SEARCH

SEARCH BY CITATION

Keywords:

  • Community structure;
  • Mediterranean Sea;
  • phytoplankton rarity

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Appendix: Rare species recorded in only one (singetons) or two (doubletons) sample units. *Gulfs: S (Saronikos), E (Evoikos), P (Pagassitikos), T (Thermaikos). Seasons: 1 (Spring), 2 (Summer), 3 (Autumn)

Analysis of quantitative and qualitative composition of rare phytoplankton species was performed using a data set collected over a large geographic area (four eutrophic gulfs of the Aegean Sea, E. Mediterranean Sea) during 2002–2003. We examined the effects of excluding rare species on comparisons of species richness, diversity, similarity and niche breadth as well as the regional and seasonal contribution of rare species to cell abundance and carbon biomass. Overall, the total of 401 species included 182 rare species contributing 45.1% of the total species number. However, there was a considerable variation in this relationship among the other parameters, as rare species contributed only 6.4% of total cell abundance, 13.1% of total species diversity, 21.2% of total cell biovolume and 16.6% of total carbon biomass. The results showed that rarity may be a significant issue in studies detecting and quantifying phytoplankton community structure.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Appendix: Rare species recorded in only one (singetons) or two (doubletons) sample units. *Gulfs: S (Saronikos), E (Evoikos), P (Pagassitikos), T (Thermaikos). Seasons: 1 (Spring), 2 (Summer), 3 (Autumn)

In ecology, species that are restricted in numbers or spatial occurrence are considered rare compared with the distribution and abundance of other species making up the pool of a community (Gaston 1994). Rarity is a subject of increasing ecological importance in the context of biodiversity and productivity-related processes. Concern about rapid biodiversity loss in response to anthropogenic activities and climate change has intensified the need to understand the role of rare species in maintaining the structure and biomass accumulation within the communities in which they carry out their activities (Ohlemüller et al. 2008; Willis & Bhagwat 2009). However, most of our current understanding of rarity has come from studies of terrestrial plants, birds, mammals and some insects (Chapman 1999).

Phytoplankton, forming the base of the food chain and controlling the carbon cycle in the ocean, has a large impact on the functioning of marine ecosystems and on the global climate (Boyd et al. 2007). They include species that vary in many traits including size, relative abundance, frequency of occurrence, and dominance (Litchman & Klausmeier 2008). Studies on phytoplankton species rarity are scanty but available evidence indicates (Ignatiades et al. 2009; Cermeno et al. 2010) that phytoplankton communities are made up of common species having high abundance and frequency of occurrence, and determining to a large extent the rate of ecosystem processes, and a large pool of rare species with low abundance and frequency of occurrence.

The role of phytoplankton species rarity in affecting the overall community functioning is a subject of debate. Some investigators (Garate-Lizarraga & Siqueiros Beltrones 1998) reported that rare species are artifacts and they should be discarded in data analysis because they add noise to statistical solutions, whereas others (Flöder et al. 2010) claimed that rare species constitute an important component of population dynamics and that they should be taken into account. The contribution of rare phytoplankton species to total abundance also remains unclear and contradictory. Jeffrey & Hallegraef (1980) reported that they contributed very little to total community abundance, but the work of Ulrich & Ollik (2004) discussed the substantial contribution of rare species to this parameter. These contradictions might be due to the fact that most investigators tend to quantify rare species by cell abundance. However, the abundance fluctuations of phytoplankton species are regulated by cell size and shape descriptors that determine the uptake of nutrients and light, alternative nutritional strategies (i.e. mixotrophy), intracellular storage capacity (Verity et al. 2002; Naselli-Flores et al. 2007; Litchman & Klausmeier 2008) and grazing (Metaxatos & Ignatiades 2011). Estimates of phytoplankton abundance should therefore include, in addition to total cell numbers, total cell carbon estimators (Llewellyn et al. 2005).

The linking of rarity to species diversity has been the subject of extensive research in terrestrial organisms (Blackburn & Lawton 1994; Caterino 2007) but there are only a few studies in marine communities. Boero (1994) characterized rare species as important reservoirs of genetic and ecological diversity in coastal marine environments, Flöder et al. (2010) reported that the stability and diversity of phytoplankton populations is supported by the compensatory growth of rare species, and Weithoff (2003) proposed the insurance theory according to which rare phytoplankton species form a backup for species functional diversity, responding quickly to disturbance and therefore increasing the resilience of ecosystem processes.

Another important trait of rarity is niche breadth, the degree to which a species occurs in a variety of habitats or is restricted to one or a few sites (Rabinowitz 1981; Tokeshi 1999). Conceptualization of phytoplankton niche properties has been reported by several investigators (Sommer et al. 1993; Smayda & Reynolds 2003; Stomp et al. 2004) but without reference to rare species. The potential effect of habitat eutrophication status on phytoplankton species rarity is also a topic that has not been discussed.

The aim of this work was to investigate the concepts of phytoplankton species rarity using a data set collected over a large geographic area covering four eutrophic gulfs of the Aegean Sea during 2002–2003. The distribution of rare species among samples was analysed in terms of occurrence, abundance, cell size and cell carbon content and their spreading (niche breadth) among sampling sites was compared. The hypothesis that rare species are important contributors to phytoplankton biomass, species richness and diversity was also tested (Cao et al. 1998). This paper is in accordance with the European initiative recommending a focus on the research of species rarity (Fontaine et al. 2007).

Material and Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Appendix: Rare species recorded in only one (singetons) or two (doubletons) sample units. *Gulfs: S (Saronikos), E (Evoikos), P (Pagassitikos), T (Thermaikos). Seasons: 1 (Spring), 2 (Summer), 3 (Autumn)

Monitoring and microscopic analyses

Detection of rare species is influenced by the number of samples, based on a wide temporal and spatial monitoring protocol (Cao et al. 2001). These requirements were addressed adequately in this work since monitoring was performed along a large scale of sampling stations located in four gulfs (Saronikos, Evoikos, Pagasitikos, Thermaikos) in the Western Aegean Sea (Fig. 1). A total of 20 stations (maximum water depth 10–15 m) were sampled from 1 m depth monthly in spring, summer and autumn during 2002–2003. The 250 samples collected were analysed for temperature, salinity, phosphates, total inorganic nitrogen and silicates according to the methodology previously described (Ignatiades et al. 2007).

image

Figure 1. Location of Gulfs studied. S, Saronikos Gulf; E, Evoikos Gulf; P, Pagassitikos Gulf; T, Thermaikos Gulf.

Download figure to PowerPoint

Duplicate water samples for species identification and enumeration were fixed with Lugol's solution (without acetic acid), settled in 50-ml sedimentation chambers and the species belonging to three phytoplankton classes (diatoms, dinoflagellates and coccolithophores) were counted at 200× and/or 400× under a Zeiss inverted microscope according to the Utermöhl (1958) method. Cell counting of each sample included two steps: (i) several fields (depending on the density of cells) were counted, averaged and used with an appropriate factor, derived from calibration of the sedimentation chamber, to compute cells per litre; (ii) the entire bottom of the chamber was scanned to discover any cells (usually rare) that were not included in the field counts. The linear dimensions of all recorded species were measured on a routine basis along with the species identification and found to be within the ranges of cell dimensions of the same species given in the literature (Trégouboff & Rose 1957a,b; Rampi & Bernhard 1980, 1981; Sournia 1986; Ricard 1987; Tomas 1997).

Data analyses

Cell volume and cell carbon biomass

Cell volume (V) and surface area (S) were calculated by fitting the cellular dimensions in formulae for solid geometric shapes most closely matching the shape of the cells (Hillebrand et al. 1999; Sun & Liu 2003). Cellular biovolume was determined by multiplying the number of total cells l−1 of each species by its estimated cell volume. Total sample biovolume was derived by summing the respective cellular biovolumes of all species.

Phytoplankton cell carbon biomass (pgC·μm−3) for each species was estimated from known relationships with cell volume as follows:

  • For diatoms: log10C = 0.811 log10 V–0.541 (Menden-Deuer & Lessard 2000).
  • For dinoflagellates: log10C = 0.819 log10 V – 0.119 (Menden-Deuer & Lessard 2000).
  • For coccolithophores: log10C = –0.34 log10V – 0.06 (Llewellyn & Gibb 2000).
Species rarity, biodiversity and niche breadth

Rare species were determined by setting the frequency of occurrence criterion (Gauch 1982; McGill et al. 2006). Frequency distribution analysis (statistical package SPSS 10.0, SPSS Inc., Chicago, IL, USA) was applied in the entire set of 250 samples derived from all Gulfs and included all species of the three classes (diatoms, dinoflagellates and coccolithophores). Rare species were defined as those persisting with limited range of occurrences (frequency of occurrence 1–2).

The data were analysed (PRIMER 6, Primer-E Ltd, Plymouth Marine Laboratory, Plymouth, UK) to assess the biodiversity values of (i) total species (common + rare) and (ii) after the exclusion of rare species (common only) to test the effect of species rarity in terms of species richness, species diversity and species pairwise similarity using the following indices:

Margalef's (1958) richness index: d = (S 1)/(logen) where S is the total number of species and n is the total number of individuals. This index gives equal weight to all species.

Hill's (1973) diversity number: N1 = eH where H is Shannon's index (Shannon & Weaver 1949). Hill's number index measures the effective number of species present in a sample, giving a measure of the degree to which proportional abundances are distributed among the species (Ludwig & Reynolds 1988).

The Jaccard's (Ludwig & Reynolds 1988; Magurran 2004) similarity index: J = α/α + b + c for presence/absence data, where α is the total number of species present in both compared samples, b is the number of species present only in sample 1, and c is the number of species present only in sample 2. J ranges from 0 (when no species are shared between any two samples) to 1 (when all species are shared), and emphasizes species compositional changes and serves as a metric of β-diversity.

The niche breadth of each species was measured by the expression:

  • display math

where nir is the number of individuals at the i-th taxon found in the sample from the r-th station, and Ni the summation of individuals of the i-th taxon found at all Q stations (McIntire & Overton 1971). The magnitude of Bi is a measure of the taxon's degree of successful growth at the stations under consideration and its value can range from 1 to Q.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Appendix: Rare species recorded in only one (singetons) or two (doubletons) sample units. *Gulfs: S (Saronikos), E (Evoikos), P (Pagassitikos), T (Thermaikos). Seasons: 1 (Spring), 2 (Summer), 3 (Autumn)

Physical and chemical parameters

Regional variations of the analysed hydrographic parameters are presented as monthly averages for each season in Table 1. The overall ranges of temperatures and salinities indicate their uniform seasonal variation among the gulfs (spring: 17.12–17.59 °C, 35.09–37.95 salinity; summer: 24.39–25.09 °C, 35.84–37.81 salinity; autumn: 20.50–21.88 °C, 35.34–37.71 salinity). According to the nutrient concentration scaling (Ignatiades et al. 1992; Gotsis-Skretas & Ignatiades 2007) the investigated gulfs (Fig. 1) were characterized ‘eutrophic’ because the concentrations of phosphorus and nitrogen (i) approached the levels of critical values (P-PO4: 0.34 μm; N-NH3 + N-NO3 + N-NO2:1.68 μm) used as indicators for evaluation of eutrophication. Silicate rages (spring: 3.58–23.16 μm; summer: 2.70–15.60 μm; autumn: 4.14–14.16 μm) were also at non-limiting levels for diatom growth. The N:P ratio deviated from the Redfield optimal value (N:P = 16) being higher in Saronikos (N:P = 24.16–34.86) Evoikos (N:P = 26.16–43.85) and Pagassitikos (N:P = 43.06–53.65) and lower (N:P = 5.11–6.16) in Thermaikos Gulf.

Table 1. Physical and chemical parameters in the four gulfs. Values are overall means of all sampled stations at each Gulf, in spring, summer and autumn during April–October for the years 2002 and 2003. Standard deviations between years for each season are given in parentheses
GulfSeasonTemp. (°C)Salinity (psu)P-PO4m)DINam)N/PSi-SiO4m)
  1. a

    Total dissolved inorganic nitrogen (NH3 + NO3 + NO2).

Saronikos

(8 stations)

Spring 17.59 37.950.375.9824.153.58
(0.40)(0.43)(0.12)(1.50)(2.3)(2.18)
Summer25.0937.810.385.9034.862.80
(1.65)(0.29)(0.02)(0.57)(11.65)(1.72)
Autumn20.8437.710.407.3034.618.15
(0.54)(0.40)(0.17)(4.57)(13.91)(0.08)

Evoikos

(4 stations)

Spring17.1236.610.357.3833.866.94
(1.56)(1.01)(0.03)(1.25)(16.12)(1.76)
Summer25.0237.130.324.7726.165.30
(1.71)(0.49)(0.00)(3.69)(20.07)(3.49)
Autumn21.8837.090.387.7443.855.62
(0.33)(0.37)(0.03)(1.71)(18.37)(1.34)

Pagassitikos

(4 stations)

Spring17.3335.090.5417.3934.0623.16
(0.98)(2.60)(0.39)(10.54)(4.30)(13.51)
Summer24.3935.840.3412.0453.6515.60
(1.80)(1.85)(0.08)(3.38)(3.89)(7.74)
Autumn21.7335.340.3511.3940.6714.16
(0.61)(2.34)(0.09)(8.11)(11.87)(15.75)

Thermaikos

(4 stations)

Spring17.2636.490.924.096.168.66
(0.68)(0.74)(0.06)(0.93)(2.04)(7.96)
Summer24.4536.710.451.675.112.70
(0.49)(0.16)(0.02)(0.17)(0.53)(0.92)
Autumn20.5036.420.633.685.784.14
(0.77)(0.66)(0.15)(2.06)(2.09)(3.19)

Definition of common and rare species

Calculations were carried out with the use of pooled data from the whole survey since pooling provided a larger number of common and rare species. The plot of the distribution of frequencies of occurrences against the species numbers (Fig. 2) had very large positive skewness (log series model), and its greatest frequency occurred on the left of the graph representing the number of rare species (Tokeshi 1999). Among the 401 species recorded in the entire set of 250 samples, 182 (45%) were rare (frequency of occurrence 1–2) and 219 (55%) were common (frequency of occurrence >2); 146 of the rare species (Rare species recorded in only one (singetons) or two (doubletons) sample units. *Gulfs: S (Saronikos), E (Evoikos), P (Pagassitikos), T (Thermaikos). Seasons: 1 (Spring), 2 (Summer), 3 (Autumn) 1) were singletons and 36 doubletons, recorded at only one sample unit or double sample units correspondingly (Magurran 2004, 2005).

image

Figure 2. Frequency distribution of species numbers in relation to the ranges of occurrences of rare and common species.

Download figure to PowerPoint

Species cell abundance, niche breadth and rarity

The overall pattern of relative contribution in the abundance of common and rare species was performed by species ranking from commonest to rarest (on the frequency-based estimator) into classes of abundance distributed in logarithmic size intervals. The obtained curve pattern (Fig. 3A) of a decreasing power function (y = 190.16x−2.26; R2 = 0.67; P < 0.001) in relative abundance from commonness to rarity (Ulrich & Ollik 2004) revealed the small contribution of rare species (0.16%) to the total cell abundance relative to the common (99.83%) ones, in spite of their large pool in species numbers.

image

Figure 3. Phytoplankton relative abundance distribution plotted against species rank in abundance (A) and niche breadth (B). Solid line is the best fitting of data.

Download figure to PowerPoint

The application of a quantification-based approach for niche breadth estimation was particularly useful in determining the species habitation in space, i.e. whether common and/or rare species occur in a variety of habitats or are restricted to one or a few specialized sites. The results showed (Fig. 3B) that relative cell abundance distribution in relation to niche breadth index followed the power law model (y = 0.0002x2.26; R2 = 0.65; P < 0.001) as described by McGill (2003a). Niche breadth index for common species ranged from 1.22 to 45.50 and for rare from 1.05 to 3.09, and these values represented 88.19% and 11.81% of total niche size, respectively. These results are in agreement with Tokeshi's (1996) principle that the abundance of species is directly related to niche size, i.e. greater abundance results in larger niche.

Species biodiversity and rarity

The three indices used to examine the relationships of species rarity and biodiversity (Table 2) did not generate different partitions, although they measure different aspects of the assemblage. Thus, the exclusion of rare species from an assemblage reduced the species richness (Margalef's index) by 10–18%, and the species diversity (Hill's N1 index) by 12–20%, consequently decreasing the community similarity (Jaccard's index) by a percentage ranging from 11 to 20%. Patterns of these indices changed in a similar way across time and space.

Table 2. Tests for differences in species richness (Margalef's index) and diversity (Hill's N1 index) for total, common and rare species and the %reduction after the removal of rare species from common. Jaccard's similarity index evaluates pairwise comparisons (total versus common)
GulfSaronikosEvoikosPagassitikosThermaikos
SeasonSpringSummerAutumnSpringSummerAutumnSpringSummerAutumnSpringSummerAutumn
Margalef's index
Total2.201.902.281.981.771.931.611.721.581.551.652.26
Common1.801.632.041.711.521.731.391.511.411.321.451.98
Rare0.400.230.240.270.250.200.220.210.170.230.200.28
%Reduction181411141410141211151212
Hill's (N) index
Total146.7123.6152.0129.7111.4123.9100.5108.2103.998.2103.0150.5
Common116.7104.5133.7109.593.8109.285.192.991.082.188.6129.3
Rare30.019.118.320.217.614.715.315.312.916.314.421.2
%Reduction201512161612151412161414
Jaccard's index
Total versus Common0.800.840.870.840.840.880.840.860.890.830.860.85

Regional and seasonal contribution of rare species to cell abundance and carbon biomass

The overall average values in terms of spatial distribution show (Fig. 4A) that the highest total cell concentration was recorded in Thermaikos Gulf (1.7 × 104 cells·l−1) followed by Saronikos Gulf (6.7 × 103 cells·l−1) and that the gulfs Evoikos and Pagassitikos exhibited similar levels (3.1–3.4 × 103 cells·l−1). Seasonally, the highest cell concentrations were found in spring and summer (1.1 × 104–1.2 × 104 cells·l−1) and declined in autumn (2.3 × 103 cells·l−1). The regional reduction from exclusion of rare from total cell abundance ranged from 6 to 8%, and the seasonal from 6 to 9%.

image

Figure 4. Regional and seasonal distribution of cell abundance (A) and carbon biomass (B) of total, common, rare and percentage of rare species.

Download figure to PowerPoint

Regional and seasonal trends were also observed in total carbon biomass (Fig. 4B) although maxima of this parameter differed on some occasions from those in cell abundance due to the differences in cell volume of the participant species. Thus, the Thermaikos and Saronikos Gulfs exhibited higher levels of carbon biomass (35.1 and 13.9 μC·l−1, respectively) in relation to Evoikos (8.2 μC·l−1) and Pagassitikos (4.1 μC·l−1). The seasonal variation was also well defined and fluctuated as follows: 21.4 μC·l−1 (spring), 16.9 μC·l−1 (summer) and 7.5 μC·l−1 (autumn). The exclusion of rare species from the total species reduced the carbon biomass from 11 to 19% regionally and from 10 to 19% seasonally.

A synoptic quantification of the assemblage attributes examined (species number, cell abundance, species diversity, biovolume and carbon biomass) of total species, rare species and the percent reduction after exclusion of rare species recorded during the period 2001–2003 presented in Table 3. Overall, the total of 401 species included 182 rare ones contributing 45.1% to the total species number but there was considerable variation in this relationship among the other parameters since, rare species contributed 6.4% of the total cell abundance, 13.1% of the total species diversity, 21.2% of the total cell biovolume and 16.6% of the total carbon biomass.

Table 3. Overall mean values through time and space of species numbers, cell abundances, species diversities, biovolumes and carbon biomasses (SD in parentheses) for total species, rare species and the percent reduction after exclusion of rare species. Time period: 2001–2003; seasons: spring, summer, autumn; Gulfs: 4; samples: 250
ParametersSpecies (n)Cell abundance (cells·l−1)Species diversity Margalef's indexBiovolume (μm3·l−1)Carbon biomass (μg·l−1)
Total species4017.8 × 103 (±5.5 × 102)1.87 (±0.26)4.4 × 1010 (±1.6 × 109)15.3 (±10.5)
Rare excluded1825.1 × 102 (±3.1 × 10)2.5 (± 0.6)9.4 × 108 (±3.6 × 107)2.5 (±2.1)
Percent reduction45.16.413.121.216.6

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Appendix: Rare species recorded in only one (singetons) or two (doubletons) sample units. *Gulfs: S (Saronikos), E (Evoikos), P (Pagassitikos), T (Thermaikos). Seasons: 1 (Spring), 2 (Summer), 3 (Autumn)

Importance, frequency of occurrence and relative abundance of rare species

In recent years, species rarity has been the focus of many ecological theories and controversies (Irwin et al. 2006) but it is clearly accepted that regardless of the community type, the constituent species in a community are dominated by many rare and a few highly abundant species (Magurran 2004). Grime (1998) in his mass ratio theory postulated that species with low abundances will have concomitantly low ecosystem impact but Lyons et al. (2005) supported the important role of phytoplankton rare species biomass in the concepts of trophodynamics and ecosystem functioning. The importance of rare species in community structure has also been supported by two interesting hypotheses. The complementarity hypothesis (Loreau & Hector 2001) suggests that rare species may be important due to their involvement in resource acquisition. This implies that an assemblage with common and rare species utilizes resources more efficiently than one with a single or a few dominant species. The insurance hypothesis (Weithoff 2003) states that rare species form a functional backup for dominant species and that they can respond quickly to disturbance, thus increasing the resilience of ecosystem processes.

Several investigators (Cao et al. 1998; Padisák et al. 2010) have reported that finding appropriate criteria for quantifying phytoplankton ‘rare’ species is difficult because this is not an easy group to study when rarity is addressed. The analysis of the present data suggests that the distribution plot of the number of species in relation to frequency of occurrences per species (Fig. 2) was appropriate for common and rare specimens quantification, as reported by other investigators (Cao et al. 1998; Magurran 2004) and thus the plot can be used to describe ‘commonness and rarity’ for phytoplankton communities. This plot appears to be universal, since there are no multi-species communities, ranging from marine benthos to the Amazonian rainforest, that violate it (McGill et al. 2007). Numerically, rare species accounted for a substantial fraction (45.4%) of the overall phytoplankton species numbers. This pattern is very similar to the one found by Cermeno et al. (2010) in their study on the common and rare species abundance distribution for phytoplankton of the Atlantic Meridional Transect.

Species abundance has also been used to define the overall variation of numerically common and rare species (Brown 1984; Vázquez & Gaston 2004). Knowledge of the patterns in species abundance can provide insight into how a community functions. For many communities a log-normal distribution provides an accurate description of the abundances of species in a community. Besides the log-normal distribution, there are other mathematical models in use, e.g. power function, geometric series, log series, broken stick (McGill et al. 2007). The data of this work are presented in a diagram (Fig. 3) where log-abundance is plotted against species rank and displayed the power function model (Ulrich & Ollik 2004) showing the pronounced differences of this parameter among common and rare species. According to McGill (2003b), intensively sampled species abundance distributions show left skew on a log scale because there are too many rare species to fit a lognormal distribution and thus it converges to power distribution, as the variance goes to infinity. Symmetric lognormal type distributions appear when many independent factors act together in a multiplicative way to structure closed communities (Nee et al. 1991). If instead, stochastic dispersal was the dominating structuring force, abundance distributions should significantly deviate from log normality (Ulrich & Ollik 2004). Schindler et al. (2003) reported that rare species in phytoplankton communities drop in and out of the system on an irregular basis assuming that the community is not in equilibrium.

Niche breadth of rare species

Interspecific differences in abundance and distribution may reflect a dynamic equilibrium based on niche specialization of the component species (Crawley et al. 1997). A species' niche breadth has often been seen as a property of a species related to commonness and rarity (Rabinowitz et al. 1986; Azeria & Kolasa 2008) and it usually involves measuring abundance and dispersion of species in various categories of habitat; species that have a wide niche breadth tolerate wider ranges of environmental conditions and therefore will be regionally common, as opposed to species with narrow niches (Dolédec et al. 2000). Most niche-based modelling approaches of phytoplankton communities did not consider the presence of rare species (Passy & Legendre 2006; Spatharis et al. 2009).

The niche breadth index used in this investigation (McIntire & Overton 1971) can determine each species' niche, allowing the evaluation of common–rare species differences. The index does not require information on environmental factors and does not account for idiosyncrasies and constraints due to biotic interactions and species' dispersal abilities. This index is well suited for the investigation of niche breadth in the case of trophically similar species (phytoplankton) competing for the same resources (light, CO2, nutrients) and inhabiting areas characterized by similar environmental factors (Table 1). Focusing on the results obtained in this work (Fig. 3B) it is obvious that the abundance and niche breadth of species tend to be linked, such that species declining in abundance (rare species) often show a decline in their ecological dispersion (Gaston et al. 2000). The present data support the theory of niche differentiation, assuming coexistence of common and rare species (Boulangeat et al. 2003), which might be due to genome divergence (Rocap et al. 2003), species–specific growth rates (Kuwata & Miyazaki 2000), complementary resource utilization (Symstad et al. 2003), adaptive divergence in pigment composition (Stomp et al. 2004) or grazer control (Sommer 2000). In contrast, Hubbell's (2001) neutral theory is weak in explaining the results of the present investigation, since it assumes that all species are identical and consequently no single species is at a competitive advantage or disadvantage.

Species diversity and rarity

In species diversity studies, rare species are often considered as ‘noise’ and removed from the analysis of data with the argument that they contribute little to community structure (Cao et al. 1998). In our literature search we found a limited number of studies addressing the occurrence of rare species in phytoplankton communities. With the exception of the information that rare species contributed up to 47% to species richness of the Mediterranean Sea (Ignatiades et al. 2009), reports from the Eastern Australian Current (Jeffrey & Hallegraef 1980), the Santa Barbara Basin (Venrick et al. 2008) as well as the South Aegean (Archonditsis et al., 2003) and North Aegean Sea (Tas et al. 2009) pointed out the existence of rare species without making reference to their role in species diversity.

In the present investigation an effort has been made to fill this gap by comparing species diversity measures before and after the exclusion of rare species in phytoplankton samples collected seasonally from different study areas (Table 2). One of the most significant characteristics of a diversity index is its sensitivity to the contribution of rare species in community analyses (Chao et al. 2006). In this study, comparative analyses of phytoplankton assemblages were performed with the use of diversity indices (Margalef's richness, Hill's N1, Jaccard's similarity) having sensitivity to changes in rare species and providing an overall view of commonness and rarity (Boyle et al. 1990; Gering et al. 2003; Magurran 2004). The most interesting features of the present data (Table 2) are: (i) the levels of the diversity indices studied showed a high degree of concurrence and therefore similar sensitivity to species rarity, (ii) common and rare species demonstrated similar diversity trends in space and time that can probably be explained by the generalist habitat requirements of phytoplankton, and (iii) exclusion of rare species considerably reduced (11–20%) the species diversity. Thus, rare species are of extreme importance and their contribution to diversity must be known in order to understand inexplicable phenomena such as modifications in community composition (Loreau et al. 2001). According to Boero (1994) rare species are a reservoir of potential diversity and contain the information for the possible future composition of a community after disturbances.

Spatial and seasonal distribution of rare species in eutrophic waters

Eutrophication is a process driven by enrichment of water by nutrients, especially compounds of nitrogen and phosphorus, leading to changes in community structure (Ferreira et al. 2011) but the potential effect of habitat trophic status on species rarity has not been discussed until today. Records on the trophic status of the Aegean Sea (Gotsis-Skretas & Ignatiades 2007) proved that the investigated Gulfs were ‘eutrophic’ because the nutrient concentrations (Table 1) approached the levels of critical values used as indicators for evaluation of eutrophication (Ignatiades et al. 1992) and the N:P ratio deviated from the Redfield optimal value (N:P = 16).

The results indicated detectable spatial and seasonal distribution of rare species in terms of cell abundance and carbon biomass in eutrophic waters. The spatial aspect of rare species has been discussed by Hanski (1982) who discriminated their distribution in ‘physical space’ from that in ‘niche space’. According to other investigators (Rabinowitz et al. 1986; Gaston & Kunin 1997) rare species have sparse and or restricted spatial distribution patterns and they are habitat specialists. These views are in agreement with the present data since the 182 rare species were randomly distributed as singletons (a single individual species) or doubletons (two individual species) in the entire set of 250 samples collected along the investigated areas. However, species defined as ‘rare’ proved to be present continuously in time and space (Fig. 4), providing a constant fraction (6–9%) of total cell abundance, whereas their seasonal and regional contribution to total carbon biomass was significantly higher (11–19%) than that (0.001–0.01%) reported by Jeffrey & Hallegraef (1980) for phytoplankton of the East Australian current. Several investigators (Rhee & Gotham 1980; Stelzer & Lamberti 2001; Ignatiades et al. 2007) reported that N:P deviations from optimal value do not support the N:P requirements of certain individual algal species and depress their growth and abundance and this might also be a factor explaining the low abundance of rare species in the investigated Gulfs.

In conclusion, the data analyses presented in this work indicate clearly that:

  1. Rarity may be a significant issue in the interpretation of other potential criteria of phytoplankton community structure, i.e. species cell abundance, biomass, richness, diversity, dispersal abilities (niche breadth) and seasonal /spatial fluctuations.
  2. Analyses of large sample numbers from different habitats and seasons improve the detection of rare species, and can be used to assess the overall differences between rare and common species.
  3. Rare species cannot be excluded from community studies as an artifact or a group of marginal importance. Rather, they should be targeted as an interesting ecological phenomenon that might be associated with the question of whether the stability of ecosystem properties depends on population dynamics of common species or on compensatory growth of rare species.
  4. Important questions for future studies are whether common and rare species retain their ‘commonness’ and ‘rarity’ status for long periods and whether rare species are relatively more prone to extinction.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Appendix: Rare species recorded in only one (singetons) or two (doubletons) sample units. *Gulfs: S (Saronikos), E (Evoikos), P (Pagassitikos), T (Thermaikos). Seasons: 1 (Spring), 2 (Summer), 3 (Autumn)
  • Archonditsis G., Karydis M., Tsirtsis G. (2003) Analysis of phytoplankton community structure using similarity indices: a new methodology for discriminating among eutrophication levels in coastal marine ecosystems. Environmental Management, 31, 619632.
  • Azeria E.T., Kolasa J. (2008) Nestedness, niche metrics and temporal dynamics of a metacommunity in a dynamic natural model system. Oikos, 117, 10061019.
  • Blackburn T.M., Lawton J.H. (1994) Population abundance and body size in animal assemblages. Philosophical Transactions of the Royal Society of London B, 343, 3339.
  • Boero F. (1994) Fluctuations and variations in coastal marine environments. Marine Ecology, 15, 325.
  • Boulangeat I., Lavergne S., Van Es J., Garraud L., Thuiller W. (2003) Niche breadth, rarity and ecological characteristics within a regional flora spanning large environmental gradients. Journal of Biogeography, 39, 204214.
  • Boyd P.W., Doney S.C., Strzepek R., Dusenberry J., Lindsay K., Fung I. (2007) Climate-mediated changes to mixed-layer properties in the Southern Ocean: assessing the phytoplankton response. Biogeosciences Discussions, 4, 42834322.
  • Boyle T.P., Smillie G.M., Anderson J.C., Beeson D.R. (1990) A sensitivity analysis of nine diversity and seven similarity indices. Research Journal of the Water Pollution Control Federation, 62, 749762.
  • Brown J.H. (1984) On the relationship between abundance and distribution of species. American Naturalist, 124, 255279.
  • Cao Y., Williams D.D., Williams N.E. (1998) How important are rare species in aquatic community ecology and bioassessment? Limnology and Oceanography, 43, 14031409.
  • Cao Y., Larsen D.P., Hughes R.M. (2001) Evaluating sampling sufficiency in fish assemblage surveys: a similarity-based approach. Canadian Journal of Fisheries and Aquatic Sciences, 58, 17821793.
  • Caterino M.S. (2007) Species richness and complementarity of beetle faunas in a mediterranean-type biodiversity hotspot. Biodiversity and Conservation, 16, 39934007.
  • Cermeno P., de Vargas C., Abrantesm F., Falkowski P.G. (2010) Phytoplankton biogeography and community stability in the ocean. PLoS ONE, 5, e10037.
  • Chao A., Chazdon R.L., Colwell R.K., Shen T.-J. (2006) Abundance-based similarity indices and their estimation when there are unseen species in samples. Biometrics, 62, 361371.
  • Chapman M.G. (1999) Are there adequate data to assess how well theories of rarity apply to marine invertebrates? Biodiversity and Conservation, 8, 12951318.
  • Crawley M.J., Harvey P.J., Purvis A. (1997) Comparative ecology of the native and alien floras of the British Isles. In: Silvertown J., Franco M., Harper J.L. (Eds), Plant Life Histories. Cambridge University Press, Cambridge, UK: 3656.
  • Dolédec S., Chessel D., Gimaret-Carpentier C. (2000) Niche separation in community analysis: a new method. Ecology, 81, 29142927.
  • Ferreira J.G., Andersen J.H., Borja A., Bricker S.B., Camp J., Cardoso da Silva M., Garcés E., Heiskanen A.-S., Humborg C., Ignatiades L., Lancelot C., Menesguen A., Tett P., Hoepffner N., Claussen U. (2011) Overview of eutrophication indicators to assess environmental status within the European Marine Strategy Framework Directive. Estuarine, Coastal and Shelf Science, 93, 117131.
  • Flöder S., Jaschinski S., Wells G., Burns C.W. (2010) Dominance and compensatory growth in phytoplankton communities under salinity stress. Journal of Experimental Marine Biology and Ecology, 395, 223231.
  • Fontaine B., Bouchet P., Achterberg K.V., Alonso-Zarazaga M.A., Araujo R., Asche M., Aspock U., Audisio P., Aukema B., Bailly N., Balsamo M., Bank R.A., Barnard P., Belfiore C., Bogdanowicz W., Bongers T., Boxshall G., Burckhardt D., Camicas J.-L., Chylarecki P., Crucitti P., Deharveng L., Dubois A., Enghoff H., Faubel A., Fochetti R., Gargominy O., Gibson D., Gibson R., Lopez M.S.G., Goujet D., Harvey M.S., Heller K.-G., Helsdingen P.V., Hoch H., De Jong H., De Jong Y., Karsholt O., Los W., Lundqvist L., Magowski W., Manconi R., Martens J., Massard J.A., Massard-Geimer G., Mcinnes S.I., Mendes L.F., Mey E., Michelsen V., Minelli A., Nielsen C., Nafrıa J.M.N., Van Nieukerken E.J., Noyes J., Pape T., Pohl H., De Prins W., Ramos M., Ricci C., Roselaar C., Rota E., Schmidt-Rhaesa A., Segers H., Zur Strassen R., Szeptycki A., Thibaud J.-M. (2007) The European union's 2010 target: putting rare species in focus. Biodiversity and Conservation, 139, 16785.
  • Garate-Lizarraga I., Siqueiros Beltrones D.A. (1998) Time variation in phytoplankton assemblages in a subtropical lagoon system after the 1982–1983 ‘EI Nino’ event (1984 to 1986). Pacific Science, 52, 7997.
  • Gaston K.J. (1994) Rarity. Chapman and Hall, London: 220.
  • Gaston K.J., Kunin W.E. (1997) Rare-common differences: an overview. In: Kunin W.E., Gaston K.J. (Eds), The Biology of Rarity: Causes and Consequences of Rare-Common Differences. Chapman and Hall, London: 1229.
  • Gaston K.J., Blackburn T.M., Greenwood J.J.D., Gregory R.D., Quinn R.M., Lawton J.H. (2000) Abundance-occupancy relationships. Journal of Applied Ecology, 37(Suppl. 1), 3959.
  • Gauch H.G. (1982) Multivariate Analysis in Community Ecology. Cambridge University, Cambridge: 298
  • Gering J.C., Crist T.O., Veech J.A. (2003) Additive partitioning of species diversity across multiple spatial scales: implications for regional conservation of biodiversity. Conservation Biology, 17, 488499.
  • Gotsis-Skretas O., Ignatiades L. (2007) Distribution of chlorophyll α in the Aegean and Ionian Sea. In: Papaconstantinou C., Zenetos A., Vassilopoulou V., Tserpes G. (Eds), State of the Hellenic Fisheries. HCMR, Athens: 2427.
  • Grime J.P. (1998) Banefits of plant diversity to ecosystems: immediate, filter and founder effects. Journal of Ecology, 86, 902910.
  • Hanski I. (1982) Dynamics of regional distribution: the core and satellite species hypothesis. Oikos, 38, 210221.
  • Hill M.O. (1973) Diversity and evenness: a unifying notation and its consequences. Ecology, 54, 427431.
  • Hillebrand H., Duerselen C.D., Kirschtel D., Pollingher U., Zohary T. (1999) Biovolume calculation for pelagic and benthic microalgae. Journal of Phycology, 35, 403424.
  • Hubbell S.P. (2001) The Unified Neutral Theory of Biodiversity and Biogeography. Princeton University Press, Princeton: 375.
  • Ignatiades L., Karydis M., Vounatsou P. (1992) A possible method for evaluating oligotrophy and eutrophication based on nutrient concentration scales. Marine Pollution Bulletin, 24, 238243.
  • Ignatiades L., Gotsis-Skretas O., Metaxatos A. (2007) Field and culture studies on the ecophysiology of the toxic dinoflagellate Alexandrium minutum (Halim) present in Greek coastal waters. Harmful Algae, 6, 153165.
  • Ignatiades L., Gotsis-Skretas O., Pagou K., Krasakopoulou E. (2009) Diversification of phytoplankton community structure and related parameters along a large east-west transect of the Mediterranean Sea. Journal of Plankton Research, 31, 441448.
  • Irwin A.J., Finkel Z.V., Schofield O.M.E., Falkowski P.G. (2006) Scaling-up from nutrient physiology to the size-structure of phytoplankton communities. Journal of Plankton Research, 28, 459471.
  • Jeffrey S.W., Hallegraef G.M. (1980) Studies of phytoplankton species and photosynthetic pigments in a warm core eddy of the East Australian Current. I. Summer populations. Marine Ecology Progress Series, 3, 285294.
  • Kuwata A., Miyazaki T. (2000) Effects of ammonium supply rates on competition between Microcystis novacekii (Cyanobacteria) and Scenedesmus quadricauda (Chlorophyta): simulation study. Ecological Modelling, 135, 8187.
  • Litchman E., Klausmeier C.A. (2008) Trait-based community ecology of phytoplankton. Annual Review of Ecology, Evolution, and Systematics, 39, 615639.
  • Llewellyn C.A., Gibb S.W. (2000) Intra-class variability in the carbon, pigment and biomineral content of prymnesiophytes and diatoms. Marine Ecology Progress Series, 193, 3344.
  • Llewellyn C.A., Fishwick J.R., Blackford J.C. (2005) Phytoplankton community assemblage in the English Channel: a comparison using chlorophyll a derived from HPLC-CHEMTAX and carbon derived from microscopy cell counts. Journal of Plankton Research, 27, 103119.
  • Loreau M., Hector A. (2001) Partitioning selection and complementarity in biodiversity experiments. Nature, 412, 7276.
  • Loreau M., Naeem S., Inchausti P., Bengtsson J., Grime J.P., Hector A., Hooper D.U., Huston M.A., Raffaelli D., Schmid B., Tilman D., Wardle D.A. (2001) Biodiversity and ecosystem functioning: current knowledge and future challenges. Science, 294, 804808.
  • Ludwig J.A., Reynolds J.F. (1988) Statistical Ecology: A Primer on Methods and Computing. J. Wiley and Sons, New York: 337.
  • Lyons K.G., Brigham C.A., Traut B.H., Schwartz M.W. (2005) Rare species and ecosystem functioning. Conservation Biology, 19, 10191024.
  • Magurran A.E. (2004) Measuring Biological Diversity. Blackwell Science Ltd., Oxford: 248.
  • Magurran A.E. (2005) Species abundance distributions: pattern or process? Functional Ecology, 19, 177181.
  • Margalef R. (1958) Information theory in ecology. General Systems, 3, 3671.
  • McGill B.J. (2003a) Strong and weak tests of macroecological theory. Oikos, 102, 679685.
  • McGill B.J. (2003b) Does mother nature really prefer rare species or are log-left-skewed SADs a sampling artefact? Ecology Letters, 6, 766773.
  • McGill B.J., Enquist B.J., Weiher E., Westoby M. (2006) Rebuilding community ecology from functional traits. Trends in Ecology and Evolution, 21, 178185.
  • McGill B.J., Etienne R.S., Gray J.S., Alonso D., Anderson M.J., Benecha H.K., Dornelas M., Enquist B.J., Green J.L., He F., Hurlbert A.H., Magurran A.E., Marquet P.A., Maurer B.A., Ostling A., Soykan C.U., Ugland K.I., White E.P. (2007) Species abundance distributions: moving beyond single prediction theories to integration within an ecological framework. Ecology Letters, 10, 9951015.
  • McIntire C.D., Overton W.S. (1971) Distributional patterns in assemblages of attached diatoms from Yaquina Estuary, Oregon. Ecology, 52, 758777.
  • Menden-Deuer S., Lessard E.J. (2000) Carbon to volume relationships for dinoflagellates, diatoms and other protist plankton. Limnology and Oceanography, 45, 569579.
  • Metaxatos A., Ignatiades L. (2011) Clearance rate in the venerid bivalve Callista chione (L) in response to endemic algal species and bacteria:effects of cell biovolume and body size. Marine and Freshwater Behaviour and Physiology, 44, 305320.
  • Naselli-Flores L., Padisak J., Albay M. (2007) Shape and size in phytoplankton ecology: do they matter? Hydrobiologia, 578, 157161.
  • Nee S., Harvey P.H., May R.M. (1991) Lifting the veil on abundance patterns. Proceedings of the Royal Society of London B, 243, 161163.
  • Ohlemüller R., Anderson B.J., Araújo M.B., Butchart S.H.M., Kudrna O., Ridgely R.S., Thomas C.D. (2008) The coincidence of climatic and species rarity: high risk to small-range species from climate change. Biology Letters, 4, 56857.
  • Padisák J., Hajnal E., Krienitz L., Lakner J., Üveges V. (2010) Rarity, ecological memory, rate of floral change in phytoplankton – and the mystery of the Red Cock. Hydrobiologia, 653, 4564.
  • Passy S.I., Legendre P. (2006) Are algal communities driven toward maximum biomass? Proceedings of the Royal Society of London B, 273, 26672674.
  • Rabinowitz D. (1981) Seven forms of rarity. In: Synge H. (Ed.), The Biological Aspects of Rare Plant Conservation. J. Wiley and Sons, New York: 205215.
  • Rabinowitz D., Cairns S., Dillon T. (1986) Seven forms of rarity and their frequencies in the flora of the British Isles. In: Soulé M.J. (Ed.), Conservation Biology: the Science of Scarsity and Diversity. Sinauer, Sunderland, MA: 182204.
  • Rampi L., Bernhard M. (1980) Chiave per la Determinazione delle Peridinee Pelagiche Mediterranee. Comitato Nazionale Energia Nucleare in Roma, Rome, T/BIO (80) 8.
  • Rampi L., Bernhard M. (1981) Chiave per la Determinazione delle Coccolithoforidee Mediterranee. Comitato Nazionale Energia Nucleare in Roma, Rome, T/BIO (81) 13.
  • Rhee G.-Y., Gotham I.J. (1980) Optimum N:P ratios and coexistence of planktonic algae. Journal of Phycology, 16, 486489.
  • Ricard M. (1987) Diatomophycees. In: Sournia A. (Ed.), Atlas du Phytoplancton Marin, Vol II. Editions du CNRS, Paris: 297.
  • Rocap G., Larimer F.W., Larimer J., Malfatti S., Chain P., Ahlgren N.A., Arellano A., Coleman M., Hauser L., Hess W.R., Johnson Z.I., Land M., Lindell D., Post A.F., Regala W., Shah M., Shaw S.L., Steglich C., Sullivan M.B., Ting C.S., Tolonen A., Webb E.A., Zinser E.R., Chisholm S.W. (2003) Genome divergence in two Prochlorococcus ecotypes reflects oceanic niche differentiation. Nature, 424, 10421047.
  • Schindler D.E., Chang G.C., Lubetkin S., Abella S.E.B., Edmondson W.T. (2003) Rarity and functional importance in a phytoplankton community. In: Kareiva P.M., Levin S.A. (Eds), The Importance of Species: Perspectives on Expendability and Triage. Princeton University Press, Princeton, NJ: 206220.
  • Shannon C.E., Weaver W. (1949) The Mathematical Theory of Communication. University of Illinois Press, Urbana: 117.
  • Smayda T.J., Reynolds C.S. (2003) Strategies of marine dinoflagellate survival and some rules of assembly. Journal of Sea Research, 49, 95106.
  • Sommer U. (2000) Scarcity of medium-sized phytoplankton in the northern Red Sea explained by strong bottom-up and weak top-down control. Marine Ecology Progress Series, 197, 1925.
  • Sommer U., Padisak I., Reynolds C.S., Juhasznagy P. (1993) Hutchison Heritage – the diversity disturbance relationship in phytoplankton. Hydrobiologia, 249, 17.
  • Sournia A. (1986) Atlas du Phytoplancton Marin. Vol. 1 Introduction, Cyanophydes, Dictyocho-phycies, Dinophyctes et Raphidophycees. Editions du CNRS, Paris. 219.
  • Spatharis S., Mouillot D., Chi T.D., Danielidis D.B., Tsirtsis G. (2009) A niche-based modeling approach to phytoplankton community assembly rules. Oecologia, 159, 171180.
  • Stelzer R.S., Lamberti G.A. (2001) Effects of N:P ratio and total nutrient concentration on stream periphyton community structure, biomass, and elemental composition. Limnology and Oceanography, 46, 356367.
  • Stomp M., Huisman J., de Jongh F., Veraart A.J., Gerla D., Rijkeboer M., Ibelings B.W., Wollenzien U.I.A., Stal L.J. (2004) Adaptive divergence in pigment composition promotes phytoplankton biodiversity. Nature, 432, 1047.
  • Sun J., Liu D. (2003) Geometric models for calculating cell biovolume and surface area for phytoplankton. Journal of Plankton Research, 11, 13311346.
  • Symstad A.J., Chapin F.S., Wall D.H., Gross K.L., Huenneke L.F., Mittelbach G.G., Peters D.P.C., Tilman D. (2003) Long-term and large-scale perspectives on the relationship between biodiversity and ecosystem functioning. BioScience, 53, 8998.
  • Tas S., Yilmaz I.N., Okus E. (2009) Phytoplankton as an indicator of improving water quality in the Golden Horn Estuary. Estuaries and Coasts, 32, 12051224.
  • Tokeshi M. (1996) Power fraction: a new explanation of relative abundance patterns in species-rich assemblages. Oikos, 75, 543550.
  • Tokeshi M. (1999) Species Coexistence: Ecological and Evolutionary Perspectives. Blackwell Science, Oxford: 454.
  • Tomas C.R. (1997) Identifying Marine Phytoplankton. Academic Press, New York: 858.
  • Trégouboff G., Rose M. (1957a) Manuel de Planktonologie Méditerranéenne. Tome I. CNRS, Paris: 587.
  • Trégouboff G., Rose M. (1957b) Manuel de Planktonologie Méditerranéenne. Tome II. CNRS, Paris: 203.
  • Ulrich W., Ollik M. (2004) Frequent and occasional species and the shape of relative-abundance distributions. Diversity and Distributions, 10, 263269.
  • Utermöhl M. (1958) Zur vervollkommnung der quantitativen phytoplankton methodik. Mitteilungen der Internationalen Vereinigung für Theoretische und Angewandte Limnologie, 9, 138.
  • Vázquez L.B., Gaston K.J. (2004) Rarity, commonness, and patterns of species richness: the mammals of Mexico. Global Ecology and Biogeography, 13, 535542.
  • Venrick E.L., Lange C.B., Reid F.M.H., Dever E.P. (2008) Temporal patterns of species composition of siliceous phytoplankton flux in the Santa Barbara Basin. Journal of Plankton Research, 30, 283297.
  • Verity P.G., Smetacek V., Smayda T.J. (2002) Status, trends and the future of the marine pelagic ecosystem. Environmental Conservation, 29, 207237.
  • Weithoff G. (2003) The concepts of ‘plant functional types’ and ‘functional diversity’ in lake phytoplankton – a new understanding of phytoplankton ecology? Freshwater Biology, 48, 16691675.
  • Willis K.J., Bhagwat S.A. (2009) Biodiversity and climate change. Science, 326, 806807.

Appendix: Rare species recorded in only one (singetons) or two (doubletons) sample units. *Gulfs: S (Saronikos), E (Evoikos), P (Pagassitikos), T (Thermaikos). Seasons: 1 (Spring), 2 (Summer), 3 (Autumn)

  1. Top of page
  2. Abstract
  3. Introduction
  4. Material and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Appendix: Rare species recorded in only one (singetons) or two (doubletons) sample units. *Gulfs: S (Saronikos), E (Evoikos), P (Pagassitikos), T (Thermaikos). Seasons: 1 (Spring), 2 (Summer), 3 (Autumn)
One sample unitOne sample unit
SpeciesGulf/Season*SpeciesGulf/Season*
Acanthoica aculeata (Kamptner)S1Goniodoma sphaericum (Murr. & Whitt.)S2
Acanthoica coranata (Lohmann)E1Gossleriella tropica (Schütt)T1
Acanthoica quattrospina (Lohmann)S1Grammatophora angulosa (Ehrenberg)E1
Acanthoica rubus (Kamptner)P2Grammatophora serpentina (Ehrenberg)E1
Alexandrium margalefii (Balech)E3Gymnodinium abbreviatum (Kof.&Swezy)S2
Alexandrium monilatum (Howell)S1Gymnodinium conicum (Kof.&Swezy)P2
Alexandrium tropicale (Balech)T3Gymnodinium fussum (Ehrenb.) SteinS3
Amphidinium crassum (Lohmann)P1Gymnodinium grammaticum (Pouchet)E1
Amphidinium herdmanii (Kofoid & Swezy)T2Gymnodinium mikimotoi (Miy.Kom.ex Oda)S3
Amphidinium pelagicum (Lebour)S2Gymnodinium rhomboids (Schütt)S3
Amphiprora angustata (spec. nov.)T3Gymnodinium stellatum (Hulburt)S1
Amphiprora hyalina (Cleve)E1Gymnodinium variabile (Herdman)E2
Amphora ocellata (Donkin)E2Gyrosigma balticum (Ehrenberg) CleveS2
Anthosphaera bicornu (Schlauder)S2Gyrosigma littorale (Wm. Smith) CleveE2
Anthosphaera fragaria (Kamptner)P1Gyrosigma wansbeckii (Donkin) CleveT3
Bacillaria paradoxa (Gmelin)E1Helicosphaera hyalina (Gaarder)P1
Bacteriastrum elongatum (Cleve)E1Helladosphaera richardi (Bernard)S3
Berkeleya micans (Grunow)T1Heterodinium whittingae (Kofoid)E1
Biddulphia sinensis (Greville)T3Lohmannosphaera citrus (Schlauder)T1
Cachonina niei (Loeblich)S1Mesoporus adriaticus (Schiller) LilllickP2
Calciosolenia murrayi (Gran)S1Mesoporus bisimpressus (Schiller) LilllickT1
Caloneis subsalina (Donkin) HendeyT3Mesoporus globulus (Schiller) LilllickT1
Calyptrosphaera circumspicta (Schiller)S2Mesoporus perforatus (Gran) LilllickE3
Calyptrosphaera galea (Lecal)E2Micracantodinium setiferum (Lohm.) Deflan.E2
Calyptrosphaera sphaeroidea (Schiller)T2Navicula calida (sp. nova)T3
Calyptrosphaera superba (Lecal)E1Navicula crucifera (Grun.) SchmidtS1
Calyptrosphaera tholifera (Kamptner)S1Navicula distans (Wm. Smith) SchmidtT2
Centrodinium eminens (Böhm)T2Navicula florinae (Møller)P3
Centrodinium maximum (Pavillard)T2Navicula menaiana (Hendey)E2
Ceratium geniculatum (Lemm.) CleveT1Navicula pennata (Schmidt)S1
Ceratium hexacanthum (Gourret)P1Navicula rossii (Salah)T3
Ceratoperidinium yeye (Margalef)S2Navicula rectangulata (Greg.) RabenhorstE3
Chaetoceros atlanticus (Cleve)T3Navicula transitans (Grunow) CleveP3
Chaetoceros brevis (Schütt)E1Okedenia inflexa (Eulenstein ex de Toni)E2
Chaetoceros concavicorne (Mangin)T3Ophiaster formosus (Gran)T3
Chaetoceros difficilis (Cleve)S2Oxytoxum caudatum (Schiller)S2
Chaetoceros messanensis (Castracane)T3Oxytoxum crassum (Schiller)P3
Chaetoceros seiracanthus (Gran)E2Oxytoxum cristatum (Kofoid)T2
Chaetoceros similis (Cleve)S1Oxytoxum globosum (Schiller)T2
Chaetoceros subsecuntum (Grunow) HustedtS2Oxytoxum obliquum (Schiller)P2
Chaetoceros tortissimus (Gran)E2Oxytoxum ovale (Schiller)T2
Cochlodinium achromaticum (Lebour)T3Oxytoxum minutum (Rampi)T2
Cochlodinium pulchellum (Lebour)S1Oxytoxum spinosum (Rampi)E3
Cyclococcolithus fragilis (Lohmann) DeflandreS1Oxytoxum tesselatum (Stein) Schütt P1
Dinopysis ovum (Schütt)T1Pinnularia cruciformis (Donkin) CleveE3
Diploneis crabo (Ehrenberg)E3Pinnularia rectangulata (Greg.) RabenhorstE3
Diplopsalis lenticula (Bergh)T3Podolampas palmipes (Stein)E3
Exuviaella baltica (Lohmann)P1Polykrikos kofoidii (Chatton)S1
Glenodinium cinctum (Ehrenberg)T1 Pomatodinium impatiens (Cachon &Cachon) T1
Glenodinium monensis (Herdman)E3Pontosphaera achillae (Kamptner)T2
Gonyaulax fragilis (Schütt) KofoidT3Pontosphaera haeckeli (Lohmann)E2
Gonyaulax milneri (Kofoid)P2Prorocentrum balticum (Lohmann) LoeblichS1
Gonyaulax mitra (Schütt) KofoidP3Prorocentrum dentatum (Stein)T1
Gonyaulax tamarensis (Lebour)T3Prorocentrum gracile (Schütt)S1
    
Prorocentrum minimum (Pavil.) SchillerT2 TWO SAMPLE UNITS *Gulfs/Season
Prorocentrum ovum (Schiller) DodgeS1  
Protoceratium aerolatum (Kofoid)S3Alexandrium pseudogonyaulax (Biecheler)T2, T3
Protoceratium pepo (Kofoid & Michener)T3Algirosphaera robusta (Lohmann) NorrisT2, T3
Protoperidinium bipes (Paulsen) BalechT3Amphora hyaline (Kützing)E2, P3
Protoperidinium conicum (Gran) BalechT2Calyptrosphaera dalmatica (Schiller)S3, T3
Protoperidinium marielebourae (Paulsen) BalechS1Centrodinium intermedium (Pavillard)S3, S1
Protoperidinium oceanicum (Vanhoffen)S1Chaetoceros anastomosans (Grunow)S2, P2
Protoperidinium quarnerense (Schröder)S3Cocconeis speciosa (Gregory)E1, P2
Pseudo-nitzschia granii (Hasle) P2Cochlodinium brandti (Wulff)E3, T3
Pseudo-nitzschia subcurvata (Hasle)P2Corisphaera corona (Kamptner)P3, P1
Pseudo-nitzschia turgidula (Hustedt)E3Deutschlandia cinera (Lecal)S1, T1
Pyrocystis elegans (Pavillard)S1Diploneis bombus (Ehrenberg) CleveS2, E1
Pyrocystis lunula (Schütt) SchüttS3Diploneis lineata (Donkin) CleveE3, E2
Rhabdonema adriaticum (Kützing)P3Fragilaria crotonensis (Kitton)S1, E2
Rhabdonema arcuatum (Lyngbye) KützingT1Goniaudoma spaericum (Murray & Whitting)S2, S3
Rhabdonema minutum (Kützing)P1Gonyaulax elegans (Rampi)S1, P1
Rhabdosphaera tubulosa (Schiller)T2Gonyaulax ligustica (Rampi)S2, P2
Rhaphoneis amphiceros (Ehrenberg)T3Gonyaulax monacantha (Pavillard)P1, P2
Rhizosolenia robusta (Norman)S3Gymnodinium heterostriatum (Kof.& Swezy)E2, T3
Sphaerocalyptra quandridentata (Schiller)S2Gymnodinium placidum (Herdman)E1, P1
Synedra superba (Kützing)E1Gyrodinium instriatum (Freud. & Lee)P2, T1
Synedra undulata (Bailey) GregoryS1Lohmannosphaera cedrus (Lecal)S1, S2
Syracolithus cordiformis (Schiller)S1Navicula linearis (Grunow) BoyerE2, E3
Syracolithus clypeatus (Lecal)E2Navicula meniscus (Schumann)P2, T2
Syracolithus pastillusus (Lecal)S3Oxytoxum ligusticum (Rampi)S1, T1
Syracolithus profundus (Bernard)T3Oxytoxum punctulatum (Rampi)T1, T3
Syracolithus schilleri (Kamptner)T2Oxytoxum rampii (Sournia)P1, P3
Syracosphaera prolongata (Gran)S2Oxytoxum sphaeroideum (Stein)S1, S3
Syracosphaera spinosa (Lohmann)P1Oxytoxum tenuistriatum (Rampi)E1, T2
Tergestiella adriatica (Kamptner)S1Oxytoxum viride (Schiller)S3, P1
Thalassionema bacillare (Heiden) KolbeP2Pachydinium verrucosum (Schiller)S2, S3
Thalassiosira mendiolana (Hasle & Heimdal)S1Palaeophalacroma unicinctum (Schiller)E1, P1
Tropidoneis confusa (spec. nova)S3Pontosphaera pellucida (Lohmann)S2, E2
Umbilicosphaera mirabilis (Lohmann)E2Pontosphaera syracusana (Lohmann)S1, P1
Zygosphaera amoena (Kamptner)E3Rhabdosphaera subopaca (Bernard)E2, P3
Zygosphaera hellenica (Kamptner)S1Surirella striatula (Turpin)E3, P2
Zygosphaera minor (Schlauder)T2Syracosphaera nodosa (Kamptner)S2, E3