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Green tides on inter- and subtidal sandy shores: differential impacts on infauna and flatfish

Published online by Cambridge University Press:  25 January 2017

N. Quillien*
Affiliation:
Laboratoire des Sciences de l'Environnement Marin, Institut Universitaire Européen de la Mer, Université de Bretagne Occidentale, Plouzané, France Åbo Akademi University, Environmental and Marine Biology, Turku, Finland Observatoire Marin, Institut Universitaire Européen de la Mer, Plouzané, France
M. C. Nordström
Affiliation:
Åbo Akademi University, Environmental and Marine Biology, Turku, Finland
H. Le Bris
Affiliation:
ESE, Ecology and Ecosystem Health, Agrocampus Ouest, INRA, Rennes, France
E. Bonsdorff
Affiliation:
Åbo Akademi University, Environmental and Marine Biology, Turku, Finland
J. Grall
Affiliation:
Observatoire Marin, Institut Universitaire Européen de la Mer, Plouzané, France
*
Correspondence should be addressed to: N. Quillien, Laboratoire des Sciences de l'Environnement Marin, Institut Universitaire Européen de la Mer, Université de Bretagne Occidentale, Plouzané, France email: nolwenn.quillien@gmail.com
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Abstract

Beach ecosystems extend from dune to offshore areas along most coasts, and provide essential services that are not provided by any other ecosystem. Indeed, sandy systems contain unique biodiversity and supply nursery and foraging areas for numerous commercially important marine species, such as flatfish. However, these systems are threatened by increasing anthropogenic pressure. Green tides (GT, i.e. accumulations of green opportunistic macroalgae) are a major human-induced threat to marine ecosystems, from inshore to nearshore. This eutrophication process greatly affects both benthic invertebrate communities and flatfish communities, within sheltered and non- or microtidal systems. However, the responses of dynamic open macrotidal sandy systems to eutrophication in the form of macroalgal mats are not yet fully understood. In particular, understanding the effects of GT on two connected biological compartments (infauna and flatfish) within two connected habitats (intertidal and subtidal) is crucial. Here, we set out to assess the influence of several environmental variables, including Ulva biomass, on the variability in infauna and flatfish communities in both the intertidal and the subtidal at four sites impacted or not by GT. In total, 110 biodiversity samples were analysed with classic and novel analytical approaches. Our results demonstrate that the presence of GT specifically impacts intertidal macroinvertebrate communities. However, small effects of GT on subtidal infauna communities, as well as on species-specific flatfish at both intertidal and subtidal, were still detectable. Our findings underline the vulnerability of highly dynamic ecosystems exposed to anthropogenic stress, in particular intertidal sandy shores.

Information

Type
Research Article
Copyright
Copyright © Marine Biological Association of the United Kingdom 2017 
Figure 0

Figure 1. Location (Brittany, north-western Europe) of the four study sites (circles) at the low-intertidal (light colours) and at the shallow subtidal (dark colours) of the two studied sandy sediment areas [colour online]. Blue lines along coastline represent isobaths (0, 5 and 10 m). The sites impacted by green tides are denoted by green circles and are located downstream of an agricultural catchment area (area filled with shades of green). The blue circles denote the sites that are never affected by accumulation of Ulva (un-impacted area denoted by the area filled with shades of blue).

Figure 1

Figure 2. Schematic illustration of the distribution of green tides occurring at two contrasted seasons: (A) eutrophied state in winter, and (B) eutrophied state in summer. Arrows denote algal material in motion.

Figure 2

Figure 3. Sampling design over time (from early spring (ES), to early winter = (EW); S, summer; F, autumn), showing the four sites (Intertidal – No GT, Intertidal – GT, Subtidal – No GT, Subtidal – GT), core and grab samples (black crosses), beach and beam trawling (triangles) and three environmental variables (WAV., waves; DESSI., desiccation; GT, green tide). ULV. MATS, Ulva mats; MTM, middle tidal mark; LTM, low tidal mark; 5 m = 5 m depth.

Figure 3

Table 1. Environmental characterization of the four sites (Intertidal – No GT, Intertidal – GT, Subtidal – No GT, Subtidal – GT) sampled seasonally from February to December 2013. SWT, Seawater temperature; Sorting = sorting index calculated based on first and third quartile ratio.

Figure 4

Figure 4. Monthly biomass of stranded Ulva through the year 2013 at intertidal (A; source: CEVA) and subtidal (B; source: this study) impacted sites. Note that the scales are not the same on the two plots.

Figure 5

Table 2. Per cent dominance in terms of abundance for the major species (threshold = 90% for zoobenthos, 100% for flatfish) living at intertidal and subtidal sandy bottoms harbouring or not harbouring green tides (GT or no-GT). Numbers in bold show contributions that are higher than 1%. Numbers in italics refer to values that are not relative abundance values. Taxonomic group and selected biological traits (feeding habit, feeding strategy, mobility, maximal size and reproduction/development) are given for each species. Traits data collected from MarLIN, EOL, polytraits and BIOTIC databases, and personal observations. For fish species, age groups have been based on individual sizes and peer literature and research reports on flatfish growth.

Figure 6

Figure 5. RDA correlation triplots (scaling 2) of macrofaunal community data (abundance) and explanatory variables of the four sites together: Inter – NoGT (squares), Inter – GT (triangles), Sub – NoGT (diamonds), Sub – Gt (reversed triangles); highlighting differences between habitats (A), environmental drivers (B) and seasonal patterns (C). GT, Ulva biomass; Sal, Salinity; Org, organic matter content, SWT, Seawater temperature.

Figure 7

Figure 6. Venn diagrams illustrating the result of variance partitioning of the macrofauna time series at intertidal (A) and subtidal (B) sites with respect to the presence of Ulva mats (GT/No GT), and temporal (distance-based Moran's eigenvector maps [dbMEMs]) explanatory variables. Variation explained is expressed as a percentage (%) based on adjusted R2. T, temporal variables; U, environmental variables; Residuals: unexplained variation.

Figure 8

Table 3. Variance partitioning of the macrofauna time series at both intertidal and subtidal sites with respect to temporal (distance-based Moran’s eigenvector maps [dbMEMs]), Ulva (occurrence and biomass), and spatial (location across shore encoded by Helmert contrasts) explanatory variables. Variation explained is expressed as percentage (%) based on adjusted R2. The significance of the fraction of interest is denoted by stars; *** denotes P < 0.001. T, temporal variables; U, Ulva variables; S, spatial variables; Unexpl., unexplained variation.

Figure 9

Figure 7. RDA correlation triplots (scaling 2) of age-grouped flatfish community data (apparent abundance) and explanatory variables of the four sites together: Inter – NoGT (squares), Inter – GT (triangles), Sub – NoGT (diamonds), Sub – GT (reversed triangles); highlighting differences between habitats (A), environmental drivers (B) and seasonal patterns (C). GT, Ulva biomass; Sal, Salinity; Org, organic matter content; SWT, seawater temperature.

Figure 10

Figure 8. Relative abundance of flatfish depending on their age-group at sandy bottoms within the intertidal (top panels) and the subtidal (low panels), harbouring green tides (right panels) or not (left panels). Numbers on top of bars show mean apparent abundance, with standard deviation in italics and between parentheses. TUR, Scophthalmus maximus; CAR, Pleuronectes platessa; BAR, Scophthalmus rhombus; ARN, Arnoglossus laterna; SOL, Pegusa lascaris; BUG, Buglossidium luteum.