Predictive models for biomass and carbon stock estimation in male bamboo (Dendrocalamus strictus L.) in Doon valley, India

Agroforestry systems in the mid-hills of the north-western Himalaya: A sustainable pathway to improved soil health and climate resilience

Identifying the new tree crop combinations plays an important function in transforming the low input agriculture into land units with high economic returns, increasing carbon (C) sink and nutrients storage capacity, and acting as a panacea to achieve Sustainability Development Goals (SDGs). The present study aims to evaluate various tree-crop combinations for (i) biomass production, (ii) carbon accumulation, and (iii) soil nutrient enrichment of traditional and commercially evolved eight agroforestry systems (AFSs), including agri-silvi-horticulture system, agri-silviculture system, silvi-pasture, fruit tree, fodder tree, bamboo, melia and poplar based AFSs with sole cropping system in the mid-hill zone of the north-western Himalaya. The results demonstrated that poplar based AFS accumulated a higher amount of biomass (130.87 Mg ha-1) and carbon (65.44 Mg ha-1) closely followed by melia-based AFS. The C stored in leaf litter was higher (0.66 Mg ha-1) in poplar-based AFS, however, soil C stock was maximum (114.69 Mg ha-1) under bamboo-based AFS. Overall, the Melia based AFS exhibited a higher rate of carbon dioxide mitigation (19.30 Mg ha-1 yr-1) and C-sequestration (5.26 Mg ha-1 yr-1) than other studied AFSs. Moreover, soil macro-nutrients (available N, P, K, S and Ca) were maximum under bamboo-based AFS, on the other hand, the fruit-based AFS had the higher concentrations of micro-nutrients i.e., Cu (3.05), Fe (31.10 mg g-1) and Mn (17.31 mg g-1). The soil microbial counts were higher in poplar-based AFS, whereas, the soil quality index improved significantly under bamboo based and fruit tree based AFSs. Hence, it can be concluded that the experimentally evolved AFSs represent an effective approach for boosting C-sequestration, soil fertility, regenerating the soil and sustainability of hill agriculture in the north-western Himalayas over traditional AFSs and sole cropping.

An allometric model-based approach for estimating biomass in seven Indian bamboo species in western Himalayan foothills, India

The rapid growth rate, high biomass production, and annual harvesting make bamboo a suitable species for commercial production. Allometric equations for many broadleaf and conifer tree species are available. However, knowledge of biomass production and allometric equations of bamboos is limited. This study aims to develop species- specific allometric models for predicting biomass and synthetic height values as a proxy variable for seven bamboo species in Himalayan foothills. Two power form-based allometric models were used to predict aboveground and culm biomass using diameter at breast height (D) alone and D combined with culm height (H) as an independent variable. This study also extended to establishing an H–D allometric model that can be used to generate synthetic H values as a proxy to missing H. In the seven bamboo species studied, among three major biomass components (culm, branch and foliage), culm is the most important component with the highest share (69.56–78.71%). The distribution of percentage (%) share of culm, branch and foliage to above-ground fresh weight varies significantly between different bamboo species. D. hamiltonii has the highest productivity for above-ground biomass components. Ratio of dry to fresh weight of seven bamboo species was estimated for culm, branch, foliage and above-ground biomass to convert fresh weight to dry weight.

Dynamic Changes in Leaf Biomass and the Modeling of Individual Moso Bamboo (Phyllostachys edulis (Carrière) J. Houz) under Intensive Management

Accurate estimations of leaf biomass are required to quantify the amount of material and energy exchanged between vegetation and the atmosphere, to enhance the primary productivity of forest stands, and to assess the contributions of vegetation towards the mitigation of global climate change. The leaf biomass of Moso bamboo (Phyllostachys edulis (Carrière) J. Houz) changes dramatically during the year owing to changes in the leaves and the growth of new shoots. Furthermore, the relationship between the leaf biomass of Moso bamboo under cutting the top of the culm and the diameter at breast height (D) and culm height is decoupling, which increases the difficulty of estimating leaf biomass. Consequently, an effective method to accurately estimate the leaf biomass of Moso bamboo under cutting the top of the culm is required. In this study, leaf biomass and other factors (age, D, culm height, crown length, and crown width) were measured for 54 bamboo samples collected from December 2019 to December 2020. Models for predicting the leaf biomass of the Moso bamboo were established using multiple linear regression with two strategies, and their accuracies were evaluated using leave-one-out cross-validation. The results showed that crown length, crown width, and age were highly correlated with leaf biomass, and these were important factors when making estimations. Variation in monthly averaged leaf biomass is significant, with a decreasing trend from January to May and an increasing trend from June to December in off-years. The leaf biomass model that utilized data from the three leaf change periods had a better fit and accuracy, with R2 values of 0.583–0.848 and prediction errors between 8.59% and 24.19%. The model that utilized data for all months had a worse fit and accuracy, with an R2 value of 0.228 and prediction error of 46.79%. The results of this study provide reference data and technical support to help clarify the dynamic changes in Moso bamboo leaf biomass, and therefore, aid in the development of accurate simulations.

Distribution of soil carbon fractions under different bamboo species in northwest Himalayan foothills, India

Soil carbon and its fractions are important in understanding the mechanism of soil carbon sequestration. The present study evaluated the impact of seven commercial bamboo species, viz., Bambusa balcooa, B. bambos, B. vulgaris, B. nutans, Dendrocalamus hamiltonii, D. stocksii, and D. strictus, on labile and non-labile carbon fractions. In the 0-15-cm layer, B. nutans had the highest very labile C (7.65 g kg^-1) followed by B. vulgaris > B. balcooa > D. stocksii > D. hamiltonii > B. bambos > D. strictus > open. The active carbon pool was significantly low under the control plot (i.e. the open) indicating the positive influence of bamboo in soil C build-up in the top 0-15 cm soil layer. Amongst the different species of bamboo evaluated in this study, D. strictus accumulated the highest active C pool in 0-30-cm soil layer followed by B. vulgaris. Of the total organic C in the 0-30 cm soil depth, majority (55-60%) was contributed by the passive C pool comprising the less labile and the non-labile fraction of SOC. A high value of carbon stratification ratio (> 2) was observed for D. strictus, B. bambos, and D. hamiltonii which proves their potential for restoration of the degraded lands. The majority of bamboo species except for B. balcooa and D. stocksii showed a higher carbon management index than open systems, thereby indicating higher rates of soil C rehabilitation. Of the seven bamboo species, B. vulgaris, D. strictus, and B. nutans can be adopted for cultivation in the northwest Himalayas given their ability to positively impact the SOC and its fractions in both surface and sub-surface soil.

Build-up of labile, non-labile carbon fractions under fourteen-year-old bamboo plantations in the Himalayan foothills

Carbon fractions under different bamboo species viz., Bambusa balcooa, Bambusa bambos, Bambusa nutans, Dendrocalamus hamiltonii, Dendrocalamus asper and Dendrocalamus strictus were evaluated to understand the potential of these different bamboo species in soil rehabilitation in Himalayan foothills. The highest accumulation of the different carbon fractions likes very labile (6.12 mg g⁻¹), less labile (2.55 mg g⁻¹) and non-labile (11.40 mg g⁻¹) was observed under D. hamiltonii, while highest labile fraction (3.17 mg g⁻¹) was recorded under D. strictus. The highest active (8.85 mg g⁻¹) and passive pool (13.95 mg g⁻¹) were recorded under D. hamiltonii. Higher carbon management index (CMI) was obtained under D. hamiltonii (186.04) which was comparable with D. strictus (182.66) and B. nutans (179.24). Among all the six species, D. hamiltonii had the highest buildup of active and passive pool in both the soil depths. Bamboo plantations irrespective of the different species helped in enhancing the SOC fraction and enhanced C buildup in the soil in comparison to the open fallow land and holds potential in combating the problems of land degradation and soil rehabilitation.

Seasonal variation in biochemical responses of bamboo clones in the sub-tropical climate of Indian Himalayan foothills

Seasonal variations affect the rate of biomass accumulation in plants which is internally governed by biochemical metabolites. Studying the impact of atmospheric seasonal changes on biochemical parameters can improve our understanding of various plant species' physiological plasticity. Bamboos are a fast-growing group of woody grass species, widely distributed across tropical and sub-tropical regions of the world, and are an important species of the Indian subcontinent. Nevertheless, limited information is available on the seasonal response of biochemical's in bamboo species growing in ambient atmospheric circumstances. Therefore, we investigated the seasonal biochemical responses of Dendrocalamus strictus clones viz. Pantnagar (PNT) and Dhampur (DHM) to seasonal ambient atmospheric conditions. The concentrations of chlorophyll, protein, carbon, nitrogen, phosphorus, potassium, and magnesium in bamboo leaves were increased significantly (p < 0.025) in monsoon compared to summer and winter seasons. Carotenoid, total sugar and ascorbic acid contents were highest during winters and reduced significantly during monsoon. Proline content was highest in summer and reduced by 97% during monsoon, indicating effective adaptation to both clones' water-limited conditions. It was inferred that seasonal variation in atmospheric conditions significantly influenced the biochemical constituents of plants. This study provides a biochemical approach for screening potential bamboo species with adaptive nature for plantation purposes intended to mitigate climate change.

Ecosystem-level carbon storage and its links to diversity, structural and environmental drivers in tropical forests of Western Ghats, India

Tropical forests are rich in biodiversity with great potential for carbon (C) storage. We estimated ecosystem-level C stock using data from 70 forest plots in three major forest types: tropical dry deciduous (TDD I and TDD II), tropical semi-evergreen (TSE I and TSE II) and tropical evergreen forests (TEF I, TEF II and TEF III) of Kanyakumari Wildlife Sanctuary, Western Ghats, India. The average C stock in these forests was 336.8 Mg C/ha, of which 231.3, 3.0, 2.4, 15.2 and 84.9 Mg C/ha were stored in woody vegetation, understorey, litter, deadwood and soil respectively. The live vegetation, detritus and soil contributed 65.5%, 5.5% and 29% respectively to the total ecosystem-level C stock and distributed in forest types in the order: TEF III > TEF II > TEF I > TSE I > TDD II > TSE II > TDD I. The plant diversity, structural attributes and environmental factors showed significant positive correlations with C stocks and accounted for 6.7, 77.2 and 16% of variance. These findings indicate that the tropical forests in the Western Ghats store large amount of C, and resulting data are invaluable for planning and monitoring forest conservation and management programs to enhance C storage in tropical forests.

Individual Plant Allometric Equations for Estimating Aboveground Biomass and Its Components for a Common Bamboo Species (Bambusa procera A. Chev. and A. Camus) in Tropical Forests

Bamboo forests play an important role in achieving the objectives of the United Nations program on Reducing Emission from Deforestation and Forest Degradation. We developed and validated a modeling system that simultaneously estimate aboveground biomass and its components for a common bamboo species (Bambusa procera A. Chev. and A. Camus) in tropical forests. Eighty-three bamboo culms were destructively sampled from seventeen 100 m2 sample plots located in different parts of the Central Highlands in Viet Nam to obtain total plant aboveground biomass (AGB) and its components. We examined the performance of weighted nonlinear models fit by maximum likelihood and weighted nonlinear seemingly unrelated regression fit by generalized least squares for predicting bamboo biomass. The simultaneous estimation of AGB and its components produced higher reliability than the models of components and total developed separately. With a large number of bamboo species, it may not be feasible to develop species- specific biomass models, hence genus-specific allometric models may be considered.