Projects per year
Abstract
The overarching theme for this thesis is spatial and temporal variations in ecosystems. The focus is on describing mechanisms that are responsible for generating the spatial and temporal patterns. The thesis contains two separate projects, each exploring a possible mechanism for pattern formation. In both projects, the model formulations result in partial integrodiﬀerential equations. The ﬁrst project in the thesis considers temporal patterns in a size structured population. Size structure is relevant for species that goes through signiﬁcant changes through their lifetime. The population’s response to regular temporal variations in the environment is investigated by introducing a periodic forcing in the system. This can for instance represent seasonal changes. The eﬀect of an imposed forcing is explored both when the underlying unforced system has a stable equilibrium and when it has stable oscillatory dynamics. The numerical solutions show regular cycles where the period is equal to, or an integer multiple of, the forcing period and where the population can have one or more pulses of reproduction in each cycle. Additionally, the numerical results indicate quasiperiodic or chaotic solutions, period doubling bifurcations and coexisting attractors. The bifurcation structure is similar to results for comparable unstructured population models in the literature. This indicates that size structure does not aﬀect the response to periodic forcing. The next project in the thesis considers spatiotemporal pattern formation in a predator–prey system where animals move towards higher ﬁtness. Reactiondiﬀusion systems have been used extensively to describe spatiotemporal patterns in a variety of systems. However, animals rarely move completely at random, as expressed by diﬀusion. This has lead to models with taxis terms, describing individuals moving in the direction of an attractant. An example is chemotaxis models, where bacteria are attracted to a chemical substance. From an evolutionary perspective, it is expected that animals act as to optimize their ﬁtness. Based on this principle, a predator–prey system with ﬁtness taxis and diﬀusion is proposed. Here, ﬁtness taxis refer to animals moving towards higher values of ﬁtness, and the speciﬁc growth rates of the populations are used as a measure of the ﬁtness values. To determine the conditions for pattern formation, a linear stability analysis is conducted. The analysis reveals that the ﬁtness taxis leads to mechanisms for pattern formation, which are based on the prey gathering together. It turns out, that in some cases the problem is not wellposed and an ultraviolet catastrophe occurs, i.e., perturbations with inﬁnitely short wavelength grow inﬁnitely fast. To prevent this, the population dynamics are revised with a spatial feeding kernel, that deﬁnes a spatial range wherein a predator consumes prey. A linear stability analysis for the revised system reveals the ultraviolet catastrophe is avoided and the basic mechanisms for pattern formation are unchanged. Numerical solutions to the revised system are computed to visualize the patterns. The solutions encompass stationary spatial patterns in addition to traveling waves, standing waves and irregular solutions that might be spatiotemporal chaos. The modeling approach of ﬁtness taxis presents a general way to express movement and it is concluded that the model provides a useful framework for describing generic mechanisms for pattern formation.
Original language  English 

Publisher  DTU Compute 

Number of pages  95 
Publication status  Published  2017 
Series  DTU Compute PHD2017 

Volume  453 
ISSN  09093192 
Fingerprint Dive into the research topics of 'Analysis of traitbased models in marine ecosystems.'. Together they form a unique fingerprint.
Projects
 1 Finished

Analysis of traitbased models in marine ecosystems
Heilmann, I. L. T., Sørensen, M. P., Andersen, K. H., Starke, J., Thygesen, U. H., Karamehmedovic, M., Wyller, J. A. & Andreasen, V.
Technical University of Denmark
01/10/2012 → 22/09/2017
Project: PhD