TY  - JOUR
A1  - Vilk, Ohad
A1  - Aghion, Erez
A1  - Nathan, Ran
A1  - Toledo, Sivan
A1  - Metzler, Ralf
A1  - Assaf, Michael
T1  - Classification of anomalous diffusion in animal movement data using power spectral analysis
JF  - Journal of physics : A, Mathematical and theoretical
N2  - The field of movement ecology has seen a rapid increase in high-resolution data in recent years, leading to the development of numerous statistical and numerical methods to analyse relocation trajectories. Data are often collected at the level of the individual and for long periods that may encompass a range of behaviours. 

Here, we use the power spectral density (PSD) to characterise the random movement patterns of a black-winged kite (Elanus caeruleus) and a white stork (Ciconia ciconia). The tracks are first segmented and clustered into different behaviours (movement modes), and for each mode we measure the PSD and the ageing properties of the process. 

For the foraging kite we find 1/f noise, previously reported in ecological systems mainly in the context of population dynamics, but not for movement data. We further suggest plausible models for each of the behavioural modes by comparing both the measured PSD exponents and the distribution of the single-trajectory PSD to known theoretical results and simulations.
KW  - diffusion
KW  - anomalous diffusion
KW  - power spectral analysis
KW  - ecological
KW  - movement data
Y1  - 2022
U6  - https://doi.org/10.1088/1751-8121/ac7e8f
SN  - 1751-8113
SN  - 1751-8121
VL  - 55
IS  - 33
PB  - IOP Publishing
CY  - Bristol
ER  - 
TY  - JOUR
A1  - Padash, Amin
A1  - Aghion, Erez
A1  - Schulz, Alexander
A1  - Barkai, Eli
A1  - Chechkin, Aleksei V.
A1  - Metzler, Ralf
A1  - Kantz, Holger
T1  - Local equilibrium properties of ultraslow diffusion in the Sinai model
JF  - New journal of physics
N2  - We perform numerical studies of a thermally driven, overdamped particle in a random quenched force field, known as the Sinai model. We compare the unbounded motion on an infinite 1-dimensional domain to the motion in bounded domains with reflecting boundaries and show that the unbounded motion is at every time close to the equilibrium state of a finite system of growing size. This is due to time scale separation: inside wells of the random potential, there is relatively fast equilibration, while the motion across major potential barriers is ultraslow. Quantities studied by us are the time dependent mean squared displacement, the time dependent mean energy of an ensemble of particles, and the time dependent entropy of the probability distribution. Using a very fast numerical algorithm, we can explore times up top 10(17) steps and thereby also study finite-time crossover phenomena.
KW  - Sinai diffusion
KW  - clustering
KW  - local equilibrium
Y1  - 2022
U6  - https://doi.org/10.1088/1367-2630/ac7df8
SN  - 1367-2630
VL  - 24
IS  - 7
PB  - IOP Publishing
CY  - Bristol
ER  - 
TY  - JOUR
A1  - Vilk, Ohad
A1  - Aghion, Erez
A1  - Avgar, Tal
A1  - Beta, Carsten
A1  - Nagel, Oliver
A1  - Sabri, Adal
A1  - Sarfati, Raphael
A1  - Schwartz, Daniel K.
A1  - Weiß, Matthias
A1  - Krapf, Diego
A1  - Nathan, Ran
A1  - Metzler, Ralf
A1  - Assaf, Michael
T1  - Unravelling the origins of anomalous diffusion
BT  - from molecules to migrating storks
JF  - Physical review research / American Physical Society
N2  - Anomalous diffusion or, more generally, anomalous transport, with nonlinear dependence of the mean-squared displacement on the measurement time, is ubiquitous in nature. It has been observed in processes ranging from microscopic movement of molecules to macroscopic, large-scale paths of migrating birds. Using data from multiple empirical systems, spanning 12 orders of magnitude in length and 8 orders of magnitude in time, we employ a method to detect the individual underlying origins of anomalous diffusion and transport in the data. This method decomposes anomalous transport into three primary effects: long-range correlations (“Joseph effect”), fat-tailed probability density of increments (“Noah effect”), and nonstationarity (“Moses effect”). We show that such a decomposition of real-life data allows us to infer nontrivial behavioral predictions and to resolve open questions in the fields of single-particle tracking in living cells and movement ecology.
Y1  - 2022
U6  - https://doi.org/10.1103/PhysRevResearch.4.033055
SN  - 2643-1564
VL  - 4
IS  - 3
PB  - American Physical Society
CY  - College Park, MD
ER  -