Home
Resource
Computational workflow for ancient network reconstruction
PDF
PDF format is widely accepted and good for printing.
Plug-in required
PDF-1(618.78 kb)
A pdf supplem...(45.45 kb)
Citation & Export
View Usage Statistics
Staff View

Citation & Export
Hide

Simple citation

Derago, Alexa. Computational workflow for ancient network reconstruction. Retrieved from https://doi.org/doi:10.7282/t3-mgbf-e436

Export

Click here for information about Citation Management Tools at Rutgers.

Statistics
Hide

Description

TitleComputational workflow for ancient network reconstruction
NameDerago, Alexa (author); Gonzalez, Angelica (chair); Piccoli, Benedetto (member); Gonzalez, Angelica (member); Geneva, Anthony (member); Rutgers University; Graduate School - Camden
Date Created2022
Other Date2022-05 (degree)
SubjectMathematics, Ecology, Community ecology, Ecological networks, Food webs, Paleoecology
Extent19 pages : illustrations
DescriptionA network approach to studying palaeoecologically data can provide us with information on how past communities responded to change. This information can then be used to make predictions on how present-day communities may adapt to changing conditions. Rodent middens, preserved plant matter and arthropod remains, offer a useful source for palaeoecologically data. They can be used as records of past assemblages. This thesis provides a computational framework for the reconstruction of ancient networks using paleomidden data. This framework will take into consideration predator-prey relations using body mass ratios, the spatial distance of samples, and the difference in time scales between samples. We provide a complete workflow, which is amenable to extensions and ready to be used with independently collected paleomidden data.
NoteM.S.
NoteIncludes bibliographical references
Genretheses
Persistent URLhttps://doi.org/doi:10.7282/t3-mgbf-e436
LanguageEnglish
CollectionCamden Graduate School Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.
Version 8.5.5
Rutgers University Libraries - Copyright ©2024