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  • 1. Anglart, D
    et al.
    Emanuelson, U
    Rönnegård, Lars
    Dalarna University, School of Information and Engineering, Statistics.
    Sandgren, C Hallén
    Detecting and predicting changes in milk homogeneity using data from automatic milking systems.2021In: Journal of Dairy Science, ISSN 0022-0302, E-ISSN 1525-3198, Vol. 104, no 10, p. 11009-11017Article in journal (Refereed)
    Abstract [en]

    To ensure milk quality and detect cows with signs of mastitis, visual inspection of milk by prestripping quarters before milking is recommended in many countries. An objective method to find milk changed in homogeneity (i.e., with clots) is to use commercially available inline filters to inspect the milk. Due to the required manual labor, this method is not applicable in automatic milking systems (AMS). We investigated the possibility of detecting and predicting changes in milk homogeneity using data generated by AMS. In total, 21,335 quarter-level milk inspections were performed on 5,424 milkings of 624 unique cows on 4 farms by applying visual inspection of inline filters that assembled clots from the separate quarters during milking. Images of the filters with clots were scored for density, resulting in 892 observations with signs of clots for analysis (77% traces or mild cases, 15% moderate cases, and 8% heavy cases). The quarter density scores were combined into 1 score indicating the presence of clots during a single cow milking and into 2 scores summarizing the density scores in cow milkings during a 30-h sampling period. Data generated from the AMS, such as milk yield, milk flow, conductivity, and online somatic cell counts, were used as input to 4 multilayer perceptron models to detect or predict single milkings with clots and to detect milking periods with clots. All models resulted in high specificity (98-100%), showing that the models correctly classified cow milkings or cow milking periods with no clots observed. The ability to successfully classify cow milkings or cow periods with observed clots had a low sensitivity. The highest sensitivity (26%) was obtained by the model that detected clots in a single milking. The prevalence of clots in the data was low (2.4%), which was reflected in the results. The positive predictive value depends on the prevalence and was relatively high, with the highest positive predictive value (72%) reached in the model that detected clots during the 30-h sampling periods. The misclassification rate for cow milkings that included higher-density scores was lower, indicating that the models that detected or predicted clots in a single milking could better distinguish the heavier cases of clots. Using data from AMS to detect and predict changes in milk homogeneity seems to be possible, although the prediction performance for the definitions of clots used in this study was poor.

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  • 2.
    Derakhshan, Reza
    et al.
    Dalarna University, School of Information and Engineering.
    Yousefzadeh Boroujeni, Soroush
    Dalarna University, School of Information and Engineering.
    Body Rumen Fill Scoring of Dairy Cows Using Digital Images2024Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The research presented in this thesis focuses on an innovative use of digital imaging, and the machine learning techniques to assess the body rumen fill scoring in dairy cows. This study aims to enhance the efficiency of monitoring and managing dairy cow health, which is crucial for the dairy industry's productivity and sustainability.

    The primary objective was to develop an automated annotation system fore valuating rumen fill status in dairy cows using digital images extracted from recorded videos. This system leverages advanced machine learning algorithms and neural networks, aiming to mimic manual assessments by veterinarians and specialists on farms. To achieve the above objectives, this thesis made use of already existing video records from a Swedish dairy farm hosting mainly the Swedish Redand the Swedish Holstein breeds. A subset of these images were then processed, manually classified using a modified rumen fill scoring system based on visual assessment, and supervised classification algorithms were trained on 277 manually annotated images.

    The thesis explored various machine learning techniques for classifying these images, including Logistic Regression, Support Vector Machine (SVM), and a Deep Neural Network using the VGG16 architecture. These models were trained, validated, and tested with a dataset that included variations in cow color patterns, aiming to determine the most effective approach for automated rumen fill scoring.The results indicated that while each model had its strengths and weaknesses, the simple logistic model was performing the best in terms of test accuracy and F1 score.

    This research contributes to the field of precision livestock farming, particularly in the context of dairy farming. By automating the process of rumen fill scoring, the study aims to provide dairy farmers with a reliable, efficient, and cost-effective tool for monitoring cow health. This tool has the potential to enhance dairy cow welfare, improve milk production, and support the sustainability of dairy farming operations. However, at the current state, the model accuracy of the best model was only moderate. There is a need for further improvement of the prediction performance possibly by adding more cow images, using improved image processing, and feature engineering.

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  • 3.
    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.

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  • 4.
    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).

  • 5.
    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.

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    Genetic Control of Residual Variance for Teat Number in Pigs
  • 6.
    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)
  • 7. Hallén Sandgren, C
    et al.
    Anglart, D
    Klaas, I C
    Rönnegård, Lars
    Dalarna University, School of Information and Engineering, Statistics.
    Emanuelson, U
    Homogeneity density scores of quarter milk in automatic milking systems.2021In: Journal of Dairy Science, ISSN 0022-0302, E-ISSN 1525-3198, Vol. 104, no 9, p. 10121-10130Article in journal (Refereed)
    Abstract [en]

    Milk quality and clinical mastitis in dairy cows are monitored by detecting visually abnormal milk. A standardized method to evaluate clots in milk and studies of the incidence and dynamics of clots in milk at the quarter level are lacking. We validated a method to score clot density in quarter milk samples and describe the prevalence and dynamics of the density scores between consecutive samplings and periods in 4 farms with automatic milking systems. Using in-line filters, we collected quarter milk samples at each milking during 3 periods of 30 h each in each farm. Clot density was scored based on coverage of the filter area as 0 (negative), 1 (trace), 2 (mild), 3 (moderate), 4 (heavy), and 5 (very heavy). The score for a specific quarter and milking is referred to as the quarter milking score (QMS). Three assessors independently scored 902 images of filter samples with a Fleiss kappa value of 0.72. In total, 21,202 quarter milk samples from 5,398 milkings of 621 cows were collected. Of the quarter filter samples, 2.4% had visible clots, distributed as mild (1.4%), moderate (0.6%), heavy (0.3%), and very heavy (<0.1%, n = 8). Cases with a cow period sum of QMS ≥ 4, corresponding to 9.4% of all periods, harbored 86% and 94% of all QMS of 2 to 5 and 3 to 5, respectively. Of these cases, cows sampled in all 3 periods and clots in only 1 period had a quarter period sum score ≥ 1 in 1.8 different quarters in average. Corresponding numbers for the cows with clots or traces in 2 or 3 periods were 2.2 and 2.5 different quarters, respectively. A QMS of 2 to 5 in the preceding milking increased the chance of a QMS >1 in the following milking, with an average chance of 38%. The probability of a QMS > 1 increased with increasing previous QMS, a higher sum of QMS during the milking period, longer milking interval, and higher lactation number, but decreased with increasing days in milk. Our study showed that the method of clot-density scoring is feasible to perform and reproducible for investigating the occurrence and dynamics of clots in milk. Elevated clot-density scores clustered within certain cows and cow periods and appeared in new quarters of the cows over time. The low recurrence of QMS of 1 and 2 within quarters indicated that QMS 3 could be a reasonable threshold for detecting quarters with abnormal milk that require further attention.

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  • 8.
    Hansson, I
    et al.
    Swedish University of Agricultural Sciences, Uppsala.
    Silvera, A
    Swedish University of Agricultural Sciences, Uppsala.
    Ren, K
    Swedish University of Agricultural Sciences, Uppsala.
    Woudstra, S
    University of Copenhagen, Frederiksberg, Denmark.
    Skarin, A
    Swedish University of Agricultural Sciences, Uppsala.
    Fikse, W F
    Swedish University of Agricultural Sciences, Uppsala.
    Nielsen, P P
    RISE Research Institute of Sweden, Lund.
    Rönnegård, Lars
    Dalarna University, School of Information and Engineering, Statistics. Swedish University of Agricultural Sciences, Uppsala.
    Cow characteristics associated with the variation in number of contacts between dairy cows2023In: Journal of Dairy Science, ISSN 0022-0302, E-ISSN 1525-3198, Vol. 106, no 4, p. 2685-2699Article in journal (Refereed)
    Abstract [en]

    In modern freestall barns where large groups of cows are housed together, the behavior displayed by herd mates can influence the welfare and production of other individuals. Therefore, understanding social interactions in groups of dairy cows is important to enhance herd management and optimize the outcomes of both animal health and welfare in the future. Many factors can affect the number of social contacts in a group. This study aimed to identify which characteristics of a cow are associated with the number of contacts it has with other group members in 2 different functional areas (feeding and resting area) to increase our understanding of the social behavior of dairy cows. Inside 2 herds housed in freestall barns with around 200 lactating cows each, cow positions were recorded with an ultra-wideband real-time location system collecting all cows' positions every second over 2 wk. Using the positioning data of the cows, we quantified the number of contacts between them, assuming that cows spending time in proximity to one another (within a distance of 2.5 m for at least 10 min per day) were interacting socially. We documented in which barn areas these interactions occurred and used linear mixed models to investigate if lactation stage, parity, breed, pregnancy status, estrus, udder health, and claw health affect the number of contacts. We found variation in the number of contacts a cow had between individuals in both functional areas. Cows in later lactation had more contacts in the feeding area than cows in early lactation. Furthermore, in one herd, higher parity cows had fewer contacts in the feeding area than first parity cows, and in the other herd, cows in third parity or higher had more contacts in the resting area. This study indicates that cow characteristics such as parity and days in milk are associated with the number of contacts a cow has daily to its herd mates and provides useful information for further research on social interactions of dairy cows.

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  • 9.
    Kroese, Adrien
    et al.
    Swedish University of Agricultural sciences, Uppsala.
    Alam, Moudud
    Dalarna University, School of Information and Engineering, Statistics.
    Hernlund, Elin
    Swedish University of Agricultural sciences, Uppsala.
    Berthet, David
    Sony Nordic, Lund.
    Tamminen, Lena-Mari
    Swedish University of Agricultural sciences, Uppsala.
    Fall, Nils
    Swedish University of Agricultural sciences, Uppsala.
    Högberg, Niclas
    Swedish University of Agricultural sciences, Uppsala.
    3D pose estimation to detect posture transition in free-stall housed dairy cows2024In: Journal of Dairy Science, ISSN 0022-0302, E-ISSN 1525-3198Article in journal (Refereed)
    Abstract [en]

    Free stall comfort is reflected in various indicators, including the ability for dairy cattle to display unhindered posture transition movements in the cubicles. To ensure farm animal welfare, it is instrumental for the farm management to be able to continuously monitor occurrences of abnormal motions. Advances in computer vision have enabled accurate kinematic measurements in several fields such as human, equine and bovine biomechanics. An important step upstream to measuring displacement during posture transitions is to determine that the behavior is accurately detected. In this study, we propose a framework for detecting lying to standing posture transitions from 3D pose estimation data. A multi-view computer vision system recorded posture transitions between Dec. 2021 and Apr. 2022 in a Swedish stall housing 183 individual cows. The output data consisted of the 3D coordinates of specific anatomical landmarks. Sensitivity of posture transition detection was 88.2% while precision reached 99.5%. Analyzing those transition movements, breakpoints detected the timestamp of onset of the rising motion, which was compared with that annotated by observers. Agreement between observers, measured by intra-class correlation, was 0.85 between 3 human observers and 0.81 when adding the automated detection. The intra-observer mean absolute difference in annotated timestamps ranged from 0.4s to 0.7s. The mean absolute difference between each observer and the automated detection ranged from 1.0s to 1.3s. There was a significant difference in annotated timestamp between all observer pairs but not between the observers and the automated detection, leading to the conclusion that the automated detection does not introduce a distinct bias. We conclude that the model is able to accurately detect the phenomenon of interest and that it is equatable to an observer.

  • 10.
    Marina, Héctor
    et al.
    Swedish University of Agricultural Sciences, Uppsala.
    Ren, Keni
    Swedish University of Agricultural Sciences, Uppsala.
    Hansson, Ida
    Swedish University of Agricultural Sciences, Uppsala.
    Fikse, Freddy
    Swedish University of Agricultural Sciences, Uppsala.
    Nielsen, Per Peetz
    RISE Research Institute of Sweden; RISE Ideon, Lund.
    Rönnegård, Lars
    Dalarna University, School of Information and Engineering, Statistics. Swedish University of Agricultural Sciences, Uppsala.
    New insight into social relationships in dairy cows, and how time of birth, parity and relatedness affect spatial interactions later in life2024In: Journal of Dairy Science, ISSN 0022-0302, E-ISSN 1525-3198, Vol. 107, no 2, p. 1110-1123Article in journal (Refereed)
    Abstract [en]

    Social interactions between cows play a fundamental role in the daily activities of dairy cattle. Real-time location systems provide on a continuous and automated basis information about the position of individual cows inside barns, offering a valuable opportunity to monitor dyadic social contacts. Understanding dyadic social interactions could be applied to enhance the stability of the social structure promoting animal welfare and to model disease transmission in dairy cattle. This study aimed to identify the impact of different cow characteristics on the likelihood of the formation and persistence of social contacts in dairy cattle. The individual position of the lactating cows was automatically collected once per second for 2 weeks, using an ultra-wideband system on a Swedish commercial farm consisting of nearly 200 dairy cows inside a free-stall barn. Social networks were constructed using the position data of 149 cows with available information on all characteristics during the study period. Social contacts were considered as a binary variable indicating whether a cow pair was within 2.5 m of each other for at least 10 min per day. The role of cow characteristics in social networks was studied by applying separable temporal exponential random graph models. Our results revealed that cows of the same parity interacted more consistently, as well as those born within 7 d of each other or are closely related by pedigree. The repeatability of the topological parameters indicated a consistent short-term stability of the individual animal roles within the social network structure. Additional research is required to elucidate the underlying mechanisms governing the long-term evolution of social contacts among dairy cattle and to investigate the relationship between these networks and the transmission of diseases in the dairy cattle population.

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  • 11.
    Ren, Keni
    et al.
    Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden.
    Alam, Moudud
    Dalarna University, School of Information and Engineering, Statistics.
    Nielsen, Per Peetz
    Department of Agriculture and Food, RISE Research Institutes of Sweden (RISE), Lund, Sweden.
    Gussmann, Maya
    Department of Veterinary and Animal Sciences, University of Copenhagen, Frederiksberg, Denmark.
    Rönnegård, Lars
    Dalarna University, School of Information and Engineering, Statistics. Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden.
    Interpolation Methods to Improve Data Quality of Indoor Positioning Data for Dairy Cattle2022In: Frontiers in Animal Science, E-ISSN 2673-6225, Vol. 3, article id 896666Article in journal (Refereed)
    Abstract [en]

    Position data from real-time indoor positioning systems are increasingly used for studying individual cow behavior and social behavior in dairy herds. However, missing data challenges achieving reliable continuous activity monitoring and behavior studies. This study investigates the pattern of missing data and alternative interpolation methods in ultra-wideband based real-time indoor positioning systems in a free-stall barn. We collected 3 months of position data from a Swedish farm with around 200 cows. Data sampled for 6 days from 69 cows were used in subsequent analyzes to determine the location and duration of missing data. Data from 20 cows with the most reliable tags were selected to compare the effects of four different interpolation methods (previous, linear interpolation, cubic spline data interpolation and modified Akima interpolation). By comparing the observed data with the interpolations of the simulated missing data, the mean error distance varied from around 55 cm, using the previously last observed position, to around 17 cm for modified Akima. Modified Akima interpolation has the lowest error distance for all investigated activities (rest, walking, standing, feeding). Larger error distances were found in areas where the cows walk and turn, such as the corner between feeding and cubicles. Modified Akima interpolation is expected to be useful in the subsequent analyses of data gathered using real-time indoor positioning systems.

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  • 12.
    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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