Limnol. Oceanogr., 55(6), 2010, 2645–2659
2010, by the American Society of Limnology and Oceanography, Inc.
doi:10.4319/lo.2010.55.6.2645
E
Characteristics and sources of chromophoric dissolved organic matter in lakes of the
Yungui Plateau, China, differing in trophic state and altitude
Yunlin Zhang,a,*,1 Enlou Zhang,a Yan Yin,a Mark A. van Dijk,b Longqing Feng,c Zhiqiang Shi,a
Mingliang Liu,a and Boqiang Qina
a Taihu
Lake Laboratory Ecosystem Research Station, State Key Laboratory of Lake Science and Environment, Nanjing Institute of
Geography and Limnology, Chinese Academy of Sciences, Nanjing, China
b Netherlands Institute of Ecology (NIOO-KNAW), Department of Microbial Ecology, Nieuwersluis, The Netherlands
c College of Resource and Environment Science, Nanjing Agricultural University, Nanjing, China
Abstract
The high-mountain lakes on the Yungui Plateau in China are exposed to high-intensity ultraviolet radiation, and
contain low concentrations of chromophoric dissolved organic matter (CDOM). We determined CDOM
absorption, fluorescence, composition, and source in 38 lakes on the Yungui Plateau at altitudes of 1516 to
4591 m above sea level. Total nitrogen (TN), total phosphorus (TP), and chlorophyll a (Chl a) concentrations
significantly increased with increasing trophic state, and decreased with altitude. The CDOM absorption coefficient
aCDOM(280) significantly increased with increasing trophic state, but not with altitude. There were significant and
negative correlations between altitude and TN, TP, Chl a concentrations, and aCDOM(280). Parallel factor analysis
identified two humic-like and two protein-like fluorescent components. Humic-like component 1 was terrestrially
derived and positively correlated to CDOM absorption. Component 2 was similar to a marine humic-like substance
originating from biological degradation of phytoplankton. Components 3 and 4 were autochthonous tryptophanlike and tyrosine-like fluorophores. CDOM was, thus, a mixture of material from the catchment and autochthonous
material produced by biota in the lake. CDOM fluorescence characteristics of oligotrophic and mesotrophic lakes
were dominated by the spectral signatures of protein-like components, but marine and terrestrial humic-like
components dominated in eutrophic lakes. The fluorescence indices FI255, FI310, and FI370 were useful tools for
readily defining and classifying CDOM characteristics in the Yungui Plateau lake waters.
Dissolved organic matter (DOM) is mainly composed of
humic substances, carbohydrates, and proteinaceous material, and plays an important role in the global carbon cycle
(Benner 2002). Chromophoric dissolved organic matter
(CDOM) is the colored fraction of DOM with chemical
properties that cause it to absorb energy, and re-emit it as
fluorescence. It originates from in situ microbial decomposition of plant matter and extracellular release by aquatic
organisms (autochthonous [Wang et al. 2007; Zhang et al.
2009]), as well as from partially degraded organic material
from the surrounding terrestrial environment transported by
rivers and groundwater (allochthonous; Murphy et al. 2008).
As an optically active substance, the CDOM concentration
can significantly influence the underwater light field
(Laurion et al. 2000). Furthermore, photo-degradation and
microbial degradation of CDOM result in the emission of
the greenhouse gases CO2 and CH4, accelerating global
warming (Stedmon et al. 2007; Tranvik et al. 2009).
Although the ultraviolet-B (UV-B) radiation-penetration
inhibiting properties and ecological significance of CDOM
have often been reported in plateau and high-mountain
lakes (Sommaruga and Psenner 1997; Laurion et al. 2000;
Sommaruga 2001), little is known about the composition,
sources, dynamics, and fate of CDOM in these environ* Corresponding author: ylzhang@niglas.ac.cn; yunlinzhang@
yeah.net
1 Present address: Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, P. R. China
ments (Mladenov et al. 2008). Both the trophic state and
altitude of a lake can be expected to have a fundamental
effect on dissolved organic carbon (DOC) concentration
and composition (Williamson et al. 1999; Sobek et al. 2007;
Webster et al. 2008). Eutrophication by increased terrestrial
nutrient input will significantly increase the CDOM
concentration by increasing algal blooms (Tzortziou et al.
2008; Zhang et al. 2009). Altitude affects CDOM in three
ways: (1) high altitude inhibits human activity and, thus,
decreases anthropogenic CDOM input; (2) UV-B radiation
increases with altitude, which leads to higher increases in
the photochemical degradation rate of CDOM, which
further lowers the equilibrium CDOM concentration and
alters CDOM composition; (3) the natural export of
CDOM from terrestrial to aquatic ecosystems will decrease
as terrestrial productivity and the size of the catchment area
decreases with increasing altitude (Jansson et al. 2008).
CDOM is a complex mixture of organic materials and,
therefore, it is very difficult to identify every constituent.
However, optical techniques including spectrophotometry
and three-dimensional excitation-emission spectra (EEMs)
fluorometry have provided useful information about the
DOM composition, sources, and molecular size (Kowalczuk et al. 2005; Liu et al. 2007; Wang et al. 2007). EEMs is
considered the simplest and most effective technique for
studying the composition and source of CDOM, due to its
simplicity and sensitivity. However, there has been a
limitation because the EEMs of CDOM from natural
waters are composed of overlapping signals of various
types of fluorophores, making it very difficult to assess the
2645
2646
Zhang et al.
Table 1. Location, area, and trophic state of the 38 lakes on the Yungui Plateau, China. The trophic states are: E 5 eutrophic, M 5
mesotrophic, O 5 oligotrophic. nd 5 no data.
Lake
Bigutianchi
Bitahai
Chenhai
Cheou
Cibihu
Cuoniba
Cuonibapang
Dahaikou
Daxueshantianchi
Erhai
Fuxianhu
Hegou
Lashihai
Lietahu
Litanghu
Longchang
Luguhu
Poshankou
Pugelian
Qiaohai
Qiluhu
Qingdagou
Qingshuihai
Shadecuo
Shadehe 1
Shadehe 2
Shadehe 3
Shuduhu
Tagonghu 1
Tagonghu 2
Wuxuhai
Xinyicuo 1
Xinyicuo 2
Xinyunhu
Yangzonghai
Yihai
Yuejinshuiku
Zheduoshanyakou
Latitude
(N)
27.623
27.828
26.45–26.633
29.262
26.166
30.302
30.320
27.324
28.591
25.600–25.967
24.350–24.633
27.355
26.872
29.092
29.474
29.410
27.683–2.75
25.589
27.324
27.783–27.867
24.133–24.217
30.215
25.594
29.745
29.681
29.714
29.727
27.913
30.300
30.302
29.491
29.393
29.395
24.283–24.383
24.850–24.967
28.733
nd
30.078
No. of samples
Longitude
(E)
Altitude
(m)
Area
(km2)
Trophic
state
2006
2007
99.642
99.944
100.633–100.683
100.035
99.941
99.552
99.561
102.456
99.865
100.010–100.300
102.817–102.95
100.070
100.143
101.572
100.207
100.278
100.75–100.833
103.113
102.455
102.267–102.35
102.717–102.817
101.066
103.112
101.358
101.408
101.400
101.388
99.952
101.294
101.303
101.402
100.104
100.094
102.750–102.800
102.967–103.017
102.235
nd
101.796
3809
3568
1550
4446
2033
4400
4483
3192
4506
1954
1720
4121
2435
4291
4591
4292
2691
2173
3237
1516
1801
2906
2182
4423
3255
3639
3821
3611
4323
4299
3625
4392
4389
1732
1775
2274
2496
4194
0.21
1.4
77.2
,1
8.5
,1
,1
,1
,1
249
211
,1
14.4
,1
1.5
,1
48.5
,1
,1
31.0
36.9
,1
7.2
,1
,1
,1
,1
1.1
,1
,1
,1
,1
,1
34.7
31.7
,1
,1
,1
M
M
M
M
O
O
O
E
O
M
O
O
M
M
O
M
O
M
M
M
E
O
O
O
O
O
O
E
O
O
O
O
O
E
O
M
E
O
1
1
0
1
1
1
1
1
1
0
1
0
0
1
1
0
0
1
0
1
1
0
1
1
0
0
0
1
1
1
1
1
1
1
1
1
1
1
1
1
3
1
0
0
1
0
1
8
8
1
1
1
0
1
3
0
1
0
1
1
1
1
1
1
1
1
0
0
1
1
1
3
3
1
0
0
dynamics of CDOM based solely on the apparent EEMs.
To address this, Stedmon et al. (2003) applied a statistical
modeling approach called Parallel Factor Analysis (PARAFAC) to decompose EEMs into individual fluorescent
components. This approach provides a considerable
advantage over traditional methods in interpreting the
multidimensional nature of EEMs data sets.
In the present study, we determined the absorption,
fluorescence, and source characteristics of CDOM in 38
lakes on the Yungui Plateau of southwest China, which
differed in their trophic state and altitude. The main
objectives of this study were to: (1) determine CDOM
absorption coefficients along gradients of trophic state and
altitude; (2) characterize CDOM components from EEMs,
and determine their potential sources, using the PARAFAC model and fluorescence index; and (3) determine the
correlations between CDOM fluorescence and the absorption coefficient, and other water-quality parameters.
Methods
Study lakes—Thirty-eight lakes on the Yungui Plateau in
southwest China, with elevations from 1516 m to 4591 m
above sea level, and of various trophic states, were sampled
in October 2006 and 2007 (Table 1). The study included all
lakes larger than 1 km2, with the exception of Lake
Dianchi, which was excluded due to high, wind-induced
waves. The lakes were classified into three trophic-state
classes: oligotrophic (n 5 19), mesotrophic (n 5 14), and
eutrophic (n 5 5). The trophic state was assessed according
to four water-quality indices: Secchi disk depth (SDD);
total nitrogen (TN); total phosphorus (TP); and chlorophyll a (Chl a), using the Trophic State Index (TSI; Jing et
al. 2008).
To analyze regional variations, we arranged the data
according to three trophic states (oligotrophic, mesotrophic, and eutrophic), and three altitude categories
CDOM in lakes of the Yungui Plateau
2647
(# 2000 m, 2000–4000 m, and $ 4000 m). We also
qualitatively assessed the effect of trophic state on CDOM
concentration and composition using the correlations
between the value of TSI and CDOM absorption, and
the fluorescent component intensity.
indicate the molecular weight, source, and the degree of
photo-bleaching of CDOM. We adopted this approach,
and calculated S by applying nonlinear regression using Eq.
2 from 280 nm to 500 nm, 275nm to 295 nm, and 350 nm to
400 nm, then SR was defined as S275–295 : S350–400.
Sample collection—To determine CDOM absorption,
fluorescence, Chl a, and nutrient concentrations, water
from 0-m to 1.0-m depth was collected in 4-liter acidcleaned plastic bottles, and held on ice in the field. Single
samples were collected from the center in most lakes
between 07 and 30 September 2006, and between 25
September and 30 October 2007; in addition, several evenly
distributed samples were collected in some lakes between 25
September and 30 October 2007 (Table 1). The SDD was
measured in situ with a 30-cm-diameter black and white
quadrant disk. Latitude, longitude, and altitude, were
recorded in situ using a Global Positioning System.
Three-dimensional fluorescence measurement—EEMs of
CDOM were measured using a Hitachi F-7000 fluorescence
spectrometer (Hitachi High-Technologies) with a 700voltage xenon lamp. The scanning ranges we used were
200–450 nm for excitation, and 250–600 nm for emission.
Readings were collected in ratio mode at 5-nm intervals for
excitation, and at 1-nm intervals for emission, using a
scanning speed of 2400 nm min21. The band-passes were
5 nm for both excitation and emission. A Milli-Q water
blank of the EEMs was subtracted to eliminate the water
Raman scatter peaks.
In order to be able to make comparisons with other
studies using different fluorometers, a correction of the
spectra for instrumental response was conducted according
to the procedure recommended by Hitachi (Hitachi F-7000
Instruction Manual; Cory et al. 2010), which comprised
both excitation and emission calibration. First, excitation
was calibrated by using Rhodamine B as standard
(quantum counter), and a single-side frosted red filter in
excitation scan mode. Then, emission was calibrated with a
diffuser in synchronous scan mode. The excitation and
emission spectra obtained over the range 200–600 nm were
applied internally by the instrument (through fluorescence
solutions 2.1 software) to correct the subsequent spectra.
In order to eliminate the inner-filter effect, the EEMs
were corrected for absorbance by multiplying each value in
the EEMs with a correction factor, based on the premise
that the average path length of absorption of the excitation
and emission light is one-half the cuvette length (McKnight
et al. 2001).
Fluorescence intensity was calibrated in quinine sulfate
units (QSU), where 1 QSU is the maximum fluorescence
intensity of 0.01 mg L21 of quinine (qs) in 1 mol L21
H2SO4 at the excitation wavelength of 350 nm and emission
wavelength of 450 nm (Hoge et al. 1993; Wada et al. 2007).
Rayleigh scatter effects were removed from the data set by
excluding any emission measurements made at wavelengths
# excitation wavelength + 5 nm, and at wavelengths $
excitation wavelength + 300 nm. Values in the two triangle
regions (emission wavelength # excitation wavelength +
5 nm, and $ excitation wavelength + 300 nm) were
substituted by zeroes in the EEMs. The contour figures of
the EEMs were drawn using Origin 6.0.
Absorption measurement—All samples were filtered at
low pressure, first through a precombusted Whatman
GF/F filter (0.7 mm), and then through a prerinsed 25mm Millipore membrane cellulose filter (0.22 mm) into glass
bottles precombusted at 550uC for 6 h.
The absorption spectra of CDOM were obtained
between 240 nm and 800 nm, at 1-nm intervals, using a
Shimadzu UV-2401PC UV-Vis recording spectrophotometer with matching 4-cm quartz cells. Milli-Q water was
used as reference. Absorbance spectra (l) were baselinecorrected, by subtracting the mean absorbance for the
spectral range from 650 nm to 700 nm. Absorption
coefficients were obtained by using the following equation:
aCDOM ðlÞ~2:303ODðlÞ=r
ð1Þ
where aCDOM(l) is the CDOM absorption coefficient,
OD(l) is the corrected optical density, and r is the cuvette
path length in m. In this study, the concentration of
CDOM is expressed using aCDOM(280).
The spectral slope of the CDOM absorption curve, (S),
is calculated by nonlinear regression over the 280–500-nm
wavelength range, according to the equation of Stedmon et
al. (2000):
aCDOM ðlÞ~aCDOM ðl0 Þexp½S ðl0 {lÞzK
ð2Þ
where aCDOM(l) is the absorption coefficient, aCDOM(l0) is
the absorption coefficient at reference wavelength l0, which is
generally chosen to be 440 nm, and S is the spectral slope as a
measure of absorption decrease with increasing wavelength.
K is a background parameter accounting for baseline shifts or
attenuation due to factors other than CDOM.
A diversity of linear, nonlinear, and hyperbolic fittings
across different spectral ranges have previously been used
to obtain values for the spectral slope S, making interlaboratory comparisons very difficult (Twardowski et al.
2004; Zhang et al. 2007). To eliminate such variability,
Helms et al. (2008), by comparing CDOM from water from
wetlands to photo-bleached oceanic water, advocated that
the spectral slope ratio (SR) of two narrow wavelength
ranges (275–295 nm and 350–400 nm) can be used to
Calculation of fluorescence index—To characterize
CDOM in the Yungui Plateau lakes, we used three different
indices; FI255, FI310 (Zsolnay et al. 1999; Huguet et al.
2009), and FI370 (McKnight et al. 2001). Each of these is
now briefly described.
The humification index (FI254) introduced by Zsolnay et
al. (1999), was based on location of emission spectra, and
initially used to estimate the degree of maturation of DOM
in soil; subsequently, it was used by Huguet et al. (2009) to
define and classify DOM characteristics in estuarine waters.
2648
Zhang et al.
FI254 is defined as the ratio between the average fluorescence intensity from 300 nm to 345 nm, divided by the
average from 435 nm to 480 nm, both excited at 254 nm (in
the present study, 255 nm was used—hence, FI255). When
the degree of aromaticity of DOM increases, the emission
spectrum excited at 254 nm becomes red-shifted; thus, FI254
increases. High FI254 values correspond to a maximal
fluorescence intensity at long wavelengths and, thus, to the
presence of complex molecules such as high-molecularweight aromatics (Senesi et al. 1991).
The index of recent autochthonous contribution, indicating the presence of the autochthonous biological activity
(FI310) was introduced by Huguet et al. (2009), and was
determined as the ratio of fluorescence intensity at 380 nm,
divided by that at 430 nm, both excited at 310 nm. High
values of FI310 (. 1) corresponded to a predominantly
autochthonous origin of DOM and to the presence of
organic matter freshly released into water, whereas a low
value of FI310 (0.6–0.7) indicates lower autochthonous
DOM production in natural waters.
To distinguish sources of isolated aquatic fulvic acids,
McKnight et al. (2001) presented a fluorescence index (FI370)
from the ratio of fluorescence intensity at an emission
wavelength of 450 nm divided by fluorescence intensity at an
emission wavelength of 500 nm, both excited at 370 nm. This
index has a value of , 1.9 for microbially derived fulvic
acids, and , 1.4 for terrestrially derived fulvic acids.
Shimadzu UV2401 UV-Vis spectrophotometer. Water
samples were first filtered through Whatman GF/F filters
(0.7 mm) to analyze total dissolved nitrogen (TDN), and
total dissolved phosphorus (TDP). The filtered water
samples were then digested by alkaline potassium persulphate in a high-pressure sterilization vessel at 120uC, prior
to determination of TDN and TDP concentrations with the
spectrophotometer (Zhu et al. 2008). The TDN and TDP
concentrations were measured only for the 2007 samples.
Samples (250 mL–2 liters) for Chl a were collected on
Whatman GF/F filters. The Chl a was extracted with
ethanol (90%) at 80uC and analyzed spectrophotometrically at 750, 663, 645, and 630 nm (SCOR-UNESCO 1966).
Statistical analyses—Statistical analyses (mean value,
linear, nonlinear fitting, and multiple regression) were
performed with Statistical Program for Social Sciences
(SPSS) 11.0 software. Differences in parameters between
the three different trophic states (oligotrophic, mesotrophic, and eutrophic states), and the three different altitudes
(# 2000 m, 2000–4000 m, and $ 4000 m), were assessed
with an independent samples t-test using a p-value of 0.05
to determine significance. Regression and correlation
analyses were used to examine the relationships between
variables (CDOM absorption, fluorescence, water-quality
parameters, and altitude) using a p-value of 0.05.
Results
The PARAFAC modeling—PARAFAC statistically decomposes the EEMs of the complex mixture of DOM
fluorophores to determine the components, without any
assumptions about the shape of their spectra, or concentration, or number. The data signal is decomposed into a
set of three linear terms and a residual array (Stedmon et al.
2003). The number of fluorescent components found using
PARAFAC ranges from 4 to 13 for diverse marine and
freshwater environment (Cory and McKnight 2005; Yamashita et al. 2008; Kowalczuk et al. 2009).
Stedmon and Bro (2008) described how to characterize
DOM fluorescence with PARAFAC, including a split-half
analysis used to validate the identified fluorescent components. Split-half analysis involves dividing the data set into
two random, typically equal-sized groups, and then making
a PARAFAC model of both halves independently. If the
correct number of components is chosen, the loadings from
both models should be the same, due to the uniqueness of
the PARAFAC model.
The PARAFAC analysis in our study was carried out in
matrix laboratory (MATLAB) with the dissolved organic
matter fluorescence (DOMFluor) toolbox for MATLAB,
according to Stedmon and Bro (2008). For PARAFAC
modeling, excitation wavelengths from 200 nm to 220 nm,
and emission wavelengths from 250 nm to 300 nm, were
deleted from each EEMs because of the unreliable data in
these regions. Two samples were removed after intercomparison of the data set to determine whether samples
contained measurement errors.
Other water-quality parameters—TN and TP were
analyzed by the molybdenum blue method using a
General characteristics—The 38 lakes comprised 19
oligotrophic, 14 mesotrophic, and 5 eutrophic lakes. The
percentage of lakes that were oligotrophic increased with
increasing altitude, accounting for 28.6%, 47.1%, and
78.6% at the three altitude categories of # 2000 m, 2000–
4000 m, and $ 4000 m, respectively. There was no
eutrophic lake at an altitude higher than 4000 m, due to
the natural changes in catchment properties and low
human activities with increased altitude.
From oligotrophic to mesotrophic, and further to
eutrophic lakes, the TN, TP, and Chl a concentrations
increased significantly: for TN from 0.23 6 0.11 (mean
value 6 SD) to 0.56 6 0.29, and further to 1.77 6
0.69 mg L21; for TP from 0.012 6 0.006 to 0.027 6 0.014,
and further to 0.118 6 0.076 mg L21; and for Chl a from
1.04 6 1.07 to 5.69 6 4.32, and further to 37.5 6
26.7 mg L21 (t-test, p , 0.001; Table 2). With increasing
altitude from # 2000 m to 2000–4000 m, and further to $
4000 m, TN, TP, and Chl a concentrations significantly
decreased (t-test, p # 0.05; Table 2). Significant and
negative correlations were found between altitude and
TN, TP, Chl a concentrations, and TSI (Fig. 1). However,
altitude explained , 39% of the variability in TN, TP, and
Chl a concentrations, indicating that other variables also
affected the variability in TN, TP, and Chl a concentrations.
Optical properties of CDOM—Among the 38 lakes,
aCDOM(280) ranged from 0.73 m21 to 22.07 m21, with a
mean of 6.63 6 5.33 m21. The lowest aCDOM(280) was
recorded in the oligotrophic lake Daxueshantianchi, lying
CDOM in lakes of the Yungui Plateau
2649
Table 2. Mean values of water-quality parameters and CDOM absorption grouped as: all sites (all), all oligotrophic sties (O), all
mesotrophic sites (M), all eutrophic sites (E), all sites with altitude ,2 km (#2 km), all sites with altitude between 2 km and 4 km (2–
4 km), and all sites with altitude .4 km ($4 km).
Item
TN (mg L21)
TP (mg L21)
Chl a (mg L21)
aCDOM(280; m21)
S280–500 (mm21)
SR
n*
All
O
M
E
#2 km
2–4 km
$4 km
0.5960.62
0.2360.11
0.5660.29
1.7760.69
0.8860.76
0.4560.39
0.2060.06
0.03360.047
0.01260.006
0.02760.014
0.11860.076
0.05160.064
0.02460.021
0.01260.005
7.85615.81
1.0461.07
5.6964.32
37.5626.7
14.48621.85
5.3268.66
0.7460.89
6.6365.33
3.0361.60
7.7462.91
16.5864.86
8.1266.34
6.6664.93
4.3262.98
18.8969.41
14.64610.65
23.1866.02
23.0463.46
23.5169.58
15.1367.80
16.3168.17
3.1361.83
4.1861.69
2.3561.52
1.5960.30
3.6862.03
2.5761.27
2.9861.92
78(38)
39(19)
28(14)
11(5)
32(7)
25(17)
21(14)
* First value in the column n is the number of samples, second value in brackets is the number of lakes.
at 4506 m above sea level, and the highest aCDOM(280) was
recorded in the eutrophic lake Qiluhu at 1767 m. With
increasing trophic state, CDOM absorption increased
significantly (t-test, p , 0.001), with the mean aCDOM(280)
ranging from 3.03 6 1.60 m21 to 7.74 6 2.91 m21 and
further to 16.58 6 4.86 m21 for oligotrophic, mesotrophic,
and eutrophic lakes, respectively (Table 2). A significant
and positive linear relationship was found between TSI and
aCDOM(280)(r2 5 0.46, p , 0.001).
When all three trophic states were considered together,
aCDOM(280) decreased from 8.12 6 6.34 m21 to 6.66 6
4.93 m21, and further to 4.32 6 2.98 m21, in the three
altitude categories of # 2000 m, 2000–4000 m, and $
4000 m; but this decrease was not statistically significant.
However, a significant negative linear relationship was
found between log-transformed aCDOM(280) and logtransformed altitude (r2 5 0.07, p , 0.05). The multiple
linear regression analysis showed that a higher determination coefficient was recorded (r2 5 0.51, p , 0.001) when
TSI and altitude were used as variable inputs than when
any single variable was used.
The mean spectral slope S280–500 based on all data was
18.88 6 9.41 mm21. From the oligotrophic to mesotrophic
state, S280–500 increased significantly (t-test, t 5 23.824, df
5 65, p , 0.001), and SR decreased significantly (t-test, t 5
4.519, df 5 65, p , 0.001). From the mesotrophic to
eutrophic state, there was almost no change in S280–500, and
no statistically significant change in SR. There was a
significant positive linear relationship between TSI and
S280–500 (r2 5 0.29, p , 0.001), and a significant negative
linear relationship between TSI and SR (r2 5 0.09, p ,
0.01). With increasing altitude from # 2000 m to 2000–
4000 m, S280–500 and SR decreased significantly (t-test, t 5
23.548, df 5 55, p 5 0.001 and t-test, t 5 2.381, df 5 55, p
5 0.021), but from 2000–4000 m to $ 4000 m, S280–500 and
SR did not change significantly (Table 2). The significant
and negative linear relationships were found between logtransformed altitude and S280–500 (r2 5 0.12, p , 0.005),
Fig. 1. Scatter plots and linear regressions for the relationships between log-transformed
altitude and (A) log-transformed TN, (B) log-transformed TP, (C) log-transformed Chl a
concentrations, and (D) log-transformed TSI.
2650
Zhang et al.
Fig. 2. Examples of EEMs for one water sample from each trophic state ([A] oligotrophic; [B] mesotrophic; [C] eutrophic).
Fluorescence is in QSU units.
and between log-transformed altitude and SR (r2 5 0.07, p
, 0.05).
EEMs characterization of CDOM—For all 76 samples,
four marked fluorescence peaks were recorded, based on
the EEMs ‘peak picking’ technique; the peaks comprised
two humic-like fluorescence peaks and two protein-like
fluorescence peaks (Coble 1996). An example of measured
EEMs for each trophic state is shown in Fig. 2. The first
humic-like fluorescence peak was in the ultraviolet range
(Exmax , 250 nm, Emmax 5 400–430 nm), and the second
was in the visible range (Exmax 5 300–340 nm, Emmax 5
400–450 nm). The first protein-like fluorescence peak was
at shorter excitation wavelengths (Exmax 5 220–240 nm,
Emmax 5 340–350 nm), due to tryptophan fluorescence,
and the second protein-like peak, at a longer excitation
wavelength (Exmax 5 260–280 nm, Emmax 5 330–350 nm)
was also due to tryptophan fluorescence.
The fluorescence properties of CDOM differed substantially with trophic state. In an oligotrophic lake, such as
Lake Daxueshantianchi, the protein-like fluorescence peaks
were markedly higher than the humic-like fluorescence
peaks. In contrast, in a eutrophic lake, such as Lake
Qiluhu, the humic-like fluorescence peaks were markedly
higher than the protein-like fluorescence peaks.
Four fluorescent components were identified by PARAFAC, based on the split-half validation procedure
(Fig. 3). The largely overlapping excitation and emission
loadings of the four components, modeled on the halves of
the data set, and on the whole data set, are shown in Fig. 3.
All fluorescent components had single emission maxima,
and single or multiple excitation maxima. The excitation
and emission characteristics of these CDOM fluorescent
components we identified are given in Table 3, together
with examples of matching components identified by other
researchers who have modeled CDOM EEMs in aquatic
environments using the PARAFAC model.
The four components we identified from the fluorescence
spectra were a terrestrial humic-like component (C1), a
biological degradation humic component (C2; named as
marine humic-like component in marine environment), and
protein-like components (C3 and C4; Table 3). Component
1 displayed two excitation maxima (at 255 nm and 350 nm)
corresponding to a single emission maximum (at 471 nm),
similar to the humic-like fluorophores defined by Coble
(1996) and Coble et al. (1998), with excitation maxima in
the ultraviolet region (peak A) and the visible region (peak
C). Component 2 had similar excitation and emission
maxima as the M peak and N peak observed in the ocean
and in phytoplankton degradation experiments (Coble
1996; Coble et al. 1998; Zhang et al. 2009). Peak
fluorescence in this region is considered to be coupled to
phytoplankton productivity, because it is most often
observed in the open ocean environment, and has also
been found to be produced and altered by microbial
reprocessing during a mesocosm experiment with CDOM
produced by plankton (Stedmon and Markager 2005a).
Components 3 and 4 had excitation and emission
characteristics similar to an autochthonous protein-like
compound (Coble et al. 1998; Yamashita et al. 2008;
Kowalczuk et al. 2009). Component 3 had excitation and
emission characteristics similar to tyrosine, and component
4 had excitation and emission characteristics similar to
tryptophan. These two components represent DOM that
contains autochthonous CDOM.
The mean fluorescence intensity of the four components,
and their respective contribution to total CDOM fluorescence intensity (the percentage of fluorescence maximum
score for each component to the total fluorescence
maximum scores of all components), as derived by the
PARAFAC model, differed per trophic state and altitude
(Fig. 4). For oligotrophic lakes, the fluorescence intensities
of the autochthonous fluorophores (C3 and C4) were
especially high (43.3% and 34.6%, respectively), and those
of the allochthonous fluorophores (C1) were especially low
(5.2%). In contrast, for eutrophic lakes, the contribution of
allochthonous fluorophores (C1) was substantially higher,
from 5.2% to 15.3%.
With the increase of trophic state, when all altitudes were
considered together, the total fluorescence intensity signif-
CDOM in lakes of the Yungui Plateau
2651
Fig. 3. The PARAFAC model output showing fluorescence signatures of the four fluorescent components. (A–D) The contour plots
present spectral shapes of excitation and emission. (E–H) The line plots present split-half validation results; excitation (left) and emission
(right) spectra were estimated from two independent halves of the data set (red and green lines), and the complete data set (black lines). A
perfect validation is obtained if loadings from the two halves are identical.
icantly increased from 8.49 6 3.93 to 10.63 6 3.52, and to
13.94 6 2.95 QSU (t-test, p , 0.05). Correspondingly, the
fluorescence intensities and the contributions of C1 and C2
significantly increased (t-test, p , 0.01), and the contributions of C3 and C4 decreased, but not significantly. From
the oligotrophic state to mesotrophic, and further to
eutrophic, the contributions of C1 and C2 significantly
increased from 5.2% and 16.9%, to 9.9% and 24.2%, and
further to 15.3% and 42.0% (t-test, p , 0.01). In parallel,
the contributions of C3 and C4 decreased from 43.3% and
34.6%, to 38.6% and 27.3%, and further to 30.6% and
12.2%, but these decreases were not significantly different.
There were significant and positive linear relationships
between TSI and C1 intensity (r2 5 0.31, p , 0.001), and
between TSI and C2 intensity (r2 5 0.58, p , 0.001), but no
linear relationships between TSI and C3 intensity, or
between TSI and C4 intensity.
We demonstrated trends for changes in intensity and
contribution of all four fluorescent components with
increase of altitude, regardless of trophic state. With
increasing altitude from # 2000 m to 2000–4000 m and
further to $ 4000 m, the total fluorescence intensity and the
respective intensities of C1, C3, and C4 firstly increased and
then decreased, but not significantly. With increasing
altitude from # 2000 m to 2000–4000 m and further to
$ 4000 m, the intensity of C2 first slightly (but not
significantly) decreased , then significantly decreased (t-test,
t 5 2.352 df 5 43, p 5 0.023). Of the four components,
only the contribution of C2 significantly decreased from
# 2000 m to 2000–4000 m (t-test, t 5 2.333, df 5 54, p 5
0.023); there was no statistically significant difference for
any of the other three components and altitude. Significant
and negative linear relationships were present between log-
transformed altitude and the intensity (r2 5 0.10, p , 0.01),
and contribution (r2 5 0.10, p , 0.01) of C2.
The multiple linear regression analysis showed that a
higher determination coefficient was recorded when TSI
and altitude were used as variable inputs for C1 (r2 5 0.46,
p , 0.001) and C2 (r2 5 0.61, p , 0.001) than when TSI
was used as variable input for C1 (r2 5 0.31, p , 0.001) and
C2 (r2 5 0.58, p , 0.001), and when altitude was as variable
input for C1 (r2 5 0.00, p . 0.05) and C2 (r2 5 0.10, p ,
0.01). However, there was still no significant linear
relationship for C3 and C4.
Fluorescence index—The variations in the three fluorescence indices, according to different trophic states and
altitude, are shown in Fig. 5. The FI255 ranged from 0.23 to
6.00, with a mean of 1.57 6 1.14, and a coefficient of
variation (CV) of 72.3% for all samples. From the
oligotrophic state to mesotrophic, and further to eutrophic,
the mean value of FI255 significantly increased from 0.99 6
0.62 to 1.77 6 1.02 and further to 3.04 6 1.35 (t-test, p ,
0.005). A significant and positive linear relationship was
found between TSI and FI255 (r2 5 0.20, p , 0.001). In
contrast, from the altitudes of # 2000 m to 2000–4000 m,
and to $ 4000 m, the mean values of FI255 did not vary
significantly (1.63 6 0.88, 1.66 6 1.50, 1.37 6 0.99), and
there was no significant linear relationship between altitude
and FI255.
The FI310 ranged from 0.60 to 1.54, with a mean of 0.93
6 0.18 (CV 5 19.6%) for all samples. From the
oligotrophic to mesotrophic state, the mean value of FI310
significantly decreased, from 1.00 6 0.19 to 0.83 6 0.15 (ttest, t 5 3.865, df 5 65, p , 0.001). However, no significant
differences were found for FI310 between the mesotrophic
2652
Zhang et al.
Table 3. Spectral characteristics of excitation (Exmax) and emission (Emmax) maxima of the four fluorescent components identified
by Parallel Factor Analysis (PARAFAC) modeling for the whole EEM data set, compared with previously identified sources.
Component
No.
Exmax (nm)*
Emmax (nm)
Coble (1996),
Coble et al. (1998)*
Comparison with other
studies using PARAFAC*
Description and
probable source
A peak: Exmax5230–260 and
Emmax5380–460
C peak: Exmax5320–360 and
Emmax5420–480
M peak: Exmax5290–310 and
Emmax5370–420
N peak: Exmax5280 and
Emmax5370
C3: Exmax5270(360) and
Emmax5478{
C4: Exmax5250(360) and
Emmax5440{
C3: Exmax5295 and
Emmax53981
C2: Exmax5315 and
Emmax5418I
C6: Exmax5325(,260) and
Emmax5385"
C4: Exmax5275 and
Emmax53061
C8: Exmax5275 and
Emmax5304{
C1: Exmax5275 and
Emmax,300I
C7: Exmax5270 and
Emmax5299"
C6: Exmax5280 and
Emmax53381
C7: Exmax5280 and
Emmax5344{
C6: Exmax5250(290) and
Emmax5356#
Terrestrial humic-like
substances
C1
255(350)
471
C2
235(290)
397
C3
#225(275)
322
B peak: Exmax5225–230(275)
and Emmax5305–310
C4
#225(285)
344
T peak: Exmax5225–230(275)
and Emmax5340–350
Marine humic-like
substances
(phytoplankton
degradation)
Autochthonous
tyrosine-like
fluorescence
Autochthonous
tryptophan-like
fluorescence
* Secondary excitation band is given in brackets.
{ Stedmon et al. (2003).
{ Stedmon and Markager (2005b).
1 Stedmon and Markager (2005a).
I Murphy et al. (2008).
" Yamashita et al. (2008).
# Kowalczuk et al. (2009).
and eutrophic state, or between the oligotrophic and
eutrophic state. No significant linear relationship was
found between TSI and FI310. With increasing altitude
from # 2000 m to 2000–4000 m, and further to $ 4000 m,
FI310 first significantly decreased (t-test, t 5 4.693, df 5 55,
p , 0.001), then slightly (but not significantly) increased. A
significant and negative linear relationship was found
between log-transformed altitude and FI310 (r2 5 0.21, p
, 0.001).
The FI370 ranged from 1.14 to 1.80, with a mean of 1.37
6 0.12 (CV 5 8.6%) for all samples, suggesting that
CDOM was a mixture of allochthonous humic material
from the surrounding environment, and autochthonous
material produced by biota in the lake. From the
oligotrophic to mesotrophic state, the mean value of FI370
significantly decreased from 1.40 6 0.13 to 1.32 6 0.10 (ttest, t 5 2.764, df 5 65, p 5 0.007). However, no significant
differences were found for FI370 between the mesotrophic
and eutrophic state, or between the oligotrophic and
eutrophic state. No significant linear relationship was
found between TSI and FI370. With the increase of altitude
from # 2000 m to 2000–4000 m, and further to $ 4000 m,
FI370 firstly significantly decreased (t-test, t 5 2.349, df 5
55, p 5 0.023), then slightly and not significantly decreased.
A significant and negative linear relationship was found
between log-transformed altitude and FI370 (r2 5 0.10, p ,
0.01).
Correlations between CDOM fluorescence and absorption
coefficient, and other water-quality parameters—The determination coefficients and the significance level of the linear
relationships between CDOM absorption, the four fluorescent components, and five water-quality parameters are
shown in Table 4. The significant and positive linear
correlations between TN and TDN, TP, and TDP
(Table 4), and the high percentage of TDN in TN (61.0
6 19.8%) and of TDP in TP (48.2 6 25.7%), showed that
dissolved nutrients were an important part of the total
nutrient budget. The higher determination coefficients
(positive linear relationships) between TN, TDN, and Chl
a than between TP, TDP, and Chl a (Table 4), suggested
that the phytoplankton biomass was mainly controlled by
the nitrogen concentration, and that nitrogen was the
probable limiting factor of phytoplankton growth in the
Yungui Plateau lakes.
The significant and positive linear correlations between
CDOM absorption aCDOM(280) and TN, TDN, TP, and
TDP showed a close relationship between CDOM and
nutrients. The significant and positive correlation between
CDOM absorption and Chl a in the Yungui Plateau lakes
CDOM in lakes of the Yungui Plateau
2653
Fig. 4. Composition of CDOM fluorescence intensity (QSU) of (A, B) four components and
(C, D) their respective percent contribution (%) to total CDOM fluorescence intensity derived by
the PARAFAC model, differing by trophic state (O 5 oligotrophic, M 5 mesotrophic, and E 5
eutrophic) and altitude.
indicated that phytoplankton accumulation and decomposition were a contributing source of CDOM.
The aCDOM(280) was strongly and positively correlated
with the fluorescence of the two humic-like peaks, but only
weakly and negatively correlated, or not correlated, with
the fluorescence of the two protein-like peaks (Table 4;
Fig. 6). This result was consistent with prior studies that
showed a stronger correlation between CDOM absorption
and the humic-like peak than between CDOM absorption
and the protein-like peak (Baker and Spencer 2004;
Kowalczuk et al. 2005).
Table 4 shows that components 1 and 2, and components 3 and 4, were strongly and positively linearly
correlated, suggesting that each pair (humic-like and
protein-like fluorescence) had a common source or the
same variation. The absence of significant correlation
between components 1, 2 and components 3, 4 showed
that the humic-like and protein-like fluorescence originated
from different sources.
Discussion
The effect of trophic state and altitude on lake CDOM—
Compared with previous results, CDOM absorption in
lakes of the Yungui Plateau are markedly lower than those
in lakes in the middle and lower reaches of the Yangtze
River (Zhang et al. 2005). We have shown that both trophic
state and altitude significantly affected CDOM absorption
in the Yungui Plateau lakes. With the increase of trophic
state, CDOM increased significantly, and this would be
expected to decrease the attenuation depth of UV radiation
(UVR [Morris and Hargreaves 1997; Laurion et al. 2000]).
Several mechanisms can explain this significant effect of
trophic state on CDOM absorption. The increase of
CDOM absorption with trophic state may be partly due
to increased anthropogenic and terrestrial input caused by
human activity in the catchment area, and partly due to
climate change, especially for the low-altitude lakes. In a
large database of DOC concentrations and other param-
Fig. 5. Variations in fluorescence indices FI255, FI310, and FI370, according to (A) trophic
state (O 5 oligotrophic, M 5 mesotrophic, and E 5 eutrophic) and (B) altitude. The left scale is
for FI255 and the right scale is for FI310 and FI370.
2654
Zhang et al.
Table 4. Determination coefficients and significance levels of the linear relationships between chromophoric dissolved organic
matter (CDOM) absorption, fluorescent components, and water-quality parameters. TN: total nitrogen; TDN: total dissolved nitrogen;
TP: total phosphorus; TDP: total dissolved phosphorus; Chl a: chlorophyll a; aCDOM(280): CDOM absorption coefficient at 280 nm; C1–
C4: Components 1–4.
TN
TDN
TP
TDP
Chl a
aCDOM(280)
C1
C2
C3
C4
TN
TDN
TP
TDP
Chl a
aCDOM(280)
C1
C2
C3
C4
1.00
0.90*
0.48*
0.31*
0.86*
0.66*
0.43*
0.76*
0.00
0.02
—
1.00
0.61*
0.41*
0.84*
0.68*
0.31*
0.76*
0.00
0.01
—
—
1.00
0.88*
0.34*
0.48*
0.32*
0.64*
0.03
0.01
—
—
—
1.00
0.16**
0.31*
0.18**
0.51*
0.00
0.02
—
—
—
—
1.00
0.53*
0.38*
0.64*
0.01
0.01
—
—
—
—
—
1.00
0.80*
0.86*
0.01
0.08***
—
—
—
—
—
—
1.00
0.72*
0.03
0.05
—
—
—
—
—
—
—
1.00
0.02
0.02
—
—
—
—
—
—
—
—
1.00
0.16**
—
—
—
—
—
—
—
—
—
1.00
* p#0.001; ** p#0.005; *** p#0.05.
eters (for 7514 lakes on six continents), Sobek et al. (2007)
found that the catchment, the soil, and the climate
significantly affected DOC concentrations. Furthermore,
the input of nutrients accelerated the growth of phytoplankton, which would increase CDOM absorption,
accompanied by CDOM release from phytoplankton
degradation (Zhang et al. 2009). Additionally, the increase
of CDOM may cause the increase of nutrients through
photo-degradation and microbial degradation (Stedmon et
al. 2007; Piccini et al. 2009; Tranvik et al. 2009).
Considering the interactions between CDOM and trophic
state, some researchers have proposed to define lake
trophic status using the nutrient-color paradigm, which
represents CDOM absorption (Williamson et al. 1999;
Webster et al. 2008).
The significant increase of humic-like components (C1
and C2) with the increase of trophic state, and the
significant positive linear relationships between TSI and
C1 and C2, showed that trophic state mainly affected the
two fluorescence substances. The increase of trophic state,
due to the input of terrestrial nutrients from the catchment,
would increase the terrestrial humic-like component (C1).
The increase of trophic state attributed to the increase of
phytoplankton biomass, would increase the production of
humic component (C2) during biological degradation
processes. Our previous phytoplankton degradation experiment, and other similar observations, also demonstrated
the rapid increase of this fluorescent substance (Miller et al.
2009; Zhang et al. 2009).
For the lakes of the Yungui Plateau, there was a
significant negative linear relationship between log-transformed altitude and log-transformed aCDOM(280), suggesting that altitude significantly affected CDOM absorption;
however, there were no significant differences between
CDOM absorption aCDOM(280) at the three different
altitudes when raw data were analyzed. Sobek et al.
(2007) also found a significant negative correlation between
altitude and DOC concentrations based on a large database
of 7514 lakes from six continents. As mentioned in the
introduction, altitude affects CDOM through decreasing
human activity, increasing photochemical degradation, and
decreasing terrestrial CDOM input due to the decreases of
terrestrial productivity and reducing the catchment area for
high-altitude lakes. For example, Morris and Hargreaves
(1997) found that aCDOM(320) and the specific absorption
a*CDOM (320; the ratio of CDOM absorption to DOC
concentration), decreased by 35–52% and 31–48%, respectively, during 7 d of exposure to incident solar radiation in
an experiment on three lakes on the Pocono Plateau. Also
in the present study, altitude was also a master variable that
incorporated climatic, topographic, and edaphic effects on
CDOM, as Sobek et al. (2007) pointed out.
Our multiple linear analysis showed that higher determination coefficients were recorded for CDOM absorption,
Fig. 6. Correlations between the fluorescence intensities of components 1 (open squares)
and 2 (closed circles), and the CDOM absorption coefficients aCDOM(280).
CDOM in lakes of the Yungui Plateau
and for the C1 and C2 components of fluorescence
intensity, when TSI and altitude were used together as
variable input, than when any single variable was used.
This indicated that trophic state and altitude were likely to
be linked each other, and affected CDOM concentration
and composition altogether. However, we also noted a
marked increase of the determination coefficient when TSI
was added, but only a slight increase of the determination
coefficient when altitude was added in the multiple linear
analysis, which indicated a more important effect of trophic
state on CDOM concentration and composition compared
to altitude. Of course, altitude might also affect CDOM
concentration and composition through the indirect effect
of altitude on trophic state, due to the effects of altitude on
nutrient input and on human activity, particularly land use.
As our results showed, there was a significant negative
linear relationship between TSI and altitude.
CDOM fluorescence as a tracer for inland waters—The
number of components identified by PARAFAC modeling,
and the spectral characteristics of the CDOM EEMs for the
Yungui Plateau lakes, were similar to those found
previously in aquatic environments (Table 3 [Cory and
McKnight 2005; Yamashita et al. 2008; Kowalczuk et al.
2009]). For example, Stedmon et al. (2003) observed five
peaks belonging to terrestrial and autochthonous organic
matter in the Baltic Sea, including components with
spectral characteristics that are comparable to those of
components 1 and 2 found in the present study (Table 3).
The characteristics of the excitation and emission spectra of
component 2 that we recorded fall in the transition zone
between terrestrial and marine humic-like components
(Stedmon et al. 2003). Component 2 has excitation and
emission maxima at shorter wavelengths than component
1, and is similar to peak M and peak N (Coble et al. 1998),
which are believed to belong to marine humic-like
fluorophores or to be associated with phytoplankton
productivity (Coble 1996; Coble et al. 1998; Wang et al.
2007). In a phytoplankton degradation experiment (Zhang
et al. 2009), a fluorescent component similar to component
2 in the present study significantly increased, which
supports the hypothesis that component 2 is of biological
origin and is not exclusively a marine component. Further
evidence that component 2 is derived from phytoplankton
degradation can be deduced from the fact that there was a
marked increase of component 2 in the transition from the
mesotrophic to eutrophic state (from 2.39 6 0.67 to 5.85 6
1.61 QSU). The increase of component 2 may be related to
the significant increase in the Chl a concentration from the
mesotrophic to the eutrophic lakes (from 5.69 6 4.32 to
37.5 6 26.7 mg L21).
The peak position of component 2 (Exmax and Emmax:
235(290) and 397 nm) was the result of blue-shifting
(toward shorter wavelengths) of the Exmax and Emmax
peaks of component 1 (Exmax and Emmax: 255(350) and
471 nm), which was dominated by the terrestrial humic-like
fluorophore. This blue-shifting resulted from the increase
of autochthonous humic substances from phytoplankton
degradation (microbial activities; Boehme and Wells 2006).
Previously, Coble (1996) observed blue-shifting of a humic-
2655
like fluorescence peak, with Exmax and Emmax of 340 nm
and 448 nm in the river, 342 nm and 442 nm in the
nearshore area, and 310 nm and 423 nm in the transition
zone of a shallow sea. More recently, Her et al. (2003) and
Boehme and Wells (2006) observed similar shifts in openwater areas compared to nearshore areas, due to the
increase of autochthonous humic substances in the former
location.
By using the relative contributions of the various
components to the total fluorescence intensity as markers
of CDOM properties, we have characterized a distinct
CDOM fluorescence pattern in the Yungui Plateau lakes
of each of the three different trophic states. For oligotrophic lake waters, the CDOM fluorescence was dominated
by the spectral characteristics of protein-like components
(C3 and C4), with minor contributions of humic-like
components (C1 and C2). Two protein-like components
accounted for 77.9% of the total fluorescence. These
properties closely matched the CDOM fluorescence composition of autochthonous production associated with
biological degradation of CDOM (Coble et al. 1998;
Stedmon and Markager 2005b). For mesotrophic lakes,
the CDOM fluorescence was still dominated by the
presence of the protein-like components (C3 and C4
accounting for 38.6% and 27.3%, respectively). However,
the contribution of humic-like components (C1 and C2)
increased significantly from 22.0% to 34.1% compared
to oligotrophic lake waters. For eutrophic lake waters,
the CDOM fluorescence was dominated by the humiclike components (C1 and C2 accounting for 15.3% and
42.0%, respectively), and the protein-like components
contributed only 42.7%. These properties closely match
the CDOM fluorescence composition of allochthonous
input from the catchment, and from phytoplankton
degradation (Coble et al. 1998; Stedmon and Markager
2005b; Zhang et al. 2009). However, we also note that
autochthonous protein-like components still formed an
important contribution to total fluorescence.
For lake waters of all three trophic states, the higher
contribution of C2 than C1 suggests that a larger portion of
the humic-like component was microbially (algal) derived
rather than being derived from the surrounding catchment.
Past similar results have been reported in alpine and
subalpine lakes (Hood et al. 2003; Miller et al. 2009). For
example, Hood et al. (2003) reported that the changes in
the fluorescence properties of fulvic acids at the highest
elevation sites, suggested that the DOC derived from algal
and microbial biomass in the lakes was a more important
source of DOC above the tree line during late summer and
autumn than other seasons.
Significance of fluorescence indices—The characteristics
of DOM (CDOM) associated with the values for each of
the three established fluorescent indices are shown in
Table 5. In the present study, instead of 254 nm, 255 nm
was used as excitation wavelength for one of the indices,
because the EEMs of CDOM were measured at 5-nm
intervals for excitation. Therefore, the range of FI255 values
used to differentiate CDOM characteristics was slightly
different from the FI254 value in Table 5. The low FI255
2656
Zhang et al.
Table 5. DOM and CDOM characteristics associated with ranges of values for fluorescence indices FI254 (Huguet et al. 2009), FI255
(this study), FI310 (Huguet et al. 2009), and FI370 (McKnight et al. 2001).
Fluorescence index and range
Characteristics
FI254 for DOM
,4
4–6
FI255 for CDOM
,1.5
1.5–3
6–10
.16
3–6
.6
Biological or aquatic bacterial origin
Weak humic character and important recent autochthonous
component
Strong humic character and weak recent autochthonous component
Strong humic character and high terrigeneous contribution
FI310 for DOM
0.6–0.7
0.7–0.8
0.8–1
.1
Low autochthonous component
Intermediate autochthonous component
Strong autochthonous component
Biological or aquatic bacterial origin
FI370 for DOM
,1.4
1.4–1.9
.1.9
Terrestrially derived fulvic acids
Terrestrially and microbially derived fulvic acids
Microbially derived fulvic acids
values (0.23–6.00) reported here indicated that the CDOM
in the Yungui Plateau lakes partly originated from
autochthonous biological activity. The highest FI255 values
were associated with higher trophic state lakes, due to the
increased contribution of terrigeneous humic fluorophores
from the catchment, which is consistent with previous
studies (Huguet et al. 2009; Table 5). The increase of humic
components C1 and C2 with increasing trophic state
(Fig. 4) further demonstrates that FI255 could be used to
characterize CDOM source and composition. The corresponding range of FI255 in Table 5 for CDOM in lakes of
the Yungui Plateau should be , 1.5, 1.5–3, 3–6, . 6. The
four values corresponded to CDOM with biological or
aquatic bacterial origin; weak humic character and
important recent autochthonous component; strong humic
character and weak recent autochthonous component; and
strong humic character and high terrigeneous contribution,
respectively. The marked difference between the ranges of
FI255 and FI254 reported by Huguet et al. (2009) was
attributed to the following four aspects: (1) the different
excitation wavelength (255 nm vs. 254 nm); (2) the
difference in filter pore (CDOM with the filter pore of
0.22 mm vs. DOM with the filter pore of 0.7 mm); (3)
instrument response correction (excitation correction vs. no
excitation correction); and (4) water type (inland waters vs.
estuarine waters).
The FI310 values (0.60–1.54) in the present study fell into
the range reported by Huguet et al. (2009), and could be
used to differentiate between CDOM from oligotrophic
and mesotrophic states. For eutrophic waters, the mean
value of 0.90 6 0.14 indicated CDOM from biological or
aquatic bacterial origin (Fig. 5). However, the EEMs and
PARAFAC model showed the importance of CDOM of
terrestrial origin in the eutrophic state. One possible
interpretation of this inconsistency is that there were high
rates of microbial production of CDOM, but that the
spectral signal may have been masked by the more strongly
fluorescing terrestrially derived humic CDOM.
FI370 ranged from 1.14 to 1.80, with a mean of 1.37 6
0.12 (CV 5 8.6%) for all samples, which was similar to the
value reported by McKnight et al. (2001). For oligotrophic
Yungui lakes, the mean value of 1.40 6 0.13 for FI370 was
similar to the value of 1.4 reported by McKnight et al.
(2001) as indicative of terrestrially and microbially derived
fulvic acids. From the oligotrophic to mesotrophic state,
and further to the eutrophic state, FI370 decreased,
indicating the decrease of autochthonous CDOM. The
significant decrease from 1.40 6 0.13 to 1.32 6 0.10 from
the oligotrophic to the mesotrophic state, but no significant
decrease from oligotrophic to eutrophic, or from mesotrophic to eutrophic, were inconsistent with the result of EEM
spectra and the PARAFAC model.
There were significantly positive correlations between
FI310 and FI370 (p , 0.001), and significant negative
correlations between FI255 and both FI310 and FI370 (p ,
0.001), showing that the indication significance of FI310 and
FI370 was similar. FI255 was the only fluorescence index for
which significant differences were found among the three
different trophic states, suggesting that this index could
best used to determine the effect of trophic state on
CDOM. Furthermore, significant negative linear relationships were found between log-transformed altitude and
both FI310 and FI370, but no significant correlation between
log-transformed altitude and FI255, suggesting that FI310
and FI370 could be used to characterize the effect of altitude
on CDOM, but FI255 could not. Based on the above
analysis, FI255, FI310, and FI370 could be used in combination to assess the effects of trophic state and altitude on
CDOM sources and composition in the Yungui Plateau
lakes.
Implications for the study of CDOM in lakes—Many
studies, including the present one, have shown that CDOM
absorption was the major factor determining attenuation of
UVR in plateau and alpine lakes, and some empirical
correlations have been developed to model UVR attenua-
CDOM in lakes of the Yungui Plateau
tion using CDOM absorption coefficients (Scully and Lean
1994; Laurion et al. 1997; Huovinen et al. 2003). The
optical and fluorescence properties of CDOM, and its
chemical composition and source, play a vital role in
plateau and alpine lake ecosystems. Especially in clear
oligotrophic lakes, small changes in CDOM absorption
and specific absorption are likely to lead to major changes
in the water-column UVR (Williamson et al. 1996; Morris
and Hargreaves 1997), and in the biologically important
UVR and visible spectral balance (Laurion et al. 1997).
The ecosystems of plateau lakes are highly sensitivity to
climate change due to the tight coupling between climate,
catchments, and the biogeochemistry of lakes. Changes in
climate, such as the ozone-layer–related increase in UV-B
radiation, will affect the CDOM in lakes, which will in turn
affect ecosystem structure and functioning, and thereby
alter significant biogeochemical fluxes, such as the emission
of CO2 from lakes to the atmosphere (Zepp et al. 2007;
Tranvik et al. 2009). The increase of CO2 emission from
photo-degradation of CDOM in lakes will affect global
warming (Tranvik et al. 2009).
Much of the above discussion is based on extrapolation
of local measurements to a regional scale. It is, however,
difficult to obtain data sets on UV-B attenuation and
CDOM absorption for remote plateau and alpine lakes.
Remote sensing is, therefore, a suitable alternative for
providing more direct information on the CDOM distribution in these remote plateau and alpine lakes (Winn et al.
2009). If the appropriate sensors are flown, then the
estimation of DOC concentrations and CO2 emission of
plateau lakes by remote sensing is possible, using regional
correlations between CDOM and DOC, and CO2 (Kutser
et al. 2005a,b). In summary, the study of CDOM in plateau
lakes has potential applications not only in UV-B radiation
attenuation, but also in global carbon cycle studies.
Acknowledgments
X. Wang and R. Wang assisted with field work and laboratory
analyses. We also thank the anonymous reviewers for their
constructive comments and helpful suggestions.
This study was jointly funded by the National Natural Science
Foundation of China (grants 40971252, 40825004, 40730529,
40601099), the Major Projects on Control and Rectification of
Water Body Pollution (2009ZX07101-013) and the Knowledge
Innovation Project of the Chinese Academy of Sciences (KZCX2YW-QN312).
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Associate editor: Stephen P. Opsahl
Received: 09 April 2010
Accepted: 12 August 2010
Amended: 07 September 2010