Metsovo, scattered plants of Phlomis fruticosa and Juniperus foetidissima are present. Also along the road, individuals of Pinus nigra grow, having spread from.
The University of Leeds
Faculty of Biological Sciences
How pollen content in lake sediment of different depths reflect vegetation at Ioannina basin
“Thesis Submitted in accordance with the requirements for the degree of Master of Science”
Chrysanthi Z. Michelaki
Abstract This study attempts to fill the lack of knowledge about the modern pollen rain in the most important site in southeast Europe for Quaternary vegetation history, Ioannina basin. Additionally, the study attempts to determine the scale in which local terrestrial and lake margin vegetation may contaminate the regional pollen signal. By following two different transects (SE and SW) across the lake of Ioannina and analysing 36 samples with pollen analysis, the modern pollen rain of the area was recorded. With a General Linear Model the spatially coherent difference in the number of taxa (taxa richness) among samples and the difference in the number of grains in each taxon among the samples were tested. The modern pollen record created by this study contains all the important taxa that feature in the prehistorical records of Ioannina basin, though some differences in the relative abundances of some taxa were found from the Holocene pollen record. No systematic variability in the taxa-richness and the relative abundances of each taxon was found among the different transects and between the sample points of different depths and distance from the edge.
Acknowledgements At that point I wish to acknowledge Dr Ian T. Lawson for the supervision of this project; Prof Chronis Tzedakis for the general mentorship and Prof Oliver Phillips for the helpful comments on the draft of this study. Additionally, I would like to thank V. Margari and K. Roucoux for the practical support and Grigorious, Natalia, Varun, Tim and Alice for any help they offered me. Finally I want to acknowledge Marry Currie Fellowship for the financial help.
I
Table of contents
Abstract
I
Acknowledgements
I
Table of contents
II
List of figures
IV
List of tables
VI
1. Introduction
1
1.1. Pollen grains
1
1.2. Modern Pollen analysis
3
1.3. Area of study
3
1.4. Previous palynological research
5
1.5. Objectives
8
2. Methods
9
2.1. Sampling
9
2.2. Treatment of samples
10
2.3. Pollen Counting
11
2.4. Pollen diagrams
12
2.5. Pollen Proportions relative to total
12
2.6. Pollen Densities relative to the exotic
13
2.7. Statistical Analysis
13
3. Results
14
3.1. Description of modern pollen rain in Ioannina basin
14
3.2. The modern-day pollen signal in Ioannina Lake
27
II
4. Discussion
29
4.1. The modern pollen rain in Ioannina basin
29
4.2. Pollen signal in Ioannina Lake
30
4.3. Further study
31
References Appendix
32
III
List of figures: Figure 1: a. Dryopteris (no apertures), b. Gramineae (one pore), c. Mentha (many colpi), d. Rumex (3 colpi each combined with a pore)
2
Figure 2: Pollen percentages for the uppermost 23.65 m of core I-284
7
Figure 3 A: Pollen diagram showing percentages of each arboreal taxon at each sampled point along the first transect
14
Figure 3 B: Pollen diagram showing percentages of each arboreal taxon at each sampled point along the second transect
15
Figure 4 A: Pollen diagram showing percentages of each shrub taxon at each sampled point along the first transect
15
Figure 4 B: Pollen diagram showing percentages of each shrub taxon at each sampled point along the second transect
16
Figure 5 A: Pollen diagram showing percentages of each herb taxon at each sampled point along the first transect
16
Figure 5 B: Pollen diagram showing percentages of each herb taxon at each sampled point along the second transect
17
Figure 6 A: Pollen diagram showing percentages of each heath taxa at each sampled point along the first transect
17
Figure 6 B: Pollen diagram showing percentages of heath each taxa at each sampled point along the second transect
18
Figure 7 A: Summary pollen diagram showing percentages of the main plant types for each sample point of the first transect
18
Figure 7 B: Summary pollen diagram showing percentages of the main plant types for each sample point of the second transect
19
3
Figure 8 A: Pollen diagram showing pollen grains per cm of each sample point of the arboreal taxa along the first transect
20
Figure 8 B: Pollen diagram showing pollen grains per cm3 of each sample point of the arboreal taxa along the second transect
21 3
Figure 9 A: Pollen diagram showing pollen grains per cm of each sample point of the shrub taxa along the first transect
21
Figure 9 B: Pollen diagram showing pollen grains per cm3 of each sample point of the shrub taxa along the second transect
22
IV
Figure 10 A: Pollen diagram showing pollen grains per cm3 of each sample point of the herb taxa along the first transect
22 3
Figure 10 B: Pollen diagram showing pollen grains per cm of each sample point of the herb taxa along the second transect
23
Figure 11 A: Pollen diagram showing pollen grains per cm3 of each sample point of the heath taxa along the first transect
23 3
Figure 11 B: Pollen diagram showing pollen grains per cm of each sample point of the heath taxa along the second transect
24
Figure 12 A: Summary pollen diagram showing pollen grains per cm3 for each sample point of the main plant types of the first transect
24 3
Figure 12 B: Summary pollen diagram showing pollen grains per cm for each sample point of the main plant types of the second transect
25
Figure 13: Spatial bubble graphs with the arboreal, herb, shrub and heath pollen concentrations for both transects for each sample point
26
Figure 14: Pie charts with the proportions of each plant type to the total pollen sum of the samples for the first transect, the second transect, and for both transects together
27
V
List of tables:
Table 1: Taxa list of modern pollen record in Ioannina Lake
11
Table 2: T-test: Paired Samples Test for the number of taxa between the two transects
32
Table 3 A: General Linear Model: Univariate Analysis of Variance, Tests of Between-Subjects Effects for the taxon-richness along the first transect including the first sampling point. The last corrected model presented where depth seams to be significant important
32
Table 3 B: General Linear Model: Univariate Analysis of Variance, Tests of Between-Subjects Effects for the taxon-richness along the first transect excluding the first sampling point. The last corrected model presented where depth isn’t anymore significant important
32
Table 4: General Linear Model: Univariate Analysis of Variance, Tests of Between-Subjects Effects for the taxon-richness along the second transect. The last corrected model presented
33
Table 4: General Linear Model: Univariate Analysis of Variance, Tests of Between-Subjects Effects for the taxon-richness along all the sampling points of the both transects. The last corrected model presented
33
VI
1. Introduction Ecology can be defined as the study of the living organisms in relation with their present environment. By that we can define palaeoecology as the study of past organisms in relation with the environment they used to live in (Birks & Birks, 1980). Palaeoecology in strongly linked both with biology and geology, but even though it shares similar objectives with ecology different working methods are applied because of certain difficulties. Most importantly, past ecosystems cannot be observed directly. So palaeoecologists are restricted to the study of those organisms that are preserved as fossils, with little control over the sample limits in time and space, unable to repeat an observation and long periods of time associated with each sample (typically 20-50 years resolution) (Birks and Gordon, 1985). So in practice palaeoecology is concerned with the reconstruction of past environments and ecosystems. To reconstruct past environments, firstly the type of organisms or parts of organisms that they are going to be observed, recorded and counted must be decided (Birks & Birks, 1980). In the case that pollen grains produced by seed plants, angiosperms and gymnosperms, and spores, produced by pteridophytes, bryophytes, algae and fungi, are the object of the study, then we are concerned with palynology. Palynology is based on features of the structure and morphology of ancient and modern pollen grains and spores (Moore et al., 1991). 1.1. Pollen grains A pollen grain contains the male gamete of angiosperm and gymnosperm plants, while a spore is the resting and dispersal phase of cryptogams (Moore et al., 1991). Pollen grains and spores are about 10-100 microns across and are produced in great abundance by vascular plants (Birks and Gordon, 1985). Different plants produce different amount of pollen or spores. In general wind-pollinated species produce more pollen than insect-pollinated species (Birks & Birks, 1980). In any case only few of these are actually used for fertilisation, while the majority of grains and spores after being well mixed in atmosphere by the turbulent flow of the wind reach the ground. The atmospheric mixture often results in a uniform pollen rain within an area (Birks and Gordon, 1985). When pollen and spores reach waterlogged areas, such as bogs, fens, lake bottoms or the ocean floor, they may become fossilized because of the anoxic conditions.
1
The wall of the pollen grains in angiosperms and gymnosperms plants as well as the spores’ wall in lower plants has the important function of protecting the genetic material until the time of reproduction (Moore et al., 1991). At the same time it appears to have a very complicated structure, equipped with apertures and with sculptured surface, the functional significance of which is hard to explain. A unique combination of certain characteristics of grain’s exine is what allows us to identify pollen. Apertures are missing parts of the grain’s exine (Moore et al., 1991). There are two different types of apertures, pori (pores) and colpi (furrows). Grains can appear with any, one or more pori or colpi or a mixture of them (Birks & Birks, 1980). During transport of the pollen from anther to stigma grains often suffer from mechanical stress. It is possible that apertures help grains to resist hydration and rehydration avoiding battering. Many apertures can also help the passage of the germinating tube as well as the recognition proteins. (Moore et al., 1991)
a.
b.
c.
d.
Figure 1: a. Dryopteris (no apertures), b. Gramineae (one pore), c. Mentha (many colpi), d. Rumex (3 colpi each combined with a pore). The elaboration of grain’s exine is called sculpture (Birks & Birks, 1980). There is a great variety on pollen’s sculpture with many different structures and patterns. Researchers had tried to group those patterns into categories that help classification. It is believed that the sculpture types (such as psilate, scabrate, rugulate, striate, etc.) affect the ways of pollen’s transportation (Moore et al., 1991). Other characteristics that help in classification are the shape and the size of the grain. Shape is important when it is extremely unique, but otherwise should be treated with scepticism as it may vary within species, and may be altered by environmental conditions or the treatment procedure (Moore et al., 1991). Pollen size ranges between 5 - 100 µm, with most grains around 30 µm. Size can be useful to distinguish species, especially when two grains are very similar. (Birks & Birks, 1980)
2
1.2. Modern Pollen analysis Pollen analysis provides the data for reconstruction of past floras, plant populations and vegetation communities of the area surrounding the site of study. The interpretation of such data requires knowledge of the present ecology of the plant taxa, as well as information on the relationships between the modern pollen spectra and the composition of the vegetation from which the spectra are derived (Birks and Gordon, 1985). This relation can be studied by comparing the extant vegetation with its present pollen rain (Bottema, 1974). It is assumed that a quantitative relationship exist between the number of pollen grains of a taxon deposited in the sediment at a site and the number of individuals of that taxon in the vegetation surrounding that site (Birks and Gordon, 1985). In sites that information on the relative pollen production and dispersal of various taxa is provided, the fossil spectra can be compared with modern analogues (Bottema, 1974). When they show the same pollen composition a good basis for the reconstruction of past vegetations is present. Of course the possibility exists that no modern analogue can be found. In Greece and other Mediterranean countries, reconstruction of past vegetations is difficult because of the long-term human press in these areas (Bottema, 1974). 1.3. Area of study This survey was conducted in Ioannina Lake, (Pamvotida), in Greece.
The
property.
lake
Lake
is
public
Pamvotida,
situated in northwest Greece (39o 40’ 00” N, 20o 53’ 0” E) between the town of Ioannina and the mountain Mitsikeli, is a Natura 2000 protected area with the code
number
GR2130005.
It
occupies the southern end of the basin formed in the Ioannina plateau, at 480 m altitude (1,Lawson et al., 2004) The basin is 35 km long in the NNW – SSE axis and http://natura.minenv.gr/natura/, Conservation and Environment Researchers’ Forum, last visit 08/07
1
3
from 3 to 10 km wide. It is surrounded to the west by the Tomarochoria Mountains (1173 m), to the northeast by the Mitsikeli Mountain (1810 m) and from the northwest to southeast by the Pindus Mountains. The basin’s floor is flat with elevational variation of less than 10 m (Lawson et al., 2004). The substrate of the basin is mainly limestone with siliceous components while at northwest and south alluvial sediment are present (1, Bottema, 1974). The lake itself covers an area of 1,920 ha, is 11 km long by 5 km wide and has a maximum depth of 11 m at the area between the island and the northeast bank, while at its centre the lake has a maximum depth of 7.5 m (1, Lawson et al., 2004). The small island named Nisos Ioanninon in the northeaster part of Ioannina Lake has a small village on it, with approximately 480 inhabitants. Till early ‘60 another lake with many marshes, Lapsista, was situated north of the town of Ioannina. Lapsista Lake has since been drained and the area was taken for cultivation.
1
Pamvotis Lake is what remains of the lake once filled the basin. (Lawson et al., 2004) From a hydrological point of view the basin is closed since it has no superficial outlet or drainage (Tzedakis et al., 2003). Ioannina Lake has been formed from the collection of the water of the basin 1. Run–off from the surrounding Mountains to the east is minimal. Surface waters cycling through the sinkholes and springs of Mountain Mitsikeli feed the Lake on its north and east banks. (1, Anagnostidis et al., 1980) The excess water of the lake is channelled through swallow holes in the Kalamas River 1. Run-off from the north–west lowlands is more substantial (Anagnostidis et al., 1980). The climate of this area is unusually wet for the Mediterranean region, being characterized by an average of 1200 mm of annual precipitation (Tzedakis, 1993), much greater than for the eastern and southern parts of Greece because of the moist warm Adriatic air that is forced upwards by the Pindus Mountains (Lawson et al., 2004). Winters are rather cold and summers not too hot in comparison with the rest of Greece (Bottema, 1974). The lake banks and the island coasts are covered with dense extensive reed communities - either pure Phragmitetum with Phragmites communis, or transformed to Scirpeto-Phragmitetum. The Scirpeto-Phragmitetum zone has an average width of 30-40 m, while the Phragmitetum zone has an average width of 50-70 m. On the northeast banks, where the Kryoneri (or Drabatova) spring flows, the Scirpetum-Phragmitetum association forms a zone of about 100 m width
4
composed nearly exclusively of Phragmites communis. In the periphery of the lake remnants of native woody vegetation are dispersed - primarily Salix alba and Salix
cinerea, as well as Ulmus campestris. Also, aquatic associations of MyriophylletoNupharetum and Potamogetonetum are developed. In the lake, associations of
Nymphaea albae are formed while Iris pseudacorus forms patches near the reed communities. On the island coasts, in addition to the Scirpetum-Phragmitetum and the pure Phragmitetum communities, Typha domingensis and Sparganium
erectum occur. Sparganium erectum is also abundant on the banks of an irrigation channel within the lake area. The hill of Ioannina Island has been reforested with
Pinus nigra. In the substantially bare area, between the lake and the road to Metsovo, scattered plants of Phlomis fruticosa and Juniperus foetidissima are present. Also along the road, individuals of Pinus nigra grow, having spread from the reforested area. (1, Gkargkoulas-Bakakis et al., 2003, Kasiomi, 1994) The mountain Mitsikeli (Oros Mitsikeli) that dominates the Ioannina basin is also a Natura 2000 protected area with the code number GR2130008. The western part of the mountain is bare due to repeated fires. In the higher altitudes Abies
borisii-regis occurs, either forming sparse stands or mixed with Quercus pubescens. Stands of Quercus pubescens appear above the maquis zone or in some places are mixed with Quercus coccifera and Juniperus oxycedrus. Formations with dwarf thickets of J. oxycedrus, Q. coccifera and Phlomis fruticosa occur in the lower altitudes. On the southwestern side of Mitsikeli, limited reforestation has been conducted to protect the Ioannina Lake from sedimentation with eroded material. So a reforested zone of Pinus nigra, about 500 m long, occurs in the area of Amfithea, and mixed reforested areas with P. nigra and Cupressus sempervirens can be seen in the area of the village of Ligiades. At the eastern side of Mitsikeli extensive formations dominated by characteristic species of Ostryo-Carpinion and Quercion frainetto, such as Ostrya carpinifolia, Carpinus orientalis, Fraxinus ornus,
Quercus pubescens, Corylus sp., Acer sp. etc., occur. (1, Gkargkoulas-Bakakis et al., 2003, Kasiomi, 1994) 1.4. Previous palynological research Four pollen sequences from Ioannina basin have been taken up to present. The first pollen diagrams produced by Bottema (1974) from the two cores he took http://natura.minenv.gr/natura/, Conservation and Environment Researchers’ Forum, last visit 08/07
1
5
designated as Ioannina-I and Ioannina-II. The next two cores were taken by IGME (Greek Institute for Geology and Mineral Exploration) in 1989, cores I-249 and I-284. Tzedakis (1991, 1993, 1994) studied the first one as part of this survey, looking at pollen, magnetic susceptibility and loss-on-ignition. Unfortunately, this core was discarded by IGME. Later, more detailed work has been undertaken on the palynology, malacology and sedimentology of the second long core, I-284, by Frogley and Tzedakis (Frogley 1997; Frogley and Tzedakis 1999), as well as by Lawson (Lawson, 2001; Lawson et al., 2004). Beach deposits in Kastritsa cave and around the basin have been studied by, amongst others, Higgs and Vita-Finzi (1966), Higgs et al. (1967), Higgs (1978), Prentice et al. (1992a), and Galanidou et al. (2000). The past pollen spectra for Ioannina basin starts 25,100 14C years before present. During the full Glacial at ca 25,100 to 15,600 14C BP (Figure 2, periods 12 to 11), vegetation is dominated by herb taxa mainly Gramineae, Artemisia,
Chenopodiaceae (cool steppe) and Cruciferae, Labiatea, Crassulaceae, and some tree taxa as Quercus (deciduous spp) and Pinus. At the Lateglacial ca 15,600 to 9,900 14C BP (Figure 2, periods 10 to 8), all the thermophilous taxa start to expand, mostly Quercus (deciduous spp) and Pinus as well as Oxyria, Corylus, Ostrya, and
Fraxinous. Additionally Artemisia, Chenopodiacea and Gramineae increase this period. Through the early Holocene ca 9,900 to 5,500 14C BP (Figure 2, periods 7 to 5), woodlands are dominated by deciduous species of Quercus, Ostrya, Carpinus,
Fraxinus, Corylus and Pistacia. (Lawson et al., 2004) As the human press increases at the second half of Holocene ca 5,500 14C BP till present (Figure 2, periods 4 to 1), a rapid decrease in arboreal pollen observed mainly in Abies, Pinus and the deciduous species of Quercus. Various other taxa point to expansion because of the pastoralism and the agriculture. On the other hand other taxa that either escape from agriculture lands or resist to the grazing expand. Such as evergreen species of Quercus, Phillyrea, Castanea, Juglans,
Plantago, Rumex, Umbelliferae, Chenopodiaceae and Artemisia. (Lawson et al., 2004) Bottema (1974) surface sample study from sites all over Greece is trying to predict the representation of various plant taxa in the pollen precipitation. Evergreen species of Quercus seems to be in general over-represented, because even young individuals of the species flower abundantly. Olea has a good pollen dispersal so can be always found in the pollen record. Phillyrea has a moderate pollen
6
production but poor pollen dispersal so is normally under-represented. A degraded deciduous oak forest is badly represented n the pollen rain. Carpinus and Ostrya’s
Figure 2: Pollen percentages for the uppermost 23.65 m of core I-284. The main sum includes all terrestrial trees, shrubs, herbs and heaths. (Lawson et al., 2004)
7
pollen production is high and well transported, but low shrub are badly represented in the pollen record. Fraxinus is quite represented in the pollen rain. Buxus has a rather good pollen production but the small size of the shrub is a handicap to its dispersal. Juglans, Artemisia and Chenopodiaceae are well-represented in the pollen rain. Plantago is over-represented. Gramineae pollen is normally found in percentages 20 to 30% or the pollen sum. Umbelliferae, Tubuliflorae and
Liguliflorae and in general all these zoogamous species increased as the proportion of other taxa decreased as a result of deforestation, grazing and farming. Pteridium is distinctly under-represented. (Bottema, 1974) 1.5. Objectives 1. This study attempts to fill the lack of knowledge about the modern pollen rain in the most important site in southeast Europe for Quaternary vegetation history, Ioannina basin. My hypothesis is that the modern pollen record has no analogue at any point in the paleo-record, which dates back over 25,100
14
C years before
present. To test this hypothesis three questions will be addressed. Firstly, are there any vegetation taxa important in the past that are missing for the modern pollen record? Secondly, are there vegetation taxa important in the modern pollen record that are absent in the past records? And finally, are there significant differences in the relative abundances of the important taxa between the modern and the past records? 2. Additionally, the study will attempt to determine the scale in which local terrestrial and lake margin vegetation may contaminate the regional pollen signal. To test the null hypothesis (regional pollen signal uncontaminated by local vegetation), two questions will be asked. Is there a spatially coherent difference in the number of taxa (taxa richness) among samples? And, is there a difference in the number of grains in each taxon among the samples?
8
2. Methods 2.1. Sampling In this study a central purpose is to explore whether there are spatial changes in pollen content of different cores taken from Ioannina basin, and if so what factors might explain these. Thus collection of surface samples from the lake sediment was judged as the most appropriate method, bearing in mind the limits of taphonomy. According to Moore et al. (1991) the concentration of pollen grains in a single observation point can be influenced by the depth of the lake or the distance from the bank. In
order
to
test
the
applications of this theory in Ioannina lake, 36 samples were collected by following two different transects (SE and SW) across the lake. To help test my hypotheses, for each sample point I record the distance from the edge, the depth of the sample, and the transect to which it belongs. The first observation point in each transect was at the edge of the reed bed since it was impossible to reach the bank. After that samples were taken every 100 m until 1200m distance from the edge. Then, since the lake’s depth stabilised, from this point to the centre of the lake samples were taken only every 200 m. In the first transect the bank was approximately 200 m further from the first observation point and in the second 50 m. The minimum depth was 2 m in the first transect and 3m in the second; the maximum depth was 7.5 m at the lake’s centre. The samples were placed in separate polythene bags during transportation from the field to the laboratory, carefully sealed to ensure that they did not dry or contaminate each other. Each bag was marked with water-resistant ink. In the lab they were kept refrigerated until the treatment.
9
2.2. Treatment of samples All lab work was carried out with lab coat, latex gloves and safety goggles. The pollen preparation laboratory is fitted with an air filtration system to avoid the intrusion of modern pollen that would contaminate the samples. With a calibrated volumetric sampler 1 cm2 was taken from each sample. The samples were placed in 50 ml centrifuge tubes. 2 spike tablets, with 10.679 Lycopodium grains each were added in each tube in order to be able to quantify the concentration of pollen grains for each sample. The 50 ml tubes were filed with 7% HCL and placed into a hot water bath for 20 minutes in order to dissolve any carbonates. After being balanced, centrifuged, decanted and water-washed, the tubes were filled with 10% NaOH and placed again in the hot water bath but only for a few minutes this time. This is necessary to alter the pH to alkaline and to dissolve the humic acids. This stage must be short because the NaOH may attack the pollen grains. Next, the samples were sieved, water-washed, balanced, centrifuged and decanted. A wash with 7% HCL followed to acidify samples again and to make sure there are no residual carbonates left. Then hot HF was dispensed into each tube until 2/3 full and the samples were left for 2 hours in the hot water bath (80 oC) to remove silicates, and for 1 hour after that with 7% HCL to remove silicate residues and flourosilicates from the residues. A final water wash was required and the samples where left like that overnight. At the second day of each preparation a wash with CH3COOH removed water from samples for the acetolysis. 5 ml of the acetolysis mixture (9 parts Acetic anhydride acid and 1 part Concentrated Sulphuric acid) were placed in each tube and the samples were left in the water bath for 3 minutes. Acetolysis removes cellulose and polysaccharides by oxidation and if left longer will damage the pollen grains. At that point another wash with CH3COOH was necessary to stop the acetolysis reaction. After a water-wash, a 10% NaOH wash turned the pH alkaline again. After another water-wash, 0.2% aqueous safranin was added to the samples to stain the pollen grains red and make the counting procedure easier. The remaining water was removed from the samples with a TBA wash. Finally the remainders were placed in labelled vials and few drops of silicon oil were added. When the TBA was absolutely evaporated, one or two days later, samples were ready to be spread in microscope slides.
10
All lab work was carried out following the instructions of the University of Leeds, Department of Geography, Pollen Preparation Laboratory’s protocol and under the supervision of John Corr. 2.3. Pollen Counting Pollen grains were identified with aid of two keys (Moore et al. 1991, Chester and Raine 2001). Slides with sample material were placed in microscopy under x400 magnification. All pollen grains and spores in field of view were counted in linear traverses from one edge of the slide to the other, to overcome possible nonrandom distribution of the pollen grains (Birks and Gordon, 1985). For some grains higher (x1000) magnification using an oil-immersion objective was necessary. In each sample 300 pollen grains were counted. That number of grains was suggested by Maher (1972) as acceptable for the 95% confidence limit of the total pollen density. In that pollen sum of 300 grains all the tree, herb, shrub and heath taxa that were found in the samples are included. Pollen grains from aquatic plants and algae and spores were also counted but excluded from the sum because they are locally produced from the open lake environment and not the subject of this study (Birks & Birks, 1980). All the exotic grains (Lycopodium grains) that were added during the treatment procedure and found in the field of view were counted too but excluded from the sum. The references slides are available to anyone. Table 1: Taxa list of modern pollen record in Ioannina Lake. Taxon Trees:
Taxon Herb:
Betula pubescens Alnus Pinus Fraxinus excelsior Carpinus Fagus Quercus (deciduous spp.) Ulmus Juglans Olea Phillyrea Tilia Quercus (evergreen spp.) Ostrya Abies
Gramineae Cereal - cf Hordeum t Cyperaceae Compositae tubululiflorae Artemisia Centaurea Compositae liguliflorae Caryaophyllaceae Chenopodiaceae Cruciferae Filipendula Leguminosae Plantago undiff Plantago lanceolata Ranunculus
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Heath: Ericaceae undiff Spores Pteropsida trilete undiff Pteropsida monolete undiff Aquatic: Myriophyllum alterniflorum Nymphaea Potamogeton subg Potamogeton Sparganium Nuphar Typha latifolia Typha augustifolia Pediastrum Exotic
Rosaceae Rubiaceae Rumex Saxifragaceae Thalictrum Urtica undiff Mentha t Umbelliferae Shrub: Corylus Juniperus Salix Hedera helix Ilex Ephedra distachya Buxus
2.4. Pollen diagrams Pollen analytical data are effectively represented in pollen diagrams. Pollen diagrams are made by a series of graphs of the different pollen taxa (Birks & Birks, 1980). In a diagram of contemporaneous pollen, the vertical axis represents the ordering of the surface samples (distance from the edge in this case) (Birks and Gordon, 1985) and the horizontal axis the abundances of each pollen taxon, either as proportions, percentages of a general sum, or as absolute values independent of each other (Moore et al., 1991). The abundances of the pollen taxa in each sample are indicated by a bar histogram. Taxa in diagrams are arranged in vegetation groups, with arboreal types first, followed by shrubs, then herbs and finally heath. In each vegetation group taxa are just displayed by the order they were met during the pollen counting. 2.5. Pollen Proportions relative to total Each taxon was expressed as a percentage of the pollen sum for each sample. Additionally each plant group (tree, grass etc.) was expressed as a percentage of the pollen sum for each sample. In order to be able to present as percentages the aquatic taxa, spores and algae, to the pollen sum of the sample I first added separately the pollen sum of the aquatic taxa, spores, or algae correspondingly, to avoid percentages higher than a hundred (Birks and Gordon, 1985).
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2.6. Pollen Densities relative to the exotic I also expressed in the diagrams,, the actual densities of every taxon and vegetation group in each sample. Since the number of marked grains (exotic) that where added to the samples was known, the actual number of grains was calculated from the observed proportions, and hence the density of grains in each sample.
(Berglund, 1986) 2.7. Statistical Analysis Spatial patterns among the samples were assessed with the use of SPSS 14.0 for Windows. The difference in the number of taxa between the two transects is tested with a paired samples t-test for each distance from vegetation edge category, since the data are continuous and normally distributed (Dytham, 1999). The variances of the two transects are homogeneous Additionally, a general Linear Model (GLM, univariate) with dependent variable the total taxa richness in each sample and predictor variables the depth and the distance from the edge was developed, seperately for each transect. Finally, a general Linear model (GLM, multivariate) with dependant variables the percentages of pollen grains and separately the number of pollen grains per cc of sample of all the found taxa, fixed factor the transect in which each sample belongs and covariates the depth and the distance from the edge, was constructed. The effect of depth, distance from the edge, transect and the combined effects of these factors in each transect were tested. In order to achieve a reasonable sample for statistical analysis and reduce problems associated with multiple hypothesis testing, all taxa with less that a grain per sample on average were excluded from the analysis. This resulted in 29 of the 57 taxa found in the pollen counting being excluded: Fagus, Ulmus, Tilia, Hedera helix, Buxus, Artemisia,
Centaurea, Cruciferaea, Filipendula, Plantago lanceolata, Ranunculus, Rubiaceae, Rumex, Saxifragaceae, Thalictrum, Urtica, Menta, Umbeliferae, and all the aquatic taxa and spores.
13
3. Results 3.1. Description of modern pollen rain in Ioannina basin By following two different transects across the lake of Ioannina and analysing 36 samples, the modern pollen rain of the area was recorded. The next figures present, firstly, the pollen proportions and, secondly, the actual number of pollen grains per cm3 of sample for all the tree (Figures 3, A, B and 8, A, B), shrub (Figures 4, A, B and 9, A, B), herb (Figures 5, A, B and 10, A, B) and heath (Figures 6, A, B and 11, A, B) species found in each sample, plotted according to the distance from the reedbed edge. Summary pollen diagrams follow showing the main plant types (Figures 7, A, B and 12 A, B). Additionally, each plant type’s proportions are plotted in separate spatial bubble graphs, with the proportion value for each sample displayed as the size of the bubble marker (Figure 13). Finally, the concentrations of each vegetation type as a fraction of the total pollen concentration of the samples are displayed in pie charts, both separately for each transect and in total for the pollen rain of the area (Figure 14).
Figure 3 A: Pollen diagram showing percentages of each arboreal taxon at each sampled point along the first transect.
14
Figure 3 B: Pollen diagram showing percentages of each arboreal taxon at each sampled point along the second transect.
Figure 4 A: Pollen diagram showing percentages of each shrub taxon at each sampled point along the first transect.
15
Figure 4 B: Pollen diagram showing percentages of each shrub taxon at each sampled point along the second transect.
Figure 5 A: Pollen diagram showing percentages of each herb taxon at each sampled point along the first transect.
16
Figure 5 B: Pollen diagram showing percentages of each herb taxon at each sampled point along the second transect.
Figure 6 A: Pollen diagram showing percentages of each heath taxa at each sampled point along the first transect.
17
Figure 6 B: Pollen diagram showing percentages of the each heath taxa at each sampled point along the second transect.
Figure 7 A: Summary pollen diagram showing percentages of the main plant types for each sample point of the first transect. 18
Figure 7 B: Summary pollen diagram showing percentages of the main plant types for each sample point of the second transect.
Pollen analytical data are usually presented as percentages of some specified sum. This conversion to percentages removes the effects of the different total number of pollen grains among the samples (Birks and Gordon, 1985). It does, however, introduce another problem, when one pollen’s type relative frequency increase, some other type or types decrease. Thus, in this survey it was decided that pollen data should be presented in both ways.
19
Figure 8 A: Pollen diagram showing pollen grains per cm3 of each sample point of the arboreal taxa along the first transect.
20
Figure 8 B: Pollen diagram showing pollen grains per cm3 of each sample point of the arboreal taxa along the second transect.
Figure 9 A: Pollen diagram showing pollen grains per cm3 of each sample point of the shrub taxa along the first transect.
21
Figure 9 B: Pollen diagram showing pollen grains per cm3 of each sample point of the shrub taxa along the second transect.
Figure 10 A: Pollen diagram showing pollen grains per cm3 of each sample point of the herb taxa along the first transect.
22
Figure 10 B: Pollen diagram showing pollen grains per cm3 of each sample point of the herb taxa along the second transect.
Figure 11 A: Pollen diagram showing pollen grains per cm3 of each sample point of the heath taxa along the first transect. 23
Figure 11 B: Pollen diagram showing pollen grains per cm3 of each sample point of the heath taxa along the second transect.
Figure 12 A: Summary pollen diagram showing pollen grains per cm3 for each sample point of the main plant types of the first transect.
24
Figure 12 B: Summary pollen diagram showing pollen grains per cm3 for each sample point of the main plant types of the second transect.
25
Figure 13: Spatial bubble graphs with the arboreal, herb, shrub and heath pollen concentrations for both transects for each sample point.
26
Figure 14: Pie charts with the proportions of each plant type to the total pollen sum of the samples for the first transect, the second transect, and for both transects together.
The above figures constitute a detailed presentation of the modern pollen rain in Ioannina basin. Figures showing the percentages and the number of pollen grains per cm3 of the aquatic species, spores and algae are not included since they appear in rather small concentrations in the samples. 3.2. The modern-day pollen signal in Ioannina Lake The number of taxa do not differ significantly between the two transects (ttest: t=0.975, df=16, p=0.344). With the General Linear Model I specified the factors that affect taxon richness in the two transects. Taxon richness along Transect 2 wasn’t significantly affected by either the depth of the sample or the distance from the edge; neither was it affected by the interaction of these two factors. However
27
the first transect appears to be affected by the depth of the sample (univariate analysis of variance: F=5.534, df=1, Sig=0.033). It is possible that the first sampling point of the transect is affected by “sediment focusing”. If first sample point of the first transect is removed and the GLM analysis repeated, no factor appears to significantly affect the taxa richness. GLM analysis repeated taking in mind all the sampling points this time (even the first sample point of the first transect, which was eliminated before), with transect as a fixed factor. No significant result came from any factor or combination of factors. A multivariate analysis of variance was also applied to determine which factors affect the percentages and the number of pollen grains per cm3 of sample for each of 28 taxa that passed the abundance threshold (see Methods). However the large number of taxa involved means that a correction still needs to be applied to reduce the chance of inappropriate rejection of the null hypothesos - without a correction there is a chance of 0.7622 (76.22%) of finding one or more significant differences in 28 tests, by chance alone. Results were therefore adjusted using a Bonferroni correction. This Bonferroni adjustment lowers the alpha for each test to 0.001785714.
2
At these levels, no taxon displayed any relationship between either
proportion or absolute abundance of grains with the depth of the sample, the distance from the edge, or the location of the transect.
Therefore both the
percentages as well as the concentrations of grains in each taxon appear to be welldistributed through the sample area.
http://www.quantitativeskills.com/sisa/calculations/bonfer.htm, Bonferroni adjustment online. Adjustment for multiple comparisons.
2
28
4. Discussion This study presented the first modern pollen record for the Ioannina region, filling a significant gap. This location has emerged as one of the most important paleo-ecological sites in Europe, and work here has been used to suggest different interpretations of past European vegetation (Lawson et al., 2004; Tzedakis 1991, 1993, 1994) and the western Balkan region may have been the most important refugium for warm temperate, mesic plants and animals especially during the last glacial (Tzedakis, 1994). These studies have been based mainly on just 2 cores (I-284 and I-249). My work can therefore help to test interpretation of fossil pollen record and reconstruction of vegetation and climate in the past. The basis for this approach is the assumption that surface pollen records reflect plant and regional vegetation patterns (Yu et al., 2004). Additionally, the present research can help to test the accuracy of the results emerging from these two cores. 4.1. The modern pollen rain in Ioannina basin The modern pollen record created by this study contains all the important taxa that feature in the prehistorical records of Ioannina basin (Lawson et al., 2004 and Bottema, 1974). On the other hand, some of the important taxa found here in the past, such as Fraxinus ornus, Pistacia, Castanea and Platanus, are absent from the present pollen rain (see Figure 2). These taxa are also missing from the modern vegetation in the hydrological catchment. The last glacial pollen record from Ioannina basin as it is expected saws significant differences from the modern one (see Figure 2, periods 12 to 8). It is dominated by herb taxa with Gramineae, Artemisia, Chenopodiaceae, Cruciferae,
Labiatea and Crassulaceae, in much greater abundances than in present. The arboreal pollen is mainly dominated by Quercus (deciduous spp) and Pinus but with percentages close to zero. The Holocene pollen record is much closer to the modern one (see Figure 2, periods 7 to 1). The only taxa that present substantial differences in their relative abundances between the modern and past records are Fraxinus excelsior and the evergreen species of Quercus. Fraxinus appears to be well represented in the pollen rain and evergreen species of Quercus are rather over-represented (Bottema, 1974). In the modern record they show much greater abundance than in the past records.
29
Fraxinus excelsior is a wind-dispersed species, with great pollen-immigration rate (Gerard et al., 2006). Individuals of these species have also been used in recent years for reforestation of the mountain Mitsikeli in Ioannina basin (GkargkoulasBakakis et al., 2003), which could explain its current strong representation in the pollen record. The human impact in Ioannina basin leads to major changes in the vegetation of the area, as happens across the whole Mediterranean (Bottema, 1974). The grazing pressure leads many plant species to local extinction or reduces their distributions (Lawson et al., 2004). Evergreen Quercus species are adapted to survival in poor environments – whether shaded or on shallow soils - and by carrying a bitter taste (tannins) in their leaves survive grazing and have a competitive advantage over other taxa (Arampatzidis, 2001). This resilience to grazing is the most likely explanation for their historically unprecedented current high abundance in the pollen record.
Since the end of the twentieth century
grazing pressure in the area has been decreasing (Gkargkoulas-Bakakis et al., 2003), in the future we might expect evergreen oaks to become progressively less dominant ecologically and palynologically, in favour of other species such as deciduous species of Oak. 4.2. Pollen signal in Ioannina Lake Apart from some evidence for atypical overall pollen concentrations and proportions immediately next to the reed-bed edge, no systematic variability in the taxa-richness and the relative abundances of each taxon was found among the different transects and between the sample points of different depths and distance from the edge. According to Davis and Ford (1982) sediment as a whole can move from shallow to deeper parts of the lake basin with water currents, especially during overturn. This phenomenon that results greater accumulation in deeper parts is termed as “sediment focusing”. Sediment focusing as well as the expected wash next to the banks of the lake can explain the low concentrations of total pollen (i.e., the low absolute values) in the first sampling point of each transect. This result shows that there is no spatially coherent difference among the samples, and thus that across the area the pollen deposited is close to uniform. A major concern for palynological work is the impossibility of replication (Birks and Gordon, 1985) While there is clearly some random error associated with individual pollen cores, the implication of my work is that, assuming that the dispersal pollen
30
pattern was the same in the past, the location of cores may not have a systematic effect on the local pollen record, and therefore that single cores may be usually sufficient for reconstruction of past environments. Moreover, any differences found along the length of historical pollen cores are likely to reflect real vegetation changes in the past. 4.3. Further study None of the previous researchers working here attempted to specify the catchment of Pamvotida Lake. However, two main assumptions, first that it cannot be small because the lake itself is rather big, and second that it cannot be very large otherwise it wouldn’t differ so markedly from the pollen records of other Greece sites, lead to the conclusion that the palynological catchment of the lake is likely to be on the same scale as the hydrological catchment, and probably largely coincides with it. Further research is clearly needed to investigate this hypothesis. Such work could involve delineation of the catchment itself and conducting a quantitative vegetation survey, with the help of remote-sensing imagery. It could also involve specifying several buffer zones of different sizes around the lake and carrying out vegetation surveys in each zone, and then comparing vegetation cover over these different areas with the modern pollen signal. If the modern lake’s pollen catchment is defined, then it can be applied to the past and help to the interpolation of the former vegetation. The pollen dispersal can be estimated and compared with the present survey can provide important information for testing the reconstruction models and the climate parameters during the geological past. It is important the relationships between surface pollen and source plants to be tested. Results of such surveys from other sites have been proved very interesting in the past (see Yu et al., 2004).
31
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Appendix Some tables suggestively are following from the statistical analysis. Table 2: T-test: Paired Samples Test for the number of taxa between the two transects. Paired Differences
Mean Pair 1
tra1 tra2
1,11765
Std. Deviation 4,72867
95% Confidence Interval of the Difference
Std. Error Mean
Lower
Upper
t
1,14687
-1,31361
3,54890
,975
Sig. (2tailed)
df 16
,344
Table 3 A: General Linear Model: Univariate Analysis of Variance, Tests of Between-Subjects Effects for the taxon-richness along the first transect including the first sampling point. The last corrected model presented where depth seams to be significant important. Dependent Variable: No of taxa 1 tr Source Corrected Model Intercept
Type III Sum of Squares 30,756(a)
df
1025,091
1
Mean Square 30,756
1
F
Sig. 5,534
,033
1025,091
184,455
,000
5,534
,033
depth
30,756
1
30,756
Error
83,361
15
5,557
Total
15837,000
17
Corrected Total
114,118 a R Squared = ,270 (Adjusted R Squared = ,221)
16
Table 3 B: General Linear Model: Univariate Analysis of Variance, Tests of Between-Subjects Effects for the taxon-richness along the first transect excluding the first sampling point. The last corrected model presented where depth isn’t anymore significant important. Dependent Variable: No of taxa 1 tr Source Corrected Model Intercept depth
Type III Sum of Squares 8,782(a)
df 1
Mean Square 8,782
357,344
1
8,782
1
5,926
Error
82,968
14
Total
14612,000
16
Corrected Total
91,750 a R Squared = ,096 (Adjusted R Squared = ,031)
F
Sig. 1,482
,244
357,344
60,298
,000
8,782
1,482
,244
15
32
Table 4: General Linear Model: Univariate Analysis of Variance, Tests of BetweenSubjects Effects for the taxon-richness along the second transect. The last corrected model presented. Dependent Variable: No of taxa 1 tr Type III Sum of Source
Squares
df
Mean Square
F
Sig.
Corrected Model
1,812(a)
1
1,812
,156
,698
Intercept
5100,439
1
5100,439
440,409
,000
depth * distanse
1,812
1
1,812
,156
,698
Error
173,717
15
11,581
Total
14764,000
17
Corrected Total
175,529
16
a R Squared = ,010 (Adjusted R Squared = -,056)
Table 4: General Linear Model: Univariate Analysis of Variance, Tests of BetweenSubjects Effects for the taxon-richness along all the sampling points of the both transects. The last corrected model presented. Dependent Variable: No of taxa 1 tr Source Corrected Model Intercept transect
Type III Sum of Squares 10,618(a)
df 1
Mean Square 10,618
1,173
,287
30300,735
1
30300,735
3347,604
,000
10,618
1
10,618
1,173
,287
9,051
Error
289,647
32
Total
30601,000
34
Corrected Total
300,265 a R Squared = ,035 (Adjusted R Squared = ,005)
F
Sig.
33
33
