du.sePublications
Change search
Link to record
Permanent link

Direct link
BETA
Publications (10 of 36) Show all publications
Svenson, K., McRobbie, S. & Alam, M. (2019). Detecting road pavement deterioration with finite mixture models. The international journal of pavement engineering, 20(4), 458-465
Open this publication in new window or tab >>Detecting road pavement deterioration with finite mixture models
2019 (English)In: The international journal of pavement engineering, ISSN 1029-8436, E-ISSN 1477-268X, Vol. 20, no 4, p. 458-465Article in journal (Refereed) Published
Abstract [en]

Budget restrictions often limit the number of possible maintenance activities in a road network each year. To effectively allocate resources, the rate of road pavement deterioration is of great importance. If two maintenance candidates have an equivalent condition, it is reasonable to maintain the segment with the highest deterioration rate first. To identify such segments, finite mixture models were applied to road condition data from a part of the M4 highway in England. Assuming that data originates from two different normal distributions – defined as a ‘change’ distribution and an ‘unchanged’ distribution – all road segments were classified into one of the groups. Comparisons with known measurement errors and maintenance records showed that segments in the unchanged group had a stationary road condition. Segments classified into the change group showed either a rapid deterioration, improvement in condition because of previous maintenance or unusual measurement errors. Together with additional information from maintenance records, finite mixture models can identify segments with the most rapid deterioration rate, and contribute to more efficient maintenance decisions.

Keywords
Finite mixture models, pavement deterioration, road maintenance
National Category
Probability Theory and Statistics
Research subject
Complex Systems – Microdata Analysis
Identifiers
urn:nbn:se:du-24767 (URN)10.1080/10298436.2017.1309193 (DOI)000457029200009 ()2-s2.0-85017252284 (Scopus ID)
Available from: 2017-04-24 Created: 2017-04-24 Last updated: 2019-02-14Bibliographically approved
Thomas, I., Alam, M., Bergquist, F., Johansson, D., Memedi, M., Nyholm, D. & Westin, J. (2019). Sensor-based algorithmic dosing suggestions for oral administration of levodopa/carbidopa microtablets for Parkinson's disease: a first experience. Journal of Neurology, 266(3), 651-658
Open this publication in new window or tab >>Sensor-based algorithmic dosing suggestions for oral administration of levodopa/carbidopa microtablets for Parkinson's disease: a first experience
Show others...
2019 (English)In: Journal of Neurology, ISSN 0340-5354, E-ISSN 1432-1459, Vol. 266, no 3, p. 651-658Article in journal (Refereed) Published
Abstract [en]

OBJECTIVE: Dosing schedules for oral levodopa in advanced stages of Parkinson's disease (PD) require careful tailoring to fit the needs of each patient. This study proposes a dosing algorithm for oral administration of levodopa and evaluates its integration into a sensor-based dosing system (SBDS).

MATERIALS AND METHODS: In collaboration with two movement disorder experts a knowledge-driven, simulation based algorithm was designed and integrated into a SBDS. The SBDS uses data from wearable sensors to fit individual patient models, which are then used as input to the dosing algorithm. To access the feasibility of using the SBDS in clinical practice its performance was evaluated during a clinical experiment where dosing optimization of oral levodopa was explored. The supervising neurologist made dosing adjustments based on data from the Parkinson's KinetiGraph™ (PKG) that the patients wore for a week in a free living setting. The dosing suggestions of the SBDS were compared with the PKG-guided adjustments.

RESULTS: The SBDS maintenance and morning dosing suggestions had a Pearson's correlation of 0.80 and 0.95 (with mean relative errors of 21% and 12.5%), to the PKG-guided dosing adjustments. Paired t test indicated no statistical differences between the algorithmic suggestions and the clinician's adjustments.

CONCLUSION: This study shows that it is possible to use algorithmic sensor-based dosing adjustments to optimize treatment with oral medication for PD patients.

Keywords
Algorithmic suggestions, Levodopa, Oral medication, Parkinson’s disease, Sensor data
National Category
Probability Theory and Statistics Other Medical Sciences
Research subject
Complex Systems – Microdata Analysis; Complex Systems – Microdata Analysis
Identifiers
urn:nbn:se:du-29314 (URN)10.1007/s00415-019-09183-6 (DOI)000459203400013 ()30659356 (PubMedID)2-s2.0-85060256040 (Scopus ID)
Available from: 2019-01-21 Created: 2019-01-21 Last updated: 2019-03-14Bibliographically approved
Thomas, I., Westin, J., Alam, M., Bergquist, F., Nyholm, D., Senek, M. & Memedi, M. (2018). A treatment–response index from wearable sensors for quantifying Parkinson's disease motor states. IEEE journal of biomedical and health informatics, 22(5), 1341-1349
Open this publication in new window or tab >>A treatment–response index from wearable sensors for quantifying Parkinson's disease motor states
Show others...
2018 (English)In: IEEE journal of biomedical and health informatics, ISSN 2168-2194, E-ISSN 2168-2208, Vol. 22, no 5, p. 1341-1349Article in journal (Refereed) Published
Abstract [en]

The goal of this study was to develop an algorithm that automatically quantifies motor states (off,on,dyskinesia) in Parkinson's disease (PD), based on accelerometry during a hand pronation-supination test. Clinician's ratings using the Treatment Response Scale (TRS), ranging from -3 (very Off) to 0 (On) to +3 (very dyskinetic), was used as target. For that purpose, 19 participants with advanced PD and 22 healthy persons were recruited in a single center open label clinical trial in Uppsala, Sweden. The trial consisted of single levodopa dose experiments for the people with PD (PwP), where participants were asked to perform standardized wrist rotation tests, using each hand, before and at pre-specified time points after the dose. The participants used wrist sensors containing a 3D accelerometer and gyroscope. Features to quantify the level, variation and asymmetry of the sensor signals, three-level Discrete Wavelet Transform features and approximate entropy measures were extracted from the sensors data. At the time of the tests, the PwP were video recorded. Three movement disorder specialists rated the participants’ state on the TRS scale. A Treatment Response Index from Sensors (TRIS) was constructed to quantify the motor states based on the wrist rotation tests. Different machine learning algorithms were evaluated to map the features derived from the sensor data to the ratings provided by the three specialists. Results from cross validation, both in 10-fold and a leave-one-individual out setting, showed good predictive power of a support vector machine model and high correlation to the TRS scale. Values at the end tails of the TRS scale were under and over predicted due to the lack of observations at those values but the model managed to accurately capture the dose - effect profiles of the patients. In addition, the TRIS had good test-retest reliability on the baseline levels of the PD participants (Intraclass correlation coefficient of 0.83) and reasonable sensitivity to levodopa treatment (0.33 for the TRIS). For a series of test occasions the proposed algorithms provided dose - effect time profiles for participants with PD, which could be useful during therapy individualization of people suffering from advanced PD

Keywords
Accelerometers, Accelerometry, Diseases, Feature extraction, Levodopa response, Machine learning, Parkinson's disease, Pattern recognition, Sensor phenomena and characterization, Signal processing, Wearable sensors, Wrist
National Category
Computer and Information Sciences
Research subject
Complex Systems – Microdata Analysis
Identifiers
urn:nbn:se:du-26745 (URN)10.1109/JBHI.2017.2777926 (DOI)000441795800002 ()29989996 (PubMedID)2-s2.0-85035809095 (Scopus ID)
Available from: 2017-12-11 Created: 2017-12-11 Last updated: 2019-02-06Bibliographically approved
Thomas, I., Alam, M., Nyholm, D., Senek, M. & Westin, J. (2018). Individual dose-response models for levodopa infusion dose optimization. International Journal of Medical Informatics, 112, 137-142
Open this publication in new window or tab >>Individual dose-response models for levodopa infusion dose optimization
Show others...
2018 (English)In: International Journal of Medical Informatics, ISSN 1386-5056, E-ISSN 1872-8243, Vol. 112, p. 137-142Article in journal (Refereed) Published
Abstract [en]

Background and Objective

To achieve optimal effect with continuous infusion treatment in Parkinson’s disease (PD), the individual doses (morning dose and continuous infusion rate) are titrated by trained medical personnel. This study describes an algorithmic method to derive optimized dosing suggestions for infusion treatment of PD, by fitting individual dose-response models. The feasibility of the proposed method was investigated using patient chart data.

Methods

Patient records were collected at Uppsala University hospital which provided dosing information and dose-response evaluations. Mathematical optimization was used to fit individual patient models using the records’ information, by minimizing an objective function. The individual models were passed to a dose optimization algorithm, which derived an optimized dosing suggestion for each patient model.

Results

Using data from a single day’s admission the algorithm showed great ability to fit appropriate individual patient models and derive optimized doses. The infusion rate dosing suggestions had 0.88 correlation and 10% absolute mean relative error compared to the optimal doses as determined by the hospital’s treating team. The morning dose suggestions were consistency lower that the optimal morning doses, which could be attributed to different dosing strategies and/or lack of on-off evaluations in the morning.

Conclusion

The proposed method showed promise and could be applied in clinical practice, to provide the hospital personnel with additional information when making dose adjustment decisions.

Place, publisher, year, edition, pages
Elsevier, 2018
Keywords
Levodopa infusion; Algorithmic dosing suggestions; Patient-specific models; Parkinson’s disease
National Category
Computer and Information Sciences
Research subject
Complex Systems – Microdata Analysis
Identifiers
urn:nbn:se:du-27065 (URN)10.1016/j.ijmedinf.2018.01.018 (DOI)000426130900018 ()29500011 (PubMedID)
Available from: 2018-02-02 Created: 2018-02-02 Last updated: 2019-02-06Bibliographically approved
Skarin, A., Sandström, P. & Alam, M. (2018). Out of sight of wind turbines — Reindeer response to wind farms in operation. Ecology and Evolution, 8, 9906-9919
Open this publication in new window or tab >>Out of sight of wind turbines — Reindeer response to wind farms in operation
2018 (English)In: Ecology and Evolution, ISSN 2045-7758, E-ISSN 2045-7758, Vol. 8, p. 9906-9919Article in journal (Refereed) Published
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.

Keywords
anthropogenic disturbance, calving season, cumulative impact, habitat selection, large herbivore, Rangifer tarandus, renewable energy, semi-domesticated reindeer
National Category
Biological Sciences Energy Engineering
Research subject
Complex Systems – Microdata Analysis
Identifiers
urn:nbn:se:du-28489 (URN)10.1002/ece3.4476 (DOI)000448803000029 ()30386585 (PubMedID)2-s2.0-85052859300 (Scopus ID)
Available from: 2018-09-18 Created: 2018-09-18 Last updated: 2018-11-15Bibliographically approved
Saqlain, M., Alam, M., Brandt, D., Rönnegård, L. & Westin, J. (2018). Stochastic differential equations modelling of levodopa concentration in patients with Parkinson's disease. In: : . Paper presented at The 40th Conference on Stochastic Processes and their Applications – SPA 2018, June 11-15 2018, Gothenburg.
Open this publication in new window or tab >>Stochastic differential equations modelling of levodopa concentration in patients with Parkinson's disease
Show others...
2018 (English)Conference paper, Poster (with or without abstract) (Other academic)
Abstract [en]

The purpose of this study is to investigate a pharmacokinetic model of levodopa concentration in patients with Parkinson's disease by introducing stochasticity so that inter-individual variability may be separated into measurement and system noise. It also aims to investigate whether the stochastic differential equations (SDE) model provide better fits than its ordinary differential equations (ODE) counterpart, by using a real data set. Westin et al. developed a pharmacokinetic-pharmacodynamic model for duodenal levodopa infusion described by four ODEs, the first three of which define the pharmacokinetic model. In this study, system noise variables are added to the aforementioned first three equations through a standard Wiener process, also known as Brownian motion. The R package PSM for mixed-effects models is used on data from previous studies for modelling levodopa concentration and parameter estimation. First, the diffusion scale parameter, σ, and bioavailability are estimated with the SDE model. Second, σ is fixed to integer values between 1 and 5, and bioavailability is estimated. Cross-validation is performed to determine whether the SDE based model explains the observed data better or not by comparingthe average root mean squared errors (RMSE) of predicted levodopa concentration. Both ODE and SDE models estimated bioavailability to be about 88%. The SDE model converged at different values of σ that were signicantly different from zero while estimating bioavailability to be about 88%. The average RMSE for the ODE model wasfound to be 0.2980, and the lowest average RMSE for the SDE model was 0.2748 when σ was xed to 4. Both models estimated similar values for bioavailability, and the non-zero σ estimate implies that the inter-individual variability may be separated. However, the improvement in the predictive performance of the SDE model turned out to be rather small, compared to the ODE model.

Keywords
levodopa, parkinson's disease, pharmacokinetic model, stochastic modelling, PSM.
National Category
Probability Theory and Statistics
Research subject
Complex Systems – Microdata Analysis, General Microdata Analysis - methods
Identifiers
urn:nbn:se:du-28268 (URN)
Conference
The 40th Conference on Stochastic Processes and their Applications – SPA 2018, June 11-15 2018, Gothenburg
Available from: 2018-08-08 Created: 2018-08-08 Last updated: 2018-12-17Bibliographically approved
Skarin, A. & Alam, M. (2017). Reindeer habitat use in relation to two small wind farms, during preconstruction, construction, and operation. Ecology and Evolution, 7(11), 3870-3882
Open this publication in new window or tab >>Reindeer habitat use in relation to two small wind farms, during preconstruction, construction, and operation
2017 (English)In: Ecology and Evolution, ISSN 2045-7758, E-ISSN 2045-7758, Vol. 7, no 11, p. 3870-3882Article in journal (Refereed) Published
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.

Keywords
Rangifer, Anthropogenic disturbance, Before after design, Pellet group count, Renewable energy development, Spatial correlation, Sámi reindeer husbandry
National Category
Other Agricultural Sciences
Research subject
Complex Systems – Microdata Analysis
Identifiers
urn:nbn:se:du-24825 (URN)10.1002/ece3.2941 (DOI)000403273000024 ()2-s2.0-85017692325 (Scopus ID)
Available from: 2017-05-08 Created: 2017-05-08 Last updated: 2018-01-13Bibliographically approved
Thomas, I., Alam, M., Bergquist, F., Senek, M., Nyholm, D. & Westin, J. (2016). Individual levodopa dosing suggestions based on a single dose test. In: : . Paper presented at 4th World Parkinson Congress, Portland, Oregon, September 20-23, 2016.
Open this publication in new window or tab >>Individual levodopa dosing suggestions based on a single dose test
Show others...
2016 (English)Conference paper, Poster (with or without abstract) (Other academic)
National Category
Other Computer and Information Science
Research subject
Complex Systems – Microdata Analysis
Identifiers
urn:nbn:se:du-23618 (URN)
Conference
4th World Parkinson Congress, Portland, Oregon, September 20-23, 2016
Projects
FLOAT
Available from: 2016-12-19 Created: 2016-12-19 Last updated: 2018-01-13Bibliographically approved
Thomas, I., Alam, M., Senek, M., Dag, N. & Westin, J. (2016). Minimizing levodopa titration period for Parkinson’s disease. In: : . Paper presented at 20th International Congress of Parkinson's Disease and Movement Disorders, June 19-23 2016, Berlin (pp. S633-S633). , 31(suppl. 2)
Open this publication in new window or tab >>Minimizing levodopa titration period for Parkinson’s disease
Show others...
2016 (English)Conference paper, Poster (with or without abstract) (Other academic)
National Category
Software Engineering
Research subject
Complex Systems – Microdata Analysis
Identifiers
urn:nbn:se:du-22627 (URN)10.1002/mds.26688 (DOI)
Conference
20th International Congress of Parkinson's Disease and Movement Disorders, June 19-23 2016, Berlin
Available from: 2016-07-18 Created: 2016-07-18 Last updated: 2018-01-10
Skarin, A., Sandström, P., Alam, M., Buhot, Y. & Nellemann, C. (2016). Renar och vindkraft II: Vindkraft i drift och effekter på renar och renskötsel. Uppsala: Sveriges lantbruksuniversitet, Institutionen för husdjurens utfodring och vård
Open this publication in new window or tab >>Renar och vindkraft II: Vindkraft i drift och effekter på renar och renskötsel
Show others...
2016 (Swedish)Report (Other academic)
Alternative title[en]
Impacts of wind power infrastructure development on semi-domesticated reindeer and reindeer husbandry
Abstract [sv]

Utbyggnaden av vindkraft inom renskötselområdet har ökat markant det senaste decenniet, trots att kunskapen om påverkan av vindkraftsetableringar ännu inte är fullt utredd och dokumenterad. I den här rapporten beskriver vi framförallt hur vindkraftparker i driftsfas påverkar renarna och renskötseln i tre olika områden. I Malå sameby har vi studerat kalvningsområdet kring Storliden och Jokkmokkslidens vindkraftparker. I Vilhelmina Norra sameby har vi studerat vinterbetesområdet kring Stor-Rotlidens vindkraftpark, samt Lögdeålandets betesområde med Gabrielsbergets vindkraftpark som används av Byrkije reinbetesdistrikt från Norge.

För att få en helhetsbild av hur renarna använder sitt betesområde är det viktigt att studera renarnas betes- och förflyttningsmönster långsiktigt och över hela deras betesområde och inte bara inom det lokala området nära parken. Det är också viktigt att ta hänsyn till att renarnas betesutnyttjande skiftar från år till år och mellan olika årstider beroende på väderlek och andra yttre förutsättningar. Vi vill också understryka vikten av att kombinera den traditionella kunskapen från renskötarna med vedertagna vetenskapliga analysmetoder för att besvara de frågor som är viktiga för att kunna bedriva en hållbar renskötsel.

Vi har undersökt renarnas användning av områdena genom att utföra spillningsinventeringar under åren 2009-2015 (endast i Malå sameby), och genom att följa renar utrustade med GPS-halsband under åren 2005-2015. Datat är insamlat före och under byggfas och under driftsfas (för Gabrielsberget finns GPS-data endast för driftsfasen). Vi har analyserat data genom att utveckla statistiska modeller för val av betesområde för varje område där vi har beräknat hur renarna förhåller sig till vindkraftparksområdet före, under och efter byggnation, och på Gabrielsberget när parken varit avstängd under 40 dagar och under drift vid olika renskötselsituationer. Genom intervjuer, möten och samtal, samt information från Gabrielsbergets vindkraftparks kontrollprogram, har vi tagit del av renskötarnas erfarenheter av hur renarnas beteende, och därmed även renskötseln, påverkats av vindkraftsutbyggnaden i respektive område.

Våra resultat visar att renarna både på kalvnings- och på vinterbetesområden påverkas negativt av vindkraftsetableringarna (Tabell a). Renarna undviker att beta i områden där de kan se och/eller höra vindkraftsverken och föredrar att vistas i områden där vindkraftverken är skymda. I kalvningsområdet i Malå ökade användningen av skymda områden med 60 % under driftsfas. I vinterbetesområdet på Gabrielsberget, när renarna utfodrades i parken och kantbevakades intensivt för att stanna i parkområdet under driftsfas, ökade användningen av skymda områden med 13 % jämfört med när de inte var utfodrade och fick ströva mer fritt. Resultaten visar också att renarna minskar sin användning av området nära vindkraftparkerna. I kalvningslandet i Malå minskar renarna sin användning av områden inom 5 km från parkerna med 16-20 %. Vintertid vid Gabrielsbergets vindkraftpark undvek renarna parken med 3 km. Våra resultat visar även att renarnas betesro minskar inom en radie på 4 km från vindkraftparkerna under kalvningsperioden och tiden därefter i jämförelse med perioden före byggfas.

Exakta avstånd som renarna påverkas beror på förutsättningarna i respektive område, exempelvis hur topografin ser ut eller om området är begränsat av stängsel eller annan infrastruktur. Förändringarna i habitatutnyttjande i våra studieområden blev tydligare när parkerna var centralt belägna i renarnas betesområde, som i kalvningsområdet i Malå eller i vinterbeteslandet på Gabrielsberget, medan det inte var lika tydliga effekter kring Stor-Rotlidens park, som ligger i utkanten av ett huvudbetesområde.

Oftast är snöförhållandena bättre ur betessynpunkt högre upp i terrängen än nere i dalgångarna, på grund av stabilare temperatur, vind som blåser bort snötäcket och mer variation i topografin. Därför kan etablering av vindkraftparker i höglänta områden försämra möjligheten att använda sådana viktiga reservbetesområden under vintrar med i övrigt dåliga snöförhållanden, vilka blir allt vanligare i och med klimatförändringarna. Våra resultat tyder inte direkt på att renarna påverkats negativt under dåliga betesvintrar men fler år av studier behövs för att ytterligare klargöra hur vindkraft påverkar renarna under dessa vintrar.

Våra studier har visat att etablering av vindkraft har konsekvenser för renskötseln under både barmarkssäsongen och under vintern, men effekterna förmodas få störst inverkan inom vinterbetesområdet där det är svårt att hitta alternativa betesområden för renarna. Under sommaren är betestillgången oftast mindre begränsad och renarna kan lättare hitta alternativa områden. En direkt konsekvens av Gabrielsbergets vindkraftpark som är placerad mitt i ett vinterbetesområde har blivit att renarna behöver tillskottsutfodras och bevakas intensivare för att de inte ska gå ut ur området. När den naturliga vandringen mellan olika betesområden störs för att renarna undviker att vistas i ett område kan det leda till att den totala tillgången till naturligt bete minskar och att man permanent måste tillskottsutfodra, alternativt minska antalet renar.

Annan infrastruktur som vägar och kraftledningar påverkar också renarna. Vid Storliden och Jokkmokksliden och vid Stor-Rotliden där data samlats in innan vindkraftparken uppfördes visar våra resultat att renarna undviker de omkringliggande landsvägarna redan innan parkerna etablerades. Vid Stor-Rotliden ökar dock renarna användningen av områden nära vägarna efter att parken är byggd. På Gabrielsberget, där vi endast har data under drifttiden, är renarna närmare vägarna (även stora vägar som E4) när renskötarna minskar på kantbevakningen för att inte hålla renarna nära parken. Detta ökar naturligtvis risken för trafikolyckor och innebär att renskötarna måste bevaka dessa områden intensivare.

Sist i rapporten presenterar vi förslag till åtgärder som kan användas för att underlätta arbetet för renskötseln om det är så att en vindkraftpark redan är byggd. Några exempel på åtgärder som är direkt kopplat till parken är att stänga av vägarna in i vindkraftparken för att förhindra nöjeskörning med skoter och bil under den tiden renarna vistas i området samt tät dialog mellan vindkraftsbolag och sameby angående vinterväghållningen av vägarna till och inom vindkraftparken. Andra mer regionala åtgärder för att förbättra förutsättningarna för renskötselarbetet på andra platser för samebyn, kan vara att sätta stängsel längst större vägar och järnvägar (t.ex. E4:an eller stambanan) i kombination med strategiskt utplacerade ekodukter. Detta för att underlätta och återställa möjligheterna till renarnas fria strövning och renskötarnas flytt av renar mellan olika betesområden.   

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.

Place, publisher, year, edition, pages
Uppsala: Sveriges lantbruksuniversitet, Institutionen för husdjurens utfodring och vård, 2016. p. 74
Series
Rapport / Sveriges lantbruksuniversitet, Institutionen för husdjurens utfodring och vård, ISSN 0347-9838 ; 294
Keywords
Sámi reindeer husbandry, wind power, Rangifer tarandus tarandus, GPS-collars, pellet-group counts, traditional ecological knowledge, Sámi reindeer husbandry, wind power, Rangifer tarandus tarandus, GPS-collars, pellet-group counts, traditional ecological knowledge
National Category
Animal and Dairy Science
Research subject
Complex Systems – Microdata Analysis, Effektutvärdering
Identifiers
urn:nbn:se:du-22697 (URN)978-91-576-9420-1 (ISBN)
Available from: 2016-08-15 Created: 2016-08-15 Last updated: 2016-10-25Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-3183-3756

Search in DiVA

Show all publications