TY  - JOUR
A1  - Pennekamp, Frank
A1  - Iles, Alison C.
A1  - Garland, Joshua
A1  - Brennan, Georgina
A1  - Brose, Ulrich
A1  - Gaedke, Ursula
A1  - Jacob, Ute
A1  - Kratina, Pavel
A1  - Matthews, Blake
A1  - Munch, Stephan
A1  - Novak, Mark
A1  - Palamara, Gian Marco
A1  - Rall, Bjorn C.
A1  - Rosenbaum, Benjamin
A1  - Tabi, Andrea
A1  - Ward, Colette
A1  - Williams, Richard
A1  - Ye, Hao
A1  - Petchey, Owen L.
T1  - The intrinsic predictability of ecological time series and its potential to guide forecasting
JF  - Ecological monographs : a publication of the Ecological Society of America.
KW  - empirical dynamic modelling
KW  - forecasting
KW  - information theory
KW  - permutation entropy
KW  - population dynamics
KW  - time series analysis
Y1  - 2019
U6  - https://doi.org/10.1002/ecm.1359
SN  - 0012-9615
SN  - 1557-7015
VL  - 89
IS  - 2
PB  - Wiley
CY  - Hoboken
ER  - 
TY  - JOUR
A1  - Wiesner, Karoline
A1  - Ladyman, James
T1  - Complex systems are always correlated but rarely information processing
JF  - Journal of physics. Complexity
N2  - 'Complex systems are information processors' is a statement that is frequently made. Here we argue for the distinction between information processing-in the sense of encoding and transmitting a symbolic representation-and the formation of correlations (pattern formation/self-organisation). The study of both uses tools from information theory, but the purpose is very different in each case: explaining the mechanisms and understanding the purpose or function in the first case, versus data analysis and correlation extraction in the latter. We give examples of both and discuss some open questions. The distinction helps focus research efforts on the relevant questions in each case.
KW  - correlations
KW  - information theory
KW  - complex systems
KW  - information
KW  - processing
KW  - self-organisation
Y1  - 2021
U6  - https://doi.org/10.1088/2632-072X/ac371c
SN  - 2632-072X
VL  - 2
IS  - 4
PB  - IOP Publ. Ltd.
CY  - Bristol
ER  -