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Uncovering ecological state dynamics with hidden Markov models ArchiMer
Mcclintock, Brett T.; Langrock, Roland; Gimenez, Olivier; Cam, Emmanuelle; Borchers, David L.; Glennie, Richard; Patterson, Toby A.; Coulson, Tim.
Ecological systems can often be characterised by changes among a finite set of underlying states pertaining to individuals, populations, communities or entire ecosystems through time. Owing to the inherent difficulty of empirical field studies, ecological state dynamics operating at any level of this hierarchy can often be unobservable or ‘hidden’. Ecologists must therefore often contend with incomplete or indirect observations that are somehow related to these underlying processes. By formally disentangling state and observation processes based on simple yet powerful mathematical properties that can be used to describe many ecological phenomena, hidden Markov models (HMMs) can facilitate inferences about complex system state dynamics that might otherwise...
Tipo: Text Palavras-chave: Behavioural ecology; Community ecology; Ecosystem ecology; Hierarchical model; Movement ecology; Observation error; Population ecology; State-space model; Time series.
Ano: 2020 URL: https://archimer.ifremer.fr/doc/00655/76692/77831.pdf
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