Sammendrag
Recent development and application of computer-intensive analysing techniques
have improved our ecological knowledge, and challenged the creativity of data
handling among ecologists. In this project I will explore how
computer-intensive estimates of continuous spatial distributions may be
applied to explain the spatial distribution of organisms. Methods to estimate
continuous spatial distributions give a value at each spatial pixle in the
landscape in question that is a result of the whole landscape sampled.
Compared to the traditional use of discrete point- or grid cell estimates,
continuous distributions have some beneficial properties: 1) Smoothing out
missing observations, or failure to observe certain spatial positions; 2) it
is partly independent of arbitrary choice of spatial resolution; and last, but
probably most important in an ecological context: 3) continuous spatial
distributions may be a single index that describes the whole aspect of
landscape configuration.
For the purpose of this project, 3 large-scale datasets have been made
available to me: 1) A large-scale, long-term dataset on grey-sided voles
Clethrionomys rufocanus from Hokaido, Japan, to study how resource
distribution is connected to the spatiotemporal dynamics; 2) A large-scale,
long-term dataset on capercaillie Tetrao tetrix that has been subject to
forest fragmentation, to study whether capercaillie perceives a landscape
mosaic or just the local habitat; and 3) A large-scale study based on line
transects of willow ptarmigan Lagopus lagopus that makes it possible to study
density dependent habitat utilisation.
Here, I suggest to use continuous spatial distributions to answer biological
questions related to the spatiotemporal dynamics of organisms and resource
utilisation in a landscape context. The project is scheduled for a period of
two years and includes funding of a post doc position for myself. I will
develop these ideas in close collaboration with highly competent environments
at the University of Oslo, and Alaska Department of Fish and Game (closely
linked to the University of
Vis fullstendig beskrivelse
Vitenskapelig sammendrag
Recent development and application of computer-intensive analysing techniques
have improved our ecological knowledge, and challenged the creativity of data
handling among ecologists. In this project I will explore how
computer-intensive estimates of continuous spatial distributions may be
applied to explain the spatial distribution of organisms. Methods to estimate
continuous spatial distributions give a value at each spatial pixle in the
landscape in question that is a result of the whole landscape sampled.
Compared to the traditional use of discrete point- or grid cell estimates,
continuous distributions have some beneficial properties: 1) Smoothing out
missing observations, or failure to observe certain spatial positions; 2) it
is partly independent of arbitrary choice of spatial resolution; and last, but
probably most important in an ecological context: 3) continuous spatial
distributions may be a single index that describes the whole aspect of
landscape configuration.
For the purpose of this project, 3 large-scale datasets have been made
available to me: 1) A large-scale, long-term dataset on grey-sided voles
Clethrionomys rufocanus from Hokaido, Japan, to study how resource
distribution is connected to the spatiotemporal dynamics; 2) A large-scale,
long-term dataset on capercaillie Tetrao tetrix that has been subject to
forest fragmentation, to study whether capercaillie perceives a landscape
mosaic or just the local habitat; and 3) A large-scale study based on line
transects of willow ptarmigan Lagopus lagopus that makes it possible to study
density dependent habitat utilisation.
Here, I suggest to use continuous spatial distributions to answer biological
questions related to the spatiotemporal dynamics of organisms and resource
utilisation in a landscape context. The project is scheduled for a period of
two years and includes funding of a post doc position for myself. I will
develop these ideas in close collaboration with highly competent environments
at the University of Oslo, and Alaska Department of Fish and Game (closely
linked to the University of
Vis fullstendig beskrivelse
