Macroalgae and phytoplankton as indicators of ... - Naturstyrelsen

More documents

Recommendations

Info

Table 3.2 Overview of functional groups (Steneck & Dethiers 1994) and our grouping of late-successional and opportunistic species in the present study. *Microalgae and crustose algae are not represented in the present study and therefore not included in our grouping. Functional group Examples of algal genus Grouping in this study 1. Microalgae (single cell)* Cyanobacteria and diatoms 2. Filamentous algae (uniseriate) Cladophora, Bangia 2.5 Filamentous and thinly corticated algae Polysiphonia, Ceramium, Sphacelaria Opportunists 3. Foliose algae (single layer) Monostroma, Ulva, Porphyra Opportunists 3.5 Foliose algae (corticated) Dictyota, Padina Opportunists 4. Corticated macrophytes Chondrus, Gigartina Late-successionals 5. Leathery macrophytes Laminaria, Fucus, Halidrys Late-successionals 6. Articulated calcareous algae Corallina, Halimeda Late-successionals 7. Crustose algae* Lithothamnion, Peyssonnelia, Ralfsia We analysed six algal variables: Total cover represented the diver estimates of total erect macroalgal cover for each sub-sample, which represented values in the range 0-100%. Cumulated cover was calculated by summing the cover values of all erect macroalgal species in each subsample. Cumulated cover values could surpass 100%, because algae can grow in several layers. The remaining algal variables to be analysed were related to the composition of the macroalgal community. Cumulated cover of opportunistic algae was calculated as the summed cover of all algal species belonging to functional groups 1-3, and cumulated cover of late-successional algae was calculated as the summed cover of algae belonging to algal groups 4-6. Relative cover of opportunistic algae was finally calculated by dividing the cumulated cover of opportunists by the cumulated cover of all species and therefore provided data in the range 0-100%. Finally, the number of late-successional algal species in each subsample was calculated as the total number of the species belonging to this group and having a cover of at least 1%. All algal variables were tested for responses to physico-chemical gradients and, thus, for their potential as indicators of water quality according to the WFD. 3.3.2 Substratum Composition of substratum was registered along with the collection of algal data. Divers visually recorded the total cover of suitable hard substratum as well as the cover of various substratum classes: size classes of stones, sand, mud and shells. Data on cover of suitable hard substratum were extracted from the database together with each algal data set. 3.3.3 Physico-chemical variables Spatial variations in algal variables were related to the physico-chemical variables salinity, nutrient concentration, chlorophyll concentration and Secchi depth. These data were sampled at sites situated in the vicinity of vegetation sites. The water chemistry sites were typically located centrally in the investigated coastal areas or sub-areas, and generally 2 or more algal sites/depth gradients were related to the same water chemistry site. 22
We assumed that mean values from the various algal sites would represent the algae of a given coastal area and that the centrally located water chemistry site would represent the physical conditions and water chemistry of the same coastal area in spite of some distance between macroalgal and water chemistry sites. Water chemistry data were collected by the Danish counties and stored in NERI's database. Sampling and chemical analysis were performed according to common guidelines (Andersen et al. 2004) and typically represented a sampling frequency between weekly and monthly sampling. 3.3.4 Statistical analyses of algal variables Algal model We focused the analysis exclusively on algae from the depth range where disturbance was no longer a major controlling factor for cover (see Figure 3.2). The coastward end of this depth range was estimated as the water depth with highest algal cover using non-parametric adjustment (LOESS, Cleveland 1979). This adjustment was made separately for each area and showed that the areas could be categorised in weakly exposed areas where maximum cover was located at water depths of ~1 m, moderately exposed areas with maximum cover at water depths of ~3 m and highly exposed areas with maximum cover at water depths of ~5 m (Carstensen et al. 2005). As a consequence, we restricted the analysis to water depths >1 m in weakly exposed areas, >3 m in moderately exposed areas and >5 m in highly exposed areas. Only few (122) observations represented water depths >13 m at 6 specific localities (Bornholm West and East, North of Zealand, Hesselø and Little Belt, Northern Belt Sea) and we therefore restricted the analysis to water depths
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: Table 3.1 Overview of sampling area
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 and 46: Figure 3.8 continued Cumulated cove
Page 47 and 48: inputs (Figures 3.9 and 3.10) where
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 80 and 81:
Page 82 and 83:
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
show all

Macroalgae and phytoplankton as indicators of ... - Naturstyrelsen

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?