SEARCH

SEARCH BY CITATION

Keywords:

  • biodiversity;
  • ecosystem functioning;
  • macroalgae;
  • NIS ;
  • Sargassum muticum

Abstract

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Supporting Information

Ongoing changes in natural diversity due to anthropogenic activities can alter ecosystem functioning. Particular attention has been given to research on biodiversity loss and how those changes can affect the functioning of ecosystems, and, by extension, human welfare. Few studies, however, have addressed how increased diversity due to establishment of nonindigenous species (NIS) may affect ecosystem function in the recipient communities. Marine algae have a highly important role in sustaining nearshore marine ecosystems and are considered a significant component of marine bioinvasions. Here, we examined the patterns of respiration and light-use efficiency across macroalgal assemblages with different levels of species richness and evenness. Additionally, we compared our results between native and invaded macroalgal assemblages, using the invasive brown macroalga Sargassum muticum (Yendo) Fensholt as a model species. Results showed that the presence of the invader increased the rates of respiration and production, most likely as a result of the high biomass of the invader. This effect disappeared when S. muticum lost most of its biomass after senescence. Moreover, predictability–diversity relationships of macroalgal assemblages varied between native and invaded assemblages. Hence, the introduction of high-impact invasive species may trigger major changes in ecosystem functioning. The impact of S. muticum may be related to its greater biomass in the invaded assemblages, although species interactions and seasonality influenced the magnitude of the impact.

Abbreviations
NIS

nonindigenous species

PVC

polyvinyl chloride

Natural diversity is being modified worldwide by changes such as species loss and biological invasions of NIS (Vitousek et al. 1997, Sala et al. 2000). Understanding the consequences of such changes on ecosystem functioning has become a key topic of ecological research (e.g., Worm et al. 2006, Byrnes et al. 2007, Airoldi and Bulleri 2011). The argument that biodiversity loss could lead to a reduction in global ecosystem functioning (i.e., interactions between biotic assemblages or with their abiotic environment) emerged as an issue in the early 1990s (e.g., Ehrlich and Wilson 1991, Naeem et al. 1994).

Conversely, in some systems local species richness has increased significantly due to recent establishment of NIS, although the long-term consequences of these introductions are still debated (Sax and Gaines 2003). The spread of NIS has been considered one of the strongest anthropogenic impacts on natural ecosystems by changing abiotic factors, community structure, and ecosystem properties (Mack et al. 2000, Byers 2002, Ruesink et al. 2006). Life history features of invaders may be key factors in determining the fate and the impact of invasions. For instance, invasion by canopy-forming macroalgae (e.g., Sargassum muticum, Undaria pinnatifida) may influence the structure of understory assemblages by modifying levels of light, sedimentation (Airoldi 2003) or water movement (Eckman et al. 1989). Introduced species often exhibit novel features compared to native species and may have disproportionately high impacts on native ecosystem functioning (Ruesink et al. 2006). However, positive effects linked to the presence of invasive algal hosts have also been recorded in structuring host-epiphyte association (e.g., Jones and Thornber 2010). Although the majority of the scientific studies on the biodiversity-ecosystem functioning paradigm have been done in terrestrial ecosystems (Hooper et al. 2005), recent studies have also started to investigate ecosystem consequences of biodiversity loss in marine systems (Cardinale et al. 2006, Bracken et al. 2008, Danovaro et al. 2008, Reynolds and Bruno 2012). A general theoretical framework of marine biodiversity and ecosystem functioning is well described by Boero and Bonsdorff (2007).

Primary production is the most common ecosystem process measured in species richness manipulation experiments (Hooper et al. 2005), including marine experimental approaches (e.g., Bruno et al. 2005, Griffin et al. 2009, Tait and Schiel 2011). Primary production in the ocean is an important component of global biogeochemical cycles, and transfer of energy through most food webs can be directly linked to the fixation of carbon at the primary producer level (Field et al. 1998). Primary productivity in an ecosystem is closely related to species diversity, although effects of species identity have recently been suggested as an important component of benthic marine community production (Bruno et al. 2005, 2006). The productivity–diversity relationship, however, is very complex and may present positive, negative, hump-shaped, U-shaped or nonsignificant patterns (Waide et al. 1999). Additionally, biodiversity can also influence ecosystem predictability (McGrady-Steed et al. 1997). As a result, theory predicts a reduction in the temporal or spatial variance of ecosystem properties with increasing biodiversity (Yachi and Loreau 1999, France and Duffy 2006). Although macroalgae make up a small proportion of ocean primary production, they are the dominant primary producers of rocky shore ecosystems (Mann 1973), providing an essential ecological function for aquatic life. In addition, macroalgae are considered foundation species, providing habitat that may modify abiotic and biotic processes essential to overall ecosystem function (Bruno et al. 2003, Dijkstra et al. 2012). Hence, quantifying the primary productivity of these assemblages is essential to our understanding of energetic dynamics in coastal marine systems and the factors affecting it.

Preliminary studies on photosynthesis, growth or nutrient acquisition of macroalgae have been mainly examined in laboratory experiments (Littler and Arnold 1982) using single species (see Sand-Jensen et al. 2007 for a review). More recently, several studies suggested that for a better understanding of the primary production dynamics in macroalgae, an assemblage-based approach must be considered (Binzer and Middelboe 2005, Binzer et al. 2006, Richards et al. 2011). At the assemblage level, combining species with different sizes and morphologies allows researchers to account for effects such as canopy-shading, boundary layer effects, and resource partitioning (Middelboe and Binzer 2004). In particular, canopy structure may influence assemblage production by affecting the distribution of light to photosynthetic tissues in the assemblage and consequent efficiency of light utilization (Binzer and Sand-Jensen 2002a,b). Varying functional trait composition in assemblages is known to directly regulate ecosystem processes (Díaz and Cabido 2001, McGill et al. 2006) and has been recently incorporated in biodiversity-ecosystem functioning relationships (e.g., Griffin et al. 2009, Roscher et al. 2012) rather than species richness per se. Additionally, the individual performance of species (i.e., identity effects) has been proposed to affect the magnitude of an ecosystem process in macroalgal assemblages (Arenas et al. 2009, Griffin et al. 2009), indicating a high degree of interspecific variation in macroalgal productivity (Littler and Littler 1980).

A few laboratory studies have also incorporated an assemblage perspective using natural communities (Arenas et al. 2009, Tait and Schiel 2011). Examining different components of biodiversity (e.g., biomass, richness, evenness), Arenas et al. (2009) described a positive relationship for biomass and species richness with productivity on macroalgal assemblages on small boulders bearing intertidal macroalgal assemblages. Recently, experimental studies on marine communities have analyzed photosynthesis within intact, in situ macroalgal assemblages (e.g., Miller et al. 2009, Noël et al. 2010, Tait and Schiel 2010). For example, Tait and Schiel (2010) tested for primary production in intertidal macroalgal assemblages dominated by fucoid algae and described increased primary productivity of these macroalgal assemblages with a combination of greater biomass and greater numbers of macroalgal species.

Marine coastal ecosystems are strongly affected by invasions of NIS, which together with anthropogenic disturbances can create highly altered habitats. Nonetheless, to date, there have been virtually no studies which have focused on the functional consequences of increases in species richness due to the presence of invaders in marine habitats (but see Stachowicz and Byrnes 2006). Marine macroalgae are a significant component of introduced NIS (Schaffelke et al. 2006), highlighting the importance of studies addressing interactions at this level, particularly using strong invaders, sensu Ortega and Pearson (2005).

This study aimed to investigate assemblage-level impacts of macroalgal invasions and discriminate the mechanisms promoting its impact. In particular, we intended to understand the role of a strong invader, S. muticum (Yendo) Fensholt, and assemblage structure on the dynamics of respiration and light-use efficiency of assemblages. We used synthetic assemblages of marine macroalgae, resembling those from intertidal rock pools, with varying levels of functional diversity and invader biomass. Native species with a long history of co-evolution are expected to partition resources among them and promote ecosystem functioning via resource use complementary effects. In contrast, newly introduced species probably enhance ecosystem functioning via identity effects where the influence of the invader is much greater than expected based on its relative abundance in the assemblage (Ruesink et al. 2006). Also, we expect high-diversity assemblages to enhance the predictability of respiration and light-use efficiency response of assemblages.

Materials and Methods

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Supporting Information

Macroalgal assemblages

Macroalgal assemblages (64 cm2) were created from natural boulders collected at Praia Norte (Viana do Castelo, Portugal; 41°41′ 48″ N, 08°51′ 11″ W; see Arenas et al. 2009 for a full description of the collection site and boulder type). Using synthetic assemblages of macroalgae, we manipulated functional diversity by creating assemblages with different numbers of functional groups. Macroalgae were grouped into functional groups following Arenas et al. (2006), and three morpho-functional groups were selected: (a) encrusting coralline species, e.g., Lithophyllum incrustans; (b) turf-forming species from the genus Corallina and (c) subcanopy species, e.g., Chondrus crispus and Mastocarpus stellatus. These species are common in macroalgal assemblages from intertidal rock pools in northern Portugal (Arenas et al. 2009).

Synthetic assemblages consisted of 12 × 17 × 1 cm PVC plates with 16 pieces of rock surrounded by 1 cm PVC pieces for support and protection. Boulders were cut into 2 × 2 × 2 cm rock pieces and were attached to PVC plates using fast setting underwater cement and screws. Individual rock pieces represented one functional group characterized by a percent cover greater than 50%, or in the case of subcanopy species, the presence of one or more adult individuals. A total of 60 plates were built: 12 plates of only bare-rock, 36 plates with only one functional group (12 plates per group), and 12 plates with three functional groups. In the last case, the spatial distribution of the three functional groups within plates was random.

Synthetic macroalgal assemblages were then subjected to an artificial invasion by the brown canopy-forming macroalga S. muticum. This was accomplished by collecting fertile individuals of S. muticum with receptacles bearing exuded propagules from the field and transporting them to the laboratory where they were rinsed with freshwater to eliminate grazers. Fertile S. muticum was then placed floating over the assemblages in tanks of ~300 L of seawater. To assure different biomass of the invader in the final assemblage composition, propagule pressure was manipulated by suspending a different biomass of fertile individuals of S. muticum over the macroalgal assemblages (High density ≈ 25 kg; Low density ≈ 13 kg; Control – none). Control assemblages were used to assess natural assemblage composition in the field. A total of 20 macroalgal assemblages of combined functional diversity treatments (n = 4) were randomly assigned to each propagule pressure treatment (i.e., one tank per propagule pressure treatment). Experimental invasion was planned to be around the new moon (July 22, 2009) due to the semilunar periodicity of egg expulsion in S. muticum around new or full moons (Norton 1981).

To allow for germling settling, macroalgal assemblages were transported to the field 1 week after artificial invasion. Assemblages were randomly placed and screwed to the bottom of a large rock pool (11 × 2 m size, average depth of 35 cm) in the mid-intertidal shore (≈ 1.5 m above chart datum) of Viana do Castelo where they remained for 22 months.

Incubation procedures

This study was performed at the Laboratory of Coastal Biodiversity, at CIIMAR in Oporto. Incubation measurements were carried out in November 2010 and May 2011, to test the generality of the results for low and high biomass of the invader S. muticum, respectively. After incubations in November 2010, assemblage plates were carefully returned to the field, with no damage to the thalli being observed during transportation or redeployment of the plates. Respiration and productivity measurements were carried out under controlled conditions to reduce environmentally induced variability in the responses.

Assemblage plates were maintained in outdoor aerated seawater tanks for a maximum of 5 days under natural light and temperature conditions before the incubations were done. Nutrients were supplied every 2 d (1 mL of nutrient solution per liter of seawater; 42.50 g NaNO3 ·L−1, 10.75 g Na2 HOP4 ·L−1).

Incubations of macroalgal assemblages were carried out inside an experimental chamber, equipped with 26 18W fluorescent tubes (Osram® Light Color 840 Lumilux Cool White, Munich, Germany). Inside the experimental chamber, incubations were performed in sealed chambers and comprised measurements of the change in dissolved oxygen concentration during dark and light periods. The irradiance inside the experimental chamber was measured using a spherical scalar quantum sensor connected to a computer (Biospherical® QSL-2000, San Diego, CA, USA). Productivity–irradiance relationships were estimated at seven increasing irradiance levels: 0 (dark), 30, 60, 90, 180, 250, and 400 μmol photons · m−2 · s−1 irradiance (i.e., 30 min each).

The incubation chambers consisted of a 12.5, 15.5 or 47.5-L transparent Plexiglass chamber, depending on the biomass of the assemblage plate. Incubation chambers were partially submersed in a larger white Plexiglass chamber used as a cooling bath to assure constant temperature during incubations. Mean (±SE) temperature during incubations was 16.47 ± 0.01°C. Water movement inside the incubation chamber was maintained by small submersible aquarium pumps with diffusers to reduce turbulence. Dissolved oxygen concentration and temperature inside the incubation chambers were measured every 30 s using a luminescent dissolved oxygen (LDO), probe connected to a portable oxygen meter (Hach® HQ40, Düsseldorf, Germany). To reduce possible effects of circadian rhythms on algal productivity, incubations were always carried out during daylight hours (between 08:00 and 18:00 h).

Immediately after incubations in May 2011, macroalgae were scraped from plates, rinsed in freshwater, sorted by species and dried at 60°C for 48 h to estimate biomass (g dry weight, DW). In the case of the encrusting species, we selected 2 × 2 cm rock pieces colonized with encrusting coralline species. These were oven-dried for 48 h at 50°C and weighed for dry-weights. We then placed rock pieces in hydrochloric acid (0.5 M HCl) for 48 h to remove the calcium carbonate. Rock pieces were then rinsed with freshwater, oven-dried for 24 h and then re-weighed. The difference in the dry-weights, i.e., before and after the HCl treatment, was used to obtain the biomass of the algae per 4 cm2 and the average of 40 squares allowed us to estimate the biomass in our plates at the end of the experimental period.

Ecosystem functioning surrogates

Respiration and productivity were estimated through oxygen fluxes by regressing oxygen amount produced or consumed (μmol) through time (s−1) during dark and light periods of increasing intensities. Estimations were normalized by assemblage surface (64 cm2) or biomass (May 2011) and volume of incubation chamber (12, 15 or 47 L, measured with plates inside the chamber). Additionally, estimates of respiration and productivity were also normalized by control blanks (incubations performed simultaneously with only filtered seawater) to control for rates of respiration and production of bacteria and phytoplankton.

The variables Respiration, Photosynthetic efficiency at low light irradiance (alpha, α) and Light compensation point were measured as surrogates of ecosystem functioning. Respiration of assemblages (μmol O2 · s−1) corresponded to the oxygen consumption rate during the dark period and we assessed net primary productivity (μmol O2 · s−1) as the productivity recorded at different irradiance intensities in order to calculate alpha. Both variables were calculated by plotting oxygen concentration over incubation time and fitting a linear regression line to calculate rates of oxygen change. Alpha (μmol O2 · μmol photons · m−2), was estimated as the slope of P-I relationship at light-limited irradiances (up to 87 μmol photons · m−2 · s−1), through linear regressions. Regressions were also used to estimate light compensation point of assemblages, the irradiance level at which respiration rate is equal to photosynthetic rate and net oxygen exchange is zero.

Data analysis

General linear models were performed to investigate the influence of S. muticum (presence or absence) on each of the biological responses examined: respiration, alpha and light compensation point. After checking for normality using Normal Quantile plots, all response variables were log-transformed and linearity and normality of residual distributions were obtained. Homoscedasticity was assessed by graphical examination of the residuals.

We used two biodiversity components (i.e., species richness and species evenness) as predictive variables to test if the response of ecosystem function measures varied with the component of biodiversity used (see Hooper et al. 2005). Species richness (S) describes the number of species in the assemblage, while evenness took into account the variation in the abundance of individuals per species in the assemblage. Species evenness was calculated using the Pielou's evenness index (J'). We fitted two linear models to each of the biological responses examined. One had presence/absence (P/A) of S. muticum and species richness as predictors, and the second model had P/A of S. muticum and species evenness as predictors. Additionally, we re-analyzed respiration and alpha data after normalizing values per assemblage biomass, in order to consider the efficiency of the assemblages. All the models analyzed main and interactive effects of the predictive variables. When interaction terms were nonsignificant, models were re-run without the interaction. In order to obtain the minimum adequate model, nonsignificant main effects were also removed from the model and thus only significant effects are shown in the correspondent table. However, for a better understanding, we distinguished between native and invaded assemblages in all the figures, even when the factor native versus invaded assemblages was nonsignificant.

The coefficient of variation (CV) in an assemblage's light-use efficiency, alpha, was quantified for native and invaded assemblages in May (i.e., the period of high biomass of the invader). CV was calculated as the ratio of the standard deviation to the mean (CV = σ/μ) and was used as a measure of spatial variation.

General linear models were carried out using the linear model function (lm) in the R-program 2.15.0 (R Development Core Team 2012).

Results

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Supporting Information

In November 2010, we were only able to locate 37 macroalgal assemblage plates. These were collected from the intertidal pool to perform laboratory incubations and re-deployed in the shore. In May 2011, we were able to locate 55 macroalgal assemblages. Algal assemblages varied in species richness, total biomass, and biomass of the invader.

November 2010

The presence of S. muticum did not affect the relationship between species richness and any biological response measured (F3,33 = 1.27, P = 0.30, R2 = 0.10). Moreover, no significant relationship was found between any biological response measured and species richness (see Table S1 in the Supporting Information). However, when species evenness was considered as the predictor variable, both respiration and alpha response functions showed a significant negative relationship (F1,35 = 5.61, P = 0.02, R2 = 0.14, and F1,35 = 14.00, P = 0.001, R2 = 0.28, respectively; Fig. 1). In addition, the presence of S. muticum did not affect any of the macroalgal biological responses measured (see Table S1 in the Supporting Information).

image

Figure 1. November 2010. Relationship between the functional responses measures (per 64 cm2) and species evenness of assemblage. (a) assemblage respiration and (b) light-use efficiency, alpha. The coefficient of determination (R2) and the significance level of the minimum adequate model are presented in each plot (n = 37).

Download figure to PowerPoint

May 2011

In May 2011, the biomass of the invader ranged between 0 and 163.38 g DW (3.58 ± 2.91 g DW) per 64 cm2. Moreover, biomass of Corallina spp., S. muticum and C. crispus accounted for ≈90% of the overall biomass with 38.7, 35.1 and 18.0%, respectively. Corallina spp. and Lithophyllum incrustans were present in all algal assemblages.

Contrasting with results from November, the presence of S. muticum affected all biological responses of macroalgal assemblages measured. Although no significant relationship was observed between both response functions measured and species richness, invaded macroalgal assemblages were characterized by higher values (F1,53 = 6.66, P = 0.01, R2 = 0.11, for respiration and alpha, respectively; Fig. 2, a and b). In addition, interactive effects of S. muticum were observed on respiration when species evenness was considered (F3,51 = 5.88, P = 0.002, R2 = 0.26; Fig. 2c). Specifically, native assemblages were characterized by a negative relationship between assemblage respiration and evenness (F1,40 = 4.39, P = 0.04, R2 = 0.10), while in invaded assemblages the slope of the relationship did not differ from 0 (Fig. 2c; see also Table S2 in the Supporting Information).

image

Figure 2. May 2011. Relationship between the functional responses measures (per 64 cm2) and assemblage structure in native (n = 42) and invaded (n = 13) macroalgal assemblages. (a) Assemblage respiration; (b) light-use efficiency, alpha, and (c) assemblage respiration and evenness (R2 = 0.099, P = 0.0425 and R2 = 0.194, P = 0.132, for native and invaded assemblages, respectively). (*)P < 0.05, (***)P < 0.0001.

Download figure to PowerPoint

Patterns were, however, quite different when the efficiency of the assemblages was considered. When respiration and light-use efficiency response function were normalized by the biomass of the assemblage, the effect of invasion by S. muticum was lost (see Table S3 in the Supporting Information). However, a significant positive effect of biodiversity (both species richness and evenness) was still evident in light-use efficiency (F1,53 = 5.46, P = 0.02, R2 = 0.09, and F1,53 = 18.17, P < 0.0001, R2 = 0.25, for species richness and evenness, respectively; Fig. 3, a and b).

image

Figure 3. May 2011. Relationship between light-use efficiency, alpha and (a) species richness, and (b) evenness, after normalizing by the biomass of the assemblage. The coefficient of determination (R2) and the significance level of the minimum adequate model are presented in each plot (n = 37).

Download figure to PowerPoint

The triangular scatter of observations (Fig. 3a), suggested that variation among replicates of identical species richness decreased as species richness increased. Predictability–diversity relationships for light-use efficiency of macroalgal assemblages varied between native and invaded assemblages (Fig. 4). We observed that in native macroalgal assemblages, the CV significantly decreased with species richness (F1,4 = 12.24, P = 0.025, R2 = 0.75). Thus, the variation among replicates of identical species richness declined as species richness increased. Contrasting results were obtained for invaded macroalgal assemblages where no relationship was found (F1,2 = 7.97, P = 0.10, R2 = 0.79).

image

Figure 4. Predictability–diversity relationship. Variability in the coefficient of variation with species richness, regarding light-use efficiency, alpha, for native (n = 42) and invaded (n = 13) macroalgal assemblages.

Download figure to PowerPoint

The light compensation point did not differ between autumn and spring (47.07 and 48.81 μmol photons · m−2 · s−1, respectively). Moreover, the light compensation point of macroalgal assemblages was not affected by the presence of S. muticum (November: F3,33 = 0.11, P = 0.95, R2 = 0.01, and F3,33 = 1.22, P = 0.32, R2 = 0.10, using species richness and evenness, respectively; May: F3,51 = 2.11, P = 0.11, R2 = 0.11, and F3,51 = 1.74, P = 0.17, R2 = 0.09, using species richness and evenness, respectively).

Discussion

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Supporting Information

This study investigated how increased diversity due to the establishment of NIS affected ecosystem functioning responses in the recipient communities. The most relevant finding was that the presence of S. muticum increased the rates of respiration and light-use efficiency of macroalgal assemblages. However, this effect was only a consequence of additional biomass and thus it disappeared when S. muticum lost most of its biomass after senescence. In addition, the increased predictability between species richness and ecosystem function found in native macroalgal assemblages disappeared in invaded assemblages.

The introduction of species with traits not found in the recipient assemblage can produce large-scale alterations of ecosystem processes and structure (Ruesink et al. 2006). In this study, S. muticum when present at elevated biomass modified respiration and light-use efficiency of assemblages. However, as a habitat modifier, S. muticum individuals may also modify a variety of other ecosystem processes (Wallentinus and Nyberg 2007). S. muticum has a high growth capacity and is known to influence assemblages by modifying levels of light (Britton-Simmons 2004, Strong et al. 2006), water movement, and temperature (Strong et al. 2006) within canopy areas. Considered an invasive species in its introduced range all around the world (Critchley et al. 1983), S. muticum varies greatly in its ability to impact native systems due to its seasonal reproduction, followed by a rapid shedding of the reproductive tissues (Arenas and Fernández 1998). In the autumn, after a substantial loss of biomass, our results suggest that S. muticum acts as a weak invader and becomes a minor component of native assemblages. In the spring, due to the elevated biomass, this species becomes dominant at the expense of native species and processes and acts as a strong invader (sensu Ortega and Pearson 2005). The different morphological forms of S. muticum individuals between seasons may have significant differences in the percentage of photosynthetic tissue, net photosynthesis, and specific growth rate, as previously demonstrated for the red alga Gracilaria tikvahiae McLachlan 1979 (Hanisak et al. 1988). Thus, these varying results between seasons are not totally unexpected, although the type of relationship may be. In a previous study using intertidal macroalgal assemblages, also in November/December, correlations with evenness were not significant for any functional variable addressed (Arenas et al. 2009), contrasting with the negative relationship found in this study. The impact of S. muticum can be related to its biomass dominance in the invaded assemblages, in agreement with the sampling effect hypothesis, i.e., the increasing probability of selecting a species with a specific property with increasing species richness (Huston 1997). It has been suggested that native species with a long history of co-evolution may influence ecosystem processes through resource use efficiency, whereas NIS effects on the recipient assemblage occurs through sampling effects (Ruesink et al. 2006).

Several studies have revealed that the effect of species diversity on ecosystem functioning depends on the system studied and the function measured (Schwartz et al. 2000, Schmid 2002, Duffy 2003). Moreover, the effects of species richness on biomass production change through time and are influenced by both selection and multispecies complementarity effects (Cardinale et al. 2007). Specifically, the role of phenology has not been thoroughly assessed in primary productivity studies, although variables such as standing biomass of the species, its functioning (e.g., the outcome of carbon assimilation, nutrient uptake), and phenology have been suggested to influence net primary productivity (Lavorel and Garnier 2002). The majority of biodiversity research manipulates species richness with few studies manipulating or measuring species evenness, i.e., the relative contribution of each species to the total biomass or number of individuals (but see Wilsey and Potvin 2000, Altieri et al. 2009, Arenas et al. 2009). Contrasting with previous results in both marine and terrestrial systems (Wilsey and Potvin 2000, Altieri et al. 2009), this study showed no positive effects of evenness on ecosystem functioning in native assemblages. Most importantly, evidence suggests that different mechanisms seem to be operating in November and May.

The productivity of macroalgal assemblages was measured as O2 production, contrasting with general production studies which usually focus on carbon or biomass accumulation (e.g., Bruno et al. 2005, Cardinale et al. 2006, Reynolds and Bruno 2012). Results from the regression models indicated an overall negative effect of evenness on the performance of macroalgal assemblages in November. Negative relationships have been observed as a result of the dominance of species with greater biomass per unit area (Mulder et al. 2004), reducing evenness and increasing productivity (Nijs and Roy 2000). In our assemblages, we observed that the species used in monocultures, such as Corallina spp. and Chrondrus crispus, remained dominant throughout the experimental period (“sampling effect” of Huston 1997), which could explain the negative relationship described in our results. No significant differences were observed between native and invaded assemblages, as the biomass of the invader was scarce. In May, however, assemblages invaded by S. muticum were characterized by greater rates of respiration and light-use efficiency. The patterns observed on respiration response function, a light autonomous process, were, however, not very clear. The amount of variance explained by species evenness in native assemblages was very low at 9%. Thus, the proportion of the response variable variability left unexplained was very high. On the other hand, no relationship has been registered between respiration and species evenness in invaded assemblages. Species interactions drive biodiversity effects (Hillebrand et al. 2008) and thus, identity effects may explain our results. According to Hillebrand et al. (2008), an increase in the ecosystem process is expected if the dominant species performs better than the mean of the community, whereas the opposite should be observed if the dominant performs below average. In particular, dominance may intensify intraspecific interactions for the dominant species, negatively influencing S. muticum performance at low evenness.

It has been suggested that the magnitude of energy transferred to seaweed from a moving water mass depends on its size and shape (Norton 1991). Accordingly, after taking into consideration the biomass of the invader, the overall results were different, revealing biomass dependent effects (Emmerson and Raffaelli 2000, Tait and Schiel 2011). After normalizing by biomass, the efficiency of macroalgal assemblages was associated with effects of species richness and evenness on light-use efficiency, suggesting that at higher diversity, species may be more effective at using resources. These results are consistent with complementarity as a mechanism linking diversity and function. Recent findings comparing productivity of subtidal turf and foliose algal assemblages describe foliose assemblages to be more productive due to their greater biomass per unit area and not because of greater production per unit biomass (Miller et al. 2009). The same trend can be described for S. muticum. Due to its longer canopy height, S. muticum is more productive on a per-area basis than on a biomass-specific basis.

Finally, in agreement with the similarity hypothesis (Yachi and Loreau 1999), the increase in species richness in native macroalgal assemblages increased the predictability of primary production across space. Contrasting results were, however, obtained for invaded assemblages, where the presence of S. muticum removed the positive relationship between species richness and ecosystem function predictability. These results suggest that invaded assemblages' dynamics are less predictable than native dynamics. Further interactions between habitat-modifying species can decrease predictability of community-level effects of an invasion, particularly if invasive species show extremely variable cycles over time (Ward and Ricciardi 2010). The consequences of invasion for the invaded communities, especially with regard to their functioning, have been rarely considered (Pfisterer et al. 2004). However, the identity of the species being added or removed and its similarity to other species are often of critical importance in determining overall effects (Mooney et al. 1995). In native assemblages, the dominant species were perennial algae such as C. crispus or Corallina spp., while the dominance of the invader varied drastically between seasons. Previous studies have demonstrated a high variability in S. muticum productivity and reproductive development between habitats (Baer and Stengel 2010) and grazing pressure (Plouguerné et al. 2006). Thus, the reduced predictability of highly diverse communities when invaded suggested by our results might be related to the very large local variability of the invader.

In conclusion, our results highlight the fact that ecosystem functioning is a function of the biotic ecosystem components (Schläpfer and Schmid 1999), which vary in different ecological contexts such as seasons. Moreover, results showed that different components of diversity, beyond species richness, may also shape the relationship between diversity and ecosystem function. In agreement with previous studies, our results also suggest that richness and evenness may not be correlated positively (Buzas and Hayek 1996, Stirling and Wilsey 2001). Specifically, the impact of S. muticum was related to its greater biomass in the invaded assemblages, although species interactions and season influenced the magnitude of the impact.

The authors would like to thank Eva Cacabelos and Bernardete Lopes for their help in field work. We thank Stuart Jenkins for helpful English revision and two anonymous referees for providing valuable comments. This research was funded by AXA-Marine Alien and Climate Change project. FVP was supported by a PhD grant from the Portuguese Foundation for Science and Technology – FCT (SFRH/BD/33393/2008). FA was partially supported by the European Regional Development Fund (ERDF) through the COMPETE - Operational Competitiveness Program and National Funds through FCT under the project “PEst-C/MAR/LA0015/2011” and the FCT funded project CLEF (PTDC-AAC-AMB-102866-2008).

  • Airoldi, L. 2003. The effects of sedimentation on rocky coast assemblages. Oceanogr. Mar. Biol. Annu. Rev. 41:161236.
  • Airoldi, L. & Bulleri, F. 2011. Anthropogenic disturbance can determine the magnitude of opportunistic species responses on marine urban infrastructures. PLoS ONE 6:e22985.
  • Altieri, A. H., Trussell, G. C., Ewanchuk, P. J., Bernatchez, G. & Bracken, M. E. S. 2009. Consumers control diversity and functioning of a natural marine ecosystem. PLoS ONE 4:e5291.
  • Arenas, F. & Fernández, C. 1998. Ecology of Sargassam muticum (Phaeophyta) on the North Coast of Spain III. Reproductive ecology. Bot. Mar. 41:20916.
  • Arenas, F., Rey, F. & Pinto, I. S. 2009. Diversity effects beyond species richness: evidence from intertidal macroalgal assemblages. Mar. Ecol. Prog. Ser. 381:99108.
  • Arenas, F., Sánchez, I., Hawkins, S. J. & Jenkins, S. R. 2006. The invasibility of marine algal assemblages: role of functional diversity and identity. Ecology 87:285161.
  • Baer, J. & Stengel, D. B. 2010. Variability in growth, development and reproduction of the non-native seaweed Sargassum muticum (Phaeophyceae) on the Irish west coast. Estuar. Coast. Shelf Sci. 90:18594.
  • Binzer, T. & Middelboe, A. L. 2005. From thallus to communities: scale effects and photosynthetic performance in macroalgae communities. Mar. Ecol. Prog. Ser. 287:6575.
  • Binzer, T. & Sand-Jensen, K. 2002a. Importance of structure and density of macroalgae communities (Fucus serratus) for photosynthetic production and light utilisation. Mar. Ecol. Prog. Ser. 235:5362.
  • Binzer, T. & Sand-Jensen, K. 2002b. Production in aquatic macrophyte communities: a theoretical and empirical study of the influence of spatial light distribution. Limnol. Oceanogr. 47:174250.
  • Binzer, T., Sand-Jensen, K. & Middelboe, A. L. 2006. Community photosynthesis of aquatic macrophytes. Limnol. Oceanogr. 51:272233.
  • Boero, F. & Bonsdorff, E. 2007. A conceptual framework for marine biodiversity and ecosystem functioning. Mar. Ecol. 28:13445.
  • Bracken, M. E., Friberg, S. E., Gonzalez-Dorantes, C. A. & Williams, S. L. 2008. Functional consequences of realistic biodiversity changes in a marine ecosystem. Proc. Natl Acad. Sci. USA 105:9248.
  • Britton-Simmons, K. H. 2004. Direct and indirect effects of the introduced alga Sargassum muticum on benthic, subtidal communities of Washington State, USA. Mar. Ecol. Prog. Ser. 277:6178.
  • Bruno, J. F., Boyer, K. E., Duffy, J. E., Lee, S. C. & Kertesz, J. S. 2005. Effects of macroalgal species identity and richness on primary production in benthic marine communities. Ecol. Lett. 8:116574.
  • Bruno, J. F., Lee, S. C., Kertesz, J. S., Carpenter, R. C., Long, Z. T. & Duffy, J. E. 2006. Partitioning the effects of algal species identity and richness on benthic marine primary production. Oikos 115:1708.
  • Bruno, J. F., Stachowicz, J. J. & Bertness, M. D. 2003. Inclusion of facilitation into ecological theory. Trends Ecol. Evol. 18:11925.
  • Buzas, M. A. & Hayek, L. A. C. 1996. Biodiversity resolution: an integrated approach. Biodiversity Lett. 3:403.
  • Byers, J. E. 2002. Impact of non-indigenous species on natives enhanced by anthropogenic alteration of selection regimes. Oikos 97:44958.
  • Byrnes, J. E., Reynolds, P. L. & Stachowicz, J. J. 2007. Invasions and extinctions reshape coastal marine food webs. PLoS ONE 2:e295.
  • Cardinale, B. J., Srivastava, D. S., Duffy, J. E., Wright, J. P., Downing, A. L., Sankaran, M. & Jouseau, C. 2006. Effects of biodiversity on the functioning of trophic groups and ecosystems. Nature 443:98992.
  • Cardinale, B. J., Wright, J. P., Cadotte, M. W., Carroll, I. T., Hector, A., Srivastava, D. S., Loreau, M. & Weis, J. J. 2007. Impacts of plant diversity on biomass production increase through time because of species complementarity. Proc. Natl Acad. Sci. USA 104:181238.
  • Critchley, A. T., Farnham, W. F. & Morrell, S. L. 1983. A chronology of new European sites of attachment for the invasive brown alga, Sargassum muticum, 1973–1981. J. Mar. Biol. Ass. U.K. 63:799811.
  • Danovaro, R., Gambi, C., Dell'Anno, A., Corinaldesi, C., Fraschetti, S., Vanreusel, A., Vincx, M. & Gooday, A. J. 2008. Exponential decline of deep-sea ecosystem functioning linked to benthic biodiversity loss. Curr. Biol. 18:18.
  • Díaz, S. & Cabido, M. 2001. Vive la différence: plant functional diversity matters to ecosystem processes. Trends Ecol. Evol. 16:64655.
  • Dijkstra, J. A., Boudreau, J. & Dionne, M. 2012. Species-specific mediation of temperature and community interactions by multiple foundation species. Oikos 121:64654.
  • Duffy, J. E. 2003. Biodiversity loss, trophic skew and ecosystem functioning. Ecol. Lett. 6:6807.
  • Eckman, J. E., Duggins, D. O. & Sewell, A. T. 1989. Ecology of under story kelp environments. I. Effects of kelps on flow and particle transport near the bottom. J. Exp. Mar. Biol. Ecol. 129:17387.
  • Ehrlich, P. R. & Wilson, E. O. 1991. Biodiversity studies: science and policy. Science 253:75862.
  • Emmerson, M. C. & Raffaelli, D. G. 2000. Detecting the effects of diversity on measures of ecosystem function: experimental design, null models and empirical observations. Oikos 91:195203.
    Direct Link:
  • Field, C. B., Behrenfeld, M. J., Randerson, J. T. & Falkowski, P. 1998. Primary production of the biosphere: integrating terrestrial and oceanic components. Science 281:23740.
  • France, K. E. & Duffy, J. 2006. Diversity and dispersal interactively affect predictability of ecosystem function. Nature 441:113943.
  • Griffin, J. N., Méndez, V., Johnson, A. F., Jenkins, S. R. & Foggo, A. 2009. Functional diversity predicts overyielding effect of species combination on primary productivity. Oikos 118:3744.
  • Hanisak, M. D., Littler, M. M. & Littler, D. S. 1988. Significance of macroalgal polymorphism: intraspecific tests of the functional-form model. Mar. Biol. 99:15765.
  • Hillebrand, H., Bennett, D. M. & Cadotte, M. W. 2008. Consequences of dominance: a review of evenness effects on local and regional ecosystem processes. Ecology 89:151020.
  • Hooper, D. U., Chapin, F. S., Ewel, J. J., Inchausti, P., Lavorel, S., Lawton, J. H., Lodge, D. M. et al. 2005. Effects of biodiversity on ecosystem functioning: a consensus of current knowledge. Ecol. Monogr. 75:335.
  • Huston, M. A. 1997. Hidden treatments in ecological experiments: re-evaluating the ecosystem function of biodiversity. Oecologia 110:44960.
  • Jones, E. & Thornber, C. S. 2010. Effects of habitat-modifying invasive macroalgae on epiphytic algal communities. Mar. Ecol. Prog. Ser. 400:87100.
  • Lavorel, S. & Garnier, E. 2002. Predicting changes in community composition and ecosystem functioning from plant traits: revisiting the Holy Grail. Funct. Ecol. 16:54556.
  • Littler, M. M. & Arnold, K. E. 1982. Primary productivity of marine macroalgal functional-form groups from southwestern North America. J. Phycol. 18:30711.
  • Littler, M. M. & Littler, D. S. 1980. The evolution of thallus form and survival strategies in benthic marine macroalgae: field and laboratory tests of a functional form model. Am. Nat. 116:2544.
  • Mack, R. N., Simberloff, D., Lonsdale, W. M., Evans, H., Clout, M. & Bazzaz, F. 2000. Biotic invasions: causes, epidemiology, global consequences and control. Ecol. Appl. 10:689710.
  • Mann, K. H. 1973. Seaweeds: their productivity and strategy for growth. Science 182:97581.
  • McGill, B. J., Enquist, B. J., Weiher, E. & Westoby, M. 2006. Rebuilding community ecology from functional traits. Trends Ecol. Evol. 21:17885.
  • McGrady-Steed, J., Harris, P. M. & Morin, P. J. 1997. Biodiversity regulates ecosystem predictability. Nature 390:1625.
  • Middelboe, A. L. & Binzer, T. 2004. Importance of canopy structure on photosynthesis in single- and multi-species assemblages of marine macroalgae. Oikos 107:42232.
  • Miller, R. J., Reed, D. C. & Brzezinski, M. A. 2009. Community structure and productivity of subtidal turf and foliose algal assemblages. Mar. Ecol. Prog. Ser. 388:111.
  • Mooney, H. A., Lubchenco, J., Dirzo, J. & Sala, O. E. 1995. Biodiversity and ecosystem functioning: ecosystem analysis, Section 6. In Heywood, V. [Ed.] Global Biodiversity Assessment. UNEP, Cambridge University Press, Cambridge, pp. 347452.
  • Mulder, C. P. H., Bazeley-White, E., Dimitrakopoulos, P. G., Hector, A., Scherer-Lorenzen, M. & Schmid, B. 2004. Species evenness and productivity in experimental plant communities. Oikos 107:5063.
  • Naeem, S., Thompson, L. J., Lawler, S. P., Lawton, J. H. & Woodfin, R. M. 1994. Declining biodiversity can alter the performance of ecosystems. Nature 368:7347.
  • Nijs, I. & Roy, J. 2000. How important are species richness, species evenness and interspecific differences to productivity? A mathematical model. Oikos 88:5766.
  • Noël, L. M. L. J., Griffin, J. N., Thompson, R. C., Hawkins, S. J., Burrows, M. T., Crowe, T. P. & Jenkins, S. R. 2010. Assessment of a field incubation method estimating primary productivity in rockpool communities. Estuar. Coast. Shelf Sci. 88:1539.
  • Norton, T. A. 1981. Gamete expulsion and release in Sargassum muticum. Bot. Mar. 24:46570.
  • Norton, T. A. 1991. Conflicting constraints on the form of intertidal algae. Br. Phycol. J. 26:20318.
  • Ortega, Y. K. & Pearson, D. E. 2005. Weak vs. strong invaders of natural plant communities: assessing invasibility and impact. Ecol. Appl. 15:65161.
  • Pfisterer, A. B., Joshi, J., Schmid, B. & Fischer, M. 2004. Rapid decay of diversity-productivity relationships after invasion of experimental plant communities. Basic Appl. Ecol. 5:514.
  • Plouguerné, E., Lann, K. L., Connan, S., Jechoux, G., Deslandes, E. & Stiger-Pouvreau, V. 2006. Spatial and seasonal variation in density, reproductive status, length and phenolic content of the invasive brown macroalga Sargassum muticum (Yendo) Fensholt along the coast of Western Brittany (France). Aquat. Bot. 85:33744.
  • R Development Core Team 2012. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria.
  • Reynolds, P. L. & Bruno, J. F. 2012. Effects of trophic skewing of species richness on ecosystem functioning in a diverse marine community. PLoS ONE 7:e36196.
  • Richards, D. K., Hurd, C. L., Pritchard, D. W., Wing, S. R. & Hepburn, C. D. 2011. Photosynthetic response of monospecific macroalgal stands to density. Aquat. Biol. 13:419.
  • Roscher, C., Schumacher, J., Gubsch, M., Lipowsky, A., Weigelt, A., Buchmann, N., Schmid, B. & Schulze, E. D. 2012. Using plant functional traits to explain diversity–productivity relationships. PLoS ONE 7:e36760.
  • Ruesink, J. L., Feist, B. E., Harvey, C. J., Hong, J. S., Trimble, A. C. & Wisehart, L. M. 2006. Changes in productivity associated with four introduced species: ecosystem transformation of a ‘pristine’ estuary. Mar. Ecol. Prog. Ser. 311:20315.
  • Sala, O. E., Chapin, F. S. III, Armesto, J. J., Berlow, E., Bloomfield, J., Dirzo, R., Huber-Sanwald, E. et al. 2000. Global biodiversity scenarios for the year 2100. Science 287:17704.
  • Sand-Jensen, K., Binzer, T. & Middelboe, A. L. 2007. Scaling of photosynthetic production of aquatic macrophytes - a review. Oikos 116:28094.
  • Sax, D. F. & Gaines, S. D. 2003. Species diversity: from global decreases to local increases. Trends Ecol. Evol. 18:5616.
  • Schaffelke, B., Smith, J. E. & Hewitt, C. L. 2006. Introduced macroalgae – a growing concern. J. Appl. Phycol. 18:52941.
  • Schläpfer, F. & Schmid, B. 1999. Ecosystem effects of biodiversity: a classification of hypotheses and exploration of empirical results. Ecol. Appl. 9:893912.
  • Schmid, B. 2002. The species richness–productivity controversy. Trends Ecol. Evol. 17:1134.
  • Schwartz, M. W., Brigham, C. A., Hoeksema, J. D., Lyons, K. G., Mills, M. H. & van Mantgem, P. J. 2000. Linking biodiversity to ecosystem function: implications for conservation ecology. Oecologia 122:297305.
  • Stachowicz, J. J. & Byrnes, J. E. 2006. Species diversity, invasion success, and ecosystem functioning: disentangling the influence of resource competition, facilitation, and extrinsic factors. Mar. Ecol. Prog. Ser. 311:25162.
  • Stirling, G. & Wilsey, B. J. 2001. Empirical relationships between species richness, evenness and proportional diversity. Am. Nat. 158:28699.
  • Strong, J. A., Dring, M. J. & Maggs, C. A. 2006. Colonisation and modification of soft substratum habitats by the invasive macroalga Sargassum muticum. Mar. Ecol. Prog. Ser. 321:8797.
  • Tait, L. W. & Schiel, D. R. 2010. Primary productivity of intertidal macroalgal assemblages: comparison of laboratory and in situ photorespirometry. Mar. Ecol. Prog. Ser. 416:11525.
  • Tait, L. W. & Schiel, D. R. 2011. Dynamics of productivity in naturally structured macroalgal assemblages: importance of canopy structure on light-use efficiency. Mar. Ecol. Prog. Ser. 421:97107.
  • Vitousek, P. M., Mooney, H. A., Lubchenco, J. & Melillo, J. M. 1997. Human domination of Earth's ecosystems. Science 277:4949.
  • Waide, R. B., Willig, M. R., Steiner, C. F., Mittelbach, G. G., Gough, L., Dodson, S. I., Juday, G. P. & Parmenter, R. 1999. The relationship between productivity and species richness. Annu. Rev. Ecol. Syst. 30:257300.
  • Wallentinus, I. & Nyberg, C. D. 2007. Introduced marine organisms as habitat modifiers. Mar. Pollut. Bull. 55:32332.
  • Ward, J. M. & Ricciardi, A. 2010. Community-level effects of co-occurring native and exotic ecosystem engineers. Freshwater Biol. 55:180317.
  • Wilsey, B. J. & Potvin, C. 2000. Biodiversity and ecosystem functioning: importance of species evenness in an old field. Ecology 81:88792.
  • Worm, B., Barbier, E. B., Beaumont, N., Duffy, J. E., Folke, C., Halpern, B. S., Jackson, J. B. C. et al. 2006. Impacts of biodiversity loss on ocean ecosystem services. Science 314:78790.
  • Yachi, S. & Loreau, M. 1999. Biodiversity and ecosystem productivity in a fluctuating environment: the insurance hypothesis. Proc. Natl. Acad. Sci. USA 96:14638.

Supporting Information

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Supporting Information
FilenameFormatSizeDescription
jpy12136-sup-0001-TableS1.docxWord document24KTable S1. November 2010. General linear model analysis testing the main and interactive effects of biodiversity (either species richness (S) or evenness (J')) and invasion (presence/absence of Sargassum muticum) on the functional responses of macroalgal assemblages (per 64 cm2), i.e., respiration and light-use efficiency (alpha). When no significant effects were obtained for either factor, the full model is presented. Otherwise, we present both full and the minimum adequate model (in bold).
jpy12136-sup-0002-TableS2.docxWord document24KTable S2. May 2011. General linear model analysis testing the main and interactive effects of biodiversity (either species richness (S) or evenness (J')) and invasion (presence/absence of Sargassum muticum) on the functional responses of macroalgal assemblages (per 64 cm2), i.e., Respiration and light-use efficiency (alpha). When no significant effects were obtained for either factor, the full model is presented. Otherwise, we present both full and the minimum adequate model (in bold).
jpy12136-sup-0003-TableS3.docxWord document22KTable S3. May 2011. General linear model analysis testing the main and interactive effects of biodiversity (either species richness or evenness) and invasion (presence/absence of Sargassum muticum) on the functional responses of macroalgal assemblages, i.e., respiration and light-use efficiency (alpha). Data were corrected by macroalgal biomass (grams dry weight). When no significant effects were obtained for either factor, the full model is presented. Otherwise, we present both full and the minimum adequate model (in bold).

Please note: Wiley Blackwell is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.