Biomass and Carbon Stocks of Sofala Bay Mangrove Forests

Sitoe, Almeida; Mandlate, Luís Júnior Comissário; Guedes, Benard S.

doi:10.3390/f5081967

Cited by 106 publications

(79 citation statements)

References 19 publications

(38 reference statements)

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“…However, there was no significant difference in tree components biomass estimation, with the exception of roots, among all the available allometric equations. In some cases the power function failed, and then transformed models were needed to develop significant allometric equations for different tree species, locations, and specific-components [7,25,27,28,[42][43][44][45][46][47].…”

Section: Discussionmentioning

confidence: 99%

Biomass, Carbon and Nutrient Storage in a 30-Year-Old Chinese Cork Oak (Quercus Variabilis) Forest on the South Slope of the Qinling Mountains, China

Cao

Chen

2015

Forests

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Chinese cork oak (Quercus variabilis) forests are protected on a large-scale under the Natural Forest Protection (NFP) program in China to improve the ecological environment. However, information about carbon (C) storage to increase C sequestration and sustainable management is lacking. Biomass, C, nitrogen (N) and phosphorus (P) storage of trees, shrubs, herb, litter and soil (0-100 cm) were determined from destructive tree sampling and plot level investigation in approximately 30-year old Chinese cork oak forests on the south slope of the Qinling Mountains. There was no significant difference in tree components' biomass estimation, with the exception of roots, among the available allometric equations developed from this study site and other previous study sites. Leaves had the highest C, N and P concentrations among tree components and stems were the major compartments for tree biomass, C, N and P storage. In contrast to finding no difference in N concentrations along the whole soil profile, higher C and P concentrations were observed in the upper 0-10 cm of soil than in the deeper soil layers. The ecosystem C, N, and P storage was 163.76, 18.54 and 2.50 t ha −1 , respectively. Soil (0-100 cm) contained the largest amount of C, N and P storage, accounting for 61.76%, 92.78% and 99.72% of the total ecosystem, followed by 36.14%, 6.03% and 0.23% for trees, and 2.10%, 1.19% and 0.03% for shrubs, herbs and litter, respectively. The equations accurately estimate ecosystem biomass, and the OPEN ACCESSForests 2015, 6 1240 knowledge of the distribution of C, N and P storage will contribute to increased C sequestration and sustainable management of Chinese cork oak forests under the NFP program.

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Section: Discussionmentioning

confidence: 99%

Biomass, Carbon and Nutrient Storage in a 30-Year-Old Chinese Cork Oak (Quercus Variabilis) Forest on the South Slope of the Qinling Mountains, China

Cao

Chen

2015

Forests

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“…A review by Komiyama et al (2008) identified 13 species-specific and two common (i.e., multi-species) models for prediction of aboveground biomass of mangroves, while nine speciesspecific models and one common model were identified for belowground biomass. Additional studies on mangroves that developed models for prediction of biomass not present in this review also exist (e.g., Kairo et al 2009;Kauffman and Donato 2012;Sitoe et al 2014). With the exception of the models developed by Kairo et al (2009) in Kenya and Sitoe et al (2014) in Mozambique, most of the models have been developed for mangroves in Asia.…”

Section: Introductionmentioning

confidence: 99%

Above- and belowground tree biomass models for three mangrove species in Tanzania: a nonlinear mixed effects modelling approach

Njana

Bollandsås

Eid

et al. 2015

Annals of Forest Science

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Abstract& Key message Tested on data from Tanzania, both existing species-specific and common biomass models developed elsewhere revealed statistically significant large prediction errors. Species-specific and common above-and belowground biomass models for three mangrove species were therefore developed. The species-specific models fitted better to data than the common models. The former models are recommended for accurate estimation of biomass stored in mangrove forests of Tanzania. & Context Mangroves are essential for climate change mitigation through carbon storage and sequestration. Biomass models are important tools for quantifying biomass and carbon stock. While numerous aboveground biomass models exist, very few studies have focused on belowground biomass, and among these, mangroves of Africa are hardly or not represented. & Aims The aims of the study were to develop above-and belowground biomass models and to evaluate the predictive accuracy of existing aboveground biomass models developed for mangroves in other regions and neighboring countries when applied on data from Tanzania. & Methods Data was collected through destructive sampling of 120 trees (aboveground biomass), among these 30 trees were sampled for belowground biomass. The data originated from four sites along the Tanzanian coastline covering three dominant species: Avicennia marina (Forssk.) Vierh, Sonneratia alba J. Smith, and Rhizophora mucronata Lam. The biomass models were developed through mixed modelling leading to fixed effects/common models and random effects/speciesspecific models. & Results Both the above-and belowground biomass models improved when random effects (species) were considered. Inclusion of total tree height as predictor variable, in addition to diameter at breast height alone, further improved the model predictive accuracy. The tests of existing models from other regions on our data generally showed large and significant prediction errors for aboveground tree biomass. Handling Editor: Shuqing ZhaoContribution of co-authors: Njana: Took part in design of research, responsible for data collection and preparation, and for data analysis and manuscript development. O. M. Bollandsås: Supervising the work including providing technical guidance on data analysis and commenting on the manuscript. T. Eid: Took part in design of the research, supervising the work, commenting, and manuscript development. E. Zahabu: Supervising the work and commenting on the manuscript. R. Malimbwi: Coordinating the design of research project and commenting on the manuscript.

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“…ha -1 (Mandarin et al, 2016). This difference is thought to be caused by various factors, such as mangrove species composition, mangrove density, mangrove conservation level, and sediment conditions of mangrove habitat (Sitoe et al, 2014).…”

Section: Biomass Carbon Stock and Co2mentioning

confidence: 99%

Estimasi Stok Karbon Mangrove (Aboveground) Di Tanjung Api-Api, Sumatera Selatan

Purwiyanto

Agustriani

2018

J. Ilmu dan Teknologi Kelautan Tropis

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The rapid development of infrastructure that occurred in the area of Tanjung Api-api resulted in changes in the function of mangrove land along the coast. Directly, this also impacts on the sustainability of ecological functions of mangroves. This study aims to estimate changes (prior to infrastructure development and current conditions) of aboveground carbon reserves stored in mangrove forests in Tanjung Api-api. This research was conducted in June-August 2016. Carbon stocks in mangrove along Tanjung Api-api were conducted by surveying the mangrove species and density, and then calculating biomass and carbon stock using allometric equation. While changes in carbon stocks are calculated by converting changes in mangrove area before and after infrastructure development to carbon stock value. The change of mangrove area was done by doing image data processing in 2005 and 2016. The results showed that mangrove Tanjung Api-api has 9 species of mangrove with total mangrove aboveground biomass of Tanjung Api-api is 1.

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Biomass and Carbon Stocks of Sofala Bay Mangrove Forests

Cited by 106 publications

References 19 publications

Biomass, Carbon and Nutrient Storage in a 30-Year-Old Chinese Cork Oak (Quercus Variabilis) Forest on the South Slope of the Qinling Mountains, China

Biomass, Carbon and Nutrient Storage in a 30-Year-Old Chinese Cork Oak (Quercus Variabilis) Forest on the South Slope of the Qinling Mountains, China

Above- and belowground tree biomass models for three mangrove species in Tanzania: a nonlinear mixed effects modelling approach

Estimasi Stok Karbon Mangrove (Aboveground) Di Tanjung Api-Api, Sumatera Selatan

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