Sampling bias and the robustness of ecological metrics for plant–damage-type association networks

Simple item page
dc.contributor.authorSwain, Anshuman
dc.contributor.authorAzevedo-Schmidt, Lauren E.
dc.contributor.authorMaccracken, S. Augusta
dc.contributor.authorCurrano, Ellen D.
dc.contributor.authorDunne, Jennifer A.
dc.contributor.authorLabandeira, Conrad C.
dc.contributor.authorFagan, William F.
dc.date.accessioned2023-10-03T16:39:06Z
dc.date.available2023-10-03T16:39:06Z
dc.date.issued2022-11-22
dc.description.abstractPlants and their insect herbivores have been a dominant component of the terrestrial ecological landscape for the past 410 million years and feature intricate evolutionary patterns and co-dependencies. A complex systems perspective allows for both detailed resolution of these evolutionary relationships as well as comparison and synthesis across systems. Using proxy data of insect herbivore damage (denoted by the damage type or DT) preserved on fossil leaves, functional bipartite network representations provide insights into how plant–insect associations depend on geological time, paleogeographical space, and environmental variables such as temperature and precipitation. However, the metrics measured from such networks are prone to sampling bias. Such sensitivity is of special concern for plant–DT association networks in paleontological settings where sampling effort is often severely limited. Here, we explore the sensitivity of functional bipartite network metrics to sampling intensity and identify sampling thresholds above which metrics appear robust to sampling effort. Across a broad range of sampling efforts, we find network metrics to be less affected by sampling bias and/or sample size than richness metrics, which are routinely used in studies of fossil plant–DT interactions. These results provide reassurance that cross-comparisons of plant–DT networks offer insights into network structure and function and support their widespread use in paleoecology. Moreover, these findings suggest novel opportunities for using plant–DT networks in neontological terrestrial ecology to understand functional aspects of insect herbivory across geological time, environmental perturbations, and geographic space.
dc.description.urihttps://doi.org/10.1002/ecy.3922
dc.identifierhttps://doi.org/10.13016/dspace/8zes-fit9
dc.identifier.citationSwain, Anshuman, Azevedo-Schmidt, Lauren E., Maccracken, S. Augusta, Currano, Ellen D., Dunne, Jennifer A., Labandeira, Conrad C., and Fagan, William F.. 2023. “ Sampling Bias and the Robustness of Ecological Metrics for Plant–Damage-Type Association Networks.” Ecology 104(3): e3922.
dc.identifier.urihttp://hdl.handle.net/1903/30659
dc.language.isoen_US
dc.publisherWiley
dc.relation.isAvailableAtDigital Repository at the University of Marylanden_us
dc.relation.isAvailableAtUniversity of Maryland (College Park, Md)en_us
dc.subjectbipartite networks
dc.subjectfossil plant-insect interactions
dc.subjectfunctional networks
dc.subjectnetwork metrics
dc.subjectplant-damage type associations
dc.subjectsampling size bias
dc.titleSampling bias and the robustness of ecological metrics for plant–damage-type association networks
dc.typeArticle
local.equitableAccessSubmissionNo

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Ecology - 2022 - Swain - Sampling bias and the robustness of ecological metrics for plant damage‐type association networks.pdf
Size:
921.17 KB
Format:
Adobe Portable Document Format
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.55 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Biology Research Works