, 1963, 1965,
1972, 1976, 1979,
1986, 1987, 1991,
2006
Table 2: ecophysiological and climatological characteristics at
Ducke, Manaus
Variables
Value/description
Source
Mean annual rainfall
2 300 mm
1
Mean annual temperature
26–27°C
1, 2
Elevation
75.61 m
1
Slope
10°
1
Latitude
2.92°S
1
Soil depth
8 m (root depth)
3
Sand
49.2%
1
Climate
Site physics
Soil
Silt
3.4%
1
Clay
47.4%
1
Evergreen broadleaf
1
Vegetation
Terra-firme forest
1 = Castilho et al. (2006), 2 = Shuttleworth et al. (1984), 3 = Nepstad
et al. (2004).
we simulated NPP, Rh and NEP using time-variant atmospheric CO2, precipitation, minimum temperature (Tmin) and
maximum temperature (Tmax) for the period 1980–2005
(ftp://ftp.ncdc.noaa.gov/pub/data/gsod/). In order to discern
different responses of the Amazon rainforest to the two types
of El Niño, the carbon fluxes between the averaged five EP-El
Niño (four CP-El Niño) episodes and normal years (Table 1) are
compared.
IMPACT OF EP-EL NIÑO AND CP-EL NIÑO
ON THE AMAZON CLIMATE
Because of the different patterns and locations of convection
over the tropical Pacific Ocean, EP- and CP-El Niños induce
different atmospheric response and regional impacts over the
Amazon. Figure 1 shows the comparison of seasonal precipitation anomalies between EP- and CP-El Niño events using
Prec_land precipitation data. Similar to the classical El Niño
response (e.g. Garreaud et al. 2008), EP-El Niño is characterized by below-normal rainfall over most of tropical South
America for all seasons (Fig. 1a–d). A negative rainfall
94
Journal of Plant Ecology
anomaly starts in the Northern Amazon and Nordeste areas in
JJA and September, October, November (SON) when El Niño
is still developing in the Pacific (Fig. 1a and b); above-normal
precipitation is found over the southeastern portion of the
continent. The negative rainfall anomalies are generally less
than 1.0 mm day 1. These anomalies extend to the southern
Amazon in austral summer when El Niño is mature (Fig. 1c).
Drought intensity as indicated by the Palmer Drought
Severity Index (Dai et al. 2004) reaches its maximum in austral summer in accordance with the evolution of the ENSO
cycle (not shown). In austral fall (MAM), severe rainfall deficit is most apparent in the Nordeste area (Fig. 1d). Annual
precipitation anomalies are negative throughout the Amazon
(Fig. 5a).
Unlike the EP-El Niño events, during CP-El Niño events, significant negative rainfall anomalies can only be observed over
the Amazon in austral summer (Fig. 1g). In JJA, most of the
Amazon region is characterized by above-normal precipitation
(Fig. 1e). The negative rainfall anomalies start in SON but are
confined to a small area of the central-equatorial Amazon (0–
10°S, 53–58°W) as well as the southeastern Amazon (Fig. 1f).
In austral summer (DJF), negative rainfall anomalies during
CP-El Niño events are comparable in spatial extent, but weaker
in magnitude, to those of EP-El Niño. In austral fall (MAM),
the precipitation character of CP-El Niño events becomes strikingly different from that of EP-El Niño events, with negative
anomalies in western and southwestern Amazon and the adjacent Andes, whereas wet conditions prevail throughout much
of the central basin (Fig. 1h). Consequently, the annual rainfall anomalies over the Amazon (Fig. 5e) differ substantially
from those of EP-El Niño years (Fig. 5a).
Figure 2 compares the surface air temperatures between EPand CP-El Niño events using CRU TS 3.0 data. During EP-El
Niño years, warmer than normal conditions can be
Figure 1: composite precipitation anomalies (unit: mm day 1) for the
two types of El Niño on (a) JJA, (b) SON, (c) DJF and (d) MAM in EPEl Niño years using Prec_land data; (e–h) the same as (a–d) but for CPEl Niño years. Stippling denotes areas with at least 95% confidence
level.
Figure 2: composite temperature anomalies (unit: K) for the two
types of El Niño on (a) JJA, (b) SON, (c) DJF and (d) MAM in EPEl Niño years using CRU TS 3.0 data; (e–h) the same as (a–d) but
for CP-El Niño years. Stippling denotes areas with at least 95% confidence level.
Li et al.
|
Impact of two El Niño events on Amazon climate and ecosystem
observed over tropical and subtropical latitudes for all seasons
(Fig. 2a–d), similar to those in classical El Niño years (e.g. Garreaud et al. 2008). The positive temperature anomaly reaches
0.6–0.8 K in austral summer (DJF) over the Amazon when El
Niño peaks (Fig. 2c). Annual temperature anomalies show
abnormally warm conditions throughout the region (Fig.
5c). In contrast, during CP-El Niño years, there is no significant
temperature anomaly in JJA and SON (Fig. 2e and f) although
slightly warmer than normal conditions are observed in northern and eastern Amazon in JJA (Fig. 2e) and in southern Brazil
in SON (Fig. 2f). Abnormally high temperatures are observed
over all the Amazon in austral summer (DJF, 0.4–0.6 K, Fig.
2g); the area of significantly warmer MAM climate is limited to
the central and eastern Amazon. In the Andes, CP-El Niño
temperature anomaly is about 20% smaller than the EP-El
Niño anomaly in DJF (Fig. 2g) although in MAM, the Andean
temperature anomaly is similar to that in the EP-El Niño (Fig.
2h). Annual temperatures during CP-El Niño events show significant anomalies throughout the region, with weaker warming over the Andes than observed in EP-El Niño years (Fig. 5g).
The strong warming during CP-El Niño events is mainly due to
a secular warming trend during the period in the Amazon.
Removing this trend from the data (not shown) suggested that
CP-El Niño are characterized by slight cooling in JJA, no significant warming in SON and weaker warming over the eastern Amazon in DJF and MAM.
Model composite analysis yields a similar precipitation pattern to those observed for the two types of El Niño during the
austral spring and summer (Fig. 3). The JJA precipitation over
the central and southern Amazon is different from that of the
observation for both El Niño episodes probably due to a systematic dry bias in austral winter among many climate models
(Li et al. 2006). The annual precipitation anomalies (Fig. 5b)
are generally in agreement with observations especially during
EP-El Niño years. The UKMO-HadCM3 model realistically
simulates the spatial pattern of temperature anomalies in
EP-El Niño years, but the magnitude of the temperature
anomaly is overestimated for the seasons of SON, DJF,
MAM and the whole year (Figs. 4 and 5d). In CP-El Niño years,
modeled surface air temperature shows a stronger response
(Figs. 4 and 5h) compared to EP-El Niño years, in disagreement with observation in JJA and SON seasons. This discrepancy is also likely to be associated with the systematic dry bias
in climate models (Li et al. 2006). Fortunately, as discussed
below, the temperature discrepancy does not change the
response of Amazon ecosystem in the CP-El Niño years
because precipitation plays a more important role than temperature in the carbon sequestration for the Amazon ecosystem.
Overall, during EP-El Niño events, the Amazon experiences
warmer and drier than normal conditions, producing elevated
water stress. On the contrary, during CP-El Niño years, temperature is higher than normal only in DJF and MAM seasons
over the whole Amazon region. Below-normal precipitation is
only apparent in DJF.
95
THE POTENTIAL IMPACTS OF THE TWO
TYPES OF EL NIÑO ON THE AMAZON
ECOSYSTEM CARBON SEQUESTRATION
In order to test model performance, the carbon sequestration
results obtained from the Biome–BGC simulations are compared to those from available field-based estimates (Table
3). At the Ducke Reserve, the simulated NPP is 709–966 g C
m 2 year 1 slightly lower than the observed range of 870–
1 150 g C m 2 year 1 (Malhi et al. 2009). NEP simulated by
the Biome–BGC model yields a net carbon exchange between
the Amazon ecosystem and the atmosphere of 0.68 g C m 2
day 1, in general agreement with field measurement by Fan
et al. (1990), although the modeled NEP is about 12% higher.
Overall, NPP and NEP simulated by the Biome–BGC model are
in reasonable agreement with the results of field-based studies.
Figure 6 shows the interannual variation of the NPP, Rh and
NEP at the Ducke Reserve simulated using the Biome–BGC
model (Fig. 6). During the period 1980–2005, there were five
EP-El Niño and four CP-El Niño years (Table 1). In non-El Niño
years, the mean NEP is about 23 g C m 2 year 1, indicating
Figure 3: same as Fig. 1 but for model result.
96
Journal of Plant Ecology
Figure 5: comparison of annual mean precipitation (unit: mm day 1)
and temperature (unit: K) anomalies between EP-El Niño (left panels)
and CP-El Niño (right panels) events. (a and e) Observed precipitation,
(b and f) modeled precipitation, (c and g) observed temperature and (d
and h) modeled temperature. Stippling denotes areas with at least 95%
confidence level.
Figure 4: same as Fig. 2 but for model result.
Table 3: comparison of NPP and NEP between the simulated and
the field measurements
that the Amazon ecosystem is a net carbon sink to the atmosphere. NEP is negative in all five EP-El Niño years with a mean
NEP value of 56 g C m 2 year 1. The negative NEP values
imply that the Amazon ecosystem becomes a carbon source
to the atmosphere during EP-El Niño years. In CP-El Niño
years, however, NEP is not significantly different from that
of normal years (Fig. 6c). The mean NEP value is 34 g C m
2
year 1 in the CP-El Niño years, implying that the Amazon
ecosystem still acts as a carbon sink for the atmosphere during
this type of El Niño event.
Trends in NPP, Rh and NEP at the Ducke Reserve are estimated using the non-parametric Mann–Kendall test (Sen
1968). During the period 1980–2005, NPP increased significantly at the rate of 4.7 g C m 2 year 1 (Fig. 6a). Rh does
not change significantly during the period (Fig. 6b). As a result,
a significant, positive trend of NEP is simulated (4.0 g C m 2
year 1, Fig. 6c). This trend of NEP suggests that the Amazon
ecosystem, at least the forest in the central-equatorial Amazon,
absorbed an increasing amount of carbon from the atmosphere
during the period 1980–2005. The tendency for replacement of
Variables
NPP
Field-based
estimate
Biome–BGC-based
estimate
870–1 150 g C m
year 1
NEP (April, May/87) 0.60 g C m
2
day
2
709–966 g C m
year 1
1
0.68 g C m
2
Source
2
day
1
1
2
1 = Malhi et al. (2009), 2 = Fan et al. (1990).
EP-El Niño events by CP-El Niño events may account for much
of this trend.
Figure 7 shows the relationships between the simulated carbon fluxes and the climate variables (precipitation and surface
air temperature) at the Ducke Reserve. Both NPP and Rh are
positively correlated with annual precipitation at a high confidence level (Fig. 7a) respectively (r2 = 0.57, P < 0.01; r2 =
0.73, P < 0.01). These results are in agreement with those
of Meir and Grace (2005). There is no significant correlation
between annual mean temperature and either NPP or Rh
(Fig. 6b). This implies that precipitation (or plant available
Li et al.
|
Impact of two El Niño events on Amazon climate and ecosystem
97
water) most likely accounts for the interannual variation of
NPP and Rh over the equatorial central Amazon similar to
the results of Foley et al. (2002) and Brando et al. (2010).
DISCUSSIONS AND CONCLUSIONS
Figure 6: interannual variations of (a) NPP, (b) Rh and (c) NEP during the period of 1980–2005 simulated by the Biome–BGC model.
Unit: g C m 2. The NEP in (c) was plotted using different symbols
for normal years (open dots), EP-El Niño years (solid dots) and CPEl Niño years (asterisk).
Figure 7: variations of simulated NPP (triangle, unit: g C m 2) and Rh
(black dot, unit: g C m 2) with (a) precipitation (mm day 1) and (b) surface air temperature (°C) at Ducke Reserve during the period 1980–2005.
Previous studies concluded that the Amazon ecosystem is a net
source of atmospheric carbon dioxide during El Niño years
because of hot, dry weather over much of the region (e.g.
Foley et al. 2002; Tian et al. 1998). Based on recent research
(Yeh et al. 2009; Yu et al. 2010), we further divided El Niño
years into two groups, i.e. EP- and CP-type-El Niño events,
and analyzed the regional impacts of the two types of El Niño
over the Amazon. During EP-El Niño years, lower than normal
rainfall and abnormally warm conditions are observed in the
central, northern and eastern-Amazon region. Due to the dry
and warm conditions, we simulated negative NEP during EP-El
Niño years. The Amazon ecosystem thus acts as a carbon
source to the atmosphere. During CP-El Niño years, negative
rainfall anomalies are noticeable only in austral summer;
while above-normal precipitation can be observed over the
Amazon in other seasons. Higher precipitation in other seasons
might compensate for precipitation reduction in austral summer, resulting in NEP close to that of normal years.
The relationships between carbon fluxes, precipitation and
temperature indicate that precipitation has larger impacts on
NPP and Rh than does temperature. Therefore, the different
response of the Amazon forest to the two types of El Niño is
presumably due to the different seasonal precipitation patterns
over the Amazon region.
Some recent modeling studies have projected more frequent
and stronger El Niño events in the future (Meehl et al. 2006),
causing concern about a possible decline of carbon sequestration by the Amazon forest (Malhi et al. 2008). However, it is
also projected that EP-El Niño events will be less frequent
in the future, while CP-El Niño episodes are projected to occur
more frequently in a warming climate (Yeh et al. 2009; Yu et al.
2010). UKMO-HadCM3 is a model that has been shown to perform well in its ability to capture the ratio of the two types El
Nino (Yeh et al. 2009) and to simulate the seasonal cycle and
variability of the Amazon rainfall in the 20th century (Li et al.
2006). The UKMO-HadCM3 model projects that the frequency
of El Niño events in the 21st century will increase by 20%, and
the occurrence ratio of CP-El Niño events to EP-El Niño events
will increase as much as five times compared to that in the 20th
century (from 0.4 to 2.4). Our results suggest that during EP-El
Niño years, the Amazon ecosystem releases carbon to the
atmosphere but that during CP-El Niño years, NEP remains
positive value as in normal years. Thus, the Amazon rainforest
may still act as a carbon sink to the atmosphere during El Niño
years in the future.
Because of the different convection patterns and atmospheric responses for the EP-El Niño and CP-El Niño, impacts
of the two types of El Niño on regional climate and ecosystem
are quite different. Our work suggests that further studies of
98
Journal of Plant Ecology
the two types El Niño events and their modulation to the Earth
ecosystem are needed to reach a more realistic global carbon
budget estimate at least on interannual time scales.
Field CB, Behrenfeld MJ, Randerson JT, et al. (1998) Primary production of the biosphere: integrating terrestrial and oceanic components. Science 281:237–40.
FUNDING
Foley JA, Botta A, Coe MT, et al. (2002) El Niño–Southern oscillation
and the climate, ecosystems and rivers of Amazonia. Global Biogeochem Cycles 16:1132, doi:10.1029/2002GB001872.
This work is supported by the startup funds from Duke University and the Nicholas School Office of the Dean.
Garreaud RD, Vuille M, Compagnucci R, et al. (2008) Present-day
South American climate. Palaeogeogr Palaeoclimatol Palaeoecol
281:180–95, doi:10.1016/j.palaeo.2007.10.032.
ACKNOWLEDGEMENTS
Glassy JM, Running SW (1994) Validating diurnal climatology logic of
the MT-CLIM model across a climatic gradient in Oregon. Ecol Appl
4:248–57.
We thank the international modeling groups for providing their data
for analysis, the Program for Climate Model Diagnosis and Intercomparison (PCMDI) for collecting and archiving the model data, the JSC/
CLIVAR Working Group on Coupled Modeling (WGCM) and their
Coupled Model Intercomparison Project (CMIP) and Climate Simulation Panel for organizing the model data analysis activity and the IPCC
WG1 TSU for technical support. The IPCC Data Archive at Lawrence
Livermore National Laboratory is supported by the Office of Science,
U.S. Department of Energy. We also thank Dr Kaiguang Zhao, two
anonymous reviewers and the editor for insightful comments, and
Ms. Mary Anne Perez for editorial assistance.
Conflict of interest statement. None declared.
REFERENCES
Aceituno P (1988) On the functioning of the Southern Oscillation in
the South American sector. 1. Surface climate. Mon Weather Rev
116:505–24.
Ashok K, Behera SK, Rao SA, et al. (2007) El Niño Modoki and its possible teleconnection. J Geophys Res 112:C11007, doi:10.1029/
2006JC003798.
Asner GP, Townsend AR, Braswell BH (2000) Satellite observation
of El Niño effects on Amazon forest phenology and productivity.
Geophys Res Lett 27:981–84.
Graham EA, Mulkey SS, Kitajima K, et al. (2003) Cloud cover limits net
CO2 uptake and growth of a rainforest tree during tropical rainy seasons. Proc Natl Acad Sci U S A 100:572–576.
Grimm AM (2003) The El Niño impact on the summer monsoon in
Brazil: regional processes versus remote influences. J Climate 16:
263–80.
Huete AR, Didan K, Shimabukuro YE, et al. (2006) Amazon rainforests
green-up with sunlight in dry season. Geophys Res Lett 33:L06405,
doi:10.1029/2005GL025583.
Hunt ER, Piper SC, Nemani R, et al. (1996) Global net carbon exchange
and intra-annual atmospheric CO2 concentrations predicted by an
ecosystem process model and three-dimensional atmospheric transport model. Global Biogeochem Cycles 10:431–56.
Ichii K, Hashimoto HH, Nemani R, et al. (2005) Modeling the interannual variability and trends in gross and net primary productivity of
tropical forests from 1982 to 1999. Global Planetary Change 48:
274–86.
Ichii K, Hashimoto H, White M, et al. (2007) Constraining rooting
depths in tropical rainforests using satellite data and ecosystem
modeling for accurate simulation of gross primary production seasonality. Global Change Biol 13:67–77.
Kao H, Yu J, (2009) Contrasting eastern-Pacific and central-Pacific
types of ENSO J Climate 22:615–32.
Bosquet P, Peylin P, Ciais P, et al. (2000) Regional changes in carbon dioxide fluxes of land and oceans since 1980. Science 290:
1342–6.
Kiladis GN, Diaz HF (1986) An analysis of the 1877–78 ENSO episode and comparison with 1982–83. Mon Weather Rev 114:
1035–47.
Brando P, Goetz SJ, Baccini A, et al. (2010) Seasonal and interannual
variability of climate and vegetation indices across the Amazon. Proc
Natl Acad Sci U S A 107:14685–90.
Kindermann J, Wurth G, Kohlmaier GH, et al. (1996) Interannual variation of carbon exchange fluxes in terrestrial ecosystems. Global
Biogeochem Cycles 10:737–55.
Castilho CVD, Magnusson WE, Araujo Rno DE, et al. (2006) Variation
in aboveground tree live biomass in a central Amazonian Forest:
effects of soil and topography. For Ecol Manag 234:85–96.
Kug JS, Sooraj KP, Kim D, et al. (2009) Simulation of state-dependent
high-frequency atmospheric variability associated with ENSO. Clim
Dyn 32:635–48.
Chen M, Xie P, Janowiak JE, et al. (2002) Global land precipitation: a
50-yr monthly analysis based on gauge observations. J Hydrometeorol 3:249–66.
Dai A, Trenberth KE, Qian T, (2004) A global data set of Palmer
Drought Severity Index for 1870–2002: relationship with soil moisture and effects of surface warming. J Hydrometeorol 5:1117–30.
Fan SM, Wofsy SC, Bakwin PS, et al. (1990) Atmosphere-biosphere
exchange of CO2 and O3 in the Central-Amazon-Forest. J Geophys
Res 95:16851–64.
Fernandes K, Fu R, Betts AK (2008) How well does the ERA40 surface
water budget compare to observations in the Amazon River basin.
J Geophys Res 113:D11117. doi:10.1029/2007JD009220.
Larkin NK, Harrison DE (2005) On the definition of El Niño and associated seasonal average U.S. weather anomalies, Geophys. Res. Lett
32:L13705. doi:10.1029/2005GL022738.
Lewis SL, Phillips OL, et al. (2004) Concerted changes in tropical forest
structure and dynamics: evidence from 50 South American longterm plots Phil. Trans. R. Soc. Lond. B 359:421–36.
Li W, Fu R, Dickinson RE (2006) Rainfall and its seasonality over the
Amazon in the 21st century as assessed by the coupled models for the
IPCC AR4. J Geophys Res 111:D0211, doi:10.1029/2005JD006355.
Li W, Fu R, Negrón Juárez RI, et al. (2008) Observed change of the
standardized precipitation index, its potential cause and implications to future climate in the Amazon region. Philos Trans R Soc Lond
B Biol Sci 363:1767–72.
Li et al.
|
Impact of two El Niño events on Amazon climate and ecosystem
Malhi Y, Aragao L, Metcalfe D (2009) Comprehensive assessment of
carbon productivity, allocation and storage in three Amazonian forests. Global Change Biol 15:1255.
Malhi Y, Roberts JT, Betts RA, et al. (2008) Climate change, deforestation and the fate of the Amazon. Science 319:169–72.
Malhi Y, Wright J (2004) Spatial patterns and recent trends in the climate of tropical rainforest regions. Philos Trans R Soc Lond B Biol Sci
359:311–29.
99
Prentice IC, Lloyd J (1998) C-quest in the Amazon Basin. Nature
396:619–20.
Ropelewski CF, Halpert MS (1987) Global and regional scale precipitation patterns associated with the El-Niño Southern Oscillation.
Mon Weather Rev 115:1606–26.
Sen PK (1968) Estimates of the regression coefficient based on Kendall’s Tau. Am Stat Assoc J 63:1379–89.
Marengo JA (1992) Interannual variability of surface climate in the
Amazon basin. Int J Climatol 12:853–63.
Shuttleworth WJ, Gash JHC, Lloyd CR, et al. (1984) Eddy-correlation
measurements of energy partition for Amazonian forest. Q J R Meteorol Soc 110:1143–62.
Meehl GA, Teng H, Branstator G (2006) Future changes of El Niño in
two global coupled climate models. Clim Dyn 26:549, doi:10.1007/
s00382-005-0098-0.
Thornton PE, Law BE, Gholz HL, et al. (2002) Modeling and measuring
the effects of disturbance history and climate on carbon and water
budgets in evergreen needle leaf forests. Agric For Meteorol 113:185.
Meir P, Grace J (2005) The Effects of Drought on Tropical Forest Ecosystems.
Tropical Forests and Global Atmospheric Change. Oxford, UK : Oxford
University Press.
Tian H, Melillo JM, Kicklighter DW, et al. (1998) Effect of interannual
climate variability on carbon storage in Amazonian ecosystems.
Nature 396:664–7.
Mitchell TD, Jones PD (2005) An improved method of constructing a
database of monthly climate observations and associated high resolution grids. Int J Climatol 25:693–712.
Trenberth KE (1997) The definition of El Niño. Bull Am Meteorol Soc
78:2771–7.
Mo KC (2010) Interdecadal modulation of the impact of ENSO on precipitation and temperature over the United States. J Climate 23:
3639–56.
Negrón Juárez RI, Li W, Fu R, et al. (2009) Comparison of precipitation
dataset over tropical lands. J Hydrometeorol 10:289–99.
Nepstad D, Lefebvre P, Da Silva UL, et al. (2004) Amazon drought and
its implications for forest flammability and tree growth: a basinwide analysis. Global Change Biol 10:704–17.
van Oldenborgh GJ, Philip SY, Collins M (2005) El Niño in a changing
climate: a multi-model study. Ocean Sci 1:81–95.
White MA, Thornton PE, Running SW, et al. (2000) Parameterization
and sensitivity analysis of the BIOME-BGC terrestrial ecosystem
model: net primary production controls. Earth Interact 4:1.
Wilks DS (1995) Statistical Methods in the Atmospheric Sciences. San Diego,
CA : Academic Press.
Williamson GB, Laurance WF, Oliveira AA, et al. (2000) Amazonian
tree mortality during the 1997 El Niño drought. Conserv Biol 14:
1538–42.
Phillips OL, Malhi Y, Higuchi N, et al. (1998) Changes in the carbon
balance of tropical forests: evidence from long-term plots. Science
282:439–42.
Yeh SW, Kug JS, Dewitte B, et al. (2009) El Niño in a changing climate
Nature 461:511–4.
Potter C, Klooster S, Reis de Carvalho C, et al. (2001) Modeling seasonal and interannual variability in ecosystem carbon cycling for
the Brazilian Amazon region. J Geophys Res 106:10423–10446.
Yu J., Kao H, Lee T (2010) Subtropics-related interannual sea surface
temperature variability in the central equatorial Pacific. J Climate
23:2869–84.