Estimating aboveground biomass of broadleaved woody plants in the understory of Florida Keys pine forests

Sah, Jay P.; Ross, Michael S.; Koptur, Suzanne; Snyder, James R.

doi:10.1016/j.foreco.2004.07.059

Cited by 78 publications

(68 citation statements)

References 35 publications

(54 reference statements)

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“…Our study showed that the quadratic model and power model were most reliable for estimating organ and total biomass of the four shrub species. A quadratic equation is a common model used to estimate shrub biomass (Sah et al 2004;Foroughbakhch et al 2005), and our results are consistent with previous reports that the biomass of shrub populations can be well described with architectural variables (Foroughbakhch et al 2005). The quadratic model with D 2 was the best predictor of total biomass of L. chinense and G. jasminoides.…”

Section: Discussionsupporting

confidence: 91%

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Biomass equations for four shrub species in subtropical China

Huiqing

Liu

Zhu

et al. 2010

Journal of Forest Research

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Estimation of shrub biomass can provide more accurate estimates of forest biomass and carbon sequestration. We developed species-specific biomass regression models for four common shrub species, Chinese loropetal (Loropetalum chinense), white oak (Quercus fabri), chastetree (Vitex negundo var. cannabifolia), and Gardenia (Gardenia jasminoides), in southeast China. The objective of this study was to derive appropriate regression equations for estimation of shrub biomass. The results showed that the power model and the quadratic model are the most appropriate forms of equation. CA (canopy area, m 2 ) as the sole independent variable was a good predictor of leaf biomass. D 2 H, where D is the basal diameter (cm) and H is the shrub height (cm), is a good predictor of branch and root biomass, except for V. negundo var. cannabifolia and the root biomass of L. chinense. For total biomass, D 2 is the best variable for estimation of L. chinense and G. jasminoides, and D 2 H is the best variable for estimation of Q. fabri and V. negundo var. cannabifolia. Although variables D 2 , D 2 H, and H are the preferred predictors for biomass estimation, CV (canopy projected volume, m 3 ) could be used alone to predict branch, root, and total biomass in shrub species with acceptable accuracy and precision.

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Section: Discussionsupporting

confidence: 91%

“…This suggests that CA is the best descriptor for estimation of foliar biomass. CA as the single independent variable in biomass regression has also been recognized by others (Paton et al 1998(Paton et al , 2002Sah et al 2004). A previous study indicated that leaf biomass depends on stand factors (Satoo and Madgewick 1982).…”

Section: Regression Parameter Analysismentioning

confidence: 69%

Biomass equations for four shrub species in subtropical China

Huiqing

Liu

Zhu

et al. 2010

Journal of Forest Research

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“…densa Little and Dorman) is the dominant woody species and sole canopy tree in pine rocklands of the Lower Florida Keys. These communities support a diverse subcanopy of West Indian hardwoods and palms, and a variety of endemic herbs that are alternately encouraged or held back by fire (Noss et al 1995;Sah et al 2004). Pine rocklands once covered a vast contiguous area of southern Florida of over 75,000 ha, but fire suppression and urbanization during the 20th Century have fragmented and reduced the original range by 90% (Doren et al 1993;O'Brien 1998).…”

Section: Introductionmentioning

confidence: 99%

The Dendrochronology of Pinus elliottii in the Lower Florida Keys: Chronology Development and Climate Response

Harley¹,

Grissino-Mayer²,

Horn³

2011

Tree-Ring Research

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South Florida slash pine (Pinus elliottii var. densa) is the southernmost pine species in the United States and the foundation species of the globally endangered pine rockland communities in south Florida. To test if slash pine produces annual growth rings in the Lower Florida Keys, we counted the number of rings on samples collected from the North Big Pine Key site (NBP), which contained a fire scar from a known wildfire and a known date for hurricane-induced tree mortality (2006 or 2007). In addition, a crossdated tree-ring chronology (1871-2009) was developed from living trees and remnant wood found at the site and compared to divisional climate data to determine how the regional climate regime influences radial growth. Our analyses demonstrated that slash pine forms anatomically distinct, annual growth rings with the consistent year-to-year variability necessary for rigorous dendrochronological studies. Response-function and correlation analysis showed that annual growth of slash pine at NBP is primarily influenced by water availability during the growing season. However, no significant correlations were found between tree growth and the Atlantic Multidecadal Oscillation or the El Niñ o-Southern Oscillation. Our study reveals the potential of producing high-quality dendrochronological data in southern Florida from slash pine, which should prove useful in further studies on fire history and tree phenology and for assessing the projected impacts of impending climate change on the fragile pine rockland community.

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“…The twenty shrub species were divided, by morphology characteristics, to tree-like shrubs that have a single-stem and apparent trunk [10], and typical shrubs that are multi-stemmed, low-branching and not obvious in trunk [14]. Four tree species were small individual trees and defined as saplings.…”

Section: Species Selectionmentioning

confidence: 99%

“…Forests have gained wide attention in the past decades because of their enormous capacity for carbon storage in the global carbon pool [7][8][9]. Understory species in the forest, composed of saplings and shrubs, serve as important components of forest ecosystems [10], play important roles in forest structures and functions [11], maintain species diversity, promote forest regeneration and improve forest production [10,[12][13][14][15]. Compared with the biomass of overstory trees species, the biomass of saplings and shrubs is often neglected because of a lack of measurement technique and the difficulty in their assessment [16].…”

Section: Introductionmentioning

confidence: 99%

Biomass Equations for 24 Understory Species in Coniferous and Broadleaved Mixed Forests in Northeastern China

Zhang

et al. 2016

Preprint

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Understory plants are important components of forest ecosystem productivity and diversity. Compared to biomass models of overstory canopy trees, few are available for understory saplings and shrubs and therefore their roles in estimation of forest carbon pools are often ignored. In this study, we harvested 24 understory species including 4 saplings, 9 tree-like shrubs and 11 typical shrubs in coniferous and broadleaved mixed forest in northeastern China and developed the best fit allometric equations of above-and below-ground and total biomass by species-specific or multispecies using morphological measurements of basal diameter, height and crown area as independent variables. The result showed that single basal diameter, height or crown area had good explanatory power for both species-specific and multispecies (p<0.001). The best-fit models included only basal diameter in sapling and tree-like shrubs, and combinations of crown area, height, and basal diameter in typical shrubs. The logarithmic model was most desired among the 4 model forms of linear, quadratic, multiple linear and logarithmic, for species-specific and multispecies. The models we developed should help the estimation of forest ecosystem carbon stocks, especially for belowground component, and provide tools for quantification of individual species biomass of understory plants.

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Estimating aboveground biomass of broadleaved woody plants in the understory of Florida Keys pine forests

Cited by 78 publications

References 35 publications

Biomass equations for four shrub species in subtropical China

Biomass equations for four shrub species in subtropical China

The Dendrochronology of Pinus elliottii in the Lower Florida Keys: Chronology Development and Climate Response

Biomass Equations for 24 Understory Species in Coniferous and Broadleaved Mixed Forests in Northeastern China

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