TY  - JOUR
A1  - Guill, Christian
A1  - Hülsemann, Janne
A1  - Klauschies, Toni
T1  - Self-organised pattern formation increases local diversity in metacommunities
JF  - Ecology letters
N2  - Self-organised formation of spatial patterns is known from a variety of different ecosystems, yet little is known about how these patterns affect the diversity of communities. Here, we use a food chain model in which autotroph diversity is described by a continuous distribution of a trait that affects both growth and defence against heterotrophs. On isolated patches, diversity is always lost over time due to stabilising selection, and the local communities settle on one of two alternative stable community states that are characterised by a dominance of either defended or undefended species. In a metacommunity context, dispersal can destabilise these states and complex spatio-temporal patterns in the species' abundances emerge. The resulting biomass-trait feedback increases local diversity by an order of magnitude compared to scenarios without self-organised pattern formation, thereby maintaining the ability of communities to adapt to potential future changes in biotic or abiotic environmental conditions.
KW  - biomass-trait feedback
KW  - fitness gradient
KW  - food chain
KW  - functional
KW  - diversity
KW  - metacommunity
KW  - self-organisation
KW  - source-sink dynamics
KW  - spatio-temporal pattern
KW  - trait-based aggregate model
KW  - Turing instability
Y1  - 2021
U6  - https://doi.org/10.1111/ele.13880
SN  - 1461-023X
SN  - 1461-0248
VL  - 24
IS  - 12
SP  - 2624
EP  - 2634
PB  - Wiley-Blackwell
CY  - Oxford
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  -