The formation of landscapes is a dynamic and hierarchical process involving the interaction of physical factors and biotic components (Levin 1976; Collins 1992; Dale 2000; Turner, Gardner & O’Neill 2001). Understanding not just the temporal, but also the spatial variation in the interaction of biology, environment and disturbance which shapes landscapes is one of the central challenges in ecology and requires that spatial complexity be estimated. Using indices of spatial heterogeneity, it is possible to describe the complexity of different levels of organization within an ecosystem (from the level of an individual organism to that of a community), and also of the factors influencing the spatial patterns observed, such as disturbance (Veen et al. 2008). Spatial heterogeneity is defined as the degree of spatial dependence between the variance of a variable and some spatial dimension (Palmer 1988; Dungan et al. 2002). Grazing is one of the fundamental trophic interactions that modulate landscapes by creating spatial patterns in the vegetation in both terrestrial (Belsky 1983; Burns, Collins & Smith 2009) and marine systems (Underwood & Jernakoff 1984; Coleman et al. 2006), and has traditionally been examined using grazer exclusion experiments. Here we use grazing effects on a rocky shore as a case study to analyse how different physical and biological effects interact to shape the landscape of a marine rocky shore across a gradient of desiccation stress. We focus on marine benthic systems, but note parallels in the development of our understanding of grazer–plant interactions in terrestrial systems.
State of the Art
Grazing in intertidal landscapes
The biology of rocky shores exhibits complex spatial configurations at small scales because of the continuously changing balance between marine and terrestrial conditions. For simplicity these landscapes are traditionally divided into three major regions or zones, which vary in distance and height from the mean height of low water spring tides (MLWS): low, mid and high shore (Hawkins & Hartnoll 1983; Menge & Branch 2001). These regions differ in the diversity, strength of trophic interactions and spatial heterogeneity of the organisms they support because they represent regions along a gradient of stress that marine organisms suffer when exposed to increasingly terrestrial conditions (Hawkins & Hartnoll 1983; Foster 1992; Menge & Branch 2001).
From the 1960s to the 1970s, considerable effort was expended in identifying the proximal causes of zonation. The overall conclusion was that intertidal landscapes are shaped by physical factors represented by two gradients of stress: that of emersion (desiccation and heat, or freezing in cold latitudes) when the tide retreats (this gradient increases upshore (Southward 1975)) and that of wave action, which increases downshore and towards high tide. Wave action simultaneously causes disturbance through dislodgement of organisms and delivers propagules. Parallel to the search for the role of physical factors in causing zonation, other studies examined the role of biotic factors such as grazing and predation. These latter studies included the use of predator exclusion approaches, such as predator removal from some areas and the use of exclusion cages (Connell 1961; Kitching & Ebling 1961; Paine 1966; Dayton 1971). From the 1970s to the 1980s, grazing and predation were studied at different levels on the shore, focusing on how the interplay between abiotic and biotic factors drives zonation (Lubchenco 1978; Sousa 1979; Underwood 1980; Branch 1981; Jara & Moreno 1984; Underwood & Jernakoff 1984). Since the late 1990s two divergent lines of approach have developed. Some studies have examined changes in community structure at large spatial scales of hundreds of kilometres (bioregional and continental scales) using grazing exclusions (Bustamante, Branch & Eekhout 1995a; Bustamante et al. 1995b; Menge & Branch 2001; Coleman et al. 2006). These studies showed that there is high variability induced by the regional conditions in which a system is embedded. In these studies, patchiness within zones at small scales was almost always observed. This was usually reported but not quantified, and sometimes considered as ‘residual variability’ or variability not explained by the trophic interaction analysed in both terrestrial (Belsky 1983) and marine systems (Benedetti-Cecchi 2000). However, species interactions occur on much smaller spatial scales that depend on the physical size and mobility of the organisms and at the same time other studies focused on the meaning of such small-scale patchiness, considering it as emanating from the inequality in distribution of benign and harsh conditions for each species. Abundances of species vary accordingly, as does the strength of their interactions. For example in the case of rocky shores, small-scale topographic complexity can create humid depressions where conditions are benign for seaweeds and grazers, weakening the effects of grazers on algae, because grazers also received benefits through an increase of food availability (Williams 1993, 1994; Benedetti-Cecchi & Cinelli 1995; Williams, Davies & Nagarkar 2000). The interactive effects of grazing and disturbance were also studied in terrestrial systems in the late 1990s (Milchunas & Lauenroth 1989; Collins 1990, 2000; Knapp et al. 1999; Collins & Smith 2006) and, as with marine systems (Atalah, Anderson & Costello 2007), inequality in the distribution of disturbance and grazers was found to influence plant patchiness (Adler, Raff & Lauenroth 2001; Veen et al. 2008). At the same time, others investigated the small-scale effects of grazers in relation to variations in primary productivity and the consequences for overall algal or plant assemblages (Bakker, de Leeuw & van Wieren 1983; Belsky 1983; Branch et al. 1992; McQuaid & Froneman 1993).
All these past efforts seemed to be framed in a context of spatial reductive determinism with an unstated assumption that spatial patterns in landscapes as a whole can be predictable if it is possible to calculate each factor exactly. Finally, towards the 2000s, intertidal studies started to re-focus on predicting certain types of spatial and temporal configurations, for example random versus non-random spatial arrangements or temporal cycles of abundance and recruitment of species (Schaffer & Kot 1985; Johnson et al. 1997; Burrows & Hawkins 1998; Johnson, Burrows & Hawkins 1998; Menge et al. 2005). Spatial statistics have started to play a strong role in the identification of non-random patterns and in estimating the complexity of systems (Dale et al. 2002; Denny et al. 2004), while other studies have concentrated on explaining spatial variability of resources in trophic interactions without taking into account either the spatial structure of the resources or the spatial structure of the trophic interaction (Berlow 1999; Benedetti-Cecchi 2000, 2003). Previous studies have aimed at understanding the scales at which ecological processes occur in the intertidal, using several geostatistical tools (Denny et al. 2004; Erlandsson & McQuaid 2004). However, in the intertidal, the across-shore gradient from low-shore marine to high-shore terrestrial conditions forms a spectacularly intense gradient of physiological stress and these studies have mainly examined processes along the shore at the same tidal height, i.e. at the same point along the marine to terrestrial gradient. Here, we analyse the spatial structure in the variability of a trophic interaction across this gradient, expecting to find a gradual decay in the variance of this interaction as the severity of abiotic conditions (as perceived by marine species) increases across the landscape.
Grazer size classes
A further source of complexity is the mode of feeding and the size of grazers. Algal spatial patterns can be extremely complex when different types and sizes classes of grazers converge to inhabit the same parts of the shore simultaneously. Grazers can affect algae at two ontogenetic stages: by consuming (i) adult plants or (ii) algal sporelings and propagules (Hawkins & Hartnoll 1983; McQuaid 1996; Johnson et al. 1997; Burrows & Hawkins 1998). We categorized grazers according to body size as macrograzers, mesograzers and micrograzers, as size closely correlates with both mode of feeding and diet, and we were able to exclude different size classes in our experimental treatments. These types of grazers often coexist within zones so that their effects are interactive (McQuaid 1982), but they show broad trends of differential vertical distribution (Hawkins & Hartnoll 1983; Branch et al. 1992; Foster 1992; Menge & Branch 2001). We predicted that the strength of grazing effects on the algal community will depend partly on the balance of the size classes of the grazers present.
Grazing strength across the shore
Models of the intensity of grazing effects as a function of distance up the shore describe impact as increasing with elevation up to the mid shore, after which the importance of grazing diminishes towards the high shore (Hawkins & Hartnoll 1983; Foster 1992). While this scheme has been supported many times (e.g. Menge et al. 1986; Kaehler & Williams 1997, 1998) using traditional experimental designs, it does not consider the effects of grazer size or the existence of smaller scale variability and spatial structure in grazing effects. For example, topographic variability will alter grazing effects, influencing their spatial structure (i.e. the existence of patchiness, gradients or random patterns in grazing effects). Because traditional experimental designs involve random distribution of experimental units, they cannot provide information on the spatial structure of a variable. Here we used an alternative approach involving geostatistical tools (Dale 2000; Turner, Gardner & O’Neill 2001) to examine the relationship of grazing effects with topographic complexity and grazer size classes.
Comparison of results between the traditional approach which only considers the effects of grazing on the biomass of algae (classical zonation design) and a geostatistical approach that considers and describes numerically the spatial patterns of grazing effects on different algae was the main objective of this study. This objective was achieved by examining the following hypotheses:
- 1 Grazing affects algal biomass and species composition at all levels on the shore and the results will be in agreement with the zonation schemes of Hawkins & Hartnoll (1983) and Foster (1992).
- 2 Micro-, meso- and macrograzers influence the algal community differently. Consequently, the effect of grazing will change according to the abundances of different size classes of grazers among different heights and habitats on the shore.
- 3 The effect strength of grazing exhibits spatial structure across the shore driven by the interaction of biotic and abiotic factors.
- 4 The relationship between the spatial structure of grazing effects and these factors changes in time as the balance among these factors shifts.