| Issue |
EPL
Volume 132, Number 6, December 2020
|
|
|---|---|---|
| Article Number | 68001 | |
| Number of page(s) | 7 | |
| Section | Interdisciplinary Physics and Related Areas of Science and Technology | |
| DOI | https://doi.org/10.1209/0295-5075/132/68001 | |
| Published online | 02 March 2021 | |
Open challenges in environmental data analysis and ecological complex systems(a)
1 School of Electrical and Computer Engineering, Technical University of Crete - Chania 73100, Greece
2 Dipartimento di Fisica e Chimica “Emilio Segrè”, Group of Interdisciplinary Theoretical Physics, Università degli Studi di Palermo, and CNISM, Unità di Palermo - Palermo, Italy
3 Radiophysics Department, Lobachevsky State University - Nizhny Novgorod, Russia
4 Istituto Nazionale di Fisica Nucleare, Sezione di Catania - Catania, Italy
5 CNR- IRIB, Consiglio Nazionale delle Ricerche-Istituto per la Ricerca e l'Innovazione Biomedica Via Ugo La Malfa 153, 90146 Palermo, Italy
Received: 16 November 2020
Accepted: 4 January 2021
This letter focuses on open challenges in the fields of environmental data analysis and ecological complex systems. It highlights relations between research problems in stochastic population dynamics, machine learning and big data research, and statistical physics. Recent and current developments in statistical modeling of spatiotemporal data and in population dynamics are briefly reviewed. The presentation emphasizes stochastic fluctuations, including their statistical representation, data-based estimation, prediction, and impact on the physics of the underlying systems. Guided by the common thread of stochasticity, a deeper and improved understanding of environmental processes and ecosystems can be achieved by forging stronger interdisciplinary connections between statistical physics, spatiotemporal data modeling, and ecology.
PACS: 89.20.-a – Interdisciplinary applications of physics / 87.23.Cc – Population dynamics and ecological pattern formation / 89.60.-k – Environmental studies
© 2021 EPLA
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