Accurate estimation of tree and forest biomass is key to evaluating forest ecosystem functions and the global carbon cycle. Allometric equations that estimate tree biomass from a set of predictors, such as stem diameter and tree height, are commonly used. Most allometric equations are site specific, usually developed from a small number of trees harvested in a small area, and are either species specific or ignore interspecific differences in allometry. Due to lack of site-specific allometries, local equations are often applied to sites for which they were not originally developed (foreign sites), sometimes leading to large errors in biomass estimates. In this study, we developed generic allometric equations for aboveground biomass and component (stem, branch, leaf, and root) biomass using large, compiled data sets of 1203 harvested trees belonging to 102 species (60 deciduous angiosperm, 32 evergreen angiosperm, and 10 evergreen gymnosperm species) from 70 boreal, temperate, and subtropical natural forests in Japan. The best generic equations provided better biomass estimates than did local equations that were applied to foreign sites. The best generic equations included explanatory variables that represent interspecific differences in allometry in addition to stem diameter, reducing error by 4-12% compared to the generic equations that did not include the interspecific difference. Different explanatory variables were selected for different components. For aboveground and stem biomass, the best generic equations had species-specific wood specific gravity as an explanatory variable. For branch, leaf, and root biomass, the best equations had functional types (deciduous angiosperm, evergreen angiosperm, and evergreen gymnosperm) instead of functional traits (wood specific gravity or leaf mass per area), suggesting importance of other traits in addition to these traits, such as canopy and root architecture. Inclusion of tree height in addition to stem diameter improved the performance of the generic equation only for stem biomass and had no apparent effect on aboveground, branch, leaf, and root biomass at the site level. The development of a generic allometric equation taking account of interspecific differences is an effective approach for accurately estimating aboveground and component biomass in boreal, temperate, and subtropical natural forests.

Download full-text PDF

Source
http://dx.doi.org/10.1890/14-0175.1DOI Listing

Publication Analysis

Top Keywords

allometric equations
16
angiosperm evergreen
16
generic equations
16
generic allometric
12
biomass
12
natural forests
12
stem diameter
12
interspecific differences
12
branch leaf
12
leaf root
12

Similar Publications

Carbon reserves in coffee agroforestry in the Peruvian Amazon.

Front Plant Sci

December 2024

Centro de Investigación e Innovación para el Cambio Climático (CiiCC), Universidad Santo Tomás, Valdivia, Chile.

Introduction: Secondary forests and coffee cultivation systems with shade trees might have great potential for carbon sequestration as a means of climate change adaptation and mitigation. This study aimed to measure carbon stocks in coffee plantations under different managements and secondary forest systems in the Peruvian Amazon rainforest (San Martín Region).

Methods: The carbon stock in secondary forest trees was estimated using allometric equations, while carbon stocks in soil, herbaceous biomass, and leaf litter were determined through sampling and laboratory analysis.

View Article and Find Full Text PDF

In mammals, temporal and spatial variation in appendage sizes within and among species may be driven by variations in ambient temperature and allometric scaling. Here, we use two decades of morphological data on three rodent species distributed across vast latitudinal gradients in China to estimate temporal and spatial trends of tail, hind-foot, and ear lengths. Further, we test 14 climate variables to identify the critical drivers of these trends and use structural equation modeling (SEM) to analyze whether the effects of climate variables on the appendage lengths are direct or indirect, via effects on body length.

View Article and Find Full Text PDF

The analysis of how biological shape changes across ontogeny can provide us with valuable information on how species adapt behaviorally, physiologically, and ecologically. The white shark Carcharodon carcharias is one of the largest and most widely distributed apex predators globally, yet an understanding of ontogenetic changes in body shape and relative scaling of length and weight measures is limited, especially in relation to foraging ecology. Through analysis of a suite of shape-related metrics, we identified ontogenetic patterns of scaling throughout development.

View Article and Find Full Text PDF
Article Synopsis
  • The Montgomery equation (ME) links leaf area to leaf length and width, with its proportionality influenced by leaf shape, represented by the Montgomery parameter (MP).
  • A study sampled 840 leaves from six trees to analyze various leaf shape indices, discovering that larger trees have more ovate leaves while DBH did not significantly impact other indices like width to length ratio.
  • Results indicate that the MP (0.6466) remains consistent regardless of tree size, validating the ME for calculating leaf area at both the individual tree level and across multiple trees with minimal error when compared to a power-law equation.
View Article and Find Full Text PDF

Predicting the distribution, structure, and biomass of mangrove forests is an area of high research interest. Across the Atlantic East Pacific biogeographic region, three species are common and abundant members of local mangrove communities; , , and . Biomass prediction for these species has relied on two approaches: site-specific allometries based on the idea that environmental/climatic differences between sites drive growth differences, or the use of common allometric equations based on the idea that site driven differences are minimal.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!