Eutrophication effects on a coastal macrophyte community in the Bothnian Sea
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Eutrophication effects on a
coastal macrophyte
community in the Bothnian
Sea
Effekter av övergödning på ett
makrofytsamhället i en grund vik i
Bottenhavet
Emilia Linder Wiktorsson
Bachelor thesis, 15 ECTS
Bachelor of Science in Biology and Earthscience, 180 ECTS
Spring term 2021Abstract
Eutrophication is a major concern in the Baltic Sea and it is affecting macrophyte
communities by promoting the growth of opportunistic algae and decreasing the cover
of perennial macrophyte species via shading. It is however uncertain how common
eutrophication and its symptoms are in the northern parts of the Baltic Sea, the
Botnian Sea. The aim of this study was to evaluate if Sörleviken, a bay in the Bothnian
Sea, show signs of increased eutrophication pressure in 2020 compared to 2007 based
on changes in macrophyte cover and composition. The macrophyte community was
inventoried with under-water video techniques in 2020 along three transects, matching
transects previously inventoried by a diver in 2007. The three transects were located in
the inner, middle and the outer parts of the bay. The results showed that macrophyte
diversity was lower in 2020 than in 2007 along the outer transect, but overall, the total
cover of macrophytes, relative cover of opportunistic algae, species richness and
evenness remained unchanged. A possible higher presence of Stuckenia pectinata
(former Potamogeton pectinatus) and a possible lower presence of Chara aspera in
2o2o compared to 2007 might be evidence of higher eutrophication pressure in 2020.
However, by observing the general changes in the macrophyte community, this study
only provides weak or inconclusive signs of increased eutrophication pressure, thus
Sörleviken shows no signs of either improvement of or further increases in
eutrophication pressure by 2020 compared to the observations in 2007.
Key words: eutrophication, macrophytes, opportunistic algae, Baltic Sea, Bothnian
Sea
Bachelor thesis, 15 ECTS
Bachelor of Science in Biology and Earthscience, 180 ECTS
Spring term 2021Table of content
1 Introduction ........................................................................................................................ 1
1.1 Background ............................................................................................................... 1
1.2 Aim and hypothesis ..................................................................................................2
2 Method .................................................................................................................................3
2.1 Site description .........................................................................................................3
2.2 Data collection ..........................................................................................................3
2.3 Collection of macrophytes and identification .........................................................4
2.4 Analyzing footage ..................................................................................................... 5
2.5 Statistical analysis .................................................................................................... 5
3 Results ..................................................................................................................................6
3.1 Macrophyte cover .....................................................................................................6
3.2 Macrophyte composition ........................................................................................ 8
3.3 Depth comparison .................................................................................................. 11
4 Discussion ......................................................................................................................... 12
4.1 Conclusion............................................................................................................... 15
Acknowledgements ............................................................................................................ 15
5 References ......................................................................................................................... 15
Bachelor thesis, 15 ECTS
Bachelor of Science in Biology and Earthscience, 180 ECTS
Spring term 20211 Introduction
1.1 Background
Eutrophication, caused by the over-enrichment of nutrients, such as nitrogen and
phosphorous, has been an observed issue in the Baltic Sea for half a century (Bonsdorff 2021;
Lundberg, Jakobsson and Bonsdorff 2009). Anthropogenic activities, for example
agriculture, forestry and municipal sewage, have been major factors contributing to this
problem (Bonsdorff 2021). Even though nutrient loads from these sources have decreased
(Gustafsson et al. 2012), mainly through the establishment of sewage treatment plants
(Bonsdorff 2021; HELCOM 2018), the negative impact on aquatic ecosystems in the Baltic
Sea remains (Gustafsson et al. 2012; Rönnberg and Bonsdorff 2004). Enrichment of
nutrients has been linked to increased primary production in the pelagic. As a result, there is
now a widespread issue of hypoxia and anoxia in large offshore areas in the Baltic Sea (Cloern
2001). Hypoxia is also of major concern for benthic flora and fauna in coastal areas. In
addition, increasing productivity has, for example, led to increased sedimentation and higher
turbidity in coastal ecosystems, which have triggered changes in the macrophyte
communities established there (Cloern 2001).
Macrophytes are important in coastal ecosystems for several reasons. They are habitat
forming organisms providing shelter for fish, crustaceans and other organisms (Rinne et al.
2018) and they provide functions for important ecosystem services. Firstly, providing shelter
for the juveniles of commercially important fish stocks is an ecosystem service of great
importance to our society (Beaumont et al. 2008). Secondly, by stabilizing sediments in their
habitat, macrophytes decrease turbidity in coastal ecosystems and via a positive-feedback
loop, less suspended particles will allow increased light penetration which ultimately can
enable an increased cover of macrophytes (Austin et al. 2017). Thirdly, macrophytes are
important as primary producers in coastal ecosystems (Rinne et al. 2018) and they oxygenate
the benthic habitat (Viaroli et al. 1996). Furthermore, the cover of rooted macrophytes is
related to high ecosystem multifunctionality, i.e., how well an ecosystem can function and
perform necessary ecosystem processes, such as those mentioned above (Austin et al. 2021).
Due to the loss of macrophyte cover, eutrophication can thus have far-reaching implications
for other organisms, for whole ecosystems and for their services on which humans rely
(Austin et al. 2021).
Macrophyte communities in coastal habitats are affected by eutrophication in multiple ways.
For instance, perennial macrophyte species (e.g. Charophytes) have been shown to decline
with increasing concentrations of phosphorous (Blindow 2000; Hansen 2012). Increased
amounts of nutrients have also been found to reduce species diversity of macrophytes (Torn
and Martin 2012). However, filamentous, fast-growing ephemeral algae (henceforth called
opportunistic algae) benefit from eutrophication owing to their ability to quickly utilize a
surplus of available nutrients (Steneck and Dethier 1994). Therefore, an indirect effect of
eutrophication is light competition between opportunistic algae and other perennial
macrophytes where the latter decrease in abundance and distribution due to shading by the
opportunistic algae (Krause-Jensen et al. 2008; Rinne et al. 2018). Also, the increase in
phytoplankton biomass, in response to elevated nutrient loads, adds to the shading of
perennial macrophytes (Cloern 2001).
Within the EU’s Water Framework Directive (WFD), aquatic macrophytes are used as one of
the biological components for assessing the status of water bodies (Penning et al. 2008).
Many research studies and governmental agencies within the EU, assessing the health of
coastal ecosystems, therefore use macrophyte abundance and composition as indicators of
eutrophication pressure (Albertsson 2014; Swedish Environmental Protection Agency 2000;
Torn and Martin 2012). Different responses to indirect effects of eutrophication (e.g. light
limitation), where some species are tolerant to such effects and other species are more
1sensitive, allows for composition of perennial macrophyte species to be used when evaluating
the eutrophic condition on a temporal scale (Hansen and Snickars 2014; Blindow et al. 2016).
On the one hand, empirical evidence shows that macrophyte abundance and composition are
robust indicators for the health of an aquatic ecosystem regarding how affected it is by
eutrophication (Krause-Jensen et al. 2018). On the other hand, relative abundance of
opportunistic algae could not be attributed to eutrophication alone (Rinne, Salovius-Laurén
and Mattila 2011). For instance, macrophyte abundance and composition are, in some
instances, influenced to a greater extent by geomorphological factors and salinity rather than
by eutrophication parameters (light and nutrients) (Torn and Martin 2012).
The sub-basins of the Baltic Sea are affected by eutrophication to varying degrees, with the
greatest effects in the Baltic Proper and the Gulf of Finland. One of the least affected sub-
basins is the Bothnian Sea (HELCOM 2018) and studies over the past two decades have only
shown ambiguous signs of eutrophication in the Bothnian Sea (Rönnberg and Bonsdorff
2004, Lundberg, Jakobsson and Bonsdorff 2009, HELCOM 2018). Currently, eutrophication
in the northern Baltic Sea appears to be more of a local than a widespread problem, mainly
due to point sources of nutrients to coastal ecosystems (Rönnberg and Bonsdorff). However,
issues that might appear in the future are increasing appearances of harmful algal blooms in
offshore areas and issues with increased amounts of opportunistic algae along the coast
(Rönnberg and Bonsdorff 2004). Increasing efforts are required to evaluate eutrophication
pressure in the Bothnian Sea to understand ecosystem responses and hopefully to prevent a
wide-spread issue of eutrophication in the northern Baltic Sea.
This study is a part of a collaborative project, between Länsstyrelsen Västernorrland, SWECO
and researchers at Umeå University (Jenny Ask) and the Swedish University of Agricultural
Science (Magnus Huss) aimed to restore the eutrophic conditions in Sörleviken, a bay in the
northwest Baltic Sea. An assessment of the bay was performed in 2007 concluding that it was
in poor health (Länsstyrelsen Västernorrland 2008) and in 2019 it was suggested that
eutrophication symptoms were mainly due to nearby agriculture and summer housing
(Rocksén et al. 2019). Owing to the crucial role of macrophyte abundance and diversity for a
healthy coastal ecosystem, this project is not just important for the health of the macrophyte
community itself, but also for the other organisms within the ecosystem relying on vegetation
for spawning, shelter and as a food resource. Furthermore, on a larger scale this collaborative
project is an attempt to combat local eutrophication in the Bothnian Sea and to fill the
knowledge gap regarding the eutrophication pressures in the northern Baltic Sea. Monitoring
and evaluation are imperative measures taken to see if restoration efforts have been
successful over time. This study will provide valuable insight into how the macrophyte
community have changed since 2007, but also information of the current, pre-restoration
macrophyte community in Sörleviken.
1.2 Aim and hypothesis
The aim of this study is to compare the cover and composition of macrophytes between 2007
and 2020 and to evaluate if the bay has experienced any significant changes during this
period. Since Sörleviken was suffering from eutrophication symptoms already in 2007, the
main hypothesis is that Sörleviken would show signs of increased levels of stress in 2020
compared to 2007 as a result of increased negative impact on the ecosystem caused by
eutrophication. Based on previous studies of macrophytes’ community responses to
eutrophication, it is expected that 1) the cover of macrophytes should have decreased in 2020
due to higher nutrient levels and less available light (Krause-Jensen et al. 2008), 2) the total,
as well as the proportional, cover of opportunistic algae should have increased since 2007 in
response to nutrient over-enrichment (Steneck and Dethier 1994, Rinne et al. 2018) and 3)
diversity and richness of macrophytes should have decreased due to increased levels of
nutrients (Torn and Martin 2021). Finally, a hypothesis for a within-year comparison where
the parameters total cover of macrophytes and relative cover of opportunistic algae are
compared between the shallow part of the bay and the deep parts of the bay. The hypothesis
2is that 4) a loss in total cover of macrophytes and an increase of opportunistic algae cover
should be apparent between shallow and deep parts of the transects since light limitation
lowers the total cover of macrophytes (Krause-Jensen, Carstensen and Dahl 2007). This
should enable the establishment of opportunistic algae, thus increasing opportunistic algae
cover where light is a limiting factor.
2 Method
2.1 Site description
Sörleviken is located in Kramfors municipality, Västernorrland, Sweden. It is a shallow,
long and narrow bay of 51.0 ha in Gaviksfjärden, Bothnian Sea. The bay is surrounded
by two steep sides, a hillslope of agricultural land on one side and a mountain wall on
the other side. The catchment area (21.0 km2) of the bay is dominated by agricultural
land and forests. In 2007, the macrophyte community (here including both aquatic
vascular plants and macroalgae) was dominated by Potamogeton perfoliatus and by
Vaucheria spp. Sedimentation is high in all parts of the bay and there is a large
abundance of opportunistic algae. Furthermore, according to the Water Framework
Directive (WFD) classifications, both the ecological quality status (EQS) and the
chemical potential for Sörleviken basin was deemed as poor in 2007 (Viss 2021).
Hence, this bay has shown signs of eutrophication for more than a decade.
Figure 1. Map of the inventoried transects in Sörleviken. Red lines are dive inventories performed in 2007.
White lines are drop-video inventories and yellow lines are ROV inventories, both conducted in 2020
(Google maps 2021).
2.2 Data collection
In 2007, an inventory of macrophytes (here including aquatic vascular plants and
macroalgae) was performed by the company Tång och Sånt (Vallentuna, Stockholm)
upon a request from Västernorrland county. It was conducted following the Swedish
Environmental Protection Agency’s (EPA) standard marine inventory (Swedish
Environmental Protection Agency 2004). This inventory was carried out by scuba
divers diving along three transects, TR 23, TR 22 and TR 21 (Länsstyrelsen
Västernorrland 2008). These transect will henceforth be referred to as “inner dive
2007”, “middle dive 2007” and “outer dive 2007” respectively. Coordinates, compass
direction, temperature, salinity and secchi depth was noted for each transect (table 1).
Observations were made regarding macrophyte cover and composition along the
3transects including at what depth and distance from the shore the cover and
composition changed. Macrophytes were identified to genus or species. Crustaceans
and molluscs were also noted during the dive, but that data was not considered in this
study. Raw data from that inventory was accessed via the Swedish Meteorological and
Hydrological Institute, SMHI (SMHI 2021).
To investigate the current macrophyte community two inventories of macrophyte cover
(%) and composition were conducted by filming transects matching the dive inventory
performed in 2007 (figure 1). In the beginning of September 2020, a drop-video
inventory was performed which collected footage of the bottom of the bay. This was
conducted along three transects (inner drop-video 2020, middle drop-video 2020 and
outer drop-video 2020). The location of the outer drop-video transect was not a perfect
match to the outer dive transect from 2007 since it was located further inside the bay
(figure 1). Additionally, all three drop-video transects are lacking the immediate shore
due to inaccessibility of the camera. The camera construction used for the drop-video
was custom made at Umeå Marine Science Center (Hörnefors, Sweden). It consisted of
two cameras (GoPro Hero 5), one filmed downwards and one camera filmed forwards.
The camera construction, which was attached to a small boat, was lowered slowly and
then positioned close to the bottom of the bay before the inventory begun. At the start
of the filming, depth, direction, time and the coordinates were noted (table 1). The boat
was slowly driven in the given direction and the cameras’ distance from the bottom was
manually controlled. At the end of the transect, coordinates, time and depth were noted
again. A coordinate was also noted in the middle of the transect. The outermost
transect was filmed in two parts due to a problem with the boat engine.
The second video inventory was performed in the end of September in 2020. Footage
was obtained by a Remotely Operated Vehicle (ROV), model Aegir 25, manufactured by
Ocean Robotics. The ROV also had two cameras, one filming downwards and one
filming forwards. An operator controlled the vehicle and filming started at the shore
continuing outwards in a direction matching the dive inventory from 2007 (table 1).
This procedure was conducted along two transects (middle ROV 2020 and outer ROV
2020) (figure 1). Coordinates and depth from the beginning and end of the transects
were obtained from the video-footage (table 1). The ROV was unable to operate at the
shallow inner part of the bay, and consequently there is no ROV transect matching the
inner dive transect from 2007. Furthermore, there is a slight deviation of the
coordinates from the middle dive 2007 transect and the middle ROV 2020 transect due
to faulty coordinates from the dive inventory.
Table 1. Transect information for the inventories in 2007 and 2020.
42.3 Collection of macrophytes and identification In addition to filming, macrophytes were collected from a small boat with a rake along the inner, the middle and the two different outer transects. The rake was 2m long and could only sample the shallower parts of the transects. Coordinates and depths were noted at the points where the rake was pushed down and then dragged along the bottom for 1.0m. Samples were collected at three points along the inner and middle transects, and at two points for the two outer transects. Macrophytes stuck to the rake were collected for identification. In the lab, the macrophytes were identified using key literature for algae in the Baltic Sea (Tolstoj 2007). The rake sampling was mainly performed to get acquainted with the macrophyte species and to determine if there were species along the transects which were difficult or impossible to discover or identify on the drop-video and ROV footage. 2.4 Analyzing footage The data obtained by drop-video and the ROV were analyzed on a computer. Macrophytes were identified to species level using algae literature for the Baltic Sea (Tolstoj 2007) or deemed as unidentifiable and referred to as “unidentifiable opportunistic algae”. Observations were made of species cover (%) and compositions following the EPA:s standard marine inventory for macrophytes, i.e. similar to the method used by Västernorrlands county in 2007 (Länsstyrelsen Västernorrland 2008). Abundance was estimated by assessing the cover (%) of a species based on a 7-grade scale, 1 % for single individuals and thereafter 5, 10, 25, 50, 75 or 100 %. The total estimation along a depth gradient can exceed 100%. Whenever the cover of a species or the community structure changed, depth was noted and thereby depth intervals were created with different species cover and composition. Depth intervals without vegetation made up their own depth intervals labeled “absent vegetation”. Footage from the forward-facing cameras were not analyzed. 2.5 Statistical analysis Macrophytes were divided into two groups to statistically analyze the difference in total and relative cover of opportunistic algae (%) between the years 2007 and 2020. The two groups were called late successional species (including aquatic vascular plants such as Myriophyllum sibiricum and erect algae such Chara aspera) and opportunistic algae (including foliose and filamentous algae such as Vaucheria spp.). This division was based on Steneck and Dethiers’ (1994) grouping of algae where group 2 and 3 partly represent fast growing (opportunistic) algae which are benefitted by increased nutrient input (Rinne et al 2018). Even though some algae were unidentified, they were included in the group of opportunistic algae since they matched best with the description of group 2 and 3 in Steneck and Dethier (1994). Additionally, these unidentifiable opportunistic algae were unidentifiable due to the similarity of species within certain genuses, for example Vaucheria and Glomerata, which are both included in group 2 or 3 based on morphology. The depth difference along the inner dive 2007 and the inner drop-video 2020 transects was less than 2.0m and therefore the transects were analyzed without dividing them into a shallow and a deep part. The depth difference exceeded 2.0m for the outer dive 2007 transect and the outer ROV 2020 transect. Hence, the outer transects were divided into a shallow and a deep part so that differences in depth could be assessed and excluded as a potential source of error. Preferably, the division between shallow and deep should have been at the secchi depth of 5.5m measured for the outer transect in 2007, but this would have made the statistical analysis of the deep part impossible due to too few values (n1
The three middle transects were excluded from all statistical analysis due to the low number of sample values (n1
a b
)
Figure 2. Cumulative cover (%) of macrophyte species for each depth interval (a) along the inner dive
transect in 2007 and (b) along the inner drop-video (DV) transects in 2020. Shades of green are aquatic
vascular plants and shades of blue are opportunistic algae. The lines represent the bottom profile with
average depth (m) for each depth interval.
The middle transects were not statistically analyzed. When visually analyzing, at least
the middle ROV 2020 and the middle drop-video 2020 transect seem to show that
cumulative cover of macrophytes decline with increasing depth. The total cover of
macrophytes varied greatly between the two video inventories in 2020. Total
macrophyte cover was close to 0% below 2.0m along the middle ROV 2020 transect
and along the middle drop-video 2020 transect below 2.0m it varied between 20-120%.
The relative cover of opportunistic algae seems to be very low along both middle
transects in 2020. The opportunistic algae cover and relative cover of opportunistic
algae in 2007 along the middle transect appeared to be higher than in 2020.
Opportunistic algae cover was high and dominated most depth intervals along the outer
ROV 2020 transect and in 2007, opportunistic algae cover only reached 10% below
7.5m (figure 3).
7Figure 3. Cumulative cover (%) of macrophyte species for each depth interval (a) along the middle dive
transect in 2007, along the middle ROV transect in 2020 and (c) along the middle drop-video (DV)
transect in 2020. Shades of green are aquatic vascular plants and shades of blue are opportunistic algae.
The lines represent the bottom profile with average depth (m) for each depth interval.
Neither total cover of macrophytes, cover of opportunistic algae nor relative cover of
opportunistic algae were significantly different (p>0.05 two-tailed Mann-Whitney U-
test) when comparing median values in 2007 to median values in 2020 along the outer
transects (table 2). The outer drop-video 2020 transect was not included in the
analysis.
3.2 Macrophyte composition
The total number of taxa per entire transect varied between 4 and 12 species. In 2007, 9
late successional and 4 opportunistic species were observed collectively for all three
transects. In 2020, 8 late successional and 1 opportunistic species were observed along
all 6 transects. Although the highest species richness (12) was observed along the outer
transect in 2007 and the lowest species richness (4) was observed along the outer
transect in 2020 (figure 4), richness was marginally not significantly different when
comparing median values. There were no detectable differences in richness along the
inner transects.
8Figure 4. Cumulative cover (%) of macrophyte species for each depth interval (a) along the outer dive
transect in 2007, (b) along the outer ROV transect in 2020 and (c) along the outer drop-video transect in
2020. Note, the outer drop-video (DV) transect is located further inside the bay than the other two
transects. Shades of green are aquatic vascular plants, shades of grey are Charales, shades of yellow are
brown algae and shades of blue are opportunistic algae. The lines represent the bottom profile with average
depth (m) for each depth interval.
Six types of macrophytes (vascular plants, aquatic vascular plants, Charales, red algae,
brown algae and yellow-green algae) were collectively observed in the inventories
during both years (table 3). However, the vascular plant Phragmites australis is of no
relevance to this study since it is not a submerged aquatic plant. The same applies to
the red algae Hildenbrandia rubra since it is a highly tolerant, often deep-living
crustose perennial algae (Kim and Garbary 2006). The different opportunistic species
were unfortunately impossible to separate between in the video inventories in 2020.
During the dive inventory in 2007, identification was possible at least down to genera
(Vaucheria spp.) or grouping of two very similar opportunists (Ectocarpus/Pylaiella).
The filamentous algae Dictyosiphon foeniculaceus was identified down to species and
only observed along the outer transect in 2007 (figure 4).
9Table 2. Results from the Mann-Whitney U-test comparing transects in 2007 to transects in 2020 showing the U-value, critical U-value (p
Table 3. A list of all identified species along transects in both 2007 and 2020 and from the rake sampling in
2020. Species in bold were only found during the dive inventories in 2007. Explanations: *opportunist,
+late successional algae, ◌ vascular plant, Δ brown algae, ●Charales, † red algae and □yellow-green algae.
The median Shannon-Wiener Diversity Index varied between 0.00 and 0.96 and
Shannon-Wiener evenness varied between 1.00 and 0.00 along the analyzed transects
(table 2). The median species diversity was higher (0.96) in the shallow part of the
outer dive 2007 transect than in the shallow part of the outer ROV 2020 transect (0.12)
(table 2). Shannon-Wiener evenness was not different when comparing medians in
2007 to medians in 2020 along any of the transects (table 2).
3.3 Depth comparison
The total macrophyte cover along the shallow part of the outer dive 2007 transect
(18%) was higher than the total macrophyte cover along the deep part of the outer dive
2007 transect (2%) (table 4). This difference was not found in 2020. The depth
variation along transects is greatest for the outer dive 2007 and outer ROV 2020
transects where the depth varies between 0.0-8.0m and 0.5-9.3m respectively.
However, when visually analyzing, there is a possible negative trend between total
macrophyte cover and depth along the middle transects in 2020 (figure 3) and along all
outer transects (figure 4).
11Table 4. Results from the Mann-Whitney U-test comparing total macrophyte cover and cover of
opportunistic algae between the shallow and the deep part of the outer transect in 2007 and 2020.
Showing the U-value, critical U-value (50% cover), whereas opportunistic algae only were observed and
dominating in one out of seven depth intervals along the inner drop-video 2020 transect.
Depth is probably not a limiting factor of consideration for the inner transects since the
maximum depth was only 2.5m. One explanation for the possible lower dominance of
opportunists could therefore be an improvement of water quality reducing the spread of
opportunistic algae furthest inside the bay (Krause-Jensen et al. 2008).
The middle transects were not statistically analyzed but, a similar, yet less pronounced, trend
of lower occurrence of opportunistic algae was visible along the middle transects.
Opportunistic algae are present in fewer depth intervals in 2020 than in 2007 (figure 3),
suggesting a recline in their cover between 2007 and 2020. Such a decline could be a possible
sign of decreased nutrient concentrations and less eutrophication symptoms. Additionally,
the cumulative cover of macrophytes in 2020 appears higher than in 2007. An increase in
cumulative cover of macrophytes is an indicator of decreased pressure from eutrophication
(Krause-Jensen, Carstensen and Dahl 2007; Hansen and Snickars 2014). However, an
increase in total cover of macrophytes is not always the result of an increased cover of
perennial macrophytes, but rather the result of an increased cover of opportunistic algae.
Therefore, total cover of macrophytes alone is not a reliable sign of less eutrophication
pressures (Rinne et al. 2018). Since visual determination suggested that opportunistic cover
had decreased between 2007 and 2020, a potential increase in total macrophyte cover since
122007 would indicate an increased cover in perennial macrophytes favored by e.g. lowered eutrophication stress along the middle transects. The relative cover of opportunistic algae can however be unreliable when used as indicators of eutrophication. Many studies have shown that changes in the abundance of opportunistic algae are caused by changes in salinity and not necessarily by eutrophication parameters such as light and nutrients (Krause-Jensen, Carstensen and Dahl 2007; Krause-Jensen et al 2008). This is a study with large temporal differences and during the time-frame of 13 years, salinity could have changed, but such effects are not reflected in the results due to the lack of difference in opportunistic cover between 2007 and 2020. Additionally, there could be a bias concerning the predicted response of fast growth by opportunistic algae at enhanced levels of nutrients in brackish water if the species have been studied in their optimal environment, i.e. either fresh-water or marine environments (Krause-Jensen et al. 2008). A suboptimal salinity in the brackish water of the Baltic Sea could limit the growth response and thus allow for higher nutrient concentrations without the suggested increase in relative cover of opportunistic algal species. The results from the inventory of macrophyte composition showed a reduced macrophyte diversity for the shallow part (
concentrations of phosphorous (Blindow 2001). Thus, the lack of observed Charales (C.
aspera and T. nidifica) in 2020 compared to the presence in 2007 along the shallow part of
the outer most transect might be indicative of a more turbid environment and could be a sign
of increased phosphorous concentrations. An alternate explanation rather than a decreased
light condition is that both C. aspera and T. nidifica are small in stature (Blindow et al. 2016)
and could therefore have been missed among the stretches of larger perennial macrophytes,
e.g. M. sibiricum or P. perfoliatus, in the video footage in 2020. Supporting this is the
findings of C. aspera in the rake samples in 2020 (table 3). However, a diver could also have
missed observing Charales in dense macrophyte forests.
Along the shallow part of the outer dive 2007 transect, Charales and other perennial
macrophytes benefitted from low eutrophic pressure, and dominated the depth intervals
(figure 4). Perennial species were replaced along the shallow part of the outer ROV 2020
transect by opportunistic algae species which, in 2020, dominated the depth intervals. Such a
shift in species composition might suggest a more eutrophic condition since the replacement
of perennial algae with opportunistic algae is indicative of a poorer light climate (Krause-
Jensen et al. 2008; Rinne et al. 2018). Despite a risk that species diversity is lower in 2020,
along the outer transect, due to the grouping of several unknown opportunistic algae species
as one species, the shift in species observed between 2007 and 2020, still indicate a poorer
light availability which could be congruent with increased eutrophication pressure.
The presence of F. vesiculosus in 2020 and the absence of this species in 2007 could have
indicated a less eutrophic ecosystem in Sörleviken because F. vesiculosus can decline due to
indirect effects of eutrophication, such as increased turbidity (Berger et al. 2004). The outer
drop-video 2020 transect is located further inside the bay than the outer dive 2007 transect,
hence comparison is not valid and the presence of F. vesiculosus in 2020 is probably due to a
harder substrate along the transect where it was observed. The presence of S. pectinata along
the inner and middle transects in 2020, especially the higher cover along the inner drop-
video 2020 transect, compared to the absence of S. pectinata along the corresponding
transects in 2007 (figure 2), could be indicative of higher nutrient concentrations in 2020
(Blindow et al. 2016). This change in species composition could thus indicate a more
eutrophic condition in the inner and middle parts of the bay. Still, S. pectinata has not
unambiguously been proven to be a macrophyte species tolerant to increased eutrophication
stress (Hansen and Snickars 2014). There are two other species, C. filum and Z. palustris,
absent from the inventory in 2020 which were present the inventory in 2007 (table 3).
Nonetheless, these species are not represented with high enough cover to suggest possible
trends towards a more or less eutrophic ecosystem and no studies were found discussing the
importance of these species in such context. Additionally, both C. filum and Z. palustris were
collected in the rake sample in 2020, proving that they are not completely absent in 2020.
The total cover of macrophytes along the shallow part (3.6m). A lower cover in deeper waters
coincides with the fact that macrophytes have different depth limits (Rinne et al. 2018). The
relative abundance of opportunistic algae was not different when comparing the shallow and
deep part of the outer dive 2007 transect. This could suggest that even though the total
macrophyte cover decrease with depth, the opportunistic algae did not outcompete the
perennial macrophytes when the light was limited for both groups. A surprising result was
that, in 2020, the total macrophyte cover was not different between the shallow part (3.7m) along the outermost transect. The secchi depth should be
somewhat similar to that in 2007 and it is unfortunate that this data is lacking. A reason for a
significant difference in 2007, but not in 2020, could be that the dive transect in 2007
include more of the shallow (less light limited) habitat since it started at 0.0m and the ROV
transect in 2020 only begun at 0.6m.
Different methods were used in 2007 and 2020 and changing the method for the inventories
can have an impact on the results. However, replacing a diver can also impact the results and
14be a factor affecting the identification of species and the estimation of cover. Thus, the use of
different methods does not necessarily represent a big issue here. On the other hand, species
that were absent in the drop-video and ROV inventories in 2020 were present in the rake
sampling performed in 2020 which could indicate a difficulty in identifying smaller
macrophytes from a video footage. Such information is important to keep in mind for future
studies conducted via video inventory. Furthermore, the data set in this study would likely
have required a more complicated statistical analysis to identify any possible differences
(Albertsson 2014). Studies investigating the difference in biological indicators between one
year compared to another can find changes in these indicator parameters related to other
factors than the one studied (HELCOM 2018). In this instance, yearly variations in physical
factors such as prolonged ice-cover and wave exposure can impact macrophyte cover and
composition to a greater extent than eutrophication parameters such as light and nutrient
concentration (Hansen and Snickars 2014; Blindow et al. 2016). Data from 4-5 years would
be sufficient to link changes in macrophyte community to light and nutrient rather than to
wave exposure and ice-cover in studies analyzing temporal changes in eutrophication
pressure (Hansen and Snickars 2014).
4.1 Conclusion
This study found no solid evidence of a more deteriorated ecosystem in 2020 compared to
2007 based on the macrophyte community. The inner and middle parts of Sörleviken showed
no increase in any of the observed parameters and does therefore reject all hypotheses
indicating that there are no clear signs of a more eutrophic ecosystem in 2020 compared to
2007. The study found no evidence of an improvement either, which leads to the conclusion
that the inner and middle part of Sörleviken is suffering from eutrophication to the same
extent in 2020 as it did in 2007. The macrophyte community in the outer part of the bay
could be slightly more affected by increased eutrophication pressure, with the observed
decrease in species diversity in 2020 compared to 2007. No other evidence of increased
eutrophication was found and the eutrophication effects on the macrophyte community,
already observed in 2007, have thus not improved in 2020 along the outer part of Sörleviken
either. Owing to the importance of the macrophyte community for the whole ecosystem, the
observations of no improvements and the continuous eutrophication effects in Sörleviken
should therefore be taken seriously as it is evidence of long-term and local eutrophication in
the Bothnian Sea.
Acknowledgements
First and foremost, I want to thank my supervisor Jenny Ask for guidance and support
throughout this project and for giving me the opportunity to work on such an
interesting subject. I also want to thank Umeå Marine Science center and my fellow
students Mattias Melin and Douglas Skarp who performed the field work on my
account. And lastly, many thanks to my friends and family who have encouraged me
during the process of this bachelor thesis.
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