Next Article in Journal
The Space-Borne SBAS-DInSAR Technique as a Supporting Tool for Sustainable Urban Policies: The Case of Istanbul Megacity, Turkey
Next Article in Special Issue
Bottom Reflectance in Ocean Color Satellite Remote Sensing for Coral Reef Environments
Previous Article in Journal
Classification of Ultra-High Resolution Orthophotos Combined with DSM Using a Dual Morphological Top Hat Profile
Article Menu

Export Article

Open AccessArticle
Remote Sens. 2015, 7(12), 16480-16503; doi:10.3390/rs71215837

A Hybrid Model for Mapping Relative Differences in Belowground Biomass and Root: Shoot Ratios Using Spectral Reflectance, Foliar N and Plant Biophysical Data within Coastal Marsh

1
Department of Environmental Sciences Policy and Management, University of California, Berkeley, Berkeley, CA 94720, USA
2
Department of Marine Sciences, University of Georgia, Athens, GA 30602, USA
3
Geological Survey, Western Geographic Science Center, Menlo Park, CA 94025, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Richard W. Gould, Yoshio Inoue and Prasad S. Thenkabail
Received: 27 July 2015 / Accepted: 25 November 2015 / Published: 5 December 2015
(This article belongs to the Special Issue Remote Sensing in Coastal Environments)
View Full-Text   |   Download PDF [3005 KB, uploaded 7 December 2015]   |  

Abstract

Broad-scale estimates of belowground biomass are needed to understand wetland resiliency and C and N cycling, but these estimates are difficult to obtain because root:shoot ratios vary considerably both within and between species. We used remotely-sensed estimates of two aboveground plant characteristics, aboveground biomass and % foliar N to explore biomass allocation in low diversity freshwater impounded peatlands (Sacramento-San Joaquin River Delta, CA, USA). We developed a hybrid modeling approach to relate remotely-sensed estimates of % foliar N (a surrogate for environmental N and plant available nutrients) and aboveground biomass to field-measured belowground biomass for species specific and mixed species models. We estimated up to 90% of variation in foliar N concentration using partial least squares (PLS) regression of full-spectrum field spectrometer reflectance data. Landsat 7 reflectance data explained up to 70% of % foliar N and 67% of aboveground biomass. Spectrally estimated foliar N or aboveground biomass had negative relationships with belowground biomass and root:shoot ratio in both Schoenoplectus acutus and Typha, consistent with a balanced growth model, which suggests plants only allocate growth belowground when additional nutrients are necessary to support shoot development. Hybrid models explained up to 76% of variation in belowground biomass and 86% of variation in root:shoot ratio. Our modeling approach provides a method for developing maps of spatial variation in wetland belowground biomass. View Full-Text
Keywords: belowground biomass; carbon cycling; coastal tidal freshwater wetlands; eutrophication; Landsat; nitrogen cycling; productivity; root:shoot ratio; remote-sensing; sea level rise belowground biomass; carbon cycling; coastal tidal freshwater wetlands; eutrophication; Landsat; nitrogen cycling; productivity; root:shoot ratio; remote-sensing; sea level rise
Figures

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

O’Connell, J.L.; Byrd, K.B.; Kelly, M. A Hybrid Model for Mapping Relative Differences in Belowground Biomass and Root: Shoot Ratios Using Spectral Reflectance, Foliar N and Plant Biophysical Data within Coastal Marsh. Remote Sens. 2015, 7, 16480-16503.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top