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Warming Alters the Metabolic Balance of Ecosystems
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3
Supplementary Material
4
5 Gabriel Yvon-Durocher1, J. Iwan Jones2, Mark Trimmer1, Guy Woodward1 and
6 Jose M. Montoya1, 3
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8
1
School of Biological & Chemical Sciences, Queen Mary University of London, London
9 E1 4NS. U.K.
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2
Centre for Ecology and Hydrology, MacLean Building, Benson Lane, Crowmarsh
11 Gifford, Wallingford, OX10 8BB, UK.
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3
Institute of Marine Sciences (ICM-CSIC) Pg. Marítim de la Barceloneta, 37-49
13 E-08003 Barcelona, Spain
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16 Corresponding authors: Gabriel Yvon-Durocher (g.yvon-durocher@qmul.ac.uk)
17 and José M. Montoya (montoya@icm.csic.es)
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19
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20
21 S1. Quantitative prediction for changes in ecosystem metabolic balance in response
22 to warming.
23 The ratio RH:U of the metabolic balance between heated and unheated systems can be
24 expressed as:
25
(I)
RH :U 
ERH
ERU
ERH GPPU
/


GPPH GPPU GPPH ERU

26 Substituting ER and GPP by their allometric equations we get:
27
28
RH :U
nh
1  na

1 na  Ep / kTu  , a
Mi
 1   e  Ep / kTh M i , a   M i , h r0 e  Er / kTh 
e

V i 1
V i 1
i 1



nh
1 na  Ep / kTh  , a
1  na

Mi
e
 1   e  Ep / kTu M i , a   M i , h r0 e  Er / kTu 

V i 1
V i 1
i 1

(II)
29 ER is the sum of both heterotrophic and autotrophic respiration. For simplicity, and in
30 order to get a quantitative prediction that does not require many parameters, we assume
31 that that during non-steady state dynamics as was the case in our mesocosm experiment,
32 the temperature dependence of heterotrophic respiration is unconstrained by NPP (i.e. the
33 available contemporary carbon substrate) (see main text for empirical justification). This
34 implies that the temperature response of ecosystem respiration is mainly driven by
35 heterotrophic metabolism because Er > Ep as has been shown for marine oceanic
36 ecosystem (Lopez-Urrutia et al. 2006, Lopez-Urrutia & Moran 2007). During non-steady
37 state dynamics heterotrophic metabolism can increase at maximum capacity, getting
38 ahead of NPP and dominating the respiratory response of the ecosystem. Thus, given this
39 assumption, we can remove the term for autotrophic respiration from equation (II). As
40 such the ratio RH:U is given now by:
3
nh
na
1 Er
/kT
 1 
Ep
/kT

H
U
r
e
M
n
e
M


0
i
0
i
V
V
i
1
i
1
R

H
:
U
nh
na
1 Er
1


Ep
/kT

U
H
r
e /kT
M
n
e
M


0
i
0
i
V
V
i
1
i
1
41
(III)
42 We can then simplify equation (III) to get:

43
U
eEr/kTH eEp/kT
R


H
:U
U
eEr/kT
eEp/kTH
(IV)
44 By rearranging terms in equation (IV) we get:
45

[(
Ep

Er
)
/
kT
]

(
Er

Ep
)
/
kT
H
U
R

e
H
:
U
(V)
46 Which can be rearranged to get equation (6) in the main text as follows:
47

(Er
Ep
)(THT
U)
kT
T
HU
R
H
:Ue
(VI)
48 Equation (6) provides a simple yet informative approximation for the behaviour of the
49 metabolic
balance between heated and unheated systems while using minimal
50 parameterisations, and making the assumption that heterotrophic respiration dictates
51 ecosystem respiration in transient dynamics between different steady-states. Importantly,
52 at steady state, where ER is limited by contemporary primary production we would
53 expect to see no shift in the metabolic balance of an ecosystem. This may be the case
54 over geological time scales, but for temporal scales relevant to the effects of global
55 warming (i.e. decades) an understanding of transient non-steady state dynamics is
56 fundamental.
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57 S2. The dissolved oxygen change technique
58
The dissolved oxygen change technique assumes that changes in dissolved oxygen
59 concentration over a diel cycle represent the metabolic activity (photosynthetic and
60 respiratory) of an aquatic ecosystem and can be used to estimate fundamental
61 components of the carbon cycle in freshwater ecosystems. Apart from biological
62 metabolic activity an additional factor affecting DO concentration is diffusive exchange
63 with the atmosphere. The diffusion of oxygen across the air-water interface is dependent
64 on the solubility of oxygen in water, which generates the driving force (i.e. concentration
65 gradient between the water and the overlying air) for diffusion, and the diffusivity
66 constant. Diffusive gas exchange across the air-water interface is well described by the
67 theory of gas exchange:
68
Flux  ka (C sat  C water )
(VII)
69 where k is the diffusivity constant (cm2 s-1), a is the surface area to volume ratio of the
70 water body, Csat – Cwater is the concentration gradient between the concentration of gas in
71 the water and the concentration that would be at equilibrium with the atmosphere.
72 Importantly, k can be affected by wind velocity (Cole & Caraco 1998). However, in the
73 present study wind velocity was not was not corrected for because measured wind
74 velocities were typically very low (average 0.53 m s-1), with only 2.22% of measurements
75 above 3 m s-1 : gas exchange is largely independent of wind velocity at < ~3 m s-1. (Cole
76 & Caraco 1998). Furthermore, gas exchange due to diffusive flux alone was considered
77 insignificant and ignored for a number of reasons. Firstly, the diffusive capacity of
78 oxygen into and out of water is extremely low compared with other processes (i.e.
79 advection or biological consumption/production). For instance, diffusive flux was a
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80 vanishingly small proportion of the total oxygen pool of the mesocosm. For instance in
81 August in pond 1 (heated) the mean ratio of gas transfer to the total oxygen pool (i.e. the
82 concentration of O2 multiplied by the volume of the mesocosm) was 0.0013 (95%
83 confidence interval, 0.0011 to 0.0015) (i.e. 0.13%). Therefore, we can be confident that
84 the clear diel signal in oxygen change (see S5) is due almost entirely to biological
85 metabolism and that abiotic factors such as diffusion and re-aeration through the
86 turbulent effects of wind velocity (because velocity was below 3 m s-1) are comparatively
87 insignificant.
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Second, as previously stated gas flux across the air-water interface is driven by
89 two main factors, the concentration gradient and the diffusivity constant (equation VII).
90 Both of these parameters are dependent on temperature, but in different ways. The
91 diffusivity of oxygen in water decreases with increasing temperature which leads to
92 reduction in the driving force. Conversely, the diffusion rate of oxygen increases with
93 increasing temperature. The counteraction of these processes results in the oxygen
94 transfer rate across the air-water interface remaining approximately constant over a given
95 temperature range (i.e. 0-35 °C difference (Vogelaar et al. 2000). To demonstrate this we
96 calculated the rate of gas transfer due to diffusion in each 15 minute time interval
97 corresponding to the frequency of dissolved oxygen measurements (see methods) using
98 equation (VII). We then compared the mean rate of gas transfer over 24 hours between a
99 heated and unheated treatment (ponds 1 and 2). In line with our expectations we found
100 that there was no significant difference in the mean rate of gas transfer between heated
101 (mean = 0.65 µmol cm-2 15min-1 95% CI = 0.57 to 0.74) and unheated (mean = 0.57
102 µmol cm-2 15min-1 95% CI = 0.49 to 0.64) treatments. Therefore, because heated and
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103 unheated treatments were measured simultaneously, heated and unheated mescosms were
104 assumed to experience equivalent (and insignificant) atmospheric gas exchange regimes
105 over the diel cycle.
106
YSI 600XLM multiparameter Sondes equipped with 6562 rapid pulse™ dissolved
107 oxygen sensors were deployed for 24 hours in each heated and unheated treatment pair on
108 each of the six sampling occasions over the year. Measurements of DO, temperature and
109 pH were taken every 15 minutes for 24 hours at mid depth (0.25m) in the water column
110 of each pond. At the beginning of each sampling occasion the calibration of each Sonde
111 was tested by deploying both Sondes in the same pond for 1 hour to ensure equivalence
112 in DO readings, and re-calibration was carried out when necessary. Subsequently, prior to
113 deployment in each treatment pair, the Sondes were calibrated in water-saturated air with
114 a correction for barometric pressure. Calibration accuracy was verified by monitoring the
115 DO concentration of water-saturated air for 10 min and checking against 100% O2
116 saturation for the measured temperature and pressure.
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It should be noted that current biogeochemical techniques presently preclude the
118 disentanglement of autotrophic and heterotrophic respiration at the ecosystem level
119 (Mulholland et al. 2001) and preclude the estimation of photorespiration (Marzolf et al.
120 1994). As such, measures of GPP using the DO change technique may be slightly
121 overestimated given the inclusion of heterotrophic respiration in calculation of Rday.
122 Furthermore, in agreement with other studies it was not possible to isolate heterotrophic
123 respiration (resulting in O2 consumption) from our measures of NPP (Bales 2007), so
124 NPP estimates may be slightly underestimated.
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128 S3. Annual temperature differences between heated and unheated treatments. Example of
129 temperature regimes over the course of the experiment for a heated and unheated
130 treatment pair. Pond 1 (Heated; Red) and Pond 2 (Unheated: Black). The mean
131 temperature difference over the year was 4.8°C, ± 0.0096.
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134 S4. Diel temperature differences between heated and unheated treatments. Example of
135 diel temperature regimes for a heated and unheated treatment pair. Pond 1 (Heated; Red)
136 and Pond 2 (Unheated: Black).
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140 S5. Calculation of NPP, GPP, and ER from diel oxygen profiles. Diel Oxygen profiles
141 for Pond 1 (heated) on the 5th June 2007. (a): Dissolved oxygen concentration (μmol l-1)
142 (b) dissolved oxygen change (μmol O2 l-1 15mins-1). Net primary production (NPP) was
143 calculated as the sum of all oxygen change values during the day (i.e. vertical lines above
144 zero). Gross primary productivity (GPP, vertical lines) was calculated by the addition of
145 NPP and day respiration (Rday, cross hatched area) (i.e. sum of all vertical lines).
146 Ecosystem respiration (ER) was calculated as the integral of the region indicated by
147 horizontal lines.
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150
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Treatment Pair Mean Temperature difference (°C)
± SE
P1+P2
4.802
0.010
P3+P4
N/E
N/E
P5+P6
3.862
0.013
P7+P8
4.700
0.012
P9+P10
4.050
0.015
P11+P12
2.959
0.016
P13+P14
3.885
0.011
P15+P16
4.337
0.013
P17+P18
3.832
0.018
P19+P20
4.727
0.016
Overall mean
4.128
0.010
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152 S6. Summary of the temperature differences between heated and unheated treatments
153 over the course of the experiment (April 2007-April 2008). No data were available for
154 ponds 3 and 4 due to failure of the data loggers (N/E).
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Group
Taxa
Vasular Plants
Elodea canadensis
Myriophyllum spicatum
Ceratophyllum spicatum
Chara contraria
Potamogeton berchtoldii
Potamogeton natans
Alisma plantago-aquatica
Micrasterias crux-melitensis
Closterium costatum
Xantidium
Staurastrum
Netrium digitus
Pediastrum
Volvox
Chlorella
Spirogyra
Zygnema
Keratella Quadrata
Keratella cochlearis
Brachionus
Ostracoda
Chironomidae
Daphnia magna
Bosmina
Cyclops
Calanoida
Harpacticoida
Aspidisca costata
Coleps hirtus
Cinetochilum margaritaceum
Sathrophilus
Cyclidium brandoni
Cyclidium glaucoma
Halteria grandinella
Holophrya discolor
Acineria ucinata
Dexiotricha tranquila
Dexiotricha plagia
Loxodes rostrum
Prorodon farctus
Stichotricha secunda
Stichotricha aculeata
Phytoplankton
(Desmidae)
Phytoplankton
(Chlorophyta)
Zooplankton
Cilliates
Treatment
Heated and Ambient
Heated and Ambient
Heated and Ambient
Heated and Ambient
Heated
Ambient
Heated and Ambient
Heated and Ambient
Heated and Ambient
Heated and Ambient
Heated and Ambient
Heated and Ambient
Heated and Ambient
Heated and Ambient
Heated and Ambient
Heated and Ambient
Heated and Ambient
Heated and Ambient
Heated and Ambient
Heated and Ambient
Heated and Ambient
Heated and Ambient
Heated and Ambient
Heated and Ambient
Heated and Ambient
Heated and Ambient
Heated and Ambient
Heated and Ambient
Heated and Ambient
Heated and Ambient
Heated
Heated and Ambient
Heated and Ambient
Heated and Ambient
Ambient
Heated and Ambient
Heated and Ambient
Heated and Ambient
Heated and Ambient
Ambient
Heated and Ambient
Heated and Ambient
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Macroinvertebrates
Spirostomum
Stentor roselii
Strombidium humile
Strombilidium gyrans
Urotricha agilis
Oxytricha
Myriokaryon
Dytiscus marginarlis
Notonectidae
Corixidae
Baetidae
Ephemerella
Asellus aquaticus
Gammarus pulex
Anisoptera
Zygoptera
Lymnaea stagnalis
Trichoptera
Plecoptera
Heated and Ambient
Heated and Ambient
Heated and Ambient
Heated and Ambient
Ambient
Ambient
Ambient
Heated and Ambient
Heated and Ambient
Heated and Ambient
Heated and Ambient
Heated and Ambient
Heated and Ambient
Heated and Ambient
Heated and Ambient
Heated and Ambient
Heated and Ambient
Heated and Ambient
Heated and Ambient
164
165 S7. Species list for heated and ambient mesocosms. All taxa were recorded to the highest
166 possible taxonomic level, usually species, though in some cases only family or genus
167 level identification was possible.
168
169 References
170 Bales JD, and Nardi, M.R., (2007) Automated routines for calculating whole stream
171
metabolism. In: Theoretical background and users guide: US Geological Survey
172
Techniques and Methods 4-C2 (ed Bales JD, and Nardi, M.R.,). US Geological
173
Survey
174 Cole JJ, Caraco NF (1998) Atmospheric exchange of carbon dioxide in a low-wind
175
oligotrophic lake measured by the addition of SF6. Limnology and
176
Oceanography, 43, 647-656.
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177 Lopez-Urrutia A, Moran XAG (2007) Resource limitation of bacterial production distorts
178
the temperature dependence of oceanic carbon cycling. Ecology, 88, 817-822.
179 Lopez-Urrutia A, San Martin E, Harris RP, Irigoien X (2006) Scaling the metabolic
180
balance of the oceans. Proceedings of the National Academy of Sciences of the
181
United States of America, 103, 8739-8744.
182 Marzolf ER, Mulholland PJ, Steinman AD (1994) Improvements to the diurnal upstream183
downstream dissolved-oxygen change techniques for determining whole stream
184
metabolism in small streams. Canadian Journal of Fisheries and Aquatic
185
Sciences, 51, 1591-1599.
186 Mulholland PJ, Fellows CS, Tank JL, et al. (2001) Inter-biome comparison of factors
187
controlling stream metabolism. Freshwater Biology, 46, 1503-1517.
188 Vogelaar JCT, Klapwijk A, Van Lier JB, Rulkens WH (2000) Temperature effects on the
189
oxygen transfer rate between 20 and 55 degrees C. Water Research, 34, 1037-
190
1041.
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