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  • 1.
    Johansson, Sverker
    Högskolan i Jönköping, Högskolan för lärande och kommunikation.
    What constraints does animal communication place on human language origins?2010Conference paper (Other academic)
  • 2. Marjanovic, J.
    et al.
    Mulder, H. A.
    Rönnegård, Lars
    Dalarna University, School of Information and Engineering, Statistics. Swedish University of Agricultural Sciences, Uppsala.
    de Koning, D. -J
    Bijma, P.
    Capturing indirect genetic effects on phenotypic variability: Competition meets canalization2022In: Evolutionary Applications, E-ISSN 1752-4571, Vol. 15, no 4, p. 694-705Article in journal (Refereed)
    Abstract [en]

    Phenotypic variability of a genotype is relevant both in natural and domestic populations. In the past two decades, variability has been studied as a heritable quantitative genetic trait in its own right, often referred to as inherited variability or environmental canalization. So far, studies on inherited variability have only considered genetic effects of the focal individual, that is, direct genetic effects on inherited variability. Observations from aquaculture populations and some plants, however, suggest that an additional source of genetic variation in inherited variability may be generated through competition. Social interactions, such as competition, are often a source of Indirect Genetic Effects (IGE). An IGE is a heritable effect of an individual on the trait value of another individual. IGEs may substantially affect heritable variation underlying the trait, and the direction and magnitude of response to selection. To understand the contribution of IGEs to evolution of environmental canalization in natural populations, and to exploit such inherited variability in animal and plant breeding, we need statistical models to capture this effect. To our knowledge, it is unknown to what extent the current statistical models commonly used for IGE and inherited variability capture the effect of competition on inherited variability. Here, we investigate the potential of current statistical models for inherited variability and trait values, to capture the direct and indirect genetic effects of competition on variability. Our results show that a direct model of inherited variability almost entirely captures the genetic sensitivity of individuals to competition, whereas an indirect model of inherited variability captures the cooperative genetic effects of individuals on their partners. Models for trait levels, however, capture only a small part of the genetic effects of competition. The estimation of direct and indirect genetic effects of competition, therefore, is possible with models for inherited variability but may require a two-step analysis. © 2022 The Authors. Evolutionary Applications published by John Wiley & Sons Ltd.

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  • 3. Niebuhr, B. B.
    et al.
    Van Moorter, B.
    Stien, A.
    Tveraa, T.
    Strand, O.
    Langeland, K.
    Sandström, P.
    Alam, Moudud
    Dalarna University, School of Information and Engineering, Statistics.
    Skarin, A.
    Panzacchi, M.
    Estimating the cumulative impact and zone of influence of anthropogenic features on biodiversity2023In: Methods in Ecology and Evolution, E-ISSN 2041-210X, Vol. 14, p. 2362-2375Article in journal (Refereed)
    Abstract [en]

    The concept of cumulative impacts is widespread in policy documents, regulations and ecological studies, but quantification methods are still evolving. Infrastructure development usually takes place in landscapes with preexisting anthropogenic features. Typically, their impact is determined by computing the distance to the nearest feature only, thus ignoring the potential cumulative impacts of multiple features. We propose the cumulative ZOI approach to assess whether and to what extent anthropogenic features lead to cumulative impacts. The approach estimates both effect size and zone of influence (ZOI) of anthropogenic features and allows for estimation of cumulative effects of multiple features distributed in the landscape. First, we use simulations and an empirical study to understand under which circumstances cumulative impacts arise. Second, we demonstrate the approach by estimating the cumulative impacts of tourist infrastructure in Norway on the habitat of wild reindeer (Rangifer t. tarandus), a near-threatened species highly sensitive to anthropogenic disturbance. In the simulations, we showed that analyses based on the nearest feature and our cumulative approach are indistinguishable in two extreme cases: when features are few and scattered and their ZOI is small, and when features are clustered and their ZOI is large. The empirical analyses revealed cumulative impacts of private cabins and tourist resorts on reindeer, extending up to 10 and 20 km, with different decaying functions. Although the impact of an isolated private cabin was negligible, the cumulative impact of ‘cabin villages’ could be much larger than that of a single large tourist resort. Focusing on the nearest feature only underestimates the impact of ‘cabin villages’ on reindeer. The suggested approach allows us to quantify the magnitude and spatial extent of cumulative impacts of point, linear, and polygon features in a computationally efficient and flexible way and is implemented in the oneimpact R package. The formal framework offers the possibility to avoid widespread underestimations of anthropogenic impacts in ecological and impact assessment studies and can be applied to a wide range of spatial response variables, including habitat selection, population abundance, species richness and diversity, community dynamics and other ecological processes. © 2023 The Authors. Methods in Ecology and Evolution published by John Wiley & Sons Ltd on behalf of British Ecological Society.

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  • 4.
    Nyberg, Roger G.
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering. School of Engineering and the Built Environment, Edinburgh Napier University, EH10 5DT Edinburgh, UK.
    Gupta, Narendra K.
    School of Engineering and the Built Environment, Edinburgh Napier University, EH10 5DT Edinburgh, UK.
    Yella, Siril
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Monitoring vegetation on railway embankments: supporting maintenance decisions2013In: Proceedings of the 2013 International Conference on Ecology and Transportation, 2013, p. 1-18Conference paper (Refereed)
    Abstract [en]

    The national railway administrations in Scandinavia, Germany, and Austria mainly resort to manual inspections to control vegetation growth along railway embankments. Manually inspecting railways is slow and time consuming. A more worrying aspect concerns the fact that human observers are often unable to estimate the true cover of vegetation on railway embankments. Further human observers often tend to disagree with each other when more than one observer is engaged for inspection. Lack of proper techniques to identify the true cover of vegetation even result in the excess usage of herbicides; seriously harming the environment and threating the ecology. Hence work in this study has investigated aspects relevant to human variationand agreement to be able to report better inspection routines. This was studied by mainly carrying out two separate yet relevant investigations.First, thirteen observers were separately asked to estimate the vegetation cover in nine imagesacquired (in nadir view) over the railway tracks. All such estimates were compared relatively and an analysis of variance resulted in a significant difference on the observers’ cover estimates (p<0.05). Bearing in difference between the observers, a second follow-up field-study on the railway tracks was initiated and properly investigated. Two railway segments (strata) representingdifferent levels of vegetationwere carefully selected. Five sample plots (each covering an area of one-by-one meter) were randomizedfrom each stratumalong the rails from the aforementioned segments and ten images were acquired in nadir view. Further three observers (with knowledge in the railway maintenance domain) were separately asked to estimate the plant cover by visually examining theplots. Again an analysis of variance resulted in a significant difference on the observers’ cover estimates (p<0.05) confirming the result from the first investigation.The differences in observations are compared against a computer vision algorithm which detects the "true" cover of vegetation in a given image. The true cover is defined as the amount of greenish pixels in each image as detected by the computer vision algorithm. Results achieved through comparison strongly indicate that inconsistency is prevalent among the estimates reported by the observers. Hence, an automated approach reporting the use of computer vision is suggested, thus transferring the manual inspections into objective monitored inspections

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    ICOET2013_Paper103C_Nyberg_at_al.pdf
  • 5. Olsson, E. G. A.
    et al.
    Maad, Johanne
    Dalarna University, School of Education, Health and Social Studies, Natural Science.
    Myklebost, H. E.
    Variation in life history traits of Gentiana nivalis (Gentianaceae) in alpine and sub-alpine habitats in the Norwegian mountains and its implications for biodiversity in relation to environmental change2015In: Annales Botanici Fennici, ISSN 0003-3847, E-ISSN 1797-2442, Vol. 52, no 3-4, p. 149-159Article in journal (Refereed)
  • 6.
    Rautiainen, Heidi
    et al.
    Swedish University of Agricultural Sciences, Uppsala.
    Alam, Moudud
    Dalarna University, School of Information and Engineering, Statistics.
    Blackwell, Paul G
    School of Mathematics & Statistics, University of Sheffield, Sheffield, UK.
    Skarin, Anna
    Swedish University of Agricultural Sciences, Uppsala.
    Identification of reindeer fine-scale foraging behaviour using tri-axial accelerometer data.2022In: Movement Ecology, E-ISSN 2051-3933, Vol. 10, no 1, article id 40Article in journal (Refereed)
    Abstract [en]

    Animal behavioural responses to the environment ultimately affect their survival. Monitoring animal fine-scale behaviour may improve understanding of animal functional response to the environment and provide an important indicator of the welfare of both wild and domesticated species. In this study, we illustrate the application of collar-attached acceleration sensors for investigating reindeer fine-scale behaviour. Using data from 19 reindeer, we tested the supervised machine learning algorithms Random forests, Support vector machines, and hidden Markov models to classify reindeer behaviour into seven classes: grazing, browsing low from shrubs or browsing high from trees, inactivity, walking, trotting, and other behaviours. We implemented leave-one-subject-out cross-validation to assess generalizable results on new individuals. Our main results illustrated that hidden Markov models were able to classify collar-attached accelerometer data into all our pre-defined behaviours of reindeer with reasonable accuracy while Random forests and Support vector machines were biased towards dominant classes. Random forests using 5-s windows had the highest overall accuracy (85%), while hidden Markov models were able to best predict individual behaviours and handle rare behaviours such as trotting and browsing high. We conclude that hidden Markov models provide a useful tool to remotely monitor reindeer and potentially other large herbivore species behaviour. These methods will allow us to quantify fine-scale behavioural processes in relation to environmental events.

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  • 7. Sivertsen, Therese R.
    et al.
    Åhman, Birgitta
    Steyaert, Sam M. J. G.
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Frank, Jens
    Segerström, Peter
    Støen, Ole-Gunnar
    Skarin, Anna
    Reindeer habitat selection under the risk of brown bear predation during calving season2016In: Ecosphere, ISSN 2150-8925, E-ISSN 2150-8925, Vol. 7, no 11, article id e01583Article in journal (Refereed)
    Abstract [en]

    The depredation of semi-domesticated reindeer by large carnivores reflects an important human-wildlife conflict in Fennoscandia. Recent studies have revealed that brown bears (Ursus arctos) may kill substantial numbers of reindeer calves (Rangifer tarandus tarandus) in forest areas in Sweden. Several authors have suggested that predation risk is an important driver of habitat selection in wild Rangifer populations where predation is a limiting factor, but little is known about these mechanisms in semi-domesticated populations. We examined the habitat selection of female reindeer in relation to spatial and temporal variations in brown bear predation risk on the reindeer calving grounds and evaluated the simultaneous responses of brown bears and reindeer to landscape characteristics. We used GPS data from 110 reindeer years (97 individuals) and 29 brown bear years (19 individuals), from two reindeer herding districts in the forest area of northern Sweden. Our results did not indicate that reindeer alter their behavior in response to spatiotemporal variation in brown bear predation risk, on the scale of the calving range. Instead, we suggest that spatiotemporal behavioral adjustments by brown bears were the main driver of prey-predator interactions in our study system. Contrasting responses by brown bears and reindeer to clear-cuts and young forest indicate that forestry can influence species interactions and possibly yield negative consequences for the reindeer herd. Even if clear-cuts may be beneficial in terms of calf survival, logging activity will eventually cause greater abundance of young regenerating forest, reducing available reindeer habitats and increasing habitat preferred by brown bears. Domestication may have made semi-domesticated reindeer in Fennoscandia less adapted to cope with predators. Areal restrictions, limiting the opportunity for dispersion and escape, possibly make the calves more susceptible to predation. Also, a generally higher population density in semi-domesticated herds compared to wild populations can make dispersion a less efficient strategy and the reindeer calves easier prey. Overall, the lack of ability of the reindeer females to reduce brown bear encounter risk on the scale of the calving range is probably an important reason for the high brown bear predation rates on reindeer calves documented in our study areas. 

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  • 8. Skarin, Anna
    et al.
    Helleman, Christian
    Sandström, Per
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Lundquist, Henrik
    Renar och vindkraft: Studie från anläggningen av två vindkraftparker i Malå sameby2013Report (Other academic)
    Abstract [sv]

    Studien undersöker hur renar påverkas under konstruktionsfasen när vindkraftverk byggs. Studien följer uppförandet av två nya vindparker i Malå kommun i Västerbotten. Sammanlagt byggdes 18 vindkraftverk i Malå samebys kalvnings- och försommarland. Inventering av renspillning samt positioner från renar med GPS-halsband visar att konstruktionen av vindkraftsparkerna har påverkat renarnas användning av området. Analysen visar att renarna under tiden för byggnationen har sökt sig bort från området. Spillningsinventeringen och GPS-data visar också att renarna undviker kraftledningar och större vägar när de ska beta.

    Rapport från kunskapsprogrammet Vindval.

  • 9.
    Skarin, Anna
    et al.
    Swedish Univ Agr Sci, Dept Anim Nutr & Management, Uppsala.
    Nellemann, Christian
    GRID Arendal, United Nations Environm Programme, Lillehammer, Norway..
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Sandstrom, Per
    Swedish Univ Agr Sci, Dept Forest Resource Management, Umea, Sweden.
    Lundqvist, Henrik
    Swedish Univ Agr Sci, Dept Anim Nutr & Management, Uppsala, Sweden.
    Wind farm construction impacts reindeer migration and movement corridors2015In: Landscape Ecology, ISSN 0921-2973, E-ISSN 1572-9761, Vol. 30, no 8, p. 1527-1540Article in journal (Refereed)
    Abstract [en]

    Over the last decade, we have seen a massive increase in the construction of wind farms in northern Fennoscandia. Wind farms comprising hundreds of wind turbines are being built, with little knowledge of the possible cumulative adverse effects on the habitat use and migration of semi-domesticated free-ranging reindeer. We assessed how reindeer responded to wind farm construction in an already fragmented landscape, with specific reference to the effects on use of movement corridors and reindeer habitat selection. We used GPS-data from reindeer during calving and post-calving in the MalAyen reindeer herding community in Sweden. We analysed data from the pre-development years compared to the construction years of two relatively small wind farms. During construction of the wind farms, use of original migration routes and movement corridors within 2 km of development declined by 76 %. This decline in use corresponded to an increase in activity of the reindeer measured by increased step lengths within 0-5 km. The step length was highest nearest the development and declining with distance, as animals moved towards migration corridors and turned around or were observed in holding patterns while not crossing. During construction, reindeer avoided the wind farms at both regional and landscape scale of selection. The combined construction activities associated with even a few wind turbines combined with power lines and roads in or close to central movement corridors caused a reduction in the use of such corridors and grazing habitat and increased the fragmentation of the reindeer calving ranges.

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  • 10.
    Skarin, Anna
    et al.
    Department of Animal Nutrition and Management, Swedish University of Agricultural Sciences, Uppsala, Sweden.
    Verdonen, Mariana
    Department of Geographical and Historical Studies, University of Eastern Finland, FI-80101, Joensuu, Finland.
    Kumpula, Timo
    Department of Geographical and Historical Studies, University of Eastern Finland, FI-80101, Joensuu, Finland.
    Macias-Fauria, Marc
    School of Geography and the Environment, University of Oxford, Oxford OX1 3QY, United Kingdom.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Kerby, Jeffrey
    Aarhus Institute of Advanced Studies, Aarhus University, Aarhus, Denmark.
    Forbes, Bruce C.
    Arctic Centre, University of Lapland, FI-96101, Rovaniemi, Finland.
    Reindeer use of low Arctic tundra correlates with landscape structure2020In: Environmental Research Letters, E-ISSN 1748-9326, Vol. 15, article id 115012Article in journal (Refereed)
    Abstract [en]

    Rapid climate change in Arctic regions is linked to the expansion of woody taxa (shrubification), and an increase in biomass as tundra becomes greener. Reindeer and caribou (Rangifer tarandus) are considered able to suppress vegetative greening through grazing and trampling. Quantifying reindeer use of different land cover types can help us understand their impact on the growth and recruitment of deciduous shrubs, many of which serve as fodder (e.g. Salix spp.), in favourable habitats, such as naturally denuded landslides in permafrost areas. Understanding the spatial distribution of reindeer pressure on vegetation is important to project future patterns of greening, albedo, snow capture, active layer development, and the overall resilience of tundra rangelands under ongoing climate change. Here we quantify reindeer habitat use within the low Arctic tundra zone of Yamal, West Siberia estimated from pellet-group counts, and also how active layer thickness (ALT) relates to reindeer use. Our results confirm intensive use by reindeer of terrain with high June-July time integrated normalised difference vegetation index, steeper slopes, ridges, upper slopes and valleys, and a preference for low erect shrub tundra. These sites also seem to have a shallower ALT compared to sites less used by reindeer, although we did not find any direct relationship between ALT and reindeer use. Low use of tall Salix habitats indicated that reindeer are unlikely to suppress the growth of already tall-erect woody taxa, while they exert maximum pressure in areas where shrubs are already low in stature, e.g. ridgetops. Reindeer ability to suppress the regrowth and expansion of woody taxa in landslide areas (i.e. concavities) seems limited, as these types were less used. Our results suggest that reindeer use of the landscape and hence their effects on the landscape correlates with the landscape structure. Future research is needed to evaluate the role and efficiency of reindeer as ecosystem engineers capable of mediating the effects of climate change.

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