Wetlands Ecology and Management

, Volume 23, Issue 6, pp 1039–1047

Automated analysis of temperature variance to determine inundation state of wetlands

  • Thomas L. Anderson
  • Jennifer L. Heemeyer
  • William E. Peterman
  • Michael J. Everson
  • Brittany H. Ousterhout
  • Dana L. Drake
  • Raymond D. Semlitsch
Original Paper

DOI: 10.1007/s11273-015-9439-x

Cite this article as:
Anderson, T.L., Heemeyer, J.L., Peterman, W.E. et al. Wetlands Ecol Manage (2015) 23: 1039. doi:10.1007/s11273-015-9439-x

Abstract

Monitoring the inundation state (wet or dry) of wetlands is critical to understanding aquatic community structure but can be costly and labor-intensive. We tested the ability of temperature data from cost-effective iButton data loggers to reflect the inundation state of wetlands in central Missouri, based on our hypothesis that dry ponds would show greater daily temperature variance than ponds that remained inundated with water. We evaluated this method with two experiments in large outdoor mesocosms, and in existing natural wetlands in which we had deployed iButtons. True inundation state from pond visits was compared to predicted inundation state over different temperature variance thresholds expected to delineate wet or dry ponds. We confirmed that the daily temperature variances of dry iButtons were higher than that of iButtons under water, as expected, but that variance was influenced by factors such as canopy cover. We also describe an automated procedure that can be used to determine whether a pond was wet or dry with greater than 80 % accuracy. Using this approach, changes in inundation state, the number of days wet and dry, and the number of drying and filling events can be calculated. Several caveats are also provided that should be considered prior to using this method to maximize the accuracy in assessing inundation state.

Keywords

Drying Hydroperiod iButton Inundation Pond Water level Temperature data logger 

Supplementary material

11273_2015_9439_MOESM1_ESM.docx (738 kb)
Online Appendix A (DOCX 738 kb)
11273_2015_9439_MOESM2_ESM.docx (2 mb)
Online Appendix B (DOCX 2012 kb)
11273_2015_9439_MOESM3_ESM.docx (1.3 mb)
Online Appendix C (DOCX 1318 kb)

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  • Thomas L. Anderson
    • 1
  • Jennifer L. Heemeyer
    • 1
  • William E. Peterman
    • 1
    • 2
  • Michael J. Everson
    • 1
  • Brittany H. Ousterhout
    • 1
  • Dana L. Drake
    • 1
  • Raymond D. Semlitsch
    • 1
  1. 1.Division of Biological SciencesUniversity of MissouriColumbiaUSA
  2. 2.Illinois Natural History Survey, Prairie Research InstituteUniversity of IllinoisChampaignUSA

Personalised recommendations