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  • 1.
    Felleki, Majbritt
    Dalarna University, School of Technology and Business Studies, Statistics. Swedish University of Agricultural Sciences.
    Genetic Heteroscedasticity for Domestic Animal Traits2014Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Animal traits differ not only in mean, but also in variation around the mean. For instance, one sire’s daughter group may be very homogeneous, while another sire’s daughters are much more heterogeneous in performance. The difference in residual variance can partially be explained by genetic differences. Models for such genetic heterogeneity of environmental variance include genetic effects for the mean and residual variance, and a correlation between the genetic effects for the mean and residual variance to measure how the residual variance might vary with the mean.

    The aim of this thesis was to develop a method based on double hierarchical generalized linear models for estimating genetic heteroscedasticity, and to apply it on four traits in two domestic animal species; teat count and litter size in pigs, and milk production and somatic cell count in dairy cows.

    The method developed is fast and has been implemented in software that is widely used in animal breeding, which makes it convenient to use. It is based on an approximation of double hierarchical generalized linear models by normal distributions. When having repeated observations on individuals or genetic groups, the estimates were found to be unbiased.

    For the traits studied, the estimated heritability values for the mean and the residual variance, and the genetic coefficients of variation, were found in the usual ranges reported. The genetic correlation between mean and residual variance was estimated for the pig traits only, and was found to be favorable for litter size, but unfavorable for teat count.

  • 2.
    Felleki, Majbritt
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Lee, Dongwhan
    Department of Statistics, Seoul National University, Seoul 151-747, Korea .
    Lee, Youngjo
    Department of Statistics, Seoul National University, Seoul 151-747, Korea .
    Gilmour, Arthur R.
    School of Mathematics and Applied Statistics, Faculty of Informatics, University of Wollongong, Wollongong, NSW 2522, Australia.
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Estimation of breeding values for mean and dispersion, their variance and correlation using double hierarchical generalized linear models2012In: Genetics Research, ISSN 0016-6723, Vol. 94, no 6, p. 307-317Article in journal (Refereed)
    Abstract [en]

    The possibility of breeding for uniform individuals by selecting animals expressing a small response to environment has been studied extensively in animal breeding. Bayesian methods for fitting models with genetic components in the residual variance have been developed for this purpose, but have limitations due to the computational demands. We use the hierarchical (h)-likelihood from the theory of double hierarchical generalized linear models (DHGLM) to derive an estimation algorithm that is computationally feasible for large datasets. Random effects for both the mean and residual variance parts of the model are estimated together with their variance/covariance components. An important feature of the algorithm is that it can fit a correlation between the random effects for mean and variance. An h-likelihood estimator is implemented in the R software and an iterative reweighted least square (IRWLS) approximation of the h-likelihood is implemented using ASReml. The difference in variance component estimates between the two implementations is investigated, as well as the potential bias of the methods, using simulations. IRWLS gives the same results as h-likelihood in simple cases with no severe indication of bias. For more complex cases, only IRWLS could be used, and bias did appear. The IRWLS is applied on the pig litter size data previously analysed by Sorensen & Waagepetersen (2003) using Bayesian methodology. The estimates we obtained by using IRWLS are similar to theirs, with the estimated correlation between the random genetic effects being −0·52 for IRWLS and −0·62 in Sorensen & Waagepetersen (2003).

  • 3.
    Felleki, Majbritt
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics. Sveriges Lantbruksuniversitet.
    Lundeheim, Nils
    Sveriges Lantbruksuniversitet.
    Genetic Control of Residual Variance for Teat Number in Pigs2013In: Proc. Assoc. Advmt. Anim. Breed. Genet., AAABG , 2013, p. 538-541Conference paper (Other academic)
    Abstract [en]

    The genetic improvement in litter size in pigs has been substantial during the last 10-15 years. The number of teats on the sow must increase as well to meet the needs of the piglets, because each piglet needs access to its own teat. We applied a genetic heterogeneity model on teat numberin sows, and estimated medium-high heritability for teat number (0.5), but low heritability for residual variance (0.05), indicating that selection for reduced variance might have very limited effect. A numerically positive correlation (0.8) between additive genetic breeding values for mean and for variance was found, but because of the low heritability for residual variance, the variance will increase very slowly with the mean.

  • 4.
    Felleki, Majbritt
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Lundeheim, Nils
    Sveriges lantbruksuniversitet, Institutionen för husdjursgenetik.
    Genetic Heteroscedasticity for Teat Count in PigsManuscript (preprint) (Other academic)
  • 5.
    Skarin, Anna
    et al.
    Sveriges lantbruksuniversitet.
    Sandström, Per
    Sveriges lantbruksuniversitet.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Buhot, Yann
    Sveriges lantbruksuniversitet.
    Nellemann, Christian
    Rhipto-Norwegian Center for Global Analyses.
    Renar och vindkraft II: Vindkraft i drift och effekter på renar och renskötsel2016Report (Other academic)
    Abstract [en]

    A surge in wind power development and associated road and powerline infrastructure is currently taking place worldwide. In Sweden and Fennoscandia, plans of large-scale wind power mill farms counting several hunderd windmills and their associated infrastructure of roads and powerlines are being implemented. In this report we describe how wind farms not only during construction, but also during operational phases impact reindeer and reindeer husbandry.

    Reindeer behaviour in relation to wind farms were studied in three different study areas in Västerbotten County in northern Sweden. In the Malå reindeer herding community the effects of Storliden and Jokkmokkliden wind farms were assessed during the calving and summer grazing period. In Vilhelmina Norra reindeer herding community, use of the winter grazing range around Stor-Rotliden wind farm was studied.

    Finally, the use of the Lögdeålandets winter grazing range by reindeer from the Byrkije reindeer herding community from Norway was assessed in relation to the Gabrielbergets wind farm. Reindeer habitat use was assessed through reindeer fecal pellet-group counts and by the use of GPS-collars. Data were before and during the construction phase and during the operational phase. We estimated reindeer habitat selection by developing resource selection function (RSF) models for each area in relation to the wind farm areas before, during and after construction. In addition, reindeer use was assessed around Gabrielsberget when 1) the wind farm was turned off for 40 days; 2) during operation when the reindeer were supplementary fed, and 3) during operation without supplementary feeding. Finally, the perception, experiences and views of reindeer herders were assessed through qualitative interviews.

    Our results showed that the reindeer in both calving and winter grazing areas were negatively affected by the wind farm developments. The reindeer avoided grazing in areas where they could see and/or hear the wind turbines and preferred to use areas where the wind turbines were topographically sheltered. In Malå, the reindeer increased the use by 60% of areas topographically sheltered away from the operating wind farms compared to before construction. In winter at Gabrielsberget wind farm, with no supplementary feeding, reindeer largely avoided a 3 km zone.

    When the reindeer were fed inside the wind farm and intensively perimeter herded to stay close to the wind farm, the reindeer still increased their use of areas locally where the wind turbines were sheltered by the topography with 13 %, compared to when they were not fed nor intensively herded. In the calving area in Malå, the use decreased with 16-20 % within 5 km from the wind farm. Moreover, the reindeer significantly increased their movement rate by 18 % within 4 km from the wind farm area during operation phase, compared to before the wind farms were developed.

    Reindeer actively avoid or reduce use of areas within 3 km from wind power farms both during construction and operational phases. Reindeer are more active or vigilant when close to wind power farms. Finally, reindeer tend to – but at more modest extent – to select more sheltered areas close to windmills if forced through supplementary feeding and herding.

    During winter, wind farms situated in upland terrain may reduce the availability and access to reindeer of important higher-altitude winter grazing areas. This may have particular adverse effects and reduce the resilience of reindeer husbandry against extreme weather such as icing by restraining range accessibility. As extreme weather events are expected to be more frequent with climate change, also the ability of reindeer husbandry to adapt becomes reduced with continuing piecemeal infrastructure development.

    The results from our projects have shown that wind farm developments have considerable impacts on reindeer and reindeer husbandry both during the calving season and during the winter season. The impacts for reindeer husbandry may be expected to be most severe in the winter grazing areas, where it often is difficult to find alternative grazing areas. A direct effect of a wind farm in the middle of the winter grazing area, such as Gabrielsberget wind farm, may be that the reindeer need to be supplementary fed and intensively herded to keep the reindeer in the area, subsequently increasing the work load on the reindeer herders. It also reduces the ability of herders to mitigate extreme weather by moving reindeer to dwindling alternative grazing sites.

    Other infrastructure, such as roads and power lines, also affect the reindeer habitat selection. Prior to wind farm development, reindeer avoided areas in the vicinity of larger (>5 m wide) roads. After the wind farm was developed, the reindeer at Stor-Rotliden stopped avoiding the large roads and instead increased the habitat use closer to the large roads in the only alternative foraging areas. At Gabrielsberget, the reindeer also used areas close to the large roads, including the highway E4, when the reindeer were freely ranging in order to avoid the wind farm. This obviously increases the risk of traffic accidents and herders are subsequently required to intensify herding.

    Mitigation measures for herders and developers in areas where wind farms are already established are presented. Especially, established associated road infrastructure to the windmills should be closed for public use to avoid recreational activities, whether by ATVs or snowmobiles, or by hunters. Furthermore, a close contact should be maintained between the power company and the reindeer herding community to prevent road or mill maintenance work during sensitive periods for the reindeer. Other more regional measures to facilitate reindeer movement and migration between different grazing ranges may be to establish fences along major roads and railways (eg. E4 or the main railroad through Sweden) combined with strategically placed ecoducts.

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