Biomass equations for shrub species of Tamaulipan thornscrub of North-eastern Mexico

Návar, José; Méndez, Eduardo; Nájera, A.; Graciano, José Eduardo Alves; Dale, Virginia H.; Parresol, Bernard R.

doi:10.1016/j.jaridenv.2004.02.010

Cited by 78 publications

(75 citation statements)

References 25 publications

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“…For establishing regressions of shrub biomass, D, D 2 H, CA, and H are typically used as independent variables (Murray and Jacobson 1982;Vora 1988;Paton et al 2002;Návar et al 2004). In some cases, D is the best predictor (Clough and Scott 1989;Haase and Haase 1995;Paton et al 1998Paton et al , 2002.…”

Section: Regression Parameter Analysismentioning

confidence: 99%

“…However, compared with arboreal biomass, shrub biomass is often neglected in biomass research because of the lack of methodology and difficulty in calculation. Some research has gone into estimating the biomass of individual shrub species (Murray and Jacobson 1982;Frandsen 1983;Návar et al 2002;Paton et al 2002;Návar et al 2004). However, shrub biomass equations for the subtropical ecosystem in China have been little studied.…”

Section: Introductionmentioning

confidence: 99%

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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: Regression Parameter Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Biomass equations for four shrub species in subtropical China

Huiqing

Liu

Zhu

et al. 2010

Journal of Forest Research

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“…En effet, la biomasse aérienne des formations arbustives est en général, positivement corrélée avec le dhp (Navar et al 2004, Ali et al 2015. Cette activité n'est donc pas durable et peut aboutir à termes à une extinction localisée des espèces à bois dure, propices à la fabrication de charbon de bois (Ramaroson 2014).…”

Section: Article In Press -Early Viewunclassified

Effets de la production de charbon de bois sur les fourrés xérophiles, cas du plateau de Belomotse, Madagascar

Randriamalala

Rabeniala

Masezamana

2017

MCD

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Woody charcoal production is the main cause of dry forest degradation in the southwestern Madagascar. This paper analyses the effects of this practice on the diversity, represented by species richness, structure, species composition and regeneration of the xerophytic thickets on the Belomotse Plateau, Toliara II District. Eleven 400 m 2 plots were randomly sampled in woody charcoal production sites and 10 in control sites. Woody charcoal production has reduced xerophytic thickets mean height, density and mean diameter at breast height. It has also affected species composition while it has not affected xerophytic thicket diversity or its regeneration. However, its regeneration rate is low on both woody charcoal production and control sites. Decline of pollinator insect communities or exogenous causes such as increasing climate aridification or escalation of rainfall variability may explain this low regeneration rate. Woody charcoal production in semi arid region is an unsustainable activity. RÉSUMÉLa production de charbon de bois est l'une des causes de la dé-gradation des forêts sèches du Sud-Ouest malgache. Cet article analyse les effets de cette pratique sur (i) la diversité biologique représentée par la richesse spécifique, (ii) la structure et (iii) la composition floristique des fourrés xérophiles du plateau de Belomotse, Toliara II. Onze placeaux de 400 m 2 ont été sélectionnés de manière aléatoire dans des sites de production de charbon de bois et 10 dans des sites témoins. La production de charbon de bois affecte la composition floristique des fourrés xérophiles. De plus, elle réduit leur hauteur, densité et diamètre moyen à hauteur de poitrine (dhp). En revanche, elle n'affecte pas la richesse spéci-fique ni la régénération naturelle. Les taux de régénération sont cependant faibles, indiquant un mauvais recrutement au sein des peuplements végétaux qui occupent les fourrés xérophiles. Le dé-périssement des insectes pollinisateurs, ou des causes exogènes telles que l'aridification croissante et/ou l'accentuation de la variabilité interannuelle des précipitations peuvent expliquer cette mauvaise régénération. La production de charbon de bois en zone semi-aride n'est pas une activité durable.

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Section: Introductionmentioning

confidence: 99%

“…Different models and variable types have been used to predict shrub or tree species biomass [20,29]. Generally, power models, linear models (single and multiple) and logarithmic models have often been used to develop biomass equations [14,17,24,29,30]. Particularly power models, transformed into logarithmic models, may be one of the most commonly applied of all models as can be found in numerous studies in different ecosystem worldwide [17,25,[31][32][33][34].…”

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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Biomass equations for shrub species of Tamaulipan thornscrub of North-eastern Mexico

Cited by 78 publications

References 25 publications

Biomass equations for four shrub species in subtropical China

Biomass equations for four shrub species in subtropical China

Effets de la production de charbon de bois sur les fourrés xérophiles, cas du plateau de Belomotse, Madagascar

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

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