Individuals differ. This seemingly trivial statement has led to paradigm shifts, as three different fields of organismal biology have seen a marked change in key concepts over the last years. In behavioral biology, it has been realized that there are profound differences between individuals and that these can be stable over time and across contexts, giving rise to the concept of animal personalities. In ecology, an increasing focus is likewise on the considerable variation in the ecological niche realized by species, populations, and even individuals. In evolutionary biology, where individual variation has always been central, there is an increasing awareness of the complexity with which genotypes interact with the environment to produce unique phenotypes. As a consequence, a concept of an individualized niche is needed, rather than focusing only on a mean value for a given population.
The central research goal of the collaborative research center is to redefine the niche concept on the individual level. By doing so, we want to gain a comprehensive understanding of how individual phenotypes interact with their environment and what the ensuing consequences for ecological and evolutionary processes are. We hypothesize that, across taxa, the interaction between the individualized phenotype and the environment results in individualized niches via three mechanisms of adjustment and adaptation: niche choice, niche conformance and niche construction.
Current funding: Collaborative research center SFB Transregio 212 funded by the German Research Foundation (DFG), 2018-2021
Wheatears (genus Oenanthe) are an about 6.6 my old group of passerine birds mainly inhabiting arid and rocky ecosystems of Eurasia and Africa that exhibit striking patterns of phenotypic polymorphism: (i) High rates of character switching across the phylogeny suggests multiple convergent origins of numerous phenotypes, including melanin-based coloration and complex behavioral traits such as seasonal migration. (ii) Multiple interspecific differences segregate as polymorphisms within species. And finally, (iii) one of these polymorphisms found in black-eared wheatear (O. hispanica) and pied wheatear (O. pleschanka) supposedly arose by reciprocal introgression among these two pervasively hybridizing sister species. The convergent emergence of phenotypes across the phylogeny both within and between species points towards an involvement of a labile molecular switch between phenotypes.
We aim at addressing multiple questions relating to the evolution of phenotypic diversity within and between species, and to the evolution of species. Currently we settled out to characterize the genetic population structure across the hybrid zone of black-eared and pied wheatear using genome-wide polymorphism data. In future phenotypic, genetic, and methylomic polymorphism data from within these species, from three hybrid zones, and from across the wheatear genus will be used to identify the molecular bases of diverse color phenotypes and study their evolution, including the demographic and genomic constrains under which they evolve.
Current funding: Research Grant BU-3456/3-1 by the German Research Foundation (DFG), 2018-2021
People involved: Reto Burri
The Jena Experiment is one of the longest-running biodiversity experiments worldwide. It was designed to study the functional consequences of grassland biodiversity. Experimental plots were established already in 2002 from a pool of 60 local grassland plant species assembled in experimental communities ranging from monocultures to 60-species mixtures. The field site in the Saale floodplain currently hosts more than 300 experimental plots in an area of 10 ha. A recent video provides an excellent overview.
The Jena Experiment has provided important insights into the links between biodiversity, population processes in grassland communities, and ecosystem fluxes and services. Specifically, it has demonstrated positive effects of plant diversity on plant productivity and a large number of other ecosystem variables, supporting the hypothesis that biodiversity maintains ecosystem multifunctionality. The value of the Jena Experiment has increased over time as now long-term plots allow capturing representative biodiversity effects and the unprecedented wealth of data enables unique syntheses and meta-analyses. An extensive paper published in Basic and Applied Ecology gives a coprehensive overview of the findings from the first 15 years of the experiment.
The Jena Experiment has always been a highly collaborative project that involves several national and international collaboration partners. It has been immensely productive in terms of scientific output with well over 200 peer-reviewed scientific publications. Anne Ebeling from the Population Ecology Group has served as the scientific coordinator of the project since 2009. Since 2016, Anne has been running the subproject Consumer community structure and stability as a principle investigator.
Nutrient Network (NUTNET) One the most important impacts of human activity on grassland ecosystems is the application of fertilizers and the alteration of grazers-plant interactions. To study the effect of these activities, the Nutrient Network (NUTNET), a grassroots research effort, was established in 2007. This research network, coordinated by the Department of Ecology, Evolution, and Behaviour at the University of Minnesota, comprises over 100 grassland sites worldwide, allowing global analyses focussing on the impact of fertilization and alteration of plant-consumer interactions on grassland ecosystems. The Jena NUTNET site, one of three in Germany, is coordinated by Anne Ebeling from the Population Ecology Group and Christiane Roscher from iDiv in Leipzig. In Jena we are especially interested in the consequences of fertilizer application for plant-consumer interactions and related ecosystem processes (e.g. leaf damage by arthropods).
People involved: Anne Ebeling
Climate change affects biodiversity at different levels of organization, from the traits of individuals to populations and communities. These effects at different levels are typically the focus of different disciplines. Effects on phenotypic traits, such as body size (morphological) and the timing of reproduction (phenological traits), are often studied separately from the effects of climate change on demographic rates, such as survival and reproduction. But these effects on demographic rates come about via effects on traits. Moreover, at the population level, the effects of trait changes on one demographic rate may be buffered by opposing changes in other demographic rates. Therefore, a hierarchical framework that integrates traits and demographic rates when considering the climate effects on population dynamics is required to obtain a mechanistic understanding of climate-driven impacts on biodiversity. Changes in traits and demographic rates are triggered by both long-term changes in means of climatic factors, and by short spells of extreme weather, which are best captured by temporal climatic variability. Therefore, we here propose to consider changes in both climatic means and variability when assessing how traits moderate the effects of climate on population dynamics. To this end we will complement analyses of a recently-assembled data set (applying hierarchical population models and meta-analysis) with simulations. The proposed research will advance biodiversity research by developing a mechanistic framework that improves our ability to predict climate-induced changes across levels of organization, and by deriving generalizations of how species with different life-histories respond to climate change.
Current funding: sDiv working group funded by the German Centre for Integrative Biodiversity Research (iDiv)
People involved: Holger Schielzeth
Adaptive evolutionary change occurs when selection is acting on heritable trait variation. But not all evolutionary responses are straightforward. Genetic covariation in particular may modify the speed and the direction of adaptive evolution. Genetic covariation arises from pleiotropy (the same genetic factors influence multiple traits) or from linkage disequilibrium (coinheritance) of multiple independent genetic factors. This can affect multiple traits of the same individual, but also traits expressed in different individuals, such as traits expressed in females and males. We have therefore studied the multivariate genetic architecture of trait variation in multiple species of grasshoppers to evaluated if evolution in grasshoppers is constraint or shaped by genetic covariation.
Sexual selection is a particularly potent force that can result in the evolution of extravagant ornaments and is therefore a driving force in generating biological diversity. We have therefore focused our research on the highly sexually dimorphic club-legged grasshopper. The species is unusual in that males possess swollen front legs (‘Popeye arms’). Neither females nor any related species show this feature and this begs the question about how these structures are used and how they have evolved. We have therefore studied the behavioral ecology of sexual selection in this intriguing species. It turns out that the courtship behavior of this species is highly peculiar.
Statistical Quantification of Individual Differences is the product of the SQuID working group. The package aims to help scholars who, like us, are interested in understanding patterns of phenotypic variance. Individual differences are the raw material for natural selection to act on and hence the basis of evolutionary adaptation. Understanding the sources of phenotypic variance is thus a most essential feature of biological investigation. Mixed effects models offer a great, albeit challenging tool in this context. Disseminating the properties, potentials and interpretational challenges in the research community is thus a foremost goal of SQuID.
The squid package has two main objectives: First, it provides an educational tool useful for students, teachers and researchers who want to learn to use mixed-effects models. Users can experience how the mixed-effects model framework can be used to understand biological phenomena by interactively exploring simulated multilevel data. Second, squid offers research opportunities to those who are already familiar with mixed-effects models, as it enables the generation of datasets that users may download and use for a range of simulation-based statistical analyses such as power and sensitivity analysis of multilevel and multivariate data.