安徽沱湖夏季浮游植物群落结构特征与环境因子关系

为了揭示沱湖浮游植物群落结构特征及其与水环境因子的关系,于2016年7月(夏季),对沱湖流域上游至下游11个采样点浮游植物种类组成、细胞丰度、生物量等进行调查研究。结果显示,沱湖共有浮游植物96种(含变种),隶属8门48属,其中绿藻门(Chlorophyta)和硅藻门(Bacillariophyta)种类最多,绿藻门有23属39种,占总种数的40.63%,硅藻门有7属20种,占总种数的20.83%;其次为裸藻门(Euglenophyta),有5属17种,占总种数的17.71%,蓝藻门(Cyanophyta) 8属14种,占14.58%;甲藻门(Pyrrophyta) 2属2种,隐藻门(Cryptophyta) 1属2种,各占总种数的2.08%,黄藻门(Xanthophyta)与金藻门(Chrysophyta)均有1属1种,均占总种数的1.04%。绿藻和硅藻类物种在沱湖浮游植物群落结构中处于优势地位,沱湖夏季浮游植物种类组成表现为绿藻-硅藻型。沱湖夏季浮游植物细胞丰度与生物量从上游到下游呈逐渐增加趋势,细胞丰度与生物量平均值分别为4.022×106cells/L与3.046 mg/L,蓝藻门和绿藻门类群为沱湖浮游植物细胞丰度主体,硅藻门和裸藻门类群为沱湖浮游植物生物量的主体;上游浮游植物多样性指数与均匀度指数均略高于下游采样点,沱湖水质呈β中污型-无污染型,上游水质优于下游水质。浮游植物群落结构与水环境因子的典型对应分析(CCA)结果表明,电导率、透明度、水深及pH值等环境因子与沱湖夏季浮游植物群落结构有较强的相关性。     

鹤地水库浮游植物群落的结构与动态

鹤地水库位于雷州半岛北部(21°42'～22°22'N,109°54'～110°25'E),是一座中营养化的大型水库.为了研究其浮游植物群落的结构与变化特点,在水库设置5个采样点,并于2003年2、7、9、12月对其采样.鹤地水库浮游植物生物量变化为O.156～2.548 mg L~(-1),主要由蓝藻和硅藻组成.5个采样点的浮游植物生物量具有明显的季节变化,且变化趋势相同,即丰水期的生物量高于枯水期,主要是由于丰水期水温较高以及入库河水带入的营养盐.5个采样点的浮游植物生物量从主要入库河流至大坝区呈下降趋势,与磷浓度的降低直接相关.浮游植物优势种主要以热带代表性种类为主,且有明显的季节变化,枯水期主要为硅藻的根管藻(Rhizosolenia sp.)、小环藻(Cyclotella sp.)、颗粒直链藻(Melosira granulata)以及模糊直链藻(Melosira ambigua)等.丰水期为蓝藻的拟柱孢藻(Cylindrospermopsis raciborskii)、湖泊假鱼腥藻(Pseudanabaena limnetica)等,浮游植物优势种类的变化主要受磷浓度的影响.浮游植物前8个优势种的生物量占浮游植物群落生物量的850%～92%,显著低于温带地区浮游植物群落结构稳定的湖泊.     

A Compositional and Structural Analysis of Phytoplankton in Lake Khurpatal, (U.P.), India

The phytoplankton community in Lake Khurpatal (Kumaun Himalya), India, was analyzed in relation to physico-chemical variables. Phytoplankton biomass ranged from 2.7 to 20.0 g m⁻³ in the euphotic zone of the lake. Dinoflagellates monopolized the algal community with a mean annual contribution of 94.5 % to the total phytoplankton biomass. The community coefficient used to quantify the seasonal changes in algal population reflected the fact that successional episodes were not very significant, the percentage similarity among the consecutive algal samples ranging from 47.8 to 89.9 %. The phytoplankton community was characterized by low species richness, low equitability and species diversity. Various ecological characteristics of the community are discussed and the phytoplankton biomass is also compared with that of some tropical and temperate lakes.     

Relationship between Chlorophyll-α Concentration and Phytoplankton Biomass in Several Reservoirs in Czechoslovakia

Parallel determinations of phytoplankton biomass and chlorophyll-α concentration were carried out on five reservoirs. Highly significant positive correlations between phytoplankton biomass values and chlorophyll-α values were found. The possibility of finding a conversion factor linking these two parameters is discussed. The chlorophyll content per unit phytoplankton biomass encountered during the period of study in all reservoirs varied between 0.14 and 3.41% of fresh weight. The influence of light intensity, nutrient concentration and species composition on chlorophyll content per unit phytoplankton biomass is considered.     

巢湖春夏季节浮游植物的动态变化

2009年3月至8月,利用原位围隔实验和野外调查,研究了巢湖春夏季节浮游植物的动态变化.结果显示:围隔中浮游植物密度和生物量的变动范围分别是(2.95～102.43)×10⁵ cells·L^-1和0.0-7.39 mg·L^-1,优势种类为鱼腥藻属(Anabaena)、梅尼小环藻(Cyclotella meneghiniana)和圆筒锥囊藻(Dinobryon cylindricum),其最大生物量分别为0.82 mg·L^-1、0.66mg·L^-1和2.98 mg·L^-1,均出现在3月或4月.在巢湖湖水中,春季(3～5月)浮游植物平均生物量为5.43mg·L^-1,其中绿藻占47.59%、硅藻占40.81%、蓝藻占10.18%,优势种类为盘星藻属(Pediastrum)和梅尼小环藻;而夏季(6～7月)浮游植物平均生物量为7.89mg·L^-1,其中蓝藻占58.7%、绿藻占2.77%、硅藻占11.4%,优势种类为微囊藻属(Microcystis).磷和枝角类滤食对巢湖春夏季节浮游植物的生物量和群落结构有重要影响.     

应用光合色素研究广西钦州湾丰水期浮游植物群落结构

通过2010年6月现场航次19个站点的调查,应用反相高效液相色谱(RP - HPLC) 并结合二极管阵列检测器分析技术,分析了丰水期广西钦州湾浮游植物光合色素组成,进而由CHEMTAX 软件估算全粒级浮游植物的群落结构。结果表明,钦州湾浮游植物光合色素含量以叶绿素a最高,其次为岩藻黄素;浮游植物的优势类群为硅藻,其次为蓝藻和青绿藻,它们分别平均占据了浮游植物生物量的70.2%、12.6%和9.4%,而其它藻类除了绿藻茅岭江河口占据较高的比例(40.2%)之外在其它站点所占比例很低。钦州湾浮游植物群落结构形成了茅岭江口、内湾、外湾和湾外近海共四种类型,茅岭江口以绿藻为优势类群,内湾以硅藻、蓝藻和青绿藻为主要优势类群,外湾以硅藻为单一优势类群,湾外相对于外湾硅藻比重略为下降。主要光合色素含量及浮游植物类群生物量的分布特征与盐度、营养盐关系密切,浮游植物群落结构的分布变化主要受径流及其输入导致的营养盐变化的影响,而这种影响导致了内湾和外湾之间浮游植物主要类群的生物量多寡及浮游植物群落结构的差异。     

The time course of phytoplankton biomass and related limnological factors in shallow and deep lakes: a multivariate approach

Weekly studies of phytoplankton biomass and environmental variables were made over one year in a shallow stratifying, hypertrophic El Porcal lake near Madrid (Spain). Data were collected on abiotic factors, primary production, biomass and phytoplankton losses and subjected to reduction by means of several principal component analyses. Furthermore, weekly data on the same variables were gathered from published studies on Überlinger See, an embayment of the much deeper, mesotrophic Lake Constance (Central Europe), and treated in the same way. The two first principal components of PCAs on biological variables explained more than 60% of overall variance in both lakes. They could be ascribed to phytoplankton production + biomass and photosynthetic physiology + phytoplankton losses, respectively. The ordination of the biological trajectories in the data space of the two first principal components revealed six stable states of phytoplankton biomass in the shallow lake and seven in the deep lake. The breakpoints between stable states could be due to environmental, abiotic variables in some cases but biological interactions were suspected to be the cause of the other breakpoints. The abiotic effects on phytoplankton biomass took longer to occur in the deep lake. Also, short-term dynamics (one-three weeks) were demonstrated for both phytoplankton communities.A preliminary comparison between phytoplankton biomass dynamics in stratifying, shallow and deep lakes suggests that differences may be attributed partly to differences in depth.     

Interaction matters: Bottom-up driver interdependencies alter the projected response of phytoplankton communities to climate change

Phytoplankton growth is controlled by multiple environmental drivers, which are all modified by climate change. While numerous experimental studies identify interactive effects between drivers, large-scale ocean biogeochemistry models mostly account for growth responses to each driver separately and leave the results of these experimental multiple-driver studies largely unused. Here, we amend phytoplankton growth functions in a biogeochemical model by dual-driver interactions (CO₂ and temperature, CO₂ and light), based on data of a published meta-analysis on multiple-driver laboratory experiments. The effect of this parametrization on phytoplankton biomass and community composition is tested using present-day and future high-emission (SSP5-8.5) climate forcing. While the projected decrease in future total global phytoplankton biomass in simulations with driver interactions is similar to that in control simulations without driver interactions (5%–6%), interactive driver effects are group-specific. Globally, diatom biomass decreases more with interactive effects compared with the control simulation (−8.1% with interactions vs. no change without interactions). Small-phytoplankton biomass, by contrast, decreases less with on-going climate change when the model accounts for driver interactions (−5.0% vs. −9.0%). The response of global coccolithophore biomass to future climate conditions is even reversed when interactions are considered (+33.2% instead of −10.8%). Regionally, the largest difference in the future phytoplankton community composition between the simulations with and without driver interactions is detected in the Southern Ocean, where diatom biomass decreases (−7.5%) instead of increases (+14.5%), raising the share of small phytoplankton and coccolithophores of total phytoplankton biomass. Hence, interactive effects impact the phytoplankton community structure and related biogeochemical fluxes in a future ocean. Our approach is a first step to integrate the mechanistic understanding of interacting driver effects on phytoplankton growth gained by numerous laboratory experiments into a global ocean biogeochemistry model, aiming toward more realistic future projections of phytoplankton biomass and community composition.     

Nutrient pulsing as a regulator of phytoplankton abundance and community composition in Galveston Bay, Texas

Galveston Bay, Texas, is a large shallow estuary with a watershed that includes 60% of the major industrial facilities of Texas. However, the system exhibits low to moderate (2-20 μg l⁻¹) microalgal biomass with sporadic phytoplankton blooms. Both nitrogen (N) and phosphate (P) limitation of phytoplankton growth have been proposed for the estuary. However, shifts between N and P limitation of algae growth may occur due to annual fluctuations in nutrient concentrations. The primary goal of this work was to determine the primary limiting nutrient for phytoplankton in Galveston Bay. Nutrient addition bioassays were used to assess short-term (1-2 days) phytoplankton responses (both biomass and community composition) to potentially limiting nutrients. The experimental bioassays were conducted over an annual cycle using natural water collected from the center to lower part of the estuary. Total phytoplankton biomass increased in the nitrate (10 μM) additions in 11 of the 13 bioassays, but no significant increases were detected in the phosphate (3 μM)-only additions. Bioassay results suggest that the phytoplankton community was usually not phosphate limited. All major groups increased in biomass following nitrate additions but diatoms increased in biomass at a faster rate than other groups, shifting the community composition toward higher relative abundance of diatoms. The results of this study suggest that pulsed N input events preferentially favor increases in diatom biomass in this estuary. The broader implications of this study are that N pulsing events, primarily due to river discharge, play an important role in structuring the phytoplankton community in the Galveston Bay estuary.     

Distribution and development of under-ice phytoplankton in 90-m deep water column of Lake Päijänne (Finland) during spring convection

Distribution and development of phytoplankton were studied in the deep and large Lake Päijänne from mid-winter until the disappearance of ice. Diatoms were an important part of the phytoplankton assemblage and, with cryptophytes and chrysophytes, made up 50–80% of the phytoplankton biomass. In mid-winter, chlorophyll a and phytoplankton biomass were uniformly distributed over the whole water column down to a depth of 90 m. Thus, most of the phytoplankton was in virtual darkness and there was negligible growth. Only motile cryptophytes were concentrated in the layers below the ice and were rare in deep water. After the disappearance of snow, convection developed, but at first cryptophytes were able to resist mixing. When convection turned from penetrative to predominantly horizontal, all phytoplankton were generally uniformly distributed in the water column. In spite of the full under-ice overturn with low average availability of light, the phytoplankton biomass doubled in April. The growth of cryptophytes was higher than that of diatoms, suggesting that motile species gained an advantage by being able to maintain themselves in the upper, illuminated layers. The results show that knowledge of the basic physical framework is essential for interpretation of under-ice phytoplankton results.     

Size‐Fractionated Phytoplankton and Relationships with Metazooplankton in a Newly Flooded Reservoir

In order to yield some insights into the planktonic food web structure of new reservoirs, size‐fractionated biomass and productivity of phytoplankton were examined from 1996 to 1997 (following the 1995 flooding of the Sep Reservoir, Puy‐de‐Dôme, France), in relation to nutrients (P, N) and metazooplankton (Rotifers, Cladocera, Copepods). Autotrophic nanoplankton (ANP, size class 3–45 μm) dominated the phytoplankton biomass (as Chlorophyll a) and production, while autotrophic picoplankton (APP, 0.7–3 μm) exhibited the lowest and relatively constant biomass and production. Cells of the autotrophic microplankton (AMP, >45 μm) were considered inedible for planktonic herbivores. The production‐biomass diagram for the different size classes and the positive correlation between APP production and ANP + AMP production suggested that grazing was potentially more important than nutrients in shaping the phytoplankton size structure. Metazooplankton biomass was low compared to other newly flooded reservoirs or to natural lakes with phytoplankton biomass similar to that of the Sep Reservoir. This resulted in low ratios (metazooplankton to edible phytoplankton) both in terms of production (average 0.43% in 1996 and 0.76% in 1997) and biomass, suggesting that only a small fraction of phytoplankton was directly consumed by metazooplankton. We suggest that the observed low ratios in the Sep Reservoir, reflect possible low metazooplankton inputs in the main influents, changes in hydrologic conditions and a high potential role of microheterotrophs. The latter role was supported by (i) the positive inter‐annual correlation between ciliates and phytoplankton, (ii) the significant and negative correlations between ciliates and metazooplankton, and (iii) the significant and negative correlations between total metazooplankton biomass and total phosphorus (TP), whereas neither TP nor total metazooplankton biomass was correlated with phytoplankton variables.     

Precipitation-Induced Alternative Regime Switches in Shallow Lakes of the Boreal Plains (Alberta,Canada)

This study focused on unraveling the natural mechanism for the frequent shifts in alternative regimes in pristine shallow lakes of the Boreal Plains, Alberta, Canada. The lakes tend to be clear and dominated by submerged aquatic vegetation (SAV) or turbid and dominated by phytoplankton. We report on the inter-annual response of 23 lakes from 2001 to 2007. We explore the effect of fluctuations in annual precipitation on the lake response including water depth, total phosphorus (TP) concentration, turbidity, phytoplankton biomass, SAV biomass, and the proportion of clear and turbid lakes. The regime switches appear driven by the transient dynamics of phytoplankton, and dilution of nutrients, phytoplankton biomass, and turbidity during wet years, and evapoconcentration during dry years. Increased precipitation was correlated with decreased phytoplankton biomass, TP concentration, chloride concentration, and turbidity. In 2005, the wettest year, no phytoplankton-dominated lakes were observed. During the driest year (2002), the phytoplankton-dominant regime (>18 μg chl-a L^?1) occurred in 22% of lakes, which was higher than the study period average. SAV biomass was not directly affected by precipitation, but was negatively associated with phytoplankton biomass and positively associated with the previous year’s SAV growth. SAV biomass was carried over from year-to-year, and the occurrence of SAV-dominated (>25% cover) lakes was significantly higher in 2007 (90%) following 3 years of high precipitation levels.     

绥宁河生态修复对粒径分级叶绿素a的影响

通过对上海市的苏州河支流绥宁河治理段与非治理段水体叶绿素a分粒级分析,探讨了生态修复对水体粒径分级叶绿素a的影响．结果表明,非治理和对照以及治理采样点微型和微微型浮游植物叶绿素a占总叶绿素a的百分比均值分别为85．232、92．402和95．205％,其中微型浮游植物叶绿素a占总叶绿素a的百分比均值分别为78．460、87．943和87．211％,对全河叶绿素a的贡献平均为84．538％,是该水体叶绿素a生物量的最大贡献者;网采浮游植物对全河叶绿素a的贡献仅为9．054％．生态修复工程试验使网采浮游植物相对生物量减少,微型浮游植物相对生物量保持稳定,而微微型浮游植物相对生物量增多,对超微型浮游植物的影响不大,微型和微微型浮游植物对工程试验的反应最敏感．     

Response of Sargasso Sea phytoplankton biomass, growth rates and primary production to seasonally varying physical forcing

The response of phytoplankton biomass, growth rates and primaryproduction to seasonally varying physical forcing was studiedat a station southeast of Bermuda over an 18 month period. Phytoplanktongrowth rates and primary production were measured using thepigment-labeling method, and phytoplankton biomass was calculatedfrom these measurements. Phytoplankton carbon biomass variedsystematically over the year. Highest values were observed duringthe winter and spring. Seasonal variations of chlorophyll (Chi)a in the surface layer could primarily be attributed to variationsin phytoplankton biomass and secondarily to photoacclimation.During the summer period, average values of carbon (C)/Chl ratios(g C g^–1 Chi) ranged from 160 at the surface to 33 atthe 1.6% light level, changes attributed to photoacclimationof the phytoplankton, consistent with the observation that phytoplanktonbiomass did not vary as a function of depth. Phytoplankton growthrates in the surface layer did not vary systematically overthe year, ranging from 0.15 to 0.45 day^–1, in spite ofseasonally varying concentrations of nitrate. Growth rates variedas a function of depth from average values of 0.3 day^–1in the surface layer to <0.1 day¹ at the 1.6% light level.Thus, the primary response of the phytoplankton community tonutrient enrichment during the winter period was an increasein phytoplankton biomass rather than an increase in growth rates.A simple nutrient-phyto-plankton-zooplankton model was usedto explore this phenomenon. The model demonstrated that theobserved response of the phytoplankton to nutrient enrichmentis only possible when phytoplankton growth is not severely limitedby nutrients.     

基于遥感数据的东海浮游植物生物量时空变化研究

基于地理位置、纬度和生态特征的不同在东海选取了9个面积相同的子区域,采用1997-2015年由SeaWiFS(Sea-Viewing Wide Field-of-View Sensor)和MODIS(Moderate-Resolution Imaging Spectroradiometer)传感器获得的叶绿素a浓度资料,对我国东海浮游植物生物量的时空变化和藻华现象进行了分析。通过高斯曲线模型拟合,得到了藻华爆发的起始时间、峰值时间、结束时间及持续时间。研究表明东海浮游植物生物量在空间上的分布规律为:外海浮游植物生物量小于近岸;长江口和台州列岛海域的浮游植物生物量较大,近黄海海域的两个区域次之,较小的位于南麂列岛海域和台湾海峡,越靠近南部海域浮游植物生物量越低。藻华发生的规律为:以南麂列岛为分界线,由高纬度到低纬度,浮游植物到达藻华发生峰值的时间持续推后,爆发持续时间增长。     

Which factors affect phytoplankton biomass in shallow eutrophic lakes?

The restoration and management of shallow, pond-like systems are hindered by limitations in the applicability of the well-known models describing the relationship between nutrients and lake phytoplankton biomass in higher ranges of nutrient concentration. Trophic models for naturally eutrophic small, shallow, endorheic lakes have not yet been developed, even though these are the most frequent standing waters in continental lowlands. The aim of this study was to identify variables that can be considered as main drivers of phytoplankton biomass and to build a predictive model. The influence of potential drivers of phytoplankton biomass (nutrients, other chemical variables, land use, lake use and lake depth) from 24 shallow eutrophic lakes was tested using data in the Pannonian ecoregion (Hungary and Romania). By incorporating lake depth, TP, TN and lake use as independent and Chl-a as dependent variables into different models (multiple regression model, GLM and multilayer perception model) predictive models were built. These models explained >50% of the variance. Although phytoplankton biomass in small, shallow, enriched lakes is strongly influenced by stochastic effects, our results suggest that phytoplankton biomass can be predicted by applying a multiple stressor approach, and that the model results can be used for management purposes.     

Ecological restoration in eutrophic Lake Wuli: A large enclosure experiment

A large-scale enclosure experiment for lake restoration was carried out in Lake Wuli, a northern bay of shallow and eutrophic Lake Taihu in China. The large enclosure with an area of 10 ha was set up in the littoral zone and was bordered by waterproof fabric which did not cover the sediments. Multiple approaches were used and included fish removal, piscivorous fish stocking, shoreline reconstruction, aquatic macrophyte planting, benthic macro-animal stocking, and silver carp cultivation in pens for reduction of cyanobacteria. The results showed that the coverage of aquatic macrophytes increased from 0% to 45.7%. Mean concentrations of TN and TP inside the enclosure from May 2004 to May 2008 were 22.2% and 26.0% of those outside, respectively. Secchi depth was 0.40 m outside the enclosures and 0.75 m inside. However, responses of phytoplankton to the restoration project lagged behind improvement of water quality and reestablishment of aquatic plants. The phytoplankton biomass gradually decreased after the third year of the restoration. Stocking piscivorous fish and planting submerged macrophytes could not increase zooplankton biomass and enhance graze pressure on phytoplankton, most likely due to high omnivorous fish density and lower nutrition inside the enclosure. Higher grazing pressure of zooplankton on phytoplankton was observed in May and October every year. Zooplankton to phytoplankton biomass ratios were significantly negatively correlated with phytoplankton biomass outside (r = −0.440, p < 0.01) and inside the enclosure (r = −0.336, p < 0.05) from February 2004 to March 2007. Therefore, phytoplankton biomass inside and outside the enclosure was lower in May and October. Higher grazing pressure of zooplankton on phytoplankton in spring may result in occurrence of the clear-water phase that facilitated growth of submerged macrophytes in the littoral in Lake Wuli, and a clear-water state and improved water quality would likely be sustained throughout the year after reestablishment of submerged macrophytes.     

一座南亚热带小型贫营养水库浮游植物群落结构及季节变化

库容大小是影响水体水动力学过程的一个重要变量,它能在很大程度决定生态系统的结构,特别是浮游植物的群落结构.为了解小型贫营养水库浮游植物的群落特点,于2006年4、8、12月对位珠海市的贫营养小型水库-吉大水库的浮游植物群落结构进行采样和计数分析.3次采样共检出浮游植物32种,浮游植物细胞丰度的变化范围在69～342 cells·mL^-1,生物量的变化范围在1.34～3.69 mg·L^-1,夏季浮游植物的丰度和生物量明显高于冬季.甲藻是最主要的优势种类,且相对优势度较为稳定.夏季,隐藻门的隐藻(Cryptomonas sp.)和绿藻门的鼓藻(Cosmarium spp.)大量出现,甲藻的相对优势度有所降低.冬季,隐藻数量急剧下降,但硅藻门的颗粒直链藻(Aulacoseira granulata)大量出现,与甲藻共同成为水体中的优势种.由降雨引起的营养盐浓度增加是浮游植物变化的主要影响因子,而透明度全年维持较高的水平为浮游植物的生长形成了有利条件,此外,较为稳定的水体和甲藻利用营养盐的能力使得甲藻成为浮游植物中的最主要的优势种.     

Seasonal dynamics of zooplankton and grazing impact of microzooplankton on phytoplankton in Sanmen Bay, China

The species composition, biomass, abundance and species diversity of zooplankton were determined for samples collected from 12 stations in Sanmen Bay, China, in four cruises from August 2002 to May 2003. Growth of phytoplankton and grazing rates of microzooplankton were measured using the dilution technique. The spatial and temporal variation of zooplankton and its relationship with environmental factors were also analyzed. The results showed that a total of 89 species of zooplankton belonging to 67 genera and 16 groups of pelagic larvae were found in Sanmen Bay. The coastal low-saline species was the dominant ecotype in the study area, and the dominant species were Calanus sinicus, Labidocera euchaeta, Tortanus derjugini, Acartia pacifica, Pseudeuphausia sinica and Sagitta bedoti. Maximum biomass was recorded in August, followed by November and May, and the lowest biomass was recorded in February. Similarly, the highest abundance of zooplankton was observed in August, followed by May, November, and February. Grazing pressure of microzooplankton on phytoplankton in Sanmen Bay existed throughout the year, although the grazing rate of microzooplankton on phytoplankton varied with the season. Estimates for growth rate of phytoplankton ranged from 0.25 d^?1 to 0.89 d^?1, whereas grazing rate of microzooplankton ranged between 0.18 d^?1 and 0.68 d^?1 in different seasons. The growth rate of phytoplankton exceeded the grazing rate of microzooplankton in all the seasons. Grazing pressure of microzooplankton on phytoplankton ranged from 16.1% d^?1 to 49.1% d^?1, and the grazing pressure of microzooplankton on primary production of phytoplankton ranged from 58.3% d^?1 to 83.6% d^?1 in different seasons.