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°oW; hereafter NANO). These Multi-Agency
Rocky Intertidal Network sites (MARINe) contain dense patches ofSilvetia , 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 Silvetia 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. Silvetia 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: To examine the impacts of projected
changes in ocean temperature and pH on Silvetia 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 Silvetia 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 whereSilvetia 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 whereSilvetia 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 Silvetia individuals. This identified five genera that
made up 83% of the total understory algal biomass; namelyChondracanthus , Centroceras , Corallina ,Gelidium , and Laurencia . Because we were unable to find
enough Gelidium 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 Centroceras , 10 g of Chondracanthus , 9 g ofCorallina , and 2.5 g of Laurencia . 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 toSilvetia biomass, we scaled field densities (# of grazer
individuals per gram of Silvetia ) reported in a previous study
(Jones 2016) to our mesocosms. As a result, we added six Tegulafunebralis , six Lottia strigatella , six Lottia
scabra , ten Littorina scutulata , and one Cyanoplax
hartwegii to each mesocosm.
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 Silvetia Present
treatments, pre-weighed Silvetia (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 Silvetia 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 Silvetia 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 eachSilvetia replicate.
To understand seasonal differences in how the Silvetia 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-weighedSilvetia for this experiment averaged 71.0 ± 1.6 g. Although we
did not see as much understory degradation in the Silvetia Absent
treatments during this experiment, we maintained the 42-day experimental
duration to facilitate comparisons between the two trials (hereafter
summer and winter).
Field experiment: Experimental field plots were established at
NASO to simulate the effect of climate change-mediated loss ofSilvetia 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 Silvetia 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 Silvetia loss should be most pronounced during the less
favorable summer conditions. Plots containing Silvetia (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 Silvetia holdfasts to study
the understory species beneath where the Silvetia 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.
Plots assigned to the No Silvetia Canopy treatments simulated the
effects of climate change-mediated loss of Silvetia by trimmingSilvetia 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 Silvetia to discolor, shrivel, and lose biomass across its
entire thalli (J.D. Long 2015 [unpublished data]). To examine the
consequences of partial Silvetia loss, we trimmed Silvetiain Partial Canopy treatments from multiple layers originating from a
single holdfast to a single thallus layer. The remaining plots
containing Silvetia were left unmanipulated and represented our
High Canopy treatments. 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 PartialSilvetia treatments into a single “Silvetia Present”
treatment and compared this pooled treatment to the “SilvetiaAbsent” treatment. To manipulate the understory assemblages, the
existing assemblages in half of the plots of each Silvetiatreatment 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.
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 andSilvetia 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 Silvetiacanopy 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 ɑ-level of 0.05.