DOI: 10.5061/dryad.05qfttf8b
title: Season-specific impacts of climate change on canopy-forming seaweed communities

description: Understory assemblages associated with canopy-forming species such as
 trees, kelps, and rockweeds should respond strongly to climate stressors
 due to strong interaction strengths. Climate change can directly and
 indirectly modify these assemblages, particularly during more stressful
 seasons and climate scenarios. However, fully understanding the seasonal
 impacts of different climate conditions on canopy-reliant assemblages is
 difficult due to a continued emphasis on studying single species responses
 to a single future climate scenario during a single season. To examine
 these more complex interactions, we used mesocosm experiments to expose
 intertidal assemblages associated with the canopy-forming golden rockweed,
 Silvetia compressa, to elevated temperature and pCO2 conditions reflecting
 two projected greenhouse emission scenarios [RCP 2.6 (low) & RCP
 4.5 (moderate)]. Assemblages were grown in the presence and absence of
 Silvetia, and in two seasons. Relative to ambient conditions, predicted
 climate scenarios generally suppressed Silvetia biomass and photosynthetic
 efficiency. However, these effects varied seasonally - both future
 scenarios reduced Silvetia biomass in summer, but only the moderate
 scenario did so in winter. These reductions shifted the assemblage, with
 more extreme shifts occurring in summer. Contrarily, future scenarios did
 not shift assemblages within Silvetia Absent treatments, suggesting that
 climate primarily affected assemblages indirectly through changes in
 Silvetia. Mesocosm experiments were coupled with a field Silvetia-removal
 experiment to simulate the effects of climate-mediated Silvetia loss on
 natural assemblages. Consistent with the mesocosm experiment, Silvetia
 loss resulted in season-specific assemblage shifts, with weaker effects
 observed in winter. Together, our study supports the hypotheses that
 climate-mediated changes to canopy-forming species can indirectly affect
 the associated assemblage, and that these effects vary seasonally. Such
 seasonality is important to consider as it may provide periods of recovery
 when conditions are less stressful, especially if we can reduce the
 severity of future climate scenarios.
description: MATERIALS AND METHODS Study site: 
 We selected sites adjacent to two southern California long-term
 monitoring sites; Navy South (32.68306 °N, -117.24963 °W; hereafter NASO)
 and Navy North (32.692312 °N, -117.25297°W; hereafter NANO). These
 Multi-Agency Rocky Intertidal Network sites (MARINe) contain dense patches
 of <em>Silvetia</em>, perhaps because of the rarity of some
 stressors such as trampling (Denis 2003, Tydlaska & Edwards 2022)
 and runoff (Whitaker et al. 2010). We surveyed the
 <em>Silvetia</em> assemblages, collected the algae and grazers
 used in the mesocosm experiment, and conducted the field experiment at
 NASO. We then added NANO as a secondary collection site.
 <em>Silvetia</em> at both sites grows on emergent substrata at
 intertidal elevations between 0-1 m above Mean Lower Low Water (hereafter
 MLLW). Average water temperatures at these sites are ~18 °C and maximum
 summer water temperatures reach ~24 °C (SeaTemperatures 2023). 
 Mesocosm experiment: <br><br>To examine the impacts
 of projected changes in ocean temperature and pH on <em>Silvetia
 </em>assemblages, we conducted a mesocosm experiment at San Diego
 State University’s Coastal Marine Institute and Laboratory (CMIL) that
 exposed the assemblages to three ocean climate conditions (Ambient, RCP
 2.6, RCP 4.5). Ambient conditions represent current levels of temperature
 and pH. RCP 2.6 is a global emissions pathway representing low levels of
 climate change that will be experienced in the year 2100 (in line with the
 theoretical stabilization of global emissions by ~2020 leading to an
 average change of +1 °C/-0.1 pH units on global oceans). RCP 4.5
 represents moderate levels of climate change (+2 °C/-0.2 pH units).
 Importantly, our experiments used flow-through seawater, which allowed for
 natural variation in ambient conditions. Thus, our future scenarios that
 manipulated pH and temperature relative to ambient conditions also
 experienced such variation. Each mesocosm consisted of
 a clear plastic box (15 x 15 x 7.6 cm; l*w*h) that had three 5-cm diameter
 holes in each of two opposite sides. Window screen mesh covered these
 holes and the box tops to retain box contents and allow water exchange. We
 crossed climate scenario (Ambient, RCP 2.6, RCP 4.5) with
 <em>Silvetia</em> canopy (Present, Absent) treatments.
 Replicate mesocosms (n=10) were randomly assigned to three outdoor water
 tables (1.8 x 0.9 x 0.3 m; l*w*h) that received flow-through seawater from
 San Diego Bay. Each water table was then randomly assigned to one of the
 three climate scenarios. Because water temperatures in San Diego Bay are
 warmer than the average water temperatures at rocky shores where
 <em>Silvetia</em> occurs, we chilled the incoming seawater
 using a flow-through seawater chiller (Aqualogic, Inc.) but still allowed
 the temperature to vary with natural ambient fluctuations (Fig. 1).
 Seawater delivered to the future scenario mesocosms (i.e., RCP 2.6, RCP
 4.5) was then altered in a header tank using aquarium heaters and CO2
 injections before entering experimental mesocosms. Our goals were for 1)
 seawater in the RCP 2.6 treatments to be heated 1 °C and acidified 0.1 pH
 units relative to Ambient conditions, and 2) seawater in the RCP 4.5
 treatments to be heated 2 °C and acidified 0.2 pH units relative to
 Ambient conditions. Seawater was delivered to each header tank at 2270
 L/h, which then flowed via gravity to the experimental mesocosms. To
 create realistic tidal conditions, ball valves connected to drains were
 opened and closed using a digital watering timer (DIG Model C002, DIG
 Corporation), which resulted in the mesocosms being submerged at tide
 heights 0.5 m above MLLW, and emerged at tide heights below this. This
 tide height is representative of intertidal elevations where
 <em>Silvetia</em> occurs in southern California (Littler
 1980). We added realistic assemblages of understory
 algae to each mesocosm. To determine the species that comprised these
 representative assemblages, we surveyed natural understory algal
 communities in the field at NASO. We collected, identified, and weighed
 all the understory algae found within six 0.15 x 0.15 m quadrats that were
 placed beneath haphazardly selected <em>Silvetia</em>
 individuals. This identified five genera that made up 83% of the total
 understory algal biomass; namely <em>Chondracanthus</em>,
 <em>Centroceras</em>, <em>Corallina</em>,
 <em>Gelidium</em>, and <em>Laurencia</em>. Because
 we were unable to find enough <em>Gelidium</em> during future
 collections for our experiment, we removed it from the study. The
 remaining four genera made up 76% of total understory biomass. To create
 realistic understory assemblages, we calculated the biomass density of
 each genera in the field (grams per m2) and scaled these calculations to
 match the surface area of the mesocosm floors. Using this approach, each
 mesocosm received 4 g of <em>Centroceras</em>, 10 g of
 <em>Chondracanthus</em>, 9 g of
 <em>Corallina</em>, and 2.5 g of
 <em>Laurencia</em>. Additionally, because invertebrate grazers
 can alter algal-algal interactions (Rogers & Breen 1983, Hoffmann
 et al. 2020), they were included in all mesocosms. To add ecologically
 realistic densities of these grazers relative
 to <em>Silvetia</em> biomass, we scaled field densities (# of
 grazer individuals per gram of <em>Silvetia</em>) reported in
 a previous study (Jones 2016) to our mesocosms. As a result, we added six
 <em>Tegula funebralis</em>, six <em>Lottia
 strigatella</em>, six <em>Lottia scabra</em>, ten
 <em>Littorina scutulata</em>, and one <em>Cyanoplax
 hartwegii </em>to each mesocosm.<br> <br>Grazers and
 understory algae were collected during the establishment of the field
 experiment (see below) and held at CMIL for a 10-day acclimation period.
 Each of the four understory seaweeds were weighed to the predetermined
 biomass (± 5%), attached to a rock with superglue, and placed into one of
 the four corners of the mesocosms. Additional rocks covered the bottom of
 the mesocosms to provide a refuge for grazers. We alternated the position
 of each algal type between replicates in a Latin Square design. For the
 <em>Silvetia</em> Present treatments, pre-weighed
 <em>Silvetia</em> (72.5 ± 1.3 g, mean ± SE) were laid across
 the assemblage inside mesocosm containers. During our 42-day experiment
 (August 5th-September 17th, 2021), we measured pH and temperature of the
 seawater as it flowed from each header tank into the experimental
 mesocosms every morning using a probe (Oakton 300 Series pH/DO meter),
 except on days 32, 38, and 39, which were not measured due to logistical
 constraints.  After 42 days, we ended this experiment
 as most of the understory algae in the <em>Silvetia</em>
 Absent treatments had bleached or disintegrated. We categorized the algae
 as being either bleached (dead) and unbleached (living) and measured the
 biomass of each group in each replicate after blotting them dry. The
 remaining biomass of each understory genus was then calculated as the
 percentage of final unbleached tissue weight relative to its initial
 weight. To assess <em>Silvetia</em> health, we measured
 quantum yield [a ratio of variable fluorescence (Fv) to maximal
 fluorescence (Fm)], which estimates the light-harvesting efficiency of
 photosystem II (PS II), using a pulse amplitude modulated (PAM)
 fluorometer (sensu Edwards and Kim 2010, Bews et al. 2020). Because we
 observed within-individual variation in tissue health, we measured the
 quantum yield of each individual at five randomly selected sections of
 each thallus and averaged these measurements for each
 <em>Silvetia</em> replicate. To understand
 seasonal differences in how the <em>Silvetia </em>assemblage
 responded to climate change, we repeated this experiment in the winter
 (November 9th-December 20th, 2021). We followed the same protocols
 described above but made three changes: 1) We shortened the acclimation
 period from ten to five days, 2) we collected algae and grazers from a
 nearby site (NANO instead of NASO), and 3) the water tables were randomly
 reassigned different climate treatments. Pre-weighed
 <em>Silvetia</em> for this experiment averaged 71.0 ± 1.6 g.
 Although we did not see as much understory degradation in the
 <em>Silvetia </em>absent treatments during this experiment, we
 maintained the 42-day experimental duration to facilitate comparisons
 between the two trials (hereafter summer and
 winter). <br><br>Field experiment: Experimental field plots
 were established at NASO to simulate the effect of climate change-mediated
 loss of <em>Silvetia</em> on its understory assemblage.
 Because the effect of canopy loss on the assemblage could depend upon the
 successional stage of the assemblage, we also manipulated the assemblage
 biomass of the understory by clearing half of the plots at the start of
 the experiment. We crossed <em>Silvetia </em>Canopy (High,
 Partial, None) with the initial state of the Understory (Full, Cleared);
 n=10. We established these plots in the summer (July 2021) because we
 hypothesized that the effects of <em>Silvetia</em> loss should
 be most pronounced during the less favorable summer conditions. Plots
 containing <em>Silvetia</em> (0.15 x 0.15 m) were marked at
 their corners with Z-spar Splash Zone epoxy and were randomly assigned to
 the different treatments. Plots were positioned just below the existing
 <em>Silvetia</em> holdfasts to study the understory species
 beneath where the <em>Silvetia</em> canopy drapes over the
 substrate during low tide. Prior to manipulations, we recorded the percent
 cover of each genus within the plots using 25-point intercepts within 0.15
 x 0.15 m quadrats. <br> <br>Plots assigned to the No
 <em>Silvetia </em>Canopy treatments simulated the effects of
 climate change-mediated loss of <em>Silvetia</em> by trimming
 <em>Silvetia </em>to its holdfast using shears. This allowed
 the thallus to eventually regrow, while still subjecting the assemblage to
 any effects associated with an absent canopy for the duration of the
 experiment. In previous mesocosm experiments, future climate conditions
 caused <em>Silvetia</em> to discolor, shrivel, and lose
 biomass across its entire thalli (J.D. Long 2015 [unpublished data]). To
 examine the consequences of partial <em>Silvetia</em> loss, we
 trimmed <em>Silvetia</em> in Partial Canopy treatments from
 multiple layers originating from a single holdfast to a single thallus
 layer. The remaining plots containing <em>Silvetia</em> were
 left unmanipulated and represented our High Canopy treatments. However,
 because 1) we observed large within-treatment variation and 2) the Full
 and Partial <em>Silvetia</em> Canopy treatments provided
 similar canopies, we pooled Full and Partial <em>Silvetia</em>
 treatments into a single “<em>Silvetia</em> Present” treatment
 and compared this pooled treatment to the “<em>Silvetia</em>
 Absent” treatment. To manipulate the understory assemblages, the existing
 assemblages in half of the plots of each <em>Silvetia</em>
 treatment were removed using scrapers and chisels (Understory Cleared
 treatments) while the assemblages in the other half were left
 unmanipulated (Understory Full treatments). We measured the percent cover
 of the understory assemblages in October (hereafter fall) and December
 (hereafter winter) 2021. <br><br>Statistical analyses: All
 data were analyzed using R-Studio and Primer + PERMANOVA 7. Prior to
 analyses, data were checked for normality and heteroscedasticity using
 Shapiro-Wilk’s and Levene’s tests, respectively. For the mesocosm
 experiment, measurements of quantum yield required square-root
 transformation to meet assumptions of normality. Silvetia biomass and
 measurements of quantum yield within the mesocosms were compared among the
 three climate treatments using separate one-way ANOVAs (for each season).
 This was done as separate analyses rather than a two-way ANOVA that
 included season as a factor because the experimental mesocosms were broken
 down, cleaned, randomized, and reassigned with new assemblages prior to
 the winter trial. Tukey’s HSD post-hoc tests between pairs of climate
 treatments were then used when the ANOVAs returned significant
 differences. To visualize shifts in the understory algal assemblages
 between the Climate and Silvetia canopy treatments within each trial,
 Principal Coordinates Analysis (PCoA) was used to map similarities in the
 algae comprising each assemblage. Two-way PERMANOVAs were then used to
 determine if the assemblage shifts differed between the Climate and
 Silvetia canopy treatments. Due to a high number of zeroes for certain
 taxa in the <em>Silvetia</em> Absent treatments, the data were
 square-root transformed and the PERMANOVAs were run with a zero-inflated
 Bray-Curtis similarity indices using a dummy variable of 1. A priori
 post-hoc permutation tests were then used to examine pairwise differences
 in the assemblages between Climate and <em>Silvetia</em>
 canopy treatments. SIMPER analyses were used to identify the relative
 contribution of each understory taxon to assemblage dissimilarity between
 treatments. As discussed above, these analyses were run separately for the
 summer and winter trials. For the field experiment, a three-way PERMANOVA
 was used to assess differences in the understory communities (based on
 percent cover) between <em>Silvetia</em> canopy treatments,
 Understory treatments, and Seasons. Unlike the mesocosm experiments,
 season was included as a factor because the field experiment was run
 continuously. Following the PERMANOVA, a priori permutation post-hoc tests
 were used to determine differences in understory assemblages between the
 Silvetia canopy treatments within each Understory treatment and season.
 SIMPER analyses were used to determine the percent contribution of each
 general to the observed differences. All analyses were evaluated at an
 ɑ-level of 0.05.
description: This readme file was generated on 2023-07-14 by Anthony Truong. ORCID:
 0009-0005-0693-0270 Institution: San Diego State University Email:
 Date of data collection: Mesocosm summer
 trial: 2021-08-05 through 2021-09-17 Mesocosm winter trial: 2021-11-09
 through 2021-12-20 Field experiment: Established 2021-07, surveyed in
 2021-10 and 2021-12. Geographic location of data collection: Mesocosm
 experiment conducted at the San Diego State University Coastal &
 Marine Laboratory Institute. Collection for mesocosm experiment conducted
 at Navy North (32.692312 N, -117.25297W) and Navy South (32.68306 N,
 -117.24963 W), San Diego, CA. Field experiment conducted at Navy South
 (32.68306 N, -117.24963 W), San Diego, CA. This work was supported by
 grants received from the Cabrillo National Monument Foundation, the
 National Parks Service (P20AC00867), and San Diego State University ##
 Season-specific impacts of climate change on canopy-forming seaweed
 communities. File List: 1. mesocosm_parameters.csv Daily mesocosm
 measurements of pH and temperature for each of the three climate
 treatments across the duration of the summer and winter trials. 2.
 mesocosm_silvetia_weights.csv Measurements of Silvetia biomass taken at
 the beginning and end of each mesocosm trial denoted by the columns SILV_i
 and SILV_f, respectively. 3. mesocosm_silvetia_quantumyield.csv
 Measurements of Silvetia quantum yield taken at the beginning and end of
 each mesocosm trial. 4. mesocosm_understory.csv Measurements of understory
 biomass by genera taken at the beginning and end of each mesocosm trial.
 The following codes are used for understory genera included in the
 mesocosms: * CENT: Centroceras spp. * CHON: Chondracanthus spp. * CORA:
 Corallina spp. * LAUR: Laurencia spp. Understory biomass was categorized
 based on its condition and then formatted for analysis. Conditions and
 formatting are notified by the following where GENERA = taxa code. *
 GENERA_i: Initial biomass prior to start of experiment. * GENERAi+1:
 Initial biomass after being inflated by a dummy variable of 1. * GENERA_b:
 Bleached biomass at the end of the experiment. * GENERA_ub: Unbleached
 biomass at the end of the experiment. * GENERA_ub+1: Unbleached biomass at
 the end of the experiment after being inflated by a dummy variable of 1. *
 GENERA_f: Total bleached and unbleached biomass at the end of the
 experiment. * GENERA_delt: Difference between final unbleached biomass and
 initial biomass (i.e., x_f - x_i). * GENERA_%loss: Percentage of initial
 biomass that was lost across the experiment (i.e., x_delt/x_i) *
 GENERA_%f: Percentage of initial biomass remaining at the end of the
 experiment (i.e., 1 + x_%loss). * GENERA%f+1: Percentage of remaining
 initial biomass inflated by a dummy variable of 1. 1. mesocosm_simper.csv
 Modified data matrix derived from mesocosm_understory.csv for use in
 SIMPER analyses. 2. mesocosm_simper_environment.csv Environmental data
 from mesocosm_understory.csv for use in SIMPER analyses. 3.
 field_percentcover.csv Percent cover by genera for the field experiment
 taken in 2021-07 (Summer) prior to manipulations, in 2021-10 (Fall), and
 in 2021-12 (Winter). Grid_Count column denotes the number of grid tiles
 (out of 25) sampled for each plot. 4. field_simper.csv Modified data
 derived from field_percentcover.csv for use in SIMPER analyses. 5.
 field_environment.csv Environmental data from field_percentcover.csv for
 use in SIMPER analyses. Methodological Information: Mesocosm experiment:
 Three outdoor water tables (1.8 x 0.9 x 0.3 m; l*w*h) receiving
 flow-through seawater from San Diego Bay were designated to one of three
 climate scenarios: Ambient, RCP 2.6 (+1 C/-0.1 pH units relative to
 Ambient), and RCP 4.5 (+2 C/-0.2 pH units relative to Ambient). We
 elevated the temperature of the water in the tables designated RCP 2.6 and
 RCP 4.5 using aquarium heaters and acidified the water using CO2
 injection. Data for the file "mesocosm_parameters.csv" were
 produced by daily measurements of temperature (nearest 0.1 C) and pH
 (nearest 0.01 unit) were recorded using a probe (Oakton 300 Series pH/DO
 meter). Measurements were unable to be recorded on days 32, 38, and 39 of
 the summer trial. Within each water table, we placed 20 plastic boxes (15
 x 15 x 7.6 cm; l*w*h with three mesh-covered 5-cm diameter holes in each
 of two opposite sides for water exchange) containing grazers (six Tegula
 funebralis, six Lottia strigatella, six Lottia scabra, ten Littorina
 scutulata, and one Cyanoplax hartwegii). Understory algae (4 g of
 Centroceras, 10 g of Chondracanthus, 9 g of Corallina, and 2.5 g of
 Laurencia, 5%) was then added (these values produced column GENERA_i for
 the "mesocosm_understory.csv" dataset). Individuals of Silvetia
 compressa (72.5 1.3 g, mean SE, column SILV_i for the
 "mesocosm_silvetia_weights.csv" dataset) were laid over the
 understory species in half of the containers (Silvetia present) while the
 other half had no Silvetia (Silvetia absent). n=10. After allowing the
 experiment to run for 42 days (Summer trial: 2021-08-05 through
 2021-09-17, Winter trial: 2021-11-09 through 2021-12-20), the contents of
 each container were collected. "mesocosm_silvetia_weights.csv":
 Silvetia biomass (nearest 0.1 g) was recorded using a digital scale
 (column SILV_f). "mesocosm_quantumyield.csv": Silvetia quantum
 yield was measured at five random sections (columns M1, M2, M3, M4, and
 M5) along the thalli of the individual using a pulse amplitude modulated
 (PAM) fluorometer (sensu Edwards and Kim 2010). These measurements were
 then averaged to estimate the quantum yield of the individual (column
 Average) and converted into a percentage (column Percentage). Quantum
 yield, a measurement of light harvesting efficiency of photosystem II, is
 recorded as a ratio (nearest 0.01) of variable fluorescence (Fv) to
 maximal fluorescence (Fm) and its unit is [PSII].
 "mesocosm_understory.csv": Understory biomass (nearest 0.01 g)
 was recorded using a digital scale and further partitioned into bleached
 (column GENERA_b) and unbleached (column GENERA_ub) biomass. Column
 GENERA_f is the total bleached and unbleached biomass for the respective
 genera. Columns labeled with a +1 have had their respective values
 increased by a Bray-Curtis dummy variable of 1. Column GENERA_delt is the
 difference between final unbleached and initial biomass. Column
 GENERA_%loss is the proportion of GENERA_delt to GENERA_i. Column
 GENERA_%f is calculated as 1-GENERA_%loss, and represents the proportion
 of remaining biomass relative to initial. "mesocosm_simper.csv":
 All GENERA_%f+1 columns from the "mesocosm_understory.csv"
 dataset were moved into a new .csv file for SIMPER analysis.
 "mesocosm_environment.csv": Columns Season, Canopy, and Climate
 from the "mesocosm_understory.csv" dataset were moved into a new
 .csv file for SIMPER analysis. Field Experiment: Experimental field plots
 were established at Navy South. Plots measured 0.15 x 0.15 m and contained
 an adult Silvetia individual. We crossed Silvetia Canopy (High, Partial,
 None) with the initial state of the Understory (Full, Cleared) and
 assigned each plot randomly to one of the six resulting treatments; n=10.
 Plots assigned to Silvetia None treatments had the Silvetia occurring with
 the plots trimmed to the holdfast. Plots assigned to the Silvetia Partial
 treatments had the Silvetia trimmed to a single thallus layer while
 Silvetia High plots were unmanipulated. However, because 1) we observed
 large within treatment variation and 2) the Full and Partial Silvetia
 Canopy treatments provided similar canopies, we pooled Full and Partial
 Silvetia treatments into a single Silvetia Present treatment and compared
 this pooled treatment to the Silvetia Absent treatment. To manipulate the
 understory assemblages, the existing assemblages in half of the plots of
 each Silvetia treatment were removed using scrapers and chisels
 (Understory Cleared treatments) while the assemblages in the other half
 were left unmanipulated (Understory Full treatments).
 "field_percentcover.csv": We measured the percent cover of each
 genus within the plots using 25-point intercepts within 0.15 x 0.15 m
 quadrats once before manipulations in Summer (2021-07) then twice after
 manipulations in Fall (2021-10) and Winter (2021-12). Genera four letter
 codes: CENT = Centroceras spp. CHON = Chondracanthus spp. CORA = Corallina
 spp. GAST = Gastroclonium spp. GELI = Gelidium spp. GIGA = Gigartina spp.
 GRAC = Gracilaria spp. JANI = Jania spp. LAUR = Laurencia/Osmundea spp.
 LOME = Lomentaria spp. MAZZ = Mazzaella spp. PLOC = Plocamium spp. PTER =
 Pterygophora spp. RHOD = Rhodymenia spp. SILV = Silvetia compressa ULVA =
 Ulva spp. BARE = Bare rock OTHER = Unidentifiable genus/species
 "field_simper.csv": All genera percent cover columns from the
 "field_percentcover.csv" dataset were moved into a new .csv file
 for SIMPER analysis. "field_environment.csv": Columns Season,
 Canopy, and Understory from the "field_percentcover.csv" dataset
 were moved into a new .csv file for SIMPER analysis. Statistical Analysis:
 All data were analyzed using R-Studio and Primer + PERMANOVA 7. Prior to
 analyses, data were checked for normality and heteroscedasticity using
 Shapiro-Wilks and Levenes tests, respectively. For the mesocosm
 experiment, measurements of quantum yield required square-root
 transformation to meet assumptions of normality. Silvetia biomass and
 measurements of quantum yield within the mesocosms were compared among the
 three climate treatments using separate one-way ANOVAs (for each season).
 This was done as separate analyses rather than a two-way ANOVA that
 included season as a factor because the experimental mesocosms were broken
 down, cleaned, randomized, and reassigned with new assemblages prior to
 the winter trial. Tukeys HSD post-hoc tests between pairs of climate
 treatments were then used when the ANOVAs returned significant
 differences. To visualize shifts in the understory algal assemblages
 between the Climate and Silvetia canopy treatments within each trial,
 Principal Coordinates Analysis (PCoA) was used to map similarities in the
 algae comprising each assemblage. Two-way PERMANOVAs were then used to
 determine if the assemblage shifts differed between the Climate and
 Silvetia canopy treatments. Due to a high number of zeroes for certain
 taxa in the Silvetia Absent treatments, the data were square-root
 transformed and the PERMANOVAs were run with a zero-inflated Bray-Curtis
 similarity indices using a dummy variable of 1. A priori post-hoc
 permutation tests were then used to examine pairwise differences in the
 assemblages between Climate and Silvetia canopy treatments. SIMPER
 analyses were used to identify the relative contribution of each
 understory taxon to assemblage dissimilarity between treatments. As
 discussed above, these analyses were run separately for the summer and
 winter trials. For the field experiment, a three-way PERMANOVA was used to
 assess differences in the understory communities (based on percent cover)
 between Silvetia canopy treatments, Understory treatments, and Seasons.
 Unlike the mesocosm experiments, season was included as a factor because
 the field experiment was run continuously. Following the PERMANOVA, a
 priori permutation post-hoc tests were used to determine differences in
 understory assemblages between the Silvetia canopy treatments within each
 Understory treatment and season. SIMPER analyses were used to determine
 the percent contribution of each general to the observed differences. All
 analyses were evaluated at an -level of 0.05. ``` ```