Refine
Year of publication
Document Type
- Article (105) (remove)
Keywords
- functional traits (6)
- population dynamics (5)
- coexistence (4)
- community ecology (4)
- phytoplankton (4)
- predator-prey dynamics (4)
- Phytoplankton (3)
- biodiversity (3)
- functional diversity (3)
- lake (3)
- plankton (3)
- top-down control (3)
- Coadaptation (2)
- Eco-evolutionary dynamics (2)
- Fish (2)
- chemostat experiments (2)
- coevolution (2)
- compensatory dynamics (2)
- competition (2)
- defense against predation (2)
- eco-evolutionary feedbacks (2)
- ecoevolutionary dynamics (2)
- equalizing and stabilizing mechanisms (2)
- fitness (2)
- functional response (2)
- indirect facilitation (2)
- maintenance of functional diversity (2)
- neutrality (2)
- niche and fitness differences (2)
- predator-prey model (2)
- stability (2)
- supersaturated species coexistence (2)
- synchrony (2)
- temporal dynamics (2)
- time series analysis (2)
- trait convergence and divergence (2)
- Activity respiration (1)
- Adaptive traits (1)
- Allelopathy (1)
- Allometric Trophic Network model (1)
- Allometric trophic network model (1)
- Allometry (1)
- Anoxia (1)
- Bayesian inference (1)
- Behaviour (1)
- Chlamydomonas (1)
- Chlorella vulgaris (1)
- Communities as complex adaptive systems (1)
- Community dynamics (1)
- Competition (1)
- Complex dynamics (1)
- Compositional data analysis (1)
- DCM (1)
- Ecotoxicology (1)
- Energy transfer (1)
- Extreme environment (1)
- Fitness gradient (1)
- Fitness landscape and frequency-dependent selection (1)
- Food web (1)
- Freshwater ecosystem (1)
- Global warming (1)
- Growth (1)
- Intermittent cycles (1)
- Iron toxicity (1)
- Lake Constance (1)
- Lumpiness in pattern formation and self-organization (1)
- Modelling functional diversity (1)
- Moment closure (1)
- Moment closure for trait-based aggregate model approaches (1)
- Multimodal trait distributions (1)
- Normal and beta distribution (1)
- PCLake (1)
- Phase relationships (1)
- Phosphate limitation (1)
- Photosynthesis (1)
- Predation (1)
- Predator-prey cycles (1)
- Regime shifts (1)
- Roach (1)
- Shallow lakes (1)
- Shape of trade-offs and stabilizing and disruptive selection (1)
- Size distribution (1)
- Skewed and peaked trait distributions (1)
- Species range shift (1)
- Submerged macrophytes (1)
- Trophic interactions (1)
- Trophic transfer efficiency (1)
- Zooplankton (1)
- adaptive processes (1)
- algae (1)
- allochthony (1)
- alternative stable states (1)
- analysis (1)
- aquatic (1)
- bacterial production (1)
- benthic food chain (1)
- benthic food web (1)
- bifurcation (1)
- biofilm (1)
- bistability (1)
- carbon budget (1)
- ciliate predators (1)
- ciliates (1)
- climate (1)
- climate change (1)
- climate warming (1)
- community (1)
- competition-defense trade-off (1)
- competition–defense trade‐off (1)
- consumer diversity (1)
- critical nutrient loading (1)
- crustaceans (1)
- cyanobacteria (1)
- cyclops vicinus (1)
- diatoms (1)
- disturbance (1)
- divergence (1)
- diversity (1)
- dynamics (1)
- early-warning signals (1)
- ecological efficiency (1)
- ecosystem functioning (1)
- ecosystem modeling (1)
- ecosystem services (1)
- eicosapentaenoic acid (1)
- empirical dynamic modelling (1)
- energetic equivalence rule (1)
- environmental changes (1)
- environmental forcing (1)
- eutrophication (1)
- evolution (1)
- evolutionary rescue (1)
- experimental evolution (1)
- exploitation (1)
- exploitative competition (1)
- fatty acids (1)
- feeding trait (1)
- filtration rate (1)
- fisheries (1)
- food web (1)
- food web dynamics (1)
- food webs (1)
- food-web efficiency (1)
- food-web models (1)
- forecasting (1)
- freshwater (1)
- global change (1)
- grazing (1)
- grazing defence (1)
- hierarchical level (1)
- host-parasite interaction (1)
- hydrology (1)
- inducible defense (1)
- information theory (1)
- interference competition (1)
- intransitivity (1)
- intraspecific trait (1)
- intraspecific trait variation (1)
- invasion boundary (1)
- land-water coupling (1)
- life-cycle (1)
- light (1)
- lumpy coexistence (1)
- machine learning (1)
- maintenance (1)
- management (1)
- marine (1)
- mechanisms (1)
- mesocosms (1)
- metabolic theory (1)
- metabolic theory of ecology (1)
- microalgal resource (1)
- mitigation (1)
- model integration (1)
- model limitations (1)
- multi-trophic communities (1)
- multi-trophic dynamics (1)
- natural rotifer (1)
- non-linear dynamics (1)
- normalized biomass size spectra (1)
- nutrient (1)
- nutrient spike (1)
- nutrients (1)
- ordinary differential equation (1)
- parameter estimation (1)
- pelagic and benthic lake habitats (1)
- pelagic food chain (1)
- pelagic food web (1)
- permutation entropy (1)
- phage resistance (1)
- phenotypic plasticity (1)
- plant population and community dynamics (1)
- population (1)
- population cycles (1)
- predator (1)
- predator prey (1)
- predator trait variation (1)
- predator-prey cycles (1)
- predator-prey interaction (1)
- predator-prey system (1)
- predator-prey systems (1)
- predator–prey cycles (1)
- predictability (1)
- prediction (1)
- production (1)
- production rates (1)
- protozoa (1)
- pulse perturbation (1)
- quantitative food webs (1)
- random forest (1)
- rapid evolution (1)
- regime shift (1)
- regime shifts (1)
- replicates (1)
- resource competition (1)
- robustness (1)
- rotifers (1)
- seasonal plankton succession (1)
- seasonality (1)
- shape (1)
- size of organisms (1)
- spatial (1)
- species richness (1)
- species supersaturated assemblages (1)
- stable isotopes (1)
- stable states (1)
- stage structure (1)
- stoichiometry (1)
- synchronization (1)
- t-POM (1)
- temperature (1)
- temporal variability (1)
- terrestrial subsidy (1)
- time series (1)
- top (1)
- trade-offs (1)
- trait adaptation (1)
- trait distribution (1)
- trait diversity (1)
- trait dynamics (1)
- trait variability (1)
- transient dynamics (1)
- tritrophic food web (1)
- trophic cascades (1)
- trophic position (1)
- trophic transfer efficiency (1)
- understanding (1)
- variation (1)
- winter fish kill (1)
- zooplankton (1)
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.
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.
The shape of a defense-growth trade-off governs seasonal trait dynamics in natural phytoplankton
(2020)
Theory predicts that trade-offs, quantifying costs of functional trait adjustments, crucially affect community trait adaptation to altered environmental conditions, but empirical verification is scarce. We evaluated trait dynamics (antipredator defense, maximum growth rate, and phosphate affinity) of a lake phytoplankton community in a seasonally changing environment, using literature trait data and 21 years of species-resolved high-frequency biomass measurements. The trait data indicated a concave defense-growth trade-off, promoting fast-growing species with intermediate defense. With seasonally increasing grazing pressure, the community shifted toward higher defense levels at the cost of lower growth rates along the trade-off curve, while phosphate affinity explained some deviations from it. We discuss how low fitness differences of species, inferred from model simulations, in concert with stabilizing mechanisms, e.g., arising from further trait dimensions, may lead to the observed phytoplankton diversity. In conclusion, quantifying trade-offs is key for predictions of community trait adaptation and biodiversity under environmental change.
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
Large (472 km2) and deep (zmean=101 m) Lake Constance is undergoing re-oligotrophication. Total phosphorus during winter mixing (TPmix) decreased from >80 during 1975-1981 to 22 ;g/l in 1996. Average summer values of secchi and euphotic depth increased significantly from 4.5 to 6.5 m and from 10.5 to 13 m, respectively. The algal species composition changed and, during summer, total algal biomass decreased by 50 % and primary production by 25 %. Standing stocks of well-edible algae, rotifers, and herbivorous and carnivorous crustaceans did not exhibit a trend with TPmix, whereas their species compositions or egg-ratios were partially altered. The age-at-capture of planktivorous whitefish increased slightly. I tested the hypotheses that (1) changes should first be observed at the level of individuals or within species (altering e. g. C:P or egg-ratios) prior to changes within communities (affecting e. g. the taxonomic composition) and at the community level (affecting e. g. total biomass or production). This would imply that it is more appropriate to conceptualize step-wise responses along a hierarchical gradient of increasing aggregation as suggested by hierarchy theory, rather than simultaneous changes at all hierarchical levels. (2) Responses become dampened along the food chain and with increasing body size, i. e. bottom-up control is most important for autotrophs. All communities studied (phytoplankton, crustaceans, fish) reacted at the individual level (e. g. by changes of (re)production rates), and/or within the community (e. g. altered taxonomic composition) whereas changes of bulk parameters of the entire community were restricted to phytoplankton. Hence, the first hypothesis is partially supported by the observed reactions and demands further testing. The second hypothesis is clearly supported by our data when comparing autotrophs and consumers, but not when comparing crustaceans and fish. The testing of these hypotheses is complicated by the large differences in size and, consequently, in reaction times of pelagic organisms on the one hand and the rather fixed time scale of limnological research on the other hand. The different time scales imply a selective perception of the various potential responses of the differently sized organisms as the time scales of the responses depend on body size and the level of aggregation. For example, we are more likely to establish physiological or behaviourial changes of fish, and taxonomical or biomass changes of phytoplankton. Acknowledging the scale dependence and level of aggregation is also crucial for cross-system comparisons.
The intrinsic predictability of ecological time series and its potential to guide forecasting
(2019)
Phytoplankton dynamics in a shallow eutrophic lake were investigated over a 3-year period with respect to environmental forces which drive species composition and diversity. Diversity was calculated on the basis of species as well as on the basis of their functional properties (the C-R-S-concept). Stratification and water column mixing had a strong impact on phytoplankton composition. Application of a similarity-diversity model revealed that a high diversity was a transient non-stable state, whereas drastic changes or long-lasting stable environmental conditions are characterized by low diversity. This effect was more pronounced when the diversity was calculated on the basis of the phytoplankton species functional properties. Thus, this functional approach supports the intermediate disturbance hypothesis from field data.
Long-term measurements (1979-1994) of meteorological parameters and of algal and crustacean biomass were used in conjunction with a comprehensive hydrodynamic model to evaluate the impact of weather conditions on plankton dynamics in a large, deep, temperate lake (Upper Lake Constance), and to identify potential causal mechanisms. The natural variability of weather conditions, including the exceptionally mild winters during the late eighties, allowed us the investigation of the covariation of meteorological parameters such as irradiance, air temperature, and wind with vernal algal and crustacean population growth. Crustacean zooplankton responded strongly to differences in surface water temperature, but not to mixing depth or algal biomass. Clear relationships between changes of algal biomass and meteorological factors were only found during the rare occasions when acted together to favour or hamper algal development. Otherwise, the impact of meterological conditions on the physical conditions which were most likely conducive to phytoplankton development, could not be followed by this simple approach. This problem was overcome with a one-dimensional hydrodynamic turbulent exchange model driven by the meteorological boundary conditions at the water surface. It was used to simulate the development of the vernal density stratification and to investigate the relationships between meteorological conditions and exchange rates from the euphotic to the aphotic zone. The beginning of the spring algal bloom was shown to depend on the stabilization of the upper part of the water column. As soon as mixing below 20 m was inhibited, confining the algae to the euphotic zone for prolonged periods of time, substantial increases in algal standing stock occurred consistently. In contrast, during periods when high vertical mixing rates were computed with the model no substantial increases of algal biomass were found. This tight coupling between the estimates of vertical mixing intensity and observed algal development, combined with knowledge about the impact of individual meteorological factors on mixing, enabled predictions about the response of algae to different weather conditions during spring.
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.
Spring algal development in deep temperate lakes is thought to be strongly influenced by surface irradiance, vertical mixing and temperature, all of which are expected to be altered by climate change. Based on long-term data from Lake Constance, we investigated the individual and combined effects of these variables on algal dynamics using descriptive statistics, multiple regression models and a processoriented dynamic simulation model. The latter considered edible and less-edible algae and was forced by observed or anticipated irradiance, temperature and vertical mixing intensity. Unexpectedly, irradiance often dominated algal net growth rather than vertical mixing for the following reason: algal dynamics depended on algal net losses from the euphotic layer to larger depth due to vertical mixing. These losses strongly depended on the vertical algal gradient which, in turn, was determined by the mixing intensity during the previous days, thereby introducing a memory effect. This observation implied that during intense mixing that had already reduced the vertical algal gradient, net losses due to mixing were small. Consequently, even in deep Lake Constance, the reduction in primary production due to low light was often more influential than the net losses due to mixing. In the regression model, the dynamics of small, fast-growing algae was best explained by vertical mixing intensity and global irradiance, whereas those of larger algae were best explained by their biomass 1 week earlier. The simulation model additionally revealed that even in late winter grazing may represent an important loss factor during calm periods when losses due to mixing are small. The importance of losses by mixing and grazing changed rapidly as it depended on the variable mixing intensity. Higher temperature, lower global irradiance and enhanced mixing generated lower algal biomass and primary production in the dynamic simulation model. This suggests that potential consequences of climate change may partly counteract each other.