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The continuously increasing pollution of aquatic environments with microplastics (plastic particles < 5 mm) is a global problem with potential implications for organisms of all trophic levels. For microorganisms, trillions of these floating microplastics particles represent a huge surface area for colonization. Due to the very low biodegradability, microplastics remain years to centuries in the environment and can be transported over thousands of kilometers together with the attached organisms. Since also pathogenic, invasive, or otherwise harmful species could be spread this way, it is essential to study microplastics-associated communities.
For this doctoral thesis, eukaryotic communities were analyzed for the first time on microplastics in brackish environments and compared to communities in the surrounding water and on the natural substrate wood. With Illumina MiSeq high-throughput sequencing, more than 500 different eukaryotic taxa were detected on the microplastics samples. Among them were various green algae, dinoflagellates, ciliates, fungi, fungal-like protists and small metazoans such as nematodes and rotifers. The most abundant organisms was a dinoflagellate of the genus Pfiesteria, which could include fish pathogenic and bloom forming toxigenic species. Network analyses revealed that there were numerous interaction possibilities among prokaryotes and eukaryotes in microplastics biofilms. Eukaryotic community compositions on microplastics differed significantly from those on wood and in water, and compositions were additionally distinct among the sampling locations. Furthermore, the biodiversity was clearly lower on microplastics in comparison to the diversity on wood or in the surrounding water.
In another experiment, a situation was simulated in which treated wastewater containing microplastics was introduced into a freshwater lake. With increasing microplastics concentrations, the resulting bacterial communities became more similar to those from the treated wastewater. Moreover, the abundance of integrase I increased together with rising concentrations of microplastics. Integrase I is often used as a marker for anthropogenic environmental pollution and is further linked to genes conferring, e.g., antibiotic resistance.
This dissertation gives detailed insights into the complexity of prokaryotic and eukaryotic communities on microplastics in brackish and freshwater systems. Even though microplastics provide novel microhabitats for various microbes, they might also transport toxigenic, pathogenic, antibiotic-resistant or parasitic organisms; meaning their colonization can pose potential threats to humans and the environment. Finally, this thesis explains the urgent need for more research as well as for strategies to minimize the global microplastic pollution.
The persistence of species under changed climatic conditions depends on adaptations and plastic responses to these conditions and on interactions with their local plant community resulting in direct and indirect effects of changed climatic conditions. Populations at species' range margins may be especially crucial in containing a gene pool comprising adaptations to extreme climatic conditions. Many species of northern European bog ecosystems reach their southern lowland range limit in central Europe. In a common-garden experiment, we experimentally assessed the impact of projected climatic changes on five bog-plant species (including peat moss Sphagnum magellanicum) sampled along a latitudinal gradient of 1400km from Scandinavia to the marginal lowland populations in Germany. Populations were cultivated in monocultures and in experimental communities composed of all five species from their local community, and exposed to five combinations of three climate treatments (warming, fluctuating water-tables, fertilization) in a southern common garden. Whereas most monocultures showed a decreasing biomass production from southern to northern origins under southern environmental conditions, in the experimental mixed-species communities, an increasing biomass production towards northern communities was observed together with a shift in interspecific interactions along the latitudinal gradient. While negative dominance effects prevailed in southern communities, higher net biodiversity effects were observed in northern subarctic communities. The combined effects of climate treatments increased biomass production in monocultures of most origins. In communities, however, overall the treatments did not result in significantly changed biomass production. Among individual treatments, water-table fluctuations caused a significant decrease in biomass production, but only in southern communities, indicating higher vulnerability to changed climatic conditions. Here, negative effects of climate treatments on graminoids were not compensated by the slightly increased growth of peat moss that benefited from interspecific interactions only in northern communities.Synthesis. We conclude that shifting interactions within multispecies communities caused pronounced responses to changed climatic conditions in wetland communities of temperate southern marginal, but not of northern subarctic origin. Therefore, future models investigating the impacts of climate change on plant communities should consider geographical variation in species interactions an important factor influencing community responses to changed climatic conditions.
Intransitive competition is widespread in plant communities and maintains their species richness
(2015)
Intransitive competition networks, those in which there is no single best competitor, may ensure species coexistence. However, their frequency and importance in maintaining diversity in real-world ecosystems remain unclear. We used two large data sets from drylands and agricultural grasslands to assess: (1) the generality of intransitive competition, (2) intransitivity-richness relationships and (3) effects of two major drivers of biodiversity loss (aridity and land-use intensification) on intransitivity and species richness. Intransitive competition occurred in >65% of sites and was associated with higher species richness. Intransitivity increased with aridity, partly buffering its negative effects on diversity, but was decreased by intensive land use, enhancing its negative effects on diversity. These contrasting responses likely arise because intransitivity is promoted by temporal heterogeneity, which is enhanced by aridity but may decline with land-use intensity. We show that intransitivity is widespread in nature and increases diversity, but it can be lost with environmental homogenisation.
The underlying mechanisms and consequences of competition and diversity are central themes in ecology. A higher diversity of primary producers often results in higher resource use efficiency in aquatic and terrestrial ecosystems. This may result in more food for consumers on one hand, while, on the other hand, it can also result in a decreased food quality for consumers; higher biomass combined with the same availability of the limiting compound directly reduces the dietary proportion of the limiting compound. Here we tested whether and how interspecific competition in phytoplankton communities leads to changes in resource use efficiency and cellular concentrations of nutrients and fatty acids. The measured particulate carbon : phosphorus ratios (C:P) and fatty acid concentrations in the communities were compared to the theoretically expected ratios and concentrations of measurements on simultaneously running monocultures. With interspecific competition, phytoplankton communities had higher concentrations of the monounsaturated fatty acid oleic acid and also much higher concentrations of the ecologically and physiologically relevant long-chain polyunsaturated fatty acid eicosapentaenoic acid than expected concentrations based on monocultures. Such higher availability of essential fatty acids may contribute to the positive relationship between phytoplankton diversity and zooplankton growth, and may compensate limitations by mineral nutrients in higher trophic levels.
Predator-forager interactions are a major factor in evolutionary adaptation of many species, as predators need to gain energy by consuming prey species, and foragers needs to avoid the worst fate of mortality while still consuming resources for energetic gains. In this evolutionary arms race, the foragers have constantly evolved anti-predator behaviours (e.g. foraging activity changes). To describe all these complex changes, researchers developed the framework of the landscape of fear, that is, the spatio-temporal variation of perceived predation risk. This concept simplifies all the involved ecological processes into one framework, by integrating animal biology and distribution with habitat characteristics. Researchers can then evaluate the perception of predation risk in prey species, what are the behavioural responses of the prey and, therefore, understand the cascading effects of landscapes of fear at the resource levels (tri-trophic effects). Although tri-trophic effects are well studied at the predator-prey interaction level, little is known on how the forager-resource interactions are part of the overall cascading effects of landscapes of fear, despite the changes of forager feeding behaviour - that occur with perceived predation risk - affecting directly the level of the resources.
This thesis aimed to evaluate the cascading effects of the landscape of fear on biodiversity of resources, and how the feeding behaviour and movement of foragers shaped the final resource species composition (potential coexistence mechanisms). We studied the changes caused by landscapes of fear on wild and captive rodent communities and evaluated: the cascading effects of different landscapes of fear on a tri-trophic system (I), the effects of fear on a forager’s movement patterns and dietary preferences (II) and cascading effects of different types of predation risk (terrestrial versus avian, III).
In Chapter I, we applied a novel measure to evaluate the cascading effects of fear at the level of resources, by quantifying the diversity of resources left after the foragers gave-up on foraging (diversity at the giving-up density). We tested the measure at different spatial levels (local and regional) and observed that with decreased perceived predation risk, the density and biodiversity of resources also decreased. Foragers left a very dissimilar community of resources based on perceived risk and resources functional traits, and therefore acted as an equalising mechanism.
In Chapter II, we wanted to understand further the decision-making processes of rodents in different landscapes of fear, namely, in which resource species rodents decided to forage on (based on three functional traits: size, nutrients and shape) and how they moved depending on perceived predation risk. In safe landscapes, individuals increased their feeding activity and movements and despite the increased costs, they visited more often patches that were further away from their central-place. Despite a preference for the bigger resources regardless of risk, when perceived predation risk was low, individuals changed their preference to fat-rich resources.
In Chapter III, we evaluated the cascading effects of two different types of predation risk in rodents: terrestrial (raccoon) versus avian predation risk. Raccoon presence or absence did not alter the rodents feeding behaviour in different landscapes of fear. Rodent’s showed risk avoidance behaviours towards avian predators (spatial risk avoidance), but not towards raccoons (lack of temporal risk avoidance).
By analysing the effects of fear in tri-trophic systems, we were able to deepen the knowledge of how non-consumptive effects of predators affect the behaviour of foragers, and quantitatively measure the cascading effects at the level of resources with a novel measure. Foragers are at the core of the ecological processes and responses to the landscape of fear, acting as variable coexistence agents for resource species depending on perceived predation risk. This newly found measures and knowledge can be applied to more trophic chains, and inform researchers on biodiversity patterns originating from landscapes of fear.
Fungal plant pathogens are common in natural communities where they affect plant physiology, plant survival, and biomass production. Conversely, pathogen transmission and infection may be regulated by plant community characteristics such as plant species diversity and functional composition that favor pathogen diversity through increases in host diversity while simultaneously reducing pathogen infection via increased variability in host density and spatial heterogeneity. Therefore, a comprehensive understanding of multi-host multi-pathogen interactions is of high significance in the context of biodiversity-ecosystem functioning. We investigated the relationship between plant diversity and aboveground obligate parasitic fungal pathogen ("pathogens" hereafter) diversity and infection in grasslands of a long-term, large-scale, biodiversity experiment with varying plant species (1-60 species) and plant functional group diversity (1-4 groups). To estimate pathogen infection of the plant communities, we visually assessed pathogen-group presence (i.e., rusts, powdery mildews, downy mildews, smuts, and leaf-spot diseases) and overall infection levels (combining incidence and severity of each pathogen group) in 82 experimental plots on all aboveground organs of all plant species per plot during four surveys in 2006.
Pathogen diversity, assessed as the cumulative number of pathogen groups on all plant species per plot, increased log-linearly with plant species diversity. However, pathogen incidence and severity, and hence overall infection, decreased with increasing plant species diversity. In addition, co-infection of plant individuals by two or more pathogen groups was less likely with increasing plant community diversity. We conclude that plant community diversity promotes pathogen-community diversity while at the same time reducing pathogen infection levels of plant individuals.
Give chance a chance
(2019)
A large part of biodiversity theory is driven by the basic question of what allows species to coexist in spite of a confined number of niches. A substantial theoretical background to this question is provided by modern coexistence theory (MCT), which rests on mathematical approaches of invasion analysis to categorize underlying mechanisms into factors that reduce either niche overlap (stabilizing mechanisms) or the average fitness differences of species (equalizing mechanisms). While MCT has inspired biodiversity theory in the search for these underlying mechanisms, we feel that the strong focus on coexistence causes a bias toward the most abundant species and neglects the plethora of species that are less abundant and often show high local turnover. Given the more stochastic nature of their occurrence, we advocate a complementary cross-level approach that links individuals, small populations, and communities and explicitly takes into account (1) a more complete inclusion of environmental and demographic stochasticity affecting small populations, (2) intraspecific trait variation and behavioral plasticity, and (3) local heterogeneities, interactions, and feedbacks. Focusing on mechanisms that drive the temporary coviability of species rather than infinite coexistence, we suggest a new approach that could be dubbed coviability analysis (CVA). From a modeling perspective, CVA builds on the merged approaches of individual-based modeling and population viability analysis but extends them to the community level. From an empirical viewpoint, CVA calls for a stronger integration of spatiotemporal data on variability and noise, changing drivers, and interactions at the level of individuals. The resulting large volumes of data from multiple sources could be strongly supported by novel techniques tailored to the discovery of complex patterns in high-dimensional data. By complementing MCT through a stronger focus on the coviability of less common species, this approach can help make modern biodiversity theory more comprehensive, predictive, and relevant for applications.
Give chance a chance
(2019)
A large part of biodiversity theory is driven by the basic question of what allows species to coexist in spite of a confined number of niches. A substantial theoretical background to this question is provided by modern coexistence theory (MCT), which rests on mathematical approaches of invasion analysis to categorize underlying mechanisms into factors that reduce either niche overlap (stabilizing mechanisms) or the average fitness differences of species (equalizing mechanisms). While MCT has inspired biodiversity theory in the search for these underlying mechanisms, we feel that the strong focus on coexistence causes a bias toward the most abundant species and neglects the plethora of species that are less abundant and often show high local turnover. Given the more stochastic nature of their occurrence, we advocate a complementary cross-level approach that links individuals, small populations, and communities and explicitly takes into account (1) a more complete inclusion of environmental and demographic stochasticity affecting small populations, (2) intraspecific trait variation and behavioral plasticity, and (3) local heterogeneities, interactions, and feedbacks. Focusing on mechanisms that drive the temporary coviability of species rather than infinite coexistence, we suggest a new approach that could be dubbed coviability analysis (CVA). From a modeling perspective, CVA builds on the merged approaches of individual-based modeling and population viability analysis but extends them to the community level. From an empirical viewpoint, CVA calls for a stronger integration of spatiotemporal data on variability and noise, changing drivers, and interactions at the level of individuals. The resulting large volumes of data from multiple sources could be strongly supported by novel techniques tailored to the discovery of complex patterns in high-dimensional data. By complementing MCT through a stronger focus on the coviability of less common species, this approach can help make modern biodiversity theory more comprehensive, predictive, and relevant for applications.
Deep waters represent the largest biome on Earth and the largest ecosystem of Costa Rica. Fungi play a fundamental role in global biogeochemical cycling in marine sediments, yet, they remain little explored. We studied fungal diversity and community composition in several marine sediments from 16 locations sampled along a bathymetric gradient (from a depth of 380 to 3,474 m) in two transects of about 1,500 km length in the Eastern Tropical Pacific (ETP) of Costa Rica. Sequence analysis of the V7-V8 region of the 18S rRNA gene obtained from sediment cores revealed the presence of 787 fungal amplicon sequence variants (ASVs). On average, we detected a richness of 75 fungal ASVs per sample. Ascomycota represented the most abundant phylum with Saccharomycetes constituting the dominant class. Three ASVs accounted for ca. 63% of all fungal sequences: the yeast Metschnikowia (49.4%), Rhizophydium (6.9%), and Cladosporium (6.7%). We distinguished a cluster composed mainly by yeasts, and a second cluster by filamentous fungi, but we were unable to detect a strong effect of depth and the overlying water temperature, salinity, dissolved oxygen (DO), and pH on the composition of fungal communities. We highlight the need to understand further the ecological role of fungi in deep-sea ecosystems.
Deep waters represent the largest biome on Earth and the largest ecosystem of Costa Rica. Fungi play a fundamental role in global biogeochemical cycling in marine sediments, yet, they remain little explored. We studied fungal diversity and community composition in several marine sediments from 16 locations sampled along a bathymetric gradient (from a depth of 380 to 3,474 m) in two transects of about 1,500 km length in the Eastern Tropical Pacific (ETP) of Costa Rica. Sequence analysis of the V7-V8 region of the 18S rRNA gene obtained from sediment cores revealed the presence of 787 fungal amplicon sequence variants (ASVs). On average, we detected a richness of 75 fungal ASVs per sample. Ascomycota represented the most abundant phylum with Saccharomycetes constituting the dominant class. Three ASVs accounted for ca. 63% of all fungal sequences: the yeast Metschnikowia (49.4%), Rhizophydium (6.9%), and Cladosporium (6.7%). We distinguished a cluster composed mainly by yeasts, and a second cluster by filamentous fungi, but we were unable to detect a strong effect of depth and the overlying water temperature, salinity, dissolved oxygen (DO), and pH on the composition of fungal communities. We highlight the need to understand further the ecological role of fungi in deep-sea ecosystems.