The use of genetic methods in research on wild animal species has opened up a new world of possibilities. In this project, we want to develop new analytical opportunities, and explore how genetic data can be used to give us better knowledge about kinship relationships and migration within wild populations of wild ungulates. Genetic data can also help provide more accurate population estimates and reduce the need for invasive data collection methods.
An important advantage of genetic methods is that they can largely be based on non-invasive collection of samples (e.g., from feathers, hair, faeces). This has both a positive aspect to animal welfare and is an important quality for the actual collection work. For instance, collection of material for genetic samples can easily be included as part of existing monitoring programs. This way the use of genetic methods provide added value to already ongoing monitoring activity.
In Norway, the total post-harvest number of wild, forest-dwelling ungulates (moose, red deer and roe deer) equals about 400,000 animals. The large ungulates are ecological key species, and they also provide valuable ecosystem services as targets for recreational hunting. In addition, they might cause significant societal costs through damage on agriculture and forestry, through wildlife vehicle collisions, and through the measures taken to prevent these problems.
In Norway, deer populations are mainly regulated through recreational hunting. The objectives for population development and the choice of instruments to achieve the desired objectives are defined by local authorities and stakeholders.
For several decades, Norwegian hunters have collected data from harvested ungulates and survey data collected during the actual hunting practice. These data represent an important basis for the management of local ungulate populations. The establishment of a national monitoring program for wild cervids, and a national service for data storage have been important factors for the currently available knowledge basis.
At the same time as the national distribution and size of the populations have changed, the social and ecological issues related to the ungulate populations have also changed. As a consequence, the management’s knowledge needs have also changed. To meet these new needs of the management, development and introduction of new tools and methods represent necessary progress.
In this project we will work with genetic markers. Genetic markers are recognizable parts of the DNA and are linked to specific traits or genetic traits. The variation within the genetic markers provides an opportunity to map different individuals' variants of specific genes. In this way, individuals can be given a "genetic fingerprint" that can be used both for unique identification, but also to determine kinship between different individuals.
There are several types of genetic markers, but in our project we will primarily use so-called SNPs. These are very short and simple markers, but with a number of advantages. Compared to the use of longer and more complex markers, SNPs provide more high-resolution data. Analyses across laboratories are also directly comparable, which is not always the case when using longer markers. This increases the precision of the data, simplifies collaboration across studies and laboratories, and increase the potential areas of use.
We aim to implement four work packages in this project. In the first work package, we will develop and validate a SNP-chip for Norwegian deer. A SNP-chip is a collection of defined SNP-markers that are used to determine the individual's SNP-variants. This can in turn be used to calculate relationships between different individuals.
In the second work package, we will compare the precision of kinship analyses based on SNPs versus analyses based on data from microsatellites. The material for this work comes from a moose study on the island of Vega.
In the third work package, we want to take a closer look at the genotypic and phenotypic characteristics that characterize successful individuals in a hunted red deer population. The material for this work package has been collected from c. 2000 red deer harvested over a decade on the island of Otterøya in Namsos.
In the last work package, we aim to explore the possibility of using genetic data and kinship analyses to calculate the population size of ungulates. The method is based on genetic data and information about the age of each individual. Population size is estimated on the basis of the proportion of animals being close relatives (siblings, mother-offspring, father-offspring). The data material for this work package is collected from moose in Trøndelag.