Matang Mangrove Forest Reserve (MMFR) in Peninsular Malaysia is under systematic management since 1902 and still considered as the best managed mangrove forest in the world. The present study on silvimetrics assessed the ongoing MMFR forest management, which includes a first thinning after 15 years, a second thinning after 20 years and clear-felling of 30-year old forest blocks, for its efficiency and productivity in comparison to natural mangroves. The estimated tree structural parameters (e.g. density, frequency) from three different-aged mangrove blocks of fifteen (MF15), twenty (MF20), and thirty (MF30) years old indicated that Bruguiera and Excoecaria spp. did not constitute a significant proportion of the vegetation (<5%), and hence the results focused majorly on Rhizophora apiculata. The density of R. apiculata at MF15, MF20 and MF30 was 4,331, 2,753 and 1,767 stems ha−1, respectively. In relation to ongoing practices of the artificial thinnings at MMFR, the present study suggests that the first thinning could be made earlier to limit the loss of exploitable wood due to natural thinning. In fact, the initial density at MF15 was expected to drop down from 6,726 to 1,858 trees ha−1 before the first thinning. Therefore the trees likely to qualify for natural thinning, though having a smaller stem diameter, should be exploited for domestic/commercial purposes at an earlier stage. The clear-felling block (MF30) with a maximum stem diameter of 30 cm was estimated to yield 372 t ha−1 of the above-ground biomass and suggests that the mangrove management based on a 30-year rotation is appropriate for the MMFR. Since Matang is the only iconic site that practicing sustainable wood production, it could be an exemplary to other mangrove locations for their improved management.

/pdf/is-matang-mangrove-forest-in-malaysia-sustainably-353td58gsq.pdf

Is Matang Mangrove Forest in Malaysia sustainably rejuvenating after more than a century of conservation and harvesting management

https://www.srs.fs.usda.gov/pubs/ja/2015/ja_2015_trettin_001.pdf

Carbon stocks of mangroves within the Zambezi River Delta, Mozambique

Improving the precision of forest biomass estimates requires prioritizing the different sources of errors. In a tropical moist forest in central Africa, the choice of the allometric equation was found to be the main source of error.
 When estimating the forest biomass at the landscape level using forest inventory data and allometric models, there is a chain of propagation of errors including the measurement errors, the models' prediction error, the error due to the model choice, and the sampling error. This study aims at comparing the contributions of these different sources of error to the total error, to prioritize them, and improve the precision of biomass estimates. Using a 9-ha permanent sample plot in a moist forest near Kisangani in the Democratic Republic of Congo and seven competing allometric models, we estimated the contributions of the different sources of error to the total error of the per hectare biomass estimate, for plot sizes ranging from 0.04 to 1 ha. When there was no a priori on which model being the best and for 1-ha plots, the error due to the model choice was the largest source of error (76 % of the total error). Using weights to combine the predictions of the different models into a single ensemble prediction strongly reduced this error. Collecting training data sets on tree biomass at many sites would be needed to improve the precision of forest biomass estimates in central Africa.

/pdf/reducing-the-error-in-biomass-estimates-strongly-depends-on-whqge4bgl4.pdf

Reducing the error in biomass estimates strongly depends on model selection

Blue Carbon Ecosystems (BCEs) help mitigate and adapt to climate change but their integration into policy, such as Nationally Determined Contributions (NDCs), remains underdeveloped. Most BCE conservation requires community engagement, hence community-scale projects must be nested within the implementation of NDCs without compromising livelihoods or social justice. Thirty-three experts, drawn from academia, project development and policy, each developed ten key questions for consideration on how to achieve this. These questions were distilled into ten themes, ranked in order of importance, giving three broad categories of people, policy & finance, and science & technology. Critical considerations for success include the need for genuine participation by communities, inclusive project governance, integration of local work into national policies and practices, sustaining livelihoods and income (for example through the voluntary carbon market and/or national Payment for Ecosystem Services and other types of financial compensation schemes) and simplification of carbon accounting and verification methodologies to lower barriers to entry. 

/pdf/integrating-blue-how-do-we-make-nationally-determined-utfju6z2.pdf

Integrating blue: How do we make nationally determined contributions work for both blue carbon and local coastal communities?

A review of studies on belowground biomass (BGB) of mangroves revealed that procedures for excavation and determination of dry weight are insufficiently documented. The main objective of this study was therefore to describe procedures for quantification of tree BGB for Avicennia marina (Forssk.), Sonneratia alba J. Smith and Rhizophora mucronata Lam. The study covered four sites in Tanzania where 30 trees were sampled (10 for each species). A new root sampling procedure applied for A. marina and S. alba seemed to work adequately. Dry to fresh weight ratios (DF-ratios) varied between tree species, between tree sizes and between root components. Therefore, for each tree species, tree- and root component-specific DF-ratios were applied for dry weight determination. For A. marina and S. alba trees, a significant proportion of total tree BGB is stored in the root crown (34 and 10 % respectively). Future studies should therefore ensure inclusion of root crown when accounting for total tree BGB. Tests of previously developed models on our data revealed large prediction errors, partly due to differences in site conditions and partly due to incomprehensive excavation procedures applied when these models were developed. Local tree BGB models for mangroves should therefore be developed.

Procedures for quantification of belowground biomass of three mangrove tree species

https://www.pure.ed.ac.uk/ws/files/12710830/1_s2.0_S0378112713006610_main.pdf

Propagating uncertainty to estimates of above-ground biomass for Kenyan mangroves: A scaling procedure from tree to landscape level

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Propagating uncertainty to estimates of above-ground biomass for Kenyan mangroves: A scaling procedure from tree to landscape level