Macroalgae and phytoplankton as indicators of ... - Naturstyrelsen

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3.4.5 Reference levels and class borders sensu WFD for macroalgal variables For each of the estuaries/coastal areas we entered the TN-levels defining reference levels and class boundaries (Table 2.4 in chapter 2) and annual mean salinities (shown in Figure 3.7G) in the empirical relationships (defined in Table 3.9). We thereby calculated the level of algal variables defining reference conditions and class boundaries (Appendices 1-6). The level of the boundaries, the variability associated with them and the width of the status classes differ widely between variables and between areas. The applicability of the algal variables for assessment of water quality thus also varies between variables and areas. In order for an algal variable to be applicable for assessment of ecological status, the class borders should be defined with low variability and the status class bands should be relatively broad. This demand was best fulfilled for the variables which were associated with a low degree of stochastic variability and a strong response to changes in TN concentrations. The variables 'total cover', and 'number of late-successional species' generally showed relatively low stochastic variability and a strong response to TN concentration at high salinities so these indicators had class borders with relatively low variability in high salinity areas (Table 3.6). The 'fraction of opportunists' also had relatively limited stochastic variability with weak responses to changing TN concentrations at high salinities. So class borders of this variable generally showed high variability and narrow status class bands in high salinity areas. By contrast, in low salinity areas where responses to TN were stronger, class borders were defined with less variability. The cumulated algal cover variables were associated with more stochastic variability than the algal variables mentioned above and therefore tended to have class borders connected with relatively large variability. The response of TN concentration to changes in TN loading in a given area also affects the width of the status class. Thus, areas which demonstrate a strong response in TN upon changes in N-loading, i.e. areas having a large regression slope for the regression of TN-concentration upon TN-input (chapter 2, Figure 2.6) have broader status class bands than areas showing a weak response to TN inputs. Many open areas, such as Bornholm, show weak responses in TN to changing TN inputs and, therefore, have narrow status class bands. By contrast, areas with significant nutrient sources and low water exchange such as inner Odense Fjord, several Limfjord basins, Randers and Nissum Fjords show strong responses in TN concentration to changes in TN inputs and therefore have broader status class bands. The demand for the indicators to have low stochastic variability and high sensitivity to TN is intensified if the area in question has narrow status class bands for TN. For the Sound, Nivå Bay, Limfjorden west of Mors and Roskilde Fjord we have illustrated the class boundaries and their associated variability together with actual levels of the algal indicators (Figures 3.9 - 3.12). These figures illustrate that status class bands are narrow in the Sound and Nivå Bay – areas with a weak response of TN concentrations to TN 44
inputs (Figures 3.9 and 3.10) whereas they are much broader in Limfjorden west of Mors and Roskilde Fjord – areas with a strong response of TN concentration to TN inputs (Figures 3.11 and 3.12). All cover indicators have been estimated to a standard depth of 7 m for comparison across areas. This depth standardisation will reduce the indicator precision for those sites with few data around 7 m, and in such cases it will be more appropriate to choose a standardisation depth representing an average depth for the area. The figures also illustrate that along the open coasts of the Sound and Nivå Bay, status class bands of total cover were close to 100% and all very narrow. This is because total cover levels are potentially high in the open areas and often reach the upper boundary of 100%. Therefore, future modelling of total cover levels and class boundaries for open coastal areas should represent a water depth of 9 m where light limitation is more intense and where cover levels consequently are lower than at a depth of 7 m. In Limfjorden west of Mors status class boundaries were well separated for all variables except for the fraction of opportunists (Figure 3.11). The narrow status class bands for the fraction of opportunists in this area are due to the high salinities which weaken the response of the fraction of opportunists to TN (Figure 3.8). For the Sound and Nivå Bay, the mean levels of the algal indicators for the years 2001-2005 typically fell within the status class 'bad'. The relatively low TN levels of the Sound thus give expectations of higher levels of algal cover and numbers of perennial species and lower fractions of opportunists than found. Based on the Swedish macrophyte index, the ecological status of the northern Sound is assessed as moderate (http://www.viss.lst.se/; district= Södra Östersjön, vattenkategori=Kust; Öresund). 45
Page 1 and 2: National Environmental Research Ins
Page 3 and 4: National Environmental Research Ins
Page 5 and 6: Contents Summary 5 Sammenfatning 6
Page 7 and 8: Summary During the implementation o
Page 9 and 10: 1 Introduction This report is part
Page 11 and 12: Figure 2.1 Long-term trends in nitr
Page 13 and 14: Figure 2.2 Surface TN versus salini
Page 15 and 16: 2.2.2 Nitrogen input-TN relationshi
Page 17 and 18: Flensborg Fjord on the ranked scale
Page 19 and 20: Table 2.4 Suggested reference condi
Page 21 and 22: the gradient. These responses have
Page 23 and 24: Table 3.1 Overview of sampling area
Page 25 and 26: We assumed that mean values from th
Page 27 and 28: and 2005), averaged over the months
Page 29 and 30: The second component of the Spanish
Page 31 and 32: The variance of a macroalgae indica
Page 33 and 34: The levels of mean cumulated algal
Page 35 and 36: Figur 3.5 continued Modelled mean l
Page 37 and 38: while the fraction of opportunists
Page 39 and 40: 3.4.2 Physico-chemical variables Ph
Page 41 and 42: Figure 3.7 continued Mean modelled
Page 43 and 44: 3.4.3 Algal variables in relation t
Page 45: Figure 3.8 continued Cumulated cove
Page 49 and 50: A Total algal cover (%) 100 95 90 8
Page 51 and 52: A 100 B 140 Total algal cover (%) 8
Page 53 and 54: A response to changes in nutrient c
Page 55 and 56: In its present form the Spanish ind
Page 57 and 58: 3.6 Conclusions • All algal varia
Page 59 and 60: gime shift after changing the sluic
Page 61 and 62: Figure 4.3 Estimated site-specific
Page 63 and 64: from Randers Fjord and Odense Fjord
Page 65 and 66: moderate boundaries. Reference dept
Page 67 and 68: 4.3 Evaluation of the precision of
Page 69 and 70: The 90-percentile was clearly subst
Page 71 and 72: 5 Conclusions and recommendations R
Page 73 and 74: 6 References Andersen, J., Markager
Page 75: Nielsen, S.L., Sand-Jensen, K., Bor
Page 78 and 79: 76 Appendix 1. Reference levels and
Page 84 and 85: Appendix 7. Modelled mean levels of
Page 86 and 87: Appendix 9. Modelled mean levels of
Page 88 and 89: Appendix 11. Modelled mean levels o
Page 90 and 91: Appendix 13. Results of power analy
Page 92 and 93: Appendix 18. Results of power analy
Page 94 and 95: NERI Technical Reports NERI’s web
Page 96:
of Danish coastal waters 683 Macroa
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Macroalgae and phytoplankton as indicators of ... - Naturstyrelsen

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