@misc{SiblyGrimmMartinetal.2013,
  author    = {Sibly, Richard M. and Grimm, Volker and Martin, Benjamin T. and Johnston, Alice S. A. and Kulakowska, Katarzyna and Topping, Christopher J. and Calow, Peter and Nabe-Nielsen, Jacob and Thorbek, Pernille and DeAngelis, Donald L.},
  title     = {Representing the acquisition and use of energy by individuals in agent-based models of animal populations},
  series = {Methods in ecology and evolution : an official journal of the British Ecological Society},
  volume    = {4},
  journal   = {Methods in ecology and evolution : an official journal of the British Ecological Society},
  number    = {2},
  publisher = {Wiley-Blackwell},
  address   = {Hoboken},
  issn      = {2041-210X},
  doi       = {10.1111/2041-210x.12002},
  pages     = {151 -- 161},
  year      = {2013},
  abstract  = {Agent-based models (ABMs) are widely used to predict how populations respond to changing environments. As the availability of food varies in space and time, individuals should have their own energy budgets, but there is no consensus as to how these should be modelled. Here, we use knowledge of physiological ecology to identify major issues confronting the modeller and to make recommendations about how energy budgets for use in ABMs should be constructed. Our proposal is that modelled animals forage as necessary to supply their energy needs for maintenance, growth and reproduction. If there is sufficient energy intake, an animal allocates the energy obtained in the order: maintenance, growth, reproduction, energy storage, until its energy stores reach an optimal level. If there is a shortfall, the priorities for maintenance and growth/reproduction remain the same until reserves fall to a critical threshold below which all are allocated to maintenance. Rates of ingestion and allocation depend on body mass and temperature. We make suggestions for how each of these processes should be modelled mathematically. Mortality rates vary with body mass and temperature according to known relationships, and these can be used to obtain estimates of background mortality rate. If parameter values cannot be obtained directly, then values may provisionally be obtained by parameter borrowing, pattern-oriented modelling, artificial evolution or from allometric equations. The development of ABMs incorporating individual energy budgets is essential for realistic modelling of populations affected by food availability. Such ABMs are already being used to guide conservation planning of nature reserves and shell fisheries, to assess environmental impacts of building proposals including wind farms and highways and to assess the effects on nontarget organisms of chemicals for the control of agricultural pests.},
  language  = {en}
}
@phdthesis{Schaefer2019,
  author    = {Sch{\"a}fer, Merlin},
  title     = {Understanding and predicting global change impacts on migratory birds},
  doi       = {10.25932/publishup-43925},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-439256},
  school      = {Universit{\"a}t Potsdam},
  pages     = {XIV, 153},
  year      = {2019},
  abstract  = {This is a publication-based dissertation comprising three original research stud-ies (one published, one submitted and one ready for submission; status March 2019). The dissertation introduces a generic computer model as a tool to investigate the behaviour and population dynamics of animals in cyclic environments. The model is further employed for analysing how migratory birds respond to various scenarios of altered food supply under global change. Here, ecological and evolutionary time-scales are considered, as well as the biological constraints and trade-offs the individual faces, which ultimately shape response dynamics at the population level. Further, the effect of fine-scale temporal patterns in re-source supply are studied, which is challenging to achieve experimentally. My findings predict population declines, altered behavioural timing and negative carry-over effects arising in migratory birds under global change. They thus stress the need for intensified research on how ecological mechanisms are affected by global change and for effective conservation measures for migratory birds. The open-source modelling software created for this dissertation can now be used for other taxa and related research questions. Overall, this thesis improves our mechanistic understanding of the impacts of global change on migratory birds as one prerequisite to comprehend ongoing global biodiversity loss. The research results are discussed in a broader ecological and scientific context in a concluding synthesis chapter.},
  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{RodriguezSanchezWucherpfennigRischkeetal.2023,
  author    = {Rodr{\´i}guez S{\´a}nchez, Alejandra and Wucherpfennig, Julian and Rischke, Ramona and Iacus, Stefano Maria},
  title     = {Search-and-rescue in the Central Mediterranean Route does not induce migration},
  series = {Scientific reports},
  volume    = {13},
  journal   = {Scientific reports},
  number    = {1},
  publisher = {Macmillan Publishers Limited, part of Springer Nature},
  address   = {London},
  issn      = {2045-2322},
  doi       = {10.1038/s41598-023-38119-4},
  pages     = {1},
  year      = {2023},
  abstract  = {State- and private-led search-and-rescue are hypothesized to foster irregular migration (and thereby migrant fatalities) by altering the decision calculus associated with the journey. We here investigate this 'pull factor' claim by focusing on the Central Mediterranean route, the most frequented and deadly irregular migration route towards Europe during the past decade. Based on three intervention periods—(1) state-led Mare Nostrum, (2) private-led search-and-rescue, and (3) coordinated pushbacks by the Libyan Coast Guard—which correspond to substantial changes in laws, policies, and practices of search-and-rescue in the Mediterranean, we are able to test the 'pull factor' claim by employing an innovative machine learning method in combination with causal inference. We employ a Bayesian structural time-series model to estimate the effects of these three intervention periods on the migration flow as measured by crossing attempts (i.e., time-series aggregate counts of arrivals, pushbacks, and deaths), adjusting for various known drivers of irregular migration. We combine multiple sources of traditional and non-traditional data to build a synthetic, predicted counterfactual flow. Results show that our predictive modeling approach accurately captures the behavior of the target time-series during the various pre-intervention periods of interest. A comparison of the observed and predicted counterfactual time-series in the post-intervention periods suggest that pushback policies did affect the migration flow, but that the search-and-rescue periods did not yield a discernible difference between the observed and the predicted counterfactual number of crossing attempts. Hence we do not find support for search-and-rescue as a driver of irregular migration. In general, this modeling approach lends itself to forecasting migration flows with the goal of answering causal queries in migration research.},
  language  = {en}
}
@misc{ReilRosenfeldImholtetal.2017,
  author    = {Reil, Daniela and Rosenfeld, Ulrike M. and Imholt, Christian and Schmidt, Sabrina and Ulrich, Rainer G. and Eccard, Jana and Jacob, Jens},
  title     = {Puumala hantavirus infections in bank vole populations},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {957},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-43123},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-431232},
  pages     = {15},
  year      = {2017},
  abstract  = {Background In Europe, bank voles (Myodes glareolus) are widely distributed and can transmit Puumala virus (PUUV) to humans, which causes a mild to moderate form of haemorrhagic fever with renal syndrome, called nephropathia epidemica. Uncovering the link between host and virus dynamics can help to prevent human PUUV infections in the future. Bank voles were live trapped three times a year in 2010-2013 in three woodland plots in each of four regions in Germany. Bank vole population density was estimated and blood samples collected to detect PUUV specific antibodies. Results We demonstrated that fluctuation of PUUV seroprevalence is dependent not only on multi-annual but also on seasonal dynamics of rodent host abundance. Moreover, PUUV infection might affect host fitness, because seropositive individuals survived better from spring to summer than uninfected bank voles. Individual space use was independent of PUUV infections. Conclusions Our study provides robust estimations of relevant patterns and processes of the dynamics of PUUV and its rodent host in Central Europe, which are highly important for the future development of predictive models for human hantavirus infection risk.},
  language  = {en}
}
@article{ReilBinderFreiseetal.2018,
  author    = {Reil, Daniela and Binder, Florian and Freise, Jona and Imholt, Christian and Beyrers, Konrad and Jacob, Jens and Kr{\"u}ger, Detlev H. and Hofmann, J{\"o}rg and Dreesman, Johannes and Ulrich, Rainer G{\"u}nter},
  title     = {Hantaviren in Deutschland},
  series = {Berliner und M{\"u}nchener tier{\"a}rztliche Wochenschrift},
  volume    = {131},
  journal   = {Berliner und M{\"u}nchener tier{\"a}rztliche Wochenschrift},
  number    = {11-12},
  publisher = {Schl{\"u}tersche Verlagsgesellschaft mbH \& Co. KG.},
  address   = {Hannover},
  issn      = {0005-9366},
  doi       = {10.2376/0005-9366-18003},
  pages     = {453 -- 464},
  year      = {2018},
  abstract  = {Hantaviruses are small mammal-associated pathogens that are found in rodents but also in shrews, moles and bats. Aim of this manuscript is to give a current overview of the epidemiology and ecology of hantaviruses in Germany and to discuss respective models for the prediction of virus outbreaks. In Germany the majority of human disease cases are caused by the Puumala virus (PUUV), transmitted by the bank vole (Myodes glareolus). PUUV is associated with the Western evolutionary lineage of the bank vole and is not present in the eastern and northern parts of Germany. A second human pathogenic hantavirus is the Dobrava-Belgrade virus (DOBV), genotype Kurkino; its reservoir host, the striped field mouse (Apodemus agrarius), is mostly occurring in the eastern part of Germany. A PUUV-related hantavirus is the rarely pathogenic Tula virus (TULV), that is associated with the common vole (Microtus arvalis). In addition, Seewis virus, Asikkala virus, and Bruges virus are shrew- and mole-associated hantaviruses with still unknown pathogenicity in humans. Human disease cases are associated with the different hantaviruses according to their regional distribution. The viruses can cause mild to severe but also subclinical courses of the respective disease. The number of human PUUV disease cases in 2007, 2010, 2012, 2015 and 2017 correlates with the occurrence of high levels of seed production of beech trees ("beech mast") in the preceding year. Models based on weather parameters for the prediction of PUUV disease clusters as developed in recent years need further validation and optimisation. in addition to the abundance of infected reservoir rodents, the exposure behaviour of humans affects the risk of human infection. The application of robust forecast models can assist the public health service to develop and communicate spatially and temporally targeted information. Thus, further recommendations to mitigate infection risk for the public may be provided.},
  language  = {de}
}
@misc{RaatzvanVelzenGaedke2018,
  author    = {Raatz, Michael and van Velzen, Ellen and Gaedke, Ursula},
  title     = {Co-adaptation impacts the robustness of predator-prey dynamics against perturbations},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {809},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-44248},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-442489},
  pages     = {16},
  year      = {2018},
  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{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{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}
}
@phdthesis{Patra2013,
  author    = {Patra, Pintu},
  title     = {Population dynamics of bacterial persistence},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-69253},
  school      = {Universit{\"a}t Potsdam},
  year      = {2013},
  abstract  = {The life of microorganisms is characterized by two main tasks, rapid growth under conditions permitting growth and survival under stressful conditions. The environments, in which microorganisms dwell, vary in space and time. The microorganisms innovate diverse strategies to readily adapt to the regularly fluctuating environments. Phenotypic heterogeneity is one such strategy, where an isogenic population splits into subpopulations that respond differently under identical environments. Bacterial persistence is a prime example of such phenotypic heterogeneity, whereby a population survives under an antibiotic attack, by keeping a fraction of population in a drug tolerant state, the persister state. Specifically, persister cells grow more slowly than normal cells under growth conditions, but survive longer under stress conditions such as the antibiotic administrations. Bacterial persistence is identified experimentally by examining the population survival upon an antibiotic treatment and the population resuscitation in a growth medium. The underlying population dynamics is explained with a two state model for reversible phenotype switching in a cell within the population. We study this existing model with a new theoretical approach and present analytical expressions for the time scale observed in population growth and resuscitation, that can be easily used to extract underlying model parameters of bacterial persistence. In addition, we recapitulate previously known results on the evolution of such structured population under periodically fluctuating environment using our simple approximation method. Using our analysis, we determine model parameters for Staphylococcus aureus population under several antibiotics and interpret the outcome of cross-drug treatment. Next, we consider the expansion of a population exhibiting phenotype switching in a spatially structured environment consisting of two growth permitting patches separated by an antibiotic patch. The dynamic interplay of growth, death and migration of cells in different patches leads to distinct regimes in population propagation speed as a function of migration rate. We map out the region in parameter space of phenotype switching and migration rate to observe the condition under which persistence is beneficial. Furthermore, we present an extended model that allows mutation from the two phenotypic states to a resistant state. We find that the presence of persister cells may enhance the probability of resistant mutation in a population. Using this model, we explain the experimental results showing the emergence of antibiotic resistance in a Staphylococcus aureus population upon tobramycin treatment. In summary, we identify several roles of bacterial persistence, such as help in spatial expansion, development of multidrug tolerance and emergence of antibiotic resistance. Our study provides a theoretical perspective on the dynamics of bacterial persistence in different environmental conditions. These results can be utilized to design further experiments, and to develop novel strategies to eradicate persistent infections.},
  language  = {en}
}