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Allometric trophic network (ATN) models offer high flexibility and scalability while minimizing the number of parameters and have been successfully applied to investigate complex food web dynamics and their influence on food web diversity and stability. However, the realism of ATN model energetics has never been assessed in detail, despite their critical influence on dynamic biomass and production patterns. Here, we compare the energetics of the currently established original ATN model, considering only biomass-dependent basal respiration, to an extended ATN model version, considering both basal and assimilation-dependent activity respiration. The latter is crucial in particular for unicellular and invertebrate organisms which dominate the metabolism of pelagic and soil food webs. Based on metabolic scaling laws, we show that the extended ATN version reflects the energy transfer through a chain of four trophic levels of unicellular and invertebrate organisms more realistically than the original ATN version. Depending on the strength of top-down control, the original ATN model yields trophic transfer efficiencies up to 71% at either the third or the fourth trophic level, which considerably exceeds any realistic values. In contrast, the extended ATN version yields realistic trophic transfer efficiencies 30% at all trophic levels, in accordance with both physiological considerations and empirical evidence from pelagic systems. Our results imply that accounting for activity respiration is essential for consistently implementing the metabolic theory of ecology in ATN models and for improving their quantitative predictions, which makes them more powerful tools for investigating the dynamics of complex natural communities.
Parasites, such as bacterial viruses (phages), can have large effects on host populations both at the ecological and evolutionary levels. In the case of cyanobacteria, phages can reduce primary production and infected hosts release intracellular nutrients influencing planktonic food web structure, community dynamics, and biogeochemical cycles. Cyanophages may be of great importance in aquatic food webs during large cyanobacterial blooms unless the host population becomes resistant to phage infection. The consequences on plankton community dynamics of the evolution of phage resistance in bloom forming cyanobacterial populations are still poorly studied. Here, we examined the effect of different frequencies of a phage-resistant genotype within a filamentous nitrogen-fixing Nodularia spumigena population on an experimental plankton community. Three Nodularia populations with different initial frequencies (0%, 5%, and 50%) of phage-resistant genotypes were inoculated in separate treatments with the phage 2AV2, the green alga Chlorella vulgaris, and the rotifer Brachionus plicatilis, which formed the experimental plankton community subjected to either nitrogen-limited or nitrogen-rich conditions. We found that the frequency of the phage-resistant Nodularia genotype determined experimental community dynamics. Cyanobacterial populations with a high frequency (50%) of the phage-resistant genotype dominated the cultures despite the presence of phages, retaining most of the intracellular nitrogen in the plankton community. In contrast, populations with low frequencies (0% and 5%) of the phage-resistant genotype were lysed and reduced to extinction by the phage, transferring the intracellular nitrogen held by Nodularia to Chlorella and rotifers, and allowing Chlorella to dominate the communities and rotifers to survive. This study shows that even though phages represent minuscule biomass, they can have key effects on community composition and eco-evolutionary feedbacks in plankton communities.
Estimating parameters from multiple time series of population dynamics using bayesian inference
(2019)
Empirical time series of interacting entities, e.g., species abundances, are highly useful to study ecological mechanisms. Mathematical models are valuable tools to further elucidate those mechanisms and underlying processes. However, obtaining an agreement between model predictions and experimental observations remains a demanding task. As models always abstract from reality one parameter often summarizes several properties. Parameter measurements are performed in additional experiments independent of the ones delivering the time series. Transferring these parameter values to different settings may result in incorrect parametrizations. On top of that, the properties of organisms and thus the respective parameter values may vary considerably. These issues limit the use of a priori model parametrizations. In this study, we present a method suited for a direct estimation of model parameters and their variability from experimental time series data. We combine numerical simulations of a continuous-time dynamical population model with Bayesian inference, using a hierarchical framework that allows for variability of individual parameters. The method is applied to a comprehensive set of time series from a laboratory predator-prey system that features both steady states and cyclic population dynamics. Our model predictions are able to reproduce both steady states and cyclic dynamics of the data. Additionally to the direct estimates of the parameter values, the Bayesian approach also provides their uncertainties. We found that fitting cyclic population dynamics, which contain more information on the process rates than steady states, yields more precise parameter estimates. We detected significant variability among parameters of different time series and identified the variation in the maximum growth rate of the prey as a source for the transition from steady states to cyclic dynamics. By lending more flexibility to the model, our approach facilitates parametrizations and shows more easily which patterns in time series can be explained also by simple models. Applying Bayesian inference and dynamical population models in conjunction may help to quantify the profound variability in organismal properties in nature.
The size structure of autotroph communities - the relative abundance of small vs. large individuals - shapes the functioning of ecosystems. Whether common mechanisms underpin the size structure of unicellular and multicellular autotrophs is, however, unknown. Using a global data compilation, we show that individual body masses in tree and phytoplankton communities follow power-law distributions and that the average exponents of these individual size distributions (ISD) differ. Phytoplankton communities are characterized by an average ISD exponent consistent with three-quarter-power scaling of metabolism with body mass and equivalence in energy use among mass classes. Tree communities deviate from this pattern in a manner consistent with equivalence in energy use among diameter size classes. Our findings suggest that whilst universal metabolic constraints ultimately underlie the emergent size structure of autotroph communities, divergent aspects of body size (volumetric vs. linear dimensions) shape the ecological outcome of metabolic scaling in forest vs. pelagic ecosystems.
In ecological communities, especially the pelagic zones of aquatic ecosystems, certain bodysize ranges are often over-represented compared to others. Community size spectra, the distributions of community biomass over the logarithmic body-mass axis, tend to exhibit regularly spaced local maxima, called "domes", separated by steep troughs. Contrasting established theory, we explain these dome patterns as manifestations of top-down trophic cascades along aquatic food chains. Compiling high quality size-spectrum data and comparing these with a size-spectrum model introduced in this study, we test this theory and develop a detailed picture of the mechanisms by which bottom-up and top-down effects interact to generate dome patterns. Results imply that strong top-down trophic cascades are common in freshwater communities, much more than hitherto demonstrated, and may arise in nutrient rich marine systems as well. Transferring insights from the general theory of nonlinear pattern formation to domes patterns, we provide new interpretations of past lake-manipulation experiments.
The shape of trait distributions may inform about the selective forces that structure ecological communities. Here, we present a new moment-based approach to classify the shape of observed biomass-weighted trait distributions into normal, peaked, skewed, or bimodal that facilitates spatio-temporal and cross-system comparisons. Our observed phytoplankton trait distributions exhibited substantial variance and were mostly skewed or bimodal rather than normal. Additionally, mean, variance, skewness und kurtosis were strongly correlated. This is in conflict with trait-based aggregate models that often assume normally distributed trait values and small variances. Given these discrepancies between our data and general model assumptions we used the observed trait distributions to test how well different aggregate models with first- or second-order approximations and different types of moment closure predict the biomass, mean trait, and trait variance dynamics using weakly or moderately nonlinear fitness functions. For weakly non-linear fitness functions aggregate models with a second-order approximation and a data-based moment closure that relied on the observed correlations between skewness and mean, and kurtosis and variance predicted biomass and often also mean trait changes fairly well and better than models with first-order approximations or a normal-based moment closure. In contrast, none of the models reflected the changes of the trait variances reliably. Aggregate model performance was often also poor for moderately nonlinear fitness functions. This questions a general applicability of the normal-based approach, in particular for predicting variance dynamics determining the speed of trait changes and maintenance of biodiversity. We evaluate in detail how and why better approximations can be obtained.
Diverse communities can adjust their trait composition to altered environmental conditions, which may strongly influence their dynamics. Previous studies of trait-based models mainly considered only one or two trophic levels, whereas most natural system are at least tritrophic. Therefore, we investigated how the addition of trait variation to each trophic level influences population and community dynamics in a tritrophic model. Examining the phase relationships between species of adjacent trophic levels informs about the strength of top-down or bottom-up control in non-steadystate situations. Phase relationships within a trophic level highlight compensatory dynamical patterns between functionally different species, which are responsible for dampening the community temporal variability. Furthermore, even without trait variation, our tritrophic model always exhibits regions with two alternative states with either weak or strong nutrient exploitation, and correspondingly low or high biomass production at the top level. However, adding trait variation increased the basin of attraction of the high-production state, and decreased the likelihood of a critical transition from the high- to the lowproduction state with no apparent early warning signals. Hence, our study shows that trait variation enhances resource use efficiency, production, stability, and resilience of entire food webs.
Biological invasions are a major threat to natural biodiversity; hence, understanding the mechanisms underlying invasibility (i.e., the susceptibility of a community to invasions by new species) is crucial. Invasibility of a resident community may be affected by a complex but hitherto hardly understood interplay of (1) productivity of the habitat, (2) diversity, (3) herbivory, and (4) the characteristics of both invasive and resident species. Using experimental phytoplankton microcosms, we investigated the effect of nutrient supply and species diversity on the invasibility of resident communities for two functionally different invaders in the presence or absence of an herbivore. With increasing nutrient supply, increased herbivore abundance indicated enhanced phytoplankton biomass production, and the invasion success of both invaders showed a unimodal pattern. At low nutrient supply (i.e., low influence of herbivory), the invasibility depended mainly on the competitive abilities of the invaders, whereas at high nutrient supply, the susceptibility to herbivory dominated. This resulted in different optimum nutrient levels for invasion success of the two species due to their individual functional traits. To test the effect of diversity on invasibility, a species richness gradient was generated by random selection from a resident species pool at an intermediate nutrient level. Invasibility was not affected by species richness; instead, it was driven by the functional traits of the resident and/or invasive species mediated by herbivore density. Overall, herbivory was the driving factor for invasibility of phytoplankton communities, which implies that other factors affecting the intensity of herbivory (e.g., productivity or edibility of primary producers) indirectly influence invasions.
It is well known that functional diversity strongly affects ecosystem functioning. However, even in rather simple model communities consisting of only two or, at best, three trophic levels, the relationship between multitrophic functional diversity and ecosystem functioning appears difficult to generalize, because of its high contextuality. In this study, we considered several differently structured tritrophic food webs, in which the amount of functional diversity was varied independently on each trophic level. To achieve generalizable results, largely independent of parametrization, we examined the outcomes of 128,000 parameter combinations sampled from ecologically plausible intervals, with each tested for 200 randomly sampled initial conditions. Analysis of our data was done by training a random forest model. This method enables the identification of complex patterns in the data through partial dependence graphs, and the comparison of the relative influence of model parameters, including the degree of diversity, on food-web properties. We found that bottom-up and top-down effects cascade simultaneously throughout the food web, intimately linking the effects of functional diversity of any trophic level to the amount of diversity of other trophic levels, which may explain the difficulty in unifying results from previous studies. Strikingly, only with high diversity throughout the whole food web, different interactions synergize to ensure efficient exploitation of the available nutrients and efficient biomass transfer to higher trophic levels, ultimately leading to a high biomass and production on the top level. The temporal variation of biomass showed a more complex pattern with increasing multitrophic diversity: while the system initially became less variable, eventually the temporal variation rose again because of the increasingly complex dynamical patterns. Importantly, top predator diversity and food-web parameters affecting the top trophic level were of highest importance to determine the biomass and temporal variability of any trophic level. Overall, our study reveals that the mechanisms by which diversity influences ecosystem functioning are affected by every part of the food web, hampering the extrapolation of insights from simple monotrophic or bitrophic systems to complex natural food webs.
Trait-based approaches have broadened our understanding of how the composition of ecological communities responds to environmental drivers. This research has mainly focussed on abiotic factors and competition determining the community trait distribution, while effects of trophic interactions on trait dynamics, if considered at all, have been studied for two trophic levels at maximum. However, natural food webs are typically at least tritrophic. This enables indirect interactions of traits and biomasses among multiple trophic levels leading to underexplored effects on food web dynamics. Here, we demonstrate the occurrence of mutual trait adjustment among three trophic levels in a natural plankton food web (Lake Constance) and in a corresponding mathematical model. We found highly recurrent seasonal biomass and trait dynamics, where herbivorous zooplankton increased its size, and thus its ability to counter phytoplankton defense, before phytoplankton defense actually increased. This is contrary to predictions from bitrophic systems where counter-defense of the consumer is a reaction to prey defense. In contrast, counter-defense of carnivores by size adjustment followed the defense of herbivores as expected. By combining observations and model simulations, we show how the reversed trait dynamics at the two lower trophic levels result from a "trophic biomass-trait cascade" driven by the carnivores. Trait adjustment between two trophic levels can therefore be altered by biomass or trait changes of adjacent trophic levels. Hence, analyses of only pairwise trait adjustment can be misleading in natural food webs, while multitrophic trait-based approaches capture indirect biomass-trait interactions among multiple trophic levels.
Species can adjust their traits in response to selection which may strongly influence species coexistence. Nevertheless, current theory mainly assumes distinct and time-invariant trait values. We examined the combined effects of the range and the speed of trait adaptation on species coexistence using an innovative multispecies predator–prey model. It allows for temporal trait changes of all predator and prey species and thus simultaneous coadaptation within and among trophic levels. We show that very small or slow trait adaptation did not facilitate coexistence because the stabilizing niche differences were not sufficient to offset the fitness differences. In contrast, sufficiently large and fast trait adaptation jointly promoted stable or neutrally stable species coexistence. Continuous trait adjustments in response to selection enabled a temporally variable convergence and divergence of species traits; that is, species became temporally more similar (neutral theory) or dissimilar (niche theory) depending on the selection pressure, resulting over time in a balance between niche differences stabilizing coexistence and fitness differences promoting competitive exclusion. Furthermore, coadaptation allowed prey and predator species to cluster into different functional groups. This equalized the fitness of similar species while maintaining sufficient niche differences among functionally different species delaying or preventing competitive exclusion. In contrast to pre-
vious studies, the emergent feedback between biomass and trait dynamics enabled supersaturated coexistence for a broad range of potential trait adaptation and parameters. We conclude that accounting for trait adaptation may explain stable and supersaturated species coexistence for a broad range of environmental conditions in natural systems when the absence of such adaptive changes would preclude it. Small trait changes, coincident with those that may occur within many natural populations, greatly enlarged the number of coexisting species.
Species can adjust their traits in response to selection which may strongly influence species coexistence. Nevertheless, current theory mainly assumes distinct and time-invariant trait values. We examined the combined effects of the range and the speed of trait adaptation on species coexistence using an innovative multispecies predator–prey model. It allows for temporal trait changes of all predator and prey species and thus simultaneous coadaptation within and among trophic levels. We show that very small or slow trait adaptation did not facilitate coexistence because the stabilizing niche differences were not sufficient to offset the fitness differences. In contrast, sufficiently large and fast trait adaptation jointly promoted stable or neutrally stable species coexistence. Continuous trait adjustments in response to selection enabled a temporally variable convergence and divergence of species traits; that is, species became temporally more similar (neutral theory) or dissimilar (niche theory) depending on the selection pressure, resulting over time in a balance between niche differences stabilizing coexistence and fitness differences promoting competitive exclusion. Furthermore, coadaptation allowed prey and predator species to cluster into different functional groups. This equalized the fitness of similar species while maintaining sufficient niche differences among functionally different species delaying or preventing competitive exclusion. In contrast to previous studies, the emergent feedback between biomass and trait dynamics enabled supersaturated coexistence for a broad range of potential trait adaptation and parameters. We conclude that accounting for trait adaptation may explain stable and supersaturated species coexistence for a broad range of environmental conditions in natural systems when the absence of such adaptive changes would preclude it. Small trait changes, coincident with those that may occur within many natural populations, greatly enlarged the number of coexisting species.
Investigating the mechanisms which underlie the biomass fluctuations of populations and communities is important to better understand the processes which buffer community biomass in a variable environment. Based on long- term data of plankton biomass in Lake Constance (Bodensee), this study aims at explaining the different degree of synchrony among populations observed within two freshwater plankton groups, phytoplankton and ciliates. Established measures of temporal variability such as the variance ratio and cross-correlation coefficients were combined with first- order autoregressive models that allow estimating species interactions from time-series data. We found that predation was an important driver of the observed seasonal variability patterns in phytoplankton and ciliates, and that competitive interactions only played a subordinate role. In Lake Constance copepods and cladocerans, two major invertebrate predator groups, focus their grazing pressure at different times of the season. Model results suggested that compensatory dynamics detected in phytoplankton originate from the differential vulnerability of species to either one of these two predator groups. For ciliates model results advocated that synchrony among species occurs because ciliates tend to be vulnerable to both predator groups. Our findings underline the necessity of extending studies of community variability to multiple trophic levels because accounting for predator-prey interactions may often be more important than accounting for competitive interactions at one trophic level
Functional groups with diverse responses to environmental factors sum to produce communities with less temporal variability in their biomass than those lacking this diversity. The detection of these compensatory dynamics can be complicated by a spatio-temporal alternation in the environmental factors limiting growth (both abiotic and biotic), which restricts the occurrence of compensatory dynamics to certain periods or locations. Hence, resolving the spatio- temporal scale may uncover important spatial and/or temporal components in community variability. Using long-term data from Lake Constance (Bodensee), we find that a reduction in grazing pressure and relaxed competition for nutrients during winter and spring generates coherent dynamics among edible and less edible phytoplankton. During summer and fall, when both grazing pressure and nutrient limitation are present, edible and less edible phytoplankton exhibit compensatory dynamics. This study supports recent work suggesting that both abiotic and biotic interactions promote compensatory dynamics and to our knowledge, this is the first example of a system where compensatory and coherent dynamics seasonally alternate.
Inorganic carbon limitation and mixotrophic growth in Chlamydomonas from an acidic mining lake
(2005)
Plankton communities in acidic mining lakes (pH 2.5-3.3) are species-poor because they face extreme environmental conditions, e.g. 150 mg l(-1) Fe2++Fe3+. We investigated the growth characteristics of the dominant pigmented species, the flagellate Chlamydomonas acidophila, in semi-continuous culture experiments under in situ conditions. The following hypotheses were tested: (1) Low inorganic carbon (IC) concentrations in the epilimnion (e.g. 0.3 mg l(-1)) arising from the low pH limit phototrophic growth (H-1); (2) the additional use of dissolved organic carbon (mixotrophy) leads to higher growth rates under IC-limitation (H-2), and (3) phagotrophy is not relevant (H-3). H- 1 was supported as the culture experiments, in situ PAR and IC concentrations indicated that IC potentially limited phototrophic growth in the mixed surface layers. H-2 was also supported: mixotrophic growth always exceeded pure phototrophic growth even when photosynthesis was saturated. Dark growth in filtered lake water illuminated prior to inoculation provided evidence that Chlamydomonas was able to use the natural DOC. The alga did not grow on bacteria, thus confirming H-3. Chlamydomonas exhibited a remarkable resistance to starvation in the dark. The compensation light intensity (ca. 20 mu mol photons m(-2) s(-1)) and the maximum phototrophic growth (1.50 d(-1)) fell within the range of algae from non-acidic waters. Overall, Chlamydomonas, a typical r-strategist in circum-neutral systems, showed characteristics of a K-strategist in the stable, acidic lake environment in achieving moderate growth rates and minimizing metabolic losses. (c) 2005 Elsevier GmbH. All rights reserved
During 1987-1998, the ciliates and their prey and predator communities in large, deep, mesotrophic Lake Constance were intensively studied as it underwent re-oligotrophication. Ciliate biomass exhibited the bimodal seasonal distribution typical for meso-eutrophic lakes, with high biomass in spring and summer and low biomass in winter and during the clear-water phase. Cluster analysis produced nine groups of temporally co-occurring ciliate morphotypes with potentially similar ecological characteristics. The clusters exhibited a larger seasonality than found in the size distribution, showing that similarly-sized ciliates had seasonally compensatory dynamics. Ciliate biomass declined by approx. 30 % during the 12 years of study, i.e. considerably less than daphnids (and total phosphorus). This yielded a significant increase in the ratio between summer ciliate and daphnid biomass as re-oligotrophication progressed, in contrast to previous studies. Few indications for a mechanistic link between phosphorus concentrations (which declined threefold during the study period) and ciliate biomass or community composition via group-specific food concentrations were found. The relative contribution of three of the nine clusters changed as re-oligotrophication progressed. Ciliate size distribution was related to reoligotrophication and daphnid biomass in summer. The smallest and largest ciliates gained in importance when daphnids decreased whereas large ciliates declined. Overall, summer daphnid biomas had a greater predictive power for attributes of the ciliate community than the other factors studied (phosphorus, prey biomass, copepod biomass). The extent of bottom-up and top-down control of ciliates appeared to be time and group specific. Overall, the ciliate community exhibited remarkably recurrent seasonal patterns despite major alternations in abiotic and biotic conditions.
Biomass size spectra collate structural and functional attributes of plankton communities enabling standardised temporal and cross-system comparisons and may be rapidly obtained by automated particle counters. To examine how differences in plankton communities from highly eutrophic and more oligotrophic lakes are reflected in size spectra, a three-year time series of biomass size spectra was established for polymictic, eutrophic Lake Müggelsee, based on approximately weekly sampling and microscopic enumeration. The continuous but often bumpy size spectra reflected appropriately the seasonal and trophy-related variations in the plankton composition and growth conditions and the potential impact of daphnids on smaller plankton. We tested the hypothesis that more diverse plankton communities have smoother size spectra than impoverished ones. The spectra of L. Müggelsee and other more less eutrophic lakes covaried roughly with the functional diversity in total plankton composition but were unrelated to taxonomical diversity within the phyto- or mesozooplankton. The slopes of the normalised size spectra of Lake Müggelsee were generally more negative than -1, exhibited a recurrent seasonal pattern, and were strongly correlated with crustacean biomass. In contrast to less eutrophic systems, slopes could not be used to quantify energy fluxes within the foodweb due to highly variable algal P/B ratios and frequently bumpy size distributions. The latter indicated stronger deviations from the ideal concept of a steady energy flow along the size gradient than found in e. g. large, mesotrophic Lake Constance.
Clear-water phase (CWP) is an important event in seasonal plankton succession. We examined the influence of all herbivorous zooplankton on its initiation under different weather and climatic conditions using up to 19 years of observations from the large, deep Lake Constance (Europe) and estimates of relative clearance rates. A CWP occurred regularly, even if daphnid biomass was still very low. CWP was attributed to strong grazing either by a daphnid- dominated zooplankton community or by a diverse assemblage consisting of micro- and meso-zooplankton. Both types of zooplankton communities occurred with approximately the same frequency. The timing of the CWP was unrelated to the North Atlantic Oscillation (NAO) but correlated with the wind-dependent intensity of deep vertical mixing 3 months earlier, during early spring. Less mixing enabled early growth of phytoplankton, ciliates and rotifers despite low temperatures, which prevented daphnid development at this time. This resulted in enhanced grazing of ciliates and rotifers, which increased the importance of phytoplankton less edible for most ciliates, rotifers and daphnids. Ciliates clearly dominated the grazing pressure on phytoplankton throughout spring, maintaining high biomasses together with the phytoplankton for up to 2 months. A CWP was observed when herbivores grazing on larger phytoplankton developed in addition to ciliates
Vertical differences in food web structure were examined in an extremely acidic, iron-rich mining lake in Germany (Lake 111; pH 2.6, total Fe 150mg L-1) during the period of stratification. We tested whether or not the seasonal variation of the plankton composition is less pronounced than the differences observed over depth. The lake was strongly stratified in summer, and concentrations of dissolved organic carbon and inorganic carbon were consistently low in the epilimnion but high in the hypolimnion. Oxygen concentrations declined in the hypolimnion but were always above 2mg L-1. Light attenuation did not change over depth and time and was governed by dissolved ferric iron. The plankton consisted mainly of single-celled and filamentous bacteria, the two mixotrophic flagellates Chlamydomonas sp. and Ochromonas sp., the two rotifer species Elosa worallii and Cephalodella hoodi, and Heliozoa as top predators. We observed very few ciliates and rhizopods, and no heterotrophic flagellates, crustaceans or fish. Ochromonas sp., bacterial filaments, Elosa and Heliozoa dominated in the epilimnion whereas Chlamydomonas sp., single-celled bacteria and Cephalodella dominated in the hypolimnion. Single-celled bacteria were controlled by Ochromonas sp. whereas the lack of large consumers favoured a high proportion of bacterial filaments. The primarily phototrophic Chlamydomas sp. was limited by light and CO2 and may have been reduced due to grazing by Ochromonas sp. in the epilimnion. The distribution of the primarily phagotrophic Ochromonas sp. and of the animals seemed to be controlled by prey availability. Differences in the plankton composition were much higher between the epilimnion and hypolimnion than within a particular stratum over time. The food web in Lake 111 was extremely species-poor enabling no functional redundancy. This was attributed to the direct exclusion of species by the harsh environmental conditions and presumably enforced by competitive exclusion. The latter was promoted by the low diversity at the first trophic level which, in turn, was attributed to relatively stable growth conditions and the independence of resource availability (inorganic carbon and light) from algal density. Ecological theory suggests that low functional redundancy promotes low stability in ecosystem processes which was not supported by our data.
Mixotrophs combine resource use to outcompete specialists: Implications for aquatic food webs
(2003)
The majority of species can be grouped into those relying solely on photosynthesis (phototrophy) or those relying solely on the assimilation of organic substances (heterotrophy) to meet their requirements for energy and carbon. However, a special life history trait exists in which organisms combine both phototrophy and heterotrophy. Such 'mixotrophy' is a widespread phenomenon in aquatic habitats and is observed in many protozoan and metazoan organisms. The strategy requires investment in both photosynthetic and heterotrophic cellular apparatus, but the benefits must outweigh these costs. In accordance with the mechanistic resource competition theory, laboratory experiments revealed that pigmented mixotrophs combined light and prey as substitutable resources. Thereby, they reduced prey abundance below the critical food concentration of competing specialist grazers [Rothhaupt, K. O. (1996) Ecology 77, 716-724]. Here, we demonstrate for the first time the important consequences of this strategy for an aquatic community. In the illuminated surface strata of a lake, mixotrophs reduced prey abundance so steeply that grazers from higher trophic levels, consuming both the mixotrophs and their prey, could not persist. Thus, the mixotrophs escaped from both competition and grazing, and remained dominant. Furthermore, the mixotrophs structured the prey abundance along the vertical light gradient creating low densities near the surface and a pronounced maximum of their algal prey at depth. Such deep algal accumulations are typical features of nutrient poor aquatic habitats, previously explained by resource availability. We hypothesize instead that the mixotrophic grazing strategy is responsible for deep algal accumulations in many aquatic environments.
Interplay between energy limitation and nutritional deficiency: Empirical data and food web models
(2002)
Due to differences in the biochemical composition of autotrophs and their grazers, food quality can strongly influence herbivore population dynamics. Under nutrient depleted conditions the carbon to nutrient ratios of autotrophs can increase to such an extent that consumers become nutrient rather than energy limited. Estimating the importance of this effect in situ in pelagic food webs is complicated by the omnivory of many consumers and rapid nutrient recycling. Isolated predator-prey studies inadequately represent this interaction, instead an ecosystem perspective is required. We used seven years of data from large, deep Lake Constance to develop seasonally resolved flux models of the pelagic food web and analyze the balance between energetic and nutrient constraints. The carbon (C) and phosphorus (P) flows were simultaneously quantified and balanced. C represented food quantity/energy. P was taken as a surrogate of food quality, because algal C:P ratios exceeded the threshold above which P limitation of herbivores is predicted by stoichiometric theory throughout summer and autumn. Primary production exceeded bacterial C production by a factor of 3 but autotrophs and bacteria took up approximately equal amounts of P during summer and autumn. As a consequence the C and P supply of suspension-feeding zooplankton was decoupled: Consumer C demands were largely met by phytoplankton whereas P was mostly obtained from bacteria and their protist predators. The degree of consumer P deficiency varied according to supplementation of their algal diet with P-enriched bacteria or bacterivores. This favored the occurrence of omnivores, i.e. organisms that minimized P deficiencies at the cost of enhanced energy limitation. In contrast with previous perceptions, P remineralization during P depleted summer conditions was dominated by bacterivorous flagellates, carnivorous crustaceans and fish, which fed on prey with an elemental composition similar to their own, whereas herbivores contributed only 30% of P cycling despite their large biomass and C production. Our results suggested a co- limitation of predominantly herbivorous consumers by C and P and a mutual dependence of the two types of deficiency at the individual and system level. This pattern is not specific to pelagic systems but appears to be applicable across ecosystem types.
Background: The loss of photosynthesis has occurred often in eukaryotic evolution, even more than its acquisition, which occurred at least nine times independently and which generated the evolution of the supergroups Archaeplastida, Rhizaria, Chromalveolata and Excavata. This secondary loss of autotrophic capability is essential to explain the evolution of eukaryotes and the high diversity of protists, which has been severely underestimated until recently. However, the ecological and evolutionary scenarios behind this evolutionary ‘‘step back’’ are still largely unknown. Methodology/Principal Findings: Using a dynamic model of heterotrophic and mixotrophic flagellates and two types of prey, large bacteria and ultramicrobacteria, we examine the influence of DOC concentration, mixotroph’s photosynthetic growth rate, and external limitations of photosynthesis on the coexistence of both types of flagellates. Our key premises are: large bacteria grow faster than small ones at high DOC concentrations, and vice versa; and heterotrophic flagellates are more efficient than the mixotrophs grazing small bacteria (both empirically supported). We show that differential efficiency in bacteria grazing, which strongly depends on cell size, is a key factor to explain the loss of photosynthesis in mixotrophs (which combine photosynthesis and bacterivory) leading to purely heterotrophic lineages. Further, we show in what conditions an heterotroph mutant can coexist, or even out-compete, its mixotrophic ancestor, suggesting that bacterivory and cell size reduction may have been major triggers for the diversification of eukaryotes. Conclusions/Significance: Our results suggest that, provided the mixotroph’s photosynthetic advantage is not too large, the (small) heterotroph will also dominate in nutrient-poor environments and will readily invade a community of mixotrophs and bacteria, due to its higher efficiency exploiting the ultramicrobacteria. As carbon-limited conditions were presumably widespread throughout Earth history, such a scenario may explain the numerous transitions from phototrophy to mixotrophy and further to heterotrophy within virtually all major algal lineages. We challenge prevailing concepts that affiliated the evolution of phagotrophy with eutrophic or strongly light-limited environments only.
Global change threatens the maintenance of ecosystem functions that are shaped by the persistence and dynamics of populations. It has been shown that the persistence of species increases if they possess larger trait adaptability. Here, we investigate whether trait adaptability also affects the robustness of population dynamics of interacting species and thereby shapes the reliability of ecosystem functions that are driven by these dynamics. We model co‐adaptation in a predator–prey system as changes to predator offense and prey defense due to evolution or phenotypic plasticity. We investigate how trait adaptation affects the robustness of population dynamics against press perturbations to environmental parameters and against pulse perturbations targeting species abundances and their trait values. Robustness of population dynamics is characterized by resilience, elasticity, and resistance. In addition to employing established measures for resilience and elasticity against pulse perturbations (extinction probability and return time), we propose the warping distance as a new measure for resistance against press perturbations, which compares the shapes and amplitudes of pre‐ and post‐perturbation population dynamics. As expected, we find that the robustness of population dynamics depends on the speed of adaptation, but in nontrivial ways. Elasticity increases with speed of adaptation as the system returns more rapidly to the pre‐perturbation state. Resilience, in turn, is enhanced by intermediate speeds of adaptation, as here trait adaptation dampens biomass oscillations. The resistance of population dynamics strongly depends on the target of the press perturbation, preventing a simple relationship with the adaptation speed. In general, we find that low robustness often coincides with high amplitudes of population dynamics. Hence, amplitudes may indicate the robustness against perturbations also in other natural systems with similar dynamics. Our findings show that besides counteracting extinctions, trait adaptation indeed strongly affects the robustness of population dynamics against press and pulse perturbations.
Ecoevolutionary feedbacks in predator-prey systems have been shown to qualitatively alter predator-prey dynamics. As a striking example, defense-offense coevolution can reverse predator-prey cycles, so predator peaks precede prey peaks rather than vice versa. However, this has only rarely been shown in either model studies or empirical systems. Here, we investigate whether this rarity is a fundamental feature of reversed cycles by exploring under which conditions they should be found. For this, we first identify potential conditions and parameter ranges most likely to result in reversed cycles by developing a new measure, the effective prey biomass, which combines prey biomass with prey and predator traits, and represents the prey biomass as perceived by the predator. We show that predator dynamics always follow the dynamics of the effective prey biomass with a classic 1/4-phase lag. From this key insight, it follows that in reversed cycles (i.e., -lag), the dynamics of the actual and the effective prey biomass must be in antiphase with each other, that is, the effective prey biomass must be highest when actual prey biomass is lowest, and vice versa. Based on this, we predict that reversed cycles should be found mainly when oscillations in actual prey biomass are small and thus have limited impact on the dynamics of the effective prey biomass, which are mainly driven by trait changes. We then confirm this prediction using numerical simulations of a coevolutionary predator-prey system, varying the amplitude of the oscillations in prey biomass: Reversed cycles are consistently associated with regions of parameter space leading to small-amplitude prey oscillations, offering a specific and highly testable prediction for conditions under which reversed cycles should occur in natural systems.
It is well-known that prey species often face trade-offs between defense against predation and competitiveness, enabling predator-mediated coexistence. However, we lack an understanding of how the large variety of different defense traits with different competition costs affects coexistence and population dynamics. Our study focusses on two general defense mechanisms, that is, pre-attack (e.g., camouflage) and post-attack defenses (e.g., weaponry) that act at different phases of the predator—prey interaction. We consider a food web model with one predator, two prey types and one resource. One prey type is undefended, while the other one is pre- or post-attack defended paying costs either by a higher half-saturation constant for resource uptake or a lower maximum growth rate. We show that post-attack defenses promote prey coexistence and stabilize the population dynamics more strongly than pre-attack defenses by interfering with the predator's functional response: Because the predator spends time handling “noncrackable” prey, the undefended prey is indirectly facilitated. A high half-saturation constant as defense costs promotes coexistence more and stabilizes the dynamics less than a low maximum growth rate. The former imposes high costs at low resource concentrations but allows for temporally high growth rates at predator-induced resource peaks preventing the extinction of the defended prey. We evaluate the effects of the different defense mechanisms and costs on coexistence under different enrichment levels in order to vary the importance of bottom-up and top-down control of the prey community.
Resisting annihilation
(2018)
Allelopathic species can alter biodiversity. Using simulated assemblages that are characterised by neutrality, lumpy coexistence and intransitivity, we explore relationships between within-assemblage competitive dissimilarities and resistance to allelopathic species. An emergent behaviour from our models is that assemblages are more resistant to allelopathy when members strongly compete exploitatively (high competitive power). We found that neutral assemblages were the most vulnerable to allelopathic species, followed by lumpy and then by intransitive assemblages. We find support for our modeling in real-world time-series data from eight lakes of varied morphometry and trophic state. Our analysis of this data shows that a lake's history of allelopathic phytoplankton species biovolume density and dominance is related to the number of species clusters occurring in the plankton assemblages of those lakes, an emergent trend similar to that of our modeling. We suggest that an assemblage's competitive power determines its allelopathy resistance.
Ecological communities are complex adaptive systems that exhibit remarkable feedbacks between their biomass and trait dynamics. Trait-based aggregate models cope with this complexity by focusing on the temporal development of the community’s aggregate properties such as its total biomass, mean trait and trait variance. They are based on particular assumptions about the shape of the underlying trait distribution, which is commonly assumed to be normal. However, ecologically important traits are usually restricted to a finite range, and empirical trait distributions are often skewed or multimodal. As a result, normal distribution-based aggregate models may fail to adequately represent the biomass and trait dynamics of natural communities. We resolve this mismatch by developing a new moment closure approach assuming the trait values to be beta-distributed. We show that the beta distribution captures important shape properties of both observed and simulated trait distributions, which cannot be captured by a Gaussian. We further demonstrate that a beta distribution-based moment closure can strongly enhance the reliability of trait-based aggregate models. We compare the biomass, mean trait and variance dynamics of a full trait distribution (FD) model to the ones of beta (BA) and normal (NA) distribution-based aggregate models, under different selection regimes. This way, we demonstrate under which general conditions (stabilizing, fluctuating or disruptive selection) different aggregate models are reliable tools. All three models predicted very similar biomass and trait dynamics under stabilizing selection yielding unimodal trait distributions with small standing trait variation. We also obtained an almost perfect match between the results of the FD and BA models under fluctuating selection, promoting skewed trait distributions and ongoing oscillations in the biomass and trait dynamics. In contrast, the NA model showed unrealistic trait dynamics and exhibited different alternative stable states, and thus a high sensitivity to initial conditions under fluctuating selection. Under disruptive selection, both aggregate models failed to reproduce the results of the FD model with the mean trait values remaining within their ecologically feasible ranges in the BA model but not in the NA model. Overall, a beta distribution-based moment closure strongly improved the realism of trait-based aggregate models.
Predator-prey oscillations are expected to show a 1/4-phase lag between predator and prey. However, observed dynamics of natural or experimental predator-prey systems are often more complex. A striking but hardly studied example are sudden interruptions of classic 1/4-lag cycles with periods of antiphase oscillations, or periods without any regular predator-prey oscillations. These interruptions occur for a limited time before the system reverts to regular 1/4-lag oscillations, thus yielding intermittent cycles. Reasons for this behaviour are often difficult to reveal in experimental systems. Here we test the hypothesis that such complex dynamical behaviour may result from minor trait variation and trait adaptation in both the prey and predator, causing recurrent small changes in attack rates that may be hard to capture by empirical measurements. Using a model structure where the degree of trait variation in the predator can be explicitly controlled, we show that a very limited amount of adaptation resulting in 10-15% temporal variation in attack rates is already sufficient to generate these intermittent dynamics. Such minor variation may be present in experimental predator-prey systems, and may explain disruptions in regular 1/4-lag oscillations.
The shapes of phytoplankton units (unicellular organisms and colonies) are extremely diverse, and no unique relationship exists between their volume, V, and longest linear dimension, L. However, an approximate scaling between these parameters can be found because the shape variations within each size class are constrained by cell physiology, grazing pressure, and optimality of resource acquisition. To determine this scaling and to test for its seasonal and interannual variation under changing environmental conditions, we performed weighted regression analysis of time-dependent length-volume relations of the phytoplankton community in large deep Lake Constance from 1979 to 1999. We show that despite a large variability in species composition, the V(L) relationship can be approximated as a power law, V similar to L-alpha, with a scaling exponent alpha = 3 for small cells (L < 25 mu m) and alpha = 1.7 if the fitting is performed over the entire length range, including individual cells and colonies. The best description is provided by a transitional power function describing a regime change from a scaling exponent of 3 for small cells to an exponent of 0.4 in the range of large phytoplankton. Testing different weighted fitting approaches we show that remarkably the best prediction of the total community biovolume from measurements of L and cell density is obtained when the regression is weighted with the squares of species abundances. Our approach should also be applicable to other systems and allows converting phytoplankton length distributions (e.g., obtained with automatic monitoring such as flow cytometry) into distributions of biovolume and biovolume-related phytoplankton traits.
The intrinsic predictability of ecological time series and its potential to guide forecasting
(2019)
Phenotypic plasticity in prey can have a dramatic impact on predator-prey dynamics, e.g. by inducible defense against temporally varying levels of predation. Previous work has overwhelmingly shown that this effect is stabilizing: inducible defenses dampen the amplitudes of population oscillations or eliminate them altogether. However, such studies have neglected scenarios where being protected against one predator increases vulnerability to another (incompatible defense). Here we develop a model for such a scenario, using two distinct prey phenotypes and two predator species. Each prey phenotype is defended against one of the predators, and vulnerable to the other. In strong contrast with previous studies on the dynamic effects of plasticity involving a single predator, we find that increasing the level of plasticity consistently destabilizes the system, as measured by the amplitude of oscillations and the coefficients of variation of both total prey and total predator biomasses. We explain this unexpected and seemingly counterintuitive result by showing that plasticity causes synchronization between the two prey phenotypes (and, through this, between the predators), thus increasing the temporal variability in biomass dynamics. These results challenge the common view that plasticity should always have a stabilizing effect on biomass dynamics: adding a single predator-prey interaction to an established model structure gives rise to a system where different mechanisms may be at play, leading to dramatically different outcomes.
Phenotypic plasticity can increase individual fitness when environmental conditions change over time. Inducible defences are a striking example, allowing species to react to fluctuating predation pressure by only expressing their costly defended phenotype under high predation risk. Previous theoretical investigations have focused on how this affects predator–prey dynamics, but the impact on competitive outcomes and broader community dynamics has received less attention. Here we use a small food web model, consisting of two competing plastic autotrophic species exploited by a shared consumer, to study how the speed of inducible defences across three trade-off constellations affects autotroph coexistence, biomasses across trophic levels, and temporal variability. Contrary to the intuitive idea that faster adaptation increases autotroph fitness, we found that higher switching rates reduced individual fitness as it consistently provoked more maladaptive switching towards undefended phenotypes under high predation pressure. This had an unexpected positive impact on the consumer, increasing consumer biomass and lowering total autotroph biomass. Additionally, maladaptive switching strongly reduced autotroph coexistence through an emerging source-sink dynamic between defended and undefended phenotypes. The striking impact of maladaptive switching on species and food web dynamics indicates that this mechanism may be of more critical importance than previously recognized.
Portal alumni
(2018)
Offenheit, Vertrauen und Zuverlässigkeit – das sind wichtige Säulen langanhaltender und erfolgreicher Partnerschaften. Partnerschaften auf Augenhöhe, die auf Freiwilligkeit, gegenseitigem Wohlwollen, Respekt, Vertrauen und Wertschätzung beruhen, werden auch an der Universität Potsdam gebraucht und gefördert. Sie entstehen zwischen Lehrenden, Studierenden und Alumni oder sie werden gelebt in vielfältigen Kontakten der Universität mit Stakeholdern in Politik, Wirtschaft und Gesellschaft. Wie in jeder Partnerschaft gilt auch hier das Prinzip des gegenseitigen Gebens und Nehmens. Sind Ziele, Rollen, Erwartungen und Rahmenbedingungen geklärt, kann aus einem ersten Gespräch eine neue Perspektive, ein zündender Impuls, eine Entscheidungshilfe oder sogar eine langjährige Kooperation werden. In dem 15. Heft unseres Alumni-Magazins berichten wir von solchen Partnerschaften. So stellen wir Biologieprofessorin Ursula Gaedke vor, die zu ihren ehemaligen Studierenden und Mitarbeitern langjährige Kontakte pflegt, von denen beide Seiten profitieren. Wir berichten aber auch vom Partnerkreis „Industrie & Wirtschaft“, der Unternehmen und die Universität Potsdam verbindet. Mit diesem Netzwerk wird die Fachkräftesicherung in der Region unterstützt und der Wissenstransfer gefördert. Die Vermittlung von Studierenden und Absolventen ist dabei ein wichtiger Baustein. Und nicht zuletzt kommen Ehemalige der Universität zu Wort und erzählen von ihren Partnerschaften zu Studierenden. Katharina Strauß beispielsweise, gibt ihre Erfahrungen aus dem Jurastudium und dem Berufsleben seit zehn Jahren an Studentinnen ihres Faches weiter. Im Juristinnen-Mentoring-Programm gibt sie Anstöße und neue Impulse und mildert so manche Prüfungsangst. Darüber hinaus stellen wir in diesem Heft auch wieder aktuelle Projekte Ihrer Alma Mater vor und berichten von den Höhepunkten des Jahres 2018.
Trade-offs between functional traits are ubiquitous in nature and can promote species coexistence depending on their shape. Classic theory predicts that convex trade-offs facilitate coexistence of specialized species with extreme trait values (extreme species) while concave trade-offs promote species with intermediate trait values (intermediate species). We show here that this prediction becomes insufficient when the traits translate non-linearly into fitness which frequently occurs in nature, e.g., an increasing length of spines reduces grazing losses only up to a certain threshold resulting in a saturating or sigmoid trait-fitness function. We present a novel, general approach to evaluate the effect of different trade-off shapes on species coexistence. We compare the trade-off curve to the invasion boundary of an intermediate species invading the two extreme species. At this boundary, the invasion fitness is zero. Thus, it separates trait combinations where invasion is or is not possible. The invasion boundary is calculated based on measurable trait-fitness relationships. If at least one of these relationships is not linear, the invasion boundary becomes non-linear, implying that convex and concave trade-offs not necessarily lead to different coexistence patterns. Therefore, we suggest a new ecological classification of trade-offs into extreme-favoring and intermediate-favoring which differs from a purely mathematical description of their shape. We apply our approach to a well-established model of an empirical predator-prey system with competing prey types facing a trade-off between edibility and half-saturation constant for nutrient uptake. We show that the survival of the intermediate prey depends on the convexity of the trade-off. Overall, our approach provides a general tool to make a priori predictions on the outcome of competition among species facing a common trade-off in dependence of the shape of the trade-off and the shape of the trait-fitness relationships.
A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others ('reinventing the wheel'). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available ('having tunnel vision'). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and traitbased models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its 'leading principle', there are many opportunities for combining approaches. We take the point of view that a single 'right' approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative view on the functioning of lake ecosystems. We end with a set of specific recommendations that may be of help in the further development of lake ecosystem models.
A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others ('reinventing the wheel'). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available ('having tunnel vision'). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and traitbased models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its 'leading principle', there are many opportunities for combining approaches. We take the point of view that a single 'right' approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative view on the functioning of lake ecosystems. We end with a set of specific recommendations that may be of help in the further development of lake ecosystem models.
Simultaneous limitation of plant growth by two or more nutrients is increasingly acknowledged as a common phenomenon in nature, but its cellular mechanisms are far from understood. We investigated the uptake kinetics of CO(2) and phosphorus of the algae Chlamydomonas acidophila in response to growth at limiting conditions of CO(2) and phosphorus. In addition, we fitted the data to four different Monod-type models: one assuming Liebigs Law of the minimum, one assuming that the affinity for the uptake of one nutrient is not influenced by the supply of the other (independent colimitation) and two where the uptake affinity for one nutrient depends on the supply of the other (dependent colimitation). In addition we asked whether the physiological response under colimitation differs from that under single nutrient limitation. We found no negative correlation between the affinities for uptake of the two nutrients, thereby rejecting a dependent colimitation. Kinetic data were supported by a better model fit assuming independent uptake of colimiting nutrients than when assuming Liebigs Law of the minimum or a dependent colimitation. Results show that cell nutrient homeostasis regulated nutrient acquisition which resulted in a trade-off in the maximum uptake rates of CO(2) and phosphorus, possibly driven by space limitation on the cell membrane for porters for the different nutrients. Hence, the response to colimitation deviated from that to a single nutrient limitation. In conclusion, responses to single nutrient limitation cannot be extrapolated to situations where multiple nutrients are limiting, which calls for colimitation experiments and models to properly predict growth responses to a changing natural environment. These deviations from single nutrient limitation response under colimiting conditions and independent colimitation may also hold for other nutrients in algae and in higher plants.
The mineral and biochemical food quality of prey may limit predator production. This well-studied direct bottom-up effect is especially prominent for herbivore-plant interactions. Low-quality prey species, particularly when defended, are generally considered to be less prone to predator-driven extinction. Undefended high-quality prey species sustain high predator production thereby potentially increasing their own extinction risk. The food quality of primary producers is highly species-specific. In communities of competing prey species, predators thus may supplement their diets of low-quality prey with high-quality prey, leading to indirect horizontal interactions between prey species of different food quality. We explore how these predator-mediated indirect interactions affect species coexistence in a general predator-prey model that is parametrized for an experimental algae-rotifer system. To cover a broad range of three essential functional traits that shape many plant-herbivore interactions we consider differences in 1) the food quality of the prey species, 2) their competitive ability for nutrient uptake and 3) their defence against predation. As expected, low food quality of prey can, similarly to defence, provide protection against extinction by predation. Counterintuitively, our simulations demonstrate that being of high food quality also prevents extinction of that prey species and additionally promotes coexistence with a competing, low-quality prey. The persistence of the high-quality prey enables a high conversion efficiency and control of the low-quality prey by the predator and allows for re-allocation of nutrients to the high-quality competitor. Our results show that high food quality is not necessarily detrimental for a prey species but instead can protect against extinction and promote species richness and functional biodiversity.
Chemostat experiments are employed to study predator-prey and other trophic interactions, frequently using phytoplankton-zooplankton systems. These experiments often use population dynamics as fingerprints of ecological and evolutionary processes, assuming that the contributions of all major actors to these dynamics are known. However, bacteria are often neglected although they are frequently present. We argue that even without external carbon input bacteria may affect the experimental outcomes depending on experimental conditions and the physiological traits of bacteria, phytoplankton, and zooplankton. Using a static carbon flux model and a dynamic simulation model, we predict the minimum and maximum impact of bacteria on phytoplankton-zooplankton population dynamics. Under bacteria-suppressing conditions, we find that the effect of bacteria is indeed negligible and their omission justified. Under bacteria-favoring conditions, however, bacteria may strongly affect average biomasses of phytoplankton and zooplankton. The population dynamics may become highly complex, which may result in wrong interpretations when inferring processes (e.g., trait changes) from population dynamic patterns without considering bacteria. We provide suggestions to reduce the bacterial impact experimentally. Besides optimizing experimental conditions (e.g., the dilution rate) the appropriate choice of the zooplankton predator is decisive. Counterintuitively, bacteria have a larger impact if the predator is not bacterivorous as high bacterial biomasses and complex population dynamics arise via competition for nutrients with the phytoplankton. Only at least partial bacterivory minimizes the impact of bacteria. Our results help to improve the design of chemostat experiments and their interpretation, and advance the study of ecological and evolutionary processes in aquatic food webs.
The green microalga Chlamydomonas acidophila is an important primary producer in very acidic lakes (pH 2.0-3.5), characterized by high concentrations of ferric iron (up to 1 g total Fe L-1) and low rates of primary production. It was previously suggested that these high iron concentrations result in high iron accumulation and inhibit photosynthesis in C. acidophila. To test this, the alga was grown in sterilized lake water and in medium with varying total iron concentrations under limiting and sufficient inorganic phosphorus (Pi) supply, because Pi is an important growth limiting nutrient in acidic waters. Photosynthesis and growth of C. acidophila as measured over 5 days were largely unaffected by high total iron concentrations and only decreased if free ionic Fe3+ concentrations exceeded 100 mg Fe3+ L-1. Although C. acidophila was relatively rich in iron (up to 5 mmol Fe: mol C), we found no evidence of iron toxicity. In contrast, a concentration of 260 mg total Fe L-1 (i.e. 15 mg free ionic Fe3+ L-1), which is common in many acidic lakes, reduced Pi-incorporation by 50% and will result in Pi-limited photosynthesis. The resulting Pi-limitation present at high iron and Pi concentrations was illustrated by elevated maximum Pi-uptake rates. No direct toxic effects of high iron were found, but unfavourable chemical Pi-speciation reduced growth of the acidophile alga.
Chlamydomonas acidophila faces high heavy-metal concentrations in acidic mining lakes, where it is a dominant phytoplankton species. To investigate the importance of metals to C. acidophila in these lakes, we examined the response of growth, photosynthesis, cell structure, heat-shock protein (Hsp) accumulation, and metal adsorption after incubation in metal-rich lake water and artificial growth medium enriched with metals (Fe, Zn). Incubation in both metal-rich lake water and medium caused large decreases in photosystem II function (though no differences among lakes), but no decrease in growth rate (except for medium + Fe). Concentrations of small Hsps were higher in algae incubated in metal-rich lake- water than in metal-enriched medium, whereas Hsp60 and Hsp70A were either less or equally expressed. Cellular Zn and Fe contents were lower, and metals adsorbed to the cell surface were higher, in lake-water-incubated algae than in medium- grown cells. The results indicate that high Zn or Fe levels are likely not the main or only contributor to the low primary production in mining lakes, and multiple adaptations of C. acidophila (e.g., high Hsp levels, decreased metal accumulation) increase its tolerance to metals and permit survival under such adverse environmental conditions. Supposedly, the main stress factor present in the lake water is an interaction between low P and high Fe concentrations.
Chlamydomonas acidophila, a dominant phytoplankton species in the very acidic Lake 111 (pH 2.7) situated in Germany, faces low concentrations of inorganic phosphorus (P-i), inorganic carbon (C-i) and potassium (K+) in its environment, which may lead to a complex colimitation by these nutrients. We performed laboratory and field investigations to test for P-i limitation and its dependence on C-i and K+ concentrations. The minimum cell quota for phosphorus (Q(0)) and phosphatase enzyme activity were similar to those for neutrophilic algae, despite the low pH and high concentrations of iron and aluminium, indicating no extra metabolic costs or inhibition of enzymes by the extreme environment. The threshold concentration of soluble reactive phosphorus for growth (SRPt), the algal C:P ratio and the alkaline phosphatase enzyme activity all suggested a moderate P-i limitation of C. acidophila in Lake 111. SRPt and Q(0) were higher at low CO2 and K+ concentrations in culture, showing a relationship between C-i and P-i acquisition. Furthermore, SRPt and Q(0) were higher under K+/P-i-colimiting conditions than under P-i-limiting conditions alone, suggesting that K+ concentrations influence P-i limitation in C. acidophila as well. Our results show that a limitation by one macronutrient requires consideration of the availability of the others as their uptake mechanisms depend on each other. Notwithstanding these interactions, C-i or K+ concentrations had no clear influence on the P-i limitation of C. acidophila in Lake 111.
1. The polyunsaturated fatty acid eicosapentaenoic acid (EPA) plays an important role in aquatic food webs, in particular at the primary producerconsumer 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 (020 m) and depth (08 and 820 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.
In the deep, cooler layers of clear, nutrient-poor, stratified water bodies, phytoplankton often accumulate to form a thin band or "deep chlorophyll maximum" (DCM) of ecological importance. Under such conditions, these photosynthetic microorganisms may be close to their physiological compensation points and to the boundaries of their ecological tolerance. To grow and survive any resulting energy limitation, DCM species are thought to exhibit highly specialised or flexible acclimation strategies. In this study, we investigated several of the adaptable ecophysiological strategies potentially employed by one such species, Chlamydomonas acidophila: a motile, unicellular, phytoplanktonic flagellate that often dominates the DCM in stratified, acidic lakes. Physiological and behavioural responses were measured in laboratory experiments and were subsequently related to field observations. Results showed moderate light compensation points for photosynthesis and growth at 22A degrees C, relatively low maintenance costs, a behavioural preference for low to moderate light, and a decreased compensation point for photosynthesis at 8A degrees C. Even though this flagellated alga exhibited a physiologically mediated diel vertical migration in the field, migrating upwards slightly during the day, the ambient light reaching the DCM was below compensation points, and so calculations of daily net photosynthetic gain showed that survival by purely autotrophic means was not possible. Results suggested that strategies such as low-light acclimation, small-scale directed movements towards light, a capacity for mixotrophic growth, acclimation to low temperature, in situ exposure to low O-2, high CO2 and high P concentrations, and an avoidance of predation, could combine to help overcome this energetic dilemma and explain the occurrence of the DCM. Therefore, corroborating the deceptive ecophysiological complexity of this and similar organisms, only a suite of complementary strategies can facilitate the survival of C. acidophila in this DCM.
A rise in temperature will intensify the feeding links involving ectotherms in food webs. However, it is unclear how the effects will quantitatively differ between the plant-herbivore and herbivore-carnivore interface. To test how warming could differentially affect rates of herbivory and carnivory, we studied trophic interaction strength in a food chain comprised of green algae, herbivorous rotifers and carnivorous rotifers at 10, 15, 20 and 25 degrees C. We found significant warming-induced changes in feeding by both herbivorous and carnivorous rotifers, but these responses occurred at different parts of the entire temperature gradient. The strongest response of the per capita herbivore's ingestion rate occurred due to an increase in temperature from 15 to 20 degrees C (1.9 fold: from 834 to 1611 algal cells per h(-1)) and of the per capita carnivore's ingestion rate from 20 to 25 degrees C (1.6 fold: from 1.5 to 2.5 prey h(-1)). Handling time, an important component of a consumer's functional response, significantly decreased from 15 to 20 degrees C in herbivorous rotifers. In contrast, it decreased from 20 to 25 degrees C in carnivorous rotifers. Attack rates significantly and strongly increased from 10 to 25 degrees C in the herbivorous animals, but not at all in the carnivores. Our results exemplify how the relative forces of top-down control exerted by herbivores and carnivores may strongly shift under global warming. But warming, and its magnitude, are not the only issue: If our results would prove to be representative, shifts in ectotherm interactions will quantitatively differ when a 5 degrees C increase starts out from a low, intermediate or high initial temperature. This would imply that warming could have different effects on the relative forces of carnivory and herbivory in habitats differing in average temperature, as would exist at different altitudes and latitudes.
Ecosystem functioning is affected by horizontal (within trophic groups) and vertical (across trophic levels) biodiversity. Theory predicts that the effects of vertical biodiversity depend on consumer specialization. In a microcosm experiment, we investigated ciliate consumer diversity and specialization effects on algal prey biovolume, evenness and composition, and on ciliate biovolume production. The experimental data was complemented by a process-based model further analyzing the ecological mechanisms behind the observed diversity effects. Overall, increasing consumer diversity had no significant effect on prey biovolume or evenness. However, consumer specialization affected the prey community. Specialist consumers showed a stronger negative impact on prey biovolume and evenness than generalists. The model confirmed that this pattern was mainly driven by a single specialist with a high per capita grazing rate, consuming the two most productive prey species. When these were suppressed, the prey assemblage became dominated by a less productive species, consequently decreasing prey biovolume and evenness. Consumer diversity increased consumer biovolume, which was stronger for generalists than for specialists and highest in mixed combinations, indicating that consumer functional diversity, i.e. more diverse feeding strategies, increased resource use efficiency. Overall, our results indicate that consumer diversity effects on prey and consumers strongly depend on species-specific growth and grazing rates, which may be at least equally important as consumer specialization in driving consumer diversity effects across trophic levels.
Phenotypic plasticity can increase individual fitness when environmental conditions change over time. Inducible defences are a striking example, allowing species to react to fluctuating predation pressure by only expressing their costly defended phenotype under high predation risk. Previous theoretical investigations have focused on how this affects predator–prey dynamics, but the impact on competitive outcomes and broader community dynamics has received less attention. Here we use a small food web model, consisting of two competing plastic autotrophic species exploited by a shared consumer, to study how the speed of inducible defences across three trade-off constellations affects autotroph coexistence, biomasses across trophic levels, and temporal variability. Contrary to the intuitive idea that faster adaptation increases autotroph fitness, we found that higher switching rates reduced individual fitness as it consistently provoked more maladaptive switching towards undefended phenotypes under high predation pressure. This had an unexpected positive impact on the consumer, increasing consumer biomass and lowering total autotroph biomass. Additionally, maladaptive switching strongly reduced autotroph coexistence through an emerging source-sink dynamic between defended and undefended phenotypes. The striking impact of maladaptive switching on species and food web dynamics indicates that this mechanism may be of more critical importance than previously recognized.