Projects / Programmes source: ARRS

Development of a multi-method approach to study wildlife behavior: investigating human-bear conflicts in contrasting landscapes of Europe

Research activity

Code Science Field Subfield
4.01.01  Biotechnical sciences  Forestry, wood and paper technology  Forest - forestry 

Code Science Field
B280  Biomedical sciences  Animal ecology 

Code Science Field
4.01  Agricultural and Veterinary Sciences  Agriculture, Forestry and Fisheries 
brown bear, stable isotopes, machine learning, GPS telemetry, molecular genetics, conflict behaviour
Evaluation (rules)
source: COBISS
Researchers (10)
no. Code Name and surname Research area Role Period No. of publications
1.  15660  PhD Marko Debeljak  Biology  Researcher  2016 - 2018  303 
2.  11130  PhD Sašo Džeroski  Computer science and informatics  Researcher  2016 - 2018  1,159 
3.  32282  PhD Aneta Ivanovska  Computer science and informatics  Researcher  2016 - 2018  121 
4.  32513  PhD Maja Jan  Biology  Technician  2016 - 2018  78 
5.  22515  PhD Klemen Jerina  Forestry, wood and paper technology  Principal Researcher  2016 - 2018  438 
6.  16067  PhD Andrej Kobler  Forestry, wood and paper technology  Researcher  2016 - 2018  284 
7.  31050  PhD Dragi Kocev  Computer science and informatics  Researcher  2016 - 2018  191 
8.  29816  PhD Miha Krofel  Forestry, wood and paper technology  Researcher  2016 - 2018  691 
9.  25992  PhD Tomaž Skrbinšek  Biology  Researcher  2016 - 2018  204 
10.  14835  PhD Peter Trontelj  Biology  Researcher  2016 - 2018  403 
Organisations (3)
no. Code Research organisation City Registration number No. of publications
1.  0106  Jožef Stefan Institute  Ljubljana  5051606000  85,052 
2.  0404  Slovenian Forestry Institute  Ljubljana  5051673000  11,778 
3.  0481  University of Ljubljana, Biotechnical Faculty  Ljubljana  1626914  64,118 
Research of wildlife behaviour poses considerable methodological challenges, especially in rare, nocturnal and elusive species. The methods for studying wildlife behaviour have seen rapid development over the recent years. Although many of the new methods are powerful on their own, their real power lies in integration. However, this has been rarely done. In the proposed project we’re aiming to take this next step – to use the opportunity of large multi-method datasets we have at our disposal, and integrate these data to get a better understanding of the wildlife behaviour. We will use brown bear (Ursus arctos) as a model species. Being a charismatic, but also potentially conflict species, brown bear has been extensively used as a model species for method development. Human-bear conflicts are an important conservation issue for this protected species. Understanding of the mechanisms behind development of conflicts is essential for designing of successful conflict prevention management programs. The issue, however, is a considerable challenge for research that requires innovative approaches. Within the project we will develop a new multi-method approach that will enable a new perspective on development of behavioural patterns. The approach will combine machine learning techniques with four modern methodologies used in wildlife research: GPS telemetry, habitat modelling, molecular genetics, and analysis of stable isotopes. Work will be organized into six workpackages: 1) Population-level pedigree reconstruction in wild bears: we will use genotypes to reconstruct pedigrees for several generations of brown bears, which will be used downstream to decipher the relative roles of social learning and heritability in development of conflict behaviour. 2) Reconstruction of bear diet using stable isotope analysis: estimated dietary proportions derived from the stable isotopes contained in different bear tissues will provide insights into relative importance of major food sources to bears (including anthropogenic food sources) at different time periods of their life. 3) Spatially-explicit modelling of functional habitat: we will analyse connections between habitat characteristics and bear space use patterns with the use of spatially-explicit modelling of functional habitats of brown bear. We will use new 3-D high-resolution LIDAR spatial data, which will give us the opportunity to evaluate importance of cover (connected mainly with presence of ground vegetation), forest structure and micro-relief topography. 4) Understanding bear responses to human presence: we will compare data from different parts of Europe with different human population densities to explore general patterns in strategies adopted by brown bear to adapt to human presence, and evaluate the impact of human population density on bears’ tolerance of humans. 5) Developing methodology for remote sensing of habituated bears with the use of telemetry data: we will analyse telemetry data of bears with different levels of habituation to humans and develop methodology for detection of habituated bears from telemetry data. 6) Synthesis and multi-method analysis of the causes behind development of problem bears: we will integrate results of previous workpackages in a holistic framework with a multi-method, multivariate analysis to explore relative contribution of each analysed factor, as well as the context and interacting effects of these factors on development of conflict behaviour. We believe that the solid data foundation and multi-method approaches we’re proposing can break a new ground in the science of animal behaviour in the wild. While we expect that the study will prove very important for brown bear conservation and mitigation of human-bear conflicts, it will also serve as an interesting case study and the methodological approach developed will have much broader implications.
Significance for science
Research of animal behaviour in the wild is challenging, especially in forested landscape where direct observation is rarely feasible. However, the results of such research can be essential for understanding of biology and ecology of certain species, and also for their conservation in the fast-changing world dominated by humans. The methods we're planning to use are powerful on their own and can provide answers to many demanding questions. However, these methods are in many cases complementary and we can expect that if they are integrated, the total will be much greater than the sum of its parts. Research of the development of conflict behaviour in brown bear is a very challenging topic, which makes it a perfect case study to demonstrate the yet untapped potential of the multi-method approaches. We expect the study to have considerable benefits for brown bear conservation. It will also have considerable demonstrational value since we'll show that even in difficult to study species we can answer very demanding questions with state of the art methods, which can have an important impact on development of conservation biology. On the other hand, we'll demonstrate the potential hidden in integration of different methodological approaches in research of behaviour and ecological characteristics of animals, which can have an important long-term impact on development of ecology and research of ethological characteristics of wildlife.
Significance for the country
Every year, brown bears cause considerable economical loss to local communities and economy in Slovenia (in average 160,000 € per year), resulting in high expenditure of taxpayers' money used to compensate for damages and among some people (Krofel & Jerina 2012). In addition, bears approaching human settlements often cause fear for personal safety among local people. At the same time, European brown bear is a charismatic and endangered species that generally receives very positive attitude from general public in Slovenia (Kaczensky et al. 2004). Furthermore, Slovenia is bounded by national and European law, to ensure long-term conservation of brown bears in its territory. However, bear will survive in human-dominated landscapes of Central Europe only if the number of damages and other conflicts will not exceed the level still tolerated by the public. Therefore effective prevention of human-bear conflicts is essential to ensure its long-term survival (WSPA, 2009). Due to the complexity of human-bear conflicts, their effective prevention is very challenging and can even result become counterproductive, if not properly planned (Krofel & Jerina 2012). Through the project we will obtain vital knowledge, which will help to identify main factors and mechanisms that are promoting development of problem bears. This knowledge will enable managers to design effective future conflict-prevention programmes. For example, if results will indicate that anthropogenic food sources in the vicinity of human settlements are the main reason for development of conflict bears, it will be clear indication for the need for improved waste management and control of illegal waste disposal in a bear core area. Results about the importance of social learning and transfer of problem behaviours from mother to her offspring and the influence of genetic predisposition for conflict behaviour will be important management guideline on how to deal with problem female bears (e.g. should they be quickly removed from the nature together with their descendants or not). Nowadays, large amount of resources and effort is being invested into the supplementary feeding of bears, although the effects of this controversial management measure are still mostly poorly understood (Kavčič et al. 2013, 2015; Steyaert et al. 2014). We expect that insights gained through this project will enable development effective guidelines regarding future use of supplementary feeding and thus importantly contribute not only to reduced bear-human conflict, but also to more efficient use of public funds devoted for bear management in Slovenia. We also expect that improved understanding of mechanisms behind human-bear conflicts and development of new methodological tools within the project will have important implications for bear management and conservation also beyond Slovenia.
Most important scientific results Interim report, final report
Most important socioeconomically and culturally relevant results Interim report, final report
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