Finding missing links in interaction networks
Documenting which species interact within ecological communities is challenging and labor intensive. As a result, many interactions remain unrecorded, potentially distorting our understanding of network structure and dynamics. We test the utility of four structural models and a new coverage‐deficit...
| Auteurs principaux: | , |
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| Format: | Journal article |
| Langue: | English |
| Publié: |
Ecological Society of America
2020
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| _version_ | 1826261692700426240 |
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| author | Terry, JCD Lewis, OT |
| author_facet | Terry, JCD Lewis, OT |
| author_sort | Terry, JCD |
| collection | OXFORD |
| description | Documenting which species interact within ecological communities is challenging and labor intensive. As a result, many interactions remain unrecorded, potentially distorting our understanding of network structure and dynamics. We test the utility of four structural models and a new coverage‐deficit model for predicting missing links in both simulated and empirical bipartite networks. We find they can perform well, although the predictive power of structural models varies with the underlying network structure. The accuracy of predictions can be improved by ensembling multiple models. Augmenting observed networks with most‐likely missing links improves estimates of qualitative network metrics. Tools to identify likely missing links can be simple to implement, allowing the prioritization of research effort and more robust assessment of network properties. |
| first_indexed | 2024-03-06T19:25:20Z |
| format | Journal article |
| id | oxford-uuid:1b828130-4ce5-4426-a51c-ce8eb81e61b3 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T19:25:20Z |
| publishDate | 2020 |
| publisher | Ecological Society of America |
| record_format | dspace |
| spelling | oxford-uuid:1b828130-4ce5-4426-a51c-ce8eb81e61b32022-03-26T11:00:45ZFinding missing links in interaction networksJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:1b828130-4ce5-4426-a51c-ce8eb81e61b3EnglishSymplectic ElementsEcological Society of America2020Terry, JCDLewis, OTDocumenting which species interact within ecological communities is challenging and labor intensive. As a result, many interactions remain unrecorded, potentially distorting our understanding of network structure and dynamics. We test the utility of four structural models and a new coverage‐deficit model for predicting missing links in both simulated and empirical bipartite networks. We find they can perform well, although the predictive power of structural models varies with the underlying network structure. The accuracy of predictions can be improved by ensembling multiple models. Augmenting observed networks with most‐likely missing links improves estimates of qualitative network metrics. Tools to identify likely missing links can be simple to implement, allowing the prioritization of research effort and more robust assessment of network properties. |
| spellingShingle | Terry, JCD Lewis, OT Finding missing links in interaction networks |
| title | Finding missing links in interaction networks |
| title_full | Finding missing links in interaction networks |
| title_fullStr | Finding missing links in interaction networks |
| title_full_unstemmed | Finding missing links in interaction networks |
| title_short | Finding missing links in interaction networks |
| title_sort | finding missing links in interaction networks |
| work_keys_str_mv | AT terryjcd findingmissinglinksininteractionnetworks AT lewisot findingmissinglinksininteractionnetworks |