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One of the most striking features of ecological systems is their ability to undergo sudden outbreaks in the population numbers of one or a small number of species. The similarity of outbreak characteristics, which is exhibited in totally different and unrelated (ecological) systems naturally leads to the question whether there are universal mechanisms underlying outbreak dynamics in Ecology. It will be shown into two case studies (dynamics of phytoplankton blooms under variable nutrients supply and spread of epidemics in networks of cities) that one explanation for the regular recurrence of outbreaks stems from the interaction of the natural systems with periodical variations of their environment. Natural aquatic systems like lakes offer very good examples for the annual recurrence of outbreaks in Ecology. The idea whether chaos is responsible for the irregular heights of outbreaks is central in the domain of ecological modeling. This question is investigated in the context of phytoplankton blooms. The dynamics of epidemics in networks of cities is a problem which offers many ecological and theoretical aspects. The coupling between the cities is introduced through their sizes and gives rise to a weighted network which topology is generated from the distribution of the city sizes. We examine the dynamics in this network and classified the different possible regimes. It could be shown that a single epidemiological model can be reduced to a one-dimensional map. We analyze in this context the dynamics in networks of weighted maps. The coupling is a saturation function which possess a parameter which can be interpreted as an effective temperature for the network. This parameter allows to vary continously the network topology from global coupling to hierarchical network. We perform bifurcation analysis of the global dynamics and succeed to construct an effective theory explaining very well the behavior of the system.
Natural and human induced environmental changes affect populations at different time scales. If they occur in a spatial heterogeneous way, they cause spatial variation in abundance. In this thesis I addressed three topics, all related to the question, how environmental changes influence population dynamics. In the first part, I analysed the effect of positive temporal autocorrelation in environmental noise on the extinction risk of a population, using a simple population model. The effect of autocorrelation depended on the magnitude of the effect of single catastrophic events of bad environmental conditions on a population. If a population was threatened by extinction only, when bad conditions occurred repeatedly, positive autocorrelation increased extinction risk. If a population could become extinct, even if bad conditions occurred only once, positive autocorrelation decreased extinction risk. These opposing effects could be explained by two features of an autocorrelated time series. On the one hand, positive autocorrelation increased the probability of series of bad environmental conditions, implying a negative effect on populations. On the other hand, aggregation of bad years also implied longer periods with relatively good conditions. Therefore, for a given time period, the overall probability of occurrence of at least one extremely bad year was reduced in autocorrelated noise. This can imply a positive effect on populations. The results could solve a contradiction in the literature, where opposing effects of autocorrelated noise were found in very similar population models. In the second part, I compared two approaches, which are commonly used for predicting effects of climate change on future abundance and distribution of species: a "space for time approach", where predictions are based on the geographic pattern of current abundance in relation to climate, and a "population modelling approach" which is based on correlations between demographic parameters and the inter-annual variation of climate. In this case study, I compared the two approaches for predicting the effect of a shift in mean precipitation on a population of the sociable weaver Philetairus socius, a common colonially living passerine bird of semiarid savannahs of southern Africa. In the space for time approach, I compared abundance and population structure of the sociable weaver in two areas with highly different mean annual precipitation. The analysis showed no difference between the two populations. This result, as well as the wide distribution range of the species, would lead to the prediction of no sensitive response of the species to a slight shift in mean precipitation. In contrast, the population modelling approach, based on a correlation between reproductive success and rainfall, predicted a sensitive response in most model types. The inconsistency of predictions was confirmed in a cross-validation between the two approaches. I concluded that the inconsistency was caused, because the two approaches reflect different time scales. On a short time scale, the population may respond sensitively to rainfall. However, on a long time scale, or in a regional comparison, the response may be compensated or buffered by a variety of mechanisms. These may include behavioural or life history adaptations, shifts in the interactions with other species, or differences in the physical environment. The study implies that understanding, how such mechanisms work, and at what time scale they would follow climate change, is a crucial precondition for predicting ecological consequences of climate change. In the third part of the thesis, I tested why colony sizes of the sociable weaver are highly variable. The high variation of colony sizes is surprising, as in studies on coloniality it is often assumed that an optimal colony size exists, in which individual bird fitness is maximized. Following this assumption, the pattern of bird dispersal should keep colony sizes near an optimum. However, I showed by analysing data on reproductive success and survival that for the sociable weaver fitness in relation to colony size did not follow an optimum curve. Instead, positive and negative effects of living in large colonies overlaid each other in a way that fitness was generally close to one, and density dependence was low. I showed in a population model, which included an evolutionary optimisation process of dispersal that this specific shape of the fitness function could lead to a dispersal strategy, where the variation of colony sizes was maintained.
Understanding the interactions of predators and their prey and their responses to environmental changes is one of the striking features of ecological research. In this thesis, spring dynamics of phytoplankton and its consumers, zooplankton, were considered in dependence on the environmental conditions in a deep lake (Lake Constance) and a shallow marine water (mesocosms from Kiel Bight), using descriptive statistics, multiple regression models, and process-oriented dynamic simulation models. The development of the spring phytoplankton bloom, representing a dominant feature in the plankton dynamics in temperate and cold oceans and lakes, may depend on temperature, light, and mixing intensity, and the success of over-wintering phyto- and zooplankton. These factors are often correlated in the field. Unexpectedly, irradiance often dominated algal net growth rather than vertical mixing even in deep Lake Constance. Algal net losses from the euphotic layer to larger depth were induced by vertical mixing, but were compensated by the input from larger depth when algae were uniformly distributed over the water column. Dynamics of small, fast-growing algae were well predicted by abiotic variables, such as surface irradiance, vertical mixing intensity, and temperature. A simulation model additionally revealed that even in late winter, grazing may represent an important loss factor of phytoplankton 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. The negative effect of higher temperatures on phytoplankton biomass was due to enhanced temperature-sensitive grazing losses. Comparing the results from deep Lake Constance to those of the shallow mesocosm experiments and simulations, confirmed the strong direct effect of light in contrast to temperature, and the importance of grazing already in early spring as soon as moderate algal biomasses developed. In Lake Constance, ciliates dominated the herbivorous zooplankton in spring. The start of ciliate net growth in spring was closely linked to that of edible algae, chlorophyll a and the vertical mixing intensity but independent of water temperature. The duration of ciliate dominance in spring was largely controlled by the highly variable onset of the phytoplankton bloom, and little by the less variable termination of the ciliate bloom by grazing of meta-zooplankton. During years with an extended spring bloom of algae and ciliates, they coexisted at relatively high biomasses over 15-30 generations, and internally forced species shifts were observed in both communities. Interception feeders alternated with filter feeders, and cryptomonads with non-cryptomonads in their relative importance. These dynamics were not captured by classical 1-predator-1-prey models which consistently predict pronounced predator-prey cycles or equilibria with either the predator or the prey dominating or suppressed. A multi-species predator-prey model with predator species differing in their food selectivity, and prey species in their edibility reproduced the observed patterns. Food-selectivity and edibility were related to the feeding and growth characteristics of the species, which represented ecological trade-offs. For example, the prey species with the highest edibility also had the highest maximum growth rate. Data and model revealed endogenous driven ongoing species alternations, which yielded a higher variability in species-specific biomasses than in total predator and prey biomass. This holds for a broad parameter space as long as the species differ functionally. A more sophisticated model approach enabled the simulation of a continuum of different functional types and adaptability of predator and prey communities to altered environmental conditions, and the maintenance of a rather low model complexity, i.e., low number of equations and free parameters. The community compositions were described by mean functional traits --- prey edibility and predator food-selectivity --- and their variances. The latter represent the functional diversity of the communities and thus, the potential for adaptation. Oscillations in the mean community trait values indicated species shifts. The community traits were related to growth and grazing characteristics representing similar trade-offs as in the multi-species model. The model reproduced the observed patterns, when nonlinear relationships between edibility and capacity, and edibility and food availability for the predator were chosen. A constant minimum amount of variance represented ongoing species invasions and thus, preserved a diversity which allows adaptation on a realistic time-span.
The heterogeneity in species assemblages of epigeal spiders was studied in a natural forest and in a managed forest. Additionally the effects of small-scale microhabitat heterogeneity of managed and unmanaged forests were determined by analysing the spider assemblages of three different microhabitat structures (i. vegetation, ii. dead wood. iii. litter cover). The spider were collected in a block design by pitfall traps (n=72) in a 4-week interval. To reveal key environmental factors affecting the spider distribution abiotic and biotic habitat parameters (e.g. vegetation parameters, climate parameters, soil moisture) were assessed around each pitfall trap. A TWINSPAN analyses separated pitfall traps from the natural forest from traps of the managed forest. A subsequent discriminant analyses revealed that the temperature, the visible sky, the plant diversity and the mean diameter at breast height as key discriminant factors between the microhabitat groupings designated by the TWINSPAN analyses. Finally a Redundant analysis (RDA) was done revealing similar environmental factors responsible for the spider species distribution, as a good separation of the different forest types as well as the separation of the microhabitat groupings from the TWINSPAN. Overall the study revealed that the spider communities differed between the forest types as well as between the microhabitat structures and thus species distribution changed within a forest stand on a fine spatial scale. It was documented that the structure of managed forests affects the composition of spider assemblages compared to natural forests significantly and even small scale-heterogeneity seems to influence the spider species composition.
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.
Over the last years there is an increasing awareness that historical land cover changes and associated land use legacies may be important drivers for present-day species richness and biodiversity due to time-delayed extinctions or colonizations in response to historical environmental changes. Historically altered habitat patches may therefore exhibit an extinction debt or colonization credit and can be expected to lose or gain species in the future. However, extinction debts and colonization credits are difficult to detect and their actual magnitudes or payments have rarely been quantified because species richness patterns and dynamics are also shaped by recent environmental conditions and recent environmental changes.
In this thesis we aimed to determine patterns of herb-layer species richness and recent species richness dynamics of forest herb layer plants and link those patterns and dynamics to historical land cover changes and associated land use legacies. The study was conducted in the Prignitz, NE-Germany, where the forest distribution remained stable for the last ca. 100 years but where a) the deciduous forest area had declined by more than 90 per cent (leaving only remnants of "ancient forests"), b) small new forests had been established on former agricultural land ("post-agricultural forests"). Here, we analyzed the relative importance of land use history and associated historical land cover changes for herb layer species richness compared to recent environmental factors and determined magnitudes of extinction debt and colonization credit and their payment in ancient and post-agricultural forests, respectively.
We showed that present-day species richness patterns were still shaped by historical land cover changes that ranged back to more than a century. Although recent environmental conditions were largely comparable we found significantly more forest specialists, species with short-distance dispersal capabilities and clonals in ancient forests than in post-agricultural forests. Those species richness differences were largely contingent to a colonization credit in post-agricultural forests that ranged up to 9 species (average 4.7), while the extinction debt in ancient forests had almost completely been paid. Environmental legacies from historical agricultural land use played a minor role for species richness differences. Instead, patch connectivity was most important. Species richness in ancient forests was still dependent on historical connectivity, indicating a last glimpse of an extinction debt, and the colonization credit was highest in isolated post-agricultural forests. In post-agricultural forests that were better connected or directly adjacent to ancient forest patches the colonization credit was way smaller and we were able to verify a gradual payment of the colonization credit from 2.7 species to 1.5 species over the last six decades.
Faszination AvH
(2019)
Alexander von Humboldts Forschungsreise in die Neue Welt ist ein Gründungsmoment moderner Wissenschaft. Sie liefert uns Impulse und Grundlagen für ein 21. Jahrhundert, das im Zeichen des Zusammendenkens und Zusammenlebens stehen muss. Von der lange verschütteten Tradition einer Humboldt’schen Wissenschaft aus lassen sich heute, am Ausgang unserer aktuellen Globalisierungsphase, neue Zukünfte denken und entfalten. Das Zusammendenken von Natur und Kultur im Horizont einer Ökologie, die sich mit Gesellschafts- und Wirtschaftsstrukturen vernetzt; der Entwurf einer Kosmopolitik, die nicht auf Machtasymmetrie, Inferiorisierung und Abhängigkeit abzielt, sondern die Zirkulation von Wissen zur Grundlage einer sich demokratisierenden Weltgesellschaft macht: Dies sind Kreuzungspunkte eines Denkens, das nicht nur an Aktualität, sondern im Zeichen neu entfachter Nationalismen, neuer Fundamentalismen und neuer globaler Ausgrenzungen vor allem an Dringlichkeit gewonnen hat.
Predators can have numerical and behavioral effects on prey animals. While numerical effects are well explored, the impact of behavioral effects is unclear. Furthermore, behavioral effects are generally either analyzed with a focus on single individuals or with a focus on consequences for other trophic levels. Thereby, the impact of fear on the level of prey communities is overlooked, despite potential consequences for conservation and nature management. In order to improve our understanding of predator-prey interactions, an assessment of the consequences of fear in shaping prey community structures is crucial.
In this thesis, I evaluated how fear alters prey space use, community structure and composition, focusing on terrestrial mammals. By integrating landscapes of fear in an existing individual-based and spatially-explicit model, I simulated community assembly of prey animals via individual home range formation. The model comprises multiple hierarchical levels from individual home range behavior to patterns of prey community structure and composition. The mechanistic approach of the model allowed for the identification of underlying mechanism driving prey community responses under fear.
My results show that fear modified prey space use and community patterns. Under fear, prey animals shifted their home ranges towards safer areas of the landscape. Furthermore, fear decreased the total biomass and the diversity of the prey community and reinforced shifts in community composition towards smaller animals. These effects could be mediated by an increasing availability of refuges in the landscape. Under landscape changes, such as habitat loss and fragmentation, fear intensified negative effects on prey communities. Prey communities in risky environments were subject to a non-proportional diversity loss of up to 30% if fear was taken into account. Regarding habitat properties, I found that well-connected, large safe patches can reduce the negative consequences of habitat loss and fragmentation on prey communities. Including variation in risk perception between prey animals had consequences on prey space use. Animals with a high risk perception predominantly used safe areas of the landscape, while animals with a low risk perception preferred areas with a high food availability. On the community level, prey diversity was higher in heterogeneous landscapes of fear if individuals varied in their risk perception compared to scenarios in which all individuals had the same risk perception.
Overall, my findings give a first, comprehensive assessment of the role of fear in shaping prey communities. The linkage between individual home range behavior and patterns at the community level allows for a mechanistic understanding of the underlying processes. My results underline the importance of the structure of the landscape of fear as a key driver of prey community responses, especially if the habitat is threatened by landscape changes. Furthermore, I show that individual landscapes of fear can improve our understanding of the consequences of trait variation on community structures. Regarding conservation and nature management, my results support calls for modern conservation approaches that go beyond single species and address the protection of biotic interactions.