Estimating plant biomass in early-successional subtropical vegetation using a visual obstruction technique

  • Authors: Fleming, Genie M.; Wunderle, Joseph M.; Ewert, David N.; O''Brien, Joseph
  • Publication Year: 2014
  • Publication Series: Scientific Journal (JRNL)
  • Source: Applied Vegetation Science


Aim: Non-destructive methods for quantifying above-ground plant biomass are important tools in many ecological studies and management endeavours, but estimation methods can be labour intensive and particularly difficult in structurally diverse vegetation types. We aimed to develop a low-cost, but reasonably accurate, estimation technique within early-successional Bahamian broadleaf shrub vegetation. Location: Eleuthera, The Bahamas. Methods: Our biomass estimation technique was based on a visual obstruction method originally developed for use in grassland vegetation, but modified to suit our mixed vegetation structure. Visual obstruction measures were recorded for a total of 90 0.25-m2 quadrats from which all standing vegetation was subsequently collected, dried and weighed. Regression models were then developed to predict vegetation dry weight (biomass) from visual obstruction. Results: The field time and equipment costs required to obtain our visual obstruction measures were low, and the accuracy of our above-ground plant biomass predictions was on par with that reported for other estimation techniques. Should increased accuracy or additional structural information be desired, our basic technique can be enhanced by adding other easily obtained measures (e.g. woody stem circumference). Conclusions: Our low-cost technique yields reasonably accurate estimates of above-ground plant biomass and should be transferable to any shrubland vegetation type where the maximum height of vegetation is typically below 2 m.

  • Citation: Fleming, Genie M.; Wunderle, Jr., Joseph M.; Ewert, David N.; O'Brien, Joseph J. 2014. Estimating plant biomass in early-successional subtropical vegetation using a visual obstruction technique. Applied Vegetation Science, 17: 356-366.
  • Posted Date: August 14, 2014
  • Modified Date: February 4, 2016
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