Biomass carbon stocks of different land use management in the forest vegetative zone of Nigeria

Agriculture models for restoring degraded land to enhance CO2 biosequestration and carbon credits in the Vindhyan region of India

The study's objective was to evaluate the status of converted degraded land into productive agricultural models by improving the physicochemical properties of the soil, soil organic matter (SOM), soil organic carbon (SOC) fractions (active and passive), and microbial biomass carbon (MBC), while also generating carbon (C) credit for additional farmers' income. Six models were analyzed, namely: (1) Arjun forest-based agroecosystems (AFBAE); (2) Lemon grass-based agroecosystems (LGBAE); (3) Legume-cereal-moong-based agroecosystems (LCMBAE); (4) Bael-black mustard-based agroecosystems (BMBAE); (5) Guava-wheat-based agroecosystems (GWBAE), and (6) Custard apple -lentil -based agroecosystems (CALBAE). These models were replicated three times in a randomized block design (RBD). Soil samples were collected from the study area at two depths (0-0.30 and 0.30-0.60 m). At a 0-0.30 m depth, the highest bulk density (ρb) of 1.50 Mg m-3 was observed in LCMBAE, while the lowest ρb of 1.43 Mg m-3 was recorded in BMBAE. The soil organic carbon (SOC) and SOC stock values exhibited a range of 4.2-7.7 g kg-1 and 19.0-33.4 Mg ha-1, respectively. In the AFBAE, the highest levels of 163.1 % MBC were found over LCMBAE. At a 0-0.30 m depth, the recalcitrant index (RI) and lability index (LI) ranged from 0.35-0.46 to 1.97-2.11, respectively. Additionally, the AFBAE exhibited the highest total biomass accumulation (39.23 Mg ha-1), carbon dioxide (CO2) biosequestration (287.9 Mg ha-1), and the total social cost of CO2 at US$ 277 ha-1. Furthermore, in the AFBAE, there was a 198.1 % increase in total C credit (US$ 161 ha-1) compared to LCMBAE (US$ 54 ha-1). However, at 0.30-0.60 m depths, GWBAE and CALBAE were statistically equivalent (p ≤ 0.05) in total C stocks. Principal component analysis (PCA) reveals that component-1 accounts for 77.4 % of the variability, while component-2 contributes 18.6 %. This article aimed to convert the degraded land into a sustainable agricultural module by increasing SOC and CO2 biosequestration and producing more C-credit, or climate currency, on underutilized land.

Impact of progressive and retrogressive land use changes on ecosystem multifunctionality: Implications for land restoration in the Indian Eastern Himalayan region

Land use change, anthropogenic exploitation and climate change have impacted the flow of services in the Himalayan region. The dominant land uses in the region including natural forest, degraded forest, rubber (Hevea brasiliensis) plantations, Areca catechu plantations, Areca agroforestry and Piper agroforestry were considered for the study. A progressive shift in land use was defined as the conversion and restoration of a less productive system like degraded land to plantations or agroforestry systems. A land use shift was considered retrogressive when it entails the establishment of plantations after clearing natural forests or anthropogenic disturbance of natural forests resulting in forest degradation. The objectives of the current study were to estimate changes in soil properties, stand structure, tree biomass, fine root production and carbon storage following a progressive and retrogressive shift in land usage. The aboveground biomass (105.9 Mg ha-1) was highest in the natural forest, followed by Areca agroforestry (100.2 Mg ha-1) and least in the degraded forest (55.3 Mg ha-1). The aboveground biomass carbon (47.1 Mg ha-1) of Areca agroforestry was comparable with that of natural forest (51.3 Mg ha-1). The highest proportion of passive carbon concentrations was observed under Areca agroforestry, whereas the lowest (4.13 g kg-1) was found under Areca plantations in the 0-25 cm soil depth. With the progressive shift in land use from degraded forest to agroforestry, SOC stocks increased by 27.6 % and 3 % under Piper and Areca agroforests, respectively. SOC stocks decreased by 8.5 % with a shift in land use from natural forests to Areca plantations. The production of fine roots was maximum in the Areca agroforest (13.2 Mg ha-1) and lowest under rubber plantations (4.2 Mg ha-1). The results show that progressive shifts from degraded forest to agroforestry can considerably increase carbon stocks, plant species diversity and multifunctionality than shifts to monoculture plantations thereby supporting improved biodiversity and mitigation of climate change.

Modeling of biomass and stored carbon in a seasonal semidecidual forest in Brazil

This study estimated biomass and carbon from components, future carbon values ​​and to obtain economic productive value of carbon fixation of a Seasonal Semideciduous Forest. Biomass and carbon were estimated using adjusted equations and selected using regression statistics. The prognosis of the diametric distribution was performed using the movement ratio method. In the economic evaluation, it was estimated productive value of the stand, referring to the current and future carbon fixation capacity. The coefficients of determination (adjusted R²) of the equations ranged from 0.11 to 0.90 and the standard error of the estimate (Syx) ranged from 41.53% to 141.89% for the biomass of the components, and from 0.03 to 0.87 for adjusted R² and from 46.20% to 143.64% for the error, for stored carbon in the components. The total biomass of the tree component estimated was 56.25 t ha-1 and 25.88 t ha-1 of total carbon. Using the future distributions by the method of the ratio of movements, total stored carbon (aerial + roots) estimated was 14.44 t. ha-1 over the 20-year period. The productive value for the fragment reached R$ 299.95 per ha. year-1.

The Use of Very-High-Resolution Aerial Imagery to Estimate the Structure and Distribution of the Rhanterium epapposum Community for Long-Term Monitoring in Desert Ecosystems

The rapid assessment and monitoring of native desert plants are essential in restoration and revegetation projects to track the changes in vegetation patterns in terms of vegetation coverage and structure. This work investigated advanced vegetation monitoring methods utilizing UAVs and remote sensing techniques at the Al Abdali protected site in Kuwait. The study examined the effectiveness of using UAV techniques to assess the structure of desert plants. We specifically examined the use of very-high-resolution aerial imagery to estimate the vegetation structure of Rhanterium epapposum (perennial desert shrub), assess the vegetation cover density changes in desert plants after rainfall events, and investigate the relationship between the distribution of perennial shrub structure and vegetation cover density of annual plants. The images were classified using supervised classification techniques (the SVM method) to assess the changes in desert plants after extreme rainfall events. A digital terrain model (DTM) and a digital surface model (DSM) were also generated to estimate the maximum shrub heights. The classified imagery results show that a significant increase in vegetation coverage occurred in the annual plants after rainfall events. The results also show a reasonable correlation between the shrub heights estimated using UAVs and the ground-truth measurements (R² = 0.66, p < 0.01). The shrub heights were higher in the high-cover-density plots, with coverage >30% and an average height of 77 cm. However, in the medium-cover-density (MD) plots, the coverage was <30%, and the average height was 52 cm. Our study suggests that utilizing UAVs can provide several advantages to critically support future ecological studies and revegetation and restoration programs in desert ecosystems.