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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.
Species richness has been shown to increase biomass production of plant communities. Such overyielding occurs when a community performs better than its component monocultures due to the complementarity or dominance effect and is mostly detected in substrate-bound plant communities (terrestrial plants or submerged macrophytes) where resource use complementarity can be enhanced due to differences in rooting architecture and depth. Here, we investigated whether these findings arc generalizeable for free-floating phytoplankton with little potential for spatial differences in resource use. We performed aquatic microcosm experiments with eight phytoplankton species belonging to four functional groups to determine the manner in which species and community biovolume varies in relation to the number of functional groups and hypothesized that an increasing number of functional groups within a community promotes overyielding. Unexpectedly, we did not detect overyielding in any algal community. Instead. total community biovolume tended to decrease with all increasing, number of functional groups. This underyielding was mainly caused by the negative dominance effect that originated from a trade-off between growth rate and filial biovolume. In monoculture, slow-groing species built up higher biovolumes that fast-growing ones, whereas in mixture a fast-growing but low-productive species monopolized most of the nutrients and prevented competing species from developing high biovolumes expected from monocultures. Our results indicated that the Magnitude of the community biovolume was largely determined by the identify of one species. Functional diversity and resource use complementarity were of minor Importance among free-floating phytoplankton, possibly reflecting the lack of spatially heterogeneous resource distribution. As a consequence, biodiversity-ecosystem functioning relationships may not be easily generalizeable from substrate-bound plant to phytoplankton communities and vice versa.
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.
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.
Central to ecology and ecosystem management, succession theory aims to mechanistically explain and predict the assembly and development of ecological communities. Yet processes at lower hierarchical levels, e. g. at the species and functional group level, are rarely mechanistically linked to the under-investigated system-level processes which drive changes in ecosystem properties and functioning and are comparable across ecosystems. As a model system for secondary succession, seasonal plankton succession during the growing season is readily observable and largely driven autogenically. We used a long-term dataset from large, deep Lake Constance comprising biomasses, auto-and heterotrophic production, food quality, functional diversity, and mass-balanced food webs of the energy and nutrient flows between functional guilds of plankton and partly fish. Extracting population-and system-level indices from this dataset, we tested current hypotheses about the directionality of successional progress which are rooted in ecosystem theory, the metabolic theory of ecology, quantitative food web theory, thermodynamics, and information theory. Our results indicate that successional progress in Lake Constance is quantifiable, passing through predictable stages. Mean body mass, functional diversity, predator-prey weight ratios, trophic positions, system residence times of carbon and nutrients, and the complexity of the energy flow patterns increased during succession. In contrast, both the mass-specific metabolic activity and the system export decreased, while the succession rate exhibited a bimodal pattern. The weighted connectance introduced here represents a suitable index for assessing the evenness and interconnectedness of energy flows during succession. Diverging from earlier predictions, ascendency and eco-exergy did not increase during succession. Linking aspects of functional diversity to metabolic theory and food web complexity, we reconcile previously disjoint bodies of ecological theory to form a complete picture of successional progress within a pelagic food web. This comprehensive synthesis may be used as a benchmark for quantifying successional progress in other ecosystems.
The sum of benthic autotrophic and bacterial production often exceeds the sum of pelagic autotrophic and bacterial production, and hence may contribute substantially to whole-lake carbon fluxes, especially in shallow lakes. Furthermore, both benthic and pelagic autotrophic and bacterial production are highly edible and of sufficient nutritional quality for animal consumers. We thus hypothesised that pelagic and benthic transfer efficiencies (ratios of production at adjacent trophic levels) in shallow lakes should be similar. We performed whole ecosystem studies in two shallow lakes (3.5ha, mean depth 2m), one with and one without submerged macrophytes, and quantified pelagic and benthic biomass, production and transfer efficiencies for bacteria, phytoplankton, epipelon, epiphyton, macrophytes, zooplankton, macrozoobenthos and fish. We expected higher transfer efficiencies in the lake with macrophytes, because these provide shelter and food for macrozoobenthos and may thus enable a more efficient conversion of basal production to consumer production. In both lakes, the majority of the whole-lake autotrophic and bacterial production was provided by benthic organisms, but whole-lake primary consumer production mostly relied on pelagic autotrophic and bacterial production. Consequently, transfer efficiency of benthic autotrophic and bacterial production to macrozoobenthos production was an order of magnitude lower than the transfer efficiency of pelagic autotrophic and bacterial production to rotifer and crustacean production. Between-lake differences in transfer efficiencies were minor. We discuss several aspects potentially causing the unexpectedly low benthic transfer efficiencies, such as the food quality of producers, pelagic-benthic links, oxygen concentrations in the deeper lake areas and additional unaccounted consumer production by pelagic and benthic protozoa and meiobenthos at intermediate or top trophic levels. None of these processes convincingly explain the large differences between benthic and pelagic transfer efficiencies. Our data indicate that shallow eutrophic lakes, even with a major share of autotrophic and bacterial production in the benthic zone, can function as pelagic systems with respect to primary consumer production. We suggest that the benthic autotrophic production was mostly transferred to benthic bacterial production, which remained in the sediments, potentially cycling internally in a similar way to what has previously been described for the microbial loop in pelagic habitats. Understanding the energetics of whole-lake food webs, including the fate of the substantial benthic bacterial production, which is either mineralised at the sediment surface or permanently buried, has important implications for regional and global carbon cycling.
Functionally diverse communities can adjust their species composition to altered environmental conditions, which may influence food web dynamics. Trait-based aggregate models cope with this complexity by ignoring details about species identities and focusing on their functional characteristics (traits). They describe the temporal changes of the aggregate properties of entire communities, including their total biomasses, mean trait values, and trait variances. The applicability of aggregate models depends on the validity of their underlying assumptions that trait distributions are normal and exhibit small variances. We investigated to what extent this can be expected to work by comparing an innovative model that accounts for the full trait distributions of predator and prey communities to a corresponding aggregate model. We used a food web structure with well-established trade-offs among traits promoting mutual adjustments between prey edibility and predator selectivity in response to selection. We altered the shape of the trade-offs to compare the outcome of the two models under different selection regimes, leading to trait distributions increasingly deviating from normality. Their biomass and trait dynamics agreed very well for stabilizing selection and reasonably well for directional selection, under which different trait values are favored at different times. However, for disruptive selection, the results of the aggregate model strongly deviated from the full trait distribution model that showed bimodal trait distributions with large variances. Hence, the outcome of aggregate models is reliable under ideal conditions but has to be questioned when confronted with more complex selection regimes and trait distributions, which are commonly observed in nature.
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.
To improve our mechanistic understanding and predictive capacities with respect to climate change effects on the spring phytoplankton bloom in temperate marine systems, we used a process-driven dynamical model to disentangle the impact of potentially relevant factors which are often correlated in the field. The model was based on comprehensive indoor mesocosm experiments run at four temperature and three light regimes. It was driven by time-series of water temperature and irradiance, considered edible and less edible phytoplankton separately, and accounted for density- dependent grazing losses. It successfully reproduced the observed dynamics of well edible phytoplankton in the different temperature and light treatments. Four major factors influenced spring phytoplankton dynamics: temperature, light (cloudiness), grazing, and the success of overwintering phyto- and zooplankton providing the starting biomasses for spring growth. Our study predicts that increasing cloudiness as anticipated for warmer winters for the Baltic Sea region will retard phytoplankton net growth and reduce peak heights. Light had a strong direct effect in contrast to temperature. However, edible phytoplankton was indirectly strongly temperature-sensitive via grazing which was already important in early spring at moderately high algal biomasses and counter-intuitively provoked lower and later algal peaks at higher temperatures. Initial phyto- and zooplankton composition and biomass also had a strong effect on spring algal dynamics indicating a memory effect via the broadly under-sampled overwintering plankton community. Unexpectedly, increased initial phytoplankton biomass did not necessarily lead to earlier or higher spring blooms since the effect was counteracted by subsequently enhanced grazing. Increasing temperature will likely exhibit complex indirect effects via changes in overwintering phytoplankton and grazer biomasses and current grazing pressure. Additionally, effects on the phytoplankton composition due to the species-specific susceptibility to grazing are expected. Hence, we need to consider not only direct but also indirect effects, e.g. biotic interactions, when addressing climate change impacts.
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.
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.
We investigated the effects of warming on a natural phytoplankton community from the Baltic Sea, based on six mesocosm experiments conducted 2005-2009. We focused on differences in the dynamics of three phytoplankton size groups which are grazed to a variable extent by different zooplankton groups. While small-sized algae were mostly grazer-controlled, light and nutrient availability largely determined the growth of medium- and large-sized algae. Thus, the latter groups dominated at increased light levels. Warming increased mesozooplankton grazing on medium-sized algae, reducing their biomass. The biomass of small-sized algae was not affected by temperature, probably due to an interplay between indirect effects spreading through the food web. Thus, under the higher temperature and lower light levels anticipated for the next decades in the southern Baltic Sea, a higher share of smaller phytoplankton is expected. We conclude that considering the size structure of the phytoplankton community strongly improves the reliability of projections of climate change effects.
In most biodiversity studies, taxonomic diversity is the measure for the multiplicity of species and is often considered to represent functional diversity. However, trends in taxonomic diversity and functional diversity may differ, for example, when many functionally similar but taxonomically different species co-occur in a community. The differences between these diversity measures are of particular interest in diversity research for understanding diversity patterns and their underlying mechanisms. We analysed a temporally highly resolved 20-year time series of lake phytoplankton to determine whether taxonomic diversity and functional diversity exhibit similar or contrasting seasonal patterns. We also calculated the functional mean of the community in n-dimensional trait space for each sampling day to gain further insights into the seasonal dynamics of the functional properties of the community. We found an overall weak positive relationship between taxonomic diversity and functional diversity with a distinct seasonal pattern. The two diversity measures showed synchronous behaviour from early spring to mid-summer and a more complex and diverging relationship from autumn to late winter. The functional mean of the community exhibited a recurrent annual pattern with the most prominent changes before and after the clear-water phase. From late autumn to winter, the functional mean of the community and functional diversity were relatively constant while taxonomic diversity declined, suggesting competitive exclusion during this period. A further decline in taxonomic diversity concomitant with increasing functional diversity in late winter to early spring is seen as a result of niche diversification together with competitive exclusion. Under these conditions, several different sets of traits are suitable to thrive, but within one set of functional traits only one, or very few, morphotypes can persist. Taxonomic diversity alone is a weak descriptor of trait diversity in phytoplankton. However, the combined analysis of taxonomic diversity and functional diversity, along with the functional mean of the community, allows for deeper insights into temporal patterns of community assembly and niche diversification.
In population ecology, there has been a fundamental controversy about the relative importance of competition- driven (density-dependent) population regulation vs. abiotic influences such as temperature and precipitation. The same issue arises at the community level; are population sizes driven primarily by changes in the abundances of cooccurring competitors (i.e., compensatory dynamics), or do most species have a common response to environmental factors? Competitive interactions have had a central place in ecological theory, dating back to Gleason, Volterra, Hutchison and MacArthur, and, more recently, Hubbell's influential unified neutral theory of biodiversity and biogeography. If competitive interactions are important in driving year-to-year fluctuations in abundance, then changes in the abundance of one species should generally be accompanied by compensatory changes in the abundances of others. Thus, one necessary consequence of strong compensatory forces is that, on average, species within communities will covary negatively. Here we use measures of community covariance to assess the prevalence of negative covariance in 41 natural communities comprising different taxa at a range of spatial scales. We found that species in natural communities tended to covary positively rather than negatively, the opposite of what would be expected if compensatory dynamics were important. These findings suggest that abiotic factors such as temperature and precipitation are more important than competitive interactions in driving year-to-year fluctuations in species abundance within communities.
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.
Complex transient dynamics of stage-structured populations in response to environmental changes
(2013)
Stage structures of populations can have a profound influence on their dynamics. However, not much is known about the transient dynamics that follow a disturbance in such systems. Here we combined chemostat experiments with dynamical modeling to study the response of the phytoplankton species Chlorella vulgaris to press perturbations. From an initially stable steady state, we altered either the concentration or dilution rate of a growth-limiting resource. This disturbance induced a complex transient response-characterized by the possible onset of oscillations-before population numbers relaxed to a new steady state. Thus, cell numbers could initially change in the opposite direction of the long-term change. We present quantitative indexes to characterize the transients and to show that the dynamic response is dependent on the degree of synchronization among life stages, which itself depends on the state of the population before perturbation. That is, we show how identical future steady states can be approached via different transients depending on the initial population structure. Our experimental results are supported by a size-structured model that accounts for interplay between cell-cycle and population-level processes and that includes resource-dependent variability in cell size. Our results should be relevant to other populations with a stage structure including organisms of higher order.
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.
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.
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.
Seasonal changes of the impact of daphnids on the plankton biomass size distribution, the biomass within individual size ranges, the average predator-prey weight ratios, and the efficiency to transfer matter and energy from small to large organisms are analyzed in large and deep Lake Constance based on comprehensive long-term observations. A comparison of daphnid biomass and production with those of other herbivorous groups (i. e. ciliates, rotifers, herbivorous crustaceans) reveals that in early spring daphnids play a minor role in relative and absolute values as compared to small fast growing ciliates. During this time, small algae and ciliates dominate which gives rise to a decreasing Sheldon-type size spectrum, low predator-prey weight ratios, and a low transfer efficiency along the size gradient. Around June, daphnids reach maximum abundances and become keystone species for the shape of the biomass size distribution, the food web structure, and the energy flow. They accumulate biomass in their size range one order of magnitude above the average. The slope of the normalized biomass size spectrum is less negative and positively correlated with daphnid biomass if the latter exceeds about 200 mg C/m2. This indicates a more efficient transfer along the size gradient with high predator-prey weight ratios and high trophic transfer efficiencies. The coefficients of determination of regression lines fitted to size distributions decrease with daphnid abundance, i. e. the size spectra become more irregular when daphnids dominate. In midsummer, daphnids lose their dominance and coexist with other herbivores (especially ciliates) in a highly diverse plankton community. The latter gives rise to a relatively smooth and almost flat Sheldon-type size distribution, lower predator-prey weight ratios, and a slightly reduced transfer efficiency along the size gradient. In late spring/early summer, negative relationships are found between daphnid biomass and the biomasses in the size ranges of autotrophic picoplankton, small phytoplankton, heterotrophic flagellates, and small and medium sized ciliates (0.06 - 32 pg C and 100-30,000 pg C). In mid- and late summer or on annual average, hardly any of these relationships existed. This cannot solely be attributed to lower daphnid abundance but points also to a more diverse control of small plankton organisms including nutrient limitation in summer. Ciliates influence the slope and shape of the size distribution much less than daphnids although they are at least of equal importance as daphnids in respect to herbivory and related fluxes in Lake Constance on annual average. The findings on the impact of daphnids on the energy flow within the plankton food web derived from size distributions are compared to, and are consistent with results obtained by mass-balanced carbon flow diagrams.
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.
Disentangling eco-evolutionary dynamics of predator-prey coevolution: the case of antiphase cycles
(2017)
The impact of rapid predator-prey coevolution on predator-prey dynamics remains poorly understood, as previous modelling studies have given rise to contradictory conclusions and predictions. Interpreting and reconciling these contradictions has been challenging due to the inherent complexity of model dynamics, defying mathematical analysis and mechanistic understanding. We develop a new approach here, based on the Geber method for deconstructing eco-evolutionary dynamics, for gaining such understanding. We apply this approach to a co-evolutionary predator-prey model to disentangle the processes leading to either antiphase or 1/4-lag cycles. Our analysis reveals how the predator-prey phase relationship is driven by the temporal synchronization between prey biomass and defense dynamics. We further show when and how prey biomass and trait dynamics become synchronized, resulting in antiphase cycles, allowing us to explain and reconcile previous modelling and empirical predictions. The successful application of our proposed approach provides an important step towards a comprehensive theory on eco-evolutionary feedbacks in predator-prey systems.
The concept that diversity promotes reliability of ecosystem function depends on the pattern that community-level biomass shows lower temporal variability than species-level biomasses. However, this pattern is not universal, as it relies on compensatory or independent species dynamics. When in contrast within--trophic level synchronization occurs, variability of community biomass will approach population-level variability. Current knowledge fails to integrate how species richness, functional distance between species, and the relative importance of predation and competition combine to drive synchronization at different trophic levels. Here we clarify these mechanisms. Intense competition promotes compensatory dynamics in prey, but predators may at the same time increasingly synchronize, under increasing species richness and functional similarity. In contrast, predators and prey both show perfect synchronization under strong top-down control, which is promoted by a combination of low functional distance and high net growth potential of predators. Under such conditions, community-level biomass variability peaks, with major negative consequences for reliability of ecosystem function.
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 density of organisms declines with size, because larger organisms need more energy than smaller ones and energetic losses occur when larger organisms feed on smaller ones. A potential expression of density-size distributions are Normalized Biomass Size Spectra (NBSS), which plot the logarithm of biomass independent of taxonomy within bins of logarithmic organismal size, divided by the bin width. Theoretically, the NBSS slope of multi-trophic communities is exactly - 1.0 if the trophic transfer efficiency (TTE, ratio of production rates between adjacent trophic levels) is 10% and the predator-prey mass ratio (PPMR) is fixed at 10(4). Here we provide evidence from four multi-trophic lake food webs that empirically estimated TTEs correspond to empirically estimated slopes of the respective community NBSS. Each of the NBSS considered pelagic and benthic organisms spanning size ranges from bacteria to fish, all sampled over three seasons in 1 yr. The four NBSS slopes were significantly steeper than -1.0 (range -1.14 to -1.19, with 95% CIs excluding -1). The corresponding average TTEs were substantially lower than 10% in each of the four food webs (range 1.0% to 3.6%, mean 1.85%). The overall slope merging all biomass-size data pairs from the four systems (-1.17) was almost identical to the slope predicted from the arithmetic mean TTE of the four food webs (-1.18) assuming a constant PPMR of 10(4). Accordingly, our empirical data confirm the theoretically predicted quantitative relationship between TTE and the slope of the biomass-size distribution. Furthermore, we show that benthic and pelagic organisms can be merged into a community NBSS, but future studies have yet to explore potential differences in habitat-specific TTEs and PPMRs. We suggest that community NBSS may provide valuable information on the structure of food webs and their energetic pathways, and can result in improved accuracy of TTE-estimates.
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.
The amount of terrestrial particulate organic matter (t-POM) entering lakes is predicted to increase as a result of climate change. This may especially alter the structure and functioning of ecosystems in small, shallow lakes which can rapidly shift from a clear-water, macrophyte-dominated into a turbid, phytoplankton-dominated state. We used the integrative ecosystem model PCLake to predict how rising t-POM inputs affect the resilience of the clear-water state. PCLake links a pelagic and benthic food chain with abiotic components by a number of direct and indirect effects. We focused on three pathways (zoobenthos, zooplankton, light availability) by which elevated t-POM inputs (with and without additional nutrients) may modify the critical nutrient loading thresholds at which a clear-water lake becomes turbid and vice versa. Our model results show that (1) increased zoobenthos biomass due to the enhanced food availability results in more benthivorous fish which reduce light availability due to bioturbation, (2) zooplankton biomass does not change, but suspended t-POM reduces the consumption of autochthonous particulate organic matter which increases the turbidity, and (3) the suspended t-POM reduces the light availability for submerged macrophytes. Therefore, light availability is the key process that is indirectly or directly changed by t-POM input. This strikingly resembles the deteriorating effect of terrestrial dissolved organic matter on the light climate of lakes. In all scenarios, the resilience of the clear-water state is reduced thus making the turbid state more likely at a given nutrient loading. Therefore, our study suggests that rising t-POM input can add to the effects of climate warming making reductions in nutrient loadings even more urgent.
Spatial correlations in environmental stochasticity can synchronize populations over wide areas, a phenomenon known as the Moran effect. The Moran effect has been confirmed in field, laboratory and theoretical investigations. Little is known, however, about the Moran effect in a common ecological case, when environmental variation is temporally autocorrelated and this autocorrelation varies spatially. Here we perform chemostat experiments to investigate the temporal response of independent phytoplankton populations to autocorrelated stochastic forcing. In contrast to naive expectation, two populations without direct coupling can be more strongly correlated than their environmental forcing (enhanced Moran effect), if the stochastic variations differ in their autocorrelation. Our experimental findings are in agreement with numerical simulations and analytical calculations. The enhanced Moran effect is robust to changes in population dynamics, noise spectra and different measures of correlation-suggesting that noise-induced synchrony may play a larger role for population dynamics than previously thought.
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.
Estimating production in plankton food webs from biomass size spectra and allometric relationships
(2000)
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.
In large and deep Lake Constance, total phosphorus concentrations during winter mixing (TPmix) were reduced by a factor of three (> 80 to ca. 30 ;g/l) from about 1979 to 1993. This resulted in an amplification and lengthening of phosphorus (P) depleted conditions throughout the season and water column. The response of the phytoplankton community depended on the time of the year and the level of aggregation under consideration. Total phytoplankton biomass quantified in terms of algal biovolume or chlorophyll concentrations decreased in summer, i. e. during the period of most severe P depletion, to about half of the original values during the first decade. In subsequent years, summer chlorophyll concentrations remained at this lower level whereas total biovolume increased again despite further decreases of TPmix. Average algal biomass in spring and autumn fluctuated without a distinct relationship to TPmix although P was depleted below the detection level during parts of these time intervals in recent years. This moderate response by community level parameters is attributed to changes in the temporal and internal organization of the algal community. Population dynamics and the relative importance of various taxonomical and functional groups such as mixotrophs and less-edible forms clearly changed in spring and summer. The renewed increase in algal biovolume in summer is mostly caused by species which are able to exploit additional P sources. For example, Dinobryon is an evidently mixotrophic organism which ingests P rich bacteria, its strongest competitors for soluble reactive phosphorus (SRP). Ceratium hirundinella might be migrating between the euphotic zone and deeper, P enriched water layers under suitable hydrodynamical conditions. At the level of genera and higher taxa, consistent trends in respect to TPmix were observed in spring and summer mostly indicating an adaptation to more oligotrophic conditions. In contrast, the functional group of well-edible algae showed little interannual variability and did not change in absolute numbers. This suggests that, in contrast to less-edible algae, well-edible forms are more strongly under top-down than bottom-up control, and that the nutritional basis of most herbivores changed less than it would be expected from the decrease in total algal biomass.
Biodiversity decline causes a loss of functional diversity, which threatens ecosystems through a dangerous feedback loop: This loss may hamper ecosystems’ ability to buffer environmental changes, leading to further biodiversity losses. In this context, the increasing frequency of human-induced excessive loading of nutrients causes major problems in aquatic systems. Previous studies investigating how functional diversity influences the response of food webs to disturbances have mainly considered systems with at most two functionally diverse trophic levels. We investigated the effects of functional diversity on the robustness, that is, resistance, resilience, and elasticity, using a tritrophic—and thus more realistic—plankton food web model. We compared a non-adaptive food chain with no diversity within the individual trophic levels to a more diverse food web with three adaptive trophic levels. The species fitness differences were balanced through trade-offs between defense/growth rate for prey and selectivity/half-saturation constant for predators. We showed that the resistance, resilience, and elasticity of tritrophic food webs decreased with larger perturbation sizes and depended on the state of the system when the perturbation occurred. Importantly, we found that a more diverse food web was generally more resistant and resilient but its elasticity was context-dependent. Particularly, functional diversity reduced the probability of a regime shift toward a non-desirable alternative state. The basal-intermediate interaction consistently determined the robustness against a nutrient pulse despite the complex influence of the shape and type of the dynamical attractors. This relationship was strongly influenced by the diversity present and the third trophic level. Overall, using a food web model of realistic complexity, this study confirms the destructive potential of the positive feedback loop between biodiversity loss and robustness, by uncovering mechanisms leading to a decrease in resistance, resilience, and potentially elasticity as functional diversity declines.
Biodiversity decline causes a loss of functional diversity, which threatens ecosystems through a dangerous feedback loop: This loss may hamper ecosystems’ ability to buffer environmental changes, leading to further biodiversity losses. In this context, the increasing frequency of human-induced excessive loading of nutrients causes major problems in aquatic systems. Previous studies investigating how functional diversity influences the response of food webs to disturbances have mainly considered systems with at most two functionally diverse trophic levels. We investigated the effects of functional diversity on the robustness, that is, resistance, resilience, and elasticity, using a tritrophic—and thus more realistic—plankton food web model. We compared a non-adaptive food chain with no diversity within the individual trophic levels to a more diverse food web with three adaptive trophic levels. The species fitness differences were balanced through trade-offs between defense/growth rate for prey and selectivity/half-saturation constant for predators. We showed that the resistance, resilience, and elasticity of tritrophic food webs decreased with larger perturbation sizes and depended on the state of the system when the perturbation occurred. Importantly, we found that a more diverse food web was generally more resistant and resilient but its elasticity was context-dependent. Particularly, functional diversity reduced the probability of a regime shift toward a non-desirable alternative state. The basal-intermediate interaction consistently determined the robustness against a nutrient pulse despite the complex influence of the shape and type of the dynamical attractors. This relationship was strongly influenced by the diversity present and the third trophic level. Overall, using a food web model of realistic complexity, this study confirms the destructive potential of the positive feedback loop between biodiversity loss and robustness, by uncovering mechanisms leading to a decrease in resistance, resilience, and potentially elasticity as functional diversity declines.
1. Improving the mechanistic basis of biodiversity-ecosystem function relationships requires a better understanding of how functional traits drive the dynamics of populations. For example, environmental disturbances or grazing may increase synchronization of functionally similar species, whereas functionally different species may show independent dynamics, because of different responses to the environment. Competition for resources, on the other hand, may yield a wide range of dynamic patterns among competitors and lead functionally similar and different species to display synchronized to compensatory dynamics. The mixed effect of these forces will influence the temporal fluctuations of populations and, thus, the variability of aggregate community properties.
2. To search for a relationship between functional and dynamics similarity, we studied the relationship between functional trait similarity and temporal dynamics similarity for 36 morphotypes of phytoplankton using long-term high-frequency measurements.
3. Our results show that functionally similar morphotypes exhibit dynamics that are more synchronized than those of functionally dissimilar ones. Functionally dissimilar morphotypes predominantly display independent temporal dynamics. This pattern is especially strong when short time-scales are considered.
4. Negative correlations are present among both functionally similar and dissimilar phytoplankton morphotypes, but are rarer and weaker than positive ones over all temporal scales.
5. Synthesis. We demonstrate that diversity in functional traits decreases community variability and ecosystem-level properties by decoupling the dynamics of individual morphotypes.
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.
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.
1. Models aim to predict phytoplankton dynamics based on observed initial conditions and a set of equations and parameters. However, our knowledge about initial conditions in nature is never perfect. Thus, if phytoplankton dynamics are sensitive to small variations in initial conditions, they are difficult to predict. 2. We used time-series data from indoor mesocosm experiments with natural phyto- and zooplankton communities to quantify the extent to which small initial differences in the species, functional group and community biomass in parallel treatments were amplified or buffered over time. We compared the differences in dynamics between replicates and among all mesocosms of 1year. 3. Temperature-sensitive grazing during the exponential growth phase of phytoplankton caused divergence. In contrast, negative density dependence caused convergence. 4. Mean differences in biomass between replicates were similar for all hierarchical levels. This indicates that differences in their initial conditions were amplified to the same extent. Even though large differences in biomass occasionally occurred between replicates for a short time, dynamics returned to the same path at all hierarchical levels. This suggests that internal feedback mechanisms make the spring development of phytoplankton highly predictable.
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.
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.
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
The individual functional traits of different species play a key role for ecosystem function in aquatic and terrestrial systems. We modeled a multispecies predator-prey system with functionally different predator and prey species based on observations of the community dynamics of ciliates and their algal prey in Lake Constance. The model accounted for differences in predator feeding preferences and prey susceptibility to predation, and for the respective trade-offs. A low food demand of the predator was connected to a high food selectivity, and a high growth rate of the prey was connected to a high vulnerability to grazing. The data and the model did not show standard uniform predator- prey cycles, but revealed both complex dynamics and a coexistence of predator and prey at high biomass levels. These dynamics resulted from internally driven alternations in species densities and involved compensatory dynamics between functionally different species. Functional diversity allowed for ongoing adaptation of the predator and prey communities to changing environmental conditions such as food composition and grazing pressure. The trade-offs determined whether compensatory or synchronous dynamics occurred which influence the variability at the community level. Compensatory dynamics were promoted by a joint carrying capacity linking the different prey species which is particularly relevant at high prey biomasses, i.e., when grazers are less efficient. In contrast, synchronization was enhanced by the coupling of the different predator and prey species via common feeding links, e.g., by a high grazing pressure of a nonselective predator. The communities had to be functionally diverse in terms of their trade-offs and their traits to yield compensatory dynamics. Rather similar predator species tended to cycle synchronously, whereas profoundly different species did not coexist. Compensatory dynamics at the community level thus required intermediately strong tradeoffs for functional traits in both predators and their prey.
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.
Trait variation among heterospecific and conspecific organisms may substantially affect community and food web dynamics. While the relevance of competition and feeding traits have been widely studied for different consumer species, studies on intraspecific differences are more scarce, partly owing to difficulties in distinguishing different clones of the same species. Here, we investigate how intraspecific trait variation affects the competition between the freshwater ciliates Euplotes octocarinatus and Coleps hirtus in a nitrogen-limited chemostat system. The ciliates competed for the microalgae Cryptomonas sp. (Cry) and Navicula pelliculosa (Nav), and the bacteria present in the cultures over a period of 33 days. We used monoclonal Euplotes and three different Coleps clones (Col 1, Col 2, and Col 3) in the experiment that could be distinguished by a newly developed rDNA-based molecular assay based on the internal transcribed spacer (ITS) regions. While Euplotes feeds on Cry and on bacteria, the Coleps clones cannot survive on bacteria alone but feed on both Cry and Nav with clone-specific rates. Experimental treatments comprised two-species mixtures of Euplotes and one or all of the three different Coleps clones, respectively. We found intraspecific variation in the traits "selectivity" and "maximum ingestion rate" for the different algae to significantly affect the competitive outcome between the two ciliate species. As Nav quickly escaped top-down control and likely reached a state of low food quality, ciliate competition was strongly determined by the preference of different Coleps clones for Cry as opposed to feeding on Nav. In addition, the ability of Euplotes to use bacteria as an alternative food source strengthened its persistence once Cry was depleted. Hence, trait variation at both trophic levels codetermined the population dynamics and the outcome of species competition.
Lake morphometry and wind exposure may shape the plankton community structure in acidic mining lakes
(2010)
Acidic mining lakes (pH <3) are specific habitats exhibiting particular chemical and biological characteristics. The species richness is low and mixotrophy and omnivory are common features of the plankton food web in such lakes. The plankton community structure of mining lakes of different morphometry and mixing type but similar chemical characteristics (Lake 130, Germany and Lake Langau, Austria) was investigated. The focus was laid on the species composition, the trophic relationship between the phago-mixotrophic flagellate Ochromonas sp. and bacteria and the formation of a deep chlorophyll maximum along a vertical pH-gradient. The shallow wind-exposed Lake 130 exhibited a higher species richness than Lake Langau. This increase in species richness was made up mainly by mero-planktic species, suggesting a strong benthic/littoral - pelagic coupling. Based on the field data from both lakes, a nonlinear, negative relation between bacteria and Ochromonas biomass was found, suggesting that at an Ochromonas biomass below 50 mu g CL-1. the grazing pressure on bacteria is low and with increasing Ochromonas biomass bacteria decline. Furthermore, in Lake Langau, a prominent deep chlorophyll maximum was found with chlorophyll concentrations ca. 50 times higher than in the epilimnion which was build up by the euglenophyte Lepocinclis sp. We conclude that lake morphometry, and specific abiotic characteristics such as mixing behaviour influence the community structure in these mining lakes.
The importance of ciliates as herbivores and in biogeochemical cycles is increasingly recognized. An opportunity to observe the potential consequences of zooplankton dominated by ciliates arose when winter fish kills resulted in strong suppression of crustaceans by young planktivorous fish in two shallow lakes. On an annual average, ciliates made up 38-76% of the total zooplankton biomass in both lakes during two subsequent years. Consequently, ciliate biomass and their estimated grazing potential were extremely high compared with other lakes of various trophic states and depths. Grazing estimates based on abundance and size suggest that ciliates should have cleared the water column of small (<5 mu m) and intermediate (5-50 mu m) sized phytoplankton more than once a day. Especially, small feeders within the ciliates were important, likely exerting a strong top-down control on small phytoplankton. Particle-attached bacteria were presumably strongly suppressed by intermediate-sized ciliate feeders. In contrast to other lakes, large phytoplankton was proportionately very abundant. The phytoplankton community had a high evenness, which may be attributed to the feeding by numerous fast growing and selective ciliate species. Our study highlights ciliates as an important trophic link and adds to the growing awareness of the role of winter processes for plankton dynamics.
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.