Revealing biases in the sampling of ecological interaction networks
Authorde Aguiar, Marcus A.M.
Newman, Erica A.
Pires, Mathias M.
Yeakel, Justin D.
Burkle, Laura A.
Guimarães, Paulo R.
O’Donnell, James L.
Hembry, David H.
AffiliationUniv Arizona, Dept Ecol & Evolutionary Biol
Species interaction networks
Field sampling design
MetadataShow full item record
Citationde Aguiar MAM, Newman EA, Pires MM, Yeakel JD, Boettiger C, Burkle LA, Gravel D, Guimarães PR Jr, O’Donnell JL, Poisot T, Fortin M, Hembry DH. 2019. Revealing biases in the sampling of ecological interaction networks. PeerJ 7:e7566 https://doi.org/10.7717/peerj.7566
RightsCopyright © 2019 de Aguiar et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
Collection InformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at firstname.lastname@example.org.
AbstractThe 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 EcoNetGen, which constructs and samples networks with predetermined topologies. These networks may represent a wide variety of communities that vary in size and types of ecological interactions. We sampled these networks with different mathematical sampling designs that correspond to methods used in field observations. The observed networks generated by each sampling process were then analyzed with respect to the number of components, size of components and other network metrics. We show that the sampling effort needed to estimate underlying network properties depends strongly both on the sampling design and on the underlying network topology. In particular, networks with random or scale-free modules require more complete sampling to reveal their structure, compared to networks whose modules are nested or bipartite. Overall, modules with nested structure were the easiest to detect, regardless of the sampling design used. Sampling a network starting with any species that had a high degree (e.g., abundant generalist species) was consistently found to be the most accurate strategy to estimate network structure. Because high-degree species tend to be generalists, abundant in natural communities relative to specialists, and connected to each other, sampling by degree may therefore be common but unintentional in empirical sampling of networks. Conversely, sampling according to module (representing different interaction types or taxa) results in a rather complete view of certain modules, but fails to provide a complete picture of the underlying network. To reduce biases introduced by sampling methods, we recommend that these findings be incorporated into field design considerations for projects aiming to characterize large species interaction networks.
NoteOpen access journal
VersionFinal published version
SponsorsNational Science Foundation through NSF [DBI-1300426]; University of Tennessee, Knoxville; International Centre for Theoretical Physics ICTP-SAIFR [2016/01343-7 FAPESP]; FAPESP [2016/06054-3, 2016/01343-7]; CNPq [302049/2015-0]; University of Arizona Bridging Biodiversity and Conservation Science program; UC Berkeley Library
Showing items related by title, author, creator and subject.
The Implications for Network Recorder Design in a Networked Flight Test Instrumentation Data Acquisition SystemCranley, Nikki; ACRA Control (International Foundation for Telemetering, 2011-10)The higher bandwidth capacities available with the adoption of Ethernet technology for networked FTI data acquisition systems enable more data to be acquired. However, this puts increased demands on the network recorder to be able to support such data rates. During any given flight, the network recorder may log hundreds of GigaBytes of data, which must be processed and analyzed in real-time or in post-flight. This paper describes several approaches that may be adopted to facilitate data-on-demand data mining and data reduction operations. In particular, the use of filtering and indexing techniques that may be adopted to address this challenge are described.
The Implications for Network Switch Design in a Networked FTI Data Acquisition SystemCranley, Nikki; ACRA Control (International Foundation for Telemetering, 2011-10)Switches are a critical component in any networked FTI data acquisition system in order to allow the forwarding of data from the DAU to the target destination devices such as the network recorder, PCM gateways, or ground station. Commercial off the shelf switches cannot meet the harsh operating conditions of FTI. This paper describes a hardware implementation of a crossbar switching architecture that meets the reliability and performance requirements of FTI equipment. Moreover, by combining the crossbar architecture with filtering techniques, the switch can be configured to achieve sophisticated forwarding operations. By way of illustration, a Gigabit network tap application is used to demonstrate the fundamental concepts of switching, forwarding, crossbar architecture, and filtering.
FLEXIBLE NETWORK TRANSCEIVER NEXT GENERATION TELEMETRY NETWORKINGBrown, K. D.; Klimek, John; NNSA; JHU-APL (International Foundation for Telemetering, 2005-10)This paper describes the Flexible Telemetry Transceiver (FNT)-a modular, scalable, standards-based, software configurable, microwave wireless telemetry network transceiver. The FNT enables flexible, high-rate, long-range, duplex, network services across multipoint to multipoint wireless channel.