Quantifying interaction networks and stability properties of plankton food webs using multivariate first order autoregressive modelling

TY - CHAP

T1 - Quantifying interaction networks and stability properties of plankton food webs using multivariate first order autoregressive modelling

AU - Gsell, A.S.

AU - Özkundakci, Deniz

AU - Hébert, Marie-Pier

AU - Adrian, Rita

N1 - 6663 AqE; Data Archiving:

PY - 2018

Y1 - 2018

N2 - Lakes and reservoirs have been identified as sentinels of global change as they integratechanges in the surrounding landscape. While univariate indicator variables are relatively well assessed,the lack of knowledge on temporal changes in species interactions under pressure has been identified asa major gap in the bio-monitoring sciences. Multivariate autoregressive models can be used to assessdirection and strength of both direct and indirect interactions in complex communities over time. Thismodel framework also allows calculation of network stability properties (variance, resilience and reactivity). Moreover, the interaction matrix can be further analyzed for classical network structure properties (closeness- and betweenness centrality). These measures are useful indicators of changes in ecosystem stability and help identify biotic keystone groups and/or groups of species that are particularlyvulnerable to changes in the landscape

AB - Lakes and reservoirs have been identified as sentinels of global change as they integratechanges in the surrounding landscape. While univariate indicator variables are relatively well assessed,the lack of knowledge on temporal changes in species interactions under pressure has been identified asa major gap in the bio-monitoring sciences. Multivariate autoregressive models can be used to assessdirection and strength of both direct and indirect interactions in complex communities over time. Thismodel framework also allows calculation of network stability properties (variance, resilience and reactivity). Moreover, the interaction matrix can be further analyzed for classical network structure properties (closeness- and betweenness centrality). These measures are useful indicators of changes in ecosystem stability and help identify biotic keystone groups and/or groups of species that are particularlyvulnerable to changes in the landscape

KW - international

U2 - 10.25680/3366.2018.41.77.257

DO - 10.25680/3366.2018.41.77.257

M3 - Chapter

SN - 978-5-9238-0249-8

VL - 3

SP - 306

EP - 309

BT - Novel Methods and Results of Landscape Research in Europe, Central Asia and Siberia

A2 - Sychev, Viktor

A2 - Mueller, Lothar

PB - Russian Academy of Sciences

CY - Moscow

ER -