Printer Friendly

Within-site variation of growth rates and terminal sizes in Mytilus californianus along wave exposure and tidal gradients.

Abstract. Mytilus californianus is a foundation species of rocky shores of western North America. Its dominance depends on rapid growth to large sizes, which confers an advantage in size-dependent species interactions. Initial rates of growth and final (terminal) sizes of the mussels depend on environmental factors. Prior comparisons of growth made over large spatial scales (tens of meters to hundreds of kilometers) indicate that temperature, submergence time, and wave exposure affect growth. However, there are few studies quantifying variation in temperature, wave force, and mussel growth parameters at small scales within local populations--that is, meter-level increments. Such measures are necessary to better understand the consequences of the complex spatial mosaic of physical factors in the intertidal zone. We measured variation in temperature, wave force, size-specific shell growth, and terminal size at 3-4-m intervals along horizontal contours within two mussel beds separated by 15 ds of latitude. Both mussel beds showed the same general trends: growth rates attenuated along gradual clines from low and wave-exposed to high shore and sheltered. For example, young adults from low and wave-exposed microhabitats grew 9- and 6-fold higher than those from high-shore-wave-sheltered points. While higher flow may promote growth by enhancing feeding, it also appears to exert a positive effect by moderating energetically costly temperature stress. Consistent with the growth rate findings, cumulative degree-hours explained 83% and 69% of the variation of terminal sizes in regressions for the two locations.

Introduction

Recent studies of the possible impacts of global warming on intertidal organisms offer the realization that population reductions or extinctions cannot be predicted by assuming that the key physical parameters of temperature and wave action vary gradually and consistently along a latitudinal expanse of shore line (see Helmuth et al., 2002). Temperature has been shown (Helmuth, 1999; Helmuth etal, 2006; Denny et al., 2011) to vary greatly within a given site (meters to tens of meters) such that small-scale variation within a site may exceed average conditions on locations separated by many degrees of latitude. Therefore, population changes (in density or other structural features) cannot be assumed to occur first at the latitudinal limits of species distributions. A similar argument can be made about possible effects of changing wave force, which has been shown to vary greatly over a range of scales, including extreme small-scale variation (Helmuth and Denny, 2003), and which may, via varying degrees of wave splash and wash, moderate the temperatures (Mislan et al, 2011). Thus it appears that physiologically based population responses may vary according to a complex spatial mosaic of environmental parameters. Denny et al. (2011) call for studies that quantify variation in the physical parameters and organism responses at the fine scales at which they experience it--that is, meters within the local population.

This work measured variation in temperature, wave force, and shell growth at 3-4-m increments along horizontal contours within two intertidal beds of the mussel Mytilus californianus Conrad. Previous studies of spatial variation in growth of M. californianus often assessed the growth of transplanted cohorts of small mussels, comparing average differences among sites separated by many tens of meters to kilometers (Menge, 1992; Blanchette et aL, 2007). We developed a method to very precisely measure shell growth of mussels growing naturally within the beds, without the possibility of transplant artifacts and without disrupting the natural structure of their aggregations, which moderate their exposure to temperature (Helmuth, 1999)

We measured growth over the complete range of mussel sizes, providing a detailed look at size-specific growth relationships. The prior large-scale studies spanning several mussel species (e.g., Menge, 1992; Menge et al, 1994; Dahlhoff and Menge, 1996; McQuaid and Lindsay, 2000; Steffani and Branch, 2003; Blanchette et al, 2007) found a positive relationship between growth and wave exposure, possibly due to greater nutrient transport and resuspension at sites with higher flow speeds. One large-scale (hundreds of meters to hundreds of kilometers) comparison (Blanchette et al, 2007) found a negative correlation between wave exposure and growth in M. californianus, but the wave exposure comparison was confounded by shore level differences that affect submergence and feeding times. Therefore, some, if not all, of the large-scale differences in mussel growth could be attributed to the latter. Regional differences in the concentration of phytoplankton may also cause large-scale spatial differences in mussel growth (e.g., Menge, 1992; Menge et al, 1994). In the present work, the sample contours showed a gradient of wave exposure, with the seaward end receiving the brunt of breaking waves and flow speeds dissipating to the lee, but this small-scale (2-m intervals over contours <20 m long) meant that the transit of a wave was completed in a few seconds, and there was, therefore, no opportunity for the mussel bed to alter phytoplankton concentrations (see Frechette and Bourget, 1985, for circumstances in which seston depletion might occur). Controlling for shore level and phytoplankton concentration allowed us to isolate possible effects of small-scale variation in temperature and wave force.

Differing growth rates and the resulting variation in body sizes plays a pivotal role in the ecology of M. californianus. Larger mussels are less vulnerable to predators, influencing mussel population structure (Paine, 1976; Robles et al., 1990). Growth rate modifies competitiveness for space because fast-growing mussels overgrow other sedentary species on the rock surface (Dayton, 1971; Paine, 1974). In the closely related mussel Mytilus edulis, large mussels produce more gametes, contributing proportionally more to the overall production of larvae that seed local populations than do relatively small individuals (Bayne et al., 1983). Size may have effects on settlement rates because Mytilus larvae settle on the byssal threads of adults, and larger mussel have larger byssal complexes (McGrath, 1988; Caceres-Martinez, 1994; Dolmer and Stenalt, 2010). Lastly, size affects body temperature, with larger mussels having greater thermal inertia, which in turn stabilizes body temperature over fluctuating environmental conditions (Helmuth, 1998). Hence, factors that advance or retard the rate of growth may influence mortality, fecundity, and rate of larval recruitment, which in turn alters features of mussel population structure.

Growth in mussels is indeterminate: the growth rate and body size at any age are predominantly determined by environmental factors, while the remaining variation is explained by genetic processes (Koehn and Gaffney, 1984). Environmentally based differences are a consequence of shifting energy allocation (Widdows and Bayne, 1971). As mussels grow, the rate of energy intake in a given environment does not keep pace with the rising demands of maintenance and reproduction. As the latter demands approach the level of the energy consumed, growth declines to nil and a terminal size is reached. Environmental factors that increase energy input defer growth limitation to larger sizes. Factors that increase maintenance costs curtail growth at smaller sizes (see Matzelle et al, 2014, for further explanation). These relationships explain the variation associated with different shore levels (Petes et al., 2007, 2008).

High-shore mussels exhibit patterns of reduced growth and relatively small terminal sizes (Kopp, 1979). One obvious cause is relatively low energy consumption imposed by the long emergence times high on the shore. However, a further suppression of growth by thermal stress due to solar radiation during aerial exposure has recently been revealed (see Schneider, 2008). Thermal stress occurs as sublethal temperatures above some critical level denature proteins, which in turn activates the heat-shock response (Roberts et al., 1997; Buckley et a., 2001). The heat-shock response is energy-demanding (Lindquist, 1998), and the ATP used for chronic cellular rescue in frequent high-temperature events reduces reserves that could otherwise be allocated toward growth. Consequently, mussels high on the shore show higher tissue concentrations of heat-shock proteins (HSPs), greater levels of ubiquitinated proteins, and small body sizes (Hofmann and Somero, 1995; Somero, 2002; Halpin et al., 2004). Further evidence of compensatory adjustments under elevated aerial thermal stress is revealed by experimentally stressed mussels that show modifications of the transcriptome and proteome (Tomanek and Zuzow, 2010; Connor and Gracey, 2011); increased ATP synthesis (e.g., arginine kinase activity) (Gracey et al., 2008); and acquisition of atmospheric oxygen (Dowd and Somero, 2013).

Mechanisms causing growth rate differences along the wave-exposure gradient have received less study than those along the tidal gradient. However, the mechanism of indeterminate growth suggests that greater wave action may promote growth by influencing both energy gained (i.e., from the untested assumption of prolonged feeding times due to repeated wave splash or wash) and energy lost (i.e., moderating stressful temperatures and their energetic costs (e.g., Fitzhenry et al., 2004)).

In apparently the only other small-scale comparison of wave-related temperature effects, Fitzgerald-Dehoog et al. (2012) transplanted groups of small mussels (1-3 cm long) to haphazard locations along a horizontal contour of a rocky shore in Southern California. The locations were chosen to sample a range of temperature regimes that resulted from differences in wave exposure and splash. Their findings showed a strong negative correlation between average daily temperature and mussel shell growth. Adoption of the untested assumption that the differences in wave splash or wash had little effect on feeding times (energy gain), the energy losses to heat stress appear to have impacted growth substantially. We expanded upon the approach of Fitzgerald-Dehoog et al. (2012), measuring temperature, wave force at 3-4-m increments over small-scale horizontal gradients of wave energy, and comparing those measures to growth of the complete range of sizes in natural aggregations. Our results reinforce the general findings of Fitzgerald-Dehoog et al. (2012). while suggesting some additional effects on shell deposition of mussels near terminal size. The careful accounting of relevant physical factors at small scales showed similar factor-growth relationships between two sites separated by many degrees of latitude.

Materials and Methods

Site description

Growth experiments were conducted on rocky headlands at Laguna Beach, California (33[degrees]54'N, 117[degrees]80'W), and Helby Island, British Columbia (48[degrees]51'N, 125[degrees]10'W). To examine the effects of small-scale variation in flow, sites were chosen that appeared to have an alongshore gradient of wave energy. However, the wave energy between sites was not compared quantitatively. The Laguna Beach experiments occurred on the northward face ([approximately equal to]45 degree in slope) of a mussel bed attached to a roughly 20 m long extension of a larger headland where the prevailing westerly swells struck the tip of the point and ran along its vertical sides with gradually dissipating force. The Helby site is a dome-shaped islet roughly 100 m in diameter at the 0.00 mean lower low water (MLLW) contour line where the southeastward facing ([approximately equal to]45 degree in slope) mussel bed is widest (extending from low to high shore) at the northeastern tip of the wave-exposed end of the shore and extends 20 m toward the southwest. Waves traveling southeast indirectly contact the mussel bed. Toward the most leeward end, mussel density was diffuse and the upper and lower limits converged to a point

The mussel beds were not shaded by any surrounding structures. The topography of the mussel bed at Laguna was relatively uniform, and a monolayer of mussels occupied the rocky substrate. The Helby site was more uniform and mono-layered along the high-shore contour, while substrate depressions and multilayered aggregates were present on the lower shore.

Experimental design

A Topcon Total Station Surveyor was used to lay out a rectangular grid of sample plots at each site. Quadrats were placed along the surface of the beds at the intersection of transects, forming a grid. The horizontal lines stretched from most exposed to sheltered areas where mussel density began to thin, and the vertical lines extended from the lower to upper shore level limits of the beds.

At Laguna, two horizontal transects about 11 m in length from wave-exposed to sheltered microhabitats were established 0.50 vertical m apart. The lowest line was +0.30 m above MLLW (Fig. 1A). The lowest line (low-shore) was labeled 1 and the upper (high-shore) labeled 2 (Fig. 2A). Four vertical transects were placed about 3 m apart from sheltered to exposed and labeled A (sheltered), B (midsheltered), C (mid-exposed), and D (exposed) (Fig. 2A). The Helby site consisted of three horizontal transects ([approximately equal to]9 m in length) 0.50 vertical m apart and labeled 1 (low-shore), 2 (mid-shore), and 3 (high-shore) (Fig. 2B). The lowest line was +1.20 m above MLLW (Fig. IB). Three vertical transects were placed about 4 m apart and labeled A (sheltered), B (mid-exposed), and C (exposed) (Fig. 2B). At each site, size, and environmental measurements. At Laguna the coordinates were A1, B1, C1, D1, A2, B2, C2, and D2 (Fig. 2A). At Helby, they were B1, C1, A2, B2, C2, A3, B3, and C3 (2B). Growth rates were not measured at B1 because of a limited range of mussel sizes due to predation of mostly small and medium-sized mussels by the sea star Pisaster ocracheous at that location. Similarly, no coordinate was established at Al due to few mussels and an abundance of P. ocracheous (see Robles and Desharnais, 2002, for a detailed explanation of P. ocracheous--M. californianus interactions along gradients of wave exposure). No coordinates were situated in deep depressions of the topography.

Quadrat frames were constructed of PVC pipe. The areas of the quadrats were scaled in proportion to the different sizes of the largest mussels at each shore level to assure that sample sizes were similar between plots from the different levels. At Laguna, the shore level 1 quadrats were 60 X 30 cm and at level 2 were 50 X 20 cm. At Helby, quadrat dimensions from shore level 1 through 3 were 60 X 24 cm, 55 X 22 cm, and 50 X 20 cm, respectively.

Mussel growth is size-dependent (younger mussels grow fastest); thus, to assure a more complete representation in growth rate variability, growth of all of the individuals within each quadrat sample was measured.

Growth measurement

Fluorescent dye (calcein, Sigma Chemical Inc.) was used to measure growth. Mussels briefly injected with a dye-seawater solution deposit a thin band of the dye within the shell, providing a time marker from which to measure increments of shell growth (Kaehler and McQuaid, 1999). Solutions of fluorescent dye were prepared (300 mg/1), using seawater at the site. A small handheld cutting tool was used to make a small hole (approximately 1 mm in diameter) on the shell margin off-center the medial line of the dorsal-ventral surface of each mussel. Care was taken to minimize the chance of damage to any soft tissue. A syringe with needle (1.65-mm diameter, 25-mm length) was used to inject the dye solution into the mantle cavity through the hole until excess escaped between the valves. Prior studies show that, at external concentrations as high as 640 mg/1, the dye did not increase the mortality rates of mussels (Kaehler and McQuaid, 1999).

Calcein injections were done at Laguna on low tides on 18 and 19 January 2004 and at Helby on 20 and 21 June 2004. Mussels were allowed to grow for about 90 days, after which they were collected, and the shells were cleaned of soft tissue in the laboratory. Shell length was measured with digital calipers for both sites. Because of the complexities of topography, tidal cycle, season, and weather that vary between sites, we did not attempt to make quantitative comparisons of growth between locations.

To measure growth increment, the shells were cut along the longest axis between the anterior and posterior margins with a lapidary diamond saw and viewed under an epifluorescent microscope (Olympus BH2-RFCA) for growth past the dye mark that is secreted at the mantle edge (de Paula and Silveira, 2009). Mussel growth greater than 2 mm was beyond the field of view and was measured with digital calipers.

Growth in mussels fit the Von Bertalanffy (v-b) model, which relates growth as a function of age. For species that follow the v-b model, individual growth is fast early in their development, and rates attenuate as they age. The equation is expressed as

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] (Equation 1)

The parameters are L = length, L[infinity]= maximum length, t = age, and k, a growth constant. L[infinity] and k were estimated using Gulland and Holt (G&H) plots (Gulland and Holt, 1959), which are created by; regressing growth increment against initial shell length. The growth constant k is determined from the slope of the curve, and L[infinity] is represented by the x-intercept (Seed, 1980). Theoretically, fast-growing populations should have larger y- and x-intercepts then those of slow-growing populations.

Growth-rate regressions were created for each plot and used to estimate k and L[infinity]. For comparison, estimates of L[infinity] were alternatively calculated using the upper 95th percentile class in length, presumably the oldest individuals represented in each population. The mean sizes in each plot at or above the 95th percentile value were calculated. The ranges of the number of individuals in each plot at or above the 95th percentile value were 3-16 and 3-5 at Laguna and Helby, respectively. In an attempt to compare the growth of young adult mussels between microhabitats, we identified mussels at each plot that were at or below the lower 15th percentile size class. In this case, the ranges of the number of individuals in each plot were 8-16 and 3-13 at Laugna and Helly, respectively. It is important to note that individuals lost to predation or storms can alter the size distribution across microhabitats.

Environmental measurements

For one tidal cycle during the growth period, Tidbit (Onset Computers) temperature loggers secured to the shore at each plot location were used to estimate microhabitat temperatures. The loggers were affixed atop a resin disk 7.50 cm in diameter and bolted into the rocky substrate. This approach provided a metric of relative differences in temperature between microhabitats; however, absolute body temperatures are modified by complex biological and physical factors (Helmuth, 1998). The loggers were set to record temperature every 30 s, and degree-hours were calculated as the sum of hourly temperatures above ambient water temperature over a 24-h period. The tidal cycles exhibited at Laguna and Helby during temperature measurements were diurnal and semidiurnal, respectively. Although this study does not attempt to quantitatively compare the effects of temperature on growth between sites, it is important to note that at both sites mussels were exposed during midday hours when aerial temperatures were the highest in the 24-h measurement period. To further evaluate landscape differences in temperature over a range of tidal cycles, we measured habitat temperature for 11 days on a headland in Crystal Cove State Park (CCSP), Laguna Beach, California (33[degrees]33'N, 117[degrees]49"W), with topographical characteristics (e.g., angle, layering, and uniformity) similar to those at the original Laguna site. On 24 July 2013, temperature loggers were placed at three microhabitats characterized as low-shore-wave-exposed (+0.40 m above MLLW), high-shore-wave-exposed, and high-shore-sheltered (+0.90 m above MLLW). The wave-exposed and sheltered points were separated by 16 m. Mussels were present at all three microhabitats. The high-shore-sheltered microhabitat was the most leeward distributional limit of the entire headland population. The bed was not shaded by any surrounding structures.

Maximum wave speed was also measured at the growth sites. Drogues were prepared in the laboratory using PVC pipe, string, plastic balls, and springs, according to the design in Carrington Bell and Denny, 1994. Wave speed was measured during two consecutive tidal cycles beginning on the same day as the temperature measurements.

Statistical analyses

A one-way ANOVA followed by post hoc Tukey tests was performed to determine significant (P < 0.05) differences in mean growth of the lower 15th (i.e., young adults) and upper 95th (i.e., terminal size) percentile size class between plots at each site. A two-way ANCOVA (two exposure groups and two shore-level groups) was performed to test the null hypothesis that there is no difference in shell growth between sub-populations from differing wave-exposed and tidal height microhabitats. Initial shell length was used as the covariate. The plots chosen for a balanced ANCOVA analysis included A1 (low-shore-sheltered), A2 (high-shore-sheltered), D1 (low-shore-exposed), and D2 (high-shore-exposed) for Laguna; and A2 (mid-shore-sheltered), A3 (high-shore-sheltered), D2 (mid-shore-exposed), and D3 (high-shore-exposed) for Helby. A third shore level (low-shore) was omitted from the analysis because only two shore levels were evaluated at Laguna. To test the relationship between degree-hours and growth, we used a best fit regression model approach and reported the model that yielded the highest coefficient of determination. We used average terminal size rather than growth rates as the dependent variable because it represents the long-term variation in growth, and as such, serves as a better predictor of future performance of younger individuals. Lastly, we performed regression analyses on environmental data from the growth sites to determine the relationship between maximum wave speed and degree-hours. All statistical analyses were performed using IBM SPSS Statistics 20.

Results

Differential deposition of dye

A total of 583 mussels were sampled at Laguna and 445 at Helby. The number of mussels collected from each quadrat ranged from 39 to 118 at Laguna and 31 to 96 at Helby. Not every mussel to which calcein was administered deposited the dye into its shell. One would expect shell deposition to occur only if energy beyond that required of basic metabolic needs were available. Deposition of calcein-labeled shell showed a clear spatial trend, with percentages of individual deposition per quadrat being least at relatively high-shore levels and sheltered conditions, which should afford minimum presentation of food particles and higher climatic temperatures (Fig. 3A, B).

Environmental gradients

Both growth sites showed gradients in average maximum wave speed and degree-hours above ambient water temperature (Fig. 4A-D). Laguna measurements displayed greater horizontal gradients along the high-shore transect than along the low-shore transect for both maximum speed and degree-hours (Fig. 4A, B). The plot average maximum speed and degree-hours ranged from 7.02 to 12.34 cm/s and 3.20 to 74.23 degree-hours, respectively. Observations of the Helby environment revealed a gradient in maximum speed along the horizontal gradient only, while degree-hour gradients were prominent over both the horizontal and vertical gradients (Fig. 4C, D). The plot average maximum speed ranged from 6.50 to 10.05 cm/s, and degree-hours ranged between 11.37 and 47.00. Specifically, degree-hour measurements were greatest at the sheltered microhabitats in correspondence with lower average maximum speed. Although environmental data were not measured at the low-shore-sheltered point of the shore, we assume that the values at that point would have been similar to those at the high-shore-wave-exposed plot. In general agreement with these trends, daily maximum temperatures on Crystal Cove State Park were greatest at the high-shore-sheltered followed by high-shore-exposed and low-shore-exposed microhabitats (Fig. 5). The largest difference in maximum temperature between high-shore-sheltered and high-shore-exposed was 15 [degrees]C, which further highlights the relationship between horizontal shore position and thermal exposure. Finally, the putative heat-shock induction temperature in Mytilus californianus is 25 [degrees]C (Buckley et al., 2001), and the maximum habitat temperature met this threshold nine, one, and zero times at the high-shore-sheltered, high-shore-exposed, and low-shore-exposed microhabitats, respectively. Although habitat temperature and body temperature are not perfectly analogous, these findings still underscore the potential risks mussels face living at the extreme leeward end of the wave-exposure gradient.

Our initial regressions between wave exposure and degree-hours revealed low coefficients of determination, [r.sup.2] = 0.35 and [r.sup.2] = 0.31 for Laguna and Helby sites, respectively. In each case, a single outlier was identified and removed. Results from a re-analysis then revealed higher correlations; [r.sup.2] = 0.85, P < 0.05 for Laguna and [r.sup.2] = 0.66, P < 0.05 for Helby.

Growth over the intertidal landscape

Both locations revealed that terminal sizes (95th percentile) (Fig. 6), young adult growth (15th percentile), growth rates (Fig. 7), size-dependent growth increment (Fig. 8 and 9), and trajectories (k) (Table 1) measured over the horizontal and vertical transects followed a pattern of increasing size and growth with increasing wave-exposure and lower shore height. However, many of the sub-populations (quadrats) at Helby exhibited little to no individual positive growth. ANCOVA analyses revealed similar spatial growth patterns (Tables 2 and 3). The effects of wave-exposure and shore-level were significant at P < 0.05.

Regression analysis revealed a negative relationship between terminal size and degree-hours (Fig. 10). This relationship appeared logarithmic (y = -13.67 X \n(x) + 119.74), [r.sup.2] = 0.83, P < 0.05; and linear (y = -2.82 X (x) + 197.19), [r.sup.2] = 0.69, P < 0.05 at Laguna and Helby, respectively.

Discussion

On any given headland, microhabitat temperature, tide level, and wave action vary in time and intensity over the landscape of intertidal substrates (physical and biological) (Harley, 2008; Denny et al., 2011; Mislan et al, 2011); this in turn modifies levels of feeding opportunities and thermal stress in sessile inhabitants. These variables integrate to impact individual growth rate and terminal size, in addition to the spatial distribution of populations (Meager et al., 2011, and this study). As expected, our findings revealed that in general, growth rates and terminal sizes of Mytilus californianus increased toward the wave-exposed and lowshore points of headlands, where conditions for growth were optimal (e.g., cooler temperatures and longer feeding intervals). Growth along the high-shore at Laguna showed a greater than 3-fold variation in young adult growth between mussels at the wave-exposed versus sheltered microhabitats, whereas observations at Helby revealed that growth was principally confined to low-shore-wave-exposed locations. Surprisingly, the Helby site displayed limited levels of growth in mussels highest on the shore and exposed to waves. Nonetheless, the wave-exposed-high-shore mussels displayed more variability in growth than those that were high-shore-sheltered, and the observed larger terminal sizes within wave-exposed habitats suggest that these particular environments allow for greater scope for growth. Although direct comparisons between shores separated by kilometers are challenging because of differences in topographical, oceanographic, and meteorological conditions, these results support previous experiments and theory that predict bioenergetic consequences over small-scale environmental gradients (Dahlhoff and Menge, 1996; Robles and Desharnais, 2002; Fitzgerald-Dehoog et al., 2012). For example, these results agree with a previous finding that showed higher RNA:DNA ratios, an indicator for growth, in natural populations from wave-exposed versus sheltered within-shore microhabitats (Dahlhoff and Menge, 1996), and with a spatially explicit model that predicts growth and distribution over gradients of wave energy on any given expanse of shore (Robles and Desharnais, 2002).

We did not attempt to directly test the possible mechanisms driving differential growth rates along the within-shore-wave-exposure gradient. Fitzgerald-Dehoog et al. (2012) conducted laboratory experiments suggesting that elevated food levels can compensate for energy losses to thermal stress. However, in the present study, food concentrations were most likely constant across the short contours at a given shore level, while habitat degree-hours increased from wave-exposed to sheltered regions. Thus, we infer that temperature stress played a significant role in the correlated attenuation in growth rates and terminal sizes toward sheltered portions of shore. The large variation in maximum temperatures between wave-exposed and sheltered microhabitats observed over 11 days at Crystal Cove State Park further indicates the high potential for stressful events at the high-shore-sheltered edge of mussel beds.

An assumption of this discussion and of Fritzgerald-DeHoog et al. (2012) is that relatively high wave action promotes wave wash and splash, which cool mussels and reduce the durations of low-tide temperature stress. Wave wash is turbulent and highly aerated, so it seems doubtful it would support effective filter-feeding. However, M. californianus is adapted to feeding on the most wave-beaten shores, and it is possible that higher wave wash and flow speeds enhance energy acquisition at the exposed end of headlands. The precise contributions of wash and flow speed to feeding remains to be assessed.

Although temperature undoubtedly has an effect on growth in M. californianus, we still do not know how absolute temperature, rate of heating, number of acute thermal events, and duration of heating integrate to induce a particular cellular response and eventual phenotype. Resolving such complex mechanisms requires focused high-resolution field and laboratory experimental designs, including long-term (months) repeated measurements of environmental factors and the procurement of detailed stress-related and bioenergetics data. Particularly needed are critical environmental-physiological analyses, including additional measurements of heat-shock-response messenger RNA transcripts and stress-related proteins (i.e., HSP, arginine kinase activity), observations of resource acquisition and food-processing mechanisms (i.e., digestive enzyme activity, valve gape activity, gut morphology), and measurements of metabolism (i.e., respiration, metabolomics, ATP/ADP ratio). An integration of these measurements will support parameterization of dynamic energy budget models (Matzelle et al., 2014) that, when linked with long-term local climate analyses (functional trait niche models; Kearney et al., 2010), will greatly increase the predictive power of complex climate envelope models.

A generally accepted principle, based upon previous studies of mussel physiology and abiotic processes within the intertidal environment, is that mussels highest on the shore persist at or near their thermal tolerance limits and that future increases in temperature will result in losses of those populations first (Somero, 2002; Petes et al., 2007; Harley, 2011). Our temperature data suggest that vulnerability to the negative effects of temperature rises with increasing shore level and decreasing wave exposure. Thus, increases in temperature may eventually shift the boundaries of intertidal organisms toward low-shore and wave-swept points of headlands rather than simply down-shore. Alternatively, mussels may acclimatize in the short term or adapt over the long term to thermal stress during the course of a changing climate, thereby reducing a direct thermal risk (see Logan et al, 2012). The ability to acclimatize to thermal stress in the field following laboratory thermal acclimation has been shown in a number of intertidal species including M. californianus (Stillman and Somero, 2000; Stenseng et al., 2005; Willett, 2010; Fitzgerald-De-hoog et al., 2012). However, in natural settings, increasing temperatures of air and water may negatively impact nearshore phytoplankton production (Boyce et al., 2010), which could hypothetically circumvent any gains acquired through thermal acclimatization or adaptation. We are only at the beginning stages of collecting the volume of data necessary to resolve these complex issues.

As expected, growth curves represented by the Gulland and Holt (G&H) growth plots displayed spatial trends. While in general agreement with our simple expression of the Von Bertalanffy growth model, slope height increased with increasing exposure and decreasing shore level. How ever, the G&H plots diverged from the model in two important respects: (1) slopes varied between microhabitats, whereas the Von Bertalanffy model we used assumes that the slopes will be the same while intercepts differ for microhabitats with,different food availabilities (e.g., different shore levels); and (2) some G&H plots were slightly positive because some individuals exhibited slightly negative growth. Negative growth may have occurred as a consequence of a reduction in soft tissue and mantle retraction following the period after dye deposition. This mechanism causes new growth to occur slightly below the posterior shell margin and over time leads to smaller length-to-width ratios in slow-growing mussels (Dehnel, 1956). Slopes were progressively more negative with increasing wave exposure and decreasing shore level. As a consequence, the x-intercepts of the curves estimated for sheltered microhabitats predicted larger terminal sizes for mussels in those locations than for those in high-flow locations. Thus, direct measurements of shell lengths rather than predictions (x-intercept) by G&H growth plots may be a preferred method of measuring terminal sizes in natural populations of M. californianus.

We suggest several reasons for the unequal slopes of the growth curves. Most simply, mussels that did not deposit calcein were not included in the growth regressions. There was a greater percentage of non-depositors in the low-flow areas. The exclusion of the non-depositors may have biased the curves for low-flow populations upward. Furthermore, losses of individuals due to storms or predation could have also skewed results. Another possible mechanism is variation in energy allocation moderated by environmental factors. Mussels in optimal microenvironments reach sexual maturity faster and reallocate a greater fraction of assimilated energy to gamete production (Thompson, 1984; Rodhouse et al., 1986), while those in less optimal environments may delay gamete production in favor of somatic growth. As a result, those in optimal environments achieve a smaller terminal size, and those in sub-optimal environments achieve a larger size than would occur without the reallocations. This reallocation ensures a greater output when reproduction does commence, and the additional byssus and shell mass may allow the elevated survivorship this "strategy" requires. Although these hypotheses appear amenable to experimentation, such work is beyond the scope of this study.

Growth in M. californianus is complex, involving both exogenous and endogenous factors (Koehn and Gaffney, 1984; Fitzgerald-Dehoog et al., 2012). Our use of calcein to measure growth at the scale of millimeters allowed for short-term comparisons over small spatial scales, which in turn provides more insight into environmental-growth interactions. Many of the mussels in this study exhibited no growth over the 3-mon interval. One would expect that long-term observations of these individuals would provide a window into temporal variation, including episodes of optimal growth conditions. Repeated calcein injections coupled with repeated measurements of environmental factors might also support refinements to the spatial growth model. Lastly, our data suggest that temperature is the main driver of growth patterns along the wave-exposure contours of mussel beds. However, the integration of our findings with more complex studies of hydrodynamics (Ackerman, 1999), indicated that body temperatures (rather than habitat temperatures) (Helmuth, 1998), filtration/ingestion rates (Butman et al., 1994), and experiments involving molecular, biochemical, and behavioral responses (Michaelidis et al, 2014) should further reduce the unexplained variation of in situ growth of M. californianus, which stands as a fundamental illustration of size-dependent interactions.

Temperature and wave action in the intertidal environment vary in complex spatial mosaics with features that sometimes seem counterintuitive (Helmuth et al. 2006; Denny et al., 2011). The large-scale pictures of greatest interest to climate change and other environmental research are made up of the fine-scale pixels of the organisms' immediate surroundings. However, small-scale variation can match or exceed differences in mean values separated by large distances. The present study shows that on uniform, gently sloping shores, mussel growth and key physical parameters co-varied regularly and predictably at small scales.

Acknowledgments

This work was supported by a grant from the National Science Foundation, NSF HRD-0317772. A portion of this work was also supported by the University of California, Irvine, and the University of California President's Postdoctoral Fellowship. The authors thank Desiree R. Valdez for assisting with growth-rate measurements. We also extend our gratitude to the staff at Bamfield Marine Station and Crystal Cove State Park for their support.

Literature Cited

Ackerman, J. D. 1999. Effect of velocity on the filter feeding of dreissenid mussels (Dreissena polymorpha and Dreissena bugensis): implications for trophic dynamics. Can. J. Fish. Aquat. Sci. 56: 1551-1561.

Bayne, B. L., P. N. Salkeld, and C. M. Worrall. 1983. Reproductive effort and value in different populations of the marine mussel, Mytilus echdis L. Oecologia 59: 18-26.

Blanchette, C. A., B. Helmuth, and S. D. Gaines. 2007. Spatial patterns of growth in the mussel. Mytilus californianus, across a major oceanographic and biogeographic boundary at Point Conception, California, USA. J. Exp. Mar. Biol. Ecol 340: 126-148.

Boyce, D. G., M. R. Lewis, and B. Worm. 2010. Global phytoplankton decline over the past century. Nature 466: 591-596.

Buckley, B. A., M.-E. Owen, and G. E. Hofmann. 2001. Adjusting the thermostat: The threshold induction temperature for the heat-shock response in intertidal mussels (genus Mytilus) changes as a function of thermal history. J. Exp. Biol. 204: 3571-3579.

Butman, C. A., M. Frechette, W. R. Geyer, and V. R. Starczak. 1994. Flume experiments on food supply to the blue mussel Mytilus edulis L. as a function of boundary-layer flow. Limnol. Oceanogr. 39: 1755-1768.

Caceres-Martinez, J., J. A. F. Robledo, and A. Figueras. 1994. Settlement and post-larvae behaviour of Mytilus galloprovincialis: field and laboratory experiments. Mar. Ecol. Prog. Ser. 112: 107-117.

Carrington Bell, E., and M. W. Denny. 1994. Quantifying "wave ,exposure": a simple device for recording maximum velocity and results of its use at several field sites. J. Exp. Mar. Biol. Ecol. 181: 9-29.

Connor, K. M., and A. Y. Gracey. 2011. Circadian cycles are the dominant transcriptional rhythm in the intertidal mussel Mytilus californianus. Proc. Natl. Acad. Sct USA 108: 16110-16115.

Dahlhoff, E. P., and B. A. Menge. 1996. Influence of phytoplankton concentration and wave exposure on the ecophysiology of Mytilus californianus. Mar. Ecol. Prog. Ser. 144: 97-107.

Dayton, P. K. 1971. Competition, disturbance, and community organization: the provision and subsequent utilization of space in a rocky intertidal community. Ecol. Monogr. 41: 351-389.

de Paula, S. M., and M. Silveira. 2009. Studies on molluscan shells: contributions from microscopic and analytical methods. Micron 40: 669-690.

Dehnel, P. A. 1956. Growth rates in latitudinally and vertically separated populations of Mytilus californianus. Biol. Bull. 110: 43-53.

Denny, M. W., W. W. Dowd, L. Bilir, and K. J. Mach. 2011. Spreading the risk: small-scale body temperature variation among intertidal organisms and its implications for species persistence. J. Exp. Mar. Biol. Ecol. 400: 175-190.

Dolmer, P., and E. Stenalt. 2010. The impact of the adult blue mussel (Mytilus edulis) population on settling of conspecific larvae. Aquac. Int. 18: 3-17.

Dowd, W. W., and G. N. Somero. 2013. Behavior and survival of Mytilus congeners following episodes of elevated body temperature in air and seawater. J. Exp. Biol. 216: 502-514.

Fitzgerald-Dehoog, L., J. Browning, and B. J. Allen. 2012. Food and heat stress in the California mussel: evidence for an energetic trade-off between survival and growth. Biol. Bull. 223: 205-216.

Fitzhenry, T., P. Halpin, and B. Helmuth. 2004. Testing the effects of wave exposure, site, and behavior on intertidal mussel body temperatures: applications and limits of temperature logger design. Mar. Biol. 145: 339-349.

Frechette, M., and E. Bourget. 1985. Food-limited growth of Mytilus edulis L. in relation to the benthic boundary layer. Can. J. Fish. Aquat. Sci. 42: 1166-1170.

Gracey, A. Y., M. L. Chaney, J. P. Boomhower, W. R. Tyburczy, K. Connor, and G. N. Somero. 2008. Rhythms of gene expression in a fluctuating intertidal environment. Curr. Biol. 18: 1501-1507.

Gulland, J. A., and S. J. Holt. 1959. Estimation of growth parameters for data at unequal time intervals. ICES J. Mar. Sci. 25: 47-49.

Halpin, P. M., B. A. Menge, and G. E. Hofmann. 2004. Experimental demonstration of plasticity in the heat shock response of the intertidal mussel Mytilus californianus. Mar. Ecol. Prog. Ser. 267: 137-145.

Harley, C. D. G. 2008. Tidal dynamics, topographic orientation, and temperature-mediated mass mortalities on rocky shores. Mar. Ecol. Prog. Ser. 371: 37-46.

Harley, C. D. G. 2011. Climate change, keystone predation, and biodiversity loss. Science 334: 1124-1127.

Helmuth, B. 1999. Thermal biology of rocky intertidal mussels: quantifying body temperatures using climatological data. Ecology 80: 15-34.

Helmuth, B., and M. W. Denny. 2003. Predicting wave exposure in the rocky intertidal zone: Do bigger waves always lead to larger forces? Limnol. Oceanogr. 48: 1338-1345.

Helmuth, B., C. D. G. Harley, P. M. Halpin, M. O'Donnell, G. E. Hofmann, and C. A. Blanchette. 2002. Climate change and latitudinal patterns of intertidal thermal stress. Science 298: 1015-1017.

Helmuth, B., B. R. Broitman, C. A. Blanchette, S. Gilman, P. Halpin, C.D. G. Harley, M. J. O'Donnell, G. E. Hofmann, B. Menge, and D.Strickland. 2006. Mosaic patterns of thermal stress in the rocky intertidal zone: implications for climate change. Ecol. Monogr. 76: 461-479.

Helmuth, B. S. T. 1998. Intertidal mussel microclimates: predicting the body temperature of a sessile invertebrate. Ecol. Monogr. 68: 51-74.

Hofmann, G. E., and G. N. Somero. 1995. Evidence for protein damage at environmental temperatures: seasonal changes in levels of ubiquitin conjugates and hsp70 in the intertidal mussel Mytilus trossulus. J. Exp. Biol. 198: 1509-1518.

Kaehler, S., and C. D. McQuaid. 1999. Use of the fluorochrome calcein as an in situ growth marker in the brown mussel Perna perna. Mar. Biol. 133: 455-460.

Kearney, M., S. J. Simpson, D. Raubenheimer, and B. Helmuth. 2010. Modelling the ecological niche from functional traits. Philos. Trans. R. Soc. Land. B Biol. Sci. 365: 3469-3483.

Koehn, R. K., and P. M. Gaffney. 1984. Genetic heterozygosity and growth rate in Mytilus edulis. Mar. Biol. 82: 1-7.

Kopp, J. C. 1979. Growth and the intertidal gradient in the sea mussel Mytilus californianus. Conrad 1897. Veliger 22: 51-56.

Lindquist, S. 1998. The heat shock proteins. Annu. Rev. Genet. 22: 631-677.

Logan, C. A., L. E. Kost, and G. N. Somero. 2012. Latitudinal differences in Mytilus californianus thermal physiology. Mar. Ecol. Proger. 450: 93-105.

Matzelle, A., V. Montalto, G. Sara, M. Zippay, and B. Helmuth. 2014. Dynamic energy budget model parameter estimation for the bivalve Mytilus californianus: application of the covariation method. J. Sea Res. 94: 105-110.

McGrath, D., P. A. King, and E. M. Gosling. 1988. Evidence for the direct settlement of Mytilus edulis larvae On adult mussel beds Mar. Ecol. Prog. Ser. 47: 103-106.

McQuaid, C. D., and T. L. Lindsay. 2000. Effect of wave exposure on growth and mortality rates of the mussel Perna perna: bottom-up regulation of intertidal populations. Mar. Ecol. Prog. Ser. 206: 147-154.

Meager, J., T. Schlacher, and M. Green. 2011. Topographic complexity and landscape temperature patterns create a dynamic habitat structure on a rocky intertidal shore. Mar. Ecol. Prog. Ser. 428: 1-12.

Menge, B. A. 1992. Community regulation: Under what conditions are bottom-up factors important on rocky shores? Ecology 73: 755-765.

Menge, B. A., E. L. Berlow, C. A. Blanchette, S. A. Navarrete, and S. B. Yamada. 1994. The keystone species concept: variation in interaction strength in a rocky intertidal habitat. Ecol. Monogr. 64: 249-286.

Michaelidis, B., H.-O. Portner, I. Sokolova, and L. Tomanek. 2014. Advances in predicting the impacts of global warming on the mussels Mytilus galloprovincialis in the Mediterranean sea. Pp. 319-339 in The Mediterranean Sea, S. Goffredo and Z. Dubinsky, eds. Springer, Dordrecht, The Netherlands.

Mislan, K. A. S., C. A. Blanchette, B. R. Broitman, and L. Washburn. 2011. Spatial variability of emergence, splash, surge, and submergence in wave-exposed rocky-shore ecosystems. Limnol. Oceanogr. 56: 857-866.

Paine, R. T. 1974. Intertidal community structure. Oecologia 15: 93-120.

Paine, R. T. 1976. Size-limited predation: an observational and experimental approach with the Mytilus-Pisaster interaction. Ecology 57: 858-873.

Petes, L. E., B. A. Menge, and G. D. Murphy. 2007. Environmental stress decreases survival, growth, and reproduction in New Zealand mussels. J. Exp. Mar. Biol. Ecol. 351: 83-91.

Petes, L. E., B. A. Menge, and A. L. Harris. 2008. Intertidal mussels exhibit energetic trade-offs between reproduction and stress resistance. Ecol. Monogr. 78: 387-402.

Roberts, D. A., G. E. Hofmann, and G. N. Somero. 1997. Heat-shock protein expression in Mytilus californianus: acclimatization (seasonal and tidal-height comparisons) and acclimation effects. Biol. Bull. 192: 309-320.

Robles, C., and R. Desharnais. 2002. History and current development of a paradigm of predation in rocky intertidal communities. Ecology 83: 1521-1536.

Robles, C., D. Sweetnam, and J. Eminike. 1990. Lobster predation on mussels: shore-level differences in prey vulnerability and predator preference. Ecology 71: 1564-1577.

Rodhouse, P. G., J. H. McDonald, R. I. E. Newell, and R. K. Koehn. 1986. Gamete production, somatic growth and multiple-locus enzyme heterozygosity in Mytilus edulis. Mar. Biol. 90: 209-214.

Schneider, K. R. 2008. Heat stress in the intertidal: comparing survival and growth of an invasive and native mussel under a variety of thermal conditions. Biol. Bull. 215: 253-264.

Seed, R. 1980. Shell growth and form in the bivalvia. Pp. 23-67 in Skeletal Growth of Aquatic Organisms: Biological Records of Environmental Change, D. C. Rhoads and R. A. Lutz. eds. Plenum Press, New York.

Somero, G. N. 2002. Thermal physiology and vertical zonation of intertidal animals: optima, limits, and costs of living. Integr. Comp. Biol. 42: 780-789.

Steffani, C. N., and G. M. Branch. 2003. Growth rate, condition, and shell shape of Mytilus galloprovincialis: responses to wave exposure. Mar. Ecol. Prog. Ser. 246: 197-209.

Stenseng, E., C. E. Braby, and G. N. Somero. 2005. Evolutionary and acclimation-induced variation in the thermal limits of heart function in congeneric marine snails (genus Tegula): implications for vertical zonation. Biol. Bull. 208: 138-144.

Stillman. J. H., and G. N. Somero. 2000. A comparative analysis of the upper thermal tolerance limits of eastern Pacific porcelain crabs, genus Petrolisthes: influences of latitude, vertical zonation, acclimation, and phylogeny. Physiol. Biochem. Zool. 73: 200-208.

Thompson, R. J. 1984. The reproductive cycle and physiological ecology of the mussel Mytilus edulis in a subarctic, non-estuarine environment. Mar. Biol. 79: 277-288.

Tomanek, L., and M. J. Zuzow. 2010. The proteomic response of the mussel congeners Mytilus galloprovincialis and M. trossulus to acute heat stress: implications for thermal tolerance limits and metabolic costs of thermal stress. J. Exp. Biol. 213: 3559-3574.

Widdows, J., and B. E. Bayne. 1971. Temperature acclimation of Mytilus edulis with reference to its energy budget. J. Mar. Biol. Assoc. UK 51: 827-843.

Willett, C. S. 2010. Potential fitness trade-offs for thermal tolerance in the intertidal copepod Tigriopus californicus. Evolution 64: 2521-2534.

KWASI M. CONNOR (1)* AND CARLOS D. ROBLES (2)

(1) Department of Ecology and Evolutionary Biology, University of California, Irvine, California 92697; and (2) Department of Biological Sciences, California State University Los Angeles, 5151 State University Drive, Los Angeles, California 90032

(*) To whom correspondence should be addressed. E-mail: kconnor@uci.edu

Received 10 February 2014; accepted 17 November 2014.

Table 1
Constants of the Von Bertalanffy growth model, predicted by Gulland
and Holt (G&H) regressions

Site            n        k         L[infinity] (mm)       P

(a)Laguna
   Al          98       -0.11         107.64              0.00
   Bl          62       -0.10         109.10              0.00
   C1          57       -0.11         111.73              0.00
   Dl          68       -0.12         119.00              0.00
   A2         101        0.01            --               0.15
   B2          68        0.01            --               0.38
   C2          37       -0.01            --               0.49
   D2          41       -0.04         117.50              0.03
(b) Helby
   C1          32       -0.05         171.00              0.00
   A2          87        0.00            --               0.58
   B2          50        0.00            --               0.23
   C2          61       -0.04         136.00              0.00
   A3          34        0.00            --               0.66
   B3          19        0.00            --               0.79
   C3          40       -0.01            --               0.18

The constants include k = slope and L[infinity] = terminal size. P
values represent hypothesis testing of G&H regressions. Terminal sizes
were excluded from the table where slopes were near zero and the
P > 0.05.

Table 2
Mytilus californianus: ANCOVA analyses of new shell deposition at
Laguna, between levels of wave exposure and shore height

Source                      df        MS         F         P

Shore level                  1      291.87     90.97      0.00
Wave exposure                1       34.99     10.91      0.00
Initial shell length         1      159.80     49.81      0.00
Shore level X in. length     1      103.04     32.12      0.00
Wave exp. X in. length       1        6.91      2.15      0.14
Shore level X wave exp.
X in. length                 1        2.64      0.823     0.37
Shore level X wave exp       1        4.46      1.40      0.24
Error                      299        3.21

The group variables are site and level and the covariate is initial
shell length.

Table 3
Mytilus californianus: ANCOVA analyses of new shell deposition at
Helby, between levels of wave exposure and shore heigh

Source                     df         MS         F        P

Shore level                 1        9.21      15.04     0.00
Wave exposure               1       12.59      20.55     0.00
Initial shell length        1        2.67       4.36     0.04
Shore level X in. length    1        1.20       1.95     0.16
Wave exp. X in. length      1        1.74       2.84     0.09
Shore level X wave
exp. X in. length           1       10.27      16.77     0.00
Shore level X wave exp      1        1.05       1.71     0.19
Error                     214        0.61
COPYRIGHT 2015 University of Chicago Press
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2015 Gale, Cengage Learning. All rights reserved.

Article Details
Printer friendly Cite/link Email Feedback
Author:Connor, Kwasi M.; Robles, Carlos D.
Publication:The Biological Bulletin
Article Type:Report
Date:Feb 1, 2015
Words:7932
Previous Article:Development and larval feeding in the capitellid annelid Notomastus cf. tenuis.
Next Article:Biogeography of Phallusia nigra: is it really black and white?
Topics:

Terms of use | Privacy policy | Copyright © 2021 Farlex, Inc. | Feedback | For webmasters |