Space–Time Patterns of Co-Variation of Biodiversity and Primary Production in Phytoplankton Guilds of Coastal Marine Environments

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AQUATIC CONSERVATION: MARINE AND FRESHWATER ECOSYSTEMS Aquatic Conserv: Mar. Freshw. Ecosyst. 13: 489–506 (2003) Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/aqc.590

Space–time patterns of co-variation of biodiversity and primary production in phytoplankton guilds of coastal marine environments

MARIA ROSARIA VADRUCCIa*, FABIO VIGNESb, ANNITA FIOCCAa, ALBERTO BASSETa, IMMACOLATA SANTARPIAb, GIAN CARLO CARRADAb, MARINA CABRINIc and SERENA FONDA UMANIc a Dipartimento di Science e Tecnologie Biologiche e Ambientali, Universita" di Lecce, Lecce, Italy b Dipartimento di Zoologia, Universita" degli Studi Federico II di Napoli, Napes, Italy c Dipartimento di Biologia, Universita" degli Studi di Trieste, Trieste, Italy

ABSTRACT 1. The relevance of biodiversity to ecosystem processes is a major topic in ecology. Here, we analyse the relationship between biodiversity and productivity of the nano- and micro- phytoplankton guilds in coastal marine ecosystems. 2. The patterns of variation of species richness, diversity and primary productivity (as 14C assimilation) were studied in two marine areas: a eutrophic–mesotrophic area beside the River Po delta (northern Adriatic) and an oligotrophic area around the Salento peninsula (southern Adriatic– Ionian). The study was carried out at 23 sites in the northern area and at 45 sites in the southern area. Sites were arranged on expected spatial and temporal gradients of primary productivity variation, according to distance from the coast, optical depths and seasonal period. 3. 167 taxa were identiﬁed in the northern area and 153 taxa in the southern area. In both areas, the taxonomic composition of the nano- and micro-phytoplankton guilds exhibited greater temporal than spatial variation. The latter was much higher in the southern area than in the northern area (average dissimilarity between stations being 70:7 0:8% and 44:7 4:2% respectively). 4. Primary productivity varied in space and time on the gradients considered. Phytoplankton species richness and diversity exhibited signiﬁcant patterns of variation in space and time; overall, these were inversely related to the primary productivity patterns in the northern area, whereas they were directly related in the southern area. 5. The small individual size and the high turnover rate of phytoplankton are likely to underlie the observed relationships, which emphasized a threshold response to nutrient enrichment in agreement with the ‘paradox of enrichment’. Under resource enrichment conditions, the high turnover of producers leads to hierarchical partitioning of the available resources with an increasing dominance of a few species. Therefore, the relationship observed here seems likely to be explained by the complementarity hypothesis. Copyright # 2003 John Wiley & Sons, Ltd.

*Correspondence to: Maria Rosaria Vadrucci, Dipartimento di Science e Tecnologie Biologiche e Ambientali, Universita" degli Studi di Lecce, Via Provinciale Lecce–Monteroni, 73100 Lecce, Italy. E-mail: [email protected]

KEY WORDS: phytoplankton; primary production; species diversity; coastal marine environment; spatial heterogeneity, Adriatic Sea; Ionian Sea

INTRODUCTION

In recent years, many ecosystems have suffered from a loss in biodiversity as a result of the expansion of anthropogenic activity. The implications of this activity on the ecosystem functions and the services that ecosystems perform are receiving increasing attention (Schulze and Mooney, 1994; Jones and Lawton, 1995; Schlaapfer. et al., 1999). For this purpose, studies of the relationship between biodiversity and ecosystem functioning have made rapid progress in the past decade (Purvis and Hector, 2000). These have tried to determine whether biodiversity influences ecosystem functioning and, if so, what the resulting effects of human-driven biodiversity loss could be on this. Moreover, the relative importance of the argument for the conservation of species has been widely discussed (Bond and Chase, 2002). Different paradigms have arisen with regard to the diversity–function issue (Naeem et al., 1994; Tilman et al., 1996; Hooper and Vitousek, 1998; Laakso and Setaal. aa,. 1999), and this has hampered government action in terms of implementing strategies for the protection of biological diversity. The theory of niche and competition has dealt, albeit indirectly, with this relationship since the 1960s (MacArthur and Levin, 1967), pointing to direct and reciprocal links between biodiversity and productivity. The hypothesis of a direct relationship between species diversity and productivity is based on the assumption that the inter-specific differences in the use of resources by plants allow guilds characterized by greater diversity to make more efficient use of limiting resources (McNaughton, 1994; Tilman et al., 1996). This approach, based on niche partitioning, has recently been defined as the complementarity hypothesis (Fridley, 2001). A direct relationship between biodiversity and productivity has been observed primarily in terrestrial ecosystems in terms of both taxonomic (Tilman et al., 1996; Hector et al., 1999) and functional diversity (Tilman et al., 1997a; Hector et al., 1999). This emerges from field studies (Pianka, 1966; Currie and Paquin, 1987; Currie, 1991), microcosm experiments with manipulation of the number of species (Naeem et al., 1994) and mesocosm experiments (Tilman et al., 1996; Hector et al., 1999). A direct relationship between biodiversity and productivity is also supported by mathematical modelling of non-equilibrium systems, as a probabilistic effect of increasing the number of species (i.e. sampling effect; Tilman et al., 1997b; Loreau, 1998). On the other hand, the likelihood of a direct relationship between diversity and productivity seems to depend on the spatial heterogeneity of the environment (Jansen and Mulder, 1999; Fridley, 2001) and on nutrient enrichment (‘paradox of enrichment’; Rosenzweig, 1971), which limit the potential for resources partitioning among co-existing species. Indeed, the mechanism by which resources are partitioned assumes that there is heterogeneity at the scale of species response (Bell and Lechowicz, 1994). In marine environments with small producers and a high turnover, cases of nutrient enrichment have consistently been associated with increases in primary production and reductions in the number of species and diversity of producers (Margalef, 1978; Huston, 1994; Valiela, 1995). The form and the meaning of the diversity–productivity relationship are thus still controversial and seem to depend on the mechanisms that underlie the organization of communities and the evolution of biodiversity (Jansen and Mulder, 1999; Fridley, 2001), and which result in the differences between various types of ecosystem. Marine coastal ecosystems, by virtue of their highly dynamic nature and the temporal and spatial heterogeneity of their main physico-chemical characteristics on well-defined gradients of variation,

Copyright # 2003 John Wiley & Sons, Ltd. Aquatic Conserv: Mar. Freshw. Ecosyst. 13: 489–506 (2003) DIVERSITY–PRODUCTIVITY RELATIONSHIP IN PHYTOPLANKTON GUILDS 491 constitute natural laboratories in which the diversity–productivity relationship can be studied on short time scales, suitable for experimental analysis. The aim of this study is to analyse the relationship between diversity of phytoplankton producer guilds and primary production in two marine coastal areas, by verifying:

1. the existence and form of the diversity–productivity relationship in marine coastal environments; 2. the role of nutrient enrichment and spatial heterogeneity in taxonomic abundance, diversity and evenness of phytoplankton guilds, and in the relations of these with primary production; and 3. the relevance of complementarity and the sampling eﬀect in determining the diversity–productivity relationship in marine coastal environments.

To this end, the structural characteristics and primary production of nano- and micro-phytoplankton guilds, taxonomically identifiable using Utermoohl’s. method, were studied on gradients of productivity that were identifiable a priori, in two marine areas of the Adriatic–Ionian: (i) the northern Adriatic, with high trophic levels (Fonda Umani et al., 1992; Zoppini et al., 1995; Alberighi et al., 1996); (ii) the southern Adriatic–Ionian, characterized by low trophic levels (Fonda Umani et al., 1992; Rabitti et al., 1994; Socal et al., 1999; Zavatarelli et al., 2000). The original data, on which this study is based, were gathered during the PRISMA II and INTERREG II Italy–Greece oceanographic cruises, for the northern Adriatic and southern Adriatic–Ionian areas respectively, with methods that were similar, though not identical, and with different sampling times. In the present study, the two sets of data are analysed separately and the comparison between the two areas concerns only the existence or otherwise of the diversity–productivity relationship and, where appropriate, its shape.

MATERIALS AND METHODS

Sample collection The data relating to the structural and functional characteristics of the nano- and micro-phytoplankton guilds were gathered in the northern Adriatic in the course of four oceanographic cruises pertaining to sub- project 2 of the PRISMA II project and in the southern Adriatic–Ionian in the course of three oceanographic cruises pertaining to the INTERREG II Italy–Greece project. In the northern Adriatic the cruises were carried out from June 1996 to February 1998, on two parallel transects (three in the first cruise) in the area beside the River Po delta, affected by the frontal system resulting from the flow of fresh water into the central–northern Adriatic basin (Figure 1(a)). In each cruise, six sampling stations were positioned along the transects; the exception was for the cruise of June 1997, when five sampling stations were positioned. Therefore, 23 stations were sampled globally; these were then organized for data analysis into seven groups, according to their distance from the coast (see the ‘Treatment of data’ section below). Sampling was carried out using Niskin 10–12 L bottles at five optical depths, corresponding to levels of 100%, 30%, 12%, 4% and 1% of surface photosynthetic active radiation (SPAR). Light penetration was determined by a PNF 300 quantimeter (Biospherical Instruments). The determination of the nano- and micro-phytoplankton was carried out for the five optical levels and also near the bottom. In the southern Adriatic–Ionian, the cruises were carried out from March 2000 to September 2000, along seven transects (five in the first cruise) distributed between Torre Guaceto and Porto Cesareo (Figure 1(b)). Seven stations were positioned along each transect. Phytoplankton samples were collected only in three stations, and only at the first optical depth (100% SPAR).

Copyright # 2003 John Wiley & Sons, Ltd. Aquatic Conserv: Mar. Freshw. Ecosyst. 13: 489–506 (2003) 492 M. R. VADRUCCI ET AL.

Laboratory measurements The present study analyses the data relating to the taxonomic composition and primary production of nano- and micro-phytoplankton, defined as the component held by filters having a porosity of 2 mm (Sieburth, 1979). Taxonomic composition in the nano- and micro-phytoplankton guild was assessed using Utermoohl’s. method (Zingone et al., 1990). Inverted microscopes (Zeiss Axiovert 100 and Nikon T300E) were used, at 400 magnification after sedimentation of sub-samples for a period depending on the volume of the counting chamber. The sub-samples were fixed with neutralized formaldehyde (20 mL formaldehyde per 450 mL of sample) in the PRISMA II project and with Lugol solution (15 mL Lugol per litre of sample) in the INTERREG II project. For each sub-sample, 200 cells were counted and identified. Phytoplankton nomenclature was according to Tomas (1997). The determination of primary production was similar in the PRISMA II and INTERREG II projects. The 14C method was used to estimate primary production according to Magazzu" et al. (1996). Samples of water were taken using Niskin bottles and divided into clear and dark bottles ð450 mLÞ; 1mLof 14 14 bicarbonate marked with C ðNaH CO3Þ with activity density of 10–20 mCi mL was then immediately added to each bottle. The bottles were placed in a continuous-flow deck incubator in sunlight for 4 h. Furthermore, in the PRISMA II project, the incubator was equipped with a series of nickel optical screens (Stork Veco International) with open areas of 30%, 12%, 4% and 1% in order to reproduce the optical levels of the samples. To measure phytoplankton primary production, the samples were then passed through polycarbonate filters with a porosity of 2 mm (Nucleopore). The filters were stored in 20 mL vials to which 100 mLof0:01n HCl was added. After 12 h, 10 mL of scintillation cocktail was added using NEN-Aquasol 2 (PRISMA II) and Packard-Istagel Plus (INTERREG II) as scintillation liquids. The vials were left overnight in liquid scintillation counters (Beckman LS-1801 in the PRISMA II project and Packard TRI-CARB 1900 in the INTERREG II project) and then counted. Six readings of each sample were performed. Vials with blank filters were used for background counts, which were subtracted from each sample. The resulting values were converted into disintegrations per minute using the quench curves obtained with the two scintillation liquids; the counting efficiency of the unquenched standards was always higher than 95%. Dark uptake rates were subtracted from light uptake rates to obtain the photosynthetic carbon uptake. Dissolved inorganic carbon was measured by potentiometric titration with 0:01n HCl.

Treatment of data The work is based on the analysis of patterns of variation in diversity and production in nano- and micro- phytoplankton guilds on gradients of productivity identifiable a priori. The data gathered were arranged on gradients of temporal (seasons) and inshore–offshore variation in both areas and on the surface–seabed gradient in the northern area. For the analysis of the patterns of variation along the inshore–offshore gradient in the northern area, the stations in the two or three parallel transects were grouped according to their distance from the coast, which in each cruise depended on the position of the frontal system. Overall, in the northern area, this resulted in three groups of stations in the winter and four groups of stations in the summer (Table 1, Figure 1(a)). Biodiversity was evaluated from taxonomic richness data, species diversity and evenness. Three of the most commonly used diversity indices were compared here: Simpson, Margalef, and Shannon–Wiener, each of which has a different sensitivity to the occurrence of rare species (Krebs, 1989). The calculation of the indices did not take into account the phytoflagellates, which include organisms belonging to various classes, and the heterotrophic dinoflagellates.

Copyright # 2003 John Wiley & Sons, Ltd. Aquatic Conserv: Mar. Freshw. Ecosyst. 13: 489–506 (2003) DIVERSITY–PRODUCTIVITY RELATIONSHIP IN PHYTOPLANKTON GUILDS 493

Table 1. Position of the sampling stations in the northern Adriatic as distance from the coast Station Distance (nautical miles) Jun ’96 Feb ’97 Jun ’97 Feb ’98 11432810 2 20421518 325 18 4 40502524

Figure 1. Position of the sampling stations: (a) in the northern Adriatic Sea during four oceanographic cruises of the PRISMA II project (*, sampling stations in the summer period; *, sampling stations in the winter period); (b) in the southern Adriatic–Ionian Sea during three oceanographic cruises of the INTERREG II project.

In this paper, most taxa were recognized at the species level, some were recognized at the genus level and a few at order level. On the other hand, since recognized species accounted for at least 70% of the individuals sampled, the observed patterns of biodiversity are probably affected by taxonomic uncertainty only to a minor extent. Comparisons of similarity of taxonomic composition between stations were also carried out using the Renkonen (1938) index. In both areas, the sampling was based on a factorial experimental design. For the northern area, the data were analysed using a three-way analysis of variance (ANOVA), substituting the missing data from the second station during the winter period with the averages of the first and third stations. For the southern area, the number of samples lost during the first cruise made it necessary to analyse the contribution of the three sources of variation separately, using a one-way ANOVA. Owing to the potential spatial autocorrelation of data, ANOVA is used here only to compare the relevance of the different potential sources of variation of observed biodiversity and productivity.

RESULTS

Northern Adriatic Structure of the phytoplankton guilds In the period of study considered here, 167 phytoplankton taxa were identiﬁed overall, belonging to the nano- and micro-phytoplankton fractions, of which 16 were common to all sampling cruises and 80 were

Copyright # 2003 John Wiley & Sons, Ltd. Aquatic Conserv: Mar. Freshw. Ecosyst. 13: 489–506 (2003) 494 M. R. VADRUCCI ET AL.

Figure 2. Relative importance of the main nano-/micro-phytoplankton groups in the northern Adriatic (DIA ¼ diatoms; DIN ¼ dinoflagellates; COC ¼ coccolithophorids; PHY ¼ phytoflagellates; Other ¼ Crysophyiceae, Cryptophyceae, Prasinophyceae, Primnesiophyiceae, Chlorophyceae, Dyctiochophyceae, Cianophyceae and Euglenophyceae). present in just one cruise. Dinoflagellates (Dinophyceae) made up 44.6% of the taxa and 40.4% were diatoms (Bacillariophyceae), with centric diatoms (44 taxa) prevailing over pennate diatoms (23 taxa). Moreover, few species of diatom were dominant in all seasonal periods (Figure 2). Cerataulina pelagica and Chaetoceros decipiens were dominant in summer 1996 and in summer 1997 respectively, with relative percentages of 53.4% and 34.7% respectively of the total phytoplankton guild. Skeletonema costatum and Pseudonitzschia delicatissima were the dominant species in the winter period, with relative percentages of 67.8% and 24.6% respectively in February 1997, and 6.7% and 79.2% respectively in February 1998. The dinoflagellates, on average, made up only 10% of the phytoplankton guild in the summer period and 2% in the winter period. Among the dinoflagellates, the dominant genera were Prorocentrum, Ceratium and Oxytoxum for thecate forms and Amphidinium, Gyrodinium and Gymnodinium for athecate forms. The other phytoplankton groups were quantitatively less well represented (Figure 2), with a greater relative importance, however, in the summer period compared with the winter.

Patterns of spatio-temporal variation in the structure and processes of the phytoplankton guilds All the structural and functional characteristics studied here, with the exception of the number of species, showed signiﬁcant variations between seasons, but not between the two cruises carried out in the same seasons (Table 2), the data for which are therefore averaged in the following analyses. Primary production and cell density had higher average values in winter than in summer; whereas diversity (Hs) and evenness had the lowest values in winter. The diﬀerent diversity indices showed a similar pattern of temporal variation (Table 2), and only the results relative to the Shannon–Wiener index are given here (Hs). The taxonomic composition of the phytoplankton guilds showed greater temporal variation than spatial variation: the within-cruise average similarity (PS; Renkonen, 1938) was 57:7 4:2%, whereas the among- cruise average similarity was 15:2 1:1%. (Student’s t test; t ¼ 9:86; d:f: ¼ 251; p50:01); moreover, the

Copyright # 2003 John Wiley & Sons, Ltd. Aquatic Conserv: Mar. Freshw. Ecosyst. 13: 489–506 (2003) DIVERSITY–PRODUCTIVITY RELATIONSHIP IN PHYTOPLANKTON GUILDS 495

Table 2. Average values and coeﬃcient of variation (CV) of the functional and structural features of the phytoplankton guilds studied in the northern Adriatic Phytoplankton guild Summer Winter characteristics1 June 1996 June 1997 February 1997 February 1998 Average CV (%) Average CV (%) Average CV (%) Average CV (%) Cell density (cell/litre) 83 756 16.8 b 54 874 12.4 b 832 504 42.7 a 1 565 407 61.7 a Diversity Simpson 3.337 21.3 a 3.472 27.4 a 2.519 57.6 b 2.362 62.4 b Margalef 1.431 7.6 a 0.965 21.9 c 0.888 55.9 d 1.106 26.3 b Shannon–Wiener 1.453 16.8 a 1.455 12.4 a 1.119 42.7 b 0.938 61.7 b eH 4.916 19.7 a 4.909 14.5 a 3.408 69.7 b 3.407 64.9 b

Number of species 13.2 13.1 a 10.0 35.2 b 11.5 41.3 a 13.7 9.4 a

Evenness 0.582 19.9 a 0.694 24.9 a 0.443 21.6 b 0.355 58.7 b

Taxonomic similarity 44.3 79.4 c 28.1 64.9 c 82.9 11.2 a 66.1 29.4 b between stations (%)

Primary production2 0.4 55.4 b 0.6 45.6 b 1.2 77.7 a 1.3 126.1 a ðmgC m3=h1Þ 1 For each characteristic, the averages marked with the same letter are not statistically different (Student’s t test; p50:05); a is always associated to the higher value. 2 Average of five optical levels. spatial heterogeneity of the taxonomic composition of the phytoplankton guilds was much lower in winter ðPS ¼ 78:1 3:2%Þ than in summer ðPS ¼ 36:2 1:7%; Student’s t test; t ¼ 5:15; d:f: ¼ 53, p50:01). Primary production showed significant spatial heterogeneity, both on the inshore–offshore gradient with a progressive reduction as the distance from the coast increased (Table 3, Figure 3) and on the surface- seabed gradient with a progressive reduction as the light intensity decreased (Table 3, Figure 4). On both gradients, the range of variation was greater in the winter period than in summer. Phytoplankton species diversity also showed significant spatial variations, rising progressively as the distance from the coast increased (Table 3, Figure 3) and as light intensity decreased (Figure 4), although the pattern was significant only on the inshore–offshore gradient. The patterns of species diversity were due to the evenness component, since species richness remained relatively constant. A much stronger relationship between diversity and evenness than between diversity and number of species was observed. Evenness showed regular patterns of variation on both the gradients and showed broader variations in winter than in summer: there were similar values between seasons in the stations far from the coast and at deeper optical levels, and there were markedly different values in the coastal stations and at surface levels. The percentage difference between summer and winter in the evenness of phytoplankton guilds y was directly propor- tional to the winter values for primary production x on both gradients of variation (i.e. inshore– offshore: y ¼ 7:34x þ 23:13; r ¼ 0:996; d:f: ¼ 1, n.s. surface–seabed: y ¼ 7:78x þ 28:6; r ¼ 0:94; d:f: ¼ 3; p50:05Þ. In the northern Adriatic, phytoplankton species diversity was inversely related to primary production after pooling all data (Figure 5), as well as on both gradients of spatial variation (Figure 6). When the data were analysed on a seasonal basis, a statistically significant inverse relation between diversity and productivity was seen on both gradients of spatial variation only in the winter period (Figure 6).

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Southern Adriatic–Ionian Structure of the phytoplankton guilds In the period of study considered here, 153 phytoplankton taxa were identiﬁed overall, belonging to the nano- and micro-phytoplankton fractions; of these, 34 were present in all three sampling cruises, and 77

Table 3. Three-way ANOVA of average values of diversity (Hs), number of species and primary production of nano-micro/ phytoplankton guilds in the northern Adriatic in relation to three potential variation sources: seasons, position of sampling stations along the inshore–oﬀshore gradient (stations) and optical depths Source of variation Diversity Number of species Primary production d.f. Fp d.f. Fp d.f. Fp Seasons 1 24.08 50.001 1 0.12 0.727 1 25.41 50.001 Stations 3 7.35 50.001 3 1.79 0.163 3 9.8 50.001 Optical depths 4 2.04 0.106 4 2.67 0.045 4 10.8 50.001 Seasons Stations 3 2.02 0.125 3 6.46 0.001 3 5.14 0.004 Seasons Optical depths 4 0.73 0.571 4 2.57 0.052 4 5.05 0.002 Seasons Optical depths 12 0.39 0.957 12 0.98 0.481 12 1.42 0.197 Seasons Stations Optical depths 12 0.27 0.99 12 0.59 0.835 12 0.78 0.662 Errors 40 40 40

Summer Winter 4 4 3 3 2 2 1 1 Diversity (Hs) 0 0 1234 1234 40 40 30 30 20 20 10 10

Number of species 0 0 1234 1234 5 5 4

-1 4 h

-3 3 3 2 2

mgCm 1 1

Primary Production 0 0 1234 1234 Inshore > offshore Inshore > offshore Figure 3. Inshore–oﬀshore patterns of variation of diversity (Hs), number of species and primary production in the northern Adriatic during summer and winter periods. Average values are reported in the ﬁgure; the vertical bars are plus/minus one standard deviation.

Copyright # 2003 John Wiley & Sons, Ltd. Aquatic Conserv: Mar. Freshw. Ecosyst. 13: 489–506 (2003) DIVERSITY–PRODUCTIVITY RELATIONSHIP IN PHYTOPLANKTON GUILDS 497

Figure 4. Patterns of spatial variation on a surface–seabed gradient of diversity (Hs), number of species and primary production in the northern Adriatic during summer and winter periods. Average values are reported in the ﬁgure; the horizontal bars are plus/minus one standard deviation.

were observed exclusively in one of them. In terms of numerical abundance, the relative importance of the main phytoplankton groups showed substantial variations between cruises (Figure 7). In the first cruise the dominant groups were phytoflagellates and diatoms, which made up 45.0% and 44.3% respectively; of the phytoplankton guild in the second cruise the dinoflagellates were dominant, with a relative importance of 52.2%; in the third cruise the diatoms and dinoflagellates were dominant, and together accounted for 59.2% of the nano- and micro-phytoplankton guild. In the third cruise, 24.1% of the phytoplankton guild was made up of generally less well represented groups: Cryptophyceae (22.6%), Dictyochophyceae (1.2%) and Euglenophyceae (0.3%). The highest density diatom was Cylindrotheca (13.3%) in the first cruise, Chaetoceros (32.1%) in the second, and Nitzschia (6.5%) in the third. The most abundant genus of dinoflagellates was Amphidinium (10.3%) in the second cruise and Gymnodinium (14.9%) in the third.

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1 0.01 0.1 1 10 0.1 y = 0.84x-0.20 Diversity (Hs) r=0.424 df=97 p<0.001 0.01 Primary Production (mgCm-3h-1) 100

1 0.01 0.1 1 10 0.1 y = -0.118Ln(x) + 12.34 Number of species r =0.032 df = 97 n.s. 0.01 Primary production ( mgCm-3h-1)

y = 1.92x + 0.200 4 r = 0.792 df= 97 p<0.001 3 2 1

Diversity (Hs) 0 0 0.2 0.4 0.6 0.8 1 Evenness 4 y = 0.031x + 0.899 3 r=0.298 df= 97 p<0.01 2 1

Diversity (Hs) 0 0 10203040 Number of species Figure 5. Analysis of regression between diversity, species richness and primary production in the northern Adriatic. The roles of the number of species and evenness in determining the diversity values are also compared.

Patterns of spatio-temporal variation in the structure and processes of the phytoplankton guilds In the southern area, all the structural and functional characteristics studied here showed low temporal variability, with the exceptions of cell density and number of species (Tables 4 and 5). The greatest difference was observed for cell density, which globally underwent a twofold increase in the period of study, from 61 873 cell/litre to 124 539 cell/litre (Table 4). Significant temporal differences were also observed for the number of species (Tables 4 and 5). On the other hand, the taxonomic composition of the nano- and micro-phytoplankton guilds showed high spatial heterogeneity, with low similarity between stations

Copyright # 2003 John Wiley & Sons, Ltd. Aquatic Conserv: Mar. Freshw. Ecosyst. 13: 489–506 (2003) DIVERSITY–PRODUCTIVITY RELATIONSHIP IN PHYTOPLANKTON GUILDS 499

Northern Adriatic Northern Adriatic 4 4 y = -0.292Ln(x) + 1.036 3 y = -0.268Ln(x) + 1.047 3 r=0.747 df =16 p<0.001 2 r=0.721 df=21 p<0.001 2 1 1

Diversity (Hs) Diversity 0 0 012345 012345

Northern Adriatic - Winter Northern Adriatic -Winter 4 4 3 y = -0.266Ln(x) + 0.889 3 y = -0.268Ln(x) + 0.929 2 r=0.792 df= 10 p<0.01 2 r = 0.886 df =7 p<0.01 1 1

Diversity (Hs) Diversity 0 0 012345012345

4 Northern Adriatic- Summer 4 Northern Adriatic - Summer 3 3 2 2 1 1 Diversity (Hs) Diversity 0 0 012345012345 (a) Primary production (mgCm-3h-1) (b) Primary production (mgCm-3h-1) Figure 6. Analysis of regression between diversity, species richness and primary production in the northern Adriatic: along inshore– oﬀshore (a) and surface–seabed (b) gradients of variation.

100 90 80 70 60 50 40 30 20 Relative importance (%) 10 Mar '00 Jun '00 0 Set '00 DIA DIN COC PHY Other Phytoplankton groups Figure 7. Relative importance of the main nano-/micro-phytoplankton groups in the southern area (DIA ¼ diatoms; DIN ¼ dinoflagellates; COC ¼ coccolithophorids; PHY ¼ phytoflagellates; Other ¼ Cryptophyceae, Dyctiochophyceae, Cianophyceae and Euglenophyceae).

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Table 4. Average values and coeﬃcient of variation (CV) of the functional and structural features of the nano-microphytoplankton guilds studied in the southern Adriatic-Ionian Phytoplankton guild Spring March 2000 Summer June 2000 Autumn September 2000 characteristics1 Average CV (%) Average CV (%) Average CV (%) Density (cell/litre) 61 873 90.8 b 76 290 75.6 b 124 539 67.9 a Diversity Simpson 6.284 42.8 a 5.938 51.1 a 5.233 42.7 a Margalef 1.505 34.5 c 2.409 33.9 a 1.821 25.0 b Shannon–Wiener 2.281 16.1 a 2.268 22.5 a 2.051 18.3 a eH 10.385 34.5 a 10.708 42.1 a 8.280 35.8 a

Number of species 17.1 37.8 c 27.3 32.0 a 218 125 22.3 b

Evenness 0.824 13.5 a 0.700 10.1 b 0.668 14.0 b

Taxonomic similarity 23.8 46.4 c 32.8 36.3 a 29.4 55.7 b between stations (%)

Primary production2 0.7 62.0 a 0.4 54.0 b 0.6 51.0 a ðmgC m3 h1Þ 1 For each characteristic, the averages marked with the same letter are not statistically diﬀerent (Student’s t test; p50:05); a is always associated to the higher value. 2 Superﬁcial level only.

Table 5. One-way ANOVA of average values of diversity (Hs), number of species and primary production of nano-/micro- phytoplankton guilds in the southern area of study in relation to three potential sources of variation: temporal, position of sampling stations along the inshore–oﬀshore gradient (stations) and the position of sampling transects along the north–south gradient Source of variation Diversity Number of species Primary production d.f. Fpd.f. Fpd.f. Fp Seasons 2–36 0.952 0.396 2–36 4.726 0.015 2–36 2.917 0.067 Stations 2–36 4.234 0.020 2–36 1.595 0.217 2–36 2.786 0.075 North–South 7–31 0.660 0.703 7–31 1.032 0.430 7–31 0.804 0.591

ðPS ¼ 28:66 0:83Þ and seasons ðPS ¼ 14:47 0:63Þ. Greater spatial heterogeneity was observed in the first cruise, when similarity ðPS ¼ 23:81Þ was significantly lower than in the second ðPS ¼ 32:76; Student’s t test, t ¼ 4:98; d:f: ¼ 168; p50:01) and in the third ðPS ¼ 29:41; Student’s t test, t ¼ 2:77; d:f: ¼ 183; p50:01) cruises. In the second and third cruises, primary production showed a pattern of variation that was directly related to the distance from the coast (Figure 8, Table 5); globally, the relationship was close to statistical power of 0.1. In the southern area, pooling all data showed that the taxonomic diversity and primary production of the nano- and micro-phytoplankton guild were directly and significantly related (Figure 9). Evenness and number of species contributed to this relationship to a similar degree, with both parameters being strongly related to diversity (Figure 9). The relations between taxonomic diversity, taxonomic richness and production were generally positive even when the individual cruises or gradients of variation were considered separately. Relationships with primary production x were significant only for the second cruise, carried out during the summer season when highest species richness y1 and taxonomic diversity y2 values

Copyright # 2003 John Wiley & Sons, Ltd. Aquatic Conserv: Mar. Freshw. Ecosyst. 13: 489–506 (2003) DIVERSITY–PRODUCTIVITY RELATIONSHIP IN PHYTOPLANKTON GUILDS 501

Spring Summer Autumn

4 4 4 3 3 3 2 2 2 1 1 1 Diversity (Hs) 0 0 0 123 123 123

40 40 40 30 30 30 20 20 20 10 10 10 0 0 0 Number of species 123 123 123

2 2 2 -1 h -3 1 1 1 mgCm 0 0 0 Primary production 123 123 123 Inshore > offshore Inshore > offshore Inshore > offshore Figure 8. Inshore–oﬀshore patterns of variation of diversity (Hs), number of species and primary production in the southern area during spring, summer and autumn periods. Average values are reported in the ﬁgure; the vertical bars are plus/minus one standard deviation.

were observed ðy1 ¼ 0:45 lnðxÞþ2:34; r ¼ 0:525; d:f: ¼ 14; p50:05; y2 ¼ 7:47 lnðxÞþ36:8; r ¼ 0:637, d:f: ¼ 14; p50:05Þ.

DISCUSSION

The results of this study emphasized three main points: 1. the existence of signiﬁcant relationships between taxonomic diversity, taxonomic richness and productivity of phytoplankton guilds in both areas of study; 2. the inﬂuence of the level of trophy of the marine ecosystems on the way phytoplankton biodiversity and productivity are related (i.e. directly or inversely); 3. the relevance of niche complementarity as the community assembly rule underlying these relationships in both study areas.

In this paper we studied the relationship between phytoplankton biodiversity and productivity in two marine coastal areas; only regression slopes are compared among areas. Biodiversity and productivity were assessed with standard and similar techniques in the two areas (see ‘Materials and Methods’ section).

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y = 2.32x0.12 10 r=0.32 df=37 p<0.05

1 0.01 0.1 1 10 Diversity (Hs) 0.1 Primary production (mgCm-3h-1 )

y = 25.82x0.21 100 r=0.309 df=37 n.s. 10

1 0.01 0.1 1 10 Number of species 0.1

Primary production (mgCm-3h-1)

4 y = 3.35x - 0.187 3 r=0.73; df=37; p<0.001 2 1 Diversity (Hs) 0 0.0 0.2 0.4 0.6 0.8 1.0 Evenness 4 y = 0.04x + 1.15 3 r=0.77; df=37; p<0.001 2 1

Diversity (Hs) 0 0 1020304050 Number of species Figure 9. Analysis of regression between diversity, species richness and primary production in the southern area. The roles of the number of species and evenness in determining the diversity values are also compared.

Moreover, the only difference between the two experimental designs, i.e. sampling on optical depth in the northern area did not affect the shape of the biodiversity–productivity relationships, which was negative and with similar slope and significance level even accounting for only the data collected at the uppermost layer (100% SPAR). Therefore, the results are independent of the slightly different methodologies used in the two areas. The first point of discussion is supported, above all, by the significant relationships observed between productivity and diversity in the nano- and micro-phytoplankton guilds in the two areas considered. The

Copyright # 2003 John Wiley & Sons, Ltd. Aquatic Conserv: Mar. Freshw. Ecosyst. 13: 489–506 (2003) DIVERSITY–PRODUCTIVITY RELATIONSHIP IN PHYTOPLANKTON GUILDS 503 statistical significance of these relationships was higher in the northern area than in the southern area, in relation to the stronger inshore–offshore productivity gradients observed in the former area than in the latter area as a result of the freshwater inputs. A dependence of spatial gradients on the freshwater runoff has already been reported for many abiotic and biotic ecosystem features (such as salinity, nutrient concentration and phytoplanktonic biomass) in the northern area (Kuzmic and Orlic, 1995; Giordani et al., 1997; Zavatarelli et al., 1998), as well as in other coastal marine areas affected by river inflow (Justic et al., 1995). In the southern area, the freshwater inflow is negligible and primary production showed site-to-site variations according with local factors more than regular variation patterns on spatial gradients. Primary productivity measures accorded with the data available both for other northern Adriatic areas at a comparable distance from the coast (Fonda Umani et al., 1992; Relevante and Gilmartin, 1995; Zoppini et al., 1995; Alberighi et al., 1996; Degobbis et al., 1996) and for southern Adriatic–Ionian areas (Fonda Umani et al., 1992; Rabitti et al., 1994; Socal et al., 1999; Zavatarelli et al., 2000). The second point of discussion is related to the shape of the productivity–biodiversity relationships. For the northern Adriatic area we observed inverse relationships between primary productivity and taxonomic diversity or species richness, whereas for the Southern area of study we always observed direct relationships between these ecosystem features. These results seem likely to depend on the different availability of nutrients of the two areas (Fonda Umani et al., 1992). A comparative study on the biogeochemical characteristics of the Adriatic Sea reported concentrations three times higher in the northern area than in the southern area both for nitrates (3:1 mm versus 0:8 mm) and for phosphates (0:12 mm versus 0:04 mm) (Zavatarelli et al., 1998). The Adriatic basin exhibited a generally decreasing trend of nutrient concentrations from north to south, in particular due to the higher nutrient input by rivers occurring in the northern Adriatic area. Also, the prevailing cyclonic circulation of the Adriatic basin leads to stronger inshore–offshore gradients being observed in the northern area than in the southern area (Zavatarelli et al., 1998). In marine environments, contrasting patterns of variation between productivity and diversity of the phytoplankton guilds have already been observed on broad gradients of spatial variation (Huston, 1994) or on gradients of productivity linked to eutrophication or upwelling (Margalef, 1978; Valiela, 1995), although the study of the productivity–diversity relationship in marine environments has, until now, received little specific attention, particularly in low-productivity ecosystems. Nevertheless, in the large oligotrophic system of the central Pacific, Venrick (1982) observed that the number of phytoplankton species (139) in the deepest productive stratum was lower than that in the surface stratum (178 species), where productivity was higher. Therefore, the results obtained in this study represent strong experimental support for the hypothesis that, in marine environments, the relationships between productivity and diversity in the nano-/micro- phytoplankton guild (Valiela, 1995) and between biomass and diversity (Guo and Berry, 1998) follow a unimodal pattern, with the highest diversity corresponding to intermediate productivity values. Considering the data gathered in the two areas as a whole, the conclusion may be drawn that the existence of significant productivity–diversity relationships is limited to conditions in which average productivity values are lower than approximately 0:45 mgC m3 h1 (where a direct relationship is expected), or higher than approximately 1:00 mgC m3 h1 (where an inverse relationship is expected). In the range from 0.45 to 1:00 mgC m3 h1, the relationships between diversity and productivity are less predictable, both in terms of significance and in terms of slope (positive versus negative). This estimate, produced from a limited data set, can, however, be a useful point of reference for broader analyses of the form of the productivity–diversity relationship in marine environments. The fact that the taxonomic richness showed the same patterns of variation with primary productivity supports the generality of the results observed and prevents any bias due to the diversity indices used. Finally, one of the main causes of the controversies regarding the shape of the productivity–diversity relationship is the lack of knowledge about the causal mechanisms that may link these two ecosystem

Copyright # 2003 John Wiley & Sons, Ltd. Aquatic Conserv: Mar. Freshw. Ecosyst. 13: 489–506 (2003) 504 M. R. VADRUCCI ET AL. characteristics. Recently, sampling effect, complementarity and facilitation have been proposed as general mechanisms underlying the relationships between species diversity and productivity (Fridley, 2001). The relationships observed in the Adriatic–Ionian area do not seem to be due to the sampling effect (see Fridley (2001)). Indeed, in the northern area, significant relationships between the number of species and productivity were not observed. Moreover, in winter, when the strongest gradients of productivity and diversity were observed, the nano- and micro-phytoplankton guilds were dominated in the northern area by just two species: S. costatum and P. delicatissima. Furthermore, the relevance of the sampling effect is linked to the stochastic processes of immigration and extinction, which seem very low in the northern Adriatic system, characterized by a high taxonomic similarity among stations within cruises and high evenness. Similarly, the observed relationship does not seem to be due to a mechanism of facilitation. Facilitation would lead to predictable changes of taxonomic guild structure on the productivity and diversity gradients; such changes either were not observed at all, as in the northern area (where two species dominated at each site), or were not predictable, as in the southern area (where the average similarity within high- and low- diversity guilds was not different from the average similarity between low- and high-diversity guilds). Therefore, the patterns observed in the two areas of study seem to reflect the relevance of the niche complementarity concept as the community assembly rule, which assumes the existence of heterogeneity at the scale of a species response (Bell and Lechowicz, 1994) as the basis of positive relationships between diversity and productivity. However, heterogeneity cannot be sustained when nutrient enrichment makes the environment homogeneous for the individuals of the dominant species, leading to reduction of the evenness component and to inverse relationships, as observed here in the northern area. Variations in the numerical dynamics of the dominant species in response to nutrient enrichment have been proposed as the basis of unimodal relations between biodiversity and environmental quality (Jansen and Mulder, 1999), and are consistent with the expectations of the enrichment theory (Rosenzweig, 1971). In the case of the northern area of study, the temporal and spatial variations of the area affected by the flow of fresh water (Franco and Michelato, 1992) probably favour the dominance of the most competitive species without any taxonomic simplification. Indeed, the species diversity is affected much more by the evenness component (which is related to the numerical dynamics of population) than by the number of species (which is linked to processes of immigration and extinction). In the southern area, the low level of trophy could favour conditions of auto-limitation, which can open the guilds to new colonizers when resource density increases. Fonda Umani (1992) has already demonstrated strong spatial gradients in nano- and micro-phytoplankton guild diversity in the Gulf of Trieste (northern Adriatic), showing evident seasonal and inter-annual fluctuations and diversity drops, at times of reduced immigration through the advection from the more southerly areas of the basin (see Degobbis et al. (1995) for the case of 1987). Here, we refer specifically to the relationship between productivity and taxonomic diversity in nano- and micro-phytoplankton marine guilds, since the richness and diversity of the pico-phytoplankton size fraction, accounting for 45:7 12:4 to 59:9 3:6% of primary production, was not assessed. However, pico-phytoplankton biomass and productivity have been shown to be related to nano- and micro-phytoplankton biomass and productivity, both in the northern and in the southern areas (Basset et al., 2000; Vadrucci et al., 2001, unpublished results); thus, it seems likely that the current results could be generalized to the entire phytoplankton guild. In conclusion, the results obtained in the present study supported two relevant and related points. First, the greater importance attributed in marine environments to an inverse relationship between productivity and diversity in the phytoplankton guilds seems to be linked to a lack of studies of oligotrophic systems. Second, the non-linear relationship of species diversity with primary productivity and level of trophy has important implications for conservation of the coastal marine environment. Species diversity, which is considered a major descriptor of the phytoplankton quality element both in the EU Directives (e.g. Water Framework Directive, 2000) and in national law (e.g. D.M. 152/99 and D.M. 258/00 as regards Italy), does not fulfil the requirement for quality element descriptors, which is the existence of a linear co-variation with the disturbance pressure. Moreover, the conservation of phytoplankton species diversity in coastal waters

Copyright # 2003 John Wiley & Sons, Ltd. Aquatic Conserv: Mar. Freshw. Ecosyst. 13: 489–506 (2003) DIVERSITY–PRODUCTIVITY RELATIONSHIP IN PHYTOPLANKTON GUILDS 505 also seems to be weakly related to local disturbance pressures, at least in terms of nutrient loading, as in the northern Adriatic basin. It would appear from the evidence of this work that the global water circulation in the Adriatic basin is the important factor in the maintenance of the spatial and temporal heterogeneity, which seem to have a major role in co-existence relationships and species diversity in coastal marine ecosystems.

ACKNOWLEDGEMENTS

We thank Dr L. Milani for help in determining heterotrophic dinoﬂagellates and Dr A Semeraro for technical support in determining phytoplankton in the southern area. This research was supported by the Italian Ministry of University and Scientiﬁc and Technological Research (MURST) and the National Research Council (CNR) in the framework of the PRISMA II project and by ECC and Regione Puglia for INTERREG II project ‘Structure and processes in the water column’.

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