Spatial Distribution Of Phytoplankton Research Articles

Temporal and Spatial Distribution of Phytoplankton and Role of Environment Factors in the Shending River Backwater in the Danjiangkou Reservoir Area

The Danjiangkou Reservoir supplies drinking water to most residents in northern China. However, signs of eutrophication have been observed in the inlet tributaries of the reservoir, including the Shending River backwater. This research used data from the Sentinel-2 Multispectral instrument and findings from a 2021 aquatic ecological survey to analyze the spatial and temporal characteristics of phytoplankton distribution in the Shending River backwater region. The average chlorophyll a (Chl-a) concentrations by season, ranked from largest to smallest, are as follows: summer (63.96 μg/L) > autumn (41.26 μg/L) > spring (27.47 μg/L) > winter (16.21 μg/L); the upstream of the backwater area and the near-shore tributary bay had relatively higher Chl-a concentration. Bacillariophyceae (Cyclotella meneghiniana and Synedra sp.) and Cryptophyceae species (Chroomonas acuta) were dominant in spring, whereas Chlorophyceae (Scenedesmus sp. and Chlorella vulgaris) and Cyanophyceae (Dactylococcopsis acicularis, Microcystis aeruginosa and Oscillatoria tenuis) species were dominant in summer. The seasonal succession characteristics of the phytoplankton community were consistent with those of the Plankton Ecology Group model. The average phytoplankton cell density was 4.80 × 107 cells/L, and the Shannon–Wiener average diversity index was 1.95, indicating that the Shending River backwater area was moderately eutrophic. According to Pearson correlation analysis and Mantel test, the main factors causing temporal and spatial differences in phytoplankton production in the Shending River’s backwater were water level (WL), water temperature (WT), ammonia nitrogen (NH3-N) and total nitrogen (TN). In particular, WL was significantly positively correlated with Bacillariophyceae, Chlorophyceae and Cyanophyceae, whereas WT was significantly correlated with Cryptophyceae and Chlorophyceae. NH3-N and TN were significantly correlated with Cyanophyceae. Therefore, intensive nitrogen removal from the tailwater of sewage treatment plants may be considered a feasible measure to prevent cyanobacterial bloom in the Shending River backwater of the Danjiangkou Reservoir.

Use of multivariate analysis to identify phytoplankton bioindicators of stream water quality in the monomodal equatorial agroecological zone of Cameroon.

The aquatic ecosystem is compromised by many contaminants that may reduce ecosystem functions and severely affect human health. This study aimed at determining suitable phytoplankton bioindicators of water quality for biomonitoring of freshwater streams in the monomodal agroecological zone of Cameroon. Water physicochemical and hydrological parameters, together with phytoplankton abundance and diversity, were measured from June 2016 to May 2017 along the Benoe Stream. Principal component analysis and redundancy analysis were used to determine phytoplankton spatial and temporal distribution and identify indicator species. The Shannon-Wiener diversity and Pielou's evenness indices indicated a clean to mildly polluted stream with a diverse phytoplankton community consisting of 84 genera belonging to 51 families that was dominated by the Bacillariophyta (64%), followed by Chlorophyta (13%) and Cyanophyta (10%). The total dissolved solids, electrical conductivity, stream water velocity, and discharge were the most important stream characteristics affecting the abundance of the dominant phytoplankton genera. Seasonal variations in the stream characteristics as well as spatial community distribution along an urban-small-scale farming - large-scale farming gradient were unveiled and their influence on the phytoplankton relative abundances. Increased abundance of Synedra ulna was indicative of low TDS and EC, which was the contrary for Gyrosigma baltium dominance. High Pleurosira laevis abundance was associated with the urban zone while high Diatoma sp. and Oscillatoria sp. abundances were related to the large-scale farming zone of the stream. These phytoplankton species have good potential for use as bioindicators for stream water quality monitoring in the monomodal agroecological zone.

Spatio-temporal variation in phytoplankton community structure in backwaters of the Ketar River, central Ethiopia

This study assessed the spatio-temporal dynamics of the phytoplankton community in backwaters of the Ketar River, central Ethiopia, in relation to water quality and macrophyte coverage. Phytoplankton samples and physicochemical information were collected at six sites along the river over 1 year (December 2017 to November 2018). Phytoplankton was collected using a 15-μm mesh net. A total of 56 species belonging to three algal phyla were identified; the most diverse phylum was Bacillariophyta (35 species), followed by Chlorophyta (13 species) and Euglenophyta (eight species). Bacillariophyta had the highest abundance and contributed 80.08% of the total phytoplankton abundance. Site 6 in the downstream portion had the highest abundance and greatest diversity of phytoplankton species. The algal phyla present showed significant differences in species diversity and abundance both spatially and temporally. Redundancy analysis results revealed that the spatial distribution of phytoplankton in the river positively correlated with pH, electrical conductivity, dissolved oxygen and nitrate-nitrogen, while water temperature and total suspended solids correlated negatively. Some indicators of organic pollution suggest that the water quality of the river is progressively declining, meriting close monitoring.

EDNA metabarcoding revealed the seasonal and spatial variation of phytoplankton functional groups in the Chai river and their relationship with environmental factors

Environmental DNA (eDNA) metabarcoding permits a new measurement to monitor biodiversity in aquatic ecosystems. This study utilized eDNA metabarcoding to examine the seasonal and spatial distribution of phytoplankton and their relationship with environmental factors in the Chai River, Kunming, China, in the dry, and wet seasons. The process detected 108 genera of phytoplankton, which were members of 11 phyla, 41 orders, and 60 families. Distinct differences in seasonal and spatial distribution patterns of phytoplankton diversity, including community structure, α-diversity, and representative functional groups, were observed. In the dry season, Pseudanabaena, Microcystis, and Synechococcus were the predominant genera in Cyanophyta, and Chlorophyta, Bacillariophyta and Euglenophyta were predominant in the eukaryotic phytoplankton. While in the wet season, Cylindrospermopsis, Microcystis, and Planktothrix predominated in the Cyanophyta, and Bacillariophyta, Chlorophyta and Xanthophyta predominated in the eukaryotic phytoplankton. Significant differences were shown by a principal coordinate analysis and PERMANOVA test among the upper, middle, and lower reaches of the phytoplankton communities except for the cyanobacterial community structure between the upper and lower reaches at the wet season (p > 0.05). The representative functional groups of phytoplankton varied from A, D, E, LM, L0, N, S1, MP, P, TB, TC, U, W0, W1, Xph, Y, and Z in the dry season to A, B, D, E, F, J, MP, LM, S1, SN, TC, P, W0, W1, X2, and Y in the wet season. Significant differences in the water temperature (WT), pH, chemical oxygen demand, oxygen consumed, nitrate nitrogen (NO3-N), and chlorophyll a were exhibited between the dry and wet seasons (p < 0.05). In the dry season, WT, NO3-N, and pH had a substantial influence on the functional groups LM, N, and L0 of the cyanobacteria. The EC and total nitrogen (TN) had a substantial influence on the functional groups A and Y of the eukaryotic phytoplankton. In the wet season, the electrical conductivity (EC), TN, and dissolvable total phosphorus (DTP) primarily affected the functional groups LM and S1, while EC, DPI, and soluble reactive phosphorus had a substantial influence on the functional groups A and Y. This study provides insights on the conservation of phytoplankton diversity and healthy management of the Chai River.

Phytoplankton community structure in the Western Subarctic Gyre of the Pacific Ocean during summer determined by a combined approach of HPLC-pigment CHEMTAX and metabarcoding sequencing

The Western Subarctic Gyre (WSG) is a cyclonic upwelling gyre in the northwest subarctic Pacific, which is a region with a high concentration of nutrients but low chlorophyll. We investigated the community structure and spatial distribution of phytoplankton in this area by using HPLC-pigment CHEMTAX (a chemotaxonomy program) and metabarcoding sequencing during the summer of 2021. The phytoplankton community showed significant differences between the two methods. The CHEMTAX analyses identified eight major marine phytoplankton assemblages. Cryptophytes were the major contributors (24.96%) to the total Chl a, followed by pelagophytes, prymnesiophytes, diatoms, and chlorophytes. The eukaryotic phytoplankton OTUs obtained by metabarcoding were categorized into 149 species in 96 genera of 6 major groups (diatoms, prymnesiophytes, pelagophytes, chlorophytes, cryptophytes, and dinoflagellates). Dinoflagellates were the most abundant group, accounting for 44.74% of the total OTUs obtained, followed by cryptophytes and pelagophytes. Sixteen out of the 97 identified species were annotated as harmful algal species, and Heterocapsa rotundata, Karlodinium veneficum, and Aureococcus anophagefferens were assigned to the abundant group (i.e., at least 0.1% of the total reads). Nutrients were more important in shaping the phytoplankton community than temperature and salinity. The 24 stations were divided into southern and northern regions along 44°N according to the k-means method, with the former being dominated by high Chl a and low nutrients. Although different phytoplankton assemblages analyzed by the two methods showed various relationships with environmental factors, a common feature was that the dinoflagellate proportion showed a significantly negative correlation with low nutrients and a positive correlation with Chl a.

Phytoplankton diversity and chemotaxonomy in contrasting North Pacific ecosystems.

Phytoplankton is the base of majority of ocean ecosystems. It is responsible for half of the global primary production, and different phytoplankton taxa have a unique role in global biogeochemical cycles. In addition, phytoplankton abundance and diversity are highly susceptible to climate induced changes, hence monitoring of phytoplankton and its diversity is important and necessary. Water samples for phytoplankton and photosynthetic pigment analyses were collected in boreal winter 2017, along transect in the North Pacific Subtropical Gyre (NPSG) and the California Current System (CCS). Phytoplankton community was analyzed using light and scanning electron microscopy and photosynthetic pigments by high-performance liquid chromatography. To describe distinct ecosystems, monthly average satellite data of MODIS Aqua Sea Surface temperature and Chlorophyll a concentration, as well as Apparent Visible Wavelength were used. A total of 207 taxa have been determined, mostly comprised of coccolithophores (35.5%), diatoms (25.2%) and dinoflagellates (19.5%) while cryptophytes, phytoflagellates and silicoflagellates were included in the group "others" (19.8%). Phytoplankton spatial distribution was distinct, indicating variable planktonic dispersal rates and specific adaptation to ecosystems. Dinoflagellates, and nano-scale coccolithophores dominated NPSG, while micro-scale diatoms, and cryptophytes prevailed in CCS. A clear split between CCS and NPSG is evident in dendogram visualising LINKTREE constrained binary divisive clustering analysis done on phytoplankton counts and pigment concentrations. Of all pigments determined, alloxanthin, zeaxanthin, divinyl chlorophyll b and lutein have highest correlation to phytoplankton counts. Combining chemotaxonomy and microscopy is an optimal method to determine phytoplankton diversity on a large-scale transect. Distinct communities between the two contrasting ecosystems of North Pacific reveal phytoplankton groups specific adaptations to trophic state, and support the hypothesis of shift from micro- to nano-scale taxa due to sea surface temperatures rising, favoring stratification and oligotrophic conditions.

Spatial distribution of phytoplankton in the Serezha River (Nizhny Novgorod Region)

The investigation presents the results of studies of plankton in the area of the middle course of the riverSerezha in 2019. The floristic diversity of phytoplankton was characterized, its abundance and biomass were estimated, and the change in the morpho-functional groups of phytoplankton along the river was shown. The influence of some physical factors on the development of planktonic algae is considered. The water quality of this section of the watercourse was assessed by phytoplankton biomass, as well as using the community index and the Pantle-Bucksaprobity index.

МОДЕЛИРОВАНИЕ ЦВЕТЕНИЯ ВОДЫ В КУЙБЫШЕВСКОМ ВОДОХРАНИЛИЩЕ В ГОДЫ С РАЗЛИЧНЫМ РЕЖИМОМ РЕГУЛИРОВАНИЯ СТОКА

The article studies the influence that the dynamics of currents have on algal blooms in the Kuibyshev Reservoir in the conditions of an unsteady flow regime. One of the ways to improve the ecological condition of the reservoir is to reduce cyanobacteria blooms by increasing the flow rate during the maximum warming of the water. The hydrodynamics of the aquatic environment is considered as a regulatory factor that reduces the negative effects of eutrophication and improves the quality of water in the reservoir. The author performed full-scale hydroecological observations in the summer periods of 2016 and 2017 and made model calculations of the dynamics of currents and spatial distribution of phytoplankton in the water area of the Kuibyshev Reservoir. As a result, the dependence of the chlorophyll a index (Chl a) on the flow regulation regime was established. The proposed model is based on the equations of long-wave hydrodynamics, known as the shallow-water equations, the equations of convective transport and development of the components of the ecosystem, which is implemented in the author’s software environment VOLNA. The model is constructed for the near-dam water area on a regular rectangular grid with a step of 200 m. The model was verified on the basis of data from field observations, and the quality of the calculations performed was evaluated. It has been found that the phytoplankton biomass index (Chl a) is related to the water flow velocity non-linearly and varies according to a power law. The conducted studies give reason to believe that the intensity of cyanobacteria blooms largely depends not on the water content of the year, but on the intra-annual redistribution of runoff.

Spatial distribution of phytoplankton in Gamak Bay in spring, with emphasis on small phytoplankton

Spatial distribution of phytoplankton in Gamak Bay in spring, with emphasis on small phytoplankton

Spatial Distribution of Phytoplankton in the Coastal Waters off Russkii Island (Peter the Great Bay, Sea of Japan)

Spatial Distribution of Phytoplankton in the Coastal Waters off Russkii Island (Peter the Great Bay, Sea of Japan)

Atmospheric saccharide composition and its possible linkage with marine phytoplankton from North Pacific to the Antarctic regions

Saccharide compounds can distinguish the influence of both biogenic emissions and anthropogenic sources. In this study, the spatial distribution of 10 saccharide compounds was observed to determine the major factor for the production of organic aerosols in the pristine marine regions from the North Pacific Ocean to the Antarctic Ocean. The pristine marine atmospheric PM2.5 (Particle matter with an aerodynamic diameter equal to or less than nominal 2.5 μm) samples were collected using a high-volume air sampler connected to a wind sector controller installed in the Korean Ice-breaking Research Vessel (IBRV) during the cruise through the Pacific Ocean: from the Yellow Sea, Korea on October 31, 2018 to the Antarctic Ocean on December 14, 2018.In the pristine marine region, the total saccharides concentrations varied greatly from 0.16 to 16.57 ng/m3 (mean: 3.02 ± 4.76 ng/m3). The compositions of 10 saccharide compounds in each PM2.5 sample changed when the marine geographic characteristics changed. The contribution of levoglucosan in the sample collected near land was higher than the sample collected in the open ocean. In addition, saccharides concentrations had a strong positive correlation with OC (Organic carbon), indicating that the increase of saccharides concentrations strongly contributes to the increase in OC concentration in the pristine marine region. The highest concentration of saccharides was observed near the New Zealand coast, which also showed highest air mass exposure to marine biology. We also found that the spatial distribution of saccharide composition was correlated with the spatial distribution of phytoplankton. From these observations, we concluded that 1) marine phytoplankton can be a significant source of organic aerosol production and 2) the type of phytoplankton in a region affects the change of saccharides composition in PM2.5.

Cross diffusion induced spatiotemporal pattern in diffusive nutrient–plankton model with nutrient recycling

This paper presents a mathematical model of spatiotemporal interaction between the nutrient and phytoplankton. The interaction among the constituents in nutrient–phytoplankton system has been considered with Holling type-III functional response and nutrient recycling. We have also considered the effect of cross and self-diffusion in the system. The stability analysis of non-spatial and spatial systems have been studied. We have used simulation techniques to generate patterns for cross and self-diffusive systems. We have performed the numerical simulations and observed the effect of time evolution, cross-diffusion and rate of toxin release by phytoplankton on the density distribution of species. This phenomenon is elaborately discussed in this manuscript by introducing weakly nonlinear analysis. We also introduce amplitude equations which describe the structural interpretation and the stability of Turing pattern for nutrient–phytoplankton system. Amplitude equation is derived by using multiple-scale analysis. Cross-diffusion plays an important role in Turing instability and the formation of spot, stripe and spot–stripe like patterns. It suggests the positive environmental outcomes from nutrient recycling and spatial distribution of phytoplankton in the real world situation.

Таксономический состав и численность планктонных водорослей в водах Западной Антарктики (февраль–март 2020 г.)

Diversity, quantitative development and distribution of phytoplankton species were investigated. The study area included southeastern part of the Ross Sea (near Roosevelt Island) (station 3), transect 1 along the 156°W (Ross Sea at Cape Colbeck), near Russkaya station (transect 2) along the 138°W and the Bransfield Strait (transect 3) in February-March 2020, based on the data of 65th Russian Antarctic Expedition. 49 algae taxa from 7 divisions with a predominance of diatoms were identified in the phytoplankton. The spatial distribution of phytoplankton was characterized by heterogeneity which is associated with currents in the study areas, ice conditions, climatic and thermohaline factors. Development of diatoms is typical to the entire studied area. The dominant species (more than 10% of the algae population) were representatives of the genera Fragilariopsis, Chaetoceros, Actinocyclus, Corethron and Phaeocystis. The highest phytoplankton abundance (up to 264×103 cells/l) were obtained for transect 2 stations.

Spatial distribution of phytoplankton in Lasolo Bay of Southeast Sulawesi Province, Indonesia

This study aimed to analyze the distribution of phytoplankton abundance and its relationship with water quality in Lasolo Bay waters. The study was conducted during the West Season 2020. The sample consisted of 9 stations located near the mouth of the Lasolo River (station A), coastal waters (Station B) and the center part of Lasolo Bay (Station C). Phytoplankton sampling was using plankton nets with 25 µm meshsize. Identification of phytoplankton used microscope and the abundance calculation by using Sedgwick Rafter Counting Cell. The results showed that there are 23 phytoplankton genera from 5 classes found, namely 12 genera of Bacillariophycea Class, 5 genera of Dinophyceae Class, 3 genera of Chlorophyceae Class, 2 genera of Cyanophyceae class and 1 genera of Coscinodiscophyceae class. By abundance, phytoplankton compositions of the class Bacillariophyceae predominate with a percentage of 57%. The type of phytoplankton that has the highest abundance is Nitzschia sp. of 2,407 cells/l and the lowest abundance of Amphidium sp. of 1,368 cells/l. Phytoplankton abundance at Station A is 41,093 cells/l, station B is 14,234 cells/l and station C is 14,735 cells/l. The distribution of phytoplankton abundance is also influenced by physical and chemical factors such as turbidity, TSS, Nitrate and Phosphate.

Water quality characteristics and spatial distribution of phytoplankton during dry and rainy seasons in Bunam Lake and Cheonsu Bay, Korea

Water quality characteristics and spatial distribution of phytoplankton during dry and rainy seasons in Bunam Lake and Cheonsu Bay, Korea

Community structure and spatial distribution of phytoplankton in relation to hydrography in the Laptev Sea and the East Siberian Sea (autumn 2008)

The Laptev Sea and the East Siberian Sea are remote areas of the Arctic region where detailed data on phytoplankton composition and spatial distribution remain limited. In the context of the ongoing environmental changes (increasing warming and ice melting) and prospective exploration activities (oil and gas production) on the Arctic shelves, understanding of the seasonal and interannual phytoplankton community dynamics is of critical importance. Our study provides new specifying data on species composition of phytoplankton over the vast area of the Laptev Sea shelf and the East Siberian Sea shelf. We found that the outer shelf of the Laptev and East Siberian seas was characterized by typical late spring diatom species (Chaetoceros furcellatus, Chaetoceros diadema, Chaetoceros debilis, Chaetoceros constrictus). On the inner shelf of the Laptev Sea, which is strongly affected by the Lena River water masses, the phytoplankton were characterized by the transition from the summer to an autumn stage of development. Local algal assemblages were composed by mixo- and heterotrophic dinoflagellates (Dinophysis and Protoperidinium genera) together with marine and brackish water-marine diatoms (Thalassiosira hyperborea, Thalassiosira baltica, Thalassiosira gravida, Thalassiosira nordenskioeldii) accompanied by sporadically occurring freshwater riverine planktonic diatom species (Aulacoseira granulata, Aulacoseira italica, Asterionella formosa). These variations in species composition over the Laptev Sea shelf were attributed to differences in the hydrography, marine chemical conditions, and the sea-ice regime.

Phytoplankton distribution characteristics and its relationship with bacterioplankton in Dianchi Lake.

Phytoplankton and bacterioplankton perform important ecological functions in lake ecosystem. In this paper, the abundance and composition of phytoplankton and bacterioplankton at 13 sites of Dianchi lake during the wet and dry seasons were monitored, and the relationship between phytoplankton and bacterioplankton in this plateau lake was studied. Phytoplankton community structure analysis was carried out by ocular method, and bacterioplankton was investigated by high-throughput 16S rRNA gene Illumina sequencing. The relationship between phytoplankton and bacterioplankton was observed using redundancy analysis. The results showed that 87 species of phytoplankton belonging to 5 phyla and 29 genera were identified in Dianchi lake. Phytoplankton diversity and richness were higher in the wet season than those in the dry season. In the wet season, Cyanophyta was the dominant phylum whose density was 2.01 × 108 cells/L, accounting for more than 90% of the total algae, then followed by Chlorophyta, Bacillariophyta, Chrysophyta, and Cryptophyta. The spatial distribution of phytoplankton in the wet season and dry seasons showed significant differences. In the dry season, the north-central part of Dianchi lake was dominated by Limnothrix redekei and Microcystis minutissima of Cyanophyta, while Pseudanabaena moniliformis and Coelosphaerium nagelianum of Cyanophyta mainly was dominated in the south of Dianchi lake. In the wet season, Microcystis minutissima of Cyanophyta was the dominant species all the area, while Limnothrix redekei of Cyanophyta was second dominant. Proteobacteria and Bacteroidetes were the dominant phyla among bacterioplankton. The community structure of bacterioplankton was influenced by Cyanophyta and Bacillariophyta. Cyanophyta had a major influence on Pseudomonas, Acinetobacter of Proteobacteria, and Flavobacterium of Bacteroidetes. Bacillariophyta showed a strong correlation with Gemmobacter, Stenotrophomonas, and Aeromonas of Proteobacteria. Cyanophyta and Bacillariophyta produced the most significant impact on predicted functional genes of bacterioplankton, and the predicted functional genes of the samples were different in different seasons. Cell densities of Cyanophyta were positively related to metabolism-predicted functional genes of bacterioplankton. Bacillariophyta and Cryptophyta had an impact on most of the cellular processes and signaling predicted functional genes. Bacterioplankton-predicted functional gene information storage and processing were significantly affected by cell densities of Chlorophyta. Therefore, the analysis of the phytoplankton community and the bacterioplankton-predicted functional gene in Dianchi lake exerts a great significance in revealing the ecosystem function of plateau lakes and harmful algal bloom control.

Responses of morphology-based phytoplankton functional groups to spatial variation in two tropical reservoirs with long water-residence time

ABSTRACT The responses of phytoplankton to the spatial variation of 2 tropical reservoirs with long water-residence times was studied by means of morphology-based functional groups (MBFGs). The groups were compared among the pelagic, tributary, and downstream zones to determine the spatial distribution and its main drivers. Based on the zonation concept, we hypothesized that phytoplankton tolerant to nutrient depletion would be more important in the pelagic zones, and phytoplankton resistant to light limitation and turbulence would be more important in the lotic zones. We also expected nutrients and/or light availability (bottom-up control) to be the main drivers of MBFGs spatiality in tropical systems. Our results indicated the importance of this control for phytoplankton spatial distribution. The phytoplankton biovolume was more homogeneous in Serra da Mesa Reservoir (SER), while in Três Marias Reservoir (TRM) biovolume was higher in the pelagic zone. MBFG III dominated in the pelagic zone of TRM while MBFG V dominated in its tributary. The higher biovolume of MBFG III was associated with low dissolved phosphate and high water temperature and pH in SER, and lower dissolved inorganic nitrogen and high pH in the pelagic zone of TRM, as shown by RDA analyses. The dominance of MBFG V in the tributary is probably a response to higher turbidity and dissolved organic carbon availability. We conclude that within zones, resources (nutrients and light availability), temperature, and pH were the main drivers of the phytoplankton in these reservoirs. Furthermore, the MBFG scheme can be used to monitor phytoplankton spatial distribution.

High predictability of direct competition between marine diatoms under different temperatures and nutrient states.

The distribution of marine phytoplankton will shift alongside changes in marine environments, leading to altered species frequencies and community composition. An understanding of the response of mixed populations to abiotic changes is required to adequately predict how environmental change may affect the future composition of phytoplankton communities. This study investigated the growth and competitive ability of two marine diatoms, Phaeodactylum tricornutum and Thalassiosira pseudonana, along a temperature gradient (9–35°C) spanning the thermal niches of both species under both high‐nitrogen nutrient‐replete and low‐nitrogen nutrient‐limited conditions. Across this temperature gradient, the competitive outcome under both nutrient conditions at any assay temperature, and the critical temperature at which competitive advantage shifted from one species to the other, was well predicted by the temperature dependencies of the growth rates of the two species measured in monocultures. The temperature at which the competitive advantage switched from P. tricornutum to T. pseudonana increased from 18.8°C under replete conditions to 25.3°C under nutrient‐limited conditions. Thus, P. tricornutum was a better competitor over a wider temperature range in a low N environment. Being able to determine the competitive outcomes from physiological responses of single species to environmental changes has the potential to significantly improve the predictive power of phytoplankton spatial distribution and community composition models.

Phytoplankton of Inner Ambon bay during east monsoon

The Inner Ambon Bay has a potency for fisheries resources, especially the anchovy of the genus Stolephorus. This species is depended on the abundance of plankton organisms as their food sources. The research was carried out on east monsoon and was aimed to analyze the species composition, abundance, diversity, similarity and spatial distribution of phytoplankton in Inner Ambon Bay. Sampling was done by towing the Kitahara plankton net vertically from the depth of 5 meters to surface water at 10 stations. Sixty-four species of phytoplankton was found during the sampling periods. The phytoplankton abundance varied between 5.4 × 104cells/m3 and 7.7 × 105cells/m3. The average values of species diversity index (H’), evenness index (J’) and dominance index (D) were 1.31, 0.37 and 0.63, respectively. Similarity between stations ranged from 53.4% to 85.5% and can be grouped into three clusters. Spatial distribution showed that station 5, station 6 and station 8 were more abundant compare to other stations.