Local‐ and regional‐scale effects of wave exposure, thermal stress, and absolute versus effective shore level on patterns of intertidal zonation

Abstract

Rocky intertidal ecosystems are characterized by marked zonation patterns in which species replace one another along the vertical gradient of emersion time. Yet, we still do not fully understand the reasons that zonation patterns are variable in space and time. Here, we use effective shore level (ESL), a metric that incorporates the modifying influence of wave splash, to describe the relationship between uninterrupted emersion time and the zonation patterns of two ecologically important species: the mussel Mytilus californianus and the barnacle Balanus glandula. At the local scale (10s to 100s of meters) on Tatoosh Island, the upper limits of both species are closely related to ESL, regardless of substrate aspect or maximum temperature. At larger spatial scales (10s to 100s of kilometers), the upper limit of Balanus is related to ESL at cool sites but not at hotter sites. Thus, although ESL explains most of the local-scale variation in zonation at a cool site, other factors (temperature, desiccation) likely become important as spatial scale increases to incorporate warmer sites. Our results emphasize that an understanding of where and when specific ecological factors are limiting is crucial for our ability to explain and predict large-scale biological patterns in space and time.Recent advances in physiology, ecology, and biological oceanography have considerably improved our understanding of the environmental factors that generate and maintain biological pattern in the marine environment (Bertness et al. 2001;Dahlhoff et al. 2001; Helmuth and Hofmann 2001). Emerging from this recent work is the realization that the importance of any given environmental driver may vary tremendously through space and time (e.g., Bertness and Ewanchuk 2002). The present challenge for ecologists is to understand when and where organisms respond to specific drivers in their environment. Only with such an understanding will we be able to predict the ecological outcomes of perturbations resulting from resource extraction, changes in species composition (e.g., species introductions and extinctions), and changes in climate.In intertidal systems, environmental conditions range from fully aquatic to fully terrestrial over the space of a few vertical meters.

Contingencies and compounded rare perturbations dictate sudden distributional shifts during periods of gradual climate change

“…Waves have the potential to interrupt stress events by rehydrating organisms and by resetting body temperatures to that of sea water (14). Thus, the upper limits of sessile species, including M. parksii, are generally higher on the shore in areas of increasing wave exposure (14)(15)(16).…”

Interactive effects of grazing and environmental stress on macroalgal biomass in subtropical rocky shores: Modulation of bottom-up inputs by wave action

“…This is achieved by creating turbulence and reducing the thickness of the boundary layer over the plant surface, thus increasing the flux of molecules from the external fluid to plant cells (Hurd, 2000;Wheeler, 1980). Lower on the shore, effective immersion time is increasingly dominated by tides and less by waves (Harley and Helmuth, 2003) and, therefore, nutrient fluxes among shores of different wave exposure should be more similar and more dependent on local currents and turbulence. In situ measurements of nutrients and experimental manipulations (e.g.…”

Evaluation of effective shore level as a method of characterizing intertidal wave exposure regimes

“…Such calculations have been made only occasionally (e.g., Glynn 1965, Druehl andGreen 1970), presumably because they are tedious and difficult to conduct comparatively for multiple locations. Harley and Helmuth (2003) described a method for identifying immersion events from time series of intertidal temperature. Their method relied on miniature submersible temperature dataloggers that store high-frequency (twice an hour or faster) time series of temperature data for periods of 1 to 6 months.…”

“…Their method relied on miniature submersible temperature dataloggers that store high-frequency (twice an hour or faster) time series of temperature data for periods of 1 to 6 months. Harley and Helmuth (2003) used a sudden sharp drop in temperature (3°C over 20 min) on a rising tide to identify immersion events during the daytime, when cooler seawater engulfs a temperature logger that has previously been warming from exposure to terrestrial climate. Once the tide height and wave height at the time of the immersion event are identified for many such events, regression can be used to calculate the effect of wave action on the tidal height of immersion (Figure 1b).…”