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SYKE - Finnish Environment Institute (Finland)DCE - Danish Centre for Environment and Energy, Aarhus University (Denmark)EC JRC - European Commission, Joint Research CentreIRSTEA - National Research Institute of Science and Technology for Environment and Agriculture (France)CEH - Centre for Ecology & Hydrology (United Kingdom)Wageningen Environmental Research (Alterra)UFZ - Helmholtz Centre for Environmental Research (Germany)CIENS - Oslo Centre for Interdisciplinary Environmental and Social Researchpeer
 

NOS – the new free software for the analysis of ecological networks

06 October 2017, JRC

A new, free software suite for the analysis of ecological networks has been released. The suite, which is named ‘NOS’ (Node Overlap and Segregation Software) and whose features are described in detail in a recently published paper led by JRC scientist Giovanni Strona, includes a user-friendly online interface, a Python package, a standalone executable program, and an R package (available from CRAN at cran.r-project.org/web/packages/nos/index.html).

NOS helps model the extent to which the nodes of ecological networks tend to overlap or segregate. ©Strona and Veech, 2017

The suite makes it easier to assess if, and to what extent, the structure of an ecological network tends towards either node overlap or segregation, and modularity. That is, it helps quantify the tendency for two members of a network (such as two pollinators) to share interacting partners (e.g. plants), a pattern that has received much attention in recent studies, having being suggested as key to the stability and resilience of natural communities.

The core of the software revolves around the network index introduced by Strona and Veech in 2015. The many advanced (yet easy to use) software functionalities of NOS, such as the automatic identification of trophic levels in food webs, have the potential to improve scientists’ understanding of ecological network structures. In turn, considering that one of the main threats to biodiversity is how species loss may propagate through species interactions (e.g. from resources to consumers), this may provide fundamental insights into how natural systems will respond to global change.

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