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Title: Allometric Models for Predicting Aboveground Biomass and Carbon Stock of Tropical Perennial C 4 Grasses in Hawaii

Abstract

Biomass is a promising renewable energy option that provides a more environmentally sustainable alternative to fossil resources by reducing the net flux of greenhouse gasses to the atmosphere. Yet, allometric models that allow the prediction of aboveground biomass (AGB), biomass carbon (C) stock non-destructively have not yet been developed for tropical perennial C 4 grasses currently under consideration as potential bioenergy feedstock in Hawaii and other subtropical and tropical locations. The objectives of this study were to develop optimal allometric relationships and site-specific models to predict AGB, biomass C stock of napiergrass, energycane, and sugarcane under cultivation practices for renewable energy and validate these site-specific models against independent data sets generated from sites with widely different environments. Several allometric models were developed for each species from data at a low elevation field on the island of Maui, Hawaii. A simple power model with stalk diameter (D) was best related to AGB and biomass C stock for napiergrass, energycane, and sugarcane, (R 2 = 0.98, 0.96, and 0.97, respectively). The models were then tested against data collected from independent fields across an environmental gradient. For all crops, the models over-predicted AGB in plants with lower stalk D, but AGB was under-predictedmore » in plants with higher stalk D. The models using stalk D were better for biomass prediction compared to dewlap H (Height from the base cut to most recently exposed leaf dewlap) models, which showed weak validation performance. Although stalk D model performed better, however, the mean square error (MSE)-systematic was ranged from 23 to 43 % of MSE for all crops. A strong relationship between model coefficient and rainfall was existed, although these were irrigated systems; suggesting a simple site-specific coefficient modulator for rainfall to reduce systematic errors in water-limited areas. These allometric equations provide a tool for farmers in the tropics to estimate perennial C4 grass biomass and C stock during decision-making for land management and as an environmental sustainability indicator within a renewable energy system.« less

Authors:
 [1];  [1];  [2];  [3];  [4];  [5]
  1. Univ. of Hawaii at Manoa, Honolulu, HI (United States). Dept. of Tropical Plant and Soil Sciences
  2. US Dept. of Agriculture (USDA)., Temple, TX (United States). Agricultural Research Service, Grassland Soil and Water Research Lab.
  3. Texas A&M Univ., Temple, TX (United States). AgriLife Research, Blackland Research and Extension Center
  4. Hawaiian Commercial & Sugar Company, Puunene, HI (United States)
  5. Univ. of Hawaii at Manoa, Honolulu, HI (United States). Dept. of Natural Resources and Environmental Management
Publication Date:
Research Org.:
Univ. of Hawaii, Honolulu, HI (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE); US Department of the Navy, Office of Naval Research (ONR); USDA
OSTI Identifier:
1368351
Grant/Contract Number:  
FG36-08GO88037; N00014-12-1-0496; 2012-10006-19455; 60-0202-3-001
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Frontiers in Plant Science
Additional Journal Information:
Journal Volume: 8; Journal ID: ISSN 1664-462X
Publisher:
Frontiers Research Foundation
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; aboveground biomass; carbon sequestration; allometric models; C4 grasses; site-specific model; ratoon harvest

Citation Formats

Youkhana, Adel H., Ogoshi, Richard M., Kiniry, James R., Meki, Manyowa N., Nakahata, Mae H., and Crow, Susan E. Allometric Models for Predicting Aboveground Biomass and Carbon Stock of Tropical Perennial C4 Grasses in Hawaii. United States: N. p., 2017. Web. doi:10.3389/fpls.2017.00650.
Youkhana, Adel H., Ogoshi, Richard M., Kiniry, James R., Meki, Manyowa N., Nakahata, Mae H., & Crow, Susan E. Allometric Models for Predicting Aboveground Biomass and Carbon Stock of Tropical Perennial C4 Grasses in Hawaii. United States. doi:10.3389/fpls.2017.00650.
Youkhana, Adel H., Ogoshi, Richard M., Kiniry, James R., Meki, Manyowa N., Nakahata, Mae H., and Crow, Susan E. Tue . "Allometric Models for Predicting Aboveground Biomass and Carbon Stock of Tropical Perennial C4 Grasses in Hawaii". United States. doi:10.3389/fpls.2017.00650. https://www.osti.gov/servlets/purl/1368351.
@article{osti_1368351,
title = {Allometric Models for Predicting Aboveground Biomass and Carbon Stock of Tropical Perennial C4 Grasses in Hawaii},
author = {Youkhana, Adel H. and Ogoshi, Richard M. and Kiniry, James R. and Meki, Manyowa N. and Nakahata, Mae H. and Crow, Susan E.},
abstractNote = {Biomass is a promising renewable energy option that provides a more environmentally sustainable alternative to fossil resources by reducing the net flux of greenhouse gasses to the atmosphere. Yet, allometric models that allow the prediction of aboveground biomass (AGB), biomass carbon (C) stock non-destructively have not yet been developed for tropical perennial C4 grasses currently under consideration as potential bioenergy feedstock in Hawaii and other subtropical and tropical locations. The objectives of this study were to develop optimal allometric relationships and site-specific models to predict AGB, biomass C stock of napiergrass, energycane, and sugarcane under cultivation practices for renewable energy and validate these site-specific models against independent data sets generated from sites with widely different environments. Several allometric models were developed for each species from data at a low elevation field on the island of Maui, Hawaii. A simple power model with stalk diameter (D) was best related to AGB and biomass C stock for napiergrass, energycane, and sugarcane, (R2 = 0.98, 0.96, and 0.97, respectively). The models were then tested against data collected from independent fields across an environmental gradient. For all crops, the models over-predicted AGB in plants with lower stalk D, but AGB was under-predicted in plants with higher stalk D. The models using stalk D were better for biomass prediction compared to dewlap H (Height from the base cut to most recently exposed leaf dewlap) models, which showed weak validation performance. Although stalk D model performed better, however, the mean square error (MSE)-systematic was ranged from 23 to 43 % of MSE for all crops. A strong relationship between model coefficient and rainfall was existed, although these were irrigated systems; suggesting a simple site-specific coefficient modulator for rainfall to reduce systematic errors in water-limited areas. These allometric equations provide a tool for farmers in the tropics to estimate perennial C4 grass biomass and C stock during decision-making for land management and as an environmental sustainability indicator within a renewable energy system.},
doi = {10.3389/fpls.2017.00650},
journal = {Frontiers in Plant Science},
number = ,
volume = 8,
place = {United States},
year = {Tue May 02 00:00:00 EDT 2017},
month = {Tue May 02 00:00:00 EDT 2017}
}

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Works referenced in this record:

How biotech can transform biofuels
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  • Lynd, Lee R.; Laser, Mark S.; Bransby, David
  • Nature Biotechnology, Vol. 26, Issue 2, p. 169-172
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