Primary Production by Macroalgae in Kattegat, Estimated from Monitoring Data, Seaﬂoor Properties, and Model Simulations

ARTICLE IN PRESS Continental Shelf Research 26 (2006) 2415–2432 www.elsevier.com/locate/csr Primary production by macroalgae in Kattegat, estimated from monitoring data, seafloor properties, and model simulations Jo¨ rgen O¨ bergÃ Department of Oceanography, Earth Sciences Centre, Go¨teborg University, P.O. Box 460, S-405 30 Go¨teborg, Sweden Received 3 April 2005; received in revised form 29 June 2006; accepted 12 July 2006 Available online 12 September 2006 Abstract The aim of the study was to estimate yearly macroalgal production in the Kattegat. The estimate was calculated from the abundance and distribution of nine of the most dominant macroalgal species, and from factors important for abundance, distribution and growth (e.g. bottom topography and sediment composition, irradiance, nitrogen concentrations and seawater temperature). The result showed that 6.6% of the Kattegat area is suitable for macroalgal growth. The estimated production was 4–514 g C mÀ2 yearÀ1 depending on depth and sub-area. The total yearly production was estimated to 119 Â 106 kg C yÀ1. r 2006 Elsevier Ltd. All rights reserved. Keywords: Biomass; Environmental monitoring; Macroalgal growth model; Phytobenthos; Primary production; Sediment properties; Solid substrates; Europe; Scandinavia; Kattegat 1. Introduction been made (L. Edler, p. comm.; I. Wallentinus, p. comm.). A figure of 1 g C mÀ2 yÀ1 for the average The sea of Kattegat between Sweden and Den- benthic primary production in Kattegat was men- mark has approximately one third of its seafloor tioned by Borum and Sand-Jensen (1996) but the within the photic zone. This should render the underlying data, based on microalgal production in benthic primary production in Kattegat a relatively a limited area (Graneli and Sundba¨ ck, 1986), cannot high importance. Still, existing primary production be considered as being representative for the entire studies in Kattegat (e.g. Rydberg et al., 2006; Kattegat. Carstensen et al., 2003; Richardson and Heilmann, Kattegat is a small shallow sea (area 21 600 km2, 1995; Heilmann et al., 1994; Richardson and mean depth 24 m), situated between Denmark and Christoffersen, 1991) are focused on the pelagic Sweden in the transitional zone between the production, whereas a comprehensive study of the brackish Baltic Sea and the marine North Sea benthic production in Kattegat has hitherto not (Fig. 1). The scatter diagram (Fig. 2) from the open sea monitoring station Fladen (Fig. 1, no. 10) shows ÃTel.: +46 31 773 2859; fax: +46 31 773 2888. the large annual variation in salinity and tempera- E-mail address: [email protected]. ture in the photic zone of Kattegat. The summer 0278-4343/$ - see front matter r 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.csr.2006.07.005 ARTICLE IN PRESS 2416 J. O¨berg / Continental Shelf Research 26 (2006) 2415–2432 temperature can be even higher in sheltered areas. The tidal amplitude in the area is generally small, about 0.2 m in the south-western part and less in the east. The bottom topography of Kattegat shows a pronounced shelf in the northwest, with depths usually less than 20 m. Steep, rocky shores are found on the northern and southern end of the eastern coast, but the seafloor is otherwise more gently sloping. A few islands, and a number of mid-sea banks, provide substrates within the photic zone also in the central part of Kattegat. With a decreased salinity such as in Kattegat, the number of macroalgal species is lower, which chiefly affects the non-dominant species Fig. 1. Map of the Kattegat area, showing the bathymetry as well (Middelboe et al., 1997). Further, reduced salinity as the positions of the sampling locations. often means a reduction in size of the macroalgae (Lu¨ ning, 1990). The main growth season of macroalgae is in spring and early summer, extending into early autumn especially for ephemeral annual macroalgae. Low light and water temperature inhibits growth in winter. The internal nutrient reserves of the macroalgae, replenished in winter, enable the rapid growth in spring to continue into summer in spite of the reduction of dissolved nutrient concen- tration caused by the phytoplankton spring bloom (Dring, 1982). When the internal reserves are depleted, growth continues at a rate determined by the external conditions. Blades shed by macroalgae during growth, and plants torn off by wave action, are decomposed in the detritus food web. Grazing may cause a large loss of biomass in some areas, but has only a small effect in others. In the absence of limpets, Littorina spp. are the main grazers of macroalgae in the littoral zone along the Swedish west coast (Cervin and A˚berg, 1997), whereas sea urchins are the main grazers in the sub-littoral zone (Lu¨ ning, 1990). However, also crustaceans such as the isopods Idotea spp. may be important (Pavia et al., 1999). Mathematical modelling is a useful tool to obtain quantitative data of objects or phenomena when actual measurements are unavailable, to investigate the functioning of an ecosystem, or when a prediction of the future development is desired. Regarding macroalgae, recent examples of model use for the two latter reasons include simulations of the development of a single opportunistic macroalgal species (Ruesink and Collado-Vides, 2006; de Guimaraens et al., 2005; Martins and Marques, Fig. 2. Salinity (upper panel) and temperature (lower panel) 2002), and ecosystem models simulating the coex- observations at Fladen in central Kattegat during 1994–1996. istence of macroalgae of different functional groups ARTICLE IN PRESS J. O¨berg / Continental Shelf Research 26 (2006) 2415–2432 2417 (Biber et al., 2004), of macroalgae and benthic 2. Material and methods phanerogams (Giusti and Marsili-Libelli, 2005), or of macroalgae and plankton (Tanaka and Mack- 2.1. Coverage and biomass of various macroalgae enzie, 2005; Trancoso et al., 2005; Baird et al., 2003). In this study, a single-species model was used The benthic macrophytes in Kattegat have been to estimate yearly production for a number of monitored at coastal and offshore stations by the representative macroalgal species. Danish National Environmental Research Institute The aim of this study was to estimate from (NERI) and by the Halland and Ska˚ne county existing data the macroalgal contribution to the administrations. The monitoring frequency varies; total primary production in Kattegat. This re- some sites are visited every year, while others quired information on the amount and location of have been visited only once during the last decade. macroalgal presence, as well as of the species Table 1 lists the depths, years, measured variables distribution and productivity. As macroalgae only and coordinates of the monitoring stations used in grow in the photic zone, mostly attached to a solid the present study. The positions of the stations are substratum, information on depth distribution and shown in Fig. 1. All macroalgal monitoring was sediment structure was also needed to obtain a made in summer through visual inspection by divers fair description of the spatial distribution of along transects down to a maximum depth of 20 m. locations suitable for brown and red macro- The assembled coverage, defined as the share of algae. The distribution of green macroalgae was suitable hard substrate covered with macroalgae treated differently. As these macroalgae often (Krause-Jensen et al., 2001), was recorded at all appear aggregated into floating mats, the descrip- sites. The macroalgal coverage was found by tion was focussed on the availability of shallow and projecting the macroalgal thalli vertically onto the sheltered areas. seafloor, thereby estimating the proportion of Most of the publicly available Kattegat macro- substrate covered. The estimations were made algal monitoring data from the last decade was used for three replicate areas in depth segments of in this study. Ideally, all of these data would include usually 1 m vertical extension. At the S and W biomass determinations. Equally important for the sides of Kattegat, the current method of NERI productivity calculations would be estimates of (Krause-Jensen et al., 2001) was used. The results macroalgal annual productivity made in the area from these stations (Anon., 2005), as well as from or under Kattegat-like conditions. Neither of these the three most southerly Swedish stations (Anon., conditions was met for this study. Only a minority 2001), were given as figures (0–100%) of total of the macroalgal monitoring data contained aggregated coverage by all macroalgal species on biomass information. Instead, a majority of the suitable substrates. The remaining reports from the monitoring efforts were concerned with macroalgal Swedish coast (Carlson, 1996; Lundgren and coverage estimations. Through the availability of Olsson, 2001; Olsson, 2001) all used the previous simultaneous measurements of both biomass and NERI method (Krause-Jensen et al., 1995), where coverage at some stations, a relationship was the estimates are given in five categories (0–2%; established to convert the coverage data at the 2–25%; 25–50%; 50–75%; 75–100%) of the aggre- other stations to biomass figures. The lack of area- gated coverage. At these stations, the biomass specific annual productivity measurements made (g dwt mÀ2) of the occurring macroalgae, estimated model simulations a suitable alternative to obtain from manually collected samples, was also reported yearly production to biomass ratios. The simula- (Fig. 3). tions were made with an adapted version of the A selection of macroalgal species must include the macroalgal growth model by O¨ berg (2005) for nine most common species in the area. To ascertain of the most common species of macroalgae in representativity, the choice should also embrace the Kattegat. The biomass estimations and the yearly major functional groups (Littler, 1980), as otherwise productivity calculations were combined with in- highly productive annuals might have to stand back formation on the topography and sediment struc- for abundant, but less productive, perennial species ture of the Kattegat seafloor to estimate the with a high standing stock.

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