Carbon Stock and Sequestration Valuation in a Mixed Dipterocarp Forest of Malaysia

Matthew, Nitanan Koshy; Shuib, Ahmad; Muhammad, Ismail; Eusop, Muhammad Ekhzarizal Mohamed; Ramachandran, S.; Afandi, Syamsul Herman Mohammad; Samdin, Zaiton

doi:10.17576/jsm-2018-4703-04

Cited by 15 publications

(3 citation statements)

References 25 publications

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“…In Malaysia, Raihan et al [112] reported higher AGB-Cstocks than BG-Cstocks. In support of the findings of this study, Omar et al [113] and Matthew et al [114] found higher contents of aboveground carbon than belowground carbon, with net differences of at least 60%. A study in Zambia by Pelletier et al [101] affirmed that the biomass gains and carbon sink were concentrated in several dominant species, including the Fabaceae, which is a subfamily of Caesalpinioideae, although some dominant species showed threats of overexploitation.…”

Section: Carbon Stocks and Other Variables Associated With Forest Bio...supporting

confidence: 88%

“…In Malaysia, Raihan et al [112] reported higher AGB-Cstocks than BG-Cstocks. In support of the findings of this study, Omar et al [113] and Matthew et al [114] found higher contents of aboveground carbon than belowground carbon, with net differences of at least 60%. In contrast to the findings of this study, Xu et al [111] reported higher carbon stocks belowground when compared with the aboveground content.…”

Section: Carbon Stocks and Other Variables Associated With Forest Bio...supporting

confidence: 88%

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The Dynamics and Potential of Carbon Stocks as an Indicator of Sustainable Development for Forest Bioeconomy in Ghana

Nyarko,

Nwaogu,

Diagi

et al. 2024

Forests

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Sustainable forest bioeconomy (SFB), as a multidimensional approach for establishing mutual benefits between forest ecosystems, the environment, the economy, and humans, is a nature-based solution for a promising future. The study aims to evaluate the potential of carbon stocks (Cstocks) and variability for SFB. It is hypothesized that the decrease in Cstocks is related to an increase in population and agriculture, which caused a decrease in forest area and growing stock and consequently affected SFB. Primary and secondary data were collected from the field, national, and international databases, and analyzed using some statistical and geospatial software packages including IBM SPSS 29.0, CANOCO 5.0, and ArcGIS 10.5. The results revealed that large forest areas were converted to arable lands between 2000 and 2020. Across the forest zones, the aboveground and belowground Cstocks varied significantly, with the aboveground biomass being higher than the belowground biomass. The main drivers of Cstocks were politics and governance (57%), population growth (50%), soil degradation practices (50%), and socio-cultural beliefs (45%). Cstocks had significant negative correlation with population growth, carbon emissions, forest growing stock, forest loss, and the use of forest for biofuel. Evergreen forest zones (rainforest and moist) had more Cstocks than the moist deciduous and swamp/mangrove forests. The study demonstrated that the variability in Cstocks over the last three decades is attributed to an increase in population and agriculture, but Cstocks variability between the forest-vegetation belts could be better explained by differences in trees abundance than population. The study also revealed that the increase in Cstocks contributed to the realization of many SDGs, especially SDG 1, 2, 3, 6, 7, 11, 12, 13, and 15, which in turn support a sustainable forest bioeconomy. Future study is necessary to evaluate Cstocks in individual tree species, biodiversity, and other forest ecosystem services to promote SFB in the country.

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Section: Carbon Stocks and Other Variables Associated With Forest Bio...supporting

confidence: 88%

“…In Malaysia, Raihan et al [112] reported higher AGB-Cstocks than BG-Cstocks. In support of the findings of this study, Omar et al [113] and Matthew et al [114] found higher contents of aboveground carbon than belowground carbon, with net differences of at least 60%. In contrast to the findings of this study, Xu et al [111] reported higher carbon stocks belowground when compared with the aboveground content.…”

Section: Carbon Stocks and Other Variables Associated With Forest Bio...supporting

confidence: 88%

The Dynamics and Potential of Carbon Stocks as an Indicator of Sustainable Development for Forest Bioeconomy in Ghana

Nyarko,

Nwaogu,

Diagi

et al. 2024

Forests

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“…It was estimated that AGC in Endau Rompin National Park in Johor wat at an average of 281 Mg C ha −1 [68]. Assuming that forest condition in this area is similar to the Greater National Park, this study estimated the AGC in this kind of forest was at 203.61 Mg C ha −1 (Table 12-A), which is lower than that was estimated by them.…”

Section: Statistics Extracted From the Agc Mapmentioning

confidence: 58%

Production of High-Resolution Map of Biomass Carbon over Forests in Malaysia Estimated using Aboveground Carbon Density Indicator (ACDI) and a Collection of 12 Years Inventory Data

Omar,

Misman,

Linggok

et al. 2023

Preprint

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The accurate estimation of biomass carbon in forests is of paramount importance for effective forest management and mitigating climate change. This study presents a novel approach to produce a high-resolution map of biomass carbon over forests in Malaysia using the Aboveground Carbon Density Indicator (ACDI) and a comprehensive collection of 12 years of inventory data, i.e., from 2012 to 2023. The ACDI was derived based on several vegetation indices (VIs) that were produced from the original Landsat images to indicate the level of aboveground biomass carbon (AGC) stock in the forested areas. The VIs includes Normalised Difference Vegetation Index (NDVI), Normalised Burn Ratio (NBR), Shadow Index (SI), Soil-Adjusted Vegetation Index (SAVI), Iron Oxide Index (IO), Modified Normalised Difference Water Index (NDWI), and Enhanced Vegetation Index (EVI). The ACDI was then integrated with ground-based measurements, and serves as a robust indicator for estimating AGC. This calculation was conducted on Google Earth Engine (GEE) platform to match the date of field observation with the satellite imagery datasets. The production of seamless mosaic of the latest date of Landsat imagery and the forest type classification were also performed on GEE. The forested areas were classified into three major types, which are dry inland forest, mangrove forest, and peat swamp forest. Results indicated significant spatial variations in AGC across Malaysia's forests. The derived AGC prediction models based on the ACDI varied among the forest types. Based on the estimates, a 30-metre resolution, wall-to-wall map of AGC across the entire forested region of Malaysia has been created. The ACDI was calibrated and validated using a separate validation plots dataset to ensure the accuracy of the AGC estimates. The total AGC in all types of forests in Malaysia was estimated at 3.0 billion Mg C with an attainable accuracy of about 80%. These estimates were also divided into categories and reported to the AGC at the state level. This high-resolution map provides essential information for various stakeholders, with critical implications for carbon sequestration efforts, conservation priorities, and sustainable forest management. The presented methodology not only showcases the value of combining advanced remote sensing techniques with long-term inventory data but also underscores the potential for similar approaches in other tropical forest regions globally. Ultimately, this study contributes to the understanding of carbon dynamics in Malaysian forests and promotes effective strategies for mitigating climate change through better-informed forest conservation and management practices.

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Dynamic impacts of energy use, agricultural land expansion, and deforestation on CO2 emissions in Malaysia

et al. 2022

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This study empirically investigates the nexus among energy use, agricultural land expansion, deforestation, and carbon dioxide (CO 2 ) emissions in Malaysia. Time series data from 1990 to 2019 were utilized using the bounds testing (ARDL) approach followed by the Dynamic Ordinary Least Squares (DOLS) method. The DOLS estimate findings show that the energy usage coefficient is positive and significant with CO 2 emissions, indicating a 1% increase in energy consumption is related to a 0.91% rise in CO 2 emissions. In addition, the coefficient of agricultural land is positive, which indicates that agricultural land expansion by 1% is associated with an increase in CO 2 emissions by 0.84% in the long run. Furthermore, the forested area coefficient is negative, which means that decreasing 1% of the wooded area (i.e., deforestation) has a long-term effect of 5.41% increased CO 2 emissions. Moreover, the pairwise Granger causality test results show bidirectional causality between deforestation and energy use; and unidirectional causality from energy use to CO 2 emissions, agricultural land expansion to CO 2 emissions, deforestation to CO 2 emissions, agricultural land expansion to energy use, and deforestation to agricultural land expansion in Malaysia. The empirical findings reveal that increased energy use, agricultural land expansion, and deforestation have a negative impact on environmental quality in Malaysia. Thus, the effective implementation of policy measures to promote renewable energy, climate-smart agriculture, and sustainable management of forest ecosystems could be useful for reducing environmental degradation in Malaysia.

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Carbon Stock and Sequestration Valuation in a Mixed Dipterocarp Forest of Malaysia

Cited by 15 publications

References 25 publications

The Dynamics and Potential of Carbon Stocks as an Indicator of Sustainable Development for Forest Bioeconomy in Ghana

The Dynamics and Potential of Carbon Stocks as an Indicator of Sustainable Development for Forest Bioeconomy in Ghana

Production of High-Resolution Map of Biomass Carbon over Forests in Malaysia Estimated using Aboveground Carbon Density Indicator (ACDI) and a Collection of 12 Years Inventory Data

Dynamic impacts of energy use, agricultural land expansion, and deforestation on CO2 emissions in Malaysia

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