K. Baranidharan

Rubber plantations (Hevea brasiliensis (Willd. ex A.Juss.) Müll.Arg.) are expanding tropical carbon (C) stores, storing an estimated 160–300 mg C ha-1 of total ecosystem C at maturity, but precise biomass and soil organic carbon (SOC) assessment remains difficult due to age disparities, historical land-use variations and data gaps. This review systematically analyses trends and research gaps in biomass accumulation of rubber systems. PRISMA 2020 guidelines were used to examine 104 studies in Scopus published between 1999 and 2025. The literature revealed a marked increase in research studies in China and Thailand post-2013 using a bibliometric approach presented by Biblioshiny. The most important methods are species-specific allometry (coefficient of determination (R2) > 0.9), age-based growth curves, remote sensing (RS) regressions (R2 0.2–0.7) and machine learning (ML) models like Random Forest/XGBoost (R2 0.8–0.97, root mean square error (RMSE) 7–40 mg/ha), which outperform simpler parametric models. Deep learning (DL) yields the highest accuracies (RMSE ~6 mg ha-1). Gaps persist in standardised protocols, South Indian datasets (e.g., Tamil Nadu/Western Ghats) and integrated lifecycle carbon accounting, including latex/SOC. Forest-to-rubber conversion incurs net losses, while cropland-to-rubber/agroforestry offers gains. The authors recommend adopting harmonised Tier 2/3 IPCC models, multi-decadal RS archives for reducing emissions from deforestation and forest degradation (REDD+) and ML extension to Indian smallholders. Policy integration with offset markets requires avoiding deforestation to realise climate-smart benefits.

The atmospheric concentration of CO2 has risen to 420 ppm, 42.8 % higher than the pre-industrial levels, due to fossil fuel burning, deforestation and urbanization. This has resulted in global warming which leads to sea level rise, melting of ice and an increase in the temperature. The Paris Agreement aims to cap global warming at 1.5 °C, requiring a 45 % cut in emissions by 2030 and net zero by 2070. Carbon sequestration, especially through natural processes, is a key solution. Oceans and forests are a large carbon sink, but coastal ecosystems called “Blue carbon” are also important. Mangroves, tidal marshes and seagrass ecosystems cover less than 0.5 % of the seabed, sequester carbon 10 times faster than tropical forests and store more than 50 % of ocean sediments carbon. Mangroves, for example, store 3-5 times more carbon per unit area than forests, with as much as 70 % stored in the soils. These ecosystems are, however, vulnerable to human activities like aquaculture and urbanization, leading to widespread degradation. Oceans absorb 25 % of anthropogenic CO2 emissions, which has led to a 26 % increase in ocean acidity since industrialization. Blue carbon ecosystems also have ecological and economic advantages, such as coastal protection, support for biodiversity and livelihoods for millions. The conservation and restoration of ecosystems are key to achieving global climate goals and ensuring sustainable development. In conclusion, blue carbon ecosystems are crucial to climate change mitigation and their conservation is necessary for a sustainable future.

India faces a critical timber deficit, as consumption (Compound Growth Rate (CGR) 5.20 %) continues to outpace domestic production (CGR 1.97 %). By 2030, timber demand is projected to reach 36.70 million cubic metres (MCUM). The study analyses the market structure, demand-supply gap and socio-economic conditions of timber growers across five districts−Tirunelveli, Kanniyakumari, Salem, Dindigul and Thanjavur−representing diverse agro-climatic zones in Tamil Nadu. It uses primary data from 250 growers and secondary data (2000-2023) from International Tropical Timber Organization (ITTO), State Forest Records and Food and Agriculture Organization Statistical Database (FAOSTAT) to estimate CGR of timber production and import trends. Growers are predominantly male (92.4 %), middle-aged (mean 49.91 years), with 29.3 % illiterate and operate fragmented holdings (average 7.49 %). Teak is the dominant species (72.8 % adoption), though species diversification is influenced by landholding size and agro-climatic conditions. Despite 74.8 % attempting direct sales, market inefficiencies persist: complex channels involving 5 intermediaries inflate price spreads to ₹570/cft (vs. ₹440/cft in streamlined channels), reducing farmers’ share to 43 %-50 % of consumer prices. Critical constraints include water scarcity (59.04 % Garrett score), drying challenges (64.71 %), broker fees (54.37 %) and grading difficulties (57.45 %). Notably, 90.8 % of growers express readiness for digital market integration. The study recommends policy interventions targeting co-operative marketing, e-platform adoption, input subsidies and logistic optimization to enhance grower agency and bridge the supply gap.

Biochar is a carbon-rich product that is produced by pyrolysis of organic biomass like forestry waste, animal manure and crop residues in low oxygen conditions using thermochemical processes like pyrolysis, torrefaction, gasification. Slow pyrolysis is most widely utilized among them due to its increased yield and carbon stability. Properties of biochar such as pH, surface area, porosity and nutrient content depend on the feedstock and production conditions. As a green and sustainable solution, biochar finds applications across multiple sectors. In forestry, it enhances soil porosity, water retention capacity, nutrient supply and microbial activity, which stimulates forest regeneration and reduces forest fire risks. In agriculture, biochar enhances soil fertility, agricultural yields, minimizes fertilizer use and leaching of nutrients. Biochar also plays a significant role in climate change mitigation by sequestering carbon in soils for long periods and reducing greenhouse gas emissions such as methane and nitrous oxide. In environmental remediation, its porous structure allows for the adsorption of heavy metals and organic pollutants from soil and water. In the energy industry, biochar is used as a solid renewable fuel or as a byproduct of syngas-producing or bio-oil producing systems. All these multi-variant uses make biochar a powerful instrument for circular economy initiatives, sustainable land management and climate action. With continued research and policy support, biochar presents a potential route toward ecological restoration and stable ecological conditions.

The rapid growth of Unmanned Aerial Vehicles (UAVs) or Drones have significantly revolutionized the methodologies of modern forestry. Traditional methods being dependent on low resolution satellite data and labour-intensive field work are now being substituted by high resolution drone-based data offering real time monitoring and increased operational efficiency. This review examines the extensive role of UAVs in modernising various forestry practices and its associated challenges. Different types of drones namely, fixed-wing, rotary-wing and hybrid models along with advance imaging systems and sensors such as multispectral, hyperspectral, thermal and LiDAR sensors. These technologies have been proven as inevitable source of forest inventory, health monitoring, wildfire detection and suppression, biodiversity assessment and precision forestry. UAVs Provide high resolution 3D Modelling, early disease detection and pest monitoring and improved seed dispersal through precision techniques. Apart from that usage of machine learning and deep learning technologies have enabled the usage of drone swarms enhancing large scale autonomous operation like real time environment monitoring. Despite their extensive advantages UAVs also have some minor disadvantages including regulatory constrains like lack of data processing, sensor limitation and high investment cost. In the Indian context though drone regulations are evolving there are some lacks on policy enforcement and legal framework. The review insists upon the need for unified legal frameworks, improved data-sharing methodologies and open-source software to support the wider adoption of UAVs in forestry. As drone technology continues to advance with blockchain interpretation, energy harvesting and user-friendly systems, its role in sustainable forest management is set to expand. UAVs are emerging as indispensable tools for efficient, responsive and ecologically responsible forestry practices.

Tree species diversity and regeneration dynamics are vital for maintaining ecosystem health, particularly in biodiversity-rich regions such as the Western Ghats. This study investigates the tree species diversity and regeneration patterns across five forest ranges (Ahwa West, Baripada, Bheskatri, Kalibel and Singhana) of the Purna Wildlife Sanctuary in Gujarat, India. The sanctuary, located in the northern section of the Western Ghats, hosts a mix of moist and dry deciduous forests. Data were collected using transects and quadrats to assess tree density, basal cover, species richness and regeneration success. The study highlights significant spatial variations in tree density, species composition and regeneration patterns across the sanctuary’s diverse habitat types. Among the different forest ranges, the Singhana range showed the highest species density, richness, diversity index and evenness index, while it recorded the lowest Simpson index compared to the other ranges of Purna Wildlife Sanctuary. Tectona grandis was found to be the dominant species, with varying dominance across ranges. The regeneration status showed a mixture of good, fair and poor regeneration across species, with some areas showing higher sapling and seedling densities. The study emphasizes the importance of understanding tree diversity and regeneration dynamics for effective forest management and conservation efforts in Purna Wildlife Sanctuary.

Invasive species present significant risks to the local ecosystems, disrupting their biodiversity and functioning. Senna spectabilis, initially introduced for decorative purposes, has emerged as a widespread invader, particularly in regions such as India. This review delves into the ecological and biological dimensions of Senna spectabilis invasion, its effects on native plant and animal life, and approaches for managing and eradicating it. Rapid growth, abundant seed production, and allelopathic characteristics enhance its invasiveness, allowing it to outcompete indigenous species and modify ecosystem dynamics. Senna spectabilis invasion results in habitat alteration, displacement of local flora and fauna, and changes in trophic interactions, impacting ecosystem stability. Various methods, including mechanical, chemical, biological, and cultural controls, are utilized to combat Senna spectabilis infestations, albeit with varying degrees of success. Eradication endeavors encompass techniques like complete uprooting, girdling, and debarking, complemented by efforts to restore and rehabilitate affected areas through native vegetation reinstatement, habitat enhancement, and soil restoration. Community involvement and international cooperation are crucial for addressing the cross-border spread of Senna spectabilis and mitigating its adverse effects on biodiversity conservation. This review underscores the necessity for cohesive action, encompassing assessment, surveillance, strategy formulation, and global collaboration, to effectively counter the proliferation of Senna spectabilis and safeguard indigenous ecosystems. Keywords: Distribution; Invasive Alien Species; Senna spectabilis; Restoration and Rehabilitation

Siam weed (Chromolaena odorata (L.) R.M. King & H. Rob.) of Asteraceae family, a perennial shrub with an invasive character, has been shown potential application in many of scientific communication. On the basis of broader geographical distribution across tropical and subtropical regions, research is mainly concentrated in ten countries of Africa, Asia and Oceania Australia. C. odorata has been largely studied for diverse phytochemical content including flavonoids, terpenoids and phenolic compounds responsible for many of its potential health and industrial application. In present work we reviewed several scientific literature and found antioxidant, anti-inflammatory, wound healing and anti-cancer application of C. odorata. Additionally, environmental applications of C. odorata as a phytoremediation and ecosystem restoration are in agricultural innovations are well established including natural pesticide and soil fertility enhancer. Moreover, several industrial applications including bioenergy and development of sustainable materials are also established. Finally based on balanced summary of available evidence on the ecological challenges and potential as a valuable biological resource for C. odorata and synthesizes current research knowledge that can help in the filling of knowledge gaps and defining of future research directions.

Forests are essential in combating climate change by functioning as carbon sinks, sequestering atmospheric carbon dioxide and storing it in biomass and soil. India, possessing various forest ecosystems, holds substantial potential for carbon sequestration. Climate change, marked by increasing temperatures, altered precipitation patterns and extreme weather phenomena, jeopardizes forest biomass and carbon sequestration. This systematic analysis evaluates the effects of climate change on forest biomass and carbon sequestration in several forest types in India. The study evaluates different methodologies for biomass estimation, including destructive, non-destructive and remote sensing approaches. It highlights the contributions of diverse forest types such as Himalayan forests, tropical rainforests, deciduous forests, mangroves and agroforestry systems in carbon sequestration. The findings indicate that while Indian forests act as vital carbon reservoirs, deforestation, land-use changes and climate-induced stressors have generally decreased the carbon sequestration potential of these forests by reducing biomass accumulation and increasing ecosystem stress, although variability exists across forest types. Sustainable forest management, afforestation and climate-resilient strategies are essential to enhance carbon storage. Integrating remote sensing technologies, ecological modeling and policy frameworks like REDD+ can aid in better monitoring and conservation efforts. This review provides insights into future strategies to strengthen India’s forest carbon sequestration capacity and mitigate climate change impacts.

Forest fires pose a significant threat to ecosystems, biodiversity and human livelihoods, necessitating the development of advanced predictive models for timely intervention. Machine learning (ML) techniques have emerged as effective tools for predicting forest fires by utilizing various environmental, meteorological and topographical datasets. This review explores recent advancements in ML-based fire prediction, highlighting key methodologies such as Random Forest, Support Vector Machines, Neural Networks and hybrid models. The combination of remote sensing data, real-time observation and cloud computing has notably improved the prediction accuracy. Moreover, the growth of Explainable AI (XAI) has enhanced the interpretability of ML models. Despite advancements, challenges such as data imbalances, model generalization issues and computational constraints persist. Future research must focus on refining ML algorithms to improve regional adaptability, integrating climate change forecasts and establishing real-time early warning systems. By bridging the gap between theoretical advancements and practical applications, ML-driven forest fire prediction models can significantly contribute to mitigating the devastating impact of forest fire and enhancing global fire management strategies.