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ICES Journal of Marine Science: Journal du Conseil Advance Access originally published online on September 9, 2008
ICES Journal of Marine Science: Journal du Conseil 2008 65(8):1492-1497; doi:10.1093/icesjms/fsn146
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© 2008 International Council for the Exploration of the Sea. Published by Oxford Journals. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

This article appears in the following ICES Journal of Marine Science issue: Marine Environmental Indicators: Utility in Meeting Regulatory Needs [View the issue table of contents]

Descriptors from Posidonia oceanica (L.) Delile meadows in coastal waters of Valencia, Spain, in the context of the EU Water Framework Directive

Yolanda Fernández-Torquemada1, Marta Díaz-Valdés1, Francisco Colilla2, Beatriz Luna1, José Luis Sánchez-Lizaso1 and Alfonso A. Ramos-Esplá1,2

1 Department of Marine Sciences and Applied Biology, University of Alicante, Alicante, Spain
2 Centro de Investigación Marina de Santa Pola, Torre d’Enmig s/n, Cabo de Santa Pola, Alicante, Spain

Correspondence to Y. Fernández-Torquemada: tel: +34 965903400 ext. 2916; fax: +34 965909897; e-mail: yolanda.fernandez{at}ua.es

Fernández-Torquemada, Y., Díaz-Valdés, M., Colilla, F., Luna, B., Sánchez-Lizaso, J. L., and Ramos-Esplá, A. A. 2008. Descriptors from Posidonia oceanica (L.) Delile meadows in coastal waters of Valencia, Spain, in the context of the EU Water Framework Directive. – ICES Journal of Marine Science, 65: 1492–1497.

Evaluations are provided of 21 descriptors of Posidonia oceanica meadows along the coast of Valencia, Spain, with a view to using these in implementing the European Water Framework Directive (WFD). The descriptors selected are known to respond to a variety of anthropogenic disturbances. Data were collected at 17 locations during three consecutive years. A principal components analysis was used to classify the ecological status of each locality according to five classes as prescribed by the WFD. To identify the descriptors that contributed most to similarity among localities within each class and to dissimilarity between adjacent classes, a similarity percentage analysis was performed. We also correlated the descriptors with an independent set of indicators for various types of anthropogenic pressures on the water bodies associated with the different localities. The descriptors providing the most consistent information on status as well as demonstrating a significant relationship with estimated pressures were: shoot density, shoot foliar surface, dead-matte cover, meadow cover, herbivore pressure, rhizome baring/burial, foliar necrosis, percentage of plagiotropic rhizomes, and leaf-epiphyte biomass.

Keywords: biological quality element, descriptors, Posidonia oceanica, seagrass, Water Framework Directive

Received 7 December 2007; accepted 8 June 2008; advance access publication 9 September 2008.


   Introduction
Top
 Introduction
Material and methods
 Results
 Discussion
 References
 
The Water Framework Directive (WFD) establishes a comprehensive policy for monitoring and protection of the ecological status of surface waters and groundwater within the European Union (EC, 2000), including marine coastal waters. Its main objective is to reach at least a "good ecological status" for all surface water bodies by 2015. The WFD also prescribes that the status of each water body is assessed based on biological, hydromorphological, and physico-chemical quality elements. Biological quality elements (BQEs) are defined as organisms or groups of organisms that are sensitive to disturbances, including phytoplankton, macrophytes, benthic invertebrate fauna, and transitional fish fauna.

The application of the WFD in coastal waters has resulted in the development of new methodologies focused mainly on invertebrates of soft-bottom benthos (Simboura et al., 2005; Dauvin and Ruellet, 2007), macroalgal communities (Ballesteros et al., 2007; Wilkinson et al., 2007), and seagrasses (Krause-Jensen et al., 2005; Romero et al., 2007).

Seagrass meadows represent an important ecosystem that is sensitive to changes in environmental quality (Short and Wyllie-Echeverria, 1996; Hemminga and Duarte, 2000). In the Mediterranean Sea, the dominant seagrass is Posidonia oceanica (L.) Delile, an endemic species that may form extensive meadows down to 40 m. These meadows constitute one of the most productive and valuable ecosystems in the Mediterranean (Jeudy De Grissac, 1979; Boudouresque and Meinesz, 1982). Despite being listed as a protected species in the Habitats Directive (EC, 1992), P. oceanica habitats are experiencing a widespread decline (Marbà et al., 1996). These losses are commonly attributed to human activities such as bottom-trawl fishing, coastal constructions, beach replenishment, fish farming, and desalination plants (Sánchez-Lizaso et al., 1990; Delgado et al., 1999; Ruiz and Romero, 2003; Fernández-Torquemada et al., 2005; González-Correa et al., 2008). Given its broad distribution throughout the Mediterranean Sea and its sensitivity, P. oceanica might be used as an appropriate bio-indicator (Pergent-Martini and Pergent, 2000) and has been proposed as one of the BQEs for coastal waters in the area (Casazza et al., 2006).

Descriptors that have been employed most often in research and monitoring programmes include shoot density, meadow and dead-matte cover, meadow limits, epiphytic coverage, leaf biometry, shoot balance, and total non-structural carbohydrate content in rhizomes (Alcoverro et al., 2001; Krause-Jensen et al., 2004; Pergent-Martini et al., 2005; González-Correa et al., 2008). Our main objective is to evaluate some of those potential descriptors with a view to selecting appropriate indicators from the Posidonia ecosystem to use in implementing the WFD.


   Material and methods
Top
 Introduction
 Material and methods
Results
 Discussion
 References
 
Study area and sampling design
The study was conducted along the coast of Valencia, Spain, during September–October 2005, 2006, and 2007. Sampling was done by scuba divers at 17 locations (Figure 1) in the depth range 14–17 m, because meadows at these depths are not usually affected by natural alterations, such as those caused by waves or storms (Krause-Jensen et al., 2004). The locations were selected based on existing knowledge of the status of their respective Posidonia meadows. At each locality, three sampling sites separated by hundreds of metres were randomly selected to prevent spatial pseudo-replication. At each site, three 40 x 40 cm quadrats were randomly selected to measure shoot density, percentage of plagiotropic rhizomes, and rhizome baring. Living and dead Posidonia cover was estimated as the proportion of living and dead patches on three replicate 20 m transects. In addition, ten shoots were harvested at random and transported to the laboratory for further analysis (Table 1).


Figure 1
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  		Figure 1. Map of the coast of Valencia (eastern Spain) with the 17 sampling locations indicated and the water bodies distinguished.

 


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  		Table 1. Summary of the P. oceanica descriptors evaluated and methods employed for measurements in the field (F) or in the laboratory (L).

 
Analysis of data and metric selection
As a first selection of potentially useful descriptors based on the existing literature (Pergent-Martini et al., 2005; Romero et al., 2007), we chose 21 metrics known to respond to a variety of anthropogenic disturbances and that appear to contribute most information on meadow quality (Table 1). We performed a univariate analysis of variance (ANOVA; Underwood, 1997) to estimate the variability for each descriptor and to test whether or not differences in the mean values of the various descriptors varied significantly among locations. The linear model for this analysis was defined as:


Formula

where µ is the overall mean, Li a fixed effect for location i, sj(i) a random effect for site j within location i, and {epsilon}ijk is the residual error for the kth observation of site j within location i.

Furthermore, we composed two virtual sites, one with the best values observed for all individual metrics (highest values for "positive" metrics and lowest for the "negative" ones) to serve as a reference condition and one with the worst values. These were used together with the data for the 17 localities to carry out a principal component analysis (PCA). The PCA’s first component was translated into an ecological quality ratio (EQR) on a scale of 0–1, by dividing it by the component value of the reference condition. Subsequently, we applied the class boundaries established in the EU intercalibration meetings (MedGIG, 2007) to these EQR values to classify the current ecological status of the Posidonia meadows at each site, according to five classes (high, good, moderate, poor, and bad). To elucidate the contribution of each metric to the similarity among localities within a class and to the dissimilarity between adjacent classes, the similarity percentage analysis (SIMPER) routine was used (PRIMER-E software, Plymouth, UK).

We also correlated estimates of the six anthropogenic pressures that were considered most relevant to Posidonia meadows (i.e. coastal construction, beach regeneration, urban sewage, industrial sewage, pollution from rivers and channels, and pollution from agricultural soil use; Table 2), with the mean value of each descriptor for the ten water bodies designated (Figure 1). Based on all results, the nine most promising descriptors to evaluate anthropogenic impacts were selected for rerunning the PCA and the classification in WFD categories.


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  		Table 2. Data on the main anthropogenic pressures per kilometre of coastline by water body (WB; cf. Figure 1), as derived from Agència Catalana de l’Aigua (2006).

 

   Results
Top
 Introduction
 Material and methods
 Results
Discussion
 References
 
The results of the ANOVA revealed that all the descriptors evaluated differed significantly among locations, suggesting that all were potentially useful and none could be rejected a priori. Therefore, all descriptors were used in a PCA (Figure 2a), the first two axes of which (PC1 and PC2) explained 69 and 12% of the variance, respectively. Results from this PCA were also applied to obtain the classification of the 17 locations in terms of five status classes (high, good, moderate, poor, and bad), based on the EQR derived from the PC1, where the intermediate class boundaries are somewhat arbitrary (Figure 2b).


Figure 2
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  		Figure 2. Results of the principal components analysis applied (a) to all Posidonia descriptors evaluated (for abbreviations see Table 1) and (c) to a selected group of nine descriptors, and (b and d, respectively) the associated PCA ordination diagrams of the localities studied (for locality numbers see Figure 1; B.R.S., Best Reference Site; W.R.S., Worst Reference Site).

 
The similarity percentage analysis demonstrated that the descriptors that contributed more than 5% on average to similarity among localities within each status class were shoot density, shoot foliar surface, herbivore pressure, meadow cover, and maximum leaf length (Table 3). The metrics that contributed more than 5% on average to dissimilarity were shoot density, dead-matte cover, meadow cover, shoot foliar surface, and Caulerpa racemosa cover (Table 3).


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  		Table 3. Analysis of similarity within WFD classes and dissimilarity between neighbouring WFD classes for individual P. oceanica descriptors (cf. Table 1) by year.

 
Table 4 shows all correlations found between descriptors and estimates of the six selected anthropogenic pressures. High positive correlations were found between dead-matte cover and coastal constructions, and between the proportion of plagiotropic rhizomes and industrial sewage; a high negative correlation occurred between meadow cover and industrial sewage.


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  		Table 4. Correlation coefficients (*p < 0.05; **p < 0.01; ***p < 0.001) between average values of P. oceanica descriptors (cf. Table 1) per water body (only those showing at least one significant correlation are included) and the six components of anthropogenic pressure selected (n = 10).

 
Based on these analyses, we selected nine descriptors that were significantly correlated with different human pressures and that also contributed most to the (dis-)similarity in the classification of localities. Number of leaves was omitted because many other descriptors were also significantly correlated with the same pressures, although it did not contribute much to the classification. Although not contributing much either, epiphyte biomass was retained, because it was one of the few to be correlated with river discharge. The final selection included: shoot density, shoot foliar surface, dead-matte cover, meadow cover, herbivore pressure, rhizome baring/burial, necrosis, plagiotropic rhizomes, and epiphyte biomass. We then repeated the PCA with these nine metrics (Figure 2c) to investigate whether or not the meadow classification remained stable (Figure 2d). This appeared to be largely the case. Although some differences can be observed in the distribution of the localities on the second axis (Figure 2d), the PC2 only explained 6% of variance and did not seem to be related to the status of Posidonia meadows. Furthermore, the PC1 explained a greater part of the variance (82 vs. 69%), suggesting that this selection of descriptors provided a better basis for discriminating between WFD quality classes than the original list.


   Discussion
Top
 Introduction
 Material and methods
 Results
 Discussion
References
 
In evaluating the 21 Posidonia descriptors, ANOVA, PCA, similarity analysis, and correlations with anthropogenic pressures were used to select the most appropriate ones for implementation of the WFD. The final suite includes metrics relating to the community (herbivore pressure and epiphyte biomass), the population (shoot density, proportion of plagiotropic rhizomes, dead-matte cover, and meadow cover), and to individual plants (rhizome baring/burial, shoot foliar surface, and foliar necrosis). Meadow cover, shoot foliar surface, and shoot density were negatively correlated with most of these pressures.

For a selection of metrics to be applied in future monitoring programmes, cost-effectiveness is an important issue, and therefore the metrics should be easily measured and applied. Although some descriptors require that samples be analysed in the laboratory (e.g. shoot foliar surface, foliar necrosis, and epiphyte biomass), these metrics can be collected rapidly at relatively low cost. More complex and time-consuming analyses that, in some cases, could be subject to analytical errors might be rejected based on not providing much additional information (Krause-Jensen et al., 2004).

Sampling design may be a critical issue for the validity of the results obtained. Because some descriptors (such as meadow cover or shoot density) may demonstrate a high variability at small or medium spatial scales (Panayotidis et al., 1981; Balestri et al., 2003), we recommend utilizing a nested sampling design with an adequate spatial replication. Furthermore, seasonal variation at the community, population, and individual plant level must be taken into account. Descriptors such as shoot foliar surface and epiphyte biomass should be sampled during a fixed period of the year to avoid any confounding effect of seasonality.

We emphasize that P. oceanica has slower growth rates than other seagrass species (Bay, 1984; Ruiz and Romero, 2003). Therefore, the selection of indicators provided here may be unsuitable for other species. The selection may also have to be adapted to regional conditions. However, it seems important to use a reasonable range of metrics to determine the ecological status of a water body, based on seagrass. Although using less descriptors could lead to erroneous classifications, using too many would be costly in terms of time and money. Because the WFD allows for a revision of the BQE classification methodologies every 6-year reporting cycle, the data collection for Posidonia meadows will be continued.


   Acknowledgements
 
The study was financed by the Conselleria de Medi Ambient, Aigua, Urbanisme i Habitatge of the Generalitat Valenciana. We thank J. M. González-Correa, Y. del Pilar, J. A. de la Ossa, and Y. Múgica, who assisted in field-data collection, and the participants in the MedGIG (Geographical Intercalibration Group of the Mediterranean Coastal Waters) meetings for their stimulating ideas and contributions. The authors also thank the two referees and the guest editor for their helpful comments on earlier versions of the manuscript.


   References
Top
 Introduction
 Material and methods
 Results
 Discussion
 References
 

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