Herbivory in the tilapia Oreochromis niloticus: a comparison of feeding rates on phytoplankton and periphyton

A quantitative comparison of the grazing behaviour of young Oreochromis niloticus feeding on the planktonic cyanobacterium Microcystis aeruginosa and a periphytic community dominated by the cyanobacterium Oscillatoria sp., determined that biomass ingestion rates of fish filter-feeding on planktonic cyanobacteria were significantly lower than those surface-grazing on periphyton. Comparisons of published laboratory data on filter-feeding with field data on algal ingestion rates suggest that filter-feeding may be a relatively unimportant method of ingesting algae.     

Emergence of Holling type III zooplankton functional response: Bringing together field evidence and mathematical modelling

Food-web population models are rather sensitive to parameterization of functional response in predation terms. Theoretical studies predict enhancing of ecosystems’ stability for a functional response of sigmoid type (Holling type III). The choice of a correct type of response is especially important for modelling outcome of grazing control of algal blooms by zooplankton in nutrient-rich ecosystems. Extensive experiments on zooplankton feeding in laboratories show non-sigmoid nature of response for most herbivorous zooplankton species. As a consequence, there is a strong opinion in literature that the implementation of Holling III type grazing in plankton models is biologically meaningless. I argue, however, that such an ‘evident’ claim might be wrong and sigmoid functional responses in real plankton communities would emerge more often than was suggested earlier. Especially, this concerns plankton models without vertical resolution, which ignore heterogeneity in vertical distribution of species. Having conducted extensive literature search of data on zooplankton feeding in situ, I show that vertical heterogeneity in food distribution as well as active food searching behaviour of zooplankton can modify the type of functional response. In particular, the rate of food intake by the whole zooplankton population in the column, as a function of total amount of food, often exhibits a sigmoid behaviour, instead of a non-sigmoid one postulated previously based on laboratory experiments. This conceptual discrepancy is due to the ability of zooplankton to feed mostly in layers with high algal density. I propose a generic model explaining the observed alteration of type between overall and local functional responses. I show that emergence of Holling type III in plankton systems is due to mechanisms different from those well known in the ecological literature (e.g. food search learning, existence of alternative food, refuge for prey).     

Carbon steady-state model of the planktonic food web of Lake Biwa, Japan

1. A steady‐state model of carbon flows was developed to describe the summer planktonic food web in the surface mixed‐layer of the North Basin in Lake Biwa, Japan. This model synthesised results from numerous studies on the plankton of Lake Biwa. 2. An inverse analysis procedure was used to estimate missing flow values in a manner consistent with known information. Network analysis was applied to characterise emergent properties of the resulting food web. 3. The system strongly relied on flows related to detrital particles. Whereas primary production was mainly by phytoplankton >20 μm, microzooplankton were active and mainly ingested detritus and bacteria. 4. The main emergent property of the system was strong recycling, through either direct ingestion of non‐living material by zooplankton, or ingestion of bacteria after degradation of detritus to release dissolved organic carbon.     

Micro‐scale structure in the chemistry and biology of a shallow lake

1. Repeat sampling in daytime within a lily (Nuphar lutea) bed and in open water showed distinct heterogeneities in the three‐dimensional distributions of water chemistry and planktonic organisms on centimetre to decimetre scales. 2. Vertical gradients of physico‐chemical variables that did not exist at dawn developed during the day in both sites, as available nutrients were released from the sediments and were consumed towards the surface. 3. Distributions of algal standing crop suggest limitation by both nutrients and grazing. 4. Marked variability in distributions may question the assumptions often made about the homogeneity of plankton and available nutrient distributions in open water and in macrophyte stands of shallow lakes. Although simple sampling regimes for monitoring of water quality may be adequate for many purposes, they miss a fine structure in the water that is inherently interesting in understanding the underlying processes of plankton function.     

Toxin-producing plankton may act as a biological control for planktonic blooms--field study and mathematical modelling

Termination of planktonic blooms is of great importance to human health, ecosystem, environment, tourism and fisheries. Toxic substances released by plankton play an important role in this context. The effect of toxin-producing plankton (TPP) on zooplankton is observed from the field-collected samples and mathematical modelling. Information from both the studies led us to suggest that TPP may terminate the planktonic blooms by decreasing the grazing pressure of zooplankton and thus acts as a biological control.     

Microbial Exopolymers Link Predator and Prey in a Model Yeast Biofilm System

Protistan grazing on biofilms is potentially an important conduit enabling energy flow between microbial trophic levels. Contrary to the widely held assumption that protistan feeding primarily involves ingestion of biofilm cells, with negative consequences for the biofilm, this study demonstrated preferential grazing on the noncellular biofilm matrix by a ciliate, with selective ingestion of yeast and bacterial cells of planktonic origin over attached and biofilm-derived planktonic cells. Introducing a ciliate to two biofilm-forming Cryptococcus species, as well as two bacterial species in a model biofilm system, fluorescent probes were applied to determine ingestion of cellular and noncellular biofilm fractions. Fluoromicroscopy, as well as photometric quantification, confirmed that protistan grazing enhanced yeast biofilm metabolism, and an increase in biofilm biomass and viability. We propose that the extracellular polymeric matrix of biofilms may act as an interface regulating interaction between predator and prey, while serving as source of nutrients and energy for protists.     

The metabolism of lake plankton does not support the metabolic theory of ecology

We tested if the metabolic theory of ecology (MTE) correctly predicts plankton metabolism in a temperate lake, based on a long-term (about 15 years), high-frequency dataset of body size, abundance and production, using two different techniques: least squares regression and maximum likelihood. For phytoplankton, the general fit was relatively poor (r²=0.53). The assumption of the MTE on temperature dependence of metabolism was not supported, and the assumed value of ¾ of the allometric exponent was barely within 95% confidence limits. For some of the models, the value of b was significantly higher than ¾. When radiation was included as an additional predictor, it improved the model considerably (r²=0.67). Including grazing by zooplankton reduced the model residuals during the summer period, when grazing is a dominant factor. The allometric exponent had virtually no effect for phytoplankton, due to little variability in average individual size. Zooplankton production, on the other hand, was better predicted by MTE, showing stronger effects of temperature and body size, the average of which varied by a factor of more than a hundred. However, the best-fitting value of the allometric exponent for zooplankton was 0.85, and significantly higher than the ¾ predicted by the theory. The ratio of observed production to biomass for the entire plankton community declined linearly with the body size (in log-log) with a slope corresponding to a value of b=0.85. We conclude that the MTE has little predictive power for the metabolism of lacustrine plankton, in particular for phytoplankton, and especially at the scale of variability of this study, and that this could be improved by incorporating radiation into the model.     

A Bayesian model averaging approach for estimating the relative risk of mortality associated with heat waves in 105 U.S. cities

Estimating the risks heat waves pose to human health is a critical part of assessing the future impact of climate change. In this article, we propose a flexible class of time series models to estimate the relative risk of mortality associated with heat waves and conduct Bayesian model averaging (BMA) to account for the multiplicity of potential models. Applying these methods to data from 105 U.S. cities for the period 1987-2005, we identify those cities having a high posterior probability of increased mortality risk during heat waves, examine the heterogeneity of the posterior distributions of mortality risk across cities, assess sensitivity of the results to the selection of prior distributions, and compare our BMA results to a model selection approach. Our results show that no single model best predicts risk across the majority of cities, and that for some cities heat-wave risk estimation is sensitive to model choice. Although model averaging leads to posterior distributions with increased variance as compared to statistical inference conditional on a model obtained through model selection, we find that the posterior mean of heat wave mortality risk is robust to accounting for model uncertainty over a broad class of models.     

Inherent high correlation of individual motility enhances population dispersal in a heterotrophic, planktonic protist

Quantitative linkages between individual organism movements and the resulting population distributions are fundamental to understanding a wide range of ecological processes, including rates of reproduction, consumption, and mortality, as well as the spread of diseases and invasions. Typically, quantitative data are collected on either movement behaviors or population distributions, rarely both. This study combines empirical observations and model simulations to gain a mechanistic understanding and predictive ability of the linkages between both individual movement behaviors and population distributions of a single-celled planktonic herbivore. In the laboratory, microscopic 3D movements and macroscopic population distributions were simultaneously quantified in a 1L tank, using automated video- and image-analysis routines. The vertical velocity component of cell movements was extracted from the empirical data and used to motivate a series of correlated random walk models that predicted population distributions. Validation of the model predictions with empirical data was essential to distinguish amongst a number of theoretically plausible model formulations. All model predictions captured the essence of the population redistribution (mean upward drift) but only models assuming long correlation times (minute), captured the variance in population distribution. Models assuming correlation times of 8 minutes predicted the least deviation from the empirical observations. Autocorrelation analysis of the empirical data failed to identify a de-correlation time in the up to 30-second-long swimming trajectories. These minute-scale estimates are considerably greater than previous estimates of second-scale correlation times. Considerable cell-to-cell variation and behavioral heterogeneity were critical to these results. Strongly correlated random walkers were predicted to have significantly greater dispersal distances and more rapid encounters with remote targets (e.g. resource patches, predators) than weakly correlated random walkers. The tendency to disperse rapidly in the absence of aggregative stimuli has important ramifications for the ecology and biogeography of planktonic organisms that perform this kind of random walk.     

A Delay-Diffusion Model of Marine Plankton Ecosystem Exhibiting Cyclic Nature of Blooms

The cyclic nature of blooms is a very interesting characteristic of marine plankton ecosystem. Release of toxins by some phytoplanktons has an important role on planktonic interactions and hence on regulating the blooms. A mathematical model describing the phytoplankton-zooplankton interaction with these characteristics is studied. The time needed for liberation of toxins by phytoplanktons is considered. To account for the spatial heterogeneity of an aquatic environment, diffusivity of different plankton populations is also incorporated into the system. Stability and bifurcation behaviour of different steady states are analysed.     

Spatial Interaction Among Nontoxic Phytoplankton, Toxic Phytoplankton, and Zooplankton: Emergence in Space and Time

In homogeneous environments, by overturning the possibility of competitive exclusion among phytoplankton species, and by regulating the dynamics of overall plankton population, toxin-producing phytoplankton (TPP) potentially help in maintaining plankton diversity—a result shown recently. Here, I explore the competitive effects of TPP on phytoplankton and zooplankton species undergoing spatial movements in the subsurface water. The spatial interactions among the species are represented in the form of reaction-diffusion equations. Suitable parametric conditions under which Turing patterns may or may not evolve are investigated. Spatiotemporal distributions of species biomass are simulated using the diffusivity assumptions realistic for natural planktonic systems. The study demonstrates that spatial movements of planktonic systems in the presence of TPP generate and maintain inhomogeneous biomass distribution of competing phytoplankton, as well as grazer zooplankton, thereby ensuring the persistence of multiple species in space and time. The overall results may potentially explain the sustainability of biodiversity and the spatiotemporal emergence of phytoplankton and zooplankton species under the influence of TPP combined with their physical movement in the subsurface water.     

The importance of size-frequency relationships for predicting ecological impact of zebra mussel populations

Although most physiological processes of bivalves are highly size-dependent in a non-linear manner, often only total densities of populations of freshwater bivalves such as the zebra mussel are reported rather than size-frequency information. This can cause serious errors when trying to predict or assess the environmental impacts of these filter feeders on planktonic communities or the role of their pseudofeces in transferring materials from the plankton to the benthos. We used a bioenergetics model to examine the effect that differing size-frequency distribution has on influencing total phytoplankton consumption and pseudofeces production. We constructed different size-frequency distributions of 1000 zebra mussels with the same mean length or same mean body mass for comparison. In addition, we used several size-frequency distributions from the published literature. The size-frequency distribution of a population had a tremendous impact on both total consumption and pseudofeces production with rates varying by more than an order of magnitude (43.5 g consumption by 1000 smaller mussels to 654 g for a population dominated by large mussels). These data emphasize the importance of knowing not only population density, but population size structure in order to accurately understand and predict the impacts of zebra mussels, or any filter feeder on pelagic and benthic communities. This work also demonstrates the usefulness of a tool such as our bioenergetics model for partitioning the relative impacts of densities and size on a variety of factors such as consumption and pseudofeces production.     

Predation as a shaping force for the phenotypic and genotypic composition of planktonic bacteria

Predation is a major mortality factor of planktonic bacteria and an important shaping force for the phenotypic and taxonomic structure of bacterial communities. In this paper we: (1) summarise current knowledge on bacterial phenotypic properties which affect their vulnerability towards grazers, and (2) review experimental evidence demonstrating that this phenotypic heterogeneity results in shifts of bacterial community composition during enhanced protist grazing pressure. Size-structured interactions are especially important in planktonic systems and bacterial cell size influences the mortality rate and the type of grazer to which bacteria are most susceptible. When protists are the major bacterivores, both very small and large bacterial cells gain some size refuge. Recent studies have revealed that also various non-morphological traits such as motility, physicochemical surface characters and toxicity affect bacterial vulnerability and protist feeding success. These properties are effective at different stages during the feeding process of interception feeding flagellates (encounter, capture, ingestion, digestion). Grazing-resistant bacteria in natural communities can account for a substantial portion of the total bacterial biomass at least in more productive aquatic systems. In field and laboratory experiments it has been demonstrated that increased protozoan grazing results in shifts in the phenotypic and genotypic composition of the bacterial assemblage. The importance of this shaping force for the bacterial community structure depends, however, on the overall food web structure, especially on the composition of the metazooplankton. Whereas the structuring impact of bacterial grazers is well documented, relatively little is known about how grazing-mediated changes in bacterial communities influence microbially mediated processes and biogeochemically important transformations. This revised version was published online in August 2006 with corrections to the Cover Date.     

The predictive skill of species distribution models for plankton in a changing climate

Statistical species distribution models (SDMs) are increasingly used to project spatial relocations of marine taxa under future climate change scenarios. However, tests of their predictive skill in the real‐world are rare. Here, we use data from the Continuous Plankton Recorder program, one of the longest running and most extensive marine biological monitoring programs, to investigate the reliability of predicted plankton distributions. We apply three commonly used SDMs to 20 representative plankton species, including copepods, diatoms, and dinoflagellates, all found in the North Atlantic and adjacent seas. We fit the models to decadal subsets of the full (1958–2012) dataset, and then use them to predict both forward and backward in time, comparing the model predictions against the corresponding observations. The probability of correctly predicting presence was low, peaking at 0.5 for copepods, and model skill typically did not outperform a null model assuming distributions to be constant in time. The predicted prevalence increasingly differed from the observed prevalence for predictions with more distance in time from their training dataset. More detailed investigations based on four focal species revealed that strong spatial variations in skill exist, with the least skill at the edges of the distributions, where prevalence is lowest. Furthermore, the scores of traditional single‐value model performance metrics were contrasting and some implied overoptimistic conclusions about model skill. Plankton may be particularly challenging to model, due to its short life span and the dispersive effects of constant water movements on all spatial scales, however there are few other studies against which to compare these results. We conclude that rigorous model validation, including comparison against null models, is essential to assess the robustness of projections of marine planktonic species under climate change.     

Use of ciliate and phytoplankton taxonomic composition for the estimation of eicosapentaenoic acid concentration in lakes

1. The polyunsaturated fatty acid eicosapentaenoic acid (EPA) plays an important role in aquatic food webs, in particular at the primary producer–consumer interface where keystone species such as daphnids may be constrained by its dietary availability. Such constraints and their seasonal and interannual changes may be detected by continuous measurements of EPA concentrations. However, such EPA measurements became common only during the last two decades, whereas long‐term data sets on plankton biomass are available for many well‐studied lakes. Here, we test whether it is possible to estimate EPA concentrations from abiotic variables (light and temperature) and the biomass of prey organisms (e.g. ciliates, diatoms and cryptophytes) that potentially provide EPA for consumers. 2. We used multiple linear regression to relate size‐ and taxonomically resolved plankton biomass data and measurements of temperature and light intensity to directly measured EPA concentrations in Lake Constance during a whole year. First, we tested the predictability of EPA concentrations from the biomass of EPA‐rich organisms (diatoms, cryptophytes and ciliates). Secondly, we included the variables mean temperature and mean light intensity over the sampling depth (0–20 m) and depth (0–8 and 8–20 m) as factors in our model to check for large‐scale seasonal‐ and depth‐dependent effects on EPA concentrations. In a third step, we included the deviations of light and temperature from mean values in our model to allow for their potential influence on the biochemical composition of plankton organisms. We used the Akaike Information Criterion to determine the best models. 3. All approaches supported our proposition that the biomasses of specific plankton groups are variables from which seston EPA concentrations can be derived. The importance of ciliates as an EPA source in the seston was emphasised by their high weight in our models, although ciliates are neglected in most studies that link fatty acids to seston taxonomic composition. The large‐scale seasonal variability of light intensity and its interaction with diatom biomass were significant predictors of EPA concentrations. The deviation of temperature from mean values, accounting for a depth‐dependent effect on EPA concentrations, and its interaction with ciliate biomass were also variables with high predictive power. 4. The best models from the first and second approaches were validated with measurements of EPA concentrations from another year (1997). The estimation with the best model including only biomass explained 80%, and the best model from the second approach including mean temperature and depth explained 87% of the variability in EPA concentrations in 1997. 5. We show that it is possible to predict EPA concentrations reliably from plankton biomass, while the inclusion of abiotic factors led to results that were only partly consistent with expectations from laboratory studies. Our approach of including biotic predictors should be transferable to other systems and allow checking for biochemical constraints on primary consumers.     

Assimilation of Diazotrophic Nitrogen into Pelagic Food Webs

The fate of diazotrophic nitrogen (N_D) fixed by planktonic cyanobacteria in pelagic food webs remains unresolved, particularly for toxic cyanophytes that are selectively avoided by most herbivorous zooplankton. Current theory suggests that N_D fixed during cyanobacterial blooms can enter planktonic food webs contemporaneously with peak bloom biomass via direct grazing of zooplankton on cyanobacteria or via the uptake of bioavailable N_D (exuded from viable cyanobacterial cells) by palatable phytoplankton or microbial consortia. Alternatively, N_D can enter planktonic food webs post-bloom following the remineralization of bloom detritus. Although the relative contribution of these processes to planktonic nutrient cycles is unknown, we hypothesized that assimilation of bioavailable N_D (e.g., nitrate, ammonium) by palatable phytoplankton and subsequent grazing by zooplankton (either during or after the cyanobacterial bloom) would be the primary pathway by which N_D was incorporated into the planktonic food web. Instead, in situ stable isotope measurements and grazing experiments clearly documented that the assimilation of N_D by zooplankton outpaced assimilation by palatable phytoplankton during a bloom of toxic Nodularia spumigena Mertens. We identified two distinct temporal phases in the trophic transfer of N_D from N. spumigena to the plankton community. The first phase was a highly dynamic transfer of N_D to zooplankton with rates that covaried with bloom biomass while bypassing other phytoplankton taxa; a trophic transfer that we infer was routed through bloom-associated bacteria. The second phase was a slowly accelerating assimilation of the dissolved-N_D pool by phytoplankton that was decoupled from contemporaneous variability in N. spumigena concentrations. These findings provide empirical evidence that N_D can be assimilated and transferred rapidly throughout natural plankton communities and yield insights into the specific processes underlying the propagation of N_D through pelagic food webs.     

Single-cell behavior and population heterogeneity: solving an inverse problem to compute the intrinsic physiological state functions

The dynamics of isogenic cell populations can be described by cell population balance models that account for phenotypic heterogeneity. To utilize the predictive power of these models, however, we must know the rates of single-cell reaction and division and the bivariate partition probability density function. These three intrinsic physiological state (IPS) functions can be obtained by solving an inverse problem that requires knowledge of the phenotypic distributions for the overall cell population, the dividing cell subpopulation and the newborn cell subpopulation. We present here a robust computational procedure that can accurately estimate the IPS functions for heterogeneous cell populations. A detailed parametric analysis shows how the accuracy of the inverse solution is affected by discretization parameters, the type of non-parametric estimators used, the qualitative characteristics of phenotypic distributions and the unknown partitioning probability density function. The effect of finite sampling and measurement errors on the accuracy of the recovered IPS functions is also assessed. Finally, we apply the procedure to estimate the IPS functions of an E. coli population carrying an IPTG-inducible genetic toggle network. This study completes the development of an integrated experimental and computational framework that can become a powerful tool for quantifying single-cell behavior using measurements from heterogeneous cell populations.     

Influence of Environmental Heterogeneity on the Structure of Testate Amoebae (Protozoa,Rhizopoda) Assemblages in the Plankton of the Upper Paraná River Floodplain,Brazil

In freshwater environments, testate amoebae are usually found associated with macrophytes and sediments and many studies have suggested that their occurrence in plankton samples is accidental. This implies that predictable patterns detected in planktonic assemblages should not be observed in testate amoebae assemblages. This hypothesis was tested in this study. Plankton samples were collected from different environments in the Upper Paraná River floodplain. Results show that patterns in species composition and abundance of testate amoebae are predictable, and that dominant species tend to present characteristic shell morphology in hydrologically different environments. We suggest that testate amoebae must be routinely included in plankton ecology studies, at least in floodplain environments.     

Measuring and modelling nitrogen leaching: parallel problems

In studies of nitrate leaching both experimenters and modellers experience problems arising from soil variability. Because of the small-scale heterogeneity that gives rise to mobile and immobile categories of water, both measurements and modelling are easiest in homogeneous sandy soils and most difficult in strongly structured clay soils. There are also parallels at plot and field scale in the problems caused to experimenters by log-normal distributions of nitrate concentrations and those caused to modellers by non-linearity in models. All researchers need to be aware that a reliable estimate of the mean from a set of measurements or a model may necessitate considerations of variances as well as means.