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SUPPLEMENTARY MATERIAL: EXTENDED METHODS
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Title: Warming alters food web-driven changes in the CO2 flux of experimental pond
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ecosystems
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Experimental design
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Using a 2 x 2 x 2 factorial design we manipulated temperature (+3˚ C), nutrients
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(nitrogen and phosphorus), and presence of predators (Gasterosteus aculeatus) to test their
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interactive and individual effects on consumer biomass, primary producer biomass, and
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dissolved CO2 concentrations. Experiments were performed in 40, well mixed, open-air,
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experimental ponds (surface area = 2.16 m2) located at the Experimental Pond Facility at the
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University of British Columbia, Vancouver, Canada. Mesocosms were filled with 1,136 L of
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municipal water and left to de-chlorinate for one week prior to the assembly of food webs.
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Experimental food webs were assembled by inoculating mesocosms with ~20
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zooplankton taxa, ~ 50 phytoplankton taxa, and microbes from nearby ponds[1]. Zooplankton
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and phytoplankton were collected from nearby ponds using 64 µm-mesh conical tow nets.
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Additionally, 1 L of sediment containing eggs, spores, and microbes was added from nearby
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ponds to aid in community assembly. Aquatic insects naturally dispersing from adjacent
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freshwaters colonized the mesocosms throughout the experiment. Food webs were left for three
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weeks before the addition of experimental treatments.
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Mesocosms were randomly assigned one of eight treatments and replicated five times.
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Temperature manipulations, hereafter referred to as warming treatments, were achieved by
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warming ponds to 3.04˚ ± 0.05˚ C (mean ± s.e.) above ambient pond temperatures using 300 W
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submersible water heaters (Hagen, Montréal, Québec, Canada). A 3˚ C increase in ambient
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temperature falls within the range of predicted temperature projections for Northern Hemisphere
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temperate zones over the next 100 years [2]. Temperatures of all mesocosms were monitored
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using HOBO Pendant data loggers (Onset Computer Corp. Bourne, Massachusetts, USA) in 30
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min intervals. Mean water temperatures during May sampling for warmed and ambient
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mesocosms were 19.4 ± 0.3 and 16.1± 0.3˚ C. Mean water temperatures during October
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sampling for warmed and ambient mesocosms were 17.6 ± 0.8˚ C and 14.3 ± 0.7˚C,
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respectively. We manipulated nutrients through monthly additions of 264 µg of nitrogen/L (as
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NaNO3) and 27 µg of phosphorus/L (as (KH2PO4), resulting in a N:P molar ratio of 22 [1]. These
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nutrient additions represent the top end of a meso-eutrophic state for Canadian lakes[3]. Five,
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Three-Spined Stickleback (2.8 individuals m-2 of surface water) of 52.4 ± 0.05 mm in standard
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body length were added per tank as predator treatments. The open nature of the tanks allowed a
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small amount (5-10 leaves over the study period) of terrestrial leaf litter to accumulate in the
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tanks. Stickleback densities were within range of natural densities (< 1 individuals m-2 to > 25
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individuals m-2[4,5]). In the event of death, Stickleback were removed from the tank and
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replaced with a similar-sized fish. Stickleback were used because they are generalist predators
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that are found throughout freshwater ecosystems in British Columbia and have been documented
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to exert strong top-down effects on plankton and benthic macroinvertebrates [6].
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Organism Sampling
Consumers, primary producers, and in situ CO2 concentrations were measured on two
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dates during the 2010 growing season (May and October), starting 336 d after the
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implementation of experimental treatments. We chose these sampling date for three reasons: 1)
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May represents the beginning and October represents the end of the primary growing season for
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phytoplankton[1], 2) this time-frame encompasses the periods of maximum macroinvertebrate
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abundance (i.e. prior to summer emergence and after summer oviposition), and 3) the potential
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for surface waters to freeze was very low. Phytoplankton biomass was measured with in vivo
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fluorometry (Trilogy, Turner Designs, Sunnyvale, California, USA) using the concentration of
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chlorophyll a in the water column. Periphyton biomass was determined fluorometrically from
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algal growth collected from 25 mm2 unglazed tiles. Zooplankton were collected using 10 L,
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depth-integrated zooplankton samples, filtered through a 64 µm-mesh sieve. Phytoplankton
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biomass and periphyton biomass were added together to get total primary producer biomass.
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Spatial variation of zooplankton biomass within the ponds was minimized by pooling samples
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from multiple depths and locations within the tank [1]. Zooplankton were identified (usually to
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genus), counted, and measured under a 10x magnification. Biomass of zooplankton was
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estimated using length-mass regressions [1]. Benthic macro-invertebrates were sampled by
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summing together organisms collected from the bottom and walls of the tank. Macro-
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invertebrates on the bottom of the ponds were sampled with standard sweeps within a 0.02 m2
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cylinder, in two areas of the pond. Macro-invertebrates inhabiting the walls of the ponds were
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collected by sweeping two locations of the wall from the bottom of the pond to the water’s
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surface using a 12 cm, 0.5 mm-mesh net. Macro-invertebrates were identified and measured, and
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their biomass calculated using length-mass regressions [7]. Biomass of both benthic and pelagic
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consumers (not including G. aculeatus) were combined to estimate total consumer biomass.
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Biomass was converted to g C m-2 for all organism groups by dividing grams of carbon
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per tank by the tank surface area. Grams of carbon were estimated by assuming a carbon biomass
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to chlorophyll biomass ratio of 1:40 for phytoplankton [8,9], 1:50 for periphyton [10], and an
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average carbon content of 48% of dry mass for zooplankton [11] and 51.8% of ash-free dry mass
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for benthic invertebrates [12].
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Statistical analyses
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Standard errors represented in the graphs for each of the fixed effects within the model were
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approximated using the “predictSE.lme()” function in the “AICcmodavg” package in R 3.1.1 (R
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Development Core Team, 2014). This function calculates predicted values based on fixed
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effects, and standard errors are approximated from the linear mixed effects model using the delta
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method [13]. Calculating standard errors from the LME model has the advantage that error
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assigned to random effects has been accounted for in the estimates.
Table S1: Percent contribution of different taxonomic classes/orders and genus/family and total biomass for each of the eight
treatments: control (C), nutrient addition only (N), addition of a zooplanktivorous predator (P), 3o C increase in temperature (W),
nutrient + fish addition (NP), nutrient + warming addition (NW), predator + warming addition (PW), and nutrient + predator +
warming addition.
Class/Order
Benthic
Invertebrates
Coleoptera
Coleoptera
Coleoptera
Diptera
Diptera
Diptera
Diptera
Diptera
Ephemeroptera
Ephemeroptera
Hemiptera
Hemiptera
Hirudinea
Gastropoda
Gastropoda
Gastropoda
Odonata
Odonata
Odonata
Oligochaeta
Trichoptera
Genus/Family
C
P
N
W
NP
NW
PW
NPW
Agabinae
Hydrophilidae
Hydroporinae
Chironomini
Chaoborus
Ceratopogonidae
Tanypodinae
Orthocladiinae
Callibaetis
Caenis
Notonecta
Corixidae
0.0
0.0
0.0
9.4
5.6
5.3
0.5
0.0
6.9
0.2
5.2
0.4
4.9
2.3
2.2
0.0
28.0
13.9
0.0
7.5
7.9
0.0
0.0
0.0
8.7
0.0
29.2
2.7
0.4
0.0
0.0
13.9
0.8
0.0
0.0
7.3
0.0
0.0
0.0
0.0
1.0
36.1
0.0
0.0
0.0
9.6
0.6
14.1
7.3
0.1
22.0
0.0
8.2
0.8
0.0
10.7
7.1
4.9
0.0
3.3
9.0
1.4
1.0
0.0
0.0
0.0
4.2
0.0
3.4
0.0
0.7
0.2
0.3
7.3
0.1
0.0
0.0
1.9
0.0
0.0
80.4
0.0
0.1
1.3
0.0
0.0
0.0
28.8
0.0
35.7
3.9
0.2
0.0
0.0
0.2
0.0
0.0
0.0
19.0
0.0
0.0
0.0
0.0
3.6
8.7
0.0
0.0
0.0
1.1
0.4
0.7
0.3
0.0
0.5
0.0
4.1
1.8
0.0
7.9
0.6
6.0
0.4
75.2
0.0
1.0
0.0
0.0
15.5
0.0
3.9
0.0
0.7
3.7
0.1
0.0
0.0
0.0
0.0
0.0
0.0
1.1
0.0
0.0
74.5
0.0
0.5
0.0
0.1
0.0
0.0
5.4
0.0
6.6
0.9
0.0
0.6
0.0
0.0
0.0
0.0
10.3
4.0
0.0
0.0
66.1
0.0
5.3
0.6
Physa
Menetus
Lymnaea
Aeshna
Libellulidae
Ishnura
Leptoceridae
Table S1
continued
Zooplankton
Chydoridae
Chydoridae
Cladocera
Cladocera
Calanoida
Cyclopoida
Ostracoda
Monogononta
Eurotifera
Monogononta
Eurotatoria
Sididae
Alona
Chydorus
Ceriodaphnia
Daphnia
Brachionus
Keratella
Lecane
Monostyla
Diaphanosoma
1.4
35.1
9.4
26.4
3.5
1.7
2.4
0.0
19.1
0.0
1.1
0.0
0.7
16.3
0.0
0.3
2.0
0.1
2.5
0.0
77.5
0.0
0.6
0.0
0.4
12.3
0.3
21.3
10.9
0.4
5.5
0.0
48.6
0.0
0.1
0.2
0.4
1.4
2.4
60.0
5.8
2.8
0.7
8.4
13.5
0.0
0.0
4.6
0.3
1.2
0.0
1.9
84.4
0.6
3.2
0.0
5.9
0.0
2.6
0.0
0.5
0.0
35.8
0.0
9.8
3.1
2.7
0.2
29.6
0.0
0.2
18.1
0.4
0.0
0.1
9.8
4.2
0.9
30.8
0.1
49.8
0.0
0.0
3.7
2.3
0.0
11.1
0.0
2.3
1.4
3.8
0.0
50.0
0.0
22.3
Table S2: Mean (± s.e.) for total consumer biomass, total primary producer biomass and CO2
flux for our eight treatments: control (C), nutrient addition only (N), addition of a
zooplanktivorous predator (P), 3o C increase in temperature (W), nutrient + fish addition (NP),
nutrient + warming addition (NW), predator + warming addition (PW), and nutrient + predator +
warming addition.
Treatment
C
N
P
W
NP
NW
PW
NPW
Consumer biomass
(g C m-2)
0.12 (0.03)
0.37 (0.08)
0.04 (0.01)
0.21 (0.11)
0.12 (0.04)
0.75 (0.15)
0.15 (0.07)
0.22 (0.10)
Primary biomass
(g C m-2)
0.37 (0.04)
1.35 (0.17)
0.49 (0.06)
0.23 (0.03)
10.05 (3.21)
0.73 (0.10)
0.43 (0.06)
0.98 (0.16)
CO2 flux
(mg C m-2 d-1)
14.34 (8.17)
-50.33 (15.17)
-61.45 (12.34)
8.14 (10.02)
-86.52 (11.47)
10.13 (10.88)
11.41 (9.18)
-23.89 (7.75)
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