Carbon exchange of a mature, naturally regenerated pine forest in north Florida.

Abstract

We used eddy covariance and biomass measurements to quantify the carbon (C) dynamics of a naturally regenerated longleaf pine/slash pine flatwoods ecosystem in north Florida for 4 years, July 2000 to June 2002 and 2004 to 2005, to quantify how forest type, silvicultural intensity and environment influence stand-level C balance. Precipitation over the study periods ranged from extreme drought (July 2000-June 2002) to above-average precipitation (2004 and 2005). After photosynthetic photon flux density (PPFD), vapor pressure deficit (VPD) >1.5 kPa and air temperature <10 °C were important constraints on daytime half-hourly net CO₂ exchange (NEEday) and reduced the magnitude of midday CO₂ exchange by >5 μmol CO₂ m⁻² s⁻¹. Analysis of water use efficiency indicated that stomatal closure at VPD>1.5 kPa moderated transpiration similarly in both drought and wet years. Night-time exchange (NEEnight) was an exponential function of air temperature, with rates further modulated by soil moisture. Estimated annual net ecosystem production (NEP) was remarkably consistent among the four measurement years (range: 158-192 g C m⁻² yr⁻¹). In comparison, annual ecosystem C assimilation estimates from biomass measurements between 2000 and 2002 ranged from 77 to 136 g C m⁻² yr⁻¹. Understory fluxes accounted for approximately 25-35% of above-canopy NEE over 24-h periods, and 85% and 27% of whole-ecosystem fluxes during night and midday (11:00-15:00 hours) periods, respectively. Concurrent measurements of a nearby intensively managed slash pine plantation showed that annual NEP was three to four times greater than that of the Austin Cary Memorial Forest, highlighting the importance of silviculture and management in regulating stand-level C budgets.

Full text

Page 1

Carbon exchange of a mature, naturally regenerated pine
forest in north Florida
T H O M A S L . P O WE L L *w , H EN RY L . GH OL Z z, K E N N E T H L . CL A R K *§ , G R E G O RY S TAR R *} ,
W EN D E L L P. C R O P P ER JR* and T I M O TH Y A. M A RT I N *
*School of Forest Resources and Conservation, University of Florida, PO Box 110410, Gainesville, FL 32611, USA, wSmithsonian
Environmental Research Center, Mail Code DYN-3, Kennedy Space Center, FL 32899, USA, zDivision of Environmental Biology,
National Science Foundation, 4201 Wilson Boulevard, Arlington, V A 22230, USA, §USDA Forest Service, Silas Little Experimental
Forest, PO Box 232, New Lisbon, NJ 08064, USA, }Department of Biological Sciences, University of Alabama, PO Box 870206,
Tuscaloosa, AL 35487, USA
Abstract
We used eddy covariance and biomass measurements to quantify the carbon (C)
dynamics of a naturally regenerated longleaf pine/slash pine flatwoods ecosystem in
north Florida for 4 years, July 2000 to June 2002 and 2004 to 2005, to quantify how forest
type, silvicultural intensity and environment influence stand-level C balance. Precipita-
tion over the study periods ranged from extreme drought (July 2000–June 2002) to above-
average precipitation (2004 and 2005). After photosynthetic photon flux density (PPFD),
vapor pressure deficit (VPD) 41.5kPa and air temperature o101C were important
constraints on daytime half-hourly net CO2exchange (NEEday) and reduced the magni-
tude of midday CO2exchange by 45lmolCO2m?2s?1. Analysis of water use efficiency
indicated that stomatal closure at VPD41.5kPa moderated transpiration similarly in
both drought and wet years. Night-time exchange (NEEnight) was an exponential function
of air temperature, with rates further modulated by soil moisture. Estimated annual net
ecosystem production (NEP) was remarkably consistent among the four measurement
years (range: 158–192gCm?2yr?1). In comparison, annual ecosystem C assimilation
estimates from biomass measurements between 2000 and 2002 ranged from 77 to
136gCm?2yr?1. Understory fluxes accounted for approximately 25–35% of above-canopy
NEE over 24-h periods, and 85% and 27% of whole-ecosystem fluxes during night and
midday (11:00–15:00 hours) periods, respectively. Concurrent measurements of a nearby
intensively managed slash pine plantation showed that annual NEP was three to four
times greater than that of the Austin Cary Memorial Forest, highlighting the importance
of silviculture and management in regulating stand-level C budgets.
Keywords: carbon dynamics, eddy covariance, Florida, natural regeneration, net ecosystem exchange,
Pinus elliottii, Pinus palustris
Received 13 October 2007; revised version received 16 April 2008 and accepted 23 April 2008
Introduction
Forests of the southeastern US have been identified as
an important carbon (C) sink largely resulting from a
climate-driven easement of constraints on productivity
(Nemani et al., 2003) and reversion of agricultural land
to forest (Turner et al., 1995). Pine forests are one of the
most widespread ecosystem types in this region, cover-
ing approximately 257000km2and comprising 33% of
the total timberland (Conner & Hartsell, 2002). Given
the importance of pine forests for the region’s C bal-
ance, a key element of adapting forest management
to the goal of mitigating climate change is understand-
ing how various silvicultural options available to
land managers impact stand- and landscape-level
C budgets.
In Florida, approximately 50% of terrestrial ecosys-
tems are pine flatwoods, which are composed of a
mixture of about two-thirds pine uplands and one-third
deciduous cypress (Taxodium spp.) wetlands (Myers &
Ewel, 1990). Historic pine flatwoods were characterized
Correspondence: Timothy A. Martin, tel. 11 352 846 0866,
e-mail: tamartin@ufl.edu
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by open-canopy, mixed stands of longleaf pine (Pinus
palustris Mill.) and slash pine (Pinus elliottii var. elliottii
Engelm.), with a dense understory thought to be main-
tained by frequent (ca. every 3–7 years) low-intensity
fires (Abrahamson & Hartnett, 1990). Following Eur-
opean settlement, species composition, stand structure,
and regeneration were largely dictated by silviculture,
first through selective logging, and more recently by
even-aged management. Management intensity has
generally increased over time, and pine flatwoods are
now the most intensively managed forest ecosystem
in Florida (Abrahamson & Hartnett, 1990). Current
plantations are typically clearcut every 15–25 years,
mechanically and/or chemically site prepared, regen-
erated using genetically improved tree seedlings, and
treated one to three times per rotation with chemical
fertilizers and/or herbicides.
Evaluating the effects of even-aged management on
the C dynamics of pine flatwoods and cypress wetlands
has been a major focus of recent research (e.g. Gholz &
Fisher, 1982; Cropper & Gholz, 1993; Clark et al., 1999,
2004). Still largely unexamined are the 18% of Florida’s
5.76 millionha of timberlands which are naturally re-
generated, nonplantation stands. These stands are clas-
sified by the USDA Forest Service as ‘natural pine’
forests (Conner & Hartsell, 2002), and this distinction
implies a contrast to short-rotation, even-aged planta-
tions. Natural and uneven-aged management is increas-
ingly being considered as an alternative silvicultural
model for nonindustrial forest lands (Owen, 2002).
Therefore, an evaluation of the C dynamics of natural
flatwoods ecosystems is necessary to understand differ-
ences between these contrasting land uses, both today
and into the future.
Understory C dynamics may differ significantly be-
tween ‘natural stands’ and intensively managed planta-
tions because of the relatively open canopies of older,
natural flatwoods forests and the lack of intensive
silvicultural practices. Gross ecosystem production of
forest understories is controlled to a great extent by
understory leaf area index (LAI) and the amount of
light transmitted to the understory (Misson et al., 2007).
Following canopy closure in unburned plantations,
understory biomass approaches a steady state (Gholz
& Fisher, 1982), which suggests that long-term net CO2
exchange is insignificant. In contrast, the tree canopies
of natural pine flatwoods typically have a relatively low
LAI, which allows large amounts of radiation to pene-
trate the understory (Gholz et al., 1991), and implies that
the net CO2 exchange capacity of the understory is
much greater.
The objective of this study was to characterize the C
dynamics of a mature, naturally regenerated Florida
pine flatwoods ecosystem and compare its C budget
with a contrasting, intensively managed slash pine
plantation. To meet this objective, we commenced eco-
logical measurements over a natural pine flatwoods
community in north Florida to compare with simulta-
neous measurements and previously reported results
from adjacent pine plantations. We framed our research
in terms of the following questions: (1) how much C
does a mature, naturally managed pine flatwoods se-
quester on an annual basis; (2) how much of the inter-
annual variation in net ecosystem C exchange is
explained by precipitation and water stress; (3) how
much of the total ecosystem C flux is accounted for by
the understory; and (4) how does long-term net ecosys-
tem C production of a mature, less intensively managed
pine flatwoods compare with that of a younger, more
intensively managed pine plantation?
Materials and methods
Study sites
The study was conducted from July 2000 to June 2002
and January 2004 to December 2005 in a 41ha pine
flatwoods ecosystem in the Austin Cary Memorial
Forest (ACMF). The ACMF is managed by the School
of Forest Resources and Conservation of the University
of Florida and located 15km northeast of Gainesville,
Alachua County, Florida, USA (2914401700N, 821130800W;
elevation 50m). Prior to state purchase in 1936, the site
had been selectively harvested for timber and used for
low-intensity cattle grazing. In 1936, the area was
allowed to regenerate naturally from remnant seed
trees. The resulting stand was thinned in 1991 by
removing 27% of the basal area to open the canopy.
The current management objective is to restore an
uneven-aged, mixed slash and longleaf pine stand by
encouraging natural regeneration through prescribed
burns every 3–5 years.
A 30-m walkup scaffolding tower was erected in the
forest for this study. The fetch from the tower was
greater than 1km in the north and south directions,
and approximately 0.5km in the east and west direc-
tions. The fetch encompassed two similar administra-
tive compartments; before this study, the understory of
one was burned in the winter of 1997 and the other in
the winter of 1998. The overstory was composed of
longleaf pine and slash pine (72% and 28% of tree basal
area, respectively), with tree ages ranging from 20 to 80
years in 2001. The top of the tree canopy averaged 22m.
The tree canopy was vertically separated by 15m over a
1.5-m-tall, dense understory. In 2000, stand basal area
was 18.6m2ha?1, and stem density was 363treesha?1.
The understory consisted of native species dominated
by saw palmetto [Serenoa repens (Bartr.) Small], gallberry
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[Ilex glabra (L.) Gray], wax myrtle (Myrica cerifera, L.),
and wiregrass (Aristrida stricta Michx). The soils were
poorly drained ultic alaquods (sandy, siliceous, ther-
mic) with a discontinuous spodic horizon 30–60cm
deep and argillic horizon approximately 1.25m deep.
Measurements covering the same periods were
also made at the Donaldson Tract (DT) pine planta-
tion located 5.75km to the northeast of the ACMF.
Slash pine trees were planted to harvest density
( ? 2000treesha?1) following a clearcut in 1990. Domi-
nant canopy height ranged from 11.4 to 14.9m during
the study. The sonic anemometer height was raised
from 15 to 21m over the course of the study. The fetch
was 4800m in all directions from the tower. Soil
properties at this site were similar to the ACMF, but
the water table was generally deeper. Further details
about this site, experimental methods and previous flux
measurements are reported in Gholz & Clark (2002) and
Clark et al. (2004).
Meteorological and soil measurements
Photosynthetically active photon flux density (LI-190,
LI-COR Inc., Lincoln, NE, USA), net radiation (Q7,
Radiation and Energy Balance Systems Inc., Seattle,
WA, USA), wind speed and direction (No. 3001-5,
R. M. Young Company, Traverse City, MI, USA), tem-
perature and relative humidity (HMP 23 UT, Vaisala
Inc., Helsinki, Finland), and precipitation (tipping buck-
et, Sierra Misco Inc., Berkeley, CA, USA) were measured
continuously from the top of each site’s tower. At each
site, three soil heat flux plates (HFT-3.1, Radiation and
Energy Balance Systems Inc.) were buried 10cm below
the soil surface in separate locations within 8m of the
tower. All sensors were measured every minute and 30-
min averages were collected on an EasyLogger EL824-
GP data logger (Omnidata International, Ogden, UT,
USA). Water table depth was measured adjacent to each
site’s tower using a Stevens water depth gauge (F-68,
Leupold and Stevens, Beaverton, OR, USA).
Ecological measurements
The following description of the biomass sampling
methods applies to the ACMF. DT biomass was
sampled using similar procedures that are described
in Gholz & Clark (2002) and Clark et al. (2004). Four
inventory plots (50m?50m) were established in ran-
dom directions and distances between 50 and 200m
around the tower (directions constrained to place one
plot in each compass quadrant). Tree density, height,
and stem diameter at breast height (DBH; 1.37m height)
were measured in each plot in February 2000, 2001, and
2002. Allometric equations were used to determine
standing wood, bark, and foliage biomass, and annual
increment for each tissue (Taras & Clark, 1977; Taras &
Phillips, 1978). Coarse root biomass was estimated as
13% of aboveground wood (plus bark) biomass (Gholz
& Fisher, 1982). Litterfall was collected monthly from 10
1m2traps located within the inventory plots, and then
dried for 72h at 701C and separated into needles or
other material. Needle accretion in the canopy for each
year was estimated by applying needlefall from the
following year to a normalized logistic accretion curve,
assuming 18 months for needle turnover (Gholz et al.,
1991; Dougherty et al., 1995; Jokela & Martin, 2000;
Martin & Jokela, 2004). LAI was then calculated from
needlefall and needle accretion estimates.
Ten randomly distributed subplots situated in each of
the four inventory plots were established, and then
measurements of saw palmetto and gallberry – the
two dominant understory species – were applied to
allometric equations to determine their biomass (Gholz
et al., 1999; Powell et al., 2005). Biomass of grass and
herbs was estimated from nine 1m2clip plots located
around the tower at the time of peak biomass in 2000
and 2002. Forest floor mass was sampled in the winter
of 2002 from five 100cm2subplots randomly located
within each inventory plot. Samples were dried for 72h
at 701C and then weighed.
Needle litter decomposition was estimated using a
simulation model for slash pine forest floor dynamics
(Gholz et al., 1985), adjusted to reflect dynamics in
longleaf pine forest. The model consisted of three
coupled ordinary differential equations representing
fresh needle litter, a labile litter fraction, and a lignin
and cutin (refractory) fraction. The measured rate of
fresh needle decomposition (0.15year?1) in slash pine
plantations does not accurately represent decomposi-
tion in longleaf pine-dominated ecosystems; Hendricks
et al. (2002) reported a decomposition rate for longleaf
pine needles on the forest floor surface which was 64%
of the slash pine plantation estimate. Therefore, the
parameters for fresh litter decomposition and transition
rate from fresh to labile compartments were reduced to
0.096 and 0.319year?1to reflect this difference. To
estimate the relative sizes of the three litter pools, the
model was simulated from a starting point of no litter
mass (postfire conditions). The spatial heterogeneity of
the standing litter mass required separate simulation of
each plot. Measured litterfall was used as annual inputs
for the model.
Net CO2exchange
Net ecosystem fluxes of CO2(NEE, mmolCO2m?2s?1),
sensible heat (H, Wm?2), and latent heat (lE, Wm?2)
were measured with a closed-path eddy covariance
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system (Clark et al., 1999; Baldocchi, 2003; Lee et al.,
2004; Powell et al., 2005). Both the ACMF and DT
systems consisted of a three-dimensional sonic anem-
ometer (Windmaster Pro, Gill Instruments Ltd, Lyming-
ton, UK) and an infrared gas analyzer (LI-6262, LI-COR
Inc.) situated in a shed at the base of each tower. Raw
data were logged at 10Hz. The anemometer was situ-
ated at 32m (10m above mean canopy height) and 15–
21m (4m above mean canopy height) at the ACMF and
DT, respectively. Gas was sampled 10cm from the
center of the anemometer head at both sites and drawn
through an IRGA at a flow rate of 6.0Lmin?1. The
sampling tubes (4mm ID, Teflon coated) were 35m
long at both sites. The LI-6262s were calibrated twice
per week using a traceable ( ? 1%) standard for CO2
and a dew point generator (LI-COR 610, LI-COR Inc.)
for water vapor.
A 3m mobile tower with an identical eddy covariance
system was erected to measure understory fluxes be-
tween November 2000 and May 2002 in ACMF. We
assumed that net ecosystem fluxes transferred across a
horizontal plane existing between the bottom of the
canopy and the understory (Baldocchi & Vogel, 1996;
Powell et al., 2005). The understory tower was moved
between three fixed locations within the footprint of the
ACMF canopy tower to dampen localized effects of
understory heterogeneity. No systematic patterns of
variation among the three locations were observed,
and thus all data were pooled.
Flux calculation software was used to rotate the
horizontal wind velocities to obtain turbulence statistics
perpendicular to the local streamline using Reynolds
detrending (200s constant). Net fluxes were calculated
in half-hour intervals, and then collectively corrected
for attenuation of the gas concentrations in the sam-
pling tube, the nonideal frequency response of the
LI-6262, and sensor separation loss using transfer func-
tions (Moncrieff et al., 1997). Hourly barometric pres-
sure measured at the Gainesville Regional Airport,
10km southwest of the tower, was used to correct fluxes
to ambient atmospheric pressure. The rate of change of
CO2 stored within the air column below the eddy
covariance system was used to estimate the CO2storage
flux (Hollinger et al., 1994; Clark et al., 2004). We used
the meteorological convention that positive NEE indi-
cated net movement of CO2to the atmosphere from the
ecosystem.
We validated our flux-processing methods by com-
puting fluxes from the Ameriflux gold files. Processed
data were screened following a protocol described in
Powell et al. (2005). In total, canopy fluxes were mea-
sured ?70% of the time, and about a third of these data
were removed using the screening process. There was
no apparent seasonal bias in the distribution of screened
data. We used the ‘daily-differencing’ approach devel-
oped by Hollinger & Richardson (2005) to estimate
random measurement error in NEE. This approach
compares flux measurements taken on successive days
at the same time of day under ‘equivalent’ environ-
mental conditions, defined as mean half-hourly PPFD
within 75mmolm?2s?1, air temperature within 31C,
and wind speed within 1ms?1. This approach assumes
that under these constraints, environmental and phy-
siological drivers should be similar, meaning that any
difference in flux can be attributed to random error. The
inferred random measurement error, d, was then calcu-
lated as ðx1? x2Þ=
measurements meeting the conditions described above.
As has been reported for other sites (Hollinger &
Richardson, 2005; Richardson et al., 2006), we found
that the distribution of d was better described by a
double-exponential distribution than a Gaussian distri-
bution. Accordingly, we used the unbiased estimator of
the standard deviation of d for the double-exponential
distribution:

ffiffiffi
2
p
where x1and x2are the paired
sðdÞ ¼
ffiffiffi
2
p
X
N
i¼1
di??d
????=N
!
;
ð1Þ
where?d is the median d. Statistics for the distributions
of d were calculated for various stratifications of the
datasets (i.e. all data, night-time, daytime, PPFD ?
1000, growing season, and non-growing season). It
should be noted that we estimated d of NEE rather
than d of FCO2, in contrast to Hollinger & Richardson
(2005) and Richardson et al. (2006), and so our in-
ferred random error includes the calculation of stor-
age flux in addition to the measurement and calcula-
tion errors associated with the eddy covariance flux
term.
Here, we report the dynamic relationships between
NEE and environmental parameters measured at the
ACMF. A similar analysis for the DTis reported in Clark
et al. (2004). To evaluate controls over daytime net
ecosystem CO2exchange (NEEday), we used a nonrec-
tangular hyperbola to quantify the relationship between
PPFD and NEEday(Ruimy et al., 1995):
NEEday¼
ðaPPFDFsatÞ
ðaPPFD þ FsatÞþ Rd;
ð2Þ
where a (mmolCO2mmolphoton?1) is the apparent
quantum yield (dFc/dPPFD
(mmolCO2m?2s?1) is the net CO2 exchange at light
saturation, and Rd(mmolCO2m?2s?1) is dark ecosys-
tem respiration (NEE at PPFD50). The residuals from
Eqn (2) were regressed against vapor pressure deficit
(VPD) and Tato quantify both when and the magnitude
they regulate NEEday. Water use efficiency (WUE) was
atPPFD50),
Fsat
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used to examine stomatal dynamics in response to the
environment, and was defined using (Katul et al., 2000):
WUE ¼GPP
Et
¼ ZCa
1 ? Ci=Ca
VPD
??
;
ð3Þ
where GPP is mean half-hourly gross primary produc-
tion (mmolCO2m?2s?1), Et is half hourly evapotran-
spiration (mm), Z is the diffusivity ratio of CO2to H2O
gas through air (51.6), Ca is the concentration of
ambient atmospheric CO2(mmolmol?1), Ciis the con-
centration of intercellular CO2 (mmolmol?1). Et was
calculated from direct measurements of lE. GPP was
estimated as the sum of NEEdayand daytime respira-
tion calculated from Eqn (4) below. Only direct mea-
surements between 11:00 and 15:00 hours and when
PPFD exceeded 500mmolm?2s?1were used for the
residual and WUE analyses.
The sensitivity of night-time net ecosystem CO2ex-
change (NEEnight) to temperature was evaluated using
an exponential relationship (Lloyd & Taylor, 1994):
NEEnight¼ aebTa;
ð4Þ
where a and b are the regression coefficients, and Ta(1C)
is mean half-hourly air temperature. The relationships
between the different environmental variables and NEE
were established using either SAS 9.1 (SAS Institute Inc.,
Cary, NC, USA) or SIGMAPLOT 8.0 Regression Wizard
software (SPSS Inc., Chicago, IL, USA).
To estimate net ecosystem production of C (NEP)
over time steps greater than 30min, missing values of
NEEdayand NEEnightwere modeled using half-hourly
measurements of either PPFD or Taand monthly para-
meters fitted to Eqns (2) or (4), respectively (Falge et al.,
2001). For gap-filled ecosystem C production, we used
the convention NEP5(?NEE) and GEP5NEP?Re,
where GEP is the gross ecosystem production and Re
is the ecosystem respiration.
To quantify the extent to which gaps in the datasets
introduced bias or error in our annual sums, we created
50 datasets with 10% of the data removed in artificial
gaps for ACMF for 2005. The gaps were created as in
Moffat et al. (2007), with 10 scenarios each consisting of
very short gaps (isolated half-hours), short gaps (eight
consecutive half-hours), medium gaps (64 consecutive
half-hours), long gaps (12 consecutive days), and mixed
scenarios containing a combination of the preceding
scenarios. We then calculated NEP for each dataset
using the procedures outlined above, and compared
the distribution of annual NEP sums for the datasets
with artificial gaps with the NEP calculated on the
original dataset.
Results
Meteorological data
Environmental variables measured at the ACMF during
the study period are shown in Fig. 1. The sum of
precipitation for each measurement year is also reported
in Table 5. Long-term (1971–2000) mean annual precipi-
tation in the vicinity was 1228mm, and mean maximum
and minimum temperatures for the months of January
and July were 19.0 and 5.81C, and 32.7 and 21.61C,
respectively (Fig. 1a; NCDC, 2002). During the study, the
general climatic pattern was dry mild winters (Novem-
ber–March), warm dry springs, (April and May), and
warm humid summers (June–October). However, there
was a great deal of variation within this pattern. More-
over, three major environmental anomalies occurred
during this study. The first was a severe ‘100-year
drought’ that was in progress at the commencement of
the study and was not alleviated until the summer of
2002. A water table depth below 2m at both the ACMF
and DT was common from June 2000 to July 2002 and
reflected the severity of the drought (Fig. 1b). The water
table was generally near or at the surface for both
ecosystems during 2004 and 2005 when precipitation
was higher. The second anomaly was the winter be-
tween 2000 and 2001, when 32 days had minimum
temperatures below 01C – 16 more freeze days than
the long-term average (NCDC, 2002). The third anomaly
was that three tropical storms hit the sites in August and
September 2004. Heavy rain from these storms left both
sites inundated in September and October, and high
winds impacted tree canopy leaf area.
Ecological measurements
In January 2001, aboveground standing biomass was
estimated as 5911gCm?2and belowground biomass as
721gCm?2(Table 1). In December 2002, total forest
floor biomass was estimated as 1452gCm?2. Annual
increment for trees, understory, litterfall, and forest
floor was 136 and 77gCm?2yr?1for 2000 and 2001,
respectively (Table 1).
During the 2 years with average precipitation (i.e.
2004 and 2005), one large pulse of needlefall occurred in
the fall (Fig. 1e). In contrast, the drought caused the
canopy to adjust by prematurely dropping 50% of
annual needlefall in May and June of 2000 to 2002
(Fig. 1e). The unusually high pulse of needlefall in
September 2004 was caused by high winds from the
tropical storms. LAI was seasonal and the effects of the
premature needle fall and high winds are reflected in
the maximum summertime values in 2000, 2001, and
2005 (Fig. 1f). In comparison, DT LAI was approxi-
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mately 30% greater than ACMF LAI during the drought
years and very similar in 2004 before the wind damage
(Fig. 1f). The drought appeared to have less of an effect
on summertime LAI in the DT, while the tropical force
winds also reduced LAI.
Measurement error
Similar to other estimates of eddy covariance C flux
measurement error (Richardson et al., 2006, 2008), the
distribution of NEE random measurement error (d) in
this study was better described by a double-exponential
distribution than by a normal distribution (Fig. 2). The
distributions of d were similar between ACMF and DT,
with approximately equivalent medians, standard de-
viations, and skewness between the sites (Table 2).
Kurtosis for DT was higher than for ACMF, however,
meaning DT d clustered nearer the median and had
slightly lower density in the tails than did ACMF (Fig.
2). Random error tended to be lower at night than
Mar
Jun
2000
Sep
Dec
MarMar Mar Mar
2002
Jun
2001
Sep Sep Sep
Dec
Jun
LAI
3.0
3.5
4.0
4.5
5.0
5.5
6.0
6.5
7.0
ACMF
DT
Dec
Jun
2004
Dec
Jun
2005
Dec
Needlefall
(g C m–2 month –1)
20
40
60
Ta (°C)
0
10
20
30
VPD (kPa)
0.5
1.0
1.5
2.0
2.5
Water table
(depth m)
–3
–2
–1
0
SWC (% vol.)
0.04
0.06
0.08
0.10
0.12
0.14
WT ACMF
WT DT
SWC ACMF
Precip.
(mm)
50
100
150
200
400
450
Measured
LT mean
(a)
(b)
(c)
(d)
(e)
(f)
Fig. 1
long-term mean monthly precipitation from 1971 to 2000 (line; NCDC, 2002). (b) Monthly mean soil water content (SWC) at 10cm depth
and depth to the water table (WT). Donaldson Tract (DT) data are also shown. SWC was not available in 2004 and 2005. Flat line indicates
that WTexceeded maximum sensor depth. (c) Monthly mean maximum (closed circles) and monthly mean minimum (open circles) air
temperature (Ta). (d) Weekly mean afternoon (12:00–14:00 hours) vapor pressure deficit (VPD). (e) Monthly estimates of needlefall
(mean ? SE). (f) Monthly estimates of all-sided, canopy, leaf area index (LAI).
Environmental and foliage variables measured at the Austin Cary Memorial Forest (ACMF). (a) Monthly precipitation (bars) and
2528 T. L . P O W E L L et al.
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during the day, especially at DT, and error was highest
at higher radiation levels at both sites (Table 2). Grow-
ing season (March–October) error was slightly higher
than during the winter (November–February) for both
sites.
Net CO2exchange
The ACMF was photosynthetically active during all
parts of the year (Fig. 3). Light response curve para-
meters for selected months of 2001 and 2005, two
hydrologically contrasting years, are given in Table 3.
The drought and the seasonality of LAI and soil moist-
ure cause little change in the magnitude of maximum
NEEday (i.e. the dotted lines that mark the lower
boundary of points in Fig. 3) during the growing season
(March–October). For example, maximum NEEday
reached approximately ?16 to ?18mmolCO2m?2s?1
from May to October when soil moisture and LAI were
highly variable in both 2001 and 2005.
The wide scatter of data points within the light re-
sponse curves indicated that there were important sec-
ondary controls regulating NEEday, particularly during
more droughty months, such as May and July 2001 – two
months with relatively low R2values (Table 3). There-
fore, the midday (11:00–15:00 hours) residuals of each
monthly light response regression (NEEres) were plotted
against VPD and Tato elucidate when these two vari-
ables became important constraints on NEEday(Fig. 4).
These relationships were not affected by differences in
soil moisture or season (data not shown) and therefore
the data were pooled over each year. The ACMF reached
optimum C uptake near VPD51.0kPa, after which C
uptake declined linearly as VPD increased (Fig. 4a).
Interestingly, the function of this relationship was not
alteredby drought. Air temperature below 101C severely
reduced net C uptake (Fig. 4b), whereas the temperature
range of 10–301C had a little effect on NEEdayand above
301C caused net C uptake to decline somewhat.
At ACMF, WUE declined linearly with increasing
VPD, and was approximately constant at VPD41.5kPa;
this relationship was similar in both droughty 2001 and
wet 2005 (Fig. 5a). In contrast, the relationship between
WUE and VPD at DT varied between wet and dry years
(Fig. 5b). In 2005, the relationship at DT was similar to
that at ACMF, but in 2001, the relationship was more
complex, showing an increase in WUE at VPD above
2.5kPa.
Meannightly(22:00–4:00
NEEnight, was a significant function of mean night-time
Ta during well-coupled (u?> 0:2ms?1) conditions
(Table 4). Although SWC was highly variable over the
year in this ecosystem, the addition of a SWC function
to Eqn (4) was not statistically significant. However,
separating the data into two different SWC groups
(o5.5% and 45.5%) produced two significant func-
tions, the former showing a 33% reduction in respira-
hours)Cexchange,
Table 1
growth increment
Austin Cary Memorial Forest distribution of C and
C poolBiomass Biomass increment
Trees
Stem and branch
(includes bark)
Foliage
Coarse roots*
Understory
Serenoa repens
Ilex glabra
Grasses and herbs
Forest floorw
Total
2001
5543 ? 273
2000
110 ? 25
2001
59 ? 7
2 ? o0
8 ? 1
18 ? 15
244 ? 16
721
4 ? 1
14 ? 3
18 ? 15
66 ? 12
48 ? 7
10 ? 6
1452 ? 106
8084
?10 ? 12
136
?10 ? 12
77
*Coarse roots were estimated as 13% of stem and branches
(Gholz & Fisher, 1982).
wEstimated from 2002 forest floor census. Litterfall was incor-
porated into the forest floor calculation. Litterfall for year
15161 ? 10gCm?2and for year 25175 ? 13gCm?2.
Units are in gCm?2? SE.
Density
0.00
0.35
0.05
0.10
0.15
0.20
0.25
0.30
0.35
(a)
NEE random error
(µmol CO2 m–2 s–1)
–20 –15 –10 –505101520
Density
0.00
0.05
0.10
0.15
0.20
0.25
0.30
(b)
Fig. 2
ecosystem exchange (NEE) measurement error d and fitted PDF
double-exponential functions for (a) Austin Cary Memorial
Forest and (b) Donaldson Tract.
Histograms showing the distribution of the random net
C A R B O N E X C H A N G E O F A NAT U R A L LY R EG E N E R AT E D P I N E F O R E S T
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tion rates at 251C (Table 4, Fig. 6). It should be noted
that values for b (Table 4), which indicate how sensitive
respiration was to changes in temperature, were sig-
nificantly different (P50.001), while a values were
not significantly different (P50.557) for these two
conditions (determined statistically with an indicator
variable; Powell et al., 2005). When SWC was 45.5%,
mean NEEnight was 6.8mmolCO2m?2s?1
at 251C,
Table 2
regenerated Austin Cary Memorial Forest and the Donaldson Tract intensively managed pine plantation site for the time periods
July 2000–June 2002, 2004, and 2005
Statistical properties of the inferred random net ecosystem exchange measurement error, d, for the mature, naturally
Conditions
Austin Cary Memorial ForestDonaldson Tract
n
MedianSDSkewnessKurtosis
n
Median SDSkewness Kurtosis
All data
Day
Night
PPFD ? 1000
Growing season (March–October)
Winter (November–January)
8059
2254
5805
610
5658
2401
0.02
0.08
0.00
0.02
0.03
?0.03
2.6
2.9
2.5
3.2
2.7
2.5
?0.3
?0.5
?0.2
?0.2
?0.5
0.2
7.3
7.5
6.8
7.1
7.4
6.3
3650
1987
1663
715
2501
1149
0.03
0.06
0.02
0.33
0.08
?0.01
2.6
3.3
1.8
3.7
2.8
2.3
?0.8
?0.9
0.8
?0.3
?0.7
?1.1
14.3
10.2
11.9
5.4
12.3
21.3
Error calculated with the daily differencing approach as d ¼ ðx1? x2Þ=
equivalent environmental conditions 24h apart in time.
ffiffiffi
2
p
, where x1and x2are flux measurements taken under
January 2001
NEEday (µmol CO2 m–2 s–1)
–20
–10
0
10
May 2001July 2001
January 2005
–20
–10
0
10
May 2005
PPFD (µmol m–2 s–1)
July 2005October 2005
October 2001
Fig. 3
warm and dry, July and October: warm and humid. The dotted lines are a visual aid for comparative purposes to mark the bottom
boundary of daytime net ecosystem CO2exchange (NEEday). Regression parameters and statistics for each month are given in Table 3.
Light response curves for seasonally representative months in 2001 (dry year) and 2005 (wet year). January: cool and dry, May:
Table 3
year) and 2005 (wet year) for Austin Cary Memorial Forest
Model parameters and statistics of light response curves [Eqn (2)] for seasonally representative months during 2001 (dry
Month
Model parametersStatistics
Fsat
a
Rd
R2
n
January 2001
May 2001
July 2001
October 2001
January 2005
May 2005
July 2005
October 2005
?17.6 ? 1.7
?14.4 ? 0.9
?18.5 ? 1.1
?21.5 ? 0.6
?7.2 ? 0.7
?25.0 ? 2.0
?23.6 ? 1.5
?21.1 ? 1.5
?0.030 ? 0.010
?0.037 ? 0.012
?0.040 ? 0.011
?0.047 ? 0.004
?0.021 ? 0.007
?0.022 ? 0.003
?0.031 ? 0.010
?0.037 ? 0.008
4.7 ? 1.0
4.4 ? 1.1
6.0 ? 1.1
5.1 ? 0.3
1.7 ? 0.5
4.7 ? 0.5
4.9 ? 0.7
3.4 ? 0.7
0.43
0.32
0.47
0.78
0.29
0.67
0.74
0.63
380
594
354
636
375
465
243
269
January: cool and dry, May: warm and dry, July and October: warm and humid.
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while under dry conditions, (SWCo5.5%) it was
4.6mmolCO2m?2s?1at 251C. Q10for moist soil condi-
tions was 2.0; while under dry conditions, Q10 was
reduced to 1.4.
An ordinary least squares regression analysis showed
that over all times of the day, understory net ecosystem
C exchange, NEEu, was linearly related to above-
canopy NEE and accounted for approximately 37% of
total ecosystem C fluxes (Fig. 7). This relationship was
insensitive to changes in above-canopy VPD and soil
moisture. It should be noted that random error asso-
ciated with measurements of the independent variable,
NEE, violates error assumptions of an ordinary least
squares regression. Therefore, we also calculated the
half-hourly ratio of NEEuto NEE and then examined
the distribution of this ratio for 24-h, midday, and night-
time periods. Median values of this ratio were 0.28 for
24-h period, 0.27 for midday, and 0.85 for night. Season
did not have any apparent effect on these ratios. The
frequency distribution of NEEu:NEE during both the
night and midday was not normally distributed (Fig. 7b
VPD (kPa)
0.00.51.01.52.02.53.03.5
NEEres
–2
–1
0
1
2
3
4
5
2001
2005
(a)
Ta (°C)
05 10152025 3035
NEEres
–2
0
2
4
6
8
10
(b)
Fig. 4
(NEEday) at photosynthetic photon flux density (PPFD) (NEEres,
mmolCO2m?2s?1) as a function of vapor pressure deficit (VPD,
kPa) for 2001 (dry year) and 2005 (wet year). (b) NEEresas a
function of above-canopy air temperature (Ta, 1C) for July 2000–
June 2001, a period that contains 32 days with below-freezing
temperatures. NEEresare for the hours between 11:00 and 15:00
hours; mean ? 1 SE.
(a) Residuals of daytime net ecosystem CO2exchange
ACMF
WUE
(g C m–2 mm–1 H2O)
0
8
2
4
6
8
2001
2005
DT
VPD (kPa)
0.5 1.01.52.0 2.5 3.03.5
WUE
(g C m–2 mm–1 H2O)
0
2
4
6
Fig. 5
pressure deficit (VPD, kPa) for (a) Austin Cary Memorial Forest
(ACMF) and (b) Donaldson Tract (DT) during 2001 (dry year)
and 2005 (wet year). WUE values are from 11:00 to 15:00 hours
and photosynthetic photon flux density 4500mmolm?2s?1;
mean ? 1 SE.
Water use efficiency (WUE) as a function of vapor
Table 4
temperature [Eqn (4)] for Austin Cary Memorial Forest data collected between July 2000 and May 2002 for dry vs. wet soil conditions
Model parameters, statistics and Q10values for the relationship between night-time net exchange of CO2(NEEnight) and air
Model parameters*
Statistics
abR2
nP-value
Q10
Wet soil SWC45.5%
Dry soil SWCo5.5%
1.10 ? 0.09
1.85 ? 0.40
0.070 ? 0.004
0.036 ? 0.011
0.50
0.22
394
49
o 0.001
0.001
2.0
1.4
*In a dummy analysis, a parameters were not significantly different (P50.557), while the b parameters were significantly different
(P50.001).
C A R B O N E X C H A N G E O F A NAT U R A L LY R EG E N E R AT E D P I N E F O R E S T
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and c; Shapiro–Wilke, Po0.05). The night-time fre-
quency distribution was broadly centered around the
median value with 66% falling within the range of
0.65–1.08 (skewness of 0.66 and kurtosis of 2.0). In
contrast,
strongly centered around the median value with 66%
falling within the range of 0.22–0.31 (skewness of 0.43
and kurtosis of 28.8).
ACMF NEP was remarkably similar (range: 154–
192gCm?2yr?1) among the four measurement years
of this study regardless of the considerable differences
in precipitation (Table 5). The seasonality of C assimila-
tion in the ACMF was also similar among the 4 years,
with the greatest monthly C sequestration occurring in
the early spring and then being nearly C neutral from
late summer through the winter (Fig. 8a). April almost
universally experienced the highest NEP each year (Fig.
8b). In comparison, NEP for DTwas three to four times
greater than that of the ACMF for each simultaneous
measurement year (Table 5). DT seasonal NEP patterns
also contrasted ACMF in that DT generally experienced
high rates of C uptake during all parts of the year
(Fig. 8a).
The gap-filling analysis indicated that there was no
major error or bias introduced by the distribution of
gaps in our dataset. The annual NEP sum for the
original, complete 2005 dataset was 154gCm?2yr?1.
By comparison, NEP sums for the 50 gap-filling scenar-
themidday frequency distribution was
Mean Ta (°C)
05101520 25
Mean NEEnight (µmol m–2 s–1)
0
2
4
6
8
10
12
SWC > 5.5%
SWC < 5.5%
Fig. 6
dioxide above the slash pine canopy as a function of mean
nightly air temperature (Ta) under well-coupled conditions
(u40.2). Gray regression line represents nights when soil water
content (SWC)45.5% and black regression line represents nights
when SWCo5.5%. Regression parameters and statistics are
given in Table 4.
Mean nightly (22:00–4:00 hours) exchange of carbon
Canopy NEE
(µmol CO2 m–2 s–1)
–20–10010
Understory NEE
(µmol CO2 m–2 s–1)
–20
–10
0
10
y = 0.37x +16
R = 0.55
n = 5115
1:1
0
100
10
20
30
NEEu:NEE in 0.02 bins
–0.50.0 0.51.01.52.0
Frequency
0
20
40
60
80
(a)
(b)
(c)
Fig. 7
regression of all half-hourly data pooled over 24h. Histograms of NEEu:NEE for (b) night-time (22:00–4:00 hours), median50.85 and
(c) midday (11:00–15:00 hours), median50.27.
Proportion of total net ecosystem exchange (NEE) accounted for by understory net ecosystem exchange (NEEu). (a) Linear
Table 5
Carbon budget components for each year
12-month
period
Annual precipitation
(mm)
NEPGEP
Re
Re:GEP
ACMFDT ACMFDTACMFDT ACMFDT
2000–2001
2001–2002
2004
2005
956
812
1373
1185
192
159
185
154
616
660
729
490
1794
1871
1568
1785
2423
2687
2348
2248
?1602
?1715
?1383
?1631
?1807
?2026
?1619
?1758
?0.89
?0.92
?0.88
?0.91
?0.75
?0.75
?0.69
?0.78
ACMF: Austin Cary Memorial Forest, mature, naturally regenerated pine forest.
DT: Donaldson Tract, intensively managed, 10–15-year-old pine plantation.
Each year either represents a calendar year or the 12-month period of July to June the following year. Values are reported as
gCm?2yr?1.
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ios ranged from 135 to 170gCm?2yr?1, with a mean
sum of 154gCm?2yr?1and standard deviation of
7gCm?2yr?1. The distribution of NEP sums was nor-
mal (Shapiro–Wilke, P50.6818), with skewness of 0.25
and kurtosis of 0.09.
Annual Reand GEP are given for both forests in Table
5. The tropical storms in 2004 caused a reduction in Re
and GEP in both ecosystems. Interestingly, the compen-
satory reduction of these fluxes resulted in very little
difference in NEP with respect to the other years. In the
ACMF, Re and GEP had an asynchronous seasonal
pattern where GEP generally outpaced Rein the spring
and early summer (Fig. 8c), which helps to explain why
C gain was greatest during this period. The asynchro-
nous pattern was also present in DT, but it was con-
siderably less pronounced (Fig. 8c).
Discussion
Error analyses
Recent studies have reported the distribution of random
flux errors at diverse flux sites (Hollinger & Richardson,
2005; Richardson et al., 2006, 2008). The s(d) reported for
forested sites in these studies ranged from 2.4 to 4.3;
both ACMF and Donaldson Tract s(d) was 2.6. Most
sites also report higher s(d) under high radiation con-
ditions compared with that under low radiation, and
during the growing season vs. winter, as we also
observed in our data (Table 2). These patterns are
consistent with a scaling of random error with flux
magnitude, with d being lowest near fluxes of 0.0, and
increasing as fluxes become more negative or more
positive (Richardson et al., 2006).
Equations (2) and (4) have been demonstrated to
perform well as gap-filling models for a wide range of
forests (Falge et al., 2001; Moffat et al., 2007). In our case,
the gap analysis for 2005 data established uncertainty
boundaries within 12% for annual NEP and indicated
that no major bias was introduced by the distribution of
gaps. Therefore, we assumed that estimates of annual
NEP for the other measurement years likely have a gap-
filling error similar in magnitude.
Net CO2exchange
NEEday was a strong curvilinear function of PPFD
throughout each year due to the relatively mild winters
NEP cummulative
(g C m–2)
0
100
200
300
400
500
600
700
Monthly NEP
(g C m–2 month–1)
–40
–20
0
20
40
60
80
100
120
May Sep Jan May Sep Jan
2000
JanMayMay Sep
2004
JanMay Sep
2005
Jan
Monthly carbon flux
(g C m–2 month–1)
–500
–400
–300
–200
–100
0
100
200
300
400
500
20012002
(a)
(b)
(c)
Fig. 8
Donaldson Tract (DT; dashed). (b) Monthly NEP for the ACMF (black) and DT (white). (c) Seasonality of total monthly gross ecosystem
production (GEP; positive values) and ecosystem respiration (Re, negative values) for the ACMF (black) and DT (white).
(a) Cumulative net ecosystem production (NEP) over the study period for the Austin Cary Memorial Forest (ACMF; solid) and
C A R B O N E X C H A N G E O F A NAT U R A L LY R EG E N E R AT E D P I N E F O R E S T
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and year-round physiological activity of pines in
northern Florida (Martin, 2000; McGarvey et al., 2004).
The magnitude of maximum summertime NEEdayof the
ACMF (?16 to ?18mmolCO2m?2s?1, dotted lines in
Fig. 3) was
?10mmolCO2m?2s?1
adjacentDTplantation (Clark
? 5mmolCO2m?2s?1lower than an adjacent rotation-
aged plantation (Clark et al., 1999). The less negative
NEEdayof the older ACMF stand likely was a result of
higher maintenance respiration rates relative to net cano-
py assimilation and lower ecosystem LAI and stocking
density relative to the plantations (Clark et al., 1999).
However, ACMF maximum NEEdaywas similar to the
global value (ca. ?18.0mmolCO2m?2s?1) reported for a
wide range of temperate coniferous forests (Ruimy et al.,
1995; Falge et al., 2002).
On a half-hourly time scale, PPFD was the dominant
control over NEEdayexplaining 30–80% of its variation.
However, there were important secondary controls
when both ACMF and DT were under water stress.
AfterVPDexceeded2.0kPa,
NEEday in the ACMF decreased by as much as
5mmolCO2m?2s?1. We have previously observed sto-
matal closure at VPD of 1.5–2.0kPa across a range of
soil water contents which is consistent with this pattern
(Powell et al., 2005). A similar type of analysis con-
ducted for DT also showed a decrease in mean NEEday
of 5mmolCO2m?2s?1at PPFD of 1500mmolm?2s?1
when VPD exceeded 2.0kPa for both drought and
nondrought conditions (Clark et al., 2004). These results
agree with findings of an old-growth Ponderosa pine
forest in Oregon, which also experiences periods of
extreme water stress and high VPD, where NEEday
became increasingly suppressed with increasing VPD
(Anthoni et al., 2002).
There was an important contrast in how the ACMF
and plantations responded to the severe drought.
Althoughtherelativereduction
5mmolCO2m?2s?1) was the same for both ecosystems
during periods of high VPD, there was also a reduction
in maximum NEEdayduring drought compared with
nondrought periods at DT (e.g. Fig. 2 in Clark et al.,
2004). Maximum NEEdayat the ACMF, however, was
similar between drought periods in 2001 compared
with 2005 (e.g. dotted lines for My01 and Jy01 com-
pared with My05 and Jy05 in Fig. 3); these contrasting
responses were also reflected in differing patterns of
WUE response to VPD in the two stands in dry and wet
years (Fig. 5).
Residuals plotted against air temperature showed a
broad optimum between 10 and 301C. This response
can be explained by integrating the temperature re-
sponses of photosynthesis and ecosystem respiration.
At the leaf level, Teskey et al. (1994) showed that slash
lower than the
al.,2004)
et
and
themagnitudeof
inNEEday
(i.e.
pine net photosynthesis responded linearly and posi-
tively to temperature across a range of air temperature
from 10 to 351C. We see similar responses in GPP, the
sum of ecosystem photosynthesis. At a half-hourly time
scale in this study, GPP declined linearly with air
temperature (GPP50.72–0.44Ta, n518186, R250.23,
where GPP is the gross primary production in
mmolCO2m?2s?1and Tais the air temperature in 1C).
When this linear response is combined with the weakly
nonlinear response of NEEnightto temperature over the
range of 10–251C (Fig. 5b), the result is a broad tem-
perature optimum for NEEres.
In coniferous forests, global values for Fsat and a
are ?32.4mmolCO2m?2s?1and ?0.024mmolCO2mmol
photon?1, respectively (Ruimy et al., 1995). Although
seasonality was weak in this ecosystem, Fsatwas great-
est in magnitude during growing season months when
precipitation was not limiting (i.e. October 2001 and
May–October 2005; Table 3) and similar to values re-
portedfortheadjacent
(?26.5molCO2m?2s?1; Clark et al., 1999). The variation
in ACMF’s quantum efficiency (?0.021 to ?0.047) was
less than the range reported for adjacent pine planta-
tions [?0.025 to ?0.075 (excluding clearcut values);
Clark et al., 2004] and similar to that reported for a
mixed-temperate maritime forest (?0.029 to ?0.044;
Aubinet et al., 2001) and a Scots pine forest (?0.011 to
?0.047; Zha et al., 2004).
There was a statistical difference in the sensitivity of
NEEnight to Ta when SWC of 5.5% was used as a
threshold for dividing between wet and dry conditions
(Table 4, Fig. 5). However, there is probably not any
biological significance of this SWC value alone. This
relationship more likely operates along a nonlinear soil
moisture continuum as has been found in other studies
(Reichstein et al., 2002). Unfortunately, our soil moisture
sensor was damaged for 2004 and 2005, and thus our
relatively small number of data points precluded us
from further partitioning the data to better define this
relationship for the ACMF. Under wet soil conditions,
summertime NEEnightat this site (6.8mmolCO2m?2s?1
at 251C) was similar to DT and rotation-aged (24-year-
old) pine plantation NEEnight (range: 6.4–6.7mmol
CO2m?2s?1at 251C; Clark et al., 1999, 2004). Similarly,
under dry soil conditions (SWCo5.5% in the present
study), summertime NEEnight (4.6mmolCO2m?2s?1)
was similar to that of DT (Clark et al., 2004).
rotation-agedplantation
Understory C fluxes
Night-time measurements of understory fluxes have
been found to be less reliable than daytime fluxes in
open canopy forests due to a build up of a strong
inversion layer (Misson et al., 2007). To overcome this
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problem, understory data were screened using the same
u?threshold as the canopy (0.2ms?1) to ensure turbu-
lent conditions. Nevertheless, the broader frequency
distribution of night-time NEEu:NEE and large number
of values greater than 1 (Fig. 7b) was evidence that the
canopy and understory were not always well coupled
even after the u?filter was applied.
During the summertime, midday NEEuat the ACMF
accounted for 27% of NEE, which was on the higher end
of values reported by Misson et al. (2007) for a broad
range of evergreen and deciduous forests (range: ?54%
to 36%, negative indicates that respiration dominates).
During the summertime, night-time NEEucomprised
85% of NEE, which was also on the upper end of values
reported for other pine forests (range: 35–65%; Misson
et al., 2007). The proportion of 24-h mean half-hour NEE
attributed to understory fluxes in the current study
(?25–35%; Fig. 6) was a bit higher than the estimate
of 21% for a 23-year-old pine flatwoods plantation
simulated by Golkin & Ewel (1984). Periodic ceptometer
measurements indicated that 30–60% of incident PPFD
penetrated the canopy of this stand (data not shown),
suggesting that understory CO2assimilation capacity
was relatively high. In contrast, only 18–42% of incident
PPFD penetrates the canopy in adjacent pine planta-
tions (Gholz et al., 1991), indicating that the CO2assim-
ilation capacity of plantation understories is lower. Our
results were similar to those of a boreal pine forest with
a similar understory radiation environment, which ac-
counted for 20–30% of NEE (Baldocchi & Vogel, 1996).
However, our results do not support the hypothesis that
NEEuwould become a greater part of NEE as stresses
imposed by VPD and SWC increased, as has been found
in other studies of coniferous forests (e.g. Black &
Kelliher, 1989). Rather, the relationship between NEE
and NEEuwas insensitive to changes in above-canopy
VPD and soil moisture. This may be the result of the
more open canopy resulting in the understory being
subjected to similar stresses as the canopy trees.
Annual ecosystem C balance and partitioning
Annual NEP based on eddy covariance was greater
than mensurational measurements in our study by 56
and 82gCm?2yr?1for 2000–2001 and 2001–2002, re-
spectively. The differences may be accounted for by
unmeasured C translocation to coarse root carbohy-
drate storage pools. In addition to eddy covariance
measurement errors, assumptions associated with the
biomass measurements should be considered. First, our
assumption that fine roots and soil organic matter were
in steady state may be invalid. Second, although the
years overlapped for the mensurational and eddy cov-
ariance measurements, they were not the same exact
intervals. Third, designating June as the anniversary for
eddy covariance during the first 2 years separated two
halves of a growing cycle and may be problematic
because labile C storage and use can differ between
years (Sampson et al., 2001).
Spring to early summer appears to be the most
intense period of C accumulation across a range of
ecosystems within the Florida landscape [i.e. natural
and intensively managed pine forests, cypress wetlands
and scrub oak (Fig. 7a; Clark et al., 1999, 2004; Powell
et al., 2006)], keeping in mind that maximum C gain
may be decreased or shift to later in the summer in
extremely dry springs. Nevertheless, this suggests that
the asynchronous patterns of Reand GEP are similar
across species and management practices in this region.
A major contrast between the natural and managed
stands was that the ACMF was essentially C neutral
from late summer until the following spring (Fig. 8a),
while the plantations were strong C sinks throughout
the year (Figs 8a and 6a in Clark et al., 2004).
Global climate change is expected to manifest in this
region with increased tropical storm activity and more
dramatic swings between very dry and very wet con-
ditions (Twilley et al., 2001). Until this study, it was
poorly understood how mature, less intensively mana-
ged pine flatwoods would respond to future weather
scenarios. Our results demonstrate that both photo-
synthesis and respiration will be affected in different
ways. For example, water stress caused both premature
needlefall (Fig. 1e) and stomatal closure (Fig. 5), which
resulted in reduced canopy photosynthesis (i.e. Fsatin
Table 3). At the same time, soil respiration was reduced
by dry soil conditions and presumably reduced sub-
strate as a result of lowered photosynthesis (Hogberg
et al., 2001; Bhupinderpal-Singh et al., 2003; Johnsen
et al., 2007). Or in terms of the hurricane, GEP was
reduced by needle loss, while Rewas thought to be
reduced by anoxic conditions in the inundated soils
coupled with a reduction in substrate due to needle
loss. The compensatory effect of both reduced GEP and
Rein the face of either drought or tropical storms results
in NEP values that are very similar to ‘average’ years.
Our results are supported by Clark et al. (2004) and
Li et al. (2007) who found similar compensatory effects
of GEP and Reon NEP for a pine plantation exposed to
drought and a Florida scrub-oak exposed to a hurri-
cane, respectively.
The ACMF sequestered ?700gCm?2over the four
measurement years of the study. In comparison, the
highly productive DT pine plantation sequestered
?2500gCm?2over the same 4-year period. Addition-
ally, a nearby rotation-aged slash (24-year-old) pine
plantation and a loblolly pine plantation in the North
Carolina piedmont both had annual NEP estimates of
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Page 14

the same order of magnitude as DT annual NEP
(Clark et al., 1999, 2004; Juang et al., 2006). The lower
Reto GEP ratio for the plantations compared with the
ACMF (Table 5) suggests that the higher GEP in the
plantations was driven by higher LAI and a smaller
fraction of photosynthate allocated to maintenance re-
spiration. After the rotation-aged plantation was har-
vested, a large amount of C was released (e.g. ?1269
and ?882gCm?2yr?1) over the subsequent 2 years
(Clark et al., 2004). These large differences highlight
the importance of stand age and management regime
for stand-level C balance in this region.
Implications of these management regimes on C
sequestration in the long term can be assessed using
simple calculations of cumulative NEP for the ACMF
stand and for a generic slash pine plantation in the
region over a 24-year period, which is a typical planta-
tion rotation length. We used plantation calculations of
NEP for regenerating, mid-rotation, and rotation-aged
stands published by Clark et al. (1999, 2004) and Binford
et al. (2006) that started after the harvest of a previous
stand. Using the average NEP for the ACMF over the 4
years yields 4140gCm?2after 24 years vs. 9900gCm?2
for the plantation. This calculation leaves two important
uncertainties unaddressed. Timber harvesting removes
most of the accumulated C from the plantations at the
end of each rotation, and the fate of harvested C must
be tracked with life cycle analysis (Skog & Nicholson,
1998; Ross & Evans, 2004). For the ACMF stand, peri-
odic prescribed fire will return some proportion of
understory and forest floor C to the atmosphere at each
fire cycle; research on this topic is ongoing at this site.
The dynamics of landscape-level C sequestration is a
function of interactions among environmental condi-
tions, site-specific edaphic characteristics, and land
management (e.g. evergreen pine vs. deciduous cy-
press, age or time since disturbance, soil type and
topography, tree age demographics, season and year;
Gholz et al., 1991; Liu, 1998; Binford et al., 2006).
Intensively managed plantations change from a net C
source to a net C sink as early as 3 years following
harvest (Gholz & Fisher, 1982; Thornton et al., 2002;
Clark et al., 2004), and rapidly develop high rates of C
sequestration (Clark et al., 2004) that are offset by
periodic timber harvesting. These large changes do
not occur in older, less intensively managed pine
stands, such as the ACMF, because canopy cover, stand
structure, and biomass are largely maintained over
time. Therefore, arguably one of the largest uncertain-
ties in forecasting regional C budgets lies with our
ability to predict how present management practices
might change with future ownership. Finally, this study
demonstrated that prolonged severe drought had little
effect on NEP, which highlights that the effects of
projected changes in climate on coastal plain pine forest
NEP are likely to be small relative to those of land use
and management change.
Acknowledgements
This research was supported in part by the Biological and
Environmental Research (BER) Program, U.S. Department of
Energy, through the Southeast Regional Center (SERC) of the
National Institute for Global Environmental Change (NIGEC)
and the National Institute for Climatic Change Research
(NICCR); National Science Foundation award no. 0344029; the
NASA Land Cover and Land Use Change (LCLUC) Program;
the U.S. Department of Agriculture Forest Service; and the
University of Florida School of Forest Resources and Conserva-
tion. This paper was partially based on work supported by the
National Science Foundation while Henry L. Gholz was working
at the Foundation. Any opinion, findings, and conclusions
expressed here are those of the authors and do not necessarily
reflect the views of the Foundation. We thank Dr Jennifer Jacobs,
Ryan Atwood, Jose Luis Hierro, Jennifer Staiger, Antje Moffat,
and Julie Graves for their contributions to this work. We are
grateful to the Associate Editor and two anonymous referees for
their thoughtful and constructive comments.
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