@article{SiegerHovestadt2020,
  author    = {Sieger, Charlotte Sophie and Hovestadt, Thomas},
  title     = {The degree of spatial variation relative to temporal variation influences evolution of dispersal},
  series = {Oikos},
  volume    = {129},
  journal   = {Oikos},
  number    = {11},
  doi       = {10.1111/oik.07567},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-239049},
  pages     = {1611 -- 1622},
  year      = {2020},
  abstract  = {In the face of ongoing global climate and land use change, organisms have multiple possibilities to cope with the modification of their environment. The two main possibilities are to either adapt locally or disperse to a more suitable habitat. The evolution of both local adaptation and dispersal interacts and can be influenced by the spatial and temporal variation (of e.g. temperature or precipitation). In an individual based model (IBM), we explore evolution of phenotypes in landscapes with varying degree of spatial relative to global temporal variation in order to examine its influence on the evolution of dispersal, niche optimum and niche width. The relationship between temporal and spatial variation did neither influence the evolution of local adaptation in the niche optimum nor of niche widths. Dispersal probability is highly influenced by the spatio-temporal relationship: with increasing spatial variation, dispersal probability decreases. Additionally, the shape of the distribution of the trait values over patch attributes switches from hump- to U-shaped. At low spatial variance more individuals emigrate from average habitats, at high spatial variance more from extreme habitats. The comparatively high dispersal probability in extreme patches of landscapes with a high spatial variation can be explained by evolutionary succession of two kinds of adaptive response. Early in the simulations, extreme patches in landscapes with a high spatial variability act as sink habitats, where population persistence depends on highly dispersive individuals with a wide niche. With ongoing evolution, local adaptation of the remaining individuals takes over, but simultaneously a possible bet-hedging strategy promotes higher dispersal probabilities in those habitats. Here, in generations that experience extreme shifts from the temporal mean of the patch attribute, the expected fitness becomes higher for dispersing individuals than for philopatric individuals. This means that under certain circumstances, both local adaptation and high dispersal probability can be selected for for coping with the projected environmental changes in the future.},
  language  = {en}
}
@phdthesis{Sieger2020,
  author    = {Sieger, Charlotte Sophie},
  title     = {Potential evolutionary responses to landscape heterogeneity and systematic environmental trends},
  doi       = {10.25972/OPUS-21669},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-216690},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2020},
  abstract  = {Over the course of the last century, humans have witnessed drastic levels of global environmental change that endangered both, the survival of single species as well as biodiversity itself. This includes climate change, in both environmental means and in variance and subsequently frequent extreme weather events, as well as land use change that species have to cope with. With increasing urbanization, increasing agricultural area and increasing intensification, natural habitat is not only lost, but also changes its shape and distribution in the landscape. Both aspects can heavily influence an individual's fitness and therefore act as a selective force promoting evolutionary change. This way climate change influences individuals' niches and dispersal. Local adaptation and dispersal are not independent of each other. Dispersal can have two opposite effects on local adaptation. It can oppose local adaptation, by promoting the immigration of maladapted indi- viduals or favor local adaptation by introducing better adapted genotypes. Which of those effects of dispersal on local adaptation emerges in a population depends on the dispersal strategies and the spatial structure of the landscape. In principle an adaptive response can include adjustment of the niche optimum as well as habitat tolerance (niche width) or (instead) ecological tracking of adequate conditions by dispersal and range shifting. So far, there has been no extensive modeling study of the evolution of the environmental niche optimum and tolerance along with dispersal probability in complex landscapes. Either only dispersal or (part of ) the environmental niche can evolve or the landscapes used are not realistic but rather a very abstract representation of spatial structures. I want to try and disentangle those different effects of both local adaptation and dispersal during global change, as well as their interaction, especially considering the separation between the effects of increasing mean and increasing variance. For this, I implemented an individual based model (IBM), with escalating complexity. I showed that both on a temporal as well as on a spatial scale, variation can be more influential then mean conditions. Indeed, the actual spatial configuration of this heterogeneity and the relationship between spatial and temporal heterogeneity affect the evolution of the niche and of dispersal probability more than temporal or spatial mean conditions. I could show that in isolated populations, an increase of an environmental attribute's mean or variance can lead to extinction, under certain conditions. In particular, increasing variance cannot be tracked forever, since increasing tolerance has distinct limits of feasibility. Increasing mean conditions can also occur too fast to be tracked, especially from generalist individuals. When expanding the model to the metapopulation level without a temporal environmental trend, the degree of spatial vs.temporal heterogeneity influenced the evolution of random dispersal heavily. With increasing spatial heterogeneity, individuals from extreme and rare patches evolve from being philopatric to dispersive, while individuals from average patches switch in the opposite direction. With the last expansion to a different set of landscapes with varying degrees of edge density, I could show that edge effects are strong in pseudo-agricultural landscapes, while in pseudo-natural habitats they were hardly found, regardless of emigration strategy. Sharp edges select against dispersal in the edge patches and could potentially further isolate populations in agricultural landscapes. The work I present here can also be expanded further and I present several suggestions on what to do next. These expansions could help the realism of the model and eventually shed light on its bearing on ecological global change predictions. For example species distribution models or extinction risk models would be more precise, if they included both spatial and temporal variation. The current modeling practices might not be suffcient to describe the possible outcomes of global change, because spatio-temporal heterogeneity and its influence on species' niches is too important to be ignored for longer.},
  language  = {en}
}