Phytoplankton Succession in Recurrently Fluctuating Environments

Coastal marine systems are affected by seasonal variations in biogeochemical and physical processes, sometimes leading to alternating periods of reproductive growth limitation within an annual cycle. Transitions between these periods can be sudden or gradual. Human activities, such as reservoir construction and interbasin water transfers, influence these processes and can affect the type of transition between resource loading conditions. How such human activities might influence phytoplankton succession is largely unknown. Here, we employ a multispecies, multi-nutrient model to explore how nutrient loading switching mode might affect phytoplankton succession. The model is based on the Monod-relationship, predicting an instantaneous reproductive growth rate from ambient inorganic nutrient concentrations whereas the limiting nutrient at any given time was determined by Liebig’s Law of the Minimum. When these relationships are combined with population loss factors, such as hydraulic displacement of cells associated with inflows, a characterization of a species’ niche can be achieved through application of the R* conceptual model, thus enabling an ecological interpretation of modeling results. We found that the mode of reversal in resource supply concentrations had a profound effect. When resource supply reversals were sudden, as expected in systems influenced by pulsed inflows or wind-driven mixing events, phytoplankton were characterized by alternating succession dynamics, a phenomenon documented in inland water bodies of temperate latitudes. When resource supply reversals were gradual, as expected in systems influenced by seasonally developing wet and dry seasons, or annually occurring periods of upwelling, phytoplankton dynamics were characterized by mirror-image succession patterns. This phenomenon has not been reported previously in plankton systems but has been observed in some terrestrial plant systems. These findings suggest that a transition from alternating to “mirror-image” succession patterns might arise with continued coastal zone development, with crucial implications for ecosystems dependent on time-sensitive processes, e.g., spawning events and migration patterns.     

Phytoplankton Assemblage Characteristics in Recurrently Fluctuating Environments

Annual variations in biogeochemical and physical processes can lead to nutrient variability and seasonal patterns in phytoplankton productivity and assemblage structure. In many coastal systems river inflow and water exchange with the ocean varies seasonally, and alternating periods can arise where the nutrient most limiting to phytoplankton growth switches. Transitions between these alternating periods can be sudden or gradual and this depends on human activities, such as reservoir construction and interbasin water transfers. How such activities might influence phytoplankton assemblages is largely unknown. Here, we employed a multispecies, multi-nutrient model to explore how nutrient loading switching mode might affect characteristics of phytoplankton assemblages. The model is based on the Monod-relationship, predicting an instantaneous growth rate from ambient inorganic nutrient concentrations whereas the limiting nutrient at any given time was determined by Liebig’s Law of the Minimum. Our simulated phytoplankton assemblages self-organized from species rich pools over a 15-year period, and only the surviving species were considered as assemblage members. Using the model, we explored the interactive effects of complementarity level in trait trade-offs within phytoplankton assemblages and the amount of noise in the resource supply concentrations. We found that the effect of shift from a sudden resource supply transition to a gradual one, as observed in systems impacted by watershed development, was dependent on the level of complementarity. In the extremes, phytoplankton species richness and relative overyielding increased when complementarity was lowest, and phytoplankton biomass increased greatly when complementarity was highest. For low-complementarity simulations, the persistence of poorer-performing phytoplankton species of intermediate R*s led to higher richness and relative overyielding. For high-complementarity simulations, the formation of phytoplankton species clusters and niche compression enabled higher biomass accumulation. Our findings suggest that an understanding of factors influencing the emergence of life history traits important to complementarity is necessary to predict the impact of watershed development on phytoplankton productivity and assemblage structure.     

Establishment Probability in Fluctuating Environments: A Branching Process Model

We study the establishment probability of invaders in stochastically fluctuating environments and the related issue of extinction probability of small populations in such environments, by means of an inhomogeneous branching process model. In the model it is assumed that individuals reproduce asexually during discrete reproduction periods. Within each period, individuals have (independent) Poisson distributed numbers of offspring. The expected numbers of offspring per individual are independently identically distributed over the periods. It is shown that the establishment probability of an invader varies over the reproduction periods according to a stable distribution. We give a method for simulating the establishment probabilities and approximations for the expected establishment probability. Furthermore, we show that, due to the stochasticity of the establishment success over different periods, the expected success of sequential invasions is larger then that of simultaneous invasions and we study the effects of environmental fluctuations on the extinction probability of small populations and metapopulations. The results can easily be generalized to other offspring distributions than the Poisson.     

A Stochastic Model for Detecting Overlapping and Hierarchical Community Structure

Community detection is a fundamental problem in the analysis of complex networks. Recently, many researchers have concentrated on the detection of overlapping communities, where a vertex may belong to more than one community. However, most current methods require the number (or the size) of the communities as a priori information, which is usually unavailable in real-world networks. Thus, a practical algorithm should not only find the overlapping community structure, but also automatically determine the number of communities. Furthermore, it is preferable if this method is able to reveal the hierarchical structure of networks as well. In this work, we firstly propose a generative model that employs a nonnegative matrix factorization (NMF) formulization with a l_2,1 norm regularization term, balanced by a resolution parameter. The NMF has the nature that provides overlapping community structure by assigning soft membership variables to each vertex; the l_2,1 regularization term is a technique of group sparsity which can automatically determine the number of communities by penalizing too many nonempty communities; and hence the resolution parameter enables us to explore the hierarchical structure of networks. Thereafter, we derive the multiplicative update rule to learn the model parameters, and offer the proof of its correctness. Finally, we test our approach on a variety of synthetic and real-world networks, and compare it with some state-of-the-art algorithms. The results validate the superior performance of our new method.     

Uncoupled Analysis of Stochastic Reaction Networks in Fluctuating Environments

The dynamics of stochastic reaction networks within cells are inevitably modulated by factors considered extrinsic to the network such as, for instance, the fluctuations in ribosome copy numbers for a gene regulatory network. While several recent studies demonstrate the importance of accounting for such extrinsic components, the resulting models are typically hard to analyze. In this work we develop a general mathematical framework that allows to uncouple the network from its dynamic environment by incorporating only the environment''s effect onto the network into a new model. More technically, we show how such fluctuating extrinsic components (e.g., chemical species) can be marginalized in order to obtain this decoupled model. We derive its corresponding process- and master equations and show how stochastic simulations can be performed. Using several case studies, we demonstrate the significance of the approach.     

Memory and Fitness Optimization of Bacteria under Fluctuating Environments

Bacteria prudently regulate their metabolic phenotypes by sensing the availability of specific nutrients, expressing the required genes for their metabolism, and repressing them after specific metabolites are depleted. It is unclear, however, how genetic networks maintain and transmit phenotypic states between generations under rapidly fluctuating environments. By subjecting bacteria to fluctuating carbon sources (glucose and lactose) using microfluidics, we discover two types of non-genetic memory in Escherichia coli and analyze their benefits. First, phenotypic memory conferred by transmission of stable intracellular lac proteins dramatically reduces lag phases under cyclical fluctuations with intermediate timescales (1–10 generations). Second, response memory, a hysteretic behavior in which gene expression persists after removal of its external inducer, enhances adaptation when environments fluctuate over short timescales (<1 generation). Using a mathematical model we analyze the benefits of memory across environmental fluctuation timescales. We show that memory mechanisms provide an important class of survival strategies in biology that improve long-term fitness under fluctuating environments. These results can be used to understand how organisms adapt to fluctuating levels of nutrients, antibiotics, and other environmental stresses.     

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.     

Temperature-Correlated Changes in Phytoplankton Community Structure Are Restricted to Polar Waters

Globally distributed observations of size-fractionated chlorophyll a and temperature were used to incorporate temperature dependence into an existing semi-empirical model of phytoplankton community size structure. The additional temperature-dependent term significantly increased the model’s ability to both reproduce and predict observations of chlorophyll a size-fractionation at temperatures below 2°C. The most notable improvements were in the smallest (picoplankton) size-class, for which overall model fit was more than doubled, and predictive skill was increased by approximately 40%. The model was subsequently applied to generate global maps for three phytoplankton size classes, on the basis of satellite-derived estimates of surface chlorophyll a and sea surface temperature. Polar waters were associated with marked decline in the chlorophyll a biomass of the smallest cells, relative to lower latitude waters of equivalent total chlorophyll a. In the same regions a complementary increase was seen in the chlorophyll a biomass of larger size classes. These findings suggest that a warming and stratifying ocean will see a poleward expansion of the habitat range of the smallest phytoplankton, with the possible displacement of some larger groups that currently dominate. There was no evidence of a strong temperature dependence in tropical or sub-tropical regions, suggesting that future direct temperature effects on community structure at lower latitudes may be small.     

热带调水水库春季浮游植物群落的结构与动态

于2005年1-6月,对南亚热带调水水库—大镜山水库的水文、营养盐(N、P)和浮游植物进行了调查研究。共检测到浮游植物76种;浮游植物总的细胞数量在4.925×106-63.65×106cellsL-1之间,浮游植物的总生物量在1.632-20.420mgL-1之间。假鱼腥藻(Pseudanabaena sp.)是主要优势藻,但是早春(1-3月)假鱼腥藻和肘状针杆藻(Synedraulna)共同成为优势藻。浮游植物细胞的丰度晚春(4-6月)比早春的要高,但是生物量却比早春的低。在水文过程与其它水库有一定差别的典型调水水库,水温是引起浮游植物种类组成变化的主要原因。浮游植物组成与动态是受入库营养盐和水动力学的变化所影响的。     

The Evolution of Canalization and Evolvability in Stable and Fluctuating Environments

Using a multilinear model of epistasis we explore the evolution of canalization (reduced mutational effects) and evolvability (levels of additive genetic variance) under different forms of stabilizing and fluctuating selection. We show that the total selection acting on an allele can be divided into a component deriving from adaptation of the trait mean, a component of canalizing selection favoring alleles that epistatically reduce the effects of other allele substitutions, and a component of conservative selection disfavoring rare alleles. While canalizing selection operates in both stable and fluctuating environments, it may not typically maximize canalization, because it gets less efficient with increasing canalization, and reaches a balance with drift, mutation and indirect selection. Fluctuating selection leads to less canalized equilibria than stabilizing selection of comparable strength, because canalization then becomes influenced by erratic correlated responses to shifting trait adaptation. We conclude that epistatic systems under bounded fluctuating selection will become less canalized than under stabilizing selection and may support moderately increased evolvability if the amplitude of fluctuations is large, but canalization is still stronger and evolvability lower than expected under neutral evolution or under patterns of selection that shift the trait in directions of positive (reinforcing) epistasis.     

三江平原湿地同江地区水域夏季浮游植物群落结构特征

2012年6月对三江平原湿地同江地区水域浮游植物群落结构进行了初步研究。设置了13个采样点,生境类型包括大型开阔水体、小型封闭水体、湿地型水体以及河流型水体。结果在该水域发现浮游植物共计312个分类单位,包括276种33变种3变型,隶属于8门10纲21目36科92属。浮游植物细胞密度变化范围为2.68×104–2.53×106 cells·L–1。大型开阔水体种类丰富,细胞密度最大,以绿藻为优势种群;小型封闭水体中藻类的适应性强,群落结构最为复杂;湿地型水体受人为活动影响较大,发现了一些耐有机污染的种类;在河流型水体中,有一些适低温的隐藻出现并成为优势种,如啮蚀隐藻(Cryptomonas erosa)等。此外,在三江平原湿地同江地区还发现了大量β-中污染指示种类。经聚类和多维尺度分析,将不同采样点各生境水体的浮游植物群落分为4组。综合多样性指数表明,同江地区水域浮游植物群落结构较丰富且稳定性较好。     

粤西海域浮游植物群落结构特征的多元分析与评价

根据1998-1999年对粤西海域浮游植物的周年调查资料,本文采用主成分分析和聚类分析等多元统计分析方法研究该海域浮游植物的主要种类组成和群落结构的基本特征。研究结果表明,中肋骨条藻（Skeletonema costatum）、伏氏海毛藻（Thalassiothrix fauenfeldii）、小舟形藻（Navicula subminuscula）、颤藻（Oscillatoria sp．）、菱形海线藻（Thalassionema nitzschioides）、细弱海链藻（Thalassiosira subtilis）、齿角毛藻（Chaetoceros denticulatus）、北方劳德藻（Lauderia borealis）、中华盒形藻（Biddulphia sinensis）、纺锤角藻（Ceratium fusus）、翼根管藻（Rhizosolenia alata）、斯氏根管藻（Rhizosolenia stolterforthii）、短角弯角藻（Eucampia zoodiacu）、笔尖形根管藻（Rhizosolenia styliformis）、拟弯角毛藻（Chaetoceros pseudocurvisetus）等种类构成了粤西海域浮游植物的主体。春季、夏季和秋季该海域浮游植物可明显划分为近岸类群和近外海类群2个群落,冬季群落结构分化不显著,不形成明显的类群。各主要种类的季节演替现象十分明显。     

黄浦江浮游植物群落结构及其对水环境的指示作用

2004年4月至2005年2月共6次对黄浦江的浮游植物进行了调查,共设5个采样点。每2个月在各样点进行定性、定量采集浮游植物,同时测定了水体部分理化指标。采用生物指示法、香农(Shannon-Wiener)多样性指数法和Margalef多样性指数法等对水质进行了评价。结果表明,黄浦江在夏季为V类水,其它时期为IV类;所受的有机污染较为严重,属于中度-乙型(β-中污)阶段。其指示浮游植物为颗粒直链藻(Melosira granulata)及其变种和四尾栅藻(Scenedesmus quadricauda (Turp.) Br啨b.)等。     

2006年春夏期间浙江南麂海域浮游植物群落结构特征

研究了2006年春夏期间(4~6月)浙江省南麂列岛海域的浮游植物群落结构,共观察到68种浮游植物,其中硅藻53种,甲藻13种,金藻和蓝藻各1种。调查期间,该海域浮游植物群落结构变化明显,原甲藻赤潮的形成和持续是最显著的特征,三角棘原甲藻和东海原甲藻分别在5月中、下旬先后引发赤潮。原甲藻赤潮的形成与水温有密切关系,其生消引起海水中营养盐结构的相应变化。     

大庆新华湖藻类植物群落结构与环境因子的相关性

2014年5-10月对大庆新华湖藻类植物群落结构与环境因子的关系进行了初步研究, 为湖泊状况的动态监测提供基本数据。调查期间, 共发现藻类植物135种, 隶属5门63属, 其中硅藻门56种, 绿藻门49种, 蓝藻门15种, 裸藻门12种, 甲藻门3种。新华湖优势种共24种, 包括绿藻门14种, 蓝藻门6种, 硅藻门3种, 裸藻门1种, 且季节更替明显, 可以初步推断新华湖藻类植物群落组成为绿藻-硅藻型。新华湖藻类植物细胞丰度变化范围为37.57×10⁶-72.37×10⁶ cells·L^-1, 平均值为52.13×10⁶ cells·L^-1。多样性指数变化为: Simpson生态优势度指数(D)在0.642-0.928之间, Shannon-Weaver多样性指数(H')在1.698-3.1之间, Pielou均匀度指数(J)在0.324-0.561之间, 3种指数变化趋势一致, 均在秋季最高, 春季最低。研究表明, 水温、pH值、总磷、生化需氧量、溶解氧和水动力是影响新华湖藻类植物群落结构的主要因子。     

Fluctuating Environments Maintain Genetic Diversity through Neutral Fitness Effects and Balancing Selection

Genetic variation is the raw material upon which selection acts. The majority of environmental conditions change over time and therefore may result in variable selective effects. How temporally fluctuating environments impact the distribution of fitness effects and in turn population diversity is an unresolved question in evolutionary biology. Here, we employed continuous culturing using chemostats to establish environments that switch periodically between different nutrient limitations and compared the dynamics of selection to static conditions. We used the pooled Saccharomyces cerevisiae haploid gene deletion collection as a synthetic model for populations comprising thousands of unique genotypes. Using barcode sequencing, we find that static environments are uniquely characterized by a small number of high-fitness genotypes that rapidly dominate the population leading to dramatic decreases in genetic diversity. By contrast, fluctuating environments are enriched in genotypes with neutral fitness effects and an absence of extreme fitness genotypes contributing to the maintenance of genetic diversity. We also identified a unique class of genotypes whose frequencies oscillate sinusoidally with a period matching the environmental fluctuation. Oscillatory behavior corresponds to large differences in short-term fitness that are not observed across long timescales pointing to the importance of balancing selection in maintaining genetic diversity in fluctuating environments. Our results are consistent with a high degree of environmental specificity in the distribution of fitness effects and the combined effects of reduced and balancing selection in maintaining genetic diversity in the presence of variable selection.     

Phytoplankton Biogeography and Community Stability in the Ocean

Background

Despite enormous environmental variability linked to glacial/interglacial climates of the Pleistocene, we have recently shown that marine diatom communities evolved slowly through gradual changes over the past 1.5 million years. Identifying the causes of this ecological stability is key for understanding the mechanisms that control the tempo and mode of community evolution.

Methodology/Principal Findings

If community assembly were controlled by local environmental selection rather than dispersal, environmental perturbations would change community composition, yet, this could revert once environmental conditions returned to previous-like states. We analyzed phytoplankton community composition across >10⁴ km latitudinal transects in the Atlantic Ocean and show that local environmental selection of broadly dispersed species primarily controls community structure. Consistent with these results, three independent fossil records of marine diatoms over the past 250,000 years show cycles of community departure and recovery tightly synchronized with the temporal variations in Earth''s climate.

Conclusions/Significance

Changes in habitat conditions dramatically alter community structure, yet, we conclude that the high dispersal of marine planktonic microbes erases the legacy of past environmental conditions, thereby decreasing the tempo of community evolution.