Changes in macrofaunal biological traits across estuarine gradients : implications for the coastal nutrient filter

Benthic macrofaunal communities have a profound impact on organic matter turnover and nutrient cycling in marine sediments. Their activities are of particular importance in the coastal filter, where nutrients and organic matter from land are transformed and/or retained before reaching the open sea. The benthic fauna modify the coastal filter directly (through consumption, respiration, excretion and biomass production) and indirectly (through bioturbation). It is hard to experimentally quantify faunal contribution to the coastal filter over large spatial and temporal scales that encompass significant environmental and biological heterogeneity. However, estimates can be obtained with biological trait analyses. By using benthic biological traits, we explored how the potential contribution of macrofaunal communities to the coastal filter differ between inner and outer sites in an extensive archipelago area and examine the generality of the observed pattern across contrasting coastal areas of the entire Baltic Sea. Estimates of benthic bioturbation, longevity and size (i.e. ‘stability’) and total energy and nutrient contents differed between coastal areas and inner versus outer sites. Benthic traits indicative of an enhanced nutrient turnover but a decreased capacity for temporal nutrient retention dominated inner sites, while outer sites were often dominated by larger individuals, exhibiting traits that are likely to enhance nutrient uptake and retention. The overarching similarities in benthic trait expression between more eutrophied inner vs. less affected outer coastal sites across the Baltic Sea suggest that benthic communities might contribute in a similar manner to nutrient recycling and retention in the coastal filter over large geographical scales.peerReviewe

Coastal waters North East Atlantic geographic intercalibration group: Benthic invertebrate fauna ecological assessment methods

The European Water Framework Directive (WFD) requires the national classifications of good ecological status to be harmonised through an intercalibration exercise. In this exercise, significant differences in status classification among Member States are harmonized by comparing and, if necessary, adjusting the good status boundaries of the national assessment methods. Intercalibration is performed for rivers, lakes, coastal and transitional waters, focusing on selected types of water bodies (intercalibration types), anthropogenic pressures and Biological Quality Elements. Intercalibration exercises are carried out in Geographical Intercalibration Groups - larger geographical units including Member States with similar water body types - and followed the procedure described in the WFD Common Implementation Strategy Guidance document on the intercalibration process (European Commission, 2011). The Technical report on the Water Framework Directive intercalibration describes in detail how the intercalibration exercise has been carried out for the water categories and biological quality elements. The Technical report is organized in volumes according to the water category (rivers, lakes, coastal and transitional waters), Biological Quality Element and Geographical Intercalibration group. This report gives a description of the intercalibration of the different benthic assessment approaches for in coastal waters in the North East Atlantic Geographical Intercalibration Group (NEA-GIG) for types NEA 1/26 (Exposed or sheltered, euhaline, shallow waters), NEA 3/4 (Wadden sea type) and NEA 7 (Deep fjordic and sea loach systems). The benthic assessment approaches of nine European Member States (Belgium, Germany, Denmark, France, Ireland, the Netherlands, Portugal, Spain and the United Kingdom) and Norway are intercalibrated. In Spain, the competent authorities for the WFD application are the regions (‘autonomous communities’); therefore for the benthic assessment methods three regions have been considered: Basque Country, Andalusia and Cantabria (no information on Galicia or Asturias). Part D of the report describes the Germany assessment approach for the type NEA 5. This type is not shared with the rest of the Members Stares, and therefore, the Intercalibration is not possibleJRC.D.2-Water and Marine Resource

Species Sorting of Benthic Invertebrates in a Salinity Gradient – Importance of Dispersal Limitation

<div><p>The relative importance of environment and dispersal related processes for community assembly has attracted great interest over recent decades, but few empirical studies from the marine/estuarine realm have examined the possible effects of these two types of factors in the same system. Importance of these processes was investigated in a hypothetical metacommunity of benthic invertebrates in 16 micro-tidal estuaries connected to the same open sea area. The estuaries differed in size and connectivity to the open sea and represented a salinity gradient across the estuaries. The Elements of Metacommunity Structure (EMS) approach on estuary scale was complemented with a mechanistic variance partitioning approach on sample scale to disentangle effects of factors affecting assembly of three trait groups of species with different dispersivity. A quasi-Clementsian pattern was observed for all three traits, a likely response to some latent gradient. The primary axis in the pattern was most strongly related to gradients in estuary salinity and estuary entrance width and correlation with richness indicated nestedness only in the matrix of the most dispersive trait group. In the variance partitioning approach measures of turnover and nestedness between paired samples each from different estuaries were related to environmental distance in different gradients. Distance between estuaries was unimportant suggesting importance of factors characterizing the estuaries. While the high dispersive species mainly were sorted in the salinity gradient, apparently according to their tolerance ranges towards salinity, the two less dispersive traits were additionally affected by estuary entrance width and possibly also area. The results exemplify a mechanism of community assembly in the marine realm where the niche factor salinity in conjunction with differential dispersal structure invertebrates in a metacommunity of connected estuaries, and support the idea that dispersive species are more controlled by the environment than less dispersive species.</p></div

Map over the investigation area showing locations of 16 estuaries with areas indicated by different colors and id numbers as in Table 1.

<p>Open sea is indicated by blue color and the 242 sampling sites by black dots. Copyright on the base map by the Danish Geodata Agency.</p

Results of marginal and sequential tests in DistLM modeling of β_sim with three predictors (A = Salinity difference, B = Log10 Entrance width difference and C = Log10 Estuary area difference) of paired samples from different estuaries.

<p>HD = High dispersive, ID = Intermediate dispersive and LD = Low dispersive species trait group. Variance proportion = the proportion of total variance explained by the predictor (S²). Top sequence (A,B,C) shows results from marginal tests and the following three sequences (A1,B1,C1 and B2,C2,A2 and C3,A3,B3) show results from sequential tests, where A1, B2 and C3 are first fitted to data and B1,C1,C2,A2, A3, B3 gives the remaining independent variance explained after the previous variable has been fitted. Dashed vertical line indicates the total variance proportion explained by the variables. *** = P = 0.001, ** = P <0.01, * = P < 0.05 and ns = P > 0.05.</p

Environmental variables and sampling data for 16 micro-tidal Danish estuaries.

<p>Environmental variables and sampling data for 16 micro-tidal Danish estuaries.</p

Spearman’s correlation coefficients between site (estuary) scores on the primary axis from RA and predictor variables and richness.

<p>Spearman’s correlation coefficients between site (estuary) scores on the primary axis from RA and predictor variables and richness.</p

Plots of β_sor vs salinity difference of the three dispersal groups.

<p>a): Beta vs differences between estuaries and b): Beta vs differences between estuaries and adjacent open sea.</p

Results of marginal and sequential tests in DistLM modeling of β_nes with three predictors (A = Salinity difference, B = Log10 Entrance width difference and C = Log10 Estuary area difference) on paired samples from different estuaries.

<p>For more information see legend of <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0168908#pone.0168908.g004" target="_blank">Fig 4</a>.</p