Dynamics Of Phytoplankton Community Structure Research Articles

Spatio-temporal dynamics of phytoplankton community structure in the coastal waters of the Southern Beibu Gulf.

This study was conducted during October 2021 (autumn) and April 2022 (spring) to explore the phytoplankton community structure, their distribution characteristics, and the influence of environmental factors in the coastal waters of the Southern Beibu Gulf. The 15 sampling sites were grouped based on the difference in offshore distance to analyze the temporal and spatial differences in community structure and environmental driving in the investigated sea area of the coastal waters of the Southern Beibu Gulf. Permutational multivariate analysis of variance was conducted on the sample data in time and space, revealing that there is no significant difference in space (p > 0.05), but there is significant difference in time (p < 0.05). Notably, water pressure, pH, chemical oxygen demand, nitrite, and labile phosphate were higher in autumn, while total ammonia nitrogen, dissolved oxygen, and suspended solids were significantly higher in spring. Additionally, the study identified 87 phytoplankton species belonging to 6 phyla, dominating by Bacillariophyta, followed by Dinophyta and Cyanophyta. The phytoplankton density, Shannon Weiner's diversity index (H'), Pielou's evenness index (J), and Margalef's richness index (D) ranged from 84.88 to 4675.33 cells L-1, 0.56 to 2.58, 0.26 to 0.89, and 1.21 to 3.64, respectively. Permutational multivariate analysis of variance showed non-significant spatial differences in phytoplankton composition (p > 0.05) but seasonal differences (p < 0.05). Furthermore, canonical correspondence analysis (CCA) identified pH, dissolved oxygen, suspended solids, chemical oxygen demand, nitrite, and labile phosphate as key environmental factors influencing the phytoplankton community structure (p < 0.05). In this study, the dynamic changes of phytoplankton community structure and environmental factors in the southern coastal waters of Beibu Gulf were analyzed in detail from two aspects of time and space. The key environmental factors to protect the ecological environment in the southern coastal area of Beibu Gulf were found out. It provides a reference method and theoretical basis for the management and protection of Beibu Gulf and other tropical marine environment.

Spatio-temporal dynamics of phytoplankton in a diversion reservoir and the major influencing factors: taxonomic versus functional groups classification.

Identifying factors affecting phytoplankton dynamics is crucial to the management of aquatic ecosystems. A lot of scholars have conducted intensive studies on phytoplankton in lake or reservoirs, but not many studies have been conducted on diversion reservoirs. To explore the seasonal and spatial variation of phytoplankton communities and their relationship with environmental factors in the context of water diversion, a case study was carried out at XiKeng (XK) reservoir in South China. In this study, month-by-month water samples and phytoplankton were collected from this reservoir from December, 2021, to July, 2022. The results showed that the phytoplankton community was characterized by significant spatial and temporal variations. There were significant differences in phytoplankton abundance and structure in the reservoirs in terms of time. The abundance of phytoplankton cells and the proportion of Cyanobacteria in the reservoir showed a trend of increasing from autumn to spring and then decreasing from spring to summer, while the functional group evolved from S1 in autumn to SN in spring and summer. The abundance of phytoplankton was influenced by the dynamic water division and the characteristics of the reservoir itself, resulting in a spatial distribution characteristic of AIII > AII > AI. Water temperature (WT) and nutrients were the key factors driving the changes in phytoplankton abundance and community structure in the reservoir. These findings will deepen our understanding of the spatial and temporal dynamics of phytoplankton community structure in diversion reservoirs and provide a basis for freshwater water ecological management strategies.

Assessing spatio-temporal dynamics of phytoplankton assemblage and ecohydrological interaction in a community managed reservoir using GIS for sustainable fisheries management

The present study assessed the spatio-temporal dynamics of phytoplankton community structure and diversity using GIS platform, and their ecohydrological interactionsof a tropical reservoir located in Eastern India. Altogether, 74 species of phytoplankton belonging to 54 genera under seven taxonomic algal groups were recorded whose average annual abundance was 74.11 × 104 ± 17.73 × 104 cells l−1. Among seven algal groups, Chlorophyta, Cyanophyta, Bacillariophyta and Euglenophyta were remarkably influencing the total phytoplankton population contributing 97% of the total phytoplankton population in the reservoir. Cyanophyta absolutely dominated in the total phytoplankton compositions, and contributed a major share of 54% at the annual average level, however the species richness was maximum under the group Chlorophyta (35 genera). In total, thirteen phytoplankton taxa emerged as dominant (γ = < 0.02) across seasons. Among them, Phormidium sp. solely contributed (16.16%) to the total phytoplankton population, marked as dominant one in the reservoir. The diversity indices indicated the greater phytoplankton diversity in the lotic zone as compared to the transitional and lacustrine zone, showing significant variations (p<0.05) across seasons. PERMANOVA analysis exhibited a significant temporal variations of phytoplankton abundance (F=1.15, p=0.02) as well asenvironmental variables (F=1.82, p<0.05), but no significant spatial variations were recorded. The Principal Component analysis (PCA) revealed water temperature, transparency, total hardness, pH, specific conductivity, total alkalinity and nutrients parameters viz., phosphate, nitrate and silicate were the most important abiotic factors having the significant influence on the phytoplankton community compositions. Canonical Correspondence Analysis (CCA) depicted the environmental factors such as temperature, total alkalinity, total hardness, transparency, pH, and nutrients (NO3-N, PO4-P and SIO4-Si) were the determinants for the distribution of overall phytoplankton population especially the dominant phytoplankton species of the reservoir. The findings provide a better understanding of the influence of ecohydrology on phytoplankton community of a community managed reservoir and also discuss management and researchable issues considering the feeding guild of reservoir fishes and phytoplankton assemblage for ecosystem based conservation and management.

Phytoplankton Community Structure Dynamics in Relation to Water Environmental Factors in Zhalong Wetland.

Phytoplankton, as the primary producer of the wetland water ecosystem's food chain, are very sensitive to environmental changes. In order to explore the significance of phytoplankton in protecting ecosystem integrity, the wetland ecosystem in Zhalong wetland, one of the most important international wetlands, was selected as the research area. For the study, 81 sampling sites were set up in the whole wetland, and phytoplankton samples and water quality environmental factors were measured in spring, summer, and autumn of 2019. The phytoplankton community structure and water environmental factors were evaluated by canonical correspondence analysis (CCA). The main research findings are as follows: a total of 292 species and variants of phytoplankton belonging to 8 phyla and 110 genera were identified within Zhalong wetland in spring, summer, and autumn 2019. The total phytoplankton abundance and biomass in summer were higher than in spring and autumn, and Cyclotella meneghiniana was the most dominant species in three seasons and three areas. The results of random forest are generally consistent with the results of CCA in spring, when the main environmental factors affecting phytoplankton were NTU and WT; the result in summer and autumn agreed with those of CCA, which awaits further study. In addition, the phytoplankton is mainly affected by WT, depth, and DO in the lake area, TP, DO, and NTU in the river area, and WT in the wetland area.

Nutrient limitations on primary productivity and phosphorus removal by biological carbon pumps in dammed karst rivers: Implications for eutrophication control

Biological carbon pumps (BCPs) convert dissolved inorganic carbon (DIC) into autochthonous organic carbon (AOC), which is the key to form long-term stable carbonate weathering-related carbon sink. The DIC fertilization may increase the strength of BCP. As a phase of BCP, eutrophication is one of the major problems in surface water environments which shows poor water quality with harmful cyanobacteria blooms. It is generally believed that the controlling elements of eutrophication are nitrogen (N) and phosphorus (P), while the controlling elements of BCP also includes carbon (C). Meanwhile P removal by BCPs through the coprecipitation of P with calcite and Fe(III) oxyhydroxide colloids decreases its content in water bodies and prevent water from cyanobacteria eutrophication. In the present study, we examine the seasonal variations of general physiochemical parameters of the surface water, DIC, total N and total P concentrations, chlorophyll concentrations in three karst river-reservoir systems (PZR, PDR and HFR) in Guizhou Province, Southwest China. The phytoplankton community structure dynamics and the settling flux of the total P and P fractions in the settling particulate matter in PZR and HFR were also examined. It was found that: (1) the nutrient limitations of BCPs shifted from C-limitation to N- or P-limitation after the rivers were dammed; (2) P removal by BCPs reduced the total P concentration and increased the stoichiometric N:P ratio in surface waters; (3) P removal by BCPs alleviated the development of eutrophication by decreasing the relative abundance of Cyanobacteria. Our results demonstrate that the damming of a river may shift the nutrient limitation patterns of dammed karst rivers and the P removal by BCP may retard the development of water body into Cyanophyta-type eutrophication. This may have important implications for eutrophication control (i.e., strengthening BCP effect via DIC fertilization) in HCO3-Ca type surface water, especially in karst areas, which cover about 15% of the world land surface.

Understanding optical absorption associated with phytoplanktonic groups in the marginal seas

Marine phytoplankton absorption plays an important role in oceanic biological productivity and ecological environmental dynamics. Understanding the optical absorption variability associated with phytoplanktonic groups still remains a challenge. In this study, samples (n = 206) were collected for the marginal seas of the northwest Pacific Ocean from six cruise surveys that covered different seasons. Using in situ parameters, including phytoplankton absorption coefficients and concentrations of the phytoplanktonic groups derived from phytoplankton pigments collected with high-performance liquid chromatography (HPLC), we developed a Gaussian model to characterize the specific absorption spectra of eight phytoplanktonic groups, including diatoms, chlorophytes, cryptophytes, cyanobacteria, prymnesiophytes, prasinophytes, dinoflagellates, and chrysophytes, without the package effect. The model was established by accurately identifying for the numbers and locations of the Gaussian peaks and their corresponding half-wave widths. The proposed model produced promising results, and a leave-one-out cross validation generated R2 values exceeding 0.7 for the whole visible light range and above 0.85 (correspondingly MAPE <40%) for the simulated wave bands, excluding the range of 550–650 nm. Meanwhile, a comparison with several spectra observed in the lab showed a high degree of similarity, indicative of the superior performance of our model. Applying the documented specific absorption spectra to the investigated water bodies (whether water surface or profiles) enabled us to quantify the absorption coefficients from different phytoplanktonic groups and characterize their relative contributions to the total. The findings of this study support our understanding of the dynamics of phytoplankton community structure with optical data.

The importance of nonrandom and random trait patterns in phytoplankton communities: a case study from Lake Müggelsee, Germany

A fundamental challenge in ecology is to identify the processes which explain how species come to occupy diverse communities. There is uncertainty about whether community composition arises through deterministic processes, whereby trait differences between species make them more or less adapted to certain environmental conditions. We tested the capacity for deterministic processes to explain the long-term dynamics of phytoplankton community structure in Lake Muggelsee—a shallow and eutrophic lake in Berlin, Germany using a trait-based approach. We developed a null model representing random processes alone by generating a time series of random trait distributions derived from the observed long-term data. We determined the extent to which deterministic processes lead to nonrandom patterns in phytoplankton communities by comparing the resulting null-trait distributions with the observed trait distributions in the long-term data. We found that phytoplankton communities fell along a gradient from random to nonrandom trait distributions, suggesting that deterministic processes alone do not fully describe the community structure. Nonrandom patterns were observed in communities with high species richness and during late spring as well as early winter. But neither species richness nor seasonality explained nonrandom patterns consistently for different metrics and traits given the high relevance of random trait distribution patterns. Thus, deterministic and stochastic processes may be needed to fully explain the structure of phytoplankton communities under changing environmental conditions.

The Dynamic of Phytoplankton Community Structure in Face of Warming Climate in A Tropical Man-Made Lake

&lt;p&gt;In freshwater ecosystems, water temperature plays as an environmental factor that regulates its structure and function. A research on the impacts of changes in temperature to the dynamics of the Phytoplankton community structure has been done. Data from nineteen-year period (1995 to 2013) were collected from Cirata Reservoir as an example of artificial tropical lake in Indonesia. The research aimed to determine the changes of water temperature as the impact of climate warming on the dynamics of phytoplankton community structure. Different measures such as species richness, diversity index, and abundance were measured in order to understand the changes of phytoplankton community structure. Trend analysis, linear regression, and correlation were applied to achieve our objective. The study revealed that changes in water temperature have affected the species richness, but not the diversity index and abundance of the phytoplankton. Bacilariophyceae and Cyanophyceae were found as two predominant phytoplankton classes in the lake with percentage of 48,45 and 41,43 respectively, assuming their capacity to adapt the new environment. This study suggests that climate warming implies changes of the freshwater ecosystems.&lt;/p&gt;

Dynamics of phytoplankton community structure in the South China Sea in response to the East Asian aerosol input

Abstract. Recent studies have demonstrated atmospheric deposition as an important source of bioreactive compounds to the ocean. The South China Sea (SCS), where aerosol loading is among the highest in the world, however, is poorly studied, particularly on the in situ response of phytoplankton community structures to atmospheric deposition. By conducting a series of microcosm bioassays at different hydrographical locations and simulating different aerosol event scales, we observed both positive and negative responses to the input of East Asian (EA) aerosol with high nitrogen (N) and trace metal contents, in terms of biomass, composition and physiological characteristics of phytoplankton communities. High levels of aerosol loading relieved phytoplankton nitrogen and trace metal limitations in SCS, and thus increased total phytoplankton biomass, enhanced their physiological indicators (e.g. photosynthetic efficiency) and shifted phytoplankton assemblages from being dominated by picoplankton to microphytoplanton, especially diatoms. However, under low levels of aerosol loading, the composition shift and biomass accumulation were not apparent, suggesting that the stimulation effects might be counterbalanced by enhanced grazing mortality indicated by increased abundance of protist grazers. Trace metal toxicity of the aerosols might also be the reason for the reduction of picocyanobacteria when amended with high EA aerosols. The magnitude and duration of the deposition event, as well as the hydrographical and trophic conditions of receiving waters are also important factors when predicting the influence of an aerosol deposition event. Our results demonstrated different responses of phytoplankton and microbial food web dynamics to different scales of atmospheric input events in SCS and highlighted the need for achieving an accurate comprehension of atmospheric nutrient on the biogeochemical cycles of the oceans.

Annual dynamics of phytoplankton abundance and community structure (2010) in Lake Caizi, Anhui Province

2010年对菜子湖浮游植物群落结构进行了调查和分析,结果显示:(1)共鉴定浮游植物8门110属285种,不同月份浮游植物的种类组成存在极显著差异,3月份种类数最多,173种,1月份最少,105种.优势度分析显示:蓝藻存在全年高峰;硅藻存在1、5、9、11月的高峰;黄藻存在1、3、5月的高峰;绿藻存在11月的高峰,隐藻存在5月份的高峰;金藻存在1月份的高峰.不同月份浮游植物的细胞密度亦存在极显著差异,7月份最高,为(66.13±8.58)×10⁵ cells/L,1月份最低,为(12.78±0.61)×10⁵ cells/L,夏、秋季较高,冬、春季较低;不同月份浮游植物的生物量差异极显著,9月份最高,为2.80±0.17 mg/L,5月份最低,为0.72±0.03 mg/L.(2)Margalef丰度指数为1.51~3、Shannon-Weaver多样性指数为1.41~3.01、Pielou均匀度指数为0.39~0.66,各指数表现为冬、春季节大于夏、秋季节,3月份最高,7月份最低.(3)聚类分析的结果显示,月份不同影响因素不同,菜子湖水域浮游植物按群落结构特征的分组不同.(4)2007年相比,2010年浮游植物物种数有明显下降,由340种下降到285种,细胞密度明显上升,由(5.91±0.90)×10⁵ cells/L上升到(33.81±10.10)×10⁵ cells/L,群落结构变化较大,贫营养型和固着型藻类都有所减少,富营养型藻类、丝状藻类和浮游性藻类增多.;The annual dynamics of phytoplankton community structure in Lake Caizi has been investigated in 2010. The results indicated that:(1) A total of 285 phytoplankton species from 110 genera of 8 phylum were identified. Phytoplankton species composition in different months showed significant difference. The maximal number of phytoplankton species (173) occurred in March while the minimum (105) in January. The dominant class of phytoplankton changed seasonally. Cyanophyta peaked all the year round; diatoms had an apparent dominance in January, May, September and November; Xanthophyta also played an important role in January, March and May; Chlorophyta dominated in November, Cryptophyta dominated in May while Chrysophyta dominated in January. The cell density and biomass of phytoplankton were higher in summer and autumn than that in winter and spring. The cell density of phytoplankton between different months had significant difference. The maximal density, with the value (66.13 ± 8.58)×10⁵ cells/L occurred in July while the minimal value of (12.78 ± 0.61)×10⁵ cells/L appeared in January. Whereas, the maximal biomass of phytoplankton(2.80 ± 0.17 mg/L) occurred in September and the minimal(0.72 ± 0.03 mg/L) appeared in May, and the biomass in different months was also significant different. (2) Temporal variations of three indices (including Margalef index, Shannon-Wiener index and Pielou evenness index) were obvious. All the indices were higher in winter and spring than those in summer and autumn. The maximal value occurred in March while the minimal one appeared in July. (3) The phytoplankton community structure was influenced by different factors in different months. As a result, the groups of sampling station changed seasonally according to cluster analysis. (4) The obvious variation of phytoplankton community structure was present in 2010 compared with that in 2007. The number of species decreased from 340 in 2007 to 285 in 2010, however, the cell density increased obviously from (5.91 ± 0.90)×10⁵ cells/L in 2007 to (33.81 ± 10.10)×10⁵ cells/L in 2010. At the same time, both the numbers of oligotrophic algae and perphytic algae decreased to the same extent and eutrophic, filamentous and planktonic algae increased.