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BENTHIC ECOSYSTEM QUALITY INDEX 2:

DESIGN AND CALIBRATION OF THE BEQI-2 WFD METRIC FOR

MARINE BENTHOS IN TRANSITIONAL WATERS

dr. Willem M.G.M. van Loon (Centre for Water Management - RWS Waterdienst) ir. Anja J. Verschoor (National Institute for Public Health and the Environment - RIVM) dr. Arjan Gittenberger (Gimaris)

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This report will be published in the near future in an international journal. Therefore, please use this report for the purpose of intercalibration only.

Document status Final, 8 dec. 2011

Acknowledgements Angel Borja, Peter Bot, Gert van Hoeij, Dick de Jong, Graham Philips, Hans Ruiter and Gerard Spronk are acknowledged for their valuable comments.

Legend front page figure Detailed ecotope map of the Eastern part of the Westerschelde (ecotope names in Dutch). With courtesy to Dick de Jong, RWS Zeeland.

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TABLE OF CONTENTS

Summary .......................................................................................................................... 4 List of Definitions and Abbreviations ................................................................................. 5 1. Introduction ................................................................................................................... 6 2. Selection of datasets .................................................................................................... 7 3. Ecotope Classification, Sample Availability and Quality Control .................................... 8

3.1 Ecotope classification .............................................................................................. 8 3.2 Sample availability ................................................................................................... 8 3.3 Quality control ......................................................................................................... 8

4. Data pooling ................................................................................................................. 9

5. Final Selection of Indicators ........................................................................................ 11 5.1 Diversity indicator trends .......................................................................................... 11 5.2 AMBI, AMBI sedimentation, AMBI fisheries and ITI indicator trends ........................ 14 5.3 Correlation analysis ............................................................................................................... 16 5.4 Final Selection of Indicators ...................................................................................... 16 6. Calculation of national reference values ..................................................................... 17 6.1 Reference setting method ......................................................................................... 17 6.2 Reference values ...................................................................................................... 17 7. Calibration Method ...................................................................................................... 19 7.1 BEQI-2 calibration method ........................................................................................ 19 7.2 Comparison of BEQI-2 and m-AMBI using Westerschelde data pools ...................... 20 7.3 Comparison of BEQI-2 and m-AMBI using the NEAGIG dataset ............................... 21

8. Pressure-Impact Analysis ........................................................................................... 23 8.1 Qualitative pressure-impact analysis ......................................................................... 23 8.2 Qualitative description of human pressures .............................................................. 23 8.3 Quantitative pressure-impact analysis in the Dutch Westerschelde ecotopes Mesohaline-Intertidal and Polyhaline-Subtidal ................................................................ 24 9. Validation of BEQI-2 with expert judgement ................................................................ 31 10. References.33 Appendix 1: BEQI-2 results for the Dollard .................................................................... 33

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SUMMARY

The BEQI-2 is a redesigned version of the BEQI metric (Van Hoeij et al. 2007) which The Netherlands first used as their WFD metric for marine benthos. In the BEQI-2, level 1 (ratio between fytoplanton primary production and total benthic biomass) has been omitted (see Boon et al., 2011). Level 2, area assessment of habitats, has been left unchanged. Level 3, quality of the benthic community, has been redesigned fundamentally. The summary of this report is given as a method summary fact sheet. For explanations of abbreviations and definitions, see the Table on the following page.

Aspect of BEQI-2 Summary description

Indicator selection The indicators Species richness, Shannon index (log base 2) and AMBI appear to show the most sensitive trends in the Dutch transitional water benthos data and were therefore selected for use in the BEQI-2. The ITI also appears to give good results in the Westerschelde and Dollard, and shows comparable slopes and significances as the AMBI. Therefore, the more commonly used AMBI was preferred for use in BEQI-2.

Calibration method The BEQI-2 is calibrated by straightforward univariate calibration of the three individual indicators. The indicator-EQR values are combined using equal weight factors. The resulting BEQI-2 EQR values are very similar to the corresponding m-AMBI scores. However, the univariate calibration procedure is very transparant and the resulting indicator-EQR values can be communicated very well to policy makers and water managers. In addition, the BEQI-2 EQR values calculations can be automated very easily compared with the m-AMBI. Very good correlations between BEQI-2 and m-AMBI EQRs have been demonstrated for the Westerschelde and NEAGIG common dataset.

Ecotope classification

The NEAGIG ecotope classification is used: Mesohaline-Intertidal, Mesohaline-Subtidal, Polyhaline-Intertidal and Polyhaline-Subtidal. Addition of the classification sand/mud is considered less useful because of the very gradual gradients in sediment composition.

Season Only autumn data are available for the Westerschelde. For the Dollard, the autumn data show slightly higher significant trends than spring data.

Data period 1990 - 2005

Sample area and data pooling

Small manual core samples (ca. 0.015 m2) are randomly pooled to 0.1 m2 + 0.01 m2. This pooling procedure is repeated 10 times to average out random variations in the pooling process. Per ecotope-year, the average indicator values of the 10 pool runs are calculated. This surface area of 0.1 m2 is necessary to (a) obtain sufficient benthic signal for all samples, (b) get good trend analysis results and (c) to harmonize with the NEAGIG agreement on 0.1 m2.

Reference values Of a complete ecotope-indicator dataset (all years) of the Westerschelde the 99 percentile of the indicator values of Species richness and Shannon index are used. For AMBI(ref) = 0 is used as a theoretically correct value which also gives the most plausible results in both Dutch transitional water bodies compared with expert judgement. For the Dollard Mesohaline-Intertidal ecotope, the reference values

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of the corresponding Westerschelde ecotope are used because this is a national WFD procedure.

Bad values Theoretically correct bad values are used: S(bad) = 0; H(bad) = 0; AMBI(bad) = 6.

EQR trends Using this new BEQI-2 method, a considerable number of significant trends were found for Species richness, Shannon, AMBI, ITI and BEQI-2 in several ecotopes.

Pressure sensitivity validation

Significant correlations between Dissolved Oxygen concentrations (p = 0.017) and Dissolved Inorganic Nitrogen (p = 0.0010) and BEQI-2 EQRs have been found for the Westerschelde Mesohaline-Intertidal. A significant correlation (p = 0.0087) between the percentage of high dynamic intertidal ecotope (as a proxy for the maximum flow velocity) and the EQR of Westerschelde Polyhaline-Subtidal has been. These results demonstrate the human pressure sensitivity of BEQI-2.

Water body assessment

EQR-values of ecotopes are combined with the relative area of the ecotope as weight factor. All area within a water body must be represented by the ecotopes used.

List of Definitions and Abbreviations

Subject Full description / Definition

AMBI Aztec Marine Biotic Index. A commonly used indicator for the quality of benthic species.

BEQI-2 Benthic Ecosystem Quality Index 2. The Dutch WFD metric for marine benthos. The BEQI-2 is an improved version of the BEQI-1.

S Species richness. A very commonly used ecological diversity indicator.

H Shannon index. A very commonly used ecological diversity indicator. This index assesses a combination of the Species richness and relative abundances of species. Note: this index can have a log base 2, e or 10. In the BEQI-2 and m-AMBI, log base 2 is used.

IC Intercalibration

ITI Infaunal trophic index. This index is based on the classification of species into four trophic groups.

Macrozoobenthos

Animals which live in (endofauna) or on top of (epifauna) the soft bottom sediment that are retained at a sieve with a mesh size of 1 mm.. Epifauna may be sessile or mobile. Hard bottom benthos is not included in the WFD definition.

m-AMBI Multivariatie AMBI. Factorial and discriminant analysis using the indicators AMBI, S and H and multivariate calibration.

Multivariate calibration

Calibration using a multi-dimensional reference point. For example, the m-AMBI uses multivariate calibration.

Simpson index A well-known ecological diversity indicator, comparable with the Shannon index. This index assesses a combination of the Species richness and relative abundances of species.

TW Transitional water

Univariate calibration

Calibration of a single indicator, e.g. the Shannon index.

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1. Introduction

In this report, the redesign and calibration of the Dutch WFD metric for marine benthos, the Benthic Ecosystem Quality Index 2 (BEQI-2) is described. This redesign is based on the BEQI review (Boon et al., 2011) which was commissioned by RWS Waterdienst. In this review, the indicators present in BEQI, but also other commonly used indicaters and metrics in Western Europe, are reviewed. The review led to the conclusion that the original BEQI could be optimized significantly, by (a) omitting level 1 and (b) by using a different combination of indicators at level 3. Based on this review, in 2010 RWS Waterdienst started a redesign and calibration project of BEQI-2. As a part of this project, two subprojects were started for (a) the review of common Dutch benthic species and their sensitivities for environmental pressures (Gittenberger & Van Loon, 2011) and (b) calibration and intercalibration of BEQI-2 (calibration results presented in this report).

In the calibration process of BEQI-2, the most promising indicators and calibration methods (with a score > 4; highest score = 5) from the BEQI review (Boon et al., 2011) were selected for testing with Dutch transitional water data. The selected indicators and calibration methods are shown in Table 1. Table 1: selection of indicators and metrics for testing with Dutch transitional water data.

Indicators Remarks

Species richness The number of species found in a standardized sample areas.

Margalef index The number of species divided by the square root of the abundance.

Shannon index The number of species combined with the evenness.

Simpson index The number of species combined with the evenness

AMBI AZTI marine biotic index

AMBI-sedimentation In this newly designed index, the AMBI model is used but the species classifications have been optimized for the physical pressure sedimentation (see also Gittenberger & Van Loon, 2011).

AMBI-fisheries In this newly designed index, the AMBI model is used but the species classifications have been optimized for the physical pressure fisheries (see also Gittenberger & Van Loon, 2011).

ITI Infaunal Trophic Index

Calibration methods Remarks

DKI/NKI model In these models, univariatie calibration and weighted averaging of two indicator EQR values is used.

m-AMBI/BAT model In these models, multivariate calibration including factor analysis, discriminant analysis is used based on 3 indicators.

The suitability of the selected indicators has been evaluated using trend analysis in the Westerschelde and Dollard data and the results are presented in Chapter 5. The univariate and multivariate calibration methods have been compared and the results are presented in Chapter 7.

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2. Selection of datasets

The TW-NEAGIG database version 5 and 8, and the MacBEQI(ii) database containing only the official Dutch MWTL monitoring data were used for the calibration calculations. For the Westerschelde data, we selected the autumn samples because (a) this constitutes the bulk of the samples and (b) autumn data are judged by benthic experts to be the most suited for a benthos assessment considering the most full grown and stabilized community composition (Boon et al. 2011).

The dataset submitted for the Westerschelde contains a more detailed ecotope classification, including sand/mud and low/high dynamic. For the IC process, these additional ecotopes have been omitted.

Data from the Dollard, a part of the binational Eems Dollard estuary, were selected to additionally test and optimize the BEQI-2. Note however that that these data are not officially part of the intercalibration process. We have performed a review of the AMBI values of circa 300 benthic species which are more common in Dutch marine waters (Gittenberger & Van Loon, 2011). However, in the IC process we strictly use the AMBI classification given in the species table in the TW-NEAGIG database in order to obtain the best comparability. If AMBI species classifications were missing for our BEQI-2 calibration with the reviewed AMBI values, we used the AMBI-list of AZTI, version february 2010, to supplement missing values.

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3. Ecotope Classification, Sample Availability and Quality Control

3.1 Ecotope classification The distinction of ecotopes is an important method in the benthos assessment in order to improve the comparability of benthos data and to reduce the natural variability. If a suitable ecotope classification is used, the possibilities for trend analysis within an ecotope, and the comparison of similar ecotopes from different West European countries, improves significantly.

In the NEAGIG benthos intercalibration in Transitional Waters, the following ecotope classification has been agreed on:

Based on salinity: mesohaline (5 - 18 PSU) and polyhaline (18 - 30 PSU).

Based on global height: Intertidal (above the Average Low Water Line) and Subtidal (below the Average Low Water Line).

The distinction between Sandy ( 3; N > 6; percentage of total abundance AMBI classified > 80%; Borja & Mader, 2006). It appeared that approx. 40% of the samples did not meet these criteria. Especially the polyhaline sandy sampes often had too little "benthic signal" according to the m-AMBI criteria. Trend analysis of the Westerschelde dataset (approx. 2900 samples) did not show any significant instead trend, but instead showed large variations.

It was concluded in this project that the use of these individual samples with often poor benthic signals would not result in reliable assessment and trend analysis results. Therefore, it was concluded that data pooling was essential in order to obtain useful results.

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In view of the discussions and consensus in the NEAGIG benthos group, a pool area of 0.1 m2 + 10% was chosen as the standard pool area.

The BEQI-2 script reports per data pool of 0.1 m2: (a) the number of taxa, (b) the total abundance and (c) per indicator which percentage of the abundance is not AMBI-classified.

The BEQI-2 script uses a list of standardized taxa from the NEAGIG, and a separate list of taxa synonyms and their standardized taxa.

4. Data pooling

We developed an automated pool routine which uses 1000 random selections of samples and uses practically all available samples. Per-ecotope year, a limited number of samples may remain unpooled if the desired pooling area of 0.1 m2 cannot be reached. These remaining samples can be different in separate poolruns, so there is no systematic elimination of specific samples. These unpooled samples are removed from the produced poolfile. In many cases, a random combination of circa 7 samples of 0.015 m2 is made. Since the random selection process can lead to a certain variation in the indicator values obtained, the pool run is repeated 10 times, and the assessment values are calculated as the average indicator values of these 10 pool runs per ecotope-year. This procedure leads to a deviation of the indicator reference values of less than 2% of the asymptotic value for many repetitions (see Figure 1). An illustration of the (often limited) variation between 10 repeated poolruns is given in Figure 2 for the indicator Species richness in the 4 Westerschelde ecotopes, plotted as cumulative distributions. Figure 1: effect of repeating the pool procedure on the deviation from the average indicator value (residuals)

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Figure 2: variation of cumulative values of Species richness for 10 data pool runs.

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5. Final Selection of Indicators

The selection of indicators has been based by evaluating the trend analysis results for all tested indicators using the 4 Westerschelde ecotopes, 1 Dollard ecotope and the data period 1990-2005/2007. The trend analysis is performed per indicator and per ecotope, using ecotope-year averages or all separate data pools per ecotope-year. The indicators which show the most significant trends, and therefore appear to be the most sensitive for changes of the benthic community, are selected for use in BEQI-2.

5.1 Diversity indicator trends

Averaging method Trend analyses are based on average ecotope-year values. These average values can be obtained by (a) calculating the (arithmetic) average indicator value per ecotope-year or (b) calculating the median of the indicator values per ecotope-year. This choice was tested with data for the Westerschelde ecotopes Mesohaline-Intertidal and Polyhaline-Subtidal.

The following conclusions can be drawn from this test:

In the Mesohaline Subtidal, the average value shows higher R2 and p-values for the indicators S and H (which show clear linear trends) than the median values. This supports the idea that when the amount of data pools is limited, the average is a more robust choice than the median.

In the polyhaline subtidal, the median has higher R2 and p-values for S, while the average has higher R2 and p-values for H. So, in this ecotope with many data pools and well defined distributions, the median does not overall show better statistical results than the average.

The correlations and p-values for AMBI sedimentation (with a very week linear trend) do not show clearly better results for the average or median.

The AMBI organic did not show a significant linear trend. In conclusion, this comparison for the Westerschelde ecotopes shows that the

arithmetic average is on average a better choice than the median. The use of data pooling probably leads to more normalized distributions of the data pool indicator values. It is assumed that this conclusion will also hold for the Dollard data, for which data are also pooled. Trend analysis results Trend analyses have been performed using the average indicator value of the 10 pool runs for each ecotope-year dataset. In Table 2, the significant correlations with a p-value

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In the Dollard a significant negative trend of Species richness is observed (see Appendix 1). Shannon does not show a trend. The observed trend for S is consistent with the negative AMBI quality trends.

The diversity indicators Species richness, Margalef and Shannon show very significant and consistent trends in two Westerschelde ecotopes. Furthermore, these diversity indicators showed a relatively good correlation with a human pressure index in a recent study from Borja et al. (2011). Therefore, these diversity indicator trends are used as leading in the evaluation of the AMBI, AMBI sedimentation and AMBI fisheries.

Species richness gives the most significant trends in both ecotopes. The significance of the Margalef trend is somewhat lower than of Species richness. This shows that the indicator Species richness is slightly more sensitive than the Margalef index to show Species richness changes in the Westerschelde data.

Shannon also gives significant trends in the two mentioned ecotopes, and the trend is consistent with the Species richness trends.

Simpson gives a significant trend in the Polyhaline-Subtidal, but not in the Mesohaline-Intertidal. It appears therefore that the Simpson index is not as sensitive as the Shannon index to show diversity changes in the Westerschelde data. Table 2: Indicators which show significant trends (p

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Figure 3: trend analysis of S, H and AMBI in the four Westerschelde ecotopes.

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5.2 AMBI, AMBI sedimentation, AMBI fisheries and ITI indicator trends

AMBI In the Westerschelde, significant organic and chemical pressures are expected in the Mesohaline part so the AMBI is potentially relevant to use in the water body (Boon et al., 2011).

In the Westerschelde, no significant AMBI trends are observed. However, in the Mesohaline-Intertidal, where the three diversity indicators show very significant positive trends, a small (non significant) positive AMBI quality trend (decreasing AMBI) is observed. So, the non-significant AMBI trend is consistent with the diversity trends.

In the Polyhaline-Subtidal, where significant negative diversity trends are observed, a small negative AMBI quality trend (increasing AMBI) is observed. Again, the AMBI trend is consistent with the diversity trends. In the Dollard, significant chemical pressures are present so the AMBI is potentially relevant to use in this water body.

In the Dollard, a small but very significant negative AMBI quality trend (increasing AMBI) is observed (see Figure 4). This trends appears to correlate with small (non-significant) negative diversity trends. So, also in the Dollard the AMBI trend is consistent with the diversity trends. These negative quality trends can be explained by increasing chemical pressures, and maybe also partly by the presumed increasing sedimentation pressures.

In conclusion, in the cases described above the AMBI results are consistent with the diversity results and the results can be explained from the available qualitative pressure information. This gives sufficient confidence that the AMBI gives correct results and is suited for use in BEQI-2.

Figure 4: trend analysis of AMBI in the Dollard, ecotope Mesohaline-Intertidal.

AMBI review In a recent study of Gittenberger & Van Loon (2011), the standard AMBI species classifications from Borja were reviewed for the Dutch marine waters and a number of updates were proposed by 3 Dutch marine benthos taxonomic specialists. In the Polyhaline-Subtidal, a significant negative quality trend of the AMBI review (p = 0.0277) was observed. This trend correlates with the negative trends for S and H. In this ecotope, the AMBI review

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gives more significant trend analysis results than the standard AMBI. Since however in the Dollard a very signficant standard AMBI trend was observed, which is more significant than the AMBI review trend. Therefore, since the AMBI review does not consistently shows better results than the standard AMBI, at this point we choose to use the standard AMBI. AMBI sedimentation In the Westerschelde significant sedimentation pressure is present due to a considerable amount of dredging and dumping.

In the Mesohaline-Subtidal, a nearly significant negative trend for AMBI sedimentation is observed (p = 0.078). In this ecotope, Species richness shows a small and non-significant decrease, Margalef shows a small and non-significant increase and Shannon a small and non-significant increase. It appears that these three diversity indicators show small, non-significant and different trends, which do not support an ecological meaningful trend for AMBI sedimentation in this ecotope. It is concluded therefore that the AMBI sedimentation probably does not give an ecologically reliable signal in this ecotope.

In the Polyhaline-Intertidal, a nearly significant negative trend for AMBI sedimentation is observed (p = 0.089). In this ecotope, the three diversity indicators show small and consistent increases in quality. Therefore, the negative AMBI sedimentation trend is not confirmed by the positive diversity indicator trends, and the AMBI sedimentation probably does not give an ecologically reliable signal in this ecotope.

In the Dollard significant sedimentation pressure is present due to a considerable amount of dredging and dumping in the neighbouring Eems area. In this water body, a small and non-significant decrease of AMBI sedimention is observed, which would suggest a higher benthic quality. The diversity indicators however show small and non-significant decreases of the benthic quality. Again, in this case the AMBI sedimentation and diversity signals are not consistent. Furthermore, no decrease of AMBI sedimentation is expected, since the dredging and dumping activities probably remain at least at the same intensity level.

In view of these three cases, the results of the AMBI sedimentation give insufficient confidence in the sensitivity and correctness of this indicator. It is possible that the pressure sedimentation, which can also occur naturally due to e.g. storms and tidal currents, does not have very significant effects on marine benthos and therefore is difficult to detect using the AMBI sedimentation. Therefore, AMBI sedimentation is not used in BEQI-2 in transitional waters. AMBI fisheries In the Westerschelde fishing pressure has been reported by benthic experts to be small. Therefore, the AMBI fisheries is not expected to be useful in the Westerschelde. Furthermore, fisheries only occur in the subtidal ecotopes and not on the tidal flats. In the Polyhaline-Subtidal, where significant negative diversity trends occur, a positive quality trend for AMBI fisheries is observed, and these results are inconsistent.

In the Dollard, in the Mesohaline-Intertidal a small but very significant positive quality trend is observed for AMBI fisheries. However, shrimp fisheries is only performed in the Mesohaline-Subtidal and at the borders of the Mesohaline-Intertidal, and the benthos sampling has been performed at the tidal flat where no fishing occurs. So, the observed trend for AMBI fisheries cannot have been caused by a decrease of fishing activities and can be considered to be a false positive result.

In conclusion, at this point the AMBI fisheries gives insufficient confidence in the correctness of the results. Therefore, AMBI fisheries is not used in BEQI-2 for transitional waters.

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ITI The Infaunal Trophic Index was tested using the ITI species classifications collected in a database by Gittenberger & Van Loon, 2011. In the Polyhaline-Subtidal the ITI appeared to give a significant negative quality trend (p = 0.0121). This trend correlated with the negative trends of S and H. Since the AMBI review also showed a trend with a similar significance, it was concluded that the use of the more often applied AMBI was preferable to the use of the ITI. Conclusions It was concluded therefore that the AMBI is the best option for a sensitive/tolerant species indicator for the Dutch transitional waters Westerschelde and the Dollard.

5.3 Correlation analysis

The results of the correlation analysis can essentially be described as follows:

Species richness results correlate strongly with Margalef results, with a correlation coefficient ranging from 0.78 to 0.98 depending on the ecotope. This result shows that only one of these two indicators has to be used in the BEQI-2 metric.

Species richness correlates less with the Shannon index, with correlation coefficients ranging from 0.07 to 0.69. This result shows that, as expected, the Shannon index offers additional relative abundance information compared with Species richness. Therefore, the Shannon index will also be used in the BEQI-2 metric.

Species richness show a negative to low positive correlation with AMBI, ranging from -0.15 to 0.33. This result shows that the AMBI offers clearly different information than Species richness, and that combined use in the BEQI-2 metric is useful.

AMBI sedimentation, AMBI fisheries and the Simpson index are not discussed here anymore in view of the unsatisfactory pressure and trend analyses results given above.

5.4 Final Selection of Indicators

The results from the paragraphs 5.1 to 5.3 clearly show that the combination of the indicators Species richness, Shannon and AMBI gives the most useful description of changes of the benthic community in the Dutch transitional waters. With this combination, both the number of species, their relative distribution and their quality is assessed which appears to be a very logical metric design.

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6. Calculation of national reference values 6.1 Reference setting method

a. Statistical method to estimate reference values The basic assumption in the statistical reference setting procedure is that the highest indicator value within an ecotope-dataset - which is not an outlier - is a usable estimation of the average reference situation in the historical past. The indicator distributions (see Figure 5) have been analyzed in detail and show that the 99 percentiles of S and H are clearly not outliers, and are statistically robust to use as reference values. For AMBI the theoretical reference value of 0 is used, because: (a) the AMBI scale is well determined theoretically, (b) in the Westerschelde and coastal waters AMBI(ref) = 0 is closely approximated by measured data (c) this method is robust. In the Dollard the use of AMBI(ref) = 1 percentile gave erroneously high AMBI-EQR results. b. Bad values For S, H and AMBI theoretical bad values can be determined well. Clearly, S(bad) and H(bad) must be 0; in a really bad ecotope no species can survive. For the calculation of an AMBI bad at least 1 species must survive so the ecotope must not be completely bad. It was recently reported by Gittenberger & Van Loon (2011) that in the Dutch marine waters 3 common class V benthic species occur. This makes it theoretically possible to reach an AMBI of 6 in Dutch marine waters. Therefore, an AMBI(bad) of 6 is used. c. Water body or water type specific reference values During the national implementation phase of BEQI-2, it will be attempted to establish national type specific reference values for Transitional Waters. If the reference values for S, H and AMBI would be too different, than water body specific reference values will be used (as is already the case for BEQI-1).

6.2 Reference values

The reference setting methods described above result in the reference values listen in Table 3. Table 3: Reference values for the Westerschelde-MWTL data for BEQI-2.

Ecotope S ref S bad H ref H bad AMBI ref AMB bad

Meso-Inter 29.26 0 3.269 0 0 6

Meso-Sub 22.27 0 3.186 0 0 6

Poly-Inter 41.08 0 3.592 0 0 6

Poly-Sub 30.79 0 3.808 0 0 6

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Figure 5: Indicator probability distributions of Species richness, Shannon and AMBI.

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7. Calibration Method 7.1 BEQI-2 calibration method

Calibration is the transformation of an indicator value into an EQR value, using a formula and a reference and bad value. Intercalibration is (a) the harmonization of reference and bad values used by different countries for their national metrics, and (b) harmonization of national class borders.

A remaining question in the design of the BEQI-2 was, if univariatie calibration (a linear combination of univariately calibrated indicator EQR-values) was going to be used (like in the IQI, DKI, NKI) or a multivariate calibration of indicators (like in the m-AMBI and BAT). From the BEQI-review (Boon et al. 2011) it was concluded that the m-AMBI and BAT mulitvariate calibration method is probably statistically and ecologically sound in view of its scientific publications, but that this statistical method is not very transparant and not very easy to automate. Therefore, we would like to use univariate calibration of indicator-EQR values which gives comparable EQR results because (a) the calibration process is straightforward and transparant, (b) the indicator-EQR results can be communicated very well to water managers and policy makers and (c) the unvariate calculations can be automated easily in the Dutch WFD ecology software QBWAT. We therefore chose to use the following univariate model for the BEQI-2:

EQR (ecotope) = 1/3 * [Sass / Sref] + 1/3 * [Hass / Href] + 1/3 * [(6 - AMBIass) / 6]

According to expert judgement (see Table 5), a Good/Moderate and High/Good

class boundary of 0.58 and 0.78, respectively, applied to untransformed national BEQI-2 EQR values, give realistic BEQI-2 classification results. However, in our national classification system we use equidistant class boundaries (High/Good boundary = 0.8, Good/Moderate boundary = 0.6, Moderate/Poor boundary = 0.4 and Poor/Bad boundary = 0.2) since all other Dutch WFD metrics also use these. Therefore, we will apply a linear transformation to our national class boundaries and national BEQI-2 EQR values, in order to be able to use these preferred equidistant class boundaries, as shown in Table 1 below. Since the national BEQI-2 EQR values will also be transformed, the BEQI-2 classification results will remain exactly the same as those intercalibrated.

Table 1: Intercalibrated, untransformed and transformed national BEQI-2 class boundaries.

Class boundary \/

BEQI-2 Intercal. PCMa

BEQI-2 National

Untransformed

BEQI-2 National

Transformed

High/Good 0.747 0.78 0.8

Good/Moderate 0.565 0.58 0.6

Moderate/Poor Not defined 0.38 0.4

Poor/Bad Not defined 0.18 0.2 a) PCM = pseudo common metric, the average scores of other metrics than BEQI-2

For the WFD, in the end a water body assessment is necessary. This can be achieved by combining the EQR-results of the different ecotopes in the water body using area based weight factors. All area within a water body must be represented and assessed by the ecotopes used. Example of combined WFD assessment of ecotopes:

EQR(waterbody) = i (EQRi * Area fraction i) i is ecotope number

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7.2 Comparison of BEQI-2 and m-AMBI using Westerschelde data pools

In order to check if the results of the simple BEQI-2 univariate calibration is comparable with the m-AMBI/BAT multivariate calibration, we performed two correlation studies: a. Comparison of BEQI-2 and m-AMBI EQR results for 1 set of Westerschelde data pools b. Comparison of BEQI-2 and m-AMBI EQR results for the ecotope-year averages of all data from the Common Dataset of the NEAGIG transitional water intercalibration. The results of these comparisons are given in this and the next Chapter. Comparison of BEQI-2 and m-AMBI EQR values for Westerschelde data pools For transitional waters, the BEQI-2 uses data pooling of small manual core samples (of approx. 0.015 m2) to an area of approx. 0.1 m2. Due to this procedure, strongly improved benthic signals and trend detection are obtained. Also, an averaging out of EQR differences between BEQI-2 and m-AMBI is obtained, as is demonstrated in Figure 6. The results of the comparative calculations of BEQI-2 and m-AMBI for 450 sample pools (from all Westerschelde ecotopes) of 0.1 m2 are shown in the figure below.

Figure 6: Comparison of BEQI-2 (on Y-axis) with m-AMBI (on X-axis) results for 450 sample pools of 0.1 m

2 from the

Westerschelde (all 4 ecotopes) R2 =

0.994.

The mean difference between the BEQI-2 and m-AMBI = -0.008; and R2 = 0.994. There is no difference between the correlation results for the 4 ecotopes. These results show that comparability of EQR-results of BEQI-2 and m-AMBI using these data pools is very good. The BEQI-2 results are on average 0.008 lower than the m-AMBI results, and this difference can be considered small and negligible for the Westerschelde assessment.

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7.3 Comparison of BEQI-2 and m-AMBI using the NEAGIG dataset

For the Westerschelde data pools, a very good correlation between the BEQI-2 and m-AMBI is observed. However when BEQI-2 and m-AMBI are compared at the sample level for the complete NEAGIG database, a significant variation is observed between these two metrics. These variations are probably caused by the small sample sizes of the intertidal samples in the NEAGIG database. We hypothesized that these significant differences between the BEQI-2 and m-AMBI are averaged out at the data pool, ecotope and water body level, as demonstrated for the Westerschelde data pools.

We tested this EQR averaging out hypothesis by determining the correlations between BEQI-2 and m-AMBI waterbody-ecotope-year averages for all sample data in the NEAGIG dataset (approx. 6000 records). The correlation between these EQR-values is given for each water body separately in Figure 7. The following conclusions can be drawn from this figure and statistical numbers:

a. For most water bodies, the correlation between the BEQI-2 and m-AMBI for the ecotope-year averages is very good. b. For a few water bodies, such as the Elbe and Weser, two clusters can be discriminated which could be different ecotopes. It is expected that at the level of water body assessment, these differences between (assumed) ecotopes will be averaged out also. c. A few estuaries, such as the Bidassoa and the Mondego estuary show a little bit different behavior. These differences cannot be explained immediately, but possibly will become smaller if different ecotopes are averaged out in a water body assessment. d. If all the water body-ecotope-year averages are combined in 1 statistical analysis, the mean difference between the BEQI-2 and m-AMBI (determined with a paired t-test) is very small, -0.009, but significant p-value = 0.008. This means that BEQI-2 EQR-values are on average 0.009 lower than m-AMBI scores, which can be considered very small and negligible in the overall water body assessment. The overall R2 = 0.89.

In view of the very good comparability of the BEQI-2 and m-AMBI EQR-values at the average ecotope-year level at which the BEQI-2 operates, we choose to use the BEQI-2 univarate calibration considering the advantages described in Chapter 7.1. Figure 7: Correlation of BEQI-2 and m-AMBI for ecotope-year values for the NEAGIG database. Lines indicate a perfect correlation.

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8. Pressure-Impact Analysis

8.1 Qualitative pressure-impact analysis

The WFD demands that the correct performance of selected indicators and metrics is demonstrated using quantitative pressure-impact correlations. In these pressure-impact correlations, all significant pressures have to be taken into account, because in large marine water bodies, also in the Netherlands, usually a multi-pressure situation exists. A nice example of how such a quantitative multi pressure-impact correlation can be performed is the pressure-index method of Borja et al. (2011). In this method, the intensity of specific pressures is scaled from 1 (low pressure), 2 (moderate pressure) and 3 (high pressure) or blank (no pressure), and an average pressure index of the significant pressures is calculated. From this study it appears that diversity indicators, such as species richness, Shannon, Margalef and ES50 show a fairly good correlation with human pressures as quantified with the pressure index (Borja et al., 2011) in five different types of estuaries in Western Europe. These results suggest that the mentioned diversity indicators are probably also useful and sufficiently reliable as human pressure indicators in Dutch estuaries (Boon et al. 2011).

As a first step a qualitative pressure-impact analysis is performed as follows: a. A qualitative description of the human pressures in the Westerschelde and Eems Dollard estuary is give. This description is based on the official Dutch WFD characterization documents for these water bodies (Maas, 2009; Anoniem, 2009) which have been supplemented with expert judgement. b. The observed diversity indicator trends (especially the Shannon index (Borja et al., 2011) are used as sufficiently reliable indicators for human pressure trends. c. Observed trends for AMBI, AMBI-sedimentation and AMBI-fisheries are checked for their correspondence with the diversity trends. If an AMBI trend does not correlate with a diversity trend, it is considered not sufficiently reliable.

8.2 Qualitative description of human pressures

Westerschelde In the WFD document for the Westerschelde a pressure list is added (Table 3.5 I in Maas, 2009) for the current situation. For each listed pressure, it is indicated if this pressure is present, and if this pressure is substantial or small. The following signicant pressures are reported in this document:

Chemical pressures: atmospheric deposition; transborder transport of PAHs, Cu, Zn and Nitrogen. Especially in the mesohaline part of the Westerschelde, these chemical pressures are expected to be larger than in the polyhaline part.

Physical pressures: dams and dykes for flood defence; maintainance of dams, dykes and coastlines; dredging and dumping; sand suppletion. Apart from to the death of benthic organisms which are removed or fully covered by sand; dredging, dumping and suppletion lead to an increased sedimentation of sand and mud on benthic organisms in the area nearby the dredging/dumping/suppletion area.

Fisheries are probably a minor pressure in the Westerschelde. In the Western part of the polyhaline zone, fishing is prohibited because of the nearby lying Natura 2000 area (the `Vlakte van Raan`).

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Dollard Macrozoobenthos has been routinely monitored in the Dollard, a major part of the Eems Dollard, for two about decades.

The following significant pressures have been reported in the Eems Dollard WFD report:

Chemical pressures: these are among others presented by a large sewage plant, 23 industrial waste water plants, dredging sludge related pollution, shipping related pollution (oil and anti-fouling) and atmospheric deposition. In the last years the chemical pressures on the Eems Dollard appear to increase. In 2006 a good chemical status was reported, while in 2007 and 2008 a bad status was reported. WFD measures to improve the chemical water quality of the Eems Dollard have been planned.

Dredging and dumping: in view of many shipping activities a lot of dredging occurs, and dumping is performed at 11 locations in the Eems Dollard. The dumped sludge is rapidly dispersed in the Eems Dollard because of the high flow velocities. According to Jager (personal communication, 2011) the sludge dumping site `Groote Gat`, and recently a new dumping site, lead to signicant sedimentation in the Dollard region. It is therefore clear that there is a relatively high sedimentation pressure in the Dollard. According to the WFD document, the effects of the high concentrations of suspended matter on the benhos are not yet clear. WFD measures have been planned to reduce the amount of suspended matter and turbidity.

Hydromorphological pressures: the deepening of the shipping gully in the NederEems has led to a shift of salinity zones and a smaller brackish zone. This has led to a reduction of corresponding native brackish benthic communities.

Sand extraction for industrial use. This can locally damage or remove the benthos.

Fisheries (personal communications from Zwannette Jager and Dick As, 2011). Dutch shrimp fisheries were performed occasionally in the past in summer and autum in the gullies and at the borders of the tidal flats, but not on the tidal flats themselves. Therefore, since the Dollard bentos sampling was performed on the tidal flats (Heringsplaat, it is unlikely that effects of the shrimp fisheries on the benthos would be detected in the benthos monitoring. The Dutch shrimp fisheries in the Dollard have been terminated a couple of years ago as a nature compensation measure for the new Groningen seaports. German shrimp and mussel fishers are still active in the German part of the Dollard, but probably also only in the gully and at the borders of the tidal flats and not at the Heringsplaat. In conclusion, it is unlikely that fisheries represents a significant pressure on the benthos at the Heringsplaat tidal flat.

8.3 Quantitative pressure-impact analysis in the Dutch Westerschelde ecotopes Mesohaline-Intertidal and Polyhaline-Subtidal

Summary The pressure sentitivity of the BEQI-2 indicators and metric design, which is very comparable with the m-AMBI, has already been demonstrated in, at present, quite a number of publications (Borja et al., 2011). These qualitative pressure analysis, and quantitative trend analysis presented above, already make it very probable that the BEQI-2 is sensitive to human pressures in the expected way. However, the European Commision expects that member countries also validate the pressure sensitivity of their metric in their own water bodies with a quantitative pressure impact analysis. It has been agreed on in the NEAGIG benthos group that this quantitative pressure validation gives the best results at the water body/ecotope level, and therefore must be performed at this specific level. The setup of this pressure validation for the Westerschelde is described below.

For the marine benthos IC in TW, Joao Neto (Portugal) developed a quantitative pressure score list based on the publication of Aubrey & Elliot 2006. In this score list, pressures not relevant for benthos have been omitted. The results of this pressure index will be reported by Borja and co-workers.

As a next step, in this paragraph a more detailed look is given at two ecotopes in which a significant EQR trend has been found, namely the Mesohaline-Intertidal and the

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Polyhaline-Subtidal. Since it is important for the intercalibration process to demonstrate quantitative pressure-impact relationships, this was attempted for these two ecotopes.

For the Mesohaline-Intertidal ecotope, significant quantitative pressure-impact (EQR) relationships have been found for the parameters Dissolved Oxygen and Dissolved Inorganic Nitrogen (DIN). In the Polyhaline-Subtidal, a significant correlation has been found between the percentage of high dynamic literoral ecotope and the EQR. Westerschelde Mesohaline-Intertidal For the Westerschelde mesohaline-intertidal ecotope, a positive benthos quality trend has been found (see Figure 10). It is assumed that this positive trend is mainly associated with improved physic-chemical and/or chemical conditions, since at these relatively high intertidal sampling sites the hydromorphological are pressures are probably relatively low, as compared to the subtidal part.

Therefore, several chemical and physic-chemical trends were investigated for the location Schaar van Ouden Doel, which lies at the border of the Netherlands and Belgium, and can be regarded as a good indicator for the input of chemicals and physico-chemical parameters in the Mesohaline-Intertidal ecotope, because it is located at the starting point of this ecotope.

Figure 8: EQR trend for benthos in the ecotope Mesohaline-Intertidal using BEQI-2. Slope = 0.0107, r = 0.569, significance p = 0.00040.

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Priority pollutant pressures For the period of 1990-2005, the compounds which exceeded the WFD quality standards (annual average or MAC) more than 3 times were selected. These compounds are: Diuron (13 exceedings), Pentachlorobenzene (7 exceedings) and Cadmium (8 exceedings). The concentrations of these 3 compounds are plotted for the period 1990-2005 in Figures 9a, b and c.

Figure 9a: Concentration of Cadmium at Schaar van Ouden Doel

Cadmium shows a peak concentration and 1998, and furthermore an increasing trend in the period from 2000 to 2005.

Figure 9b: Concentration of Pentachlorobenzene at Schaar van Ouden Doel

Pentachlorobenzene shows a decreasing trend in the period of 2000 to 2005.

Figure 9c: Concentration of Diuron at Schaar van Ouden Doel.

Diuron shows a decreasing trend in the period from 2000 to 2005.

It appears that no consistent trends of priority pollutants can be observed based on these 3 compounds. Cadmium concentrations appear to be increasing in the period from 2000 to 2005, while the concentrations of diuron and pentachlorobenzene are decreasing in that period. In the period of 1990 to 2000, the concentrations of diuron and pentachlorobenzene are relatively high and exceed the EQS. Therefore, these trends of priority pollutants do not correlate with the general picture of benthic EQR improvement in the period of 1990 to 2005. According to several benthic experts in the Netherlands, heavy metals and organic micropollutants (with the exception of Tributyl Tin) are unlikely to cause significant effects on the quality of the benthic communities, because the amount of bioaccumulation is relatively

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low at this low level of the food chain and macrozoobenthos usually live relatively short and therefore toxic effects are unlikely to occur at the concentrations occurring in the Westerschelde. The results shown above correspond with this expert knowledge. Physico-chemical pressures For the physic-chemical data, for the indicator Oxygen (summer values) and DIN (Dissolved Inorganic Nitrogen, winter values) significant trends were found for the correlation between these physic-chemical parameters and the EQR for the Mesohaline-Intertidal ecotope.

For dissolved oxygen (see Figure 10), the importance of this parameter for the benthic quality is well known: decreased oxygen concentrations have a direct impact on the benthic quality. The correlation r = 0.586 and the correlation is significant (p = 0.017).

Figure 10: Correlation between Dissolved Oxygen (measured at Schaar van Ouden Doel; summer values) and benthos EQR for the ecotope Mesohaline-Intertidal. Slope = 0.066, r = 0.586, significance p = 0.017. This analysis was initially made using 99/1 percentile reference values.

For Dissolved Inorganic Nitrogen (DIN), the correlation (see Figure 11) with bentic quality seems intuitively logical but the mechanism of action is probably less clear cut. In principle, lower DIN concentrations leads to lower amount of eutriphication, and consequently may lead to less fytoplankton detritus and less oxygen consumption. Furthermore, it is possible that DIN could correlate with the concentration of detritus in general (and consequently the biological oxygen demand in the water column) but this hypothesis should be tested further.

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Figure 11: Correlation between DIN (measured at Schaar van Ouden Doel) and benthos EQR for the ecotope Mesohaline-Intertidal. Significance p = 0.0010.

Hydrological pressures It is assumed that the hydrological pressures (maximum flow velocity) are relatively low in the Mesohaline-Intertidal, in view of the relatively high location in the intertidal resulting in relatively short overflow times. According to Dick de Jong of RWS Zeeland, the amount of low dynamic intertidal area has increased in the past decades in the Mesohaline-Intertidal, indicating a lower maximum flow velocity. This possible decrease of hydrogical pressures could also partly explain the improvement of the benthic quality in this ecotope. These hydrological pressures are discussed in more detail for the following Polyhaline-Subtidal ecotope. Westerschelde Polyhaline-Subtidal In this ecotope, a significant negative quality trend has been found, see Figure 12. It appears that especially in 1994, 2002 and 2004 remarkable dips in the benthos quality occur, with a relatively stable period of the benthic quality from 1996 till 2001. Oxygen/DIN pressures This ecotope is situated in the Western part of the Westerschelde, near the North Sea. Conse-quently, in the polyhaline ecotopes the priority pollutants and nutrients are in principle more diluted than in the mesohaline ecotopes. An illustration of this dilution effect is given in the table below: Table 4: dilution effect of DIN in the Westerschelde

Location DIN 1990 [mg/L]

Schaar van Ouden Doel (start of mesohaline) 7.97

Hanswert (end of mesohaline) 3.98

Terneuzen (start of polyhaline) 2.46

Vlissingen (end of polyhaline) 1.07

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If the DIN data for the locations Terneuzen and Vlissingen are studied in more detail, the following table can be made: Table 5: trends of DIN at two locations in the Westerschelde

Location/year 1989 1990 1991 2009 2010 2011

DIN [mg/L] Terneuzen

3.05 2.46 1.66 1.99 1.62 1.75

DIN [mg/L] Vlissingen

1.50 1.07 0.76 1.05 0.93 0.97

It appears that the DIN has dropped strongly in the beginning of the 90s, among others due a different habour sludge disposal regime and the implementation of sewage purification plants. Afterwords, the DIN seems to have stabilized in this polyhaline ecotope and is presumably limited by diffuse and marine inputs. When the DIN concentrations from e.g. 1991 are compared with Figure 11, it seems quite likely that these DIN concentrations, and probably correlated dissolved oxygen content, will not be a limiting factor for the quality of the benthos. Furthermore, the apparent decrease of DIN in the beginning of the 90s should have caused an improvement of the benthic EQR, while a benthic deterioration has been measured in that period. Both arguments suggest that DIN and oxygen are probably not determining pressures in this ecotope. Priority pollutants pressures Related to this dilution effect for nutrients, the concentrations of priority pollutants are even less likely to cause negative effects on the benthos quality, since priority pollutants probably are not correlated to the improvement of the benthic EQR in the Mesohaline-Intertidal.

This then leaves physical pressures, especially hydrological and related salinity pressures, as the most likely causes of the significant negative quality trend which is observed in this ecotope. According to several experts, fisheries is not a significant physical pressure in the Westerschelde.

Figure 12: EQR trend for benthos in the ecotope Polyhaline-Subtidal using BEQI-2. Correlation coefficient = -0.632; Significance p = 0.0087.

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Hydrological pressures The occurance of hydrological pressures has been discussed with Dick de Jong, hydromorphological and ecological expert of RWS in the Delta area. According to the Marine Ecotope Classification system (Bouma et al., 2005), developed by RWS for the Delta marine waters (including the Westerschelde), the maximum flow velocity is a very important ecotope factor. Benthos can live well in ecotopes with relatively low maximum flow velocities (preferably

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9. Validation of BEQI-2 with expert judgement

In Table 6 a comparison is given of expert judgement of several Dutch marine water bodies compared with BEQI-2 EQR-values and classifications. A similar method was used for the Dutch WFD background document for fytoplankton (Van den Berg & Pot, 2007). Table 5: expert judgement of several Dutch marine water bodies and untransformed national BEQI-2 EQR values. Table 6: Expert judgement of the BEQI-2 classifications. The expert judgements were given without prior knowledge of the BEQI-2 scores. Expert > Water body \/

RD DdJ BEQI-2 EQR

BEQI-2 Class

a

Distance from G/M boundary

Westerschelde Mesohaline-Intertidal

Good 0.68 Good +0.1

Westerschelde Polyhaline-Subtidal

Slightly moderate

0.49 Moderate -0.09

Eems Dollard Moderate 0.48 Moderate -0.1

Waddenzee Reasonable 0.655 Good +0.075

Coastal zone

a) A Good/Moderate boundary of 0.58 is proposed for BEQI-2 based on this expert judgement b) Expert judgement on the coastal zone has to be added in near future.

We still have to find an independent marine benthos scientist to give a blind expert

judgement on the benthic quality of the Dutch coastal zone. Since the coastal zone five WFD water bodies are distinguished (Zeeuwse kust, Noordelijke Deltakust, Hollandse Kust, Waddenkust and Eems Dollard kust), and since there is a lack of clear quantitative pressure data in these regions, it is probably not an easy task to give an expert judgement on the benthic quality of these regions. In the Marine Strategy project and other RWS marine projects, new efforts are currently made to quantify human pressures on the open coastal waters and this will probably also improve our knowledge of the pressures and the benthic quality of the coastal WFD waters discussed here. However, since we already have expert judgement on three important Dutch transitional and coastal water bodies, we trust that the G/M class border of 0.58 is realistic and will not be influenced by additional expert judgement on the coastal waters.

See Chapter 5.1 for information on the use a linearly transformed national BEQI-2 class borders and EQR values.

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10. References

Anoniem, Brondocument t.b.v. KRW beheerplan waterlichaam overgangswater Eems-Dollard, 26 november 2009, RWS Waterdienst in collaboration with the German water authorities, in Dutch and German. Anonymous, Guidance on the Intercalibration Process 2008-2011, ReportEcostat,version 7.0, 18 nov 2009. Anonymous, 2008, WFD intercalibration technical report, Part 3 Coastal and Transitional Waters, Section 2 Benthic Invertabrates, EU report. Anonymous, Ecostat, IC Guidance Annex V: Definition of comparability criteria for setting class boundaries, version 5.0, 14 sept 2010. Anoniem, 2007, MER Verruiming Vaargeul, www.VNSC.eu. Aurelie Aubry, M. Elliott, The use of environmental integrative indicators to assess seabed disturbance in estuaries and coasts: Application to the Humber Estuary, UK, Marine Pollution Bulletin 53 (2006) 175185 E. van den Bergh et al., Studierapport natuurontwikkelingsmaatregelen ten behoeve van de Ontwikkelingsschets 2010 voor het Schelde-estuarium, Hoofdstuk 2. Ecologische doelen voor het Schelde-estuarium, Werkdocument/RIKZ/OS/2003.825x, in Dutch. A. Boon, A. Gittenberger and W.M.G.M. van Loon, Review of marine benthic indicators and metrics for the WFD and design of an optimized BEQI, Report, Deltares, 2011. A. Borja & J. Mader, 2006, Instructions for the use of the AMBI Index software (version 4.0), manual. A. Borja et al., Response of single benthic metrics and multi-metric methods to anthropogenic pressure gradients, in five distinct European coastal and transitional ecosystems, Marine Pollution Bulletin, 2011. A. Borja and B.G. Tunberg, Assessing benthic health in stressed subtropical estuaries, eastern Florida, USA using AMBI and M-AMBI, Ecological indicators 11 (2011) 295-303. H. Bouma, D.J. de Jong, F. Twisk and K. Wolfstein, A Dutch Ecotope System for Coastal Waters (ZES.1), Report RIKZ/2005.024. A. Gittenberger and W.M.G.M. van Loon, A list of common marine benthic species in the Netherlands, Report & Database, 2011. G. Van Hoey, J. Drent, T. Ysebaert and P. Herman, 2007, The Benthic Ecosystem Quality Index (BEQI), intercalibration and assessment of Dutch coastal and transitional waters for the Water Framework Directive, Final report, NIOO. H. Maas, Brondocument Westerschelde, RWS Waterdienst, 2009 (in Dutch). G. Spronk, 1994. Invloed van slibontrekking Beneden Zeeschelde op de waterkwaliteit op de Belgisch-Nederlandse grens. Report, RIKZ/AB/94.883X.

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Appendix 1: BEQI-2 results for the Dollard

Since the Dollard data are not an official part of the intercalibration process, they are briefly reported in this appendix as additional and supportive information for the Westerschelde results.

Benthos data have been collected by drs. R. Dekker and co-workers from the NIOZ (Netherlands Institute for Sea Research) from 1991 until now, and represent a consistently sampled and analyzed benthos dataset.

In the analyzed period of 1991 2007, 2040 samples were taken in the ecotope Mesohaline-Intertidal in the Dollard region; 1020 in spring and 1020 in autumn. The sample sizes are as follows: 1745 samples of 0.009 m2; 249 samples of 0.018 m2 and 2040 of 0.027 m2. These samples are all located on three transects; transect codes HERPT1110, HERPT1111 and HERPT1112 (HERPT = Heringplaat; an intertidal sandflat).

Reference values for the Dollard ecotope Mesohaline-Intertidal were taken from the Westerschelde Mesohaline-Intertidal ecotope. It is a Dutch WFD principle to use the same reference values per national water type, in this case O2 (Overgangswater, Transitional water). Since the autumn benthos data are preferred for the BEQI-2 assessment, the autumn reference values of the Westerschelde Mesohaline-Intertidal ecotope are suitable to apply to the autumn benthos data of the Dollard Mesohaline-Intertidal ecotope. Table 7: reference values used for the Dollard, obtained from the Westerschelde Mesohaline-Intertidal-Autumn.

Ecotope Season S ref S bad H ref H bad AMBI ref

AMBI bad

Mesohaline-Intertidal

Autumn 29.26 0 3.269 0 0 6

The trends of S, H and AMBI are shown in Figure 12 and Table 8. It appears very

cleary that for Species Richness and AMBI indicators signifcant negative quality trends are observed in both seasons. For Shannon a quality decrease can be observed but is not significant. In autumn a nearly significant BEQI-2 quality trend (p = 0.10) is observed. The signficance of the autumn trend is slightly larger than for the spring trend, which confirms the choice to use autumn data for the BEQI-2 assessment. These results show that the benthic quality of the Dollard region appears to be declining. This correlates with the pressure information from the Dutch Eems Dollard water body brondocument (Anoniem, 2009). Table 8: Significant indicator trends observed in the Dollard region, ecotope Mesohaline-Intertidal, Autumn samples. The trends for spring samples are similar.

Water body Ecotope Season Indicator Slope p value

Eems Dollarda Mesohaline-Intertidal Autumn AMBI 0.0101 0.00085

Mesohaline-Intertidal Autumn AMBI review 0.00812 0.0085

Mesohaline-Intertidal Autumn AMBI sediment. -0.0055 0.013

Mesohaline-Intertidal Autumn AMBI fisheries -0.037 0.000017

Mesohaline-Intertidal Autumn ITI 0.0168 0.000075