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NOS: a software suite to compute node overlap and segregation in ecological networks
Authors:Giovanni Strona  Thomas J Matthews  Susanne Kortsch  Joseph A Veech
Institution:1. http://orcid.org/0000‐0003‐2294‐4013;2. European Commission, Joint Research Centre, Directorate D – Sustainable Resources – Bio‐Economy Unit, Ispra (VA), Italy;3. GEES (School of Geography, Earth and Environmental Sciences), The Univ. of Birmingham, Birmingham, UK;4. CE3C – Centre for Ecology, Evolution and Environmental Changes/Azorean Biodiversity Group and Univ. dos A?ores – Depto de Ciências Agrárias, Angra do Heroísmo, A?ores, Portugal;5. http://orcid.org/0000‐0002‐6495‐4781;6. Norwegian College of Fishery Science, UIT the Arctic Univ. of Norway, Troms?, Norway;7. Dept of Biology, Texas State Univ., San Marcos, TX, USA
Abstract:Investigating the structure of ecological networks can help unravel the mechanisms promoting and maintaining biodiversity. Recently, Strona and Veech 2015 (A new measure of ecological network structure based on node overlap and segregation. – Methods Ecol. Evol. 6: 907–915) introduced a new metric (??, pronounced ‘nos’), that allows assessment of structural patterns in networks ranging from complete node segregation to perfect nestedness, and that also provides a visual and quantitative assessment of the degree of network modularity. The ?? metric permits testing of a wide range of hypotheses regarding the tendency for species to share interacting partners by taking into account ecologically plausible species interactions based on constraints such as trophic levels and habitat preference. Here we introduce NOS, a software suite (including a web interface freely accessible at  http://nos.alwaysdata.net , an executable program, and Python and R packages) that makes it possible to exploit the full potential of this method. Besides computing node overlap and segregation (??), the software provides different functions to automatically identify a set of possible resource–consumer interactions in food webs based on trophic levels. As an example of application, we analyzed two well‐resolved high‐latitude marine food webs, showing that an explicit a priori consideration of trophic levels is fundamental for a proper assessment of food web structure.
Keywords:
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