Optimizing the complexity of phytoplankton functional group modeling: An allometric approach

Elucidating patterns and mechanisms that shape phytoplankton assemblages is a popular area of research for empirical and theoretical ecologists. Despite the daunting complexity of phytoplankton dynamics, much of our current understanding has been based on simple models describing food-web interactions with few differential equations. Skeptical views in the literature raise concerns about the increasing model complexity and advice to seek parsimony rather than simplicity. To address this controversy (simple versus complex models), we propose the introduction of an extra layer of causality into plankton models by connecting algal processes (maximum growth rates, nutrient kinetics, settling velocities, metabolic rates) with species-specific morphological features (cell volume, surface-to-volume ratio, shape). In this study, we demonstrate the capacity of a size-based plankton model to reproduce observed water quality patterns (phosphate, total phosphorus, nitrate, total ammonia, total nitrogen, chlorophyll a, and total zooplankton biomass) in the Hamilton Harbour, Ontario. Consistent with empirical evidence, our modeling analysis showed that small algal species have a distinct competitive advantage in summer epilimnetic environments across the range of cell volume and nutrient loading conditions examined; especially, when they are characterized by higher optimal temperature for growth. Strong top-down pressure mediated by high zooplankton abundance effectively controls the standing biomass of phytoplankton species that can otherwise realize high growth rates under the conditions typically prevailing in the end-of-summer epilimnetic environments (e.g., higher temperature optima, higher tolerance in low water clarity). Under high zooplankton control, the secondary variations of phytoplankton are modulated by the ambient phosphorus levels and the size-based strategies for resources procurement, such as the regulation of nutrient transport kinetics. By contrast, when the summer algal assemblage is released by the zooplankton grazing, the exceedance of critical phytoplankton biomass levels and the likelihood of harmful algal blooms are determined by the multitude of factors that shape inter-specific competition patterns (e.g., relative abundance of competing species, nutrient uptake kinetics). Our study evaluates the strengths and weaknesses of this approach and identifies future directions that would provide operational models founded upon concepts of allometry.     

Growth Rates of Marine Phytoplankton: Correlation with Light Absorption by Cell Chlorophyll a

To better predict plant production in the sea, it would be desirable to be able to calculate, from easily obtainable measurements at one sampling, the growth rate of the prevailing stock of phytoplankton. To this end growth rates, pigment composition, cell volume and cell surface area data were collected for several species of marine phytoplankton in logarithmic growth at 20–21°C and 0.07 cal/cm². min light intensity. Similar data for one species, Dunaliella tertiolecta, are given for several combinations of light intensity and temperature, and for another species, Ditylum brightwellii, grown in nitrogen deficiency. The problem of estimating growth rates of phytoplankton was divided into three parts: 1) variation of growth rate among diverse species and its relationship to light absorption by cell chlorophyll a: 2) variation in growth rate with light intensity; 3) variation in growth rate with temperature. An equation has been formulated for calculating growth rate which provides a more precise fit of the data than do equations for growth rate based upon cell surface/volume ratios or cell volume. The formulation is based upon light absorption by chlorophyll a. It allows for variations in the efficiency of utilization of light absorbed by chlorophyll a and the changes in chlorophyll a content resulting from light intensity and temperature differences. We do not attempt to predict variations in growth rate with photoperiod or spectral distribution, nor do we allow for light effects upon growth rate not mediated by photosynthesis, so the model is, at best, a rough approximation of reality.     

Variation of the phytoplankton community across the subtropical convergence zone in the west pacific sector of the southern ocean during early austral Summer 1995/6

Phytoplankton of the Southern Ocean, 140–148°E and 40–53°S, was sampled from early austral summer Nov. 1995 to Dec. 1995 to examine cell abundance, cell volume and biomass (cell carbon) distribution across the fronts. A total of 90 phytoplankton taxa were identified. They were 50 diatoms, 37 dinoflagellates, 2 silicoflagellates, and 1 prymnesiophyte. 73 species were observed from north of the subtropical convergence zone and 71 species from south of the subtropical convergence zone.Pseudonitzschia spp. was the most widely distributed species. Nanoplankton predominated cell number of phytoplankton throughout the stations. The abundance of diatoms was higher than that of dinofiagellates. Total biomass profiles were dependent to microphytoplankton biomass. Maximum cell number and biomass were observed from subsurface layer. Phytoplankton community changed across the subtropical convergence zone and 50–53°S (antarctic convergence zone), and physicoehemical factors seem to controll the distribution.     

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。     

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.     

Temporal and spatial fluctuations of phytoplankton in a tropical coastal lagoon, southeast Brazil.

Spatial and temporal variability of the phytoplankton community in the tropical coastal Imboassica lagoon, an environment naturally isolated from the ocean by a narrow sandbar, was analysed every two weeks for 19 months by sampling three sites. During this study, the lagoon received direct input of marine water three times, resulting in remarkable salinity, nutrient concentrations and phytoplankton biomass variations in both temporal and spatial aspects. The phytoplankton biomass presented relatively low values ranging, on average, from 0.54 mg x L(-1) in the station closest to the sea (station 1) to 1.34 mg x L(-1) in the station close to a macrophyte bank (station 3). Diatoms and cryptomonads dominated in stations 1 and 2 (located relatively close to station 1, yet receiving the runoff of domestic sewage), and euglenoids, cryptomonads and dinoflagellates at station 3. Stations 1 and 2 usually presented the same dominant species but station 2 presented a higher phytoplankton biomass. On the other hand, station 3 showed more similar results concerning phytoplankton biomass with station 2, however the dominant species were usually different. The high fluctuations of salinity and the reduced nutrient availability are pointed out as the main factors structuring the dynamics of the phytoplankton community at the Imboassica lagoon.     

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.     

Downstream changes in phytoplankton composition and biomass in a lowland river–lake system (Warnow River, Germany)

To determine longitudinal changes in phytoplankton composition and biomass in the Warnow River (Germany), single water parcels were followed during their downstream transport in August and October 1996 and April 1997. In summer, the phytoplankton assemblage was dominated by centric diatom and cyanobacteria species. Stephanodiscus hantzschii, Pseudanabaena limnetica, Planktothrix agardhii and Aulacoseira granulata var. angustissima were the most frequent species. In autumn, small centric diatoms dominated the whole river course. Irrespective of the season, in the fluvial lakes of the upper river, a substantial increase of phytoplankton biomass was observed. Shallow upstream river stretches were associated with large biomass losses. In the deep, slow flowing lower regions, total biomass remained constant. Longitudinal changes in biomass reflected downstream variations in flow velocity and river morphology. Cyanobacteria, cryptophytes and diatom species were subjected to large biomass losses along fast flowing, shallow river sections, whereas chlorophytes were favoured. Diatoms and cryptophytes benefited from low flow velocity and increased water depth in the downstream river. Changes in water depth and flow velocity have been found as key factors that cause the longitudinal differences in phytoplankton composition and biomass in small rivers.     

Dominance patterns of planktonic algae in Swedish forest lakes

Dominance patterns of phytoplankton during a late phase (August) in the seasonal sequence of species are presented from 15 Swedish forest lakes with little or no local anthropogenic impact. The main question to elucidate is if predominance of a small number of species (1–3) occurs during a mature phase of the annual succession i.e. if there is an evident competitive exclusion of species in favour of a few dominants. Ten August months per lake are used to illustrate interannual variations caused mainly by differences in weather conditions. In general, 1–3 dominant taxa do not reach more than 60% of the total phytoplankton volume. Only lakes exposed to some stress factors exhibit a more pronounced dominance pattern with 1–3 species occupying >80% of the phytoplankton biomass. Stress factors are harsh climate (arctic lake), light deficiency (very brown water), acidification and occurrence of the invasive raphidophycean species Gonyostomum semen. The variation in phytoplankton assemblages in relation to environmental variables and years was tested by classification and ordination methods (TWINSPAN, CCA). The consistency of the species/lake groupings and the set of explanatory environmental variables was checked in a discriminant function analysis. Species associations during investigated years and environmental variables show a very good consistency and 75% of the lakes was classified in the same species group irrespective of year, indicating stable species assemblages from summer to summer.     

Gradient of dissolved free amino acids and phytoplankton in a shallow bay

A 3 h survey of the concentrations of individual free amino acids, chlorophyll a and phytoplankton species biomass was conducted in the surface waters of a shallow bay. Significant coefficients of correlation were found between chlorophyll a, nanoflagellates, and DFAA concentrations. Although phytoplankton biomass variations sometimes relate to DFAA concentration patterns, consideration of the physiological activity of both phytoplankton and microheterotrophs would undoubtedly explain a more significant fraction of the DFAA variation.This work is a contribution of GREPMA (Groupe Régional d'Etudes Pélagiques en Manche-Atlantique)     

Spatiotemporal and long-term variation in phytoplankton communities in the oligotrophic Lake Pyhäjärvi on the Finnish-Russian border

As part of the joint Finnish-Russian research and development project “Assessment of the ecological state of the transboundary waters”, seasonal and spatial variations in the phytoplankton communities of Lake Pyhäjärvi were studied in order to identify possible long-term (1963–2002) changes and to present recent data (since 2002) on phytoplankton biomass and species composition. Some changes in both phytoplankton biomass and species composition, particularly in the littoral zone and northern basins of the lake, were obvious at the end of the 1980s; in particular, the density of blue-greens increased during that period. Biomasses increased five-fold in 1980, decreased after 1990 and have remained low (0.14 mg l^?l) to the present time. The effective water protection measures applied, especially reducing the phosphorus load from municipal wastewaters and airborne pollution, can now be seen to have improved the water quality. Although no significant temporal differences were found in phytoplankton biomass during the intensive biweekly sampling in 2002, considerable spatial variation was seen within the lake. An obvious change in the species composition of phytoplankton and an increase in biomass were seen even in the loaded parts of the lake. Despite the spatial differences in phytoplankton biomass and community structure, the changed species composition in the northern part of the lake indicated a clear recovery from the blue-green and Chrysophyceae dominated high biomass of the 1980s.     

A morphometric method for correcting phytoplankton cell volume estimates

Summary Cell volume calculations are often used to estimate biomass of natural phytoplankton assemblages. Such estimates may be questioned due to morphological differences in the organisms present. Morphometric analysis of 8 species representative of phytoplankton types found in the Great Lakes shows significant differences in cell constituent volumes. Volume of physiologically inert wall material ranges from nil, in some flagellates, to over 20% of the total cell volume in certain diatoms. Likewise, empty vacuole may comprise more than 40% of the total cell volume of some diatoms, but less than 3% of the volume of some flagellates. In the organisms investigated, the total carbon containing cytoplasm ranged from 52% to 98% of the total cell volume and the metabolizing biovolume ranged from 30% to 82%. Although these differences complicate direct biomass estimation, morphometric analysis at the ultrastructural level may provide ecologically valuable insights.     

博斯腾湖浮游植物群落结构特征及其影响因子分析

2011年对博斯腾湖大湖区17个采样站位的浮游植物及水体主要理化因子进行了4次系统调查。结果表明, 在17个站位共鉴定出浮游植物127种（属）, 其中优势种（属）9种。浮游植物群落全年均以硅藻为主导, 冬、春季节, 浮游植物组成呈硅藻-甲藻型, 优势类群主要为贫-中营养型浮游藻类, 到夏、秋季节逐渐形成硅藻-绿藻型, 以富营养型的浮游藻类为优势类群。浮游植物总平均生物量为（2.512.95） mg/L, 生物量季节变动显著, 峰值出现在夏季, 冬季最低。基于Canoco的多变量分析表明: 环境变量共解释了浮游植物群落总变异的54.5%, 水温是影响浮游植物分布最重要的环境因子, 其次为枝角类丰度。水中氮含量是影响浮游植物丰度的主要因子, 同时浮游植物对水体有机物含量也有较大的影响。       

西安城市河流浮游植物群落结构及其与环境因子的关系

为探究西安市城市河流浮游植物群落结构特征及其与环境因子的关系,分别于2020年10月和2021年6月对灞河、浐河、沣河及黑河共计24个采样点进行了浮游植物群落组成、细胞密度和生物量的调查研究,并利用冗余分析(RDA)研究环境因子对浮游植物群落结构的影响。调查结果显示,枯水期共鉴定出浮游植物6门115种,主要包括蓝藻门(11.30%)、硅藻门(54.78%)及绿藻门(26.96%),浮游植物细胞密度均值为(3.36±3.50)×106 cells/L,生物量均值为(1.79±3.59) mg/L。丰水期共鉴定出浮游植物7门168种,主要包括蓝藻门(7.74%)、硅藻门(51.79%)及绿藻门(29.76%),浮游植物细胞密度均值为(9.17±9.73)×10⁶ cells/L,生物量均值为(6.54±11.57) mg/L。与枯水期相比,丰水期在物种数量、细胞密度和生物量都大于枯水期。聚类分析结果表明,西安城市河流大部分采样点之间浮游植物群落结构及水环境状况具有相似性,而人类活动可能是导致其余点位具有空间差异性的主要原因。冗余分析(RNA)结果表明影响西安市城市河流...     

Spatial Distribution of the Phytoplankton in a Tropical Lake (Lake Lanao,Philippines)

The distribution of phytoplankton was studied in Lake Lanao, Philippines. In calm weather, the species segregate vertically with motile species and buoyancy-regulating species above other species in the water column. On a distance scale of 12.5 km, horizontal variability yields a coefficient of variation of 23.6% for total biomass, 30.2% for net primary production, and an average of 30.3% for individual species biomass after removal of error variances. Variabilities on a scale of 1 km are about half as large. Horizontal patchiness of individual species is not related to their abundance, surface to volume ratio, morphotype, or taxon, but is negatively related to their size.     

Impact of nutrients on photoacclimation of phytoplankton in an oligotrophic lake measured with long-term and high-frequency data: implications for chlorophyll as an estimate of phytoplankton biomass

Hydrobiologia - Chlorophyll measurements are commonly used to estimate phytoplankton biomass. However, phytoplankton readily acclimate to variations in light through a range of phenotypic...     

Estimating phytoplankton carbon from microscopic counts: an application for riverine systems

Algal biomass, in addition to cell numbers, is a measure of the successful conversion of inorganic to organic carbon. Consequently, carbon is the main currency used in aquatic models and in flux and budget studies. On the other hand, microscopic observation and counts remain the only means for determining species composition and biomass, which is relevant to many aspects of aquatic ecology. In this study, we focus on the way to convert biovolume to carbon biomass for algal assemblages of two rivers, using a computerized system that records dimensions of phytoplankton (Gosselain & Hamilton, 2000). We first compare different equations found in the literature for converting algal cell volume to cellular carbon content. We then evaluate the accuracy of a biomass estimate based on less time-consuming measurements, using pre-determined biovolume values instead of measuring cells in all samples. Biovolume/carbon equations are evaluated using total phytoplankton carbon biomass determined from measured chlorophyll a. Equations established for freshwater taxa seem to provide better estimates of algal biomass in the two case studies presented here, the Rideau and Meuse rivers (Canada and Belgium, respectively) than do more numerous equations defined for marine taxa. Furthermore, equations that make a distinction between diatoms and other algae appear more appropriate than those considering all algal groups as a whole. Finally, mean values of algal biovolumes, determined using sufficient measurements of cell dimensions from representative sampling series, may prove sufficient for carbon estimates of taxa in relatively homogenous size ranges. The careful choice of appropriate volumetric shapes and taxa categories remains of prime importance to get precise results.     

Biomass, protein- and carbohydrate-composition of phytoplankton in Varna Bay, Black Sea

It was shown that phytoplankton from the Varna Bay, Black Sea, has significantly more suspended carbohydrates, proteins and biomass in July than in April. The dominant species were Bacillariophyceae and Dinophyceae. Electrophoretic and fluorescent spectra have shown the main differences in molecular weight and stability of phytoplankton proteins. Phytoplankton included specific proteins distributed over a limited range of molecular weights between 14 and 72 kilodaltons (kDa). The most abundant protein constituents in phytoplankton samples collected in April were around 45–55 kDa. The seasonal variations of the environment influence the quantitative and qualitative changes in phytoplankton.     

A comparison of phytoplankton biomass parameters and their interrelation with nutrients in Saronicos Gulf (Greece)

The relationship between total phytoplankton cell number, chlorophyll a, cell volume, and the response of these parameters to reactive phosphorus and nitrate in surface waters of Saronicos Gulf (Greece) was examined using simple and partial correlation statistics. Different conclusions could be drawn as to the comparability between biomass parameters and their interrelation with nutrients. Partial correlation analysis is considered to be a better method for comparing ecological data. The analysis of phytoplankton abundance should include determinations of as many biomass characteristics as possible since each has its own specificity.