BCO-DMO Logo
Access Data
ACCESS DATA
  • Dataset Search
  • Browse Catalog
    DatasetsDeploymentsProjectsProgramsInstrumentsPeopleParametersAwardsPlatformsRelated PublicationsAffiliationsFunding
  • Data Access Help
Contribute
SUBMIT DATA
  • Register Your Project
  • Submit Data
  • Contribute HelpData Submission Guidelines
Resources
RESOURCES
  • Data Management Plan
  • PrepareGeneral and topic specific data guidance
  • Education & Training
  • FAQs
  • Documentation
About Us
ABOUT US
  • Blog
  • About BCO-DMO
  • Meet the Team
  • Policies
Loading...Still loading...Hang on... This is taking longer than expected!

Related Publication

DOI: 10.1111/ele.14020

Citation Style: APA

Citation Text:

Albecker, M. A., Trussell, G. C., & Lotterhos, K. E. (2022). A novel analytical framework to quantify co‐gradient and countergradient variation. Ecology Letters, 25(6), 1521–1533. Portico. https://doi.org/10.1111/ele.14020


  • Datasets (4)
DatasetRelation
Results using simulated data used to conduct power analyses Results
Metadata for studies from meta-analysis investigating covariance between genetic and environmental (CovGE) effects in phenotypic results Results
Results from a meta-analysis investigating covariance between genetic and environmental (CovGE) effects in phenotypic results in published literatureResults
Model code and output for a comparison of methods for meta-analysis investigating covariance between genetic and environmental (CovGE) effects in phenotypic resultsResults

Access Data

  • Dataset Search
  • Browse all Data
  • Access Data Help
  • BCO-DMO API

Submit Data

  • Submit Data
  • Register your Project
  • Prepare
  • Submission Help

About Us

  • About BCO-DMO
  • Meet the Team
  • Policies
  • Products

Resources

  • Education & Training
  • Documentation
  • FAQs
NSF Logo©2020 Biological and Chemical Oceanography Data Management Office.
Funded by the U.S. National Science Foundation