Scale is one of the critical factors in ecology because our perception of most ecological variables and processes depends upon the scale at which variables are measured (Legendre et al. 1997; Martins et al. 2008). The analysis of spatial patterns is a preliminary step before testing experimental hypothesis because results of these experiments are scale dependent (Underwood and Chapman 1996; Hewitt et al. 2007).
Results of the present study indicated that most of the univariate analyses showed no significant variability at any of the studied spatial scales. Therefore, variability of the most common species, functional groups (except for the foliose group) and total biomass were invariant to spatial scale. However, the number of macroalgal taxa showed significant variability at the scale of site. In contrast with univariate results, multivariate analyses indicated that macroalgal assemblages at the species and functional group level showed significant variability at all studied spatial scales except for area.
Broitman and Kinlan (2006) proposed that lower-trophic-level species tend to be controlled by bottom-up processes (e.g. light, nutrient availability or temperature) at broad scales (100 or 1,000 s of kilometres). However, at the scale of 10 s of kilometres, like in our study, these processes seem to have a homogenous effect along the whole studied area except for the foliose functional group. The latter was mainly composed by species of the genus Ulva that are ephemeral, fast-growing macroalgae with a high capacity to respond to nutrient pulses (Karez et al. 2004). Due to their ecophysiological traits, the abundance of these species is very variable (Rubal et al. 2011). Therefore, the variability of this group between the two studied areas could be related to temporal changes in nutrient availability. Variations in nutrient availability should be more related to local nutrients inputs than with upwelling events, because upwelling seems to have a homogenous effect on the studied areas as aforementioned. However, coastal locations close to urban centres, such as Cabo do Mundo in the southern area, showed much higher nutrient values in winter (5.12 μmol L−1 of nitrate and 8.14 μmol L−1 of phosphate) than isolated locations in the north, such as Moledo (0.21 μmol L−1 of nitrate and 1.24 μmol L−1 of phosphate) (Rubal unpublished data).
At the scale of location (kilometres), however, significant variability was detected for macroalgal assemblages at the level of species and functional groups. Wave exposure is a common process responsible for variability between macroalgal assemblages at this scale (Tuya and Haroun 2006). The studied locations present a high variability in nearshore bathymetry and extent of the shore, but grade of exposure has not been measured. These two variables can play an important role in attenuating local wave power (Burrows et al. 2008) and thus affecting the structure of assemblages. Moreover, harvesting and trampling could be important processes acting at this spatial scale. Many of the studied locations such as Foz, Aguda, Amorosa and Viana are exposed to an intense seasonal trampling due to recreational activities in summer, and Araújo et al. (2009) found negative effects of trampling on macroalgal assemblages. Harvesting of invertebrates such as sea urchins is noticeable in many locations such as Viana or Belinho (personal observation). Sea urchin is one of the main grazers in the considered tidal level, and many previous studies have shown that sea urchins play a central role in shaping macroalgal communities (Paine and Vadas 1969; Palacín et al. 1998). Therefore, the elimination or reduction of sea urchins could have significant effects on macroalgal assemblages, especially due to the slow recolonization of this species after harvesting (Palacín et al. 1997).
At the scale of site (100 s of metres), significant variability was detected for the total number of species and for macroalgal assemblages, both at the level of species and functional groups. Differences in the substrate slope, pre-emption and grazing pressure are potential processes responsible for variability at this spatial scale. These factors have been mentioned as responsible for differences between sites in the previous studies (e.g. Benedetti-Cecchi et al. 1999, 2001).
The relative importance of different spatial scales in the hierarchy varied with different species and functional groups. However, the major and consistent result was that the proportion of multivariate and univariate variance at the smallest spatial scale (among quadrats) contributed most to the total variance. Such large variance at small spatial scales (metres) has been reported in many other studies (see review by Fraschetti et al. 2005), and it seems to be a common feature of rocky intertidal assemblages. However, the small spatial scale variability observed in this study was quite large in comparison with the previous studies, suggesting the great importance of processes acting at this scale in the study region. Sedimentation, dispersal of propagules and post settlement processes such as competition, grazing and desiccation are potential factors that can explain variation on small spatial scales (Coleman 2002). Moreover, Anderson et al. (2005a) have indicated that small-scale heterogeneity of habitat, differential settlement cues or patchy disturbance and succession may explain patchiness at smaller spatial scales. Only future manipulative experiments will provide a cause effect relationship between the high small-scale variability observed and the potential processes mentioned, but small-scale heterogeneity of habitat is the process more likely to be operating in this particular system, especially because our sampling did not consider a homogeneity of the substrate.
Therefore, most of the univariate analyses supported that spatial pattern was invariant at all the studied scales except for the total number of taxa and the abundance of foliose algae at the scale of location and area respectively. In contrast for multivariate analyses, this hypothesis was rejected except for the spatial scale of area.
Macroalgae are useful organisms to monitor the environmental quality and to detect impacts due to anthropogenic activities (Piazzi et al. 2001; Díez et al. 2009). In order to reduce time and resources for taxonomic determination of species, several surrogates have been suggested elsewhere (e.g. Phillips et al. 1997; Piazzi et al. 2001). A crucial attribute of surrogates has to be that they adequately represent pattern of spatial variability in assemblages at multiple spatial scales (Smale 2010). Our study confirmed that functional groups may be used as surrogate for monitoring studies, showing patterns remarkably consistent. Therefore, the spatial variability pattern of the macroalgal assemblages using species was consistent with that obtained using functional groups. However, analyses also showed that the consistence of the patterns decreased at wider scales. This reduction on similarity was probably related to the increase of rare species when samples were pooled at the site or location scale. While the number of functional groups is limited, and thus very stable, the number of species increased as quadrats were pooled, increasing the dissimilarity among sites or locations. Thus, despite some information was lost using functional groups, they have the ability to represent the spatial variability of macroalgal assemblages, and they could be successfully employed for monitoring programs. This result is in concordance with other studies where both approaches were used (Phillips et al. 1997; Piazzi et al. 2002; Konar and Iken 2009; Rubal et al. 2011).
Identifying relevant scales of variability is extremely important and necessary, especially at small scale, for implementing suitable monitoring programs and environmental impact studies (Underwood 1993; Chapman et al. 1995). The natural small-scale variation has been considered as a confounding factor to detect anthropogenic disturbance (Warwick 1988a, b). Therefore, if natural small-scale variation is not properly identified, changes due to impacts can be confounded with differences due to natural variability or, if the spatial scale sampled is greater than the natural variability scale, then impacts that do not exist could erroneously be detected (Coleman 2002). The use of functional groups as surrogate to investigate macroalgal assemblages seems to reduce the natural small-scale variation, and thus, it has been proposed as a solution to this problem (Konar and Iken 2009). However, in our study, the use of functional groups as a surrogate did not reduce small-scale variation compared to the species-level variation.
Therefore, functional groups can be used in future monitoring programs, in the studied area, without a significant loss of information resulting in a considerable reduction of cost and time. However, the use of functional groups does not reduce the high small-scale variability of macroalgal assemblages that can act as a confounding factor to detect anthropogenic disturbance. Moreover, the use of functional groups becomes less efficient at wide scales due to the increase of rare species. This could be a serious limitation in areas with high diversity of rare species, where the method should be tested before its application.