Plants & Ecology/PlantsEcology_2008_5.pdf · 2012-01-16 · Plants & Ecology Plant Ecology 2008/5...
Transcript of Plants & Ecology/PlantsEcology_2008_5.pdf · 2012-01-16 · Plants & Ecology Plant Ecology 2008/5...
Effects of macrophyte morphology on the invertebrate fauna in the
Baltic Sea by
Josefin Sagerman
Plants & Ecology Plant Ecology 2008/5 Department of Botany Stockholm University
Effects of macrophyte morphology on the invertebrate fauna in the
Baltic Sea by
Josefin Sagerman
Supervisors: Sofia Wikström and Lena Kautsky
Plants & Ecology
Plant Ecology 2008/5 Department of Botany Stockholm University
Plants & Ecology Plant Ecology Department of Botany Stockholm University S-106 91 Stockholm Sweden © Plant Ecology ISSN 1651-9248 Printed by Solna Printcenter Cover: Macrophytes in a shallow Baltic Sea bay. Photo by Upplandsstiftelsen
Summary
The physical properties of habitats have a major influence on diversity and abundance of
invertebrates. A field experiment was conducted to investigate the effects of macrophyte
structural complexity on the plant-associated invertebrate fauna of shallow soft-bottoms in the
Baltic Sea. Three common macrophytes with different levels of structural complexity
(Myriophyllum spicatum, Chara baltica and Potamogeton perfoliatus) together with
resembling artificial plants were used. The macrophytes were planted in the sediment and left
to be colonized by invertebrates for two weeks. Perimeter and number of branches per area
was used as an estimate of habitat complexity. The complex artificial M. spicatum had a
higher number of taxa per sample than C. baltica and P. perfolitus. But among the natural
plants the simple P. perfolitus hade the highest taxon density. The invertebrate abundance per
macrophyte surface area was highest on the two complex natural plants. Among the artificial
plants the intermediate complex C. baltica had the highest abundance per surface area. The
results show that the structural morphology of aquatic plants impacts on the taxon density (the
number of species per unit) and the abundance of plant-associated invertebrates in the Baltic
Sea. It was however not possible to isolate the effect of morphological complexity from the
macrophyte surface area in relation to taxon density. Additionally, the result of taxon richness
compared with rarefaction curves suggests that macrophyte complexity does not affect the
number of taxa per sampled individuals. The study also demonstrates that macrophytes of
different morphological complexity accumulates different amount of entangled macrophytes
per surface area, which in turn may affect the abundance of invertebrates.
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Sammanfattning
De fysiska egenskaperna av ett habitat påverkar diversiteten och individtätheten av djur. För
att undersöka effekterna av vattenväxters morfologiska komplexitet på ryggradslösa djur i
grunda havsvikar i Östersjön utfördes ett fältexperiment. Tre vanligt förekommande
vattenväxter med olika strukturell komplexitet (axslinga Myriophyllum spicatum, grönsträfse
Chara baltica and ålnate Potamogeton perfoliatus) användes tillsammans med likartade
plastväxter. Makrofyterna planterades i bottensedimentet och lämnades i två veckor för att bli
koloniserade av djur. Omkrets och antal förgreningar per area användes som mått på
komplexitet. Av plastväxterna hade den komplexa axslingan högst antal arter per prov jämfört
med grönsträfse och ålnate. Men bland de naturliga växterna hade den strukturellt simpla
ålnaten högst artdensitet. Individtätheten per makrofytarea var högst på de två mest komplexa
naturliga växterna. Bland plastväxterna var det den medelkomplexa grönsträfsen som hade
högst individtäthet per area. Resultaten visar att den strukturella morfologin hos vattenväxter
påverkar arttätheten och individtätheten av ryggradslösa djur i Östersjön. Men det var inte
möjligt att isolera effekten av komplexitet från makrofytarea i avseende på artdensitet.
Resultatet av artrikedom jämfört med hjälp av rarefactionkurvor visar att
makrofytkomplexitet inte påverkar antalet arter per antal individer. Studien visar även att
vattenväxter med olika morfologi samlar på sig olika mängd fintrådiga alger och annat
drivande växtmaterial per area vilket i sin tur tycks påverka individtätheten av ryggradslösa
djur.
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Introduction Shallow soft-bottom bays of the Baltic Sea have a high diversity of submerged plant species
(e.g. Munsterhjelm 1997). The diverse plant communities constitute habitats of varying
morphology colonised by a high number of invertebrate taxa (Hansen et al. 2008). The
increased nutrient load in the Baltic Sea has resulted in changes in the benthic vegetation and
thereby the physical structure of these habitats (e.g. Kautsky et al. 1986; Munsterhjelm 2005).
The physical properties of habitats has a major influence on diversity (Jeffries 1993;
Rosenzweig 1995; Statzner & Moss 2004) and abundance of invertebrates (Jeffries 1993;
Gratwicke & Speight 2005) as intricate structures can increase the amount and range of
exploitable microhabitats (McNett & Rypstra 2000). Complex plant habitats have been shown
to mediate predator prey co-existence (Diehl 1988) and have also been suggested to provide a
better substrate for attaching invertebrates, protecting them from being washed away by
turbulent currents (Taniguchi et al. 2003). Habitat structure also affects the food supply
through detritus trapping (Rooke 1984). Hence, structurally complex habitats can be expected
to contain more species (Gratwicke and Speight 2005) and have higher faunal densities
compared to structurally simpler habitats (Xie et al. 2006).
The aim of this study is to investigate the effects of macrophyte structural complexity on the
abundance and diversity of the invertebrate fauna of shallow soft-bottoms of the Baltic Sea.
Three common macrophytes with different levels of structural complexity (Myriophyllum
spicatum L., Chara baltica Bruzelius and Potamogeton perfoliatus L.) were used together
with resembling artificial plants in a colonisation experiment in the field. These three plants
also differ in vulnerability to eutrophication. Charophytes are generally negatively affected by
eutrophic processes while P. perfoliatus and M. spicatum are more tolerant and can increase
in abundance with moderate eutrophication (Wallentinus 1979; Munsterhjelm 2005;
Henricson et al. 2006). Perimeter and number of branches per area was used as an estimate of
habitat complexity.
In the study the following hypotheses were tested: I) The abundance and diversity of aquatic
invertebrates is higher in a structurally more complex plant habitat than in a structurally
simple plant habitat. II) Structurally complex plants accumulate more detritus and drifting
filamentous algae than structurally simple plants. III) Invertebrate taxa react differently to the
structural complexity of aquatic plants.
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Four different fauna taxa were used to answer the third hypothesis; the marine isopod Idotea
chelipes Pallas, the marine amphipod Gammarus spp., the freshwater snail Theodoxus
fluviatilis L. and the insect larvae Chironomidae. These taxa were chosen as they represent
different taxonomical groups, were abundant in the samples and are typical for the shallow
soft-bottom bays of the Baltic Sea (Hansen et al. 2008).
Materials and methods
Study site
The experiment was conducted in July 2007 in two adjacent shallow soft-bottom bays,
Idkroken and Södra Flan (site A and B respectively), at Askö island (N58° 49’ E17° 38’; Fig.
1), located in the north-vestern Baltic proper. The Baltic Sea is a non-tidal inland sea, with
brackish water of a salinity ranging from 2 psu in the north to 8 psu in the south. The flora
and fauna contains of a unique mixture of freshwater and marine species that can withstand
the osmotic stress in this to many species critical salinity range (Zenkewich 1963). The study
area in the inner part of site A is a very sheltered shallow area (<1.5 m), with a macrophyte
community dominated by vascular plants and charophytes such as; Potamogeton pectinatus
L., M. spicatum and C. baltica. A bit further out in the bay there are dense patches of P.
perfoliatus mixed with large quantities of the brown alga Chorda filum Stackhouse. The
bottom substrate is a gradient of mud to sand. Site B is deeper (2.5 – 3 m) and more exposed.
C. baltica does not grow in this study site naturally, but the other two experimental species
are represented in the macrophyte flora. The vegetation at site B is dominated by loose laying
Fucus vesiculosus L., C. filum, P. pectinatus, P. perfoliatus and Zannichellia palustris L. The
bottom substrate consists of coarse sand. At the experimental sites the salinity was 6.1 psu,
the surface temperature 18 to 20°C and the level of dissolved oxygen >10 mg/L through out
the study period.
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Site A
Site B
Site A
Site B
Site A
Site B
Site A
Site B
Fig. 1. Map of the Baltic Sea (top left), Askö island (bottom left) and the two experimental sites; A and B (right side). The location of the experimental blocks in site A and B are indicated by “▲” (see text for details). Field experiment
The colonisation experiment was carried out in the field, using a randomized complete block
design. Each block consisted of a single replication of the experiment. An experimental
replicate was composed of six macrophyte patches; one of each treatment, situated
approximately 2 m apart. The treatments were natural M. spicatum, C. baltica, P. perfoliatus
and artificial plants with 3 levels of structural complexity, resembling the natural plants in
morphology (Fig. 2). The plants will hereafter be referred to as natural Myriophyllum, natural
Chara, natural Potamogeton, artificial Myriophyllum, artificial Chara and artificial
Potamogeton. A total of 96 samples in 16 blocks were placed out using SCUBA. The plants
were left for 2 weeks in the field to be colonized by fauna.
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Natural
Artificial
Myriophyllum Chara Potamogeton
Natural
Artificial
Myriophyllum Chara Potamogeton Fig. 2. Morphological features of tops and top segments of the natural and artificial macrophytes used in the study.
The natural plants used in the experiment were collected at the two study sites at 1 to 2 m
depth. Throughout the experimental preparations the plants were kept in oxygenated aquaria
with sand-filtered sea water at a temperature of approximately 17°C under 34 µEinstein light
conditions (under water), for a maximum of 5 days. Macroscopic epiphytes and plant-
associated fauna were carefully removed and the plant shoots were bundled together with
cable binders. The number of shoots per bundle varied slightly (5-8), but all bundles had a
combined length of approximately 130 cm each. Plastic aquarium plants, 30 cm of height,
with five to six shoots (depending on sort) consisting of one to four identical segments, where
acquired from the manufacturer Hagen (Montreal, Canada). The plastic plants were altered
through cutting, to resemble the three natural experimental macrophytes. The experimental
plants were attached to 6.5 cm3 plastic pots half filled with concrete, that were planted in
circles (i.e. blocks) in the sediment. The experimental treatments were placed in a fixed order
and each circle were turned one notch in relationship to the previous one in an attempt to
eliminate possible bias of the bay edges.
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At sampling each macrophyte was covered with a mesh bag (mesh size 1 mm) and detached
from the pot. The bag was then sealed and transferred to the surface, where after the samples
were deep frozen until further analysis. All invertebrates in the samples were sorted, counted
and identified to species level with some exceptions; Gammarus and Hydrobia where
identified to genus, Hydrachnidia and Hirudinea were identified to suborder and subclass
respectively, and insects (mostly juvenile larvae) were identified to family. Juveniles of the
bivalves Parvicardium hauniense Petersen & Russell and Cerastoderma glaucum Poiret were
grouped as they are difficult to separate. Fish, ostracods and copepods were eliminated from
the data set due to uncertainty about whether the sampling method was appropriate for these
animals. Large detritus particles and filamentous algae (hereafter referred to as “entangled
macrophytes”) were separated from the samples, identified and weighed after drying at 49-
59°C to constant weight.
To control for effects of adjacent vegetation the percentage cover of loose and attached
macrophyte species within a 1 m radius around each sample was estimated using a seven
graded scale (Kautsky 1993) midway through the experiment. There was no significant
difference in macrophyte community composition between the treatments (P>0.9; ANOSIM
in PAST, version 1.78, Hammer et al. 2001).
Macrophyte structure and surface area
To estimate the structural complexity of the macrophytes in the experiment, 10 shoots of each
natural experimental species were collected from the study site. The plants were pressed and
scanned (grey scale, 300 dpi, TIFF format). ImageJ software (Rasband 1997-2007) was used
to convert all grey-scale images to binary images and to analyse the total shoot area and
perimeter. The number of branches was counted on each shoot. Since natural Chara and
Myriophyllum are delicately branched only their main branches were counted and then
multiplied with the average number of divisions per branch and leaf, reported in the literature
(Mossberg & Stenberg 2003; Schubert & Blindow 2003). Because of difficulties to acquire
sufficient contrast in the scanned images of the artificial macrophytes, one segment of each
type were cut in smaller pieces and photo copied. The photo copies were coloured with a dark
pen, and then scanned and analysed in the same manner as the natural plants. The area,
perimeter and branching measured for each segment of the artificial plants was multiplied
with the number of segments in each sample. For both natural and artificial plants the
perimeter and the number of branches were divided by the surface area. An average for each
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type of macrophyte was calculated and used as a measure of structural complexity. The
artificial macrophytes structurally resembled the natural macrophytes they were representing
according to these measures (Fig. 3a & b). Myriophyllum was more complex, with larger
perimeter and number of branches per surface area than Chara and Potamogeton. Chara was
of medium complexity and Potamogeton with its broad leafs had the simplest structure.
Natural Myriophyllum was, however, considerably more complex than its artificial version
and natural Chara had a higher number of branches than artificial Chara.
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Fig. 3. Morphological characters of natural and artificial Myriophyllum, Chara and Potamogeton (mean, SD for the natural plants); perimeter per surface area (a), branching per surface area (b) and surface area per sample (c). The error bar of the artificial Potamogeton is due to loss of segments in 2 samples.
After the animals in the samples had been picked out the surface area of each natural sample
macrophyte were measured using the above described procedure and software. Since all the
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artificial plants were identical no further measures of these was conducted, though a small
variation occurred due to loss of segments in 2 samples of artificial Potamogeton. Artificial
Myriophyllum had the largest surface area per sample, followed by natural and artificial
Potamogeton (Fig. 3c). To eliminate the confounding factor of differences in macrophyte
surface area, the invertebrate abundance and dry weight of entangled macrophytes were
divided by the total surface area in each macrophyte sample. But to elucidate the effect of
macrophyte surface area, the total abundance of invertebrates and the entangled macrophytes
were also analysed without normalizing the data for unequal areas. Taxon density was also
analysed per sample as it is inappropriate to normalize the density of taxa by dividing the
number of taxa by area (since the number of species increases nonlinearly with area; Gotelli
& Colwell (2001). The number of taxa generally increases with a higher abundance of
individuals (Bunge & Fitzpatrick 1993), therefore rarefaction curves were used to compare
the taxon richness (number of taxa per individuals) as a compliment to taxon density.
Statistics
Differences in taxon density (number of taxa per sample), the total invertebrate abundance
(per sample and macrophyte surface area) and the abundance of the four selected animal taxa
(I. chelipes, Gammarus spp. T. fluviatilis, and Chironomidae) were tested using complete
block ANCOVAs. Treatment (i.e. natural and artificial Myriophyllum, Chara and
Potamogeton), entangled macrophytes (i.e. gram dry weight of filamentous algae and other
plant material per sample) and block (i.e. circles of samples with each treatment represented
ones) was used as explanatory variables. In the models of taxon density and invertebrate
abundance per sample, macrophyte surface area was also used as a factor. All effects were
counted as significant at the p=0.05 level. Variation in the accumulation of entangled
macrophytes between treatments was investigated by a compete block ANOVA, with
treatment and block as factors. The models were reduced as far as possible without loss of
explanatory power, through manual deletion tests. To meet the assumptions of parametric
tests all the response variables, with the exception of taxon density, were transformed by
log10. When the effects of treatment were significant Tukey’s HSD test were used to compare
macrophytes. All statistical tests were performed using R version 2.6.1 (R Developmental
Core Team 2007). The rarefaction curves used to compare taxon richness were calculated by
bootstrap analyses with 1000 permutations performed in Microsoft Excel (Donovan &
Welden 2002).
9
Results
A total of 14 973 macroinvertebrates were counted and identified to 34 taxa in the study
(Appendix). Chironomids, Idotea chelipes and P. hauniense/C. glaucum were dominating the
samples. They constituted 65-80% of the invertebrate abundance in the different treatments,
with the exception of artificial Myriophyllum where Gammarus spp. occurred in great
numbers and together with the previous tree taxa comprised 75% of the abundance. The
number of Gammarus spp. varied greatly in the samples (see error bars in Fig. 7) and ranged
between 0 to 186 individuals per sample. The small amphipod Leptocheirus pilosus Zaddach
were mainly found in site A. Though there was a large variation in the abundance of L.
pilosus, they only occurred on natural Potamogeton when in high numbers.
The taxon density and the invertebrate abundance both per sample and per macrophyte
surface area were different between treatments (ANCOVAs: P<0.001, Table. 1). Potamogeton
had a higher taxon density than Chara, comparing only the natural plants (Fig. 4a). The other
differences in taxon density between the natural macrophytes were not significant. Amongst
artificial plants Myriophyllum had a higher number of taxa than Chara and Potamogeton.
The invertebrate abundance per sample was not significantly different between the natural
plants (Fig. 4b). Artificial Myriophyllum had a higher invertebrate abundance per sample than
artificial Chara and Potamogeton. Among both natural and artificial plants Chara had a
higher abundance of macroinvertebrates per surface area than Potamogeton (Fig. 4c). Natural
Myriophyllum had a higher number of invertebrates per surface area than natural
Potamogeton, but were not significantly different from Chara. Artificial Myriophyllum
showed the opposite pattern, i.e. had a lower invertebrate abundance than Chara, but was not
significantly different from Potamogeton.
10
Table 1. Results of complete block ANCOVAs/ANOVA testing for effects of “treatment”, “entangled macrophytes”, “surface area” and “block” on taxon density, macroinvertebrate abundance (per sample and surface area) and accumulation of entangled macrophytes per surface area. P values in bold indicate statistical significance at p=0.05. Values replaced by “-“ indicates a non-significant factor or interaction eliminated by model simplification. A complete block design requires the assumption that there are no interactions between block and any of the other factors. DF MS F P Taxon density (# taxa sample-1) Treatment 5 24.37 7.20 < 0.001 Surface area - - - - Entangled macrophytes 1 255.52 75.53 < 0.001 Block 15 12.22 3.61 < 0.001 Treatment : Surface area - - - - Treatment : Entangled macrophytes - - - - Surface area : Entangled macrophytes - - - - Treatment : Surface area : Entangled macrophytes - - - - Error 74 3.38 Macroinvertebrate abundance (log10 # ind. sample-1) Treatment 5 0.29 9.82 < 0.001 Surface area - - - - Entangled macrophytes 1 1.04 34.92 < 0.001 Block 15 0.11 3.56 < 0.001 Treatment : Surface area - - - - Treatment : Entangled macrophytes - - - - Surface area : Entangled macrophytes - - - - Treatment : Surface area : Entangled macrophytes - - - - Error 74 0.03 Macroinvertebrate abundance (log10 # ind. cm-2) Treatment 5 1.09 37.41 < 0.001 Entangled macrophytes 1 1.07 36.73 < 0.001 Block 15 0.11 3.80 < 0.001 Treatment: Entangled macrophytes - - - - Error 74 0.02 Entangled macrophytes (log10 g dw cm-2) Treatment 5 3.70 6.03 < 0.001 Block 15 7.19 11.71 < 0.001 Error 75 0.61 Treatment = six macrophytes; natural and artificial Myriophyllum, Chara and Potamogeton (Fig. 2). Surface area = surface area of the sample-macrophytes (Fig. 3c). Entangled macrophytes = gram dry weight of filamentous algae and other plant material. Block = circles of samples with each treatment represented ones.
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Natural Artif icial
Inve
rtebr
ate
abun
danc
e (#
ind.
sam
ple
-1)
a
a
c
b
d
-0.8
-0.6
-0.4
-0.2
0.0
0.2
0.4
0.6
Natural Artif icial
Inve
rtebr
ate
abun
danc
e (lo
g10
# in
d. c
m-2
)
0.000
0.004
0.008
0.012
0.016
0.020
Natural Artif icial
Enta
ngle
d m
acro
phyt
es p
er
surfa
ce a
rea
(g d
w c
m-2
)
02468
10121416
Natural Artif icial
Inve
rtebr
ate
taxo
n de
nsity
(#
taxa
sam
ple
-1)
0
50
100
150
200
250
300
350
Natural Artif icial
Inve
rtebr
ate
abun
danc
e (#
ind.
sam
ple
-1)
-0.8
-0.6
-0.4
-0.2
0.0
0.2
0.4
0.6
Natural Artif icial
Inve
rtebr
ate
abun
danc
e (lo
g10
# in
d. c
m-2
)
0.000
0.004
0.008
0.012
0.016
0.020
Natural Artif icial
Enta
ngle
d m
acro
phyt
es p
er
surfa
ce a
rea
(g d
w c
m-2
)
02468
10121416
Natural Artif icial
Inve
rtebr
ate
taxo
n de
nsity
(#
taxa
sam
ple
-1)
0
50
100
150
200
250
300
350
Natural Artif icial
Inve
rtebr
ate
abun
danc
e (#
ind.
sam
ple
-1)
a
a
c
b
d
aab bc c c a
Myriophyllum Chara Potamogeton
Myriophyllum Chara Potamogeton
Myriophyllum Chara Potamogeton
ab
c cc
a ab
bcbcbc c
ab
bcc
abc
aba
Fig. 4. Invertebrate taxon density (a), abundance per sample (b), abundance per surface area (c) and entangled macrophytes per surface area (d), on natural and artificial Myriophyllum, Chara and Potamogeton (adjusted mean, SD, n=16). Bars topped by the same letter in each panel do not differ significantly at p=0.05 according to Tukey’s HSD test with blocked design. The total biomass of entangled macrophytes consisted of 5% charophytes, 5% vascular plants,
77% filamentous algae and 13% other non-filamentous algae. The taxon density and
macrofaunal abundance per sample and per surface area were positively correlated with the
biomass of entangled macrophytes in the samples (ANCOVA: P<0.001; Table 1, Fig. 5).The
accumulated amount of entangled macrophytes per surface area were different between
treatments (ANOVA: P<0.001, Table. 1). In comparison between both natural and artificial
plants Chara had a higher biomass of entangled macrophytes per surface area than
Potamogeton (Fig. 4d). However, Myriophyllum could not be separated from either Chara or
Potamogeton on both natural and artificial plants. The biomass of entangled macrophytes per
sample were also different between treatments (ANOVA: P=0.016). The only significant
difference was that artificial Myriophyllum had a higher biomass of entangled macrophytes
per sample than artificial Potamogeton. However, natural Chara showed a tendency to
accumulate more entangled macrophytes per sample than artificial Potamogeton (Tukey’s
HSD test: p=0.064).
12
J. Sagerman
-1.0
-0.5
0.0
0.5
1.0
0.0 2.0 4.0 6.0
Entangled macrophytes (g dw )
Inve
rtebr
ate
abun
danc
e (lo
g 10 #
ind.
cm
-2)
J. Sagerm an
0
5
10
15
20
0.0 2.0 4.0 6.0
Entangled macrophytes
Taxo
n de
nsity
(#
taxa
sam
ple
-1)
a
bJ. Sagerman
-1.0
-0.5
0.0
0.5
1.0
0.0 2.0 4.0 6.0
Entangled macrophytes (g dw )
Inve
rtebr
ate
abun
danc
e (lo
g 10 #
ind.
cm
-2)
J. Sagerm an
0
5
10
15
20
0.0 2.0 4.0 6.0
Entangled macrophytes
Taxo
n de
nsity
(#
taxa
sam
ple
-1)
a
b
Fig. 5. Invertebrate taxon density (a) and abundance per surface area (b) plotted against biomass of entangled macrophytes (P<0.001 in ANCOVA; Table 1).
The number of taxa when adjusted by rarefaction was highest on natural Potamogeton
followed by artificial Chara, natural Chara and natural Myriophyllum (Fig. 6). Artificial
Myriophyllum and artificial Potamogeton had the lowest taxon richness.
13
0
5
10
15
20
25
0 1000 2000 3000 4000Individuals
Inve
rteb
rate
taxo
n ric
hnes
s (#
taxa
)
Black NaturalGrey Artificial
Myriophyllum Chara Potamogeton
0
5
10
15
20
25
0 1000 2000 3000 4000Individuals
Inve
rteb
rate
taxo
n ric
hnes
s (#
taxa
)
Black NaturalGrey Artificial
Myriophyllum Chara Potamogeton
Black NaturalGrey Artificial
Myriophyllum Chara Potamogeton
Fig. 6. Rarefaction curves for invertebrate taxa on natural and artificial Myriophyllum, Chara and Potamogeton (n = 16, mean from 1000 permutations, ±95% CI). Curves stop at maximum number of individuals in pooled samples of each treatment.
The four invertebrate taxa; Gammarus spp., I. chelipes, T. fluviatilis and chironomids
responded differently to the treatments (Table 2, Fig.7). The abundance of both I. chelipes and
chironomids was higher on natural Chara and Myriophyllum compared to natural
Potamogeton. I. chelipes occured in higher abundance on artificial Chara than on the other
two artificial plants. Chironomids were more abundant on artificial Chara and Potamogeton
than on artificial Myriophyllum. There was no significant difference in abundance of
Gammarus spp. between the natural plants. On the artificial plants, Gammarus spp. was more
abundant on Myriophyllum than on Chara and Potamogeton. There was no significant
difference in abundance of T. fluviatilis between any of the macrophytes. The abundance of
Gammarus and I. chelipes increased with increased biomass of entangled macrophytes
(ANCOVA: P<0.001), while the abundance of Chironomids and T. fluviatilis were not
affected by entangled macrophytes.
14
Table 2. Results of complete block ANCOVAs testing for effects of “treatment”, “entangled macrophytes” and “block” on the abundance of four invertebrate taxa per macrophyte surface area. P values in bold indicate statistical significance at p=0.05. Values replaced by “-“ indicates non-significant factors and interactions eliminated by model simplification. A complete block design requires the assumption that there are no interactions between block and any of the other factors. DF MS F P I. chelipes abundance (log10 # ind. cm-2) Treatment 5 2.85 32.77 < 0.001 Entangled macrophytes 1 1.38 15.89 < 0.001 Block 15 0.42 4.86 < 0.001 Treatment : Entangled macrophytes - - - - Error 74 0.09 Gammarus spp. abundance (log10 # ind. cm-2) Treatment 5 2.36 5.44 < 0.001 Entangled macrophytes 1 42.08 96.85 < 0.001 Block 15 3.15 7.24 < 0.001 Treatment : Entangled macrophytes - - - - Error 74 0.43 T. fluviatilis abundance (log10 # ind. cm-2) Treatment - - - - Entangled macrophytes 1 0.18 0.54 0.47 Block 15 1.44 4.38 < 0.001 Treatment : Entangled macrophytes - - - - Error 79 0.33 Chironomidae abundance (log10 # ind. cm-2) Treatment 5 1.82 21.39 < 0.001 Entangled macrophytes 1 0.07 0.85 0.36 Block 15 0.51 6.04 < 0.001 Treatment : Entangled macrophytes - - - - Error 74 0.09 Treatment = six macrophytes; natural and artificial Myriophyllum, Chara and Potamogeton (Fig. 2). Entangled macrophytes = gram dry weight of filamentous algae and other plant material. Block = circles of samples with each treatment represented ones.
15
-4.0
-3.0
-2.0
-1.0
0.0
Natural Artif icial
log 10
# in
d. c
m-2
-4.0
-3.0
-2.0
-1.0
0.0
Natural Artif icial
log 10
# in
d. c
m-2
Myriophyllum Chara Potamogeton
-4.0
-3.0
-2.0
-1.0
0.0
0.0 1.0 2.0 3.0 4.0 5.0 6.0
log 10
ind.
cm
-2
-4.0
-3.0
-2.0
-1.0
0.0
0.0 2.0 4.0 6.0
log 10
# in
d. c
m-2
-4.0
-3.0
-2.0
-1.0
0.0
Natural Artif icial
Natural Artif icial
log 10
# in
d. c
m-2
-4.0
-3.0
-2.0
-1.0
0.0
Natural Artif icial
log 10
# in
d. c
m-2
-4.0
-3.0
-2.0
-1.0
0.0
0.0 2.0 4.0 6.0
Entangled macrophytes (g dw )
log 10
# in
d. c
m-2
-4.0
-3.0
-2.0
-1.0
0.0
0.0 1.0 2.0 3.0 4.0 5.0 6.0
log 1
0 # in
d. c
m-2
aba ad
bc
bc
c
cc dab a
ab aa bbab
Idotea chelipes
Gammarus spp.
Theodoxus fluviatilis
Chironomidae
-4.0
-3.0
-2.0
-1.0
0.0
Natural Artif icial
log 10
# in
d. c
m-2
-4.0
-3.0
-2.0
-1.0
0.0
Natural Artif icial
log 10
# in
d. c
m-2
Myriophyllum Chara Potamogeton
-4.0
-3.0
-2.0
-1.0
0.0
0.0 1.0 2.0 3.0 4.0 5.0 6.0
log 10
ind.
cm
-2
-4.0
-3.0
-2.0
-1.0
0.0
0.0 2.0 4.0 6.0
log 10
# in
d. c
m-2
-4.0
-3.0
-2.0
-1.0
0.0
Natural Artif icial
Natural Artif icial
log 10
# in
d. c
m-2
-4.0
-3.0
-2.0
-1.0
0.0
Natural Artif icial
log 10
# in
d. c
m-2
-4.0
-3.0
-2.0
-1.0
0.0
0.0 2.0 4.0 6.0
Entangled macrophytes (g dw )
log 10
# in
d. c
m-2
-4.0
-3.0
-2.0
-1.0
0.0
0.0 1.0 2.0 3.0 4.0 5.0 6.0
log 1
0 # in
d. c
m-2
aba ad
bc
bc
c
cc dab a
ab aa bbab
-4.0
-3.0
-2.0
-1.0
0.0
Natural Artif icial
log 10
# in
d. c
m-2
-4.0
-3.0
-2.0
-1.0
0.0
Natural Artif icial
log 10
# in
d. c
m-2
Myriophyllum Chara Potamogeton
-4.0
-3.0
-2.0
-1.0
0.0
0.0 1.0 2.0 3.0 4.0 5.0 6.0
log 10
ind.
cm
-2
-4.0
-3.0
-2.0
-1.0
0.0
0.0 2.0 4.0 6.0
log 10
# in
d. c
m-2
-4.0
-3.0
-2.0
-1.0
0.0
Natural Artif icial
Natural Artif icial
log 10
# in
d. c
m-2
-4.0
-3.0
-2.0
-1.0
0.0
Natural Artif icial
log 10
# in
d. c
m-2
-4.0
-3.0
-2.0
-1.0
0.0
0.0 2.0 4.0 6.0
Entangled macrophytes (g dw )
log 10
# in
d. c
m-2
-4.0
-3.0
-2.0
-1.0
0.0
0.0 1.0 2.0 3.0 4.0 5.0 6.0
log 1
0 # in
d. c
m-2
aba ad
bc
bc
c
cc dab a
ab aa bb
-4.0
-3.0
-2.0
-1.0
0.0
Natural Artif icial
log 10
# in
d. c
m-2
-4.0
-3.0
-2.0
-1.0
0.0
Natural Artif icial
log 10
# in
d. c
m-2
Myriophyllum Chara Potamogeton
-4.0
-3.0
-2.0
-1.0
0.0
0.0 1.0 2.0 3.0 4.0 5.0 6.0
log 10
ind.
cm
-2
-4.0
-3.0
-2.0
-1.0
0.0
0.0 2.0 4.0 6.0
log 10
# in
d. c
m-2
-4.0
-3.0
-2.0
-1.0
0.0
Natural Artif icial
log 10
# in
d. c
m-2
-4.0
-3.0
-2.0
-1.0
0.0
Natural Artif icial
log 10
# in
d. c
m-2
Myriophyllum Chara Potamogeton
-4.0
-3.0
-2.0
-1.0
0.0
0.0 1.0 2.0 3.0 4.0 5.0 6.0
log 10
ind.
cm
-2
-4.0
-3.0
-2.0
-1.0
0.0
0.0 2.0 4.0 6.0
log 10
# in
d. c
m-2
-4.0
-3.0
-2.0
-1.0
0.0
Natural Artif icial
Natural Artif icial
log 10
# in
d. c
m-2
-4.0
-3.0
-2.0
-1.0
0.0
Natural Artif icial
log 10
# in
d. c
m-2
-4.0
-3.0
-2.0
-1.0
0.0
0.0 2.0 4.0 6.0
Entangled macrophytes (g dw )
log 10
# in
d. c
m-2
-4.0
-3.0
-2.0
-1.0
0.0
0.0 1.0 2.0 3.0 4.0 5.0 6.0
log 1
0 # in
d. c
m-2
-4.0
-3.0
-2.0
-1.0
0.0
Natural Artif icial
Natural Artif icial
log 10
# in
d. c
m-2
-4.0
-3.0
-2.0
-1.0
0.0
Natural Artif icial
log 10
# in
d. c
m-2
-4.0
-3.0
-2.0
-1.0
0.0
0.0 2.0 4.0 6.0
Entangled macrophytes (g dw )
log 10
# in
d. c
m-2
-4.0
-3.0
-2.0
-1.0
0.0
0.0 1.0 2.0 3.0 4.0 5.0 6.0
log 1
0 # in
d. c
m-2
aba ad
bc
bc
c
cc dab a
ab aa bbab
Idotea chelipes
Gammarus spp.
Theodoxus fluviatilis
Chironomidae
Fig. 7. Abundance of four invertebrate taxa per macrophyte surface area, (in the panels to the left) on natural and artificial Myriophyllum, Chara and Potamogeton (adjusted mean, SD, n = 16) and (in the panels to the right) plotted against biomass of entangled macrophytes (n = 96). Within each left-panel, bars topped by the same letter do not differ significantly at p=0.05 according to Tukey`s HSD test with a blocked design (no post hoc test has been applied to the left-panel of T. fluviatilis since there was no significant difference in their abundance between treatments according to ANCOVA (Table 2)).
The effect of block was significant in all models (Table 1 & 2). The variations in biomass of
entangled macrophytes between blocks were particularly high (see error bars in Fig. 4d). A
complete block design requires the assumption that there is no interaction between block and
any of the other factors. No significant interactions between the factors were detected in any
of the analysis (Table 1 & 2).
16
Discussion
The pattern of taxon density in the artificial macrophytes is in accordance with what was
expected (i.e., a rising number of taxa with increased macrophyte complexity), though the
difference between the medium and simple macrophyte structures was none-significant (Fig.
4a). Natural plants however, possess many other characters apart from different
morphological structures; e.g. release of allelopathic substances, surface textures, senescence
and patterns of undulatory movements in water currents (Taniguchi et al. 2003). These
characteristics can affect the distribution of invertebrate taxa. Therefore it is not entirely
surprising that the difference between the natural Myriophyllum and Chara is not significant,
even though their difference in complexity is considerably larger than between their artificial
versions (Fig. 3). Natural Potamogeton matches the corresponding artificial macrophyte well
both in surface area and in the two chosen measures of complexity, yet it harbours the largest
amount of taxa in the experiment. Clearly natural Potamogeton possess other properties
beyond architectural morphology that renders it a suitable habitat for many species. A
possible reason could be that both M. spicatum and C. baltica has been recorded to use
allelopathic substances (Dhillon et al. 1982; Wium-Andersen et al. 1982) that can bee toxic to
microepiphytes (Erhard & Gross 2006; Hilt 2006), an important food source for many
invertebrates (Hillebrand 2002). Allelopathic substances are rare in Potamogeton species that
are common in the Baltic Sea region (Gross 2003) and have to my knowledge never been
noted in P. perfoliatus. However, in a study conducted simultaneously as the present study (J.
Hansen pers. comm.) the number of microalgae per macrophyte surface area was not higher
on P. perfoliatus compared to C. baltica and M. spicatum. But allelocemicals can also change
the composition of different types of microscopic algae (Nakai & Hosomi 2002) which could
be of significance since the fauna can have preference for certain microphytes (Neckles et al.
1994; Sommer 1997). Hansen (2007) observed P. pectinatus to have a higher ratio of
epiphytic diatoms (fucoxanthin per chlorophyll a) than M. spicatum and C. baltica. This could
also apply to P. perfoliatus, which should be a subject for further investigations.
The taxon density (the number of species per unit) followed the pattern of invertebrate
abundance quite neatly (Fig. 4a & b), with the exception of natural Potamogeton. This is a
common pattern and could arise for pure statistical reasons: the more individuals are sampled
the more species you will come across (Bunge & Fitzpatrick 1993). Thus, species density can
be heavily dependent on how many individuals have been sampled. Differences in abundance
can point out interesting biological patterns, but it can also be a product of differences in
17
sampling effort (Gotelli & Colwell 2001). The difference in surface area between the
macrophyte treatments constitutes a bias possibly affecting the abundance of invertebrates
and thereby the taxon density.
The estimation of taxon richness (number of taxa per individuals sampled) is not affected by
the abundance of individuals and is thereby independent of differing surface areas. The
present study shows that macrophyte complexity is not the foremost factor affecting the taxon
richness in the shallow soft bottom bays of the Baltic (Fig. 6). Instead the elevated number of
taxa in the most complex artificial macrophyte reflects a higher abundance of individuals.
In most studies on macrophyte complexity species density has been used as the only measure
of diversity. In the case of habitat complexity species density is probably the more relevant of
the two measures since it shows the actual number of species in the habitat. But to also look
into species richness will reveal important underlying mechanisms and may help to avoid
making the wrong conclusions.
Macrophyte surface area and complexity often correlate in the nature (Johnson et al. 2003),
and it can be difficult to separate their effects (Thomaz et al. 2007). In many studies on the
subject the increased surface area of structures has been included as a part of complexity
(Krecher 1939; Rosine 1955; Heck & Westone 1977). In the present study there was a
difference in surface area between the macrophytes, but there was no consistent increase of
area with structural complexity (Fig. 3). Both factors likely affect the fauna simultaneously,
which could be the reason why surface area came out as none-significant in the ANCOVA’s
for both taxon density and the invertebrate abundance per sample. The effect of surface area
can however not be disregarded and must be taken in to account. Artificial plants of different
complexity with a standardised surface area have been used in several freshwater-studies, to
isolate the factor of complexity (e.g.Jeffries 1993; Taniguchi et al. 2003). In these studies
there where however less resemblance of natural plants compared to the present study. To get
around these problems I analysed the invertebrate abundance per macrophyte surface area.
There was no simple relationship between invertebrate abundance per macrophyte surface
area and structural complexity of the plants. The structurally more complex Chara did have a
higher abundance of invertebrates per area than the simpler Potamogeton, both on natural and
artificial aquatic plants (Fig. 4c). But the most complex plant Myriophyllum did not have an
increase of invertebrates in proportion to its complexity. The biomass of entangled
18
macrophytes per surface area showed a similar pattern to the abundance of invertebrates (Fig.
4d). Both natural and artificial Chara contained significantly higher dry weight of entangled
macrophytes per surface area than natural and artificial Potamogeton respectively. But it was
not possible to detect a significant difference between Myriophyllum in relationship to the
other plants. The connection between invertebrate abundance and entangled macrophytes was
seen also at the level of single samples, since the macrofaunal abundance both per sample and
per surface area was positively correlated with the biomass of the entangled macrophytes. The
entangled macrophytes consisted to a high degree of filamentous algae; an important food
source to several of the invertebrate species of high abundance in the samples (J. Hansen pers.
comm.). A possible explanation to the results is therefore that the macrophyte structure has an
indirect effect on invertebrate abundance through differences in their capacity to catch and
accumulate filamentous algae and other drifting plant material.
The present study shows that the morphology of macrophytes affects invertebrate taxa
differently (Fig. 8). Chironomids occurred in highest abundance on natural Chara (though
there was no significant difference to Myriophyllum). Since chironomids are small they might
perceive complexity at a different scale than the other animals in the study. McAbendroth et
al. (2005) found that the structural complexity of macrophytes varies across scales and that
Chara fragifera Durieu was more complex at a small scale than Myriophyllum alterniflorum
DC., though the opposite was true when they were viewed as entire plants. It is possible that
to chironomids C. baltica is the most complex macrophyte in the experiment. C. baltica have
a spiny stem which may constitute a suitable habitat for the chironomids. The artificial Chara
did not have this spiny feature.
There was no correlation between the abundance of chironomids and the biomass of
entangled macrophytes. North European chironomids are generally considered being
gathering collectors (Nilsson 1997) rather than herbivorous shredders, although the shredding
feeding mode also exists among chironomids (e.g. Merritt et al. 2002). But they are not
particularly mobile and probably can not adapt on any larger scale to the ever changing
landscape of drifting algae and plant material.
The abundance of both I. chelipes and Gammarus spp. was positively correlated with biomass
of entangled macrophytes. The result is in accordance with a food preference-study where I.
chelipes did prefer to eat the filamentous green alga Cladophora glomerata L. over M.
19
spicatum, C. baltica and P. pectinatus (Hansen 2007). In the present study I. chelipes
occurred in highest abundances per surface area on natural Myriophyllum and on natural and
artificial Chara. These were also the macrophytes with the highest biomass of entangled
macrophytes per surface area. It is likely that drifting filamentous algae interfere with the
effect of macrophyte complexity.
T. fluviatilis were neither affected by the different plants nor by the biomass of entangled
macrophytes. Snails are rather slow moving and since they can not “run” for shelter when
threatened by predators they have to rely on the thickness of their shell. Additionally T.
fluviatilis is a scraping grazer and filamentous algae do not seem to be an important food
source to them (Neumann 1969; Skoog 1978).
The brackish water amphipod L. pilosus were mainly found in site A. Though there was a
large variation in the abundance of L. pilosus, they only occurred on natural Potamogeton
when in greater numbers. L. pilosus are quite efficient swimmers, but in contrast to the
Gammarus spp. in the study area they build tube-shaped nests that they rarely leave. L.
pilosus mainly feeds trough sieving out suspended food particles in the water flow created
trough the nest by the constant beating of their pleopods. In esteuries of the British Isles L.
pilosus have been noted to build their nests on the thallus of Chondrus crispus Stackhouse or
on the surface of smooth stones (Goodhart 1939). Since C. crispus does not grow in the Askö
region, P. perfoliatus with its broad leafs might have taken over the function of most suitable
nest-substrate in these shallow soft-bottom bays.
The increased nutrient load in the Baltic Sea has enhanced the primary production of
phytoplankton and filamentous algae (Schramm & Nienhuis 1996). These species have the
capacity to out-compete slow-growing macrophytes through shading (Duarte 1995). This
change of conditions has affected the macrophyte species of the shallow soft-bottom bays
differently. Vascular plants such as Myriophyllum and Potamogeton has increased in
abundance with the nutrient enrichment while charophytes are believed to have declined
(Wallentinus 1979; Blindow 2000; Schubert & Blindow 2003; Munsterhjelm 2005). It has
been suggested that charophytes are disfavoured by poor light conditions through their way of
growing with most of their biomass concentrated close to the bottom, while vascular plants
often maintain the main part of their biomass close to the surface (Blindow 1992). The high
accumulation of filamentous algae and other drifting plant material by C. baltica might be
20
another contributing factor to its vulnerability to eutrophication. P. perfoliatus, on the other
hand, might be favoured by its morphology in an environment where drifting filamentous
algae is increasing in density. Assuming vegetation stands of the different macrophyte species
with the same density and surface area, my results show that a decline in charophytes in
favour of P. perfoliatus could lead to a reduction in invertebrate abundance. The delicately
branched Myriophyllum, which also is favoured by moderate eutrophication had just as much
invertebrate abundance and biomass of entangled macrophytes as C. baltica. Thereby M.
spicatum could, interpreting from my results, theoretically replace the function of C. baltica
as a habitat for invertebrates in the Baltic Sea. However, each macrophyte species generally
has its own associated invertebrate fauna (Dvorak & Best 1982; Scheffer et al. 1984). So even
if M. spicatum could partly replace the function of C. baltica it would most certainly affect
the invertebrate community.
To conclude, this study shows that the structural morphology of aquatic plants impacts on the
taxon density (the number of species per unit) and the abundance of invertebrates in the Baltic
Sea. It was however not possible to isolate the effect of morphological complexity from the
macrophyte surface area in relation to taxon density and the result of taxon richness compared
with rarefaction curves suggests that macrophyte complexity does not immediately affect the
number of taxa per sampled individuals in the soft-bottom bays of the Baltic Sea. The study
also demonstrates that macrophytes of different morphological complexity accumulates
different amount of entangled macrophytes per surface area, which in turn may affect the
abundance of invertebrates. Invertebrate species are affected differently by the structural
complexity of aquatic plants.
Acknowledgements
First of all I would like to thank Sofia Wikström and Joakim Hansen for all support and
guidance. I would also like to thank Lena Kautsky for proofreading and encouragement.
Further, I gratefully acknowledge Kristoffer Hylander, Peter Hambäck and Didrik
Vanhoenacker for statistical advice. Jag vill även tacka pappa för praktiska lösningar i fällt
och goda råd. Tack mamma och Johan Änggård för hjälp med mätning av syre och temperatur
trots stormigt väder, och tack Lena Larsson för växtpressen, den är flitigt använd.
21
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25
Appendix
Invertebrate taxa Total
abundance Pressence in # of samples
Chironomidae 4904 96 Parvicardium hauniense Petersen & Russell Cerastoderma glaucum Poiret 2862 94 Idotea chelipes (Pallas) 2622 95 Gammarus spp. 1226 73 Hydrobia spp. 951 78 Idotea baltica (Pallas) 657 69 Theodoxus fluviatilis (L.) 648 89 Bithynia tentaculata (L.) 291 66 Radix baltica (L.) 232 56 Leptocheirus pilosus Zaddach 114 28 Hediste diversicolor (O.F. Müller) 88 30 Cyanophthalma obscura (Schultze) 71 16 Potamopyrgus antipodarum Gray 57 26 Hydroptilidae 56 28 Opistobrachia unid. sp. 39 22 Mytilus edulis L. 27 16 Limaponthia capitata (O.F. Müller) 24 11 Jaera albifrons spp. Leach 20 13 Lymnea stagnalis (L.) 19 16 Macoma baltica (L.) 11 7 Praunus inermis (Rathke) 11 6 Cataclysta sp. 8 3 Chorophium volutator (Pallas) 7 7 Hydrachnidia 6 5 Haliplidae 4 3 Ceratopogonidae 3 3 Limnephilidae 3 3 Hirudinea 3 3 Curculionidae 2 2 Palaemon adspersus Rathke 2 2 Palaemon elegans Rathke 2 1 Mya arenaria (L.) 1 1 Coenagrionidae 1 1 Dytiscidae 1 1
26
Serien Plants & Ecology (ISSN 1651-9248) har tidigare haft namnen "Meddelanden från Växtekologiska avdelningen, Botaniska institutionen, Stockholms Universitet" nummer 1978:1 – 1993:1 samt "Växtekologi". (ISSN 1400-9501) nummer 1994:1 – 2003:3.
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fritidsbebyggelse. 1978:5 Bråvander, Lars-Gunnar och Engelmark, Thorbjörn: Botaniska studier vid
Porjusselets och St. Lulevattens stränder i samband med regleringen 1974. 1979:1 Engström, Peter: Tillväxt, sulfatupptag och omsättning av cellmaterial hos
pelagiska saltvattensbakterier. 1979:2 Eriksson, Sonja: Vegetationsutvecklingen i Husby-Långhundra de senaste
tvåhundra åren. 1979:3 Bråvander, Lars-Gunnar: Vegetation och flora i övre Teusadalen och vid Auta-
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1979:4 Liljelund, Lars-Erik, Emanuelsson, Urban, Florgård, C. och Hofman-Bang, Vilhelm: Kunskapsöversikt och forskningsbehov rörande mekanisk påverkan på mark och vegetation.
1979:5 Reinhard, Ylva: Avloppsinfiltration - ett försök till konsekvensbeskrivning. 1980:1 Telenius, Anders och Torstensson, Peter: Populationsstudie på Spergularia marina
och Spergularia media. I Frödimorfism och reproduktion. 1980:2 Hilding, Tuija: Populationsstudier på Spergularia marina och Spergularia media.
II Resursallokering och mortalitet. 1980:3 Eriksson, Ove: Reproduktion och vegetativ spridning hos Potentilla anserina L. 1981:1 Eriksson, Torsten: Aspekter på färgvariation hos Dactylorhiza sambucina. 1983:1 Blom, Göran: Undersökningar av lertäkter i Färentuna, Ekerö kommun. 1984:1 Jerling, Ingemar: Kalkning som motåtgärd till försurningen och dess effekter på
blåbär, Vaccinium myrtillus. 1986:1 Svanberg, Kerstin: En studie av grusbräckans (Saxifraga tridactylites) demografi. 1986:2 Nyberg, Hans: Förändringar i träd- och buskskiktets sammansättning i
ädellövskogen på Tullgarnsnäset 1960-1983. 1987:1 Edenholm, Krister: Undersökningar av vegetationspåverkan av vildsvinsbök i
Tullgarnsområdet. 1987:2 Nilsson, Thomas: Variation i fröstorlek och tillväxthastighet inom släktet Veronica. 1988:1 Ehrlén, Johan: Fröproduktion hos vårärt (Lathyrus vernus L.). - Begränsningar och
reglering. 1988:2 Dinnétz, Patrik: Local variation in degree of gynodioecy and protogyny in Plantago
maritima. 1988:3 Blom, Göran och Wincent, Helena: Effekter of kalkning på ängsvegetation. 1989:1 Eriksson, Pia: Täthetsreglering i Littoralvegetation. 1989:2 Kalvas, Arja: Jämförande studier av Fucus-populationer från Östersjön och
västkusten. 1990:1 Kiviniemi, Katariina: Groddplantsetablering och spridning hos smultron, Fragaria
vesca.
27
1990:2 Idestam-Almquist, Jerker: Transplantationsförsök med Borstnate. 1992:1 Malm, Torleif: Allokemisk påverkan från mucus hos åtta bruna makroalger på
epifytiska alger. 1992:2 Pontis, Cristina: Om groddknoppar och tandrötter. Funderingar kring en klonal
växt: Dentaria bulbifera. 1992:3 Agartz, Susanne: Optimal utkorsning hos Primula farinosa. 1992:4 Berglund, Anita: Ekologiska effekter av en parasitsvamp - Uromyces lineolatus på
Glaux maritima (Strandkrypa). 1992:5 Ehn, Maria: Distribution and tetrasporophytes in populations of Chondrus crispus
Stackhouse (Gigartinaceae, Rhodophyta) on the west coast of Sweden. 1992:6 Peterson, Torbjörn: Mollusc herbivory. 1993:1 Klásterská-Hedenberg, Martina: The influence of pH, N:P ratio and zooplankton
on the phytoplanctic composition in hypertrophic ponds in the Trebon-region, Czech Republic.
1994:1 Fröborg, Heléne: Pollination and seed set in Vaccinium and Andromeda. 1994:2 Eriksson, Åsa: Makrofossilanalys av förekomst och populationsdynamik hos Najas
flexilis i Sörmland. 1994:3 Klee, Irene: Effekter av kvävetillförsel på 6 vanliga arter i gran- och tallskog. 1995:1 Holm, Martin: Beståndshistorik - vad 492 träd på Fagerön i Uppland kan berätta. 1995:2 Löfgren, Anders: Distribution patterns and population structure of an economically
important Amazon palm, Jessenia bataua (Mart.) Burret ssp. bataua in Bolivia. 1995:3 Norberg, Ylva: Morphological variation in the reduced, free floating Fucus
vesiculosus, in the Baltic Proper. 1995:4 Hylander, Kristoffer & Hylander, Eva: Mount Zuquala - an upland forest of
Ethiopia. Floristic inventory and analysis of the state of conservation. 1996:1 Eriksson, Åsa: Plant species composition and diversity in semi-natural grasslands -
with special emphasis on effects of mycorrhiza. 1996:2 Kalvas, Arja: Morphological variation and reproduction in Fucus vesiculosus L.
populations. 1996:3 Andersson, Regina: Fågelspridda frukter kemiska och morfologiska egenskaper i
relation till fåglarnas val av frukter. 1996:4 Lindgren, Åsa: Restpopulationer, nykolonisation och diversitet hos växter i
naturbetesmarker i sörmländsk skogsbygd. 1996:5 Kiviniemi, Katariina: The ecological and evolutionary significance of the early life
cycle stages in plants, with special emphasis on seed dispersal. 1996:7 Franzén, Daniel: Fältskiktsförändringar i ädellövskog på Fagerön, Uppland,
beroende på igenväxning av gran och skogsavverkning. 1997:1 Wicksell, Maria: Flowering synchronization in the Ericaceae and the Empetraceae. 1997:2 Bolmgren, Kjell: A study of asynchrony in phenology - with a little help from
Frangula alnus. 1997:3 Kiviniemi, Katariina: A study of seed dispersal and recruitment of plants in a
fragmented habitat. 1997:4 Jakobsson, Anna: Fecundity and abundance - a comparative study of grassland
species. 1997:5 Löfgren, Per: Population dynamics and the influence of disturbance in the Carline
Thistle, Carlina vulgaris. 1998:1 Mattsson, Birgitta: The stress concept, exemplified by low salinity and other stress
factors in aquatic systems. 1998:2 Forsslund, Annika & Koffman, Anna: Species diversity of lichens on decaying
wood - A comparison between old-growth and managed forest.
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1998:3 Eriksson, Åsa: Recruitment processes, site history and abundance patterns of plants in semi-natural grasslands.
1998:4 Fröborg, Heléne: Biotic interactions in the recruitment phase of forest field layer plants.
1998:5 Löfgren, Anders: Spatial and temporal structure of genetic variation in plants. 1998:6 Holmén Bränn, Kristina: Limitations of recruitment in Trifolium repens. 1999:1 Mattsson, Birgitta: Salinity effects on different life cycle stages in Baltic and North
Sea Fucus vesiculosus L. 1999:2 Johannessen, Åse: Factors influencing vascular epiphyte composition in a lower
montane rain forest in Ecuador. An inventory with aspects of altitudinal distribution, moisture, dispersal and pollination.
1999:3 Fröborg, Heléne: Seedling recruitment in forest field layer plants: seed production, herbivory and local species dynamics.
1999:4 Franzén, Daniel: Processes determining plant species richness at different scales - examplified by grassland studies.
1999:5 Malm, Torleif: Factors regulating distribution patterns of fucoid seaweeds. A comparison between marine tidal and brackish atidal environments.
1999:6 Iversen, Therese: Flowering dynamics of the tropical tree Jacquinia nervosa. 1999:7 Isæus, Martin: Structuring factors for Fucus vesiculosus L. in Stockholm south
archipelago - a GIS application. 1999:8 Lannek, Joakim: Förändringar i vegetation och flora på öar i Norrtälje skärgård. 2000:1 Jakobsson, Anna: Explaining differences in geographic range size, with focus on
dispersal and speciation. 2000:2 Jakobsson, Anna: Comparative studies of colonisation ability and abundance in
semi-natural grassland and deciduous forest. 2000:3 Franzén, Daniel: Aspects of pattern, process and function of species richness in
Swedish seminatural grasslands. 2000:4 Öster, Mathias: The effects of habitat fragmentation on reproduction and population
structure in Ranunculus bulbosus. 2001:1 Lindborg, Regina: Projecting extinction risks in plants in a conservation context. 2001:2 Lindgren, Åsa: Herbivory effects at different levels of plant organisation; the
individual and the community. 2001:3 Lindborg, Regina: Forecasting the fate of plant species exposed to land use change. 2001:4 Bertilsson, Maria: Effects of habitat fragmentation on fitness components. 2001:5 Ryberg, Britta: Sustainability aspects on Oleoresin extraction from Dipterocarpus
alatus. 2001:6 Dahlgren, Stefan: Undersökning av fem havsvikar i Bergkvara skärgård, östra
egentliga Östersjön. 2001:7 Moen, Jon; Angerbjörn, Anders; Dinnetz, Patrik & Eriksson Ove: Biodiversitet i
fjällen ovan trädgränsen: Bakgrund och kunskapsläge. 2001:8 Vanhoenacker, Didrik: To be short or long. Floral and inflorescence traits of Bird`s
eye primrose Primula farinose, and interactions with pollinators and a seed predator. 2001:9 Wikström, Sofia: Plant invasions: are they possible to predict? 2001:10 von Zeipel, Hugo: Metapopulations and plant fitness in a titrophic system – seed
predation and population structure in Actaea spicata L. vary with population size. 2001:11 Forsén, Britt: Survival of Hordelymus europaéus and Bromus benekenii in a
deciduous forest under influence of forest management. 2001:12 Hedin, Elisabeth: Bedömningsgrunder för restaurering av lövängsrester i Norrtälje
kommun. 2002:1 Dahlgren, Stefan & Kautsky, Lena: Distribution and recent changes in benthic
29
macrovegetation in the Baltic Sea basins. – A literature review. 2002:2 Wikström, Sofia: Invasion history of Fucus evanescens C. Ag. in the Baltic Sea
region and effects on the native biota. 2002:3 Janson, Emma: The effect of fragment size and isolation on the abundance of Viola
tricolor in semi-natural grasslands. 2002:4 Bertilsson, Maria: Population persistance and individual fitness in Vicia pisiformis:
the effects of habitat quality, population size and isolation. 2002:5 Hedman, Irja: Hävdhistorik och artrikedom av kärlväxter i ängs- och hagmarker på
Singö, Fogdö och norra Väddö. 2002:6 Karlsson, Ann: Analys av florans förändring under de senaste hundra åren, ett
successionsförlopp i Norrtälje kommuns skärgård. 2002:7 Isæus, Martin: Factors affecting the large and small scale distribution of fucoids in
the Baltic Sea. 2003:1 Anagrius, Malin: Plant distribution patterns in an urban environment, Södermalm,
Stockholm. 2003:2 Persson, Christin: Artantal och abundans av lavar på askstammar – jämförelse
mellan betade och igenvuxna lövängsrester. 2003:3 Isæus, Martin: Wave impact on macroalgal communities. 2003:4 Jansson-Ask, Kristina: Betydelsen av pollen, resurser och ljustillgång för
reproduktiv framgång hos Storrams, Polygonatum multiflorum. 2003:5 Sundblad, Göran: Using GIS to simulate and examine effects of wave exposure on
submerged macrophyte vegetation. 2004:1 Strindell, Magnus: Abundansförändringar hos kärlväxter i ädellövskog – en
jämförelse av skötselåtgärder. 2004:2 Dahlgren, Johan P: Are metapopulation dynamics important for aquatic plants? 2004:3 Wahlstrand, Anna: Predicting the occurrence of Zostera marina in bays in the
Stockholm archipelago,northern Baltic proper. 2004:4 Råberg, Sonja: Competition from filamentous algae on Fucus vesiculosus –
negative effects and the implications on biodiversity of associated flora and fauna. 2004:5 Smaaland, John: Effects of phosphorous load by water run-off on submersed plant
communities in shallow bays in the Stockholm archipelago. 2004:6 Ramula Satu: Covariation among life history traits: implications for plant
population dynamics. 2004:7 Ramula, Satu: Population viability analysis for plants: Optimizing work effort and
the precision of estimates. 2004:8 Niklasson, Camilla: Effects of nutrient content and polybrominated phenols on the
reproduction of Idotea baltica and Gammarus ssp. 2004:9 Lönnberg, Karin: Flowering phenology and distribution in fleshy fruited plants. 2004:10 Almlöf, Anette: Miljöfaktorers inverkan på bladmossor i Fagersjöskogen, Farsta,
Stockholm. 2005:1 Hult, Anna: Factors affecting plant species composition on shores - A study made in
the Stockholm archipelago, Sweden. 2005:2 Vanhoenacker, Didrik: The evolutionary pollination ecology of Primula farinosa. 2005:3 von Zeipel, Hugo: The plant-animal interactions of Actea spicata in relation to
spatial context. 2005:4 Arvanitis, Leena T.: Butterfly seed predation. 2005:5 Öster, Mathias: Landscape effects on plant species diversity – a case study of
Antennaria dioica. 2005:6 Boalt, Elin: Ecosystem effects of large grazing herbivores: the role of nitrogen. 2005:7 Ohlson, Helena: The influence of landscape history, connectivity and area on
30
species diversity in semi-natural grasslands. 2005:8 Schmalholz, Martin: Patterns of variation in abundance and fecundity in the
endangered grassland annual Euphrasia rostkovia ssp. Fennica. 2005:9 Knutsson, Linda: Do ants select for larger seeds in Melampyrum nemorosum? 2006:1 Forslund, Helena: A comparison of resistance to herbivory between one exotic and
one native population of the brown alga Fucus evanescens. 2006:2 Nordqvist, Johanna: Effects of Ceratophyllum demersum L. on lake phytoplankton
composition. 2006:3 Lönnberg, Karin: Recruitment patterns, community assembly, and the evolution of
seed size. 2006:4 Mellbrand, Kajsa: Food webs across the waterline - Effects of marine subsidies on
coastal predators and ecosystems. 2006:5 Enskog, Maria: Effects of eutrophication and marine subsidies on terrestrial
invertebrates and plants. 2006:6 Dahlgren, Johan: Responses of forest herbs to the environment. 2006:7 Aggemyr, Elsa: The influence of landscape, field size and shape on plant species
diversity in grazed former arable fields. 2006:8 Hedlund, Kristina: Flodkräftor (Astacus astacus) i Bornsjön, en omnivors påverkan
på växter och snäckor. 2007:1 Eriksson, Ove: Naturbetesmarkernas växter- ekologi, artrikedom och
bevarandebiologi. 2007:2 Schmalholz, Martin: The occurrence and ecological role of refugia at different
spatial scales in a dynamic world. 2007:3 Vikström, Lina: Effects of local and regional variables on the flora in the former
semi-natural grasslands on Wäsby Golf club’s course. 2007:4 Hansen, Joakim: The role of submersed angiosperms and charophytes for aquatic
fauna communities. 2007:5 Johansson, Lena: Population dynamics of Gentianella campestris, effects of
grassland management, soil conditions and the history of the landscape 2007:6 von Euler, Tove: Sex related colour polymorphism in Antennaria dioica. 2007:7 Mellbrand, Kajsa: Bechcombers, landlubbers and able seemen: Effects of marine
subsidies on the roles of arthropod predators in coastal food webs. 2007:8 Hansen, Joakim: Distribution patterns of macroinvertebrates in vegetated, shallow,
soft-bottom bays of the Baltic Sea. 2007:9 Axemar, Hanna: An experimental study of plant habitat choices by
macroinvertebrates in brackish soft-bottom bays. 2007:10 Johnson, Samuel: The response of bryophytes to wildfire- to what extent do they
survive in-situ? 2007:11 Kolb, Gundula: The effects of cormorants on population dynamics and food web
structure on their nesting islands. 2007:12 Honkakangas, Jessica: Spring succession on shallow rocky shores in northern
Baltic proper. 2008:1 Gunnarsson, Karl: Påverkas Fucus radicans utbredning av Idotea baltica? 2008:2 Fjäder, Mathilda: Anlagda våtmarker i odlingslandskap- Hur påverkas
kärlväxternas diversitet? 2008:3 Schmalholz, Martin: Succession in boreal bryophyte communities – the role of
microtopography and post-harvest bottlenecks 2008:4 Jokinen, Kirsi: Recolonization patterns of boreal forest vegetation following a
severe flash flood.
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