ArticlePeerJ2019
Revealing biases in the sampling of ecological interaction networks.
Article in PeerJ, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
5 citing papers in PubMed.
- Assessing the Ecological Network of Svalbard Through Scaled Interaction Strength Data: Insights From a Century of Research.Ecology and evolution · 2026Article
- The Effects of Disturbance on Plant-Pollinator Interactions in the Native Forests of an Oceanic Island (Terceira, Azores).Insects · 2024Article
- A highly resolved network reveals the role of terrestrial herbivory in structuring aboveground food webs.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024Article
- Article
- A roadmap towards predicting species interaction networks (across space and time).Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2021Review
Corrections and comments
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The structure of ecological interactions is commonly understood through analyses of interaction networks. However, these analyses may be sensitive to sampling biases with respect to both the interactors (the nodes of the network) and interactions (the links between nodes), because the detectability of species and their interactions is highly heterogeneous. These ecological and statistical issues directly affect ecologists' abilities to accurately construct ecological networks. However, statistical biases introduced by sampling are difficult to quantify in the absence of full knowledge of the underlying ecological network's structure. To explore properties of large-scale ecological networks, we developed the software
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.