Connecting Theory and Empiricism
Population density is a key niche dimension. For most species, including many study species in the proposed CRC, population density varies on multiple spatial and temporal scales. High- and low-density environments differ in the availability of mating partners, in the intensity of resource competition, and in many other fitness-relevant ways. Thus there will be pressure on individuals to adapt to these different conditions by adjusting mate finding and mating strategies, aggressiveness, competitiveness, or foraging behaviours.
Focusing on spatial variation in population density, we will ask: Under what conditions are the differential selection pressures at high and low density expected to result in individual plasticity, and under what conditions will specialized high- and low-density genotypes evolve? Answering this question for population density as niche dimension is more challenging than for other environmental factors because population density engages in a feedback loop: Individual fitness and niche choice decisions influence local densities, which in turn influence fitness. This eco-evolutionary feedback will be explicitly accounted for in the new theory developed in this project. We will start with a simple mathematical model for the joint dynamics of multiple genotypes in a patchy landscape and will successively add more features, first niche conformance via plasticity, and then density-dependent niche choice. We will also study the conditions under which spatial variation in density can be generated and maintained and under what conditions individuals become evenly distributed in space such that density variation disappears. Finally, we will incorporate systematic temporal change in model parameters. Thereby, we can simulate important aspects of global change like habitat loss or habitat fragmentation and study their impacts on a population with individualised density niches, plasticity, and niche choice.
The proposed project includes two applications to study species within the CRC. First, the modelling results will be used to make predictions for the Drosophila evolve-and-resequence experiment in project B05 (Fricke). Second, we will adjust and parametrise the model to better understand the striking density differences among neighbouring breeding colonies of the Antarctic Fur Seal (in collaboration with project A01, Hoffman).