Download Williamson, Craig E., Jennifer A. Brentrup, Jing Zhang, William H

Limnol. Oceanogr., 59(3), 2014, 840–850
2014, by the Association for the Sciences of Limnology and Oceanography, Inc.
doi:10.4319/lo.2014.59.3.0840
E
Lakes as sensors in the landscape: Optical metrics as scalable sentinel responses to
climate change
Craig E. Williamson,1,* Jennifer A. Brentrup,1 Jing Zhang,2 William H. Renwick,3
Bruce R. Hargreaves,4 Lesley B. Knoll,5 Erin P. Overholt,1 and Kevin C. Rose 6
1 Department
of Biology, Miami University, Oxford, Ohio
of Statistics, Miami University, Oxford, Ohio
3 Department of Geography, Miami University, Oxford, Ohio
4 Department of Earth and Environmental Sciences, Lehigh University, Bethlehem, Pennsylvania
5 Lacawac Sanctuary, Lake Ariel, Pennsylvania
6 Smithsonian Environmental Research Center, Edgewater, Maryland
2 Department
Abstract
As the lowest point in the surrounding landscape, lakes act as sensors in the landscape to provide insights into
the response of both terrestrial and aquatic ecosystems to climate change. Here a novel suite of climate forcing
optical indices (CFOI) from lakes across North America is found to respond to changes in air temperature,
precipitation, and solar radiation at timescales ranging from a single storm event to seasonal changes to longerterm interdecadal trends with regression r2 values ranging from 0.73 to 0.89. These indices are based on two
optical metrics of dissolved organic carbon (DOC) quality: DOC specific absorbance (a*320) and spectral slope
(S275–295), where the ratio a*320 to S275–295 gives a composite climate forcing index. These indices of DOC quality
are more responsive to climate forcing than is DOC concentration. A similar relationship between the component
indices a*320 and S275–295 is observed across a wide range of lake types. A conceptual model is used to examine the
similarities and differences in DOC-related mechanisms and ecological consequences due to increased
temperature vs. precipitation. While both warmer and wetter conditions increase thermal stratification, these
two types of climate forcing will have opposite effects on water transparency as well as many ecological
consequences, including oxygen depletion, the balance between autotrophy and heterotrophy, and depth
distributions of phytoplankton and zooplankton.
In recent decades, trends of increasing DOC concentration have provided one of the strongest signals of change in
inland aquatic ecosystems (Williamson et al. 2009a), with
as much as a doubling of DOC concentrations in lakes in
some regions of North America and Europe (Monteith et
al. 2007). The causes of increasing DOC are a subject of
active debate. While earlier work (Monteith et al. 2007)
seemed to be converging on a central role for recovery from
anthropogenic acidification, more recent work (Zhang et
al. 2010; Couture et al. 2012) suggests that climate plays an
equally or perhaps more important role, even in systems in
which recovery from acidification has been observed.
Furthermore, climate change effects on terrestrial ecosystems are predicted to increase future DOC concentrations
in boreal lakes by as much as 65% (Larsen et al. 2011). A
clearer understanding of these increasing DOC concentrations is critical because DOC is one of the most
fundamental regulators of aquatic ecosystem structure
and function (Williamson et al. 1999; Couture et al.
2012). In most inland waters the primary source of DOC
is from the surrounding terrestrial landscape, though
phytoplankton and macrophytes also produce DOC. Due
largely to its ability to absorb light (evidenced by color),
terrestrially derived DOC plays an important role in
determining water transparency, mixing depth, and oxygen
depletion in deeper waters, as well as the processing and
bioavailability of nutrients and toxic compounds (Williamson et al. 1999). Increases in DOC can also alter the
Climate change is driving us toward an overall warmer
and wetter world, with more frequent and severe droughts
as well as more intense precipitation and floods. Future
climate scenarios point to dry regions and seasons getting
drier and wet regions and seasons getting wetter (IPCC
2012, 2013), yet deciphering the effects of the temperature
vs. precipitation components of a changing climate is
notoriously difficult. Long-term climate trends are clouded
by variability that creates noise in the system (Clark et al.
2010). To add to the challenge, climate change is
manifested not only in long-term trends but also in extreme
events and geographic variation across the landscape
(IPCC 2012). For example, while precipitation has
increased by 7% on average across the United States in
the past 100 yr, the amount of rainfall in extreme
precipitation events (the top 1% of all daily events) has
increased by 20% (Karl et al. 2009). Some regions, such as
the northeastern United States, have experienced up to a
67% increase in extreme precipitation events, while in other
regions, such as the southwestern United States, this
increase has been only 9% (Karl et al. 2009). These heavy
rainfall events can lead to more intense runoff into lakes,
which can in turn increase terrestrially derived dissolved
organic carbon (DOC) concentrations that substantially
alter thermal structure and ecosystem metabolism of lake
ecosystems (Klug et al. 2012; Sadro and Melack 2012).
* Corresponding author: [email protected]
840
Lakes as climate sentinels
response of aquatic food webs to climate change (Hansson
et al. 2012; Read and Rose 2013). Insights into the color
and quality as well as the concentration of these climatedriven changes in DOC can also help resolve important
questions about how these changes in DOC alter food
web subsidies, or inhibit them through shading due to
absorption of photosynthetically active radiation (PAR;
Jones et al. 2012). Strategies for developing a more
quantitative and informative framework to provide insights
into the contrasting effects of warmer vs. wetter conditions
on terrestrial and aquatic ecosystems are thus essential.
One of the most promising approaches to deciphering the
ecological effects of climate change involves the use of the
sentinel responses of ecosystems themselves, as these may
provide the most sensitive indicators of both drivers and
responses. For example, in the world’s oceans, ecosystems
amplify climate variation and provide stronger signals of
regime shifts than do actual physical climate measurements
(Taylor et al. 2002; Hays et al. 2005). While continental
landscapes are more complex than the pelagic zones of
oceans, these landscapes also have embedded sensors: lake
ecosystems that are highly responsive to climate change
(Williamson et al. 2009a,b). Lake responses to climate
change include physical, chemical, and biological signals
that are readily measured over multiple timescales (Adrian et
al. 2009), yet to date there is no basic framework with which
to take advantage of the power of lakes as climate sentinels.
There is a need to identify which responses are the most
valuable as clear and informative sentinels of alteration of
both terrestrial and aquatic systems by climate change.
Lakes are sensors in the landscape that provide many
types of sentinel responses, defined here as physical,
chemical, and biological signals of climate-driven ecosystem change that are both informative and quantifiable.
Sentinel responses have important ecological consequences,
defined here as responses that involve living organisms that
inform us about how climate change alters ecosystem
structure and function. Here we use this simple framework
to develop and apply a suite of DOC-related climate
forcing optical indices (CFOI) for assessing the sentinel
responses of lakes to temperature and precipitation. We
also examine the response of these indices to solar
radiation, which changes as a function of cloud cover,
one of the greatest unknowns in predicting future climate
change (IPCC 2013). We examine changes across multiple
timescales to evaluate whether short-term extreme events
ranging from single storm events to periods of high or low
drought can inform us about ecosystem-level responses
over longer timescales. Sentinel responses that share
common mechanisms and thus respond similarly across
multiple timescales or space scales can be referred to as
scalable sentinel responses as a result of their greater
potential to predict long-term responses based on shortterm data. We then present a conceptual model of some of
the potential sentinel responses to warmer vs. wetter
climates on lakes and their ecological consequences. While
these two components of climate change both induce
similar increases in thermal stratification, they have
opposite effects on water transparency and result in
opposite ecological consequences.
841
Our approach springs from recent progress in absorption
and fluorescence spectroscopy that has created new insights
into the role of DOC in aquatic ecosystems. These
techniques are based on the fact that DOC strongly and
selectively absorbs shorter wavelength solar ultraviolet
(UV) radiation (Williamson et al. 1996), making UVrelated metrics much more sensitive sentinels of environmental change than is DOC concentration (Williamson et
al. 1999). UV and PAR transparency have been shown to
be valuable sentinels of climate change in a wide variety of
lakes ranging from boreal lakes in Canada (Gunn et al.
2001) to Arctic and Antarctic lakes (Vincent et al. 1998).
More recent studies of UV and PAR transparency in a wide
variety of subalpine and alpine lakes have shown that UV is
more sensitive than PAR to environmental change (Rose et
al. 2009a,b). Prior work (Fee et al. 1996; Snucins and Gunn
2000) has suggested that small, clear-water lakes are likely
to be the most responsive systems to changes in DOC
concentration and climate as a result of the greater
importance of DOC and transparency vs. wind in
controlling mixing depth in smaller lakes and the low
background ‘noise’ levels of DOC in clear-water lakes.
Here we show that shallow turbid reservoirs can be
similarly responsive when considering DOC quality. UVbased optical metrics have also been used to demonstrate
that dust from the Sahara Desert may contribute a major
portion of the DOC to high alpine lakes in the Sierra
Nevada of Spain (Mladenov et al. 2009).
CFOI—The suite of CFOI that we propose here builds
on these prior advances in UV absorbance spectroscopy
and is based on two optical metrics of DOC quality: a*320,
the DOC-specific absorbance at 320 nm (m2 (g C)21),
which is the dissolved absorption coefficient at 320 nm
(ad320, m21) divided by DOC concentration (mg C L21),
and S275–295, the spectral slope, the slope of the linear
relationship between the natural log of the absorption
coefficient and wavelength in the 275–295-nm UV range
(nm21). The ratio of these two indices can be used as
a novel third, composite climate forcing index (CF 5
a*320 : S275–295, nm m2 (g C) 21). Increases in S275–295 are
driven largely by DOC photobleaching (Helms et al. 2008),
making these metrics informative indicators of increased
exposure to sunlight. Increases in a*320 are driven by inputs
of fresh terrestrial DOC, which decrease transparency by
introducing non-photobleached (or less-photobleached)
DOC (Hargreaves 2003; Helms et al. 2008; SanClements
et al. 2012) that is often less biolabile. The contrasting and
interrelated responses of a*320 and S275–295 to the balance
between precipitation and temperature are largely independent of DOC concentration (Hargreaves 2003; Helms et al.
2008; Loiselle et al. 2009). These two metrics are inversely
related because of the generally low prior exposure of
terrestrially derived DOC to sunlight and the loss of UV
absorbance that occurs during photobleaching. This
complementary relationship of the two metrics provides a
more robust and informative response index to climate
change than could either metric alone, and this relationship
also has the potential to more clearly differentiate
mechanisms that underlie DOC source and processing.
842
Williamson et al.
three different types of lakes were used to assess the value
of the CFOI relationship over time intervals ranging from a
single extreme event to months, years, and decades.
Methods
Fig. 1. Conceptual model of the climate forcing optical index
(CFOI) relationship. CFOI curve (dashed line) showing the
hypothesized response of DOC-specific absorbance (a*320) and
spectral slope (S275–295) to warmer, drier (e.g., drought with high
sunlight exposure, low terrestrial DOC inputs) vs. cooler, wetter
(e.g., high precipitation with low sunlight exposure, high
terrestrial DOC inputs) regimes.
Here we present a series of hypotheses predicting how
this suite of indices will respond to climate change. First of
all, as a result of the complementary responses of a*320 vs.
S275–295 to climate forcing, we predict that plotting these
two component indices against each other will provide a
robust relationship across a wide variety of lakes located in
different climate regions across North America (Fig. 1).
While myriad other environmental conditions may alter the
position of a given lake on this CFOI curve, we predict that
lakes will exhibit the potential to respond to climate change
by moving along this curve. We hypothesize that for a
given lake, warmer, drier conditions such as those
associated with heat waves and droughts will lead to a
decrease in CF as a*320 decreases as a result of a decrease in
the flux of DOC from the surrounding watershed and
S275–295 increases due to higher photobleaching (Fig. 1). In
contrast, we hypothesize that cooler, wetter conditions
associated with high precipitation events will lead to an
increase in CF because S275–295 will decrease as the result of
cloudy conditions and less photobleaching and a*320
will increase as the result of a hydrologic balance that
favors increased influx of more light-absorbing terrestrially
derived DOC (Fig. 1). Thus, we predict that CF will
decrease with increasing temperature or exposure to solar
radiation and increase with precipitation. We also hypothesize that conditions that are warmer and wetter, or colder
and drier, will fall in between these extremes depending on
the relative balance of allochthonous DOC flux and
photobleaching. We tested these hypotheses and predictions in a suite of lakes across broad spatial and temporal
scales. Single samples in 35 lakes from highly contrasting
climate zones in different geographic regions of North
America were used to test how robust the CFOI
relationship was among diverse lakes. Multiple samples in
Lake study sites—The 35 lakes sampled from across
North America are all small lakes (all but one measured
, 3.25 km2) that range from sinkholes in arid regions of
New Mexico to seepage and surface runoff lakes of glacial
origin in heavily forested regions of the central and northern
United States, to artificial impoundments in heavily
agricultural landscapes in Texas and Ohio, to subalpine
and alpine lakes at and above tree line in the U.S. Sierra
Nevada and Beartooth Mountains and Canadian Rockies.
Data for these lakes are from just one sampling during the
ice-free season. Of the three more intensively studied lakes,
Acton Lake is a small (surface area 5 2.40 km2), shallow
(maximum depth 5 8 m), hypereutrophic (mean summer
chlorophyll 5 59 mg L21, DOC 5 3.7 mg L21) Ohio
reservoir with a short hydraulic retention time (29.2 d),
embedded in an agricultural landscape. Lakes Giles and
Lacawac are both small (surface areas 5 0.48 and 0.21 km2,
respectively), natural glacial lakes located in heavily
forested, largely undisturbed catchments in northeastern
Pennsylvania. Giles is a deeper (maximum depth 5 23 m),
oligotrophic (mean summer chlorophyll 5 0.8 mg L21,
DOC 5 1.3 mg L21) lake with a hydraulic retention time of
5.6 yr. Lacawac is a moderately deep (maximum depth
5 13 m), mesotrophic, and somewhat dystrophic (mean
summer chlorophyll 5 3.8 mg L21, DOC 5 5.1 mg L21)
lake with a hydraulic retention time of 3.4 yr.
Data and analysis—Weekly water samples were taken
during the spring and summer from Acton Lake over the
course of 2 yr with contrasting weather conditions to
examine the CFOI response, enabling us to capture a major
storm event and seasonal transitions during 2008 from
the cool wet spring (April and May average daily air
temperature [ADT] 5 13.8uC, average daily precipitation
[ADP] 5 3.8 mm) to the warm dry summer (July–August
ADT 5 22.6uC, ADP 5 1.1 mm). These same data were
also used to assess interannual variation in a warmer, drier
year (2007, May–August ADT 5 22.3uC, ADP 5 1.4 mm)
vs. a cooler, wetter year (2008, May–August ADT 5
20.6uC, ADP 5 3.2 mm). July samples from Lake Giles and
nearby Lake Lacawac were used to look at the CFOI
response to interdecadal variations in rainfall during years
for which data were available (1993, 1996, 1997, 1999,
2000, 2005, 2006, 2008, 2010, and 2011) for the drier 1990s
(May–July ADP 5 2.3 mm) and the wetter 2000s (May–
July ADP 5 3.6 mm). Temperatures were similar during
May–July for the two decades (ADT 5 18.5uC for the
1990s, 18.3uC for the 2000s). The meteorological data
(ADT, ADP) are for the 75 d prior to the mid-July
sampling dates for each of these years. For Acton Lake,
meteorological data were obtained from the Environmental
Protection Agency Clean Air Status and Trends Network
(CASTNET) database for the OXF122 site (Oxford, Ohio)
located about 5 km from the lake. For Lacawac and Giles
Lakes as climate sentinels
Lakes, meteorological data were obtained from automated
instruments maintained at the Lacawac Sanctuary Field
Station by one of the authors (BRH).
Water samples were collected from the epilimnion and
filtered using ashed Whatman GF/F filters. Filtered
samples were analyzed for DOC using a Shimadzu Total
Organic Carbon Analyzer (TOC-5000 or TOC-VCPH). A
Milli-Q deionized water blank was subtracted from all
DOC measurements, and values were calibrated using a
diluted certified DOC standard (Aqua Solutions, 50 mg L21
potassium biphthalate). Dissolved absorbance properties
were measured with a Shimadzu UV and visible spectrophotometer (UV-160U, UV-1601, or UV-1650 PC). Corrected dissolved absorbance values were calculated by
subtracting a Milli-Q water blank and the average
absorption from 775 to 800 nm from raw absorbance
values. Naperian dissolved absorption coefficients were
calculated as follows:
2:303|D
r
where D is the decadal optical density value from the
spectrophotometer and r (units: m) is the path length of the
quartz cuvette. The DOC-specific absorption coefficients
(a*320) were calculated by dividing ad (320 nm, m21) by the
DOC concentration (mg C L21). Spectral slopes (nm21)
over the 275–295-nm range (S275–295) were calculated using
linear regression to estimate the slope of the relationship
between ln ad and wavelength, expressed according to
convention as a positive number.
For the regression analyses that examined the timing and
strength of the response variables within the three primary
study lakes, all meteorological data were averaged over the
preceding time interval (0–15 d, 0–30 d, 0–45 d, 0–60 d, and
0–75 d). The CFOI variables and DOC concentration were
the response variables and the weather drivers were
the predictor variables. The response variables were log
transformed to linearize the data. The data are from July
samples for Lacawac and Giles and from the weekly samples
during the 2007–2008 period in Acton. A simple linear
regression was performed to model the relationship between
the CFOI and DOC response variables and weather drivers
ranging over different time intervals. Significance was
determined at an a level of 0.05. All linear regressions were
run using R (R Development Core Team 2011 versions
0.94.110 and 0.97.248). Scatter plots (not shown) were used
to visualize the relationship between sentinel responses of the
lakes and climate drivers.
ad ~
Results
All 35 lakes from climate regions ranging from the
warm, dry southwest to the colder, wetter northeast United
States fell along the same line on the plot of a*320 vs.
S275–295, indicating a high degree of conformity of these
diverse lakes to the CFOI relationship (r2 5 0.88, Fig. 2A).
Furthermore, two very different types of lakes showed
similar responses to temperature and precipitation across
multiple timescales (Fig. 2B–D). Acton Lake (shallow,
hypereutrophic reservoir) showed responses that follow
843
the CFOI curve for a single extreme precipitation event
(arrow in Fig. 2B), for seasonal changes from spring to
summer (r2 5 0.73, Fig. 2B), and for interannual changes
from a warm, dry to a cool, wet year (r2 5 0.89, Fig. 2C).
The CF index (mean 6 standard error [SE]) was 92 6 4.1
during the warmer, drier year (2007) and 155 6 12.7 in the
cooler, wetter year (2008). The transition from the cooler,
wetter spring to the warmer, drier summer in 2008
decreased the CF index from the 134–190 range in May
to values of 94–95 in August. The extreme precipitation
event in early June 2008 (over 109 mm of rain in 2 d) drove
the CF index up to a value of 335. Lake Giles (deeper,
oligotrophic, natural lake) similarly showed responses that
conformed to the CFOI relationship on an interdecadal
timescale (r2 5 0.80, Fig. 2D). The CF index was 11 6 1.4
for the drier 1990s and almost three times as high (31 6 6.0)
for the wetter 2000s. For Lake Lacawac, a dystrophic,
natural glacial lake in the same forested region as Giles, the
CF value was 94 6 16.9 for the 1990s and 140 6 10.6 for
the 2000s. Following an extreme precipitation event in 2006
(over 200 mm in 4 d from June 25 through 28), the CF
values were driven up to 58 in Giles and 170 in Lacawac
during July.
We used linear regression to test how rapidly and
strongly a*320, S275–295, CF, and DOC concentration in the
same three lakes responded to average daily air temperature, precipitation, and solar radiation integrated over
timescales of 15, 30, 45, 60, and 75 d prior to sampling (to
give a start time close to ice-out). The r2 values were used to
evaluate the strength of each sentinel response variable to
each climate driver as well as the timing of the maximum
response. For all three lakes the strongest CFOI responses
were to precipitation (r2 5 0.62–0.78), with less pronounced
responses to air temperature (only one significant response,
a*320 in Lacawac, r2 5 0.41) and solar radiation (all three
CFOI response variables in Lacawac, r2 5 0.58–0.61, and
S275–295 in Giles, r2 5 0.39). The coefficients of determination for DOC concentration were generally lower than
for the CFOI variables, with significant responses to air
temperature only in Lake Giles (r2 5 0.48, Table 1) and to
precipitation in Lacawac (r2 5 0.52) and Acton (r2 5 0.14).
All CFOI variables showed significant responses to
precipitation in all three lakes within 30–75 d, with peak
responses generally at 60–75 d. Acton responded more
rapidly to precipitation than did the other two lakes, with a
significant response to all three CFOI variables within as
few as 15 d (Table 1). Significant responses of the CFOI
indices to solar radiation were observed between 30 and
75 d, with peak responses in Giles in as few as 45 d, in
Lacawac at 60–75 d, and with no significant responses in
Acton. Significant responses of DOC concentration were
observed within 30–75 d, with peak responses to air
temperature after 60 d in Giles and significant responses
to precipitation after 60 and 30 d in Lacawac and Acton,
respectively (Table 1).
Discussion
Sentinel responses that are effective over multiple
timescales are of great interest because they may permit
844
Williamson et al.
Fig. 2. Sentinel responses of climate forcing optical index (CFOI) variables in (A) 35 diverse lakes across North America (r2 5 0.88,
y 5 21.0 e2129 x), an agricultural reservoir following (B) an extreme rain event as well as seasonal variation in climate (r2 5 0.73, y 5 10.9
e293.9 x), and (C) interannual variation among a warm, dry (2007) and a cool, wet (2008) year (r2 5 0.89, y 5 10.2 e291.4 x), and (D)
interdecadal variation of a glacial lake in a forested watershed during the drier 1990s vs. the wetter 2000s (r2 5 0.80, y 5 10.2 e2117 x).
Note the similar CFOI responses (move to lower right during hot, dry regimes) across different timescales and lake types. (A) Letters
represent geographic region of the United States (E 5 East, MW 5 Midwest, N 5 North, W 5 West, S 5 South), R 5 reservoir, CR 5
Canadian Rocky Mountains. (B–D) Dashed lines are the regression line from (A).
new insights into the ecological consequences of both
extreme events and long-term trends in climate change by
examining short-term responses. But such responses are
especially valuable if the underlying mechanisms are the
same and if they respond in a similar fashion across
timescales so that they comprise scalable sentinel responses.
The optical metrics of DOC quality reported here share the
same mechanisms and show similar responses across
multiple timescales from single storm events to seasonal,
interannual, and interdecadal timescales and thus meet the
criteria of being scalable sentinel responses. These indices are
highly responsive to variations in precipitation and, to a
lesser extent, to changes in solar radiation and temperature,
extending prior work (Schindler et al. 1996; Snucins and
Gunn 2000) demonstrating decreases in DOC concentration
in response to drought. The data presented here show that
responses of DOC concentration are sensitive across a wide
range of timescales, from weeks to decades, and, more
importantly, demonstrate how weather and climate alter
DOC quality with important implications for both carbon
loss from terrestrial ecosystems and lake ecosystem structure
and function. These indices are particularly sensitive to
climate change as a result of the fact that DOC quality is
more sensitive to climate change than is DOC concentration
alone and as a result of the high responsiveness of both
component indices to solar radiation and precipitation in
complementary ways. For example, drought conditions are
usually characterized by high solar radiation and low
precipitation, while storm events are characterized by low
solar radiation and high precipitation.
The variations in timing and magnitude of the CFOI
responses observed here highlight the ways in which lakes
Lakes as climate sentinels
845
Table 1. Time interval (d) for maximum (top number) coefficient of determination (r2) for response of DOC concentration (mg L21)
and three climate forcing optical index variables (a*320 5 DOC-specific absorbance at 320 nm, S275–295 5 275–295-nm spectral slope, CF
5 climate forcing index, the ratio of a*320 to S275–295) to average daily precipitation (mm d21), temperature (uC), and solar radiation (kJ
m22 d21). All time intervals with significant regressions are given in parentheses when there is more than one. Data for Lakes Giles and
Lacawac were only available for 10 of the years from 1993 to 2011 (see Methods). Dashes indicate no time interval shown because r2 is so
low (, 0.1).
[DOC]
Days
Lake Giles, 1993–2011 (July)
Precipitation
Air temperature
Solar radiation
60
60
30
Lake Lacawac, 1993–2011 (July)
Precipitation
60(30,60,75)
Air temperature
—
Solar radiation
15
a*320
r2
0.3
0.48
0.12
0.52
,0.1
0.32
Acton Reservoir, 2007–2008 (May–August)
Precipitation
30
0.14
Air temperature
—
,0.1
Solar radiation
—
,0.1
S275–295
Days
r2
Days
60(30,60,75)
—
—
0.62
,0.1
,0.1
75(30–75)
15
45
0.78
0.41
0.61
0.75
,0.1
,0.1
45(30–75)
15
60(45–75)
75(15–75)
—
—
CF
r2
Days
r2
0.68
0.28
0.39
60(30–75)
—
60
0.66
,0.1
0.14
75(30–75)
15
75(30–75)
0.76
0.28
0.58
75(30–75)
15
60(45–75)
75(15–75)
—
—
0.74
,0.1
,0.1
75(15–75)
—
—
0.76
0.37
0.61
0.77
,0.1
,0.1
* Statistically significant values (p , 0.05) in bold type; significant negative correlations in bold italics.
with different types of land use and catchment characteristics
may vary in the timing and magnitude of their responses to
climate forcing. For example, the more rapid response of
Acton to precipitation (compared to the other two lakes;
Table 1) is likely due to its shallow nature and short
retention time, allowing tributary water with high allochthonous inputs to rapidly dominate the lake after a rainfall
event. The high sensitivity of Lacawac to solar radiation (in
comparison to the other two lakes; Table 1) is likely due to
the substantial portion of its watershed that comprises a bog
that provides highly photolabile DOC to the lake, but it may
also be related to iron-bound DOC from anoxic sediments
(Maloney et al. 2005). Similarly, the short retention time
combined with high inputs of inorganic sediments from the
surrounding, highly disturbed agricultural watershed (Knoll
et al. 2013) may contribute to the lack of a response to
photobleaching in Acton (Table 1).
While previous work (Snucins and Gunn 2000) has
suggested that higher transparency lakes are more sensitive
sentinels of climate-induced changes in DOC, we found
that both the CFOI variables and DOC concentration were
as responsive, if not more responsive, to precipitation in
Lacawac than they were in the higher transparency Lake
Giles (Table 1). We attribute these patterns to DOC quality
being more responsive to precipitation than is DOC
concentration alone as a response metric. The data
reported here also suggest that both DOC concentration
and quality are less sensitive to changes in temperature than
they are to changes in precipitation and photobleaching.
This is consistent with the findings of prior studies (Zhang
et al. 2010) that have suggested that precipitation and
photobleaching are the two most important processes
controlling differences in the quality and concentration of
DOC in lakes and their response to climate change.
Changes in a*320 and S275–295 may inform us about DOC
sources and lake ecosystem responses to altered DOC
quality (Hargreaves 2003) that may underlie recently
observed DOC trends. Terrestrially derived DOC has a
generally lower S275–295 and higher a*320 than does pelagic
source DOC; it also has a higher molecular weight and is
more highly colored and more photolabile but less biolabile
than pelagic source DOC (Helms et al. 2008). The balance
between photolability and biolability will in turn largely
determine whether a given concentration of DOC will
depress photosynthesis through shading or serve as a
resource subsidy for aquatic food webs (Jones et al. 2012).
Changes in a*320 may also be indicative of conditions
favorable to methane production and can lead to higher
d13C stable isotope ratios through photobleaching (Osburn
et al. 2001). In this prior study of our two Pennsylvania
study lakes the d13C values diverged between the surface
and deep waters by as much as 3–4% during periods of
thermal stratification (Osburn et al. 2001). This is likely due
to the conversion of higher molecular weight, terrestrially
derived DOC to lower molecular weight compounds in the
surface waters (Osburn et al. 2001). There are also deepwater and bottom sediment processes in the anoxic region
of Lacawac that could contribute to these differences
(Maloney et al. 2005). This difference in the stable isotope
signatures in shallow vs. deep waters has important
implications for the ongoing debates about the relative
importance of allochthonous carbon to aquatic food webs
(Jones et al. 2012) because hypolimnetic DOC has a similar
optical and isotopic signature to terrestrially derived DOC.
To further explore the relative response strength of the
CF index to precipitation vs. temperature we ranked the
years in our interannual data set in Lake Giles to identify
the warmest year (2006), the wettest year (also 2006), and
the years with the highest drought (1993, lowest Palmer
Drought Severity Index, PDSI) and with the lowest
drought (2011, highest PDSI) and compared the differences
in their CF values. The logic was that the drought indices
846
Williamson et al.
would reveal the years during which temperature, evaporation, and precipitation interacted to give us the warmest,
driest year (1993) and the coolest, wettest year (2011). The
Giles CF index values ranged from 7 in the most severe
drought year (1993) to 58 in the warmest and wettest year
(2006). These were the lowest and highest points on the
CFOI curve, respectively (Fig. 2D). The least severe drought
year (2011) and the coolest, driest year (1997) had
intermediate values of 23 and 14, respectively. This suggests
that our initial predictions that a higher CF value will be
related to colder, wetter conditions (Fig. 1) did not hold in
Lake Giles for that year at least. This pattern is consistent
with the results that emerged in our regression analyses—
precipitation is more important than temperature in driving
the observed changes in DOC quality (Table 1).
As with any indices of change, the CFOI relationship is
sensitive to other potential drivers of environmental change,
such as wind speed, land use, land management, and acid
deposition. Thus, the CFOI metrics must be used cautiously
with these potential other drivers in mind. For example,
wind speed has shown long-term trends in recent decades
(Pryor et al. 2009), and wind speed influences the depth of
the surface mixed layer in larger lakes and consequently both
photobleaching rates (decreasing a* and increasing S275–295)
as well as advection of DOC from deeper waters (potentially
increasing a* and decreasing S275–295). In spite of the
shallower mixing depths that have been observed in these
lakes and anticipated higher photobleaching rates, the
response to higher precipitation in recent years was fully
consistent with the CFOI relationship (Figs. 1, 2).
Changes in land use patterns similarly have the potential
to influence the CFOI relationship. The amount of
wetlands within a watershed is an important determinant
of DOC concentration in lakes, particularly in alpine
and subalpine regions (Winn et al. 2009). In agricultural
regions, storm events may alter DOC quality and
concentration in downstream systems in ways that differ
from those seen in well-forested watersheds (Caverly et al.
2013). Thus, draining of wetlands or conversion to (or
recovery from) agriculture must be considered when
applying the CFOI metrics. Changes in land use in the
watersheds of Lacawac and Giles have been minimal. Lake
Lacawac is located within the Lacawac Sanctuary, and
preservation of the intact watershed is a high priority, as it
is in the nearby privately owned property surrounding Lake
Giles. Thus, land use change does not explain the long-term
trends that we observed. The very similar CFOI responses
observed in Acton Lake (highly agricultural watershed) and
the Pocono lakes (preserved forested watersheds) suggest
that the CFOI metrics are robust across lakes with a wide
variety of land use patterns.
One of the leading hypotheses proposed to explain the
observed increases in DOC in both Europe and North
America is recovery from acidification, with reductions in
anthropogenic sulfate deposition (Monteith et al. 2007).
Recovery from acidification has been clearly demonstrated
to cause an increase in DOC concentration (Williamson et
al. 1996; Tanentzap et al. 2008). Drought and acidification
can also interact to alter the UV transparency of lakes
(Schindler et al. 1997). In one lake with extreme exposure to
acid deposition, drought induced a threefold increase in
UV transparency (Yan et al. 1996). The processes that
control DOC optical quality and thus potentially influence
the CFOI relationship are also pH dependent, so the nature
of the response depends on the pH range. In the pH range of
4 to 7, the loss rate of total organic carbon due to
photobleaching increases with decreasing pH (Gennings
et al. 2001), but there is little change in DOC-specific
absorbance (similar to our a*320, but absorbance was
measured at 440 nm; Pace et al. 2012). Above a pH of 7,
photobleaching induces a more rapid loss of DOC-specific
absorbance with increasing pH. Of our two primary study
lakes, only Lake Giles (pH 5.4–6.1) is likely to be influenced
by recovery from acid precipitation, because Acton has
a pH of 7.6–9.1 and a very high buffering capacity
(, 3000 meq L21). While in Giles we observed no significant
relationship between CF and pH (p 5 0.15), the trend was
positive. We suspect that pH may play some role in the
observed interdecadal response of the CFOI because the pH
in the lake increased from 5.4 in 1993 to 6.3 in 2012. In Acton
we observed a highly significant inverse relationship between
CF and pH (r2 5 0.63, p , 0.01). Both of these patterns are
consistent with what has been previously observed with the
effects of pH on photobleaching (Pace et al. 2012). However,
the relationship between pH and CF could also be driven by
the fact that high runoff events carry a higher portion of
water that has not passed through the calcic bedrock, while
at times of low flow stream water contains a greater portion
of groundwater flow. The relationship between DOC and
pH is complex because influx of DOC during rain events can
alter pH, and the response will depend on the nature of the
soils in the catchment as well as on the hydrology of a
particular lake. In spite of these caveats about pH and DOC
quality, the similarity of the responses of the CFOI across
lakes of very differing pH and multiple timescales remains
compelling and argues against acid deposition playing a
dominant role in the patterns that we observed. The
relationship between the CFOI response and pH remains
intriguing, however, and needs more investigation.
On a more general level, the debate over the role of
pH and other drivers of the observed trends in DOC
concentration has yet to be resolved. While the relative
importance of different drivers is likely to vary regionally,
climate clearly plays an important role. In Europe, analysis
of some of the largest data sets has shown climate to be
highly correlated with DOC concentration (Weyhenmeyer
and Karlsson 2009). Climate change is also predicted to
increase future DOC concentrations in boreal lakes by as
much as 65% as a result of warming increasing terrestrial
vegetation (Larsen et al. 2011). A wide range of studies
have clearly demonstrated the link between precipitation
and increases in DOC concentrations during recovery from
drought (Schindler et al. 1996), wetter climates in the
springtime (Pace and Cole 2002), and heavy rainfall
associated with global oscillations such as the Atlantic
Multidecadal Oscillation (Gaiser et al. 2009). Even in
regions where recovery from acidification has been a clear
contributor to regional increases in DOC, precipitation and
incident solar radiation appear to provide similar, if not
better, explanatory power than pH for observed trends of
Lakes as climate sentinels
847
increasing DOC and decreasing transparency (Gunn et al.
2001; Zhang et al. 2010; Couture et al. 2012). Similarly, in
58 Adirondack lakes with pH values between 4.2 and 7.0
there was no significant explanatory power of pH in terms
of predicting variation in PAR, UV transparency, DOC
concentration, or DOC-specific absorbance at 440 nm
among lakes within a single year (Bukaveckas and
Robbins-Forbes 2000). Our work extends this prior work
by demonstrating the central importance of precipitation
and incident solar radiation in driving changes in DOC
quality, as well as in demonstrating a smaller role for
temperature.
Fig. 3. Conceptual model showing the response of lake
ecosystems to warmer vs. wetter climate regimes. These two
extremes of climate forcing both increase thermal stratification
but have opposite effects on water transparency and ecological
consequences, signaled by changes in the climate forcing optical
indices, including DOC-specific absorbance (a*320), spectral slope
(S275–295), and overall climate forcing, the ratio of a*320 to S275–295
(CF). Warmer climate regimes will lead to greater water
transparency (reducing a*320, increasing S275–295) and consequently more autotrophic, nutrient-limited conditions where the
ecological consequences include less (2) oxygen depletion and
lower (2) zooplankton food quality but positive (+) effects on all
other listed ecological consequences (see + and 2 in left column).
Wetter climate regimes will increase terrestrial DOC inputs to
lakes, reducing water transparency and consequently leading to
more heterotrophic, light-limited conditions (increasing a*320,
reducing S275–295) where the effects on the ecological consequences
are the opposite effects of those of warming (see + and 2 in
right column).
Conceptual model—The effects of climate change on
lakes have been demonstrated repeatedly. Yet there
remains an urgent need to identify key sentinel responses
to develop a more coherent framework with which to
address the contrasting effects of temperature and precipitation components of climate change and their ecological
consequences for lake ecosystems. What signals are
ecosystems giving us that can help to reveal their responses
to these two primary components of climate change? Here
we present a conceptual model within the context of
climate-driven changes in DOC quality and concentration
and discuss past findings in order to better understand the
sentinel responses of lakes to these two very different, but
interrelated, climate drivers (Fig. 3).
In spite of the contrasting effects of warmer vs. wetter
conditions on water transparency, both higher temperatures and increases in precipitation will increase the
strength of thermal stratification of lakes (Fig. 3). Modeling efforts have long suggested that warmer air temperatures will lead to both shallower and warmer surface mixed
layers and longer and stronger periods of thermal
stratification (De Stasio et al. 1996). These modeling
efforts are supported by extensive empirical data. For
example, a compilation of long-term data from lakes across
the Northern Hemisphere showed trends of increasing
surface-water temperatures in 11 out of 16 lakes (Adrian et
al. 2009). Data from both remote sensing and actual in-lake
measurements indicate that the water temperatures of large
lakes are warming at almost twice the rate of air
temperatures in the same regions (Schneider et al. 2009).
Comparison of two lakes in Switzerland following the
European heat wave of 2003 showed warmer surface-water
temperatures but also thermal stratification and Schmidt
stability values that exceeded the values for the prior 1956–
2002 period by 4–5 standard deviations (Jankowski et al.
2006). Analysis of 35 yr of data (1955–1992) in the 26-kmlong South Bay of Lake Huron revealed that periods with
warmer air temperatures and higher solar radiation were
characterized by warmer surface waters and shallower
thermoclines (King et al. 1997). A study of 86 small boreal
lakes during a cool year and two warm years found that
warmer air temperatures were related to warmer surfacewater temperatures, shallower mixed layers, and stronger
thermal stratification (Snucins and Gunn 2000). In this
study the deep waters of clear lakes warmed while those of
higher DOC, more colored lakes either did not change or
even showed a cooling during the warmer years. Lake
848
Williamson et al.
cooling has actually been observed during periods of
unchanging air temperatures when increases in DOC
concentration decrease water transparency (Tanentzap et
al. 2008). Higher precipitation increases loading of terrestrial
DOC to inland waters, which reduces water transparency,
leading to more absorption of sunlight in the surface waters,
shallower mixed layer depths, and stronger thermal stratification (Read and Rose 2013). Our own work reported
above shows that increases in precipitation increase not only
DOC concentration but also the DOC-specific absorbance
(a*320). These increases in a*320 further enhance the amount
of solar radiation absorbed in the surface waters of lakes and
decrease the heating of deeper strata, increasing the strength
of thermal stratification beyond the effects of DOC
concentration alone. Thus, both warmer and wetter
conditions combined will lead to particularly strong
increases in thermal stratification, consistent with our
observation that the warmest and wettest year from our
multiyear data set also had the highest CF value.
During a 20 yr period with severe drought involving
trends of increasing air temperature (2uC) and decreasing
precipitation, small boreal lakes exhibited a trend of
increasing mixing depth (Schindler et al. 1996). This
increase in mixing depth was associated with an increase
in wind speed. Consistent with prior studies on the effects
of warming on lakes and our conceptual model (Fig. 3), in
this study we did observe an increase in transparency
(Secchi) due to decreases in DOC as well as increases in
volume-corrected lake temperature. Volume-corrected lake
temperature and air temperature increased by about the
same amount (0.108uC yr21 and 0.107uC yr21, respectively)
over the 20 yr period from 1969 to 1988. More information
on DOC quality obtained through the suite of CFOI
variables proposed here would further elucidate the
importance of DOC source and processing that likely
underlies these observed sentinel responses.
Optical differences in DOC quality have important
ecological consequences related to water transparency and
thermal stratification (Fig. 3). One of the most important
ecological consequences is that periods of warmer surface
waters and stronger thermal stratification can both depress
primary production (O’Reilly et al. 2003) and favor toxinproducing cyanobacteria (Carey et al. 2012). Periods of higher
precipitation that increase DOC can similarly favor cyanobacteria and shift the trophic structure of pelagic communities
(Bastidas Navarro and Modenutti 2012). In Lake Zurich,
which provides drinking water for 1.5 million people,
increased thermal stratification has led to an increase in the
abundance of the toxic cyanobacterium Planktothrix rubescens. This is a non–nitrogen fixing species that in contrast to
many cyanobacteria shows optimal growth under colder
conditions and low light (Posch et al. 2012). Deep annual
holomixis to depths that burst buoyancy-regulating gas
vacuoles is the primary source of mortality for this inedible
cyanobacterium. Stronger thermal stratification reduces
mixing to the damaging deeper depths, thereby permitting
this species to grow throughout the year and increasing its
population size in recent decades (Posch et al. 2012).
Other ecological consequences of increased DOC and
a*320 and reduced photobleaching and S275–295 include a
shallower compensation depth, more oxygen depletion
in deep waters, shallower chlorophyll maximum and
zooplankton distributions, reduced amplitude of zooplankton vertical migration, and alteration of the refuge from
visual predators as well as timing and strength of critical
phenological events such as the clear-water phase (Fig. 3).
Shallower vertical distributions of zooplankton related
to decreasing UV transparency following even a single
extreme storm event in 2006 have been demonstrated (Rose
et al. 2012). In contrast, drought-induced increases in lake
water residence time and incident sunlight will increase
DOC photobleaching with consequent increases in S275–295
and decreases in a*320 and corresponding increases in water
transparency and mixing depth (Figs. 1, 3). Associated
increases in DOC biolability, water transparency, and light :
nutrient ratios lead to decreases in food quality for zooplankton and fish by increasing the carbon : phosphorus ratio
(Dickman et al. 2008). The ecological consequences of increases
in DOC combined with warming temperatures have been
demonstrated to be lake-specific depending on food chain
length (Hansson et al. 2012). Warmer water temperatures can
also cause shifts in zooplankton community structure, favoring
species that either have a higher physiological tolerance for
warmer temperatures or that have higher growth rates at
warmer temperatures (Wojtal-Frankiewicz 2012). Increased
DOC loading also increases the cost of water treatment by
increasing the production of carcinogenic disinfection by-products in drinking water supplies (Beggs and Summers 2011) and
reducing water disinfection of parasites and pathogens by
sunlight (Overholt et al. 2012). The dependence of these
noxious chemical reactions on DOC quality is unknown but
will be altered by climate change (Figs. 1–3).
Recent advances in optical and other sensor technologies
make the ‘‘lakes as sentinels’’ approach particularly amenable to use in ecological observatory networks (EONS) such
as the Global Lake Ecological Observatory Network
(GLEON) and the U.S. National Ecological Observatory
Network (NEON). These EONS are playing a key role in
establishing both the broadscale networking of sites as well
as the computational and analytical infrastructure necessary
for deciphering macrosystem-scale ecological processes. Yet
EONS are also producing massive amounts of data that are
a challenge to manage. One strategy for ‘‘staying afloat in
the sensor deluge’’ (Porter et al. 2012) is to use targeted
approaches involving specific indices, such as the CFOI
metrics, coupled with high-frequency data to enable new
insights into ecosystem-level responses to climate change.
Acknowledgments
We thank Wiebke Boeing, Janet Fischer, Evelyn Gaiser,
Weston Nowlin, John Melack, Mark Olson, Jasmine Saros, and
Hilary Swain for help and logistics in collecting water samples that
contributed to the 35 lake data set and the late Robert E. Moeller
for contributing to earlier discussions regarding indices to look at
the shifting balance between hydraulic flushing and photobleaching. Comments from two anonymous reviewers improved an
earlier version of this manuscript. We also thank the GLEON for
providing forums at their meetings for presenting and discussing
some of the ideas presented here with the broader limnological
community as well as for travel support for some of the coauthors who attended these meetings. This work was supported
Lakes as climate sentinels
in part by National Science Foundation grants from the Division
of Environmental Biology (DEB)-0734277, DEB Integrated
Research Challenges in Environmental Biology-0552283, and the
Division of Graduate Education-0903560.
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Associate editor: Dariusz Stramski
Received: 02 October 2013
Accepted: 27 January 2014
Amended: 04 February 2014