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Supplemental Experimental Procedures
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Black cottonwood common garden
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In March of 2012, we created replicate clones of five black cottonwood genotypes. These five
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genotypes were selected from a large common garden experiment containing 461 black
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cottonwood genotypes originating from 136 provenance localities throughout much of their
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native range. This common garden was established in 2008 in Totem Field at the University of
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British Columbia in Vancouver, British Columbia (BC) as part of an extensive genome-wide
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association study (for further methodological details of the Totem common garden see [15]).
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The five genotypes were selected with the prerequisites that they were equally related and
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originated from southern BC localities (latitude range: 49-52 °N). The genotypes chosen varied
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in numerous traits including those related to phenology (e.g. bud set, leaf flush), growth rate,
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C:N ratio, and tannins [6,15]. For tree propagation methods, see [6].
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Mesocosm setup methods
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Mesocosms were constructed from 1136-L Rubbermaid cattle tanks (2 m in diameter, 1 m in
15
depth). Tanks were spaced 3 m apart and randomly assigned to a location in a 30 × 100 m grid
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on the campus of the University of British Columbia. Each tank was placed on a 3 × 3 m square
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of heavy-duty weed cloth to prevent vegetation growth in the immediate area and was filled with
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well water on June 18-20th, 2012. To establish an aquatic community in each mesocosm, we
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added water and 11.33 kg of sterilized play sand to each tank, which was allowed to settle for
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one week creating a ~ 1 cm sediment layer. We also inoculated each tank with phytoplankton
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and zooplankton taken from nearby experimental ponds and strained benthic mud from a nearby
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shallow lake (Browning Lake, Squamish, BC). Finally, we added 1.23 g NaNO3 and 0.09 g
1
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NaH2PO4 to each tank to initiate primary production. Supplemental water was added throughout
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the summer to compensate for evaporation and mesocosms were left uncovered to allow for the
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natural colonization of other aquatic invertebrates. For a more detailed description of the
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mesocosm set up procedure see [6].
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Community responses
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To examine the zooplankton community, we collected vertical columns of water using a PVC
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pipe (10 cm diameter × 110 cm) with care taken to sample water from the full depth of each
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mesocosm. A total of 11 liters of water was taken from each tank and sieved through 66 um
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mesh. Samples were stored in 90% ethanol and were stained with Rose Bengal solution before
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counting. Each individual in each sample was counted, measured, and identified to the lowest
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readily identifiable taxanomic unit. Abundance results are reported as counts per sample (i.e.
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number of individuals/11 liters).
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To understand how different cottonwood genotypes and fish ecotypes affected benthic
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invertebrates, we used a small dip net to collect three 120 cm2 scoops from different areas of the
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benthic substrate within each mesocosm [S2]. These samples were then combined and searched
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for live organisms by two people working simultaneously for ten minutes (i.e. a total of 20
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search minutes). Collected specimens were placed into 95% ethanol and were then counted and
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identified to the lowest feasible taxanomic unit. To sample the community of macro
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invertebrates in the water column, a rectangular net (24cm x 12cm) composed of 150um mesh
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was used to sweep the water column in a five pointed star pattern. This star was repeated two
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times after which collected specimens were placed into 95% ethanol and were later counted and
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identified to the lowest feasible taxonomic unit. Communities of both benthic and macro
2
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invertebrates were collected only once to avoid destructively sampling until the experiment was
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concluded.
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Ecosystem responses
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Tank-level gross primary productivity (GPP) productivity was estimated at 3-4 week intervals
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throughout the experiment using diurnal changes in oxygen levels [S2-S3]. Dissolved oxygen
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measurements were taken with an oxygen probe (YSI, Pro ODO2030, Yellow Springs, OH)
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three times per sample period: at sunrise (T0), sunset (T1), and the following sunrise (T2). Net
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primary productivity (NPP) was calculated as DOT1 - DOT0, respiration (R) as DOT1 - DOT2, and
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finally GPP as NPP + R.
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To understand how different tree and fish assemblages influenced the light environment, we
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measured photosynthetically available radiation (PAR) using a quantum sensor (LI-COR LI-193,
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LI-COR Biosciences, Lincoln, NE) at three time intervals during the experiment. We calculated
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the number of photons extinguished per centimeter of water using a measurement 5cm below the
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water surface and 5cm above the substrate at the bottom of each tank. The difference between
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these values was divided by the difference in the sample depths to give a measure of the amount
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of light extinguished per cm of depth ((PAR5cm below surface – PAR 5cm below maximum depth)/Maximum
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depth measurement - 5cm). PAR was measured only on days that were clear, to prevent clouds
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from impacting light readings at depth.
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To measure dissolved nutrients within each mesocosm, we filtered water through Whatman GF/F
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filters into acid washed dark plastic bottles and froze immediately. Samples were stored frozen
3
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and analyzed within four months of collection. We used a Lachat nutrient analyzer
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(ZellwegerAnalytics, QuikChem FIA AutoAnalyzer 8000 Series) to measure phosphorous (SRP)
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following [S4]. Ammonium was measured on a Trilogy fluorometer (Turner Designs) following
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[S5].
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Supplemental References
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1.
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Watkins, J.M., L. G. Rudstam and K. T. Holeck. (2011). Length-weight regression for
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zooplankton biomass calculations- a review and a suggestion for standard equations.
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Available at eCommons Cornell (http://ecommons.library.cornell.edu/handle/1813/24566).
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Accessed May 2013.
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2.
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Ingram, T., R. Svanbäck, N. J. B. Kraft, P. Kratina, L. Southcott, and D. Schluter. 2012.
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Intraguild predation drives evolutionary niche shift in threespine stickleback. Evolution 66:
81
1819–1832.
82
3.
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Wetzel, R. G. and Likens, G. E. (1991). Limnological analyses. Saunder College Publishing,
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New York, NY, second edition.
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4.
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Downing, A. L. (2005). Relative effects of species composition and richness on ecosystem
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properties in ponds. Ecology 86:701-715.
88
5.
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Murphy, J. and Riley, J., (1962). A modified single solution method for the determination of
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phosphate in natural waters. Analytica Chimica Acta 27:31
4
91
6.
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Holmes, R.M., Aminot A., Kerouel R., Hooker, B.A., Peterson, B.J. (1999). A simple and
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precise method for measuring ammonium in marine and freshwater ecosystems. Can. J. Fish.
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Aquat. Scie. 56:1801:1808).
95
7.
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Crutsinger, G.M., Rudman, S.M., Rodriguez-Cabal, M.A., McKown, A.D., Sato, T., MacDonald,
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A.M., et al. (2014). Testing a ‘genes-to-ecosystems’ approach to understanding aquatic-
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terrestrial linkages. Mol. Ecol. 23, 5888-5903.
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107
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Table S1: GLM Chi-square (or ANOVA) test results for community level responses seperated by
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taxonomic group for tree genotype (black cottonwood), Fish presence (stickleback), and the
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interaction between Tree genotype and Fish presence. If an ANOVA was used we report F, DF,
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and a p-value. If an GLM was used we report the Chisq, Df, and a P-value from a Chi-squared
118
test (Chi-sq are italicized). Degrees of freedom are lower in zooplankton tests due to one missing
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sample.
Effect
Macro invertebrates
Total richness
Menetus
snails
Notonectids
Benthic
invertebrates
Total richness
Chironomid
F/Chisq
DF
P-value
Tree genotype
2.94
4,44
0.063
Fish presence
18.81
2,44
<0.0001
Genotype ×
Fish presence
2.19
8,44
0.047
Tree genotype
32.34
4,44
<0.0001
Fish presence
27.89
2,44
<0.0001
Genotype ×
Fish presence
10.9
8,44
0.21
Tree genotype
2.81
4,44
0.59
Fish presence
61.93
2,44
<0.0001
Fish ecotype
34.14
1,29
<0.0001
Genotype ×
Fish presence
17.61
8,44
0.024
Genotype x
ecotype
15.57
4,29
0.003
Tree genotype
1.39
4,44
0.253
Fish presence
35.58
2,44
0.005
Genotype ×
Fish presence
0.72
8,44
0.676
Tree genotype
0.08
4,44
0.98
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abundance
Oligochaete
abundance
Zooplankton & Phytoplankton
Mayfly
abundance
Zooplankton
richness
Calanoid
abundance
Fish presence
6.63
2,44
0.003
Genotype ×
Fish presence
0.75
8,44
0.647
Tree genotype
2.6
4,44
0.626
Fish presence
3.54
2,44
0.17
Fish ecotype
4.74
1,29
0.029
Genotype ×
Fish presence
18.69
8,44
0.016
Genotype x
ecotype
19.92
4,29
0.0005
Tree genotype
34.27
4,44
<0.0001
Fish presence
79.09
2,44
<0.0001
Fish ecotype
1.06
1,29
0.3
Genotype ×
Fish presence
36.04
8,44
<0.0001
Genotype x
ecotype
9.77
4,29
0.05
Tree genotype
1.34
4,43
0.269
Fish presence
2.83
2,43
0.069
Genotype ×
Fish presence
0.55
8,43
0.814
Tree genotype
8.35
4,43
0.25
Fish presence
60.92
2,43
<0.0001
Fish ecotype
0.08
1,29
0.78
24.02
8,43
0.002
Genotype ×
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Fish presence
Bosmina
abundance
phytoplankton
Biomass (end
of study)
Stickleback
Genotype x
ecotype
6.93
4,29
0.14
Tree genotype
8.62
4,43
0.07
Fish presence
21.44
4,43
<0.001
Fish ecotype
1.27
1,29
0.26
Genotype ×
Fish presence
21.97
4,43
0.005
Genotype x
ecotype
13.47
4,29
0.009
Tree genotype
0.04
4,44
0.99
Fish presence
0.08
2,44
0.92
Genotype ×
Fish presence
1.16
8,44
0.34
Tree genotype
0.92
4,29
0.46
Fish ecotype
1.79
2,29
0.19
Genotype ×
Fish presence
0.73
4,29
0.58
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Table S2: ANOVA table for ecosystem level responses for tree genotype (black cottonwood),
130
fish presence (stickleback), and the interaction between Tree genotype and Fish presence. For
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SRP the effects of stickleback ecotype and the interaction between stickleback ecotype and tree
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genotype are shown. Degrees of freedom are lower in SRP due to one missing sample.
Effect
GPP
Light extinction
Soluble reactive
phosphorous
Total ammonia
F
DF
P-value
Tree genotype
2.81
4,44
0.036
Fish presence
1.2
2,44
0.311
Genotype × Fish
presence
0.33
8,44
0.948
Tree genotype
1.77
4,44
0.152
Fish presence
2.22
2,44
0.121
Genotype × Fish
presence
2.21
8,44
0.045
Tree genotype
1.91
4,43
0.125
Fish presence
8.75
2,43
0.0006
Stickleback ecotype
5.46
1,29
0.026
Genotype × Fish
presence
0.44
4,43
0.78
Genotype × Ecotype
2.76
4,29
0.041
Tree genotype
0.32
4,44
0.86
Fish presence
4.12
2,44
0.022
Genotype × Fish
presence
0.63
8,44
0.75
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Figure S1: Contribution of each black cottonwood genotype to the aquatic environment was
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measured by multiplying the total quantity of leaf litter deposited in each mesocosm (75% of the
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total litter produced by the trees) by the rate of litter decomposition (percent mass loss)
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determined for each genotype (details of decomposition study can be found in Crutsinger et al.
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2014). Decomposition rates were estimated in our prior work (see [6] for details).
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Figure S2: Data for light extinction, soluble reactive phosphorous, and phytoplankton abundance
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by tree genotype ordered by ascending productivity over a 9-month period (October 2012 to June
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2013). At the time when fish were introduced there were no significant differences between
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cottonwood genotypes in any of these three metrics. These time series figures illustrate how
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adding different ecotypes of fish impacted mesocosms already containing different genotypes of
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cottonwood leaf litter. NOTE: the data for light extinction and phytoplankton abundance in
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Fig.2 and table S2 represent the change over the course of the study (i.e. June-April).
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