@article{MassieRyabovBlasiusetal.2013, author = {Massie, Thomas Michael and Ryabov, Alexei and Blasius, Bernd and Weithoff, Guntram and Gaedke, Ursula}, title = {Complex transient dynamics of stage-structured populations in response to environmental changes}, series = {The American naturalist : a bi-monthly journal devoted to the advancement and correlation of the biological sciences}, volume = {182}, journal = {The American naturalist : a bi-monthly journal devoted to the advancement and correlation of the biological sciences}, number = {1}, publisher = {Univ. of Chicago Press}, address = {Chicago}, issn = {0003-0147}, doi = {10.1086/670590}, pages = {103 -- 119}, year = {2013}, abstract = {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.}, language = {en} } @article{RaatzvanVelzenGaedke2019, author = {Raatz, Michael and van Velzen, Ellen and Gaedke, Ursula}, title = {Co-adaptation impacts the robustness of predator-prey dynamics against perturbations}, series = {Ecology and Evolution}, volume = {9}, journal = {Ecology and Evolution}, number = {7}, publisher = {John Wiley \& Sons}, address = {Hoboken, NJ}, issn = {2045-7758}, doi = {10.1002/ece3.5006}, pages = {3823 -- 3836}, year = {2019}, abstract = {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.}, language = {en} } @article{BauerVosKlauschiesetal.2014, author = {Bauer, Barbara and Vos, Matthijs and Klauschies, Toni and Gaedke, Ursula}, title = {Diversity, functional similarity, and top-down control drive synchronization and the reliability of ecosystem function}, series = {The American naturalist : a bi-monthly journal devoted to the advancement and correlation of the biological sciences}, volume = {183}, journal = {The American naturalist : a bi-monthly journal devoted to the advancement and correlation of the biological sciences}, number = {3}, publisher = {Univ. of Chicago Press}, address = {Chicago}, issn = {0003-0147}, doi = {10.1086/674906}, pages = {394 -- 409}, year = {2014}, abstract = {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.}, language = {en} } @article{RosenbaumRaatzWeithoffetal.2019, author = {Rosenbaum, Benjamin and Raatz, Michael and Weithoff, Guntram and Fussmann, Gregor F. and Gaedke, Ursula}, title = {Estimating parameters from multiple time series of population dynamics using bayesian inference}, series = {Frontiers in ecology and evolution}, volume = {6}, journal = {Frontiers in ecology and evolution}, publisher = {Frontiers Research Foundation}, address = {Lausanne}, issn = {2296-701X}, doi = {10.3389/fevo.2018.00234}, pages = {14}, year = {2019}, abstract = {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.}, language = {en} } @article{PennekampIlesGarlandetal.2019, author = {Pennekamp, Frank and Iles, Alison C. and Garland, Joshua and Brennan, Georgina and Brose, Ulrich and Gaedke, Ursula and Jacob, Ute and Kratina, Pavel and Matthews, Blake and Munch, Stephan and Novak, Mark and Palamara, Gian Marco and Rall, Bjorn C. and Rosenbaum, Benjamin and Tabi, Andrea and Ward, Colette and Williams, Richard and Ye, Hao and Petchey, Owen L.}, title = {The intrinsic predictability of ecological time series and its potential to guide forecasting}, series = {Ecological monographs : a publication of the Ecological Society of America.}, volume = {89}, journal = {Ecological monographs : a publication of the Ecological Society of America.}, number = {2}, publisher = {Wiley}, address = {Hoboken}, issn = {0012-9615}, doi = {10.1002/ecm.1359}, pages = {17}, year = {2019}, language = {en} }