TY - JOUR A1 - Bauer, Barbara A1 - Vos, Matthijs A1 - Klauschies, Toni A1 - Gaedke, Ursula T1 - Diversity, functional similarity, and top-down control drive synchronization and the reliability of ecosystem function JF - The American naturalist : a bi-monthly journal devoted to the advancement and correlation of the biological sciences N2 - 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. KW - biodiversity KW - ecosystem services KW - population dynamics KW - predator-prey system KW - species richness KW - synchrony Y1 - 2014 U6 - https://doi.org/10.1086/674906 SN - 0003-0147 SN - 1537-5323 VL - 183 IS - 3 SP - 394 EP - 409 PB - Univ. of Chicago Press CY - Chicago ER - TY - JOUR A1 - Grimm-Seyfarth, Annegret A1 - Mihoub, Jean-Baptiste A1 - Gruber, Bernd A1 - Henle, Klaus T1 - Some like it hot BT - from individual to population responses of an arboreal arid-zone gecko to local and distant climate JF - Ecological monographs N2 - Accumulating evidence has demonstrated considerable impact of climate change on biodiversity, with terrestrial ectotherms being particularly vulnerable. While climate-induced range shifts are often addressed in the literature, little is known about the underlying ecological responses at individual and population levels. Using a 30-yr monitoring study of the long-living nocturnal gecko Gehyra variegata in arid Australia, we determined the relative contribution of climatic factors acting locally (temperature, rainfall) or distantly (La Nina induced flooding) on ecological processes ranging from traits at the individual level (body condition, body growth) to the demography at population level (survival, sexual maturity, population sizes). We also investigated whether thermoregulatory activity during both active (night) and resting (daytime) periods of the day can explain these responses. Gehyra variegata responded to local and distant climatic effects. Both high temperatures and high water availability enhanced individual and demographic parameters. Moreover, the impact of water availability was scale independent as local rainfall and La Nina induced flooding compensated each other. When water availability was low, however, extremely high temperatures delayed body growth and sexual maturity while survival of individuals and population sizes remained stable. This suggests a trade-off with traits at the individual level that may potentially buffer the consequences of adverse climatic conditions at the population level. Moreover, hot temperatures did not impact nocturnal nor diurnal behavior. Instead, only cool temperatures induced diurnal thermoregulatory behavior with individuals moving to exposed hollow branches and even outside tree hollows for sun-basking during the day. Since diurnal behavioral thermoregulation likely induced costs on fitness, this could decrease performance at both individual and population level under cool temperatures. Our findings show that water availability rather than high temperature is the limiting factor in our focal population of G.variegata. In contrast to previous studies, we stress that drier rather than warmer conditions are expected to be detrimental for nocturnal desert reptiles. Identifying the actual limiting climatic factors at different scales and their functional interactions at different ecological levels is critical to be able to predict reliably future population dynamics and support conservation planning in arid ecosystems. KW - behavioral adaptation KW - body condition KW - body growth rate KW - climate change KW - El Nino Southern Oscillation (ENSO) KW - Gehyra variegata KW - population dynamics KW - population size KW - survival KW - thermoregulation Y1 - 2018 U6 - https://doi.org/10.1002/ecm.1301 SN - 0012-9615 SN - 1557-7015 VL - 88 IS - 3 SP - 336 EP - 352 PB - Wiley CY - Hoboken ER - TY - GEN A1 - Heinken, Thilo A1 - Winkler, Eckart T1 - Non-random dispersal by ants : long-term field data versus model predictions of population spread of a forest herb N2 - Myrmecochory, i.e. dispersal of seeds by ants towards and around their nests, plays an important role in temperate forests. Yet hardly any study has examined plant population spread over several years and the underlying joint contribution of a hierarchy of dispersal modes and plant demography. We used a seed-sowing approach with three replicates to examine colonization patterns of Melampyrum pratense, an annual myrmecochorous herb, in a mixed Scots pine forest in northeastern Germany. Using a spatially explicit individualbased (SEIB) model population patterns over 4 years were explained by short-distance transport of seeds by small ant species with high nest densities, resulting in random spread. However, plant distributions in the field after another 4 years were clearly deviating from model predictions. Mean annual spread rate increased from 0.9 m to 5.1 m per year, with a clear inhomogeneous component. Obviously, after a lag-phase of several years, non-random seed dispersal by large red wood ants (Formica rufa) was determining the species’ spread, thus resulting in stratified dispersal due to interactions with different-sized ant species. Hypotheses on stratified dispersal, on dispersal lag, and on non-random dispersal were verified using an extended SEIB model, by comparison of model outputs with field patterns (individual numbers, population areas, and maximum distances). Dispersal towards red wood ant nests together with seed loss during transport and redistribution around nests were essential features of the model extension. The observed lag-phase in the initiation of non-random, medium-distance transport was probably due to a change of ant behaviour towards a new food source of increasing importance, being a meaningful example for a lag-phase in local plant species invasion. The results demonstrate that field studies should check model predictions wherever possible. Future research will show whether or not the M. pratense–ant system is representative for migration patterns of similar animal dispersal systems after having crossed range edges by long-distance dispersal events. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - paper 151 KW - Melampyrum pratense KW - population dynamics KW - seed dispersal KW - non-random dispersal KW - plant-animal interaction Y1 - 2009 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-46482 ER - TY - JOUR A1 - Imholt, Christian A1 - Reil, Daniela A1 - Eccard, Jana A1 - Jacob, Daniela A1 - Hempelmann, Nils A1 - Jacob, Jens T1 - Quantifying the past and future impact of climate on outbreak patterns of bank voles (Myodes glareolus) JF - Pest management science N2 - BACKGROUND Central European outbreak populations of the bank vole (Myodes glareolus Schreber) are known to cause damage in forestry and to transmit the most common type of Hantavirus (Puumala virus, PUUV) to humans. A sound estimation of potential effects of future climate scenarios on population dynamics is a prerequisite for long-term management strategies. Historic abundance time series were used to identify the key weather conditions associated with bank vole abundance, and were extrapolated to future climate scenarios to derive potential long-term changes in bank vole abundance dynamics. RESULTS Classification and regression tree analysis revealed the most relevant weather parameters associated with high and low bank vole abundances. Summer temperatures 2 years prior to trapping had the highest impact on abundance fluctuation. Extrapolation of the identified parameters to future climate conditions revealed an increase in years with high vole abundance. CONCLUSION Key weather patterns associated with vole abundance reflect the importance of superabundant food supply through masting to the occurrence of bank vole outbreaks. Owing to changing climate, these outbreaks are predicted potentially to increase in frequency 3-4-fold by the end of this century. This may negatively affect damage patterns in forestry and the risk of human PUUV infection in the long term. (c) 2014 Society of Chemical Industry KW - climate change KW - population dynamics KW - bank vole KW - regression tree KW - outbreak Y1 - 2015 U6 - https://doi.org/10.1002/ps.3838 SN - 1526-498X SN - 1526-4998 VL - 71 IS - 2 SP - 166 EP - 172 PB - Wiley-Blackwell CY - Hoboken ER - TY - JOUR A1 - Itonaga, Naomi A1 - Köppen, Ulrich A1 - Plath, Martin A1 - Wallschläger, Hans-Dieter T1 - Declines in breeding site fidelity in an increasing population of White Storks Ciconia ciconia JF - IBIS N2 - Following a steep decline, White Stork Ciconia ciconia populations in Germany are currently increasing, allowing us to examine potential density-dependent effects on breeding dispersal. Our data suggest that the proportion of breeding dispersers has increased over time, indicating a density-dependent component in nest-site fidelity that may be linked to increased competition. KW - age-dependent dispersal KW - density-dependent dispersal KW - population dynamics Y1 - 2011 SN - 0019-1019 VL - 153 IS - 3 SP - 636 EP - 639 PB - Wiley-Blackwell CY - Malden ER - TY - THES A1 - Malchow, Anne-Kathleen T1 - Developing an integrated platform for predicting niche and range dynamics BT - inverse calibration of spatially-explicit eco-evolutionary models N2 - Species are adapted to the environment they live in. Today, most environments are subjected to rapid global changes induced by human activity, most prominently land cover and climate changes. Such transformations can cause adjustments or disruptions in various eco-evolutionary processes. The repercussions of this can appear at the population level as shifted ranges and altered abundance patterns. This is where global change effects on species are usually detected first. To understand how eco-evolutionary processes act and interact to generate patterns of range and abundance and how these processes themselves are influenced by environmental conditions, spatially-explicit models provide effective tools. They estimate a species’ niche as the set of environmental conditions in which it can persist. However, the currently most commonly used models rely on static correlative associations that are established between a set of spatial predictors and observed species distributions. For this, they assume stationary conditions and are therefore unsuitable in contexts of global change. Better equipped are process-based models that explicitly implement algorithmic representations of eco-evolutionary mechanisms and evaluate their joint dynamics. These models have long been regarded as difficult to parameterise, but an increased data availability and improved methods for data integration lessen this challenge. Hence, the goal of this thesis is to further develop process-based models, integrate them into a complete modelling workflow, and provide the tools and guidance for their successful application. With my thesis, I presented an integrated platform for spatially-explicit eco-evolutionary modelling and provided a workflow for their inverse calibration to observational data. In the first chapter, I introduced RangeShiftR, a software tool that implements an individual-based modelling platform for the statistical programming language R. Its open-source licensing, extensive help pages and available tutorials make it accessible to a wide audience. In the second chapter, I demonstrated a comprehensive workflow for the specification, calibration and validation of RangeShiftR by the example of the red kite in Switzerland. The integration of heterogeneous data sources, such as literature and monitoring data, allowed to successfully calibrate the model. It was then used to make validated, spatio-temporal predictions of future red kite abundance. The presented workflow can be adopted to any study species if data is available. In the third chapter, I extended RangeShiftR to directly link demographic processes to climatic predictors. This allowed me to explore the climate-change responses of eight Swiss breeding birds in more detail. Specifically, the model could identify the most influential climatic predictors, delineate areas of projected demographic suitability, and attribute current population trends to contemporary climate change. My work shows that the application of complex, process-based models in conservation-relevant contexts is feasible, utilising available tools and data. Such models can be successfully calibrated and outperform other currently used modelling approaches in terms of predictive accuracy. Their projections can be used to predict future abundances or to assess alternative conservation scenarios. They further improve our mechanistic understanding of niche and range dynamics under climate change. However, only fully mechanistic models, that include all relevant processes, allow to precisely disentangle the effects of single processes on observed abundances. In this respect, the RangeShiftR model still has potential for further extensions that implement missing influential processes, such as species interactions. Dynamic, process-based models are needed to adequately model a dynamic reality. My work contributes towards the advancement, integration and dissemination of such models. This will facilitate numeric, model-based approaches for species assessments, generate ecological insights and strengthen the reliability of predictions on large spatial scales under changing conditions. N2 - Arten sind an ihren jeweiligen Lebensraum angepasst, doch viele Lebensräume sind heute einem globalen Wandel unterworfen. Dieser äußert sich vor allem in Veränderungen von Landnutzung und Klima, welche durch menschliche Aktivitäten verursacht werden und ganze Ökosysteme in ihrem Gefüge stören können. Störungen der grundlegenden öko-evolutionären Prozesse können auf der Populationsebene in Form von veränderten Verbreitungsgebieten und Häufigkeitsmustern sichtbar werden. Hier werden die Auswirkungen des globalen Wandels auf eine Art oftmals zuerst beobachtet. Um zu untersuchen, wie die Wirkung und Wechselwirkung der verschiedenen öko-evolutionären Prozesse die beobachteten Verbreitungs- und Häufigkeitsmuster erzeugen, und wie diese Prozesse wiederum von Umweltbedingungen beeinflusst werden, stellen räumlich explizite Modelle wirksame Instrumente dar. Sie beschreiben die ökologische Nische einer Art, also die Gesamtheit aller Umweltbedingungen, unter denen die Art fortbestehen kann. Die derzeit am häufigsten verwendeten Modelle stützen sich auf statische, korrelative Zusammenhänge, die zwischen bestimmten räumlichen Prädiktoren und den beobachteten Artverteilungen hergestellt werden. Allerdings werden dabei stationäre Bedingungen angenommen, was sie im Kontext des globalen Wandels ungeeignet macht. Deutlich besser geeignet sind prozessbasierte Modelle, welche explizite, algorithmische Repräsentationen von ökologischen Prozessen beinhalten und deren gemeinsame Dynamik berechnen. Solche Modelle galten lange Zeit als schwierig zu parametrisieren, doch die zunehmende Verfügbarkeit von Beobachtungsdaten sowie die verbesserten Methoden zur Datenintegration machen ihre Verwendung zunehmend praktikabel. Das Ziel der vorliegenden Arbeit ist es, diese prozessbasierten Modelle weiterzuentwickeln, sie in umfassende Modellierungsabläufe einzubinden, sowie Software und Anleitungen für ihre erfolgreiche Anwendung verfügbar zu machen. In meiner Dissertation präsentiere ich eine integrierte Plattform für räumlich-explizite, öko-evolutionäre Modellierung und entwickle einen Arbeitsablauf für dessen inverse Kalibrierung an Beobachtungsdaten. Im ersten Kapitel stelle ich RangeShiftR vor: eine Software, die eine individuenbasierte Modellierungsplattform für die statistische Programmiersprache R implementiert. Durch die Open-Source-Lizenzierung, umfangreichen Hilfeseiten und online verfügbaren Tutorials ist RangeShiftR einem breiten Publikum zugänglich. Im zweiten Kapitel demonstriere ich einen vollständigen Modellierungsablauf am Beispiel des Rotmilans in der Schweiz, der die Spezifikation, Kalibrierung und Validierung von RangeShiftR umfasst.Durch die Integration heterogener Datenquellen, wie Literatur- und Monitoringdaten, konnte das Modell erfolgreich kalibriert werden. Damit konnten anschließend validierte, raum-zeitliche Vorhersagen über das Vorkommen des Rotmilans erstellt und die dafür relevanten Prozesse identifiziert werden. Der vorgestellte Arbeitsablauf kann auf andere Arten übertragen werden, sofern geeignete Daten verfügbar sind. Im dritten Kapitel habe ich RangeShiftR erweitert, sodass demografische Prozessraten direkt mit Klimavariablen verknüpft werden können. Dies ermöglichte es, die Reaktionen von acht Schweizer Brutvogelarten auf den Klimawandel genauer zu untersuchen. Insbesondere konnte das Modell die einflussreichsten klimatischen Faktoren identifizieren, demografisch geeignete Gebiete abgrenzen und aktuelle Populationstrends auf den bisherigen Klimawandel zurückführen. Meine Arbeit zeigt, dass die Anwendung komplexer, prozessbasierter Modelle in naturschutzrelevanten Kontexten mit verfügbaren Daten möglich ist. Solche Modelle können erfolgreich kalibriert werden und andere, derzeit verwendete Modellierungsansätze in Bezug auf ihre Vorhersagegenauigkeit übertreffen. Ihre Projektionen können zur Vorhersage zukünftiger Artvorkommen und zur Einschätzung alternativer Naturschutzmaßnahmen verwendet werden. Sie verbessern außerdem unser mechanistisches Verständnis von Nischen- und Verbreitungsdynamiken unter dem Einfluss des Klimawandels. Jedoch ermöglichen nur vollständig prozessbasierte Modelle, die alle relevanten Prozesse vereinen, eine korrekte Aufschlüsselung der Auswirkungen einzelner Prozesse auf die beobachteten Abundanzen. In dieser Hinsicht hat das RangeShiftR-Modell noch Potenzial für Weiterentwicklungen, um fehlende, einflussreiche Prozesse hinzuzufügen, wie zum Beispiel die Interaktionen zwischen Arten. Um eine dynamische Realität adäquat abbilden zu können, werden dynamische, prozessbasierte Modelle benötigt. Meine Arbeit leistet einen Beitrag zur Weiterentwicklung, Integration und Verbreitung solcher Modelle und stärkt somit die Anwendung numerischer, modellbasierter Methoden für die Bewertung des Zustands von Arten, die Untersuchung ökologischer Zusammenhänge und die Steigerung der Zuverlässigkeit von Vorhersagen auf großen räumlichen Skalen unter Umweltveränderungen. T2 - Entwicklung einer integrierten Modellierungs-Plattform zur Vorhersage von Nischen- und Verbreitungs-dynamiken: Inverse Kalibrierung räumlich-expliziter öko-evolutionärer Modelle KW - species distribution modelling KW - Bayesian inference KW - individual-based modelling KW - range shifts KW - ecological modelling KW - population dynamics KW - Bayes'sche Inferenz KW - ökologische Modellierung KW - individuen-basierte Modellierung KW - Populationsdynamik KW - Arealverschiebungen KW - Artverbreitungsmodelle Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-602737 ER - TY - JOUR A1 - Malchow, Anne-Kathleen A1 - Bocedi, Greta A1 - Palmer, Stephen C. F. A1 - Travis, Justin M. J. A1 - Zurell, Damaris T1 - RangeShiftR: an R package for individual-based simulation of spatial eco-evolutionary dynamics and speciesu0027 responses to environmental changes JF - Ecography N2 - Reliably modelling the demographic and distributional responses of a species to environmental changes can be crucial for successful conservation and management planning. Process-based models have the potential to achieve this goal, but so far they remain underused for predictions of species' distributions. Individual-based models offer the additional capability to model inter-individual variation and evolutionary dynamics and thus capture adaptive responses to environmental change. We present RangeShiftR, an R implementation of a flexible individual-based modelling platform which simulates eco-evolutionary dynamics in a spatially explicit way. The package provides flexible and fast simulations by making the software RangeShifter available for the widely used statistical programming platform R. The package features additional auxiliary functions to support model specification and analysis of results. We provide an outline of the package's functionality, describe the underlying model structure with its main components and present a short example. RangeShiftR offers substantial model complexity, especially for the demographic and dispersal processes. It comes with elaborate tutorials and comprehensive documentation to facilitate learning the software and provide help at all levels. As the core code is implemented in C++, the computations are fast. The complete source code is published under a public licence, making adaptations and contributions feasible. The RangeShiftR package facilitates the application of individual-based and mechanistic modelling to eco-evolutionary questions by operating a flexible and powerful simulation model from R. It allows effortless interoperation with existing packages to create streamlined workflows that can include data preparation, integrated model specification and results analysis. Moreover, the implementation in R strengthens the potential for coupling RangeShiftR with other models. KW - connectivity KW - conservation KW - dispersal KW - evolution KW - population dynamics KW - range dynamics Y1 - 2021 SN - 1600-0587 VL - 44 IS - 10 PB - John Wiley & Sons, Inc. CY - New Jersey ER - TY - GEN A1 - Malchow, Anne-Kathleen A1 - Bocedi, Greta A1 - Palmer, Stephen C. F. A1 - Travis, Justin M. J. A1 - Zurell, Damaris T1 - RangeShiftR: an R package for individual-based simulation of spatial eco-evolutionary dynamics and speciesu0027 responses to environmental changes T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - Reliably modelling the demographic and distributional responses of a species to environmental changes can be crucial for successful conservation and management planning. Process-based models have the potential to achieve this goal, but so far they remain underused for predictions of species' distributions. Individual-based models offer the additional capability to model inter-individual variation and evolutionary dynamics and thus capture adaptive responses to environmental change. We present RangeShiftR, an R implementation of a flexible individual-based modelling platform which simulates eco-evolutionary dynamics in a spatially explicit way. The package provides flexible and fast simulations by making the software RangeShifter available for the widely used statistical programming platform R. The package features additional auxiliary functions to support model specification and analysis of results. We provide an outline of the package's functionality, describe the underlying model structure with its main components and present a short example. RangeShiftR offers substantial model complexity, especially for the demographic and dispersal processes. It comes with elaborate tutorials and comprehensive documentation to facilitate learning the software and provide help at all levels. As the core code is implemented in C++, the computations are fast. The complete source code is published under a public licence, making adaptations and contributions feasible. The RangeShiftR package facilitates the application of individual-based and mechanistic modelling to eco-evolutionary questions by operating a flexible and powerful simulation model from R. It allows effortless interoperation with existing packages to create streamlined workflows that can include data preparation, integrated model specification and results analysis. Moreover, the implementation in R strengthens the potential for coupling RangeShiftR with other models. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 1178 KW - connectivity KW - conservation KW - dispersal KW - evolution KW - population dynamics KW - range dynamics Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-523979 SN - 1866-8372 IS - 10 ER - TY - JOUR A1 - Malchow, Anne-Kathleen A1 - Bocedi, Greta A1 - Palmer, Stephen C. F. A1 - Travis, Justin M. J. A1 - Zurell, Damaris T1 - RangeShiftR BT - an R package for individual-based simulation of spatial changes JF - Ecography : pattern and diversity in ecology / Nordic Ecologic Society Oikos N2 - Reliably modelling the demographic and distributional responses of a species to environmental changes can be crucial for successful conservation and management planning. Process-based models have the potential to achieve this goal, but so far they remain underused for predictions of species' distributions. Individual-based models offer the additional capability to model inter-individual variation and evolutionary dynamics and thus capture adaptive responses to environmental change. We present RangeShiftR, an R implementation of a flexible individual-based modelling platform which simulates eco-evolutionary dynamics in a spatially explicit way. The package provides flexible and fast simulations by making the software RangeShifter available for the widely used statistical programming platform R. The package features additional auxiliary functions to support model specification and analysis of results. We provide an outline of the package's functionality, describe the underlying model structure with its main components and present a short example. RangeShiftR offers substantial model complexity, especially for the demographic and dispersal processes. It comes with elaborate tutorials and comprehensive documentation to facilitate learning the software and provide help at all levels. As the core code is implemented in C++, the computations are fast. The complete source code is published under a public licence, making adaptations and contributions feasible. The RangeShiftR package facilitates the application of individual-based and mechanistic modelling to eco-evolutionary questions by operating a flexible and powerful simulation model from R. It allows effortless interoperation with existing packages to create streamlined workflows that can include data preparation, integrated model specification and results analysis. Moreover, the implementation in R strengthens the potential for coupling RangeShiftR with other models. KW - connectivity KW - conservation KW - dispersal KW - evolution KW - population dynamics KW - range dynamics Y1 - 2021 U6 - https://doi.org/10.1111/ecog.05689 SN - 1600-0587 VL - 44 IS - 10 SP - 1443 EP - 1452 PB - Wiley-Blackwell CY - Oxford [u.a.] ER - TY - THES A1 - Martin, Benjamin T1 - Linking individual-based models and dynamic energy budget theory : lessons for ecology and ecotoxicology T1 - Individuenbasierte Modelle mit dynamischen Energiehaushalten bereichern die Ökologie und Ökotoxikologie N2 - In the context of ecological risk assessment of chemicals, individual-based population models hold great potential to increase the ecological realism of current regulatory risk assessment procedures. However, developing and parameterizing such models is time-consuming and often ad hoc. Using standardized, tested submodels of individual organisms would make individual-based modelling more efficient and coherent. In this thesis, I explored whether Dynamic Energy Budget (DEB) theory is suitable for being used as a standard submodel in individual-based models, both for ecological risk assessment and theoretical population ecology. First, I developed a generic implementation of DEB theory in an individual-based modeling (IBM) context: DEB-IBM. Using the DEB-IBM framework I tested the ability of the DEB theory to predict population-level dynamics from the properties of individuals. We used Daphnia magna as a model species, where data at the individual level was available to parameterize the model, and population-level predictions were compared against independent data from controlled population experiments. We found that DEB theory successfully predicted population growth rates and peak densities of experimental Daphnia populations in multiple experimental settings, but failed to capture the decline phase, when the available food per Daphnia was low. Further assumptions on food-dependent mortality of juveniles were needed to capture the population dynamics after the initial population peak. The resulting model then predicted, without further calibration, characteristic switches between small- and large-amplitude cycles, which have been observed for Daphnia. We conclude that cross-level tests help detecting gaps in current individual-level theories and ultimately will lead to theory development and the establishment of a generic basis for individual-based models and ecology. In addition to theoretical explorations, we tested the potential of DEB theory combined with IBMs to extrapolate effects of chemical stress from the individual to population level. For this we used information at the individual level on the effect of 3,4-dichloroanailine on Daphnia. The individual data suggested direct effects on reproduction but no significant effects on growth. Assuming such direct effects on reproduction, the model was able to accurately predict the population response to increasing concentrations of 3,4-dichloroaniline. We conclude that DEB theory combined with IBMs holds great potential for standardized ecological risk assessment based on ecological models. N2 - Für die ökologische Risikobewertung von Chemikalien sind individuenbasierte Populationsmodelle ein vielversprechendes Werkzeug um heutige Bewertungen ökologisch realistischer zu gestalten. Allerdings ist die Entwicklung und Parametrisierung derartiger Modelle zeitaufwendig und oft wenig systematisch. Standardisierte, geprüfte Untermodelle, die Einzelorganismen beschreiben, würden die individuenbasierte Modellierung effizienter und kohärenter machen. In meiner Dissertation habe ich daher untersucht, inwieweit sich die Dynamic Energy Budget-Theorie (DEB) als Standardmodell innerhalb individuenbasierter Populationsmodelle eignet, und zwar sowohl für die ökologische Risikobewertung als auch für die theoretische Populationsökologie. Zunächst habe ich eine generische Implementierung der DEB-Theorie im Rahmen individuenbasierter Modellen (IBM) erstellt: DEB-IBM. Dieses Werkzeug nutzend habe ich dann untersucht, ob es mit Hilfe der DEB-Theorie gelingt, ausgehend von den Eigenschaften und Aktivitäten einzelner Individuen, Populationsdynamik vorherzusagen. Wir nutzten dabei Daphnia magna als Modellart, für die Daten auf der Individuenebene verfügbar waren, um das Modell zu parametrisieren, sowie Populationsdaten, mit denen Modellvorhersagen verglichen werden konnten. DEB-Theorie war in der Lage, beobachtete Populationswachstumsraten sowie die maximalen Abundanzen korrekt vorherzusagen, und zwar für verschiedene Umweltbedingungen. Für Phasen des Rückgangs der Population allerdings, wenn die für die Daphnien verfügbare Nahrungsmenge gering war, kam es zu Abweichungen. Es waren deshalb zusätzliche Annahmen über nahrungsabhängige Sterblichkeit von juvenilen Daphnien erforderlich, um die gesamte Populationsdynamik korrekt vorherzusagen. Das resultierende Modell konnte dann, ohne weitere Kalibrierungen, den für Daphnien charakteristischen Wechsel zwischen Populationszyklen mit großen und kleinen Amplituden richtig vorhersagen. Wir folgern daraus, daß Ebenen übergreifende Tests dabei helfen, Lücken in aktuellen Theorien über Einzelorganismen aufzudecken Dies trägt zur Theorieentwicklung bei und liefert Grundlagen für individuenbasierte Modellierung und Ökologie. Über diese Grundlagenfragen hinaus haben wir überprüft, ob DEB-Theorie in Kombination mit IBMs es ermöglicht, den Effekt von chemischem Streß auf Individuen auf die Populationsebene zu extrapolieren. Wir nutzten Daten über die Auswirkungen von 3,4 Dichloroanalin auf einzelne Daphnien, die zeigten daß im Wesentlichen die Reproduktion, nicht aber das Wachstum beeinträchtigt ist. Mit entsprechenden Annahmen konnte unser Modell den Effekt auf Populationsebene, für den unabhängige Daten vorlagen, korrekt vorhersagen. DEB-Theorie in Kombination mit individuenbasierter Modellierung birgt somit großes Potential für einen standardisierten modellbasierten Ansatz in der ökologischen Risikobewertung von Chemikalien. KW - Ökologie KW - Ökotoxikologie KW - Populationsdynamik KW - Ecology KW - Ecotoxicology KW - population dynamics Y1 - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-67001 ER -