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  • 1. Skarin, A.
    et al.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Reindeer habitat use in relation to two small wind farms, during preconstruction, construction, and operation2017In: Ecology and Evolution, ISSN 2045-7758, E-ISSN 2045-7758, Vol. 7, no 11, p. 3870-3882Article in journal (Refereed)
    Abstract [en]

    Worldwide there is a rush toward wind power development and its associated infrastructure. In Fennoscandia, large-scale wind farms comprising several hundred windmills are currently built in important grazing ranges used for Sámi reindeer husbandry. In this study, reindeer habitat use was assessed using reindeer fecal pellet group counts in relation to two relatively small wind farms, with 8 and 10 turbines, respectively. In 2009, 1,315 15-m2 plots were established and pellet groups were counted and cleaned from the plots. This was repeated once a year in May, during preconstruction, construction, and operation of the wind farms, covering 6 years (2009-2014) of reindeer habitat use in the area. We modeled the presence/absence of any pellets in a plot at both the local (wind farm site) and regional (reindeer calving to autumn range) scale with a hierarchical logistic regression, where spatial correlation was accounted for via random effects, using vegetation type, and the interaction between distance to wind turbine and time period as predictor variables. Our results revealed an absolute reduction in pellet groups by 66% and 86% around each wind farm, respectively, at local scale and by 61% at regional scale during the operation phase compared to the preconstruction phase. At the regional, scale habitat use declined close to the turbines in the same comparison. However, at the local scale, we observed increased habitat use close to the wind turbines at one of the wind farms during the operation phase. This may be explained by continued use of an important migration route close to the wind farm. The reduced use at the regional scale nevertheless suggests that there may be an overall avoidance of both wind farms during operation, but further studies of reindeer movement and behavior are needed to gain a better understanding of the mechanisms behind this suggested avoidance.

  • 2.
    Skarin, Anna
    et al.
    SLU.
    Sandström, Per
    SLU.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Out of sight of wind turbines — Reindeer response to wind farms in operation2018In: Ecology and Evolution, ISSN 2045-7758, E-ISSN 2045-7758, Vol. 8, p. 9906-9919Article in journal (Refereed)
    Abstract [en]

    To meet the expanding land use required for wind energy development, a better understanding of the effects on terrestrial animals’ responses to such development is required. Using GPS-data from 50 freely ranging female reindeer (Rangifer tarandus) in the Malå reindeer herding community, Sweden, we determined reindeer calving sites and estimated reindeer habitat selection using resource selection functions (RSF). RSFs were estimated at both second- (selection of home range) and third-order (selection within home range) scale in relation to environmental variables, wind farm (WF) development phase (before construction, construction, and operation), distance to the WFs and at the second-order scale whether the wind turbines were in or out of sight of the reindeer. We found that the distance between reindeer calving site and WFs increased during the operation phase, compared to before construction. At both scales of selection, we found a significant decrease in habitat selection of areas in proximity of the WFs, in the same comparison. The results also revealed a shift in home range selection away from habitats where wind turbines became visible toward habitats where the wind turbines were obscured by topography (increase in use by 79% at 5 km). We interpret the reindeer shift in home range selection as an effect of the wind turbines per se. Using topography and land cover information together with the positions of wind turbines could therefore help identify sensitive habitats for reindeer and improve the planning and placement of WFs. In addition, we found that operation phase of these WFs had a stronger adverse impact on reindeer habitat selection than the construction phase. Thus, the continuous running of the wind turbines making a sound both day and night seemed to have disturbed the reindeer more than the sudden sounds and increased human activity during construction work.

  • 3.
    Youngjo, Lee
    et al.
    Seoul National University.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Noh, Maengseok
    Pukyong National University, Korea.
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Skarin, Anna
    Swedish University of Agricultural Science, Uppsala.
    Spatial modeling of data with excessive zeros applied to reindeer pellet-group counts2016In: Ecology and Evolution, ISSN 2045-7758, E-ISSN 2045-7758, Vol. 6, no 19, p. 7047-7056Article in journal (Refereed)
    Abstract [en]

    We analyze a real data set pertaining to reindeer fecal pellet-group counts obtained from a survey conducted in a forest area in northern Sweden. In the data set, over 70% of counts are zeros, and there is high spatial correlation. We use conditionally autoregressive random effects for modeling of spatial correlation in a Poisson generalized linear mixed model (GLMM), quasi-Poisson hierarchical generalized linear model (HGLM), zero-inflated Poisson (ZIP), and hurdle models. The quasi-Poisson HGLM allows for both under- and overdispersion with excessive zeros, while the ZIP and hurdle models allow only for overdispersion. In analyzing the real data set, we see that the quasi-Poisson HGLMs can perform better than the other commonly used models, for example, ordinary Poisson HGLMs, spatial ZIP, and spatial hurdle models, and that the underdispersed Poisson HGLMs with spatial correlation fit the reindeer data best. We develop R codes for fitting these models using a unified algorithm for the HGLMs. Spatial count response with an extremely high proportion of zeros, and underdispersion can be successfully modeled using the quasi-Poisson HGLM with spatial random effects.

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