PT  - JOURNAL ARTICLE
AU  - Matthew K. Lau
AU  - Stuart R. Borrett
AU  - Benjamin Baiser
AU  - Nicholas J. Gotelli
AU  - Aaron M. Ellison
TI  - Ecological Network Metrics: Opportunities for Synthesis
AID  - 10.1101/125781
DP  - 2017 Jan 01
TA  - bioRxiv
PG  - 125781
4099  - http://biorxiv.org/content/early/2017/06/25/125781.short
4100  - http://biorxiv.org/content/early/2017/06/25/125781.full
AB  - Network ecology provides a systems basis for approaching ecological questions, such as factors that influence biological diversity, the role of particular species or particular traits in structuring ecosystems, and long-term ecological dynamics (e.g., stability). Whereas the introduction of network theory has enabled ecologists to quantify not only the degree, but also the architecture of ecological complexity, these advances have come at the cost of introducing new challenges, including new theoretical concepts and metrics, and increased data complexity and computational intensity. Synthesizing recent developments in the network ecology literature, we point to several potential solutions to these issues: integrating network metrics and their terminology across sub-disciplines; benchmarking new network algorithms and models to increase mechanistic understanding; and improving tools for sharing ecological network research, in particular “model” data provenance, to increase the reproducibility of network models and analyses. We propose that applying these solutions will aid in synthesizing ecological subdisciplines and allied fields by improving the accessibility of network methods and models.