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.

1

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.

2

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.

3

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.

4

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.

5

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.

6

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

7

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.

0

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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

8

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.

11

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-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

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0.0

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log 10

ind.

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-2

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# in

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0.0

Natural Artif icial

Natural Artif icial

log 10

# in

d. c

m-2

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-2.0

-1.0

0.0

Natural Artif icial

log 10

# in

d. c

m-2

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-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

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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.

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-2

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log 10

# in

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Natural Artif icial

log 10

# in

d. c

m-2

-4.0

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-2.0

-1.0

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Natural Artif icial

log 10

# in

d. c

m-2

Myriophyllum Chara Potamogeton

-4.0

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Natural Artif icial

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Entangled macrophytes (g dw )

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# in

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m-2

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Natural Artif icial

Natural Artif icial

log 10

# in

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Natural Artif icial

log 10

# in

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m-2

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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.

Följande publikationer ingår i utgivningen: 1978:1 Liljelund, Lars-Erik: Kompendium i matematik för ekologer. 1978:2 Carlsson, Lars: Vegetationen på Littejåkkadeltat vid Sitasjaure, Lule Lappmark. 1978:3 Tapper, Per-Göran: Den maritima lövskogen i Stockholms skärgård. 1978:4: Forsse, Erik: Vegetationskartans användbarhet vid detaljplanering av

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-

och Sitjasjaure; Norra Lule Lappmark. En översiktlig inventering med anledning av områdets exploatering för vattenkraftsändamål i Ritsemprojektet.

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.

28

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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