Predictive modeling of regional carbon storage dynamics in response to land use/land cover changes: An InVEST-based analysis

Carbon stocks vary in reference to the models used, socioecological factors and agroforestry practices in Central Ethiopia

Abstract The carbon stock, biomass, and CO 2 emissions in woody species play crucial roles in understanding and managing ecosystems. Understanding these aspects is crucial for sustainable forest management, conservation, and mitigating the impact of woody species on global carbon dynamics and climate change. This study examined the nexus between carbon stock, biomass, and CO 2 emission of woody plant composition in disturbed and undisturbed areas in Southwestern Nigeria. The study involved the random establishment of plots in the disturbed and undisturbed areas and, in each plot, the woody plants were enumerated and identified to the species level. The results showed that total biomass (102.645 Mg ha -1 ), total carbon stock (51.323 Mg C ha -1 ), and total CO 2 emission (188.354 Mg C ha -1 ) values of tree species in undisturbed plots were higher than the values of total biomass (70.768 Mg ha- 1 ), total carbon stock (35.384 Mg C ha -1 ), and total CO 2 emission (129.859 Mg C ha -1 ) recorded in disturbed plots. The results also revealed that total biomass (0.123 Mg ha -1 ), total carbon stock (0.061 Mg C ha -1 ), and total CO 2 emission (0.225 Mg C ha -1 ) values of shrub species recorded in disturbed plots were higher than values of total biomass (0.067 Mg ha -1 ), total carbon stock (0.034 Mg C ha -1 ) and total CO 2 content (0.124 Mg C ha -1 ) recorded in undisturbed plots, respectively. The findings showed that in undisturbed and disturbed plots of shrubs, biomass, carbon and CO 2 emissions have a strong positive correlation of 1.000**. While biomass, carbon, and CO 2 emission have a very strong positive correlation (0.999**) in undisturbed plots of trees, the biomass, carbon, and CO 2 emission have moderate to strong positive correlations (0.458** to 0.974**) in disturbed plots of the tree. The study concluded that while biomass, carbon stock, and CO 2 emission values of tree species were higher in undisturbed plots than in disturbed plots, the biomass, carbon stock, and CO 2 emission values of shrub species were lower in undisturbed plots than in disturbed plots. It also concluded that the main purpose of establishing reserve forests is not totally achieved as human activities occurring in reserve forests still contribute to the increment of climate change. 

Nexus between carbon stock, biomass, and CO2 emission of woody species composition: evidence from Ise-Ekiti Forest Reserve, Southwestern Nigeria

This study investigates the relationship between above-ground biomass (AGB) and various vegetation indices in the tea plantations of Alipurduar District, West Bengal, India. The research was conducted in three major tea estates: Kumargram, Sankos and Newlands, using stratified random sampling across 36 plots. Field measurements of trees, shrubs and herbs were taken and AGB was estimated using allometric equations. Sentinel-2 satellite data was utilized to derive vegetation indices such as NDVI, GNDVI, SAVI, MSAVI, EVI-1, EVI-2, NDVIRE, RDVI, DVI, OSAVI and ARVI. The study found significant variation in AGB, ranging from 31.40 Mg ha-1 to 68.84 Mg ha-1, with an average of 47.22 Mg ha-1. Strong positive correlations were observed between AGB and indices like GNDVI (r=0.96) and EVI-2 (r=0.96), indicating their effectiveness in biomass prediction. The integration of remote sensing technologies enhances the scalability and precision of biomass estimation, providing valuable insights into the carbon storage potential and ecological health of tea plantations. These findings have implications for sustainable management and climate change mitigation in agroforestry systems. 

Relationship between Above-ground Biomass and Different Vegetation Indices of Tea Plantation of Alipurduar District, West Bengal, India

Jhau (Casuarina equisetifolia) is an evergreen tropical/subtropical invasive forest plantation growing on dune morphology at the longest sea beach of Cox's Bazar in Bangladesh. During contemporary times, raising climate catastrophes is viable to destroy the afforestation scheme of the plantation significantly, along with ethnographic interventions. So, in order to reach the research goal, the study considered assessing Jhau loss and its drivers of deforestation, health dynamics, biomass and carbon estimation, soil chemical elements, and wood pathological concentration. High-resolution remote-sensing satellite imagery WorldView 3/4 (i.e., spatial resolution 0.3 m) was used to delineate the Jhau patch for 2005, 2010, 2015, and 2023, aiming at change and loss analysis by applying GIS tools and techniques. Accordingly, the study assesses the dynamics of Jhau health by utilizing geophysical indices such as the Enhanced Vegetation Index (EVI) and Leaf Area Index (LAI) time series within the Google Earth Engine Platform using multi-spectral remotely sensed Landsat Mission Images spanning from 2005 to 2023. In addition, soil and wood samples from the study area were collected to explore soil chemical and pathological impacts, respectively, on deforestation. The outcome from the analysis demonstrates that coastal erosion is the prime driver of deforestation, accounting for 52% of plantation losses between 2005 and 2023. Thus, the maximum rate of LAI declined (R2=0.32,y=−1.3+1.7×10−9x) was displayed in cluster 3 (West Cox's Bazar Cricket Stadium Cluster) over the study period between 2005 and 2023. Therefore, the findings of the study will help in the afforestation implementation and green belt development strategies against climate change risk mitigation and adaptation for the associated stakeholders, including environmental resource managers, ecologists, forest managers, coastal morphologists, and decision-makers. 

Implications of Jhau (Tamarix: Casuarina equisetifolia) forest deforestation on coastal landscape ecology and climate change adaptation in Cox's Bazar, Bangladesh

Abstract The west central Indian forest ecosystems strongly contribute to livelihood of local human communities as well as climate change mitigation. However, due to the lack of accurate biomass equations and predictive tools, the contribution of these forests towards carbon stock and sequestration remains poorly recognized. At present due to some developmental and mining activities these forests face huge anthropogenic pressure. Therefore, the objective of the present study was to estimate the biomass and carbon stock of forest tree species of west central India to provide baseline information. It will also be useful for measuring the changes after the intervention as well as for future management and conservation. The non-destructive allometric equation approach was adopted to estimate the biomass, carbon stock and carbon dioxide equivalent from total 28 plots of 0.1 ha at seven sites of dry deciduous forests of west central India. In the present study, the results of biomass and carbon stock were calculated by employing two different allometric models. The model with tree diameter and wood specific gravity gave higher estimations of total plant biomass (123.39 – 65.86 Mg ha −1 ) and carbon stock (58.61—31.28 Mg ha −1 ) as compared with model having only tree diameter (108.84 – 55.91 Mg ha −1 ) and (51.70 -26.55 Mg ha −1 ), respectively. We conclude that the allometric model with tree diameter and wood specific gravity was found best suited for these forests. The results also showed the positive relation between tree diversity, basal area and aboveground biomass and carbon stock. 

/pdf/forest-carbon-stock-and-biomass-estimation-in-west-central-5v26o4oj.pdf

Forest carbon stock and biomass estimation in West Central India using two allometric models

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Forest carbon stock and biomass estimation in West Central India using two allometric models