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Analiza cirkadianih ritmov aktivnosti zveri na podlagi podatkov telemetričnih ovratnic
ID Arl, Lian (Author), ID Moškon, Miha (Mentor) More about this mentor... This link opens in a new window, ID Potočnik, Hubert (Comentor)

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Abstract
V diplomskem delu smo cirkadiane ritme aktivnosti volka, risa in šakala analizirali z metodo cosinor v kombinaciji z generaliziranimi linearnimi mešanimi modeli. Podatke telemetričnih ovratnic osebkov smo obdelali v urno aktivnost in jo modelirali z generaliziranim Poissonovim modelom s fiksnimi in mešanimi učinki. Ritme posameznih osebkov smo ocenili z modeli s fiksnimi učinki, ritme skupin pa z modeli z mešanimi učinki. Ugotovili smo, da se ritmičnost razlikuje predvsem po osebkih in ne med vrstama. Pri posameznih osebkih je bil cirkadiani ritem aktivnosti prisoten v vseh letnih časih, spreminjala pa se je le moč izraženosti ritma. Čas vrha je ostal enak. Skupinski model je ritem zaznal pri volkovih, pri risih pa ne, čeprav so ritmični vsi risi. Vzrok za to ni odsotnost ritma pri risih, temveč njihove različne faze, ki se pri združevanju v skupino med seboj izničijo. Skupinsko povprečje pokaže tisto, kar je osebkom skupno, zato pri majhnem vzorcu z velikimi razlikami med osebki analiza po posameznikih daje zanesljivejšo sliko ritmičnosti.

Language:Slovenian
Keywords:regresija cosinor, generalizirani linearni mešani modeli, časovna vrsta, analiza cirkadianih ritmov, ekologija plenilcev
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:FRI - Faculty of Computer and Information Science
Year:2026
PID:20.500.12556/RUL-187506 This link opens in a new window
COBISS.SI-ID:292442115 This link opens in a new window
Publication date in RUL:11.09.2026
Views:94
Downloads:28
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Secondary language

Language:English
Title:Analysis of Circadian Activity Rhythms in Wild Carnivores Using Telemetry Collar Data
Abstract:
In this thesis, we analysed the circadian rhythmicity of wolf, lynx and jackal activity using the cosinor method in combination with generalized linear mixed models. Data from the animals’ telemetry collars were processed into hourly activity, which was then modelled with a generalized Poisson model with fixed and random effects. The rhythms of individual animals’ activity were estimated using fixed-effects models, and the rhythms of the groups using mixed-effects models. We found that rhythmicity differs primarily between individuals rather than between the two species. In individual animals, a daily rhythm was present in all seasons with only the amplitude of the oscillation changing, while the timing of the peak remained the same. The group model detected a rhythm in wolves but not in lynx, even though all individuals were rhythmic. The reason for this is not an absence of rhythm in lynx, but rather their differing phases, which cancel each other out when individuals are pooled into a group. A group average shows what individuals have in common, so with a small sample and large differences between individuals, an individual-level analysis provides a more reliable picture of rhythmicity.

Keywords:cosinor regression, generalized linear mixed models, timeseries data, circadian rhythm analysis, predator ecology

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