Metzler, Holger
- Institutionen för skogens ekologi och skötsel, Sveriges lantbruksuniversitet
- Institutionen för växtproduktionsekologi, Sveriges lantbruksuniversitet
- Ludwig-Maximilians-Universität München (LMU)
- Max Planck Institut für Biogeochemie
Sammanfattning
Mass-balanced compartmental systems defy classical deterministic entropy measures since both metric and topological entropy vanish in dissipative dynamics. By interpreting open compartmental systems as absorbing continuous-time Markov chains that describe the random journey of a single representative particle, we allow established information-theoretic principles to be applied to this particular type of deterministic dynamical system. In particular, path entropy quantifies the uncertainty of complete trajectories, while entropy rates measure the average uncertainty of instantaneous transitions. Using Shannon's information entropy, we derive closed-form expressions for these quantities in equilibrium and extend the maximum entropy principle (MaxEnt) to the problem of model selection in compartmental dynamics. This information-theoretic framework not only provides a systematic way to address equifinality but also reveals hidden structural properties of complex systems such as the global carbon cycle.
Nyckelord
information entropy; compartmental systems; equifinality; model identification; MaxEnt; reservoir models
Publicerad i
Entropy
2025, volym: 27, nummer: 10, artikelnummer: 1085
Utgivare: MDPI
SLU författare
UKÄ forskningsämne
Statistisk fysik och komplexa system
Multidisciplinär geovetenskap
Publikationens identifierare
- DOI: https://doi.org/10.3390/e27101085
Permanent länk till denna sida (URI)
https://res.slu.se/id/publ/144593