Structural development and productivity of replanted mangrove plantations in Kenya

Kairo, James Gitundu; Lang'at, Joseph Kipkorir Sigi; Dahdouh‐Guebas, Farid; Bosire, Jared O.; Karachi, M.

doi:10.1016/j.foreco.2008.01.031

Cited by 98 publications

(99 citation statements)

References 38 publications

(49 reference statements)

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“…The low carbon value found in our study could be explained by the low carbon content in the soil, supporting what has been reported by Kairo et al [43], which is that the difference in soil carbon stocks in different regions could be explained by the difference of carbon content across depth layers in each region. The high level of mangrove disturbance and degradation in our study area could be one of the reasons of the current state of carbon stock.…”

Section: Soil Carbonsupporting

confidence: 92%

“…For example, Kairo et al [43] [37], found R 2 = 0.98 in Asia. The difference may be due to the species-specific nature of the equations developed by Kairo et al [43] and Comley and McGuinness [39] and the inclusion of DBH and tree height together as predicting variables in the equations developed by Kridiborworn et al [44] and Komiyama et al [37]. In this study, we developed a general equation to represent the six species found in the study area and used only the DBH as predicting variable due to its easiness to measure.…”

Section: Allometric Equationmentioning

confidence: 99%

“…Soil carbon content was estimated in the laboratory using the Walkley-Black method [41]. The soil carbon (Mg·ha ) per sampled depth interval was calculated using Equation 8 as suggested by several authors [7,[41][42][43].…”

Section: Soil Samplingmentioning

confidence: 99%

“…with trees growing up to 45 cm DBH and 27 m height [29,30] is clearly different from our study site dominated by relatively small trees of Avicennia marina with a dominant height of 4 m. Fatoyinbo et al [29] also suggest that mangrove productivity, as expressed by tree biomass, would vary with the quality of the upstream sediment, therefore, taller mangrove trees are found in nutrient rich sediments of the Zambezi Delta and Limpopo estuary. Kairo et al [43] stated that biomass accumulation rate is mainly influenced by tree age, species, management regime, as well as the climate, while Fatoyinbo et al [29] consider the nutrient sediment and proximity to the water stream as additional factors of mangrove productivity. In central Kalimantan, Indonesia, Mudiyarso et al [14] reported around 1220 Mg·ha −1 carbon stock, which is considered high, and the reason being the presence of both deeper soils and larger trees.…”

Section: Total Carbon Stocksmentioning

confidence: 99%

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Biomass and Carbon Stocks of Sofala Bay Mangrove Forests

Sitoe

Mandlate

Guedes

2014

Forests

107

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Mangroves could be key ecosystems in strategies addressing the mitigation of climate changes through carbon storage. However, little is known regarding the carbon stocks of these ecosystems, particularly below-ground. This study was carried out in the mangrove forests of Sofala Bay, Central Mozambique, with the aim of quantifying carbon stocks of live and dead plant and soil components. The methods followed the procedures developed by the Center for International Forestry Research (CIFOR) for mangrove forests. In this study, we developed a general allometric equation to estimate individual tree biomass and soil carbon content (up to 100 cm depth). We estimated the carbon in the whole mangrove ecosystem of Sofala Bay, including dead trees, wood debris, herbaceous, pneumatophores, litter and soil. The general allometric equation for live trees derived was [Above-ground tree dry weight (kg) = 3.254 × exp(0.065 × DBH)], root mean square error (RMSE = 4.244), and coefficient of determination (R 2 = 0.89). The average total carbon storage of Sofala Bay mangrove was 218.5 Mg·ha , of which around 73% are stored in the soil. Mangrove conservation has the potential for REDD+ programs, especially in regions like Mozambique, which contains extensive mangrove areas with high deforestation and degradation rates.

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Section: Soil Carbonsupporting

confidence: 92%

Section: Allometric Equationmentioning

confidence: 99%

Section: Soil Samplingmentioning

confidence: 99%

Section: Total Carbon Stocksmentioning

confidence: 99%

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Biomass and Carbon Stocks of Sofala Bay Mangrove Forests

Sitoe

Mandlate

Guedes

2014

Forests

107

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“…Relevant regulating services and appropriate economic values for these were identified from the literature, including papers on local forests by members of the current team (e.g. Huxham et al, 2004;Huxham et al, 2007;Kairo et al, 2008) and from the technical specifications developed for Mikoko Pamoja, a mangrove carbon offsetting scheme based at Gazi (Pamoja, 2011).…”

Section: Socio-economic and Forest Status Analysesmentioning

confidence: 99%

Applying Climate Compatible Development and economic valuation to coastal management: A case study of Kenya's mangrove forests

Huxham

Emerton²,

Kairo

et al. 2015

Journal of Environmental Management

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Evaluation of mangrove structure and condition in two trans‐boundary areas in the Western Indian Ocean

Bandeira

Macamo

Kairo

et al. 2009

Aquatic Conservation

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ABSTRACT1. The structure, forest condition and regeneration status of nine mangrove forests in two trans-boundary areas of Mozambique bordering Tanzania and South Africa were studied. The main objective was to estimate the cutting intensity in the selected sites -Saco and Sangala in southern Mozambique; Mecu´fi, Pemba, Ibo, Luchete, Ulo in northern Mozambique, and Mngoji 1 and Mngoji 2 in Tanzania.2. A total of 135, 10 m Â 10 m quadrats were set in the outer, middle and lower parts of the mangrove forests at all sampling sites. Measurements included stem diameter at breast height (DBH) and height of adult trees (i.e. all trees with stem diameter more than 2.5 cm). Young trees (with stem diameter of less than 2.5 cm) were classified as juveniles. To assess forest condition, trees within the quadrat were classified into intact, partially cut, coppiced, die back and stump. Pole quality was appraised through the classification of the lead stem into three categories-straight, semi-straight and crooked poles.3. The results indicate different levels of exploitation with Mngoji 1 and Mngoji 2, the most degraded sites, having stump densities of 959 stumps ha À1 and 592 stumps ha À1, respectively. Most sites had mostly poles of inferior quality (crooked poles), but high densities of straight and semi-straight poles were found in Mngoji 1 (742 stems ha À1 ) and Saco (636 stems ha À1). 4. Natural regeneration was observed in most sites but not for all species, with adequate regeneration in Saco (14 766 saplings ha À1) and Mecu´fi (14 706 saplings ha À1 ), while low regeneration was recorded in Mngoji 1 and 2 (2212 saplings ha À1 and 4799 saplings ha À1 , respectively). 5. These results indicate the need for improved mangrove management and replanting especially in mangrove depleted conservation areas of southern Tanzania.

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Structural development and productivity of replanted mangrove plantations in Kenya

Cited by 98 publications

References 38 publications

Biomass and Carbon Stocks of Sofala Bay Mangrove Forests

Biomass and Carbon Stocks of Sofala Bay Mangrove Forests

Applying Climate Compatible Development and economic valuation to coastal management: A case study of Kenya's mangrove forests

Evaluation of mangrove structure and condition in two trans‐boundary areas in the Western Indian Ocean

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