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ID: 66753
Title: Nano-mediated Seed Ball Technology can be a Game-changer for the Land Restoration
Author: Vishwanath Sharma, Aditi Tailor
Editor: Richa Misra
Year: 2026
Publisher: Indian Council of Forestry Research & Education.
Source: ENVIS, CES & EWRG, CES
Reference: The Indian Forester Vol. 152 (6A) June 26 Pg No. 155-156 (2026)
Subject: Nano-mediated Seed Ball Technology can be a Game-changer for the Land Restoration
Keywords: None
Abstract: Forests play a prominent role in the economic development of a country owing to the ecosystem services they provide, which eventually and in ensuring livelihood support, generating employment, and promoting sustainable development. Maintaining healthy forest systems has manufactured benefits in combating climate change, eradicating poverty, conserving biodiversity, protecting from floods/severe drought, and providing food and energy security.
Location: T E 15 New Biology building
Literature cited 1: Acharya P., Jayaprakasha G.K., Crosby K.M., Jifon J.L. and Patil B.S. (2019). Green-synthesized nanoparticles enhanced seedling growth, yield, and quality of onion (Allium cepa L.). ACS Sustainable Chemistry & Engineering, 7(17): 14580–14590. https://doi.org/10.1021/acssuschemeng. 9b02180 Gornish E.S., Arnold H. and Fehmi J. (2019). Review of seed pelletizing strategies for arid land restoration. Restoration Ecology, 27(6): 1206–1211. https://doi.org/10.1111/rec.12993
Literature cited 2: Jordan G.L. (1967). An evaluation of pelleted seeds for seeding Arizona rangeland (Technical Bulletin No. 183). University of Arizona Agricultural Experiment Station. Madsen M.D., Davies K.W., Boyd C.S., Kerby J.D. and Svejcar T.J. (2016). Emerging seed enhancement technologies for overcoming barriers to restoration. Restoration Ecology, 24(S2): S77–S84. https://doi.org/10.1111/rec.12332

ID: 66752
Title: Community Seed Banks for Climate-Resilient Forest Tree Species and Sustainable Land Management in India
Author: Manish Kumar Singh
Editor: Richa Misra
Year: 2026
Publisher: Indian Council of Forestry Research & Education.
Source: ENVIS, CES & EWRG, CES
Reference: The Indian Forester Vol. 152 (6A) June 26 Pg No. 151-156 (2026)
Subject: Community Seed Banks for Climate-Resilient Forest Tree Species and Sustainable Land Management in India
Keywords: None
Abstract: Healthy forests and resilient landscapes are essential for ecological stability, biodiversity, conservation, climate regulation and sustainable livelihoods. However, climate change, land degradation, deforestation and habitat fragmentation are increasingly threatening forest ecosytems across India. Rising temperatures, erratic rainfall, prolonged droughts and anthropogenic disturbances are affecting flowering behaviour, seed production, seed viability and natural regeneration of native forest tree species. In this context, ensuring seed security for ecological restoration and sustainable land management has become an official priority.
Location: T E 15 New Biology building
Literature cited 1: Baskin C.C. and Baskin J.M. (2014). Seeds: Ecology, Biogeography and Evolution of Dormancy and Germination. 2nd Edition. Academic Press, San Diego. Bisht I.S., Rana J.C., Yadav R. and Ahlawat S.P. (2020). Mainstreaming agricultural biodiversity in traditional production landscapes for sustainable development: The Indian scenario. Sustainability, 12(24): 10690. DOI: https://doi.org/10.3390/su122410690
Literature cited 2: Carr K., Ozowara X. and Sloey T.M. (2024). Effects of climate change on seed germination may contribute to habitat homogenization in freshwater forested wetlands. Plant Ecology, 225: 1023–1033. https://doi.org/10.1007/s11258-024-01451-4 DOI: https://doi.org/10.1007/s11258-024-01451-4 Food and Agriculture Organization FAO. (2020). Global Forest Resources Assessment 2020. Food and Agriculture Organization, Rome.

ID: 66751
Title: Emerging Pollutants as Silent Threats to Soil Health and Sustainability
Author: Krishna Giri, Manoj Kumar, Gaurav Mishra
Editor: Richa Misra
Year: 2026
Publisher: Indian Council of Forestry Research & Education.
Source: ENVIS, CES & EWRG, CES
Reference: The Indian Forester Vol. 152 (6A) June 26 Pg No. 148-150 (2026)
Subject: Emerging Pollutants as Silent Threats to Soil Health and Sustainability
Keywords: None
Abstract: Healthy soil is the foundation of the sustenance of life on earth and maintains the stability of the ecosystems. Several environmental pollutants released through anthropogenic activities find their way into the environment and accumulate in various reservoirs, i.e atmosphere, soil, water and sediments. Antibiotics are the natural secondary metabolites of microbial origin used as growth inhibitors (bacteriostatic), killing the pathogenic bacteria and fungi through targeted application (Zeng et al.,2025.)
Location: T E 15 New Biology building
Literature cited 1: Fatima H., Bhattacharya A., Gupta S. and Khare S.K. (2025). Combating antibiotic pollution and its impacts on the environment through sustainable remediation options: Current developments and challenges. International Biodeterioration and Biodegradation, 205, 106166. DOI: https://doi.org/10.1016/j.ibiod.2025.106166 Liu Y., Neal A.L., Zhang X., Fan H., Liu H. and Li Z. (2022). Cropping system exerts stronger influence on antibiotic resistance gene assemblages in greenhouse soils than reclaimed wastewater irrigation. Journal of Hazardous Materials, 425:128046. DOI: https://doi.org/10.1016/j.jhazmat.2021.128046
Literature cited 2: Mann A., Nehra K., Rana J.S. and Dahiya T. (2021). Antibiotic resistance in agriculture: Perspectives on upcoming strategies to overcome upsurge in resistance. Current Research in Microbial Sciences, 2:100030. DOI: https://doi.org/10.1016/j.crmicr.2021.100030 Thakur J.K., Mandal A., Singh A.B., Sinha N.K. and Das A. (2022). Emerging threat of antibiotic pollution in soil: Causes and consequence. Harit Dhara, 5(2):25-29.

ID: 66750
Title: Spatiotemporal Dynamics of Urban Green Spaces in Dehradun City during 2000-2020
Author: Richa Misra, Anoop Kumar, R.K. Singh
Editor: Richa Misra
Year: 2026
Publisher: Indian Council of Forestry Research & Education.
Source: ENVIS, CES & EWRG, CES
Reference: The Indian Forester Vol. 152 (6A) June 26 Pg No. 136-147 (2026)
Subject: Spatiotemporal Dynamics of Urban Green Spaces in Dehradun City during 2000-2020
Keywords: Land Use Land Cover (LULC), Remote sensing, Urbanisation, Landsat, Decadal change.
Abstract: This study assessed the decadal changes in Urban Green Spaces (UGS) of Dehradun city, Uttarakhand, India, using Landsat satellite images for the years 2000, 2010, 2020. The study aimed to classify major land cover classes, map UGS, and assess temporal changes caused by rapid urbanisation. Landsat 5 TM, Landsat 7 ETM+, and Landsat 8 OLI datasets were processed using a hybrid classification approach integrating Maximum Likelihood Classification and Iterative Self Organising (ISO) data clustering techniques. The imagery was classified into agriculture, built-up, forest, scrub, and water classes. Accuracy assessment using 350 field verification points produced an overall classification accuracy of 90.9% with a Kappa coefficient of 0.886. The results showed a rapid increase in built-up area from 14.85% in 2000 to 47.33% in 2020, while agricultural land and scrub areas declined significantly. The study also revealed that institutional campuses and roadside corridors showed noticeable greening trends. The study demonstrates the usefulness of remote sensing and GIS techniques for monitoring urban expansion and sustainable management of UGS. The findings can support future urban planning and ecological conservation strategies.
Location: T E 15 New Biology building
Literature cited 1: Bertram C. and Rehdanz K. (2015). The role of urban green space for human well-being. Ecological Economics, 120: 139–152. Bhat P.A., ul Shafiq M., Mir A.A. and Ahmed P. (2017). Urban sprawl and its impact on landuse/land cover dynamics of Dehradun City, India. International Journal of Sustainable Built Environment, 6(2) : 513–521.
Literature cited 2: Budruk M., Thomas H. and Tyrrell T. (2009). Urban green spaces: A study of place attachment and environmental attitudes in India. Society and Natural Resources, 22(9): 824–839. Dixon B. and Candade N. (2008). Multispectral landuse classification using neural networks and support vector machines: One or the other, or both? International Journal of Remote Sensing, 29(4): 1185–1206. https://doi.org/10.1080/ 01431160701294661

ID: 66749
Title: Applications of Artificial Intelligence in Restoration of Degraded Ecosystems
Author: Harshita Negi, Salil Tewari
Editor: Richa Misra
Year: 2026
Publisher: Indian Council of Forestry Research & Education.
Source: ENVIS, CES & EWRG, CES
Reference: The Indian Forester Vol. 152 (6A) June 26 Pg No. 127-135 (2026)
Subject: Applications of Artificial Intelligence in Restoration of Degraded Ecosystems
Keywords: Artificial intelligence, Restoration, Degraded ecosystem, Degraded landscapes.
Abstract: Global forest ecosystems, which occupy about 4 billion hectares (or 30%) of the world's land mass, are the most visible indicators of the health of the Planet and act as critical carbon sinks, storing 66% of all terrestrial carbon. Yet, the world has lost 32% of forest cover due to industrialization and urban development, compounded by climate change effects such as severe weather events, changing drought patterns, and increasing wildfires. This paper presents the use of Artificial Intelligence (AI) and Machine Learning (ML) in rehabilitating these ecosystems. Through integration of the "scorpan" variables - soil, climate, organisms, relief, parent material, age, and space - AI models offer unprecedented predictive accuracy in predictions for species survival, growth and carbon storage. This paper explores key algorithms such as Random Forests (RF), Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks, as well as use of Unmanned Aerial Vehicles (UAVs) for targeted reforestation and decision-making. The results suggest that AI-based restoration efforts not only improve ecosystem resilience but are crucial to reaching global carbon neutrality, provided regional data gaps and domain shift issues are overcome.
Location: T E 15 New Biology building
Literature cited 1: Alif H.A., Mashrafi, Jisan Md., Elhag Md. and Purohit S. (2025). Artificial intelligence-driven rainfall forecasting and GIS-based flood risk mapping for climate-resilient infrastructure in Bangladesh, Earth Syst. Environ. DOI: https://doi.org/10.1007/s41748-025-00958-8 Allen C.D., Macalady A.K., Chenchouni H., et al. (2010). A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests, For. Ecol. Manag., 259(4): 660-684.
Literature cited 2: Ayadi R., Forouheshfar Y. and Moghadas O. (2025). Enhancing system resilience to climate change through artificial intelligence: a systematic literature review, Front. Clim., 7: 1585331. DOI: https://doi.org/10.3389/fclim.2025.1585331 Benavidez R., Bethanna J., Deborah M. and Kevin N. (2018). A review of the (Revised) Universal Soil Loss Equation ((R)USLE): with a view to increasing its global applicability and improving soil loss estimates, Hydrology and Earth System Sciences, 22(11): 6059-6086. DOI: https://doi.org/10.5194/hess-22-6059-2018

ID: 66748
Title: Forest Simulation Models and Climate Change: A Critical Review
Author: Toshika Tamrakar, Mallesh Yalal, Ram Prakash Yadav, Sourabh Gauraj, Garima Gupta, Ramesh Barki, Nidhish Singh, Vadthyavath Avinash
Editor: Richa Misra
Year: 2026
Publisher: Indian Council of Forestry Research & Education.
Source: ENVIS, CES & EWRG, CES
Reference: The Indian Forester Vol. 152 (6A) June 26 Pg No. 122-126 (2026)
Subject: Forest Simulation Models and Climate Change: A Critical Review
Keywords: Forest simulation models, Climate change, Process-based models, Gap models, MaxEnt, 3-PG, Forest dynamics, India.
Abstract: Forests cover approximately 4.14 billion hectares globally and play an important role in carbon sequestration, biodiversity conservation, and rural livelihoods. However, accelerating climate change is reshaping forest structure, species composition, and ecosystem functioning at an unprecedented pace, creating an urgent need for robust predictive tools. This review examines the major categories of forest simulation models, empirical, process-based, gap, landscape, and hybrid, evaluating their theoretical foundations, practical strengths, and inherent limitations in the context of climate change research. A historical timeline traces model development from 18th-century yield tables to contemporary Earth System Models. Four case studies drawn from India, Spain, and the United States demonstrate how different modelling frameworks perform across contrasting ecological and management contexts, confirming that no single model type is universally appropriate. The review identifies the near complete absence of process-based forest modelling applications in Indian ecosystems as the most significant knowledge gap in the field. Future research priorities include physiological parameterization of Indian tree species, long-term monitoring network development, and the application of multi-model ensemble frameworks to tropical and subtropical forest systems.
Location: T E 15 New Biology building
Literature cited 1: Botkin D.B., Janak J.F. and Wallis J.R. (1972). Some ecological consequences of a computer model of forest growth. Journal of Ecology, 60(3): 849–872. DOI: https://doi.org/10.2307/2258570 Bugmann H.K.M. (1996). A simplified forest model to study species composition along climate gradients. Ecology, 77(7): 2055–2074. DOI: https://doi.org/10.2307/2265700
Literature cited 2: Bugmann H.K.M. (2001). A review of forest gap models. Climatic Change, 51(3–4), ): 259–305. DOI: https://doi.org/10.1023/A:1012525626267 De Bruijn A., Gustafson E.J., Sturtevant B.R., Foster J.R., Miranda B.R. and Lichti, N.I. (2014). Toward more robust projections of forest landscape dynamics under novel environmental conditions. Ecological Modelling, 287: 44–57. DOI: https://doi.org/10.1016/j.ecolmodel.2014.05.004

ID: 66747
Title: Integration of SAR and Optical Remote Sensing Data for Spatial Estimation of Forest Carbon Stock in Meghalaya, India
Author: Dhruval Bhavsar, Suraj Kumar Swain, Kasturi Chakraborty, H.C. Chaudhary
Editor: Richa Misra
Year: 2026
Publisher: Indian Council of Forestry Research & Education.
Source: ENVIS, CES & EWRG, CES
Reference: The Indian Forester Vol. 152 (6A) June 26 Pg No. 117-121 (2026)
Subject: Integration of SAR and Optical Remote Sensing Data for Spatial Estimation of Forest Carbon Stock in Meghalaya, India
Keywords: Forest carbon stock, Land degradation neutrality, Biomass, Remote Sensing.
Abstract: Land degradation and climate change threaten ecosystem sustainability, particularly in tropical forests. Spatial assessment of forest carbon stock is essential for supporting Land Degradation Neutrality (LDN). This study integrates optical and Synthetic Aperture Radar (SAR) remote sensing data to estimate and map forest carbon stock in reserve and protected forests of Khasi Hills, Meghalaya. Field data from 221 plots were used to derive aboveground biomass (AGB) and estimate total carbon. A multi-linear regression model using vegetation indices and SAR backscatter achieved R2 = 0.66 (RMSE = 50.34 Mg ha-1), while total carbon estimation showed a validation accuracy of R2 = 0.67 (RMSE = 26.27 Mg ha-1). Vegetation carbon was largely concentrated between 100–150 Mg ha-1 and soil organic carbon between 60–90 Mg ha-1, leading to total carbon values predominantly in the range of 150–250 Mg ha-1 with some areas exceeding 250 Mg ha-1. The study demonstrates the effectiveness of multi-sensor approaches for carbon assessment, supporting ecosystem restoration and LDN objectives.
Location: T E 15 New Biology building
Literature cited 1: Chaturvedi V., Ghosh A., Garg A., Avashia V., Vishwanathan S.S., Gupta D. and Prasad S. (2024). India's pathway to net zero by 2070: status, challenges, and way forward. Environmental Research Letters, 19(11): 112501. DOI: https://doi.org/10.1088/1748-9326/ad7749 Choi W., Ryu Y., Kong J., Jeong S. and Lee K. (2025). Evaluation of spatial and temporal variability in Sentinel-2 surface reflectance on a rice paddy landscape. Agricultural and Forest Meteorology, 363: 110401. DOI: https://doi.org/10.1016/j.agrformet.2025.110401
Literature cited 2: Fararoda R., Reddy R.S., Rajashekar G., Chand T.K., Jha C.S. and Dadhwal V.K. (2021). Improving forest above ground biomass estimates over Indian forests using multi source data sets with machine learning algorithm. Ecological Informatics, 65: 101392. DOI: https://doi.org/10.1016/j.ecoinf.2021.101392 FRI (2002). Indian Woods: Their Identification, Properties and Uses, Vol. I-VI (Revised Edition). Forest Research Institute, Indian Council of Forestry Research and Education, Ministry of Environment and Forests, Government of India, Dehradun.

ID: 66746
Title: AI for Restoring Degraded Lands: Mapping Degradation, Predicting Climate Risk and Valuing Ecosystem Services
Author: Sayanta Ghosh, Jitendra Vir Sharma
Editor: Richa Misra
Year: 2026
Publisher: Indian Council of Forestry Research & Education.
Source: ENVIS, CES & EWRG, CES
Reference: The Indian Forester Vol. 152 (6A) June 26 Pg No. 109-112 (2026)
Subject: AI for Restoring Degraded Lands: Mapping Degradation, Predicting Climate Risk and Valuing Ecosystem Services
Keywords: Artificial Intelligence, Land restoration, Climate risk prediction, Ecosystem services, Land degradation mapping, Remote sensing, Machine learning.
Abstract: Land degradation is a major global challenge, with up to 40% of the world's land estimated to be degraded, affecting more than 3 billion people and weakening food security, biodiversity, climate resilience and ecosystem services. In this context, the objective of this review is to examine how artificial intelligence (AI), remote sensing and geospatial analytics can support land restoration by integrating three connected domains: land degradation mapping, climate-risk prediction and ecosystem service valuation. The review focuses on AI-based approaches for identifying degradation hotspots, assessing vegetation and soil stress, predicting drought, heat, evapotranspiration and fire-related risks, and estimating ecosystem services such as carbon sequestration, soil retention, water regulation, forage productivity and biodiversity support. Methodologically, the paper adopts a thematic synthesis of peer-reviewed literature, with emphasis on machine learning, deep learning, hybrid geospatial models and multi-source data integration. The synthesis indicates that AI can improve restoration planning by strengthening spatial diagnosis, capturing nonlinear land-climate interactions, anticipating future risk and estimating likely ecosystem service gains from restoration interventions. However, the review also finds that operational adoption remains constrained by data gaps, limited field validation, scale mismatch, uncertainty and weak interpretability of complex models. The paper therefore argues for a shift from isolated AI applications towards integrated, explainable and decision-oriented frameworks that combine Earth Observation, climate data, field evidence and ecosystem service indicators. Future research should prioritise groundvalidated datasets, multi-scale modelling, uncertainty reporting, local ecological knowledge and operational decision-support systems. Such integration can help identify where restoration is most urgently needed, where it is most likely to succeed, and what ecological and livelihood benefits it can generate. This review provides state-of-the-art insights on using AI-enabled land degradation mapping, climate-risk prediction and ecosystem service valuation as decision-support tools for sustainable land management, ecosystem resilience and evidence-based restoration of degraded landscapes.
Location: T E 15 New Biology building
Literature cited 1: Adhikari K. and Hartemink A.E. (2016). Linking soils to ecosystem services: A global review. Geoderma, 262: 101–111. https://doi.org/10.1016/j.geoderma.2015.08.009 DOI: https://doi.org/10.1016/j.geoderma.2015.08.009 Amani S. and Shafizadeh-Moghadam H. (2023). A review of machine learning models and influential factors for estimating evapotranspiration using remote sensing and ground-based data. Agricultural Water Management, 284: 108324. https://doi.org/10.1016/j.agwat.2023.108324 DOI: https://doi.org/10.1016/j.agwat.2023.108324
Literature cited 2: Andrianarivony H.S. and Akhloufi M.A. (2024). Machine learning and deep learning for wildfire spread prediction: A review. Fire, 7(12): 482. https://doi.org/10.3390/fire7120482 DOI: https://doi.org/10.3390/fire7120482 D'Acunto F., Marinello F. and Pezzuolo A. (2024). Rural land degradation assessment through remote sensing: Current technologies, models, and applications. Remote Sensing, 16(16): 3059. https://doi.org/10.3390/rs16163059 DOI: https://doi.org/10.3390/rs16163059

ID: 66745
Title: Recent Advances in Techniques, Methods and Policy Frameworks to Combat Forest Degradation under Climate Change
Author: Sukirti, Shikha Chandola, Rajendra Kumar Meena, Maneesh S. Bhandari, Santan Bharthwal, Manisha Thapliyal
Editor: Richa Misra
Year: 2026
Publisher: Indian Council of Forestry Research & Education.
Source: ENVIS, CES & EWRG, CES
Reference: The Indian Forester Vol. 152 (6A) June 26 Pg No. 99-108 (2026)
Subject: Recent Advances in Techniques, Methods and Policy Frameworks to Combat Forest Degradation under Climate Change
Keywords: Forest degradation, Climate change, Remote sensing, Climatesmart forestry, REDD+, Ecosystem restoration, Conservation genetics.
Abstract: Degradation of forests, marked by a slow but continuous deterioration of forest structure, diversity, and ecosystem functioning, is now regarded as an important environmental concern in light of the ongoing climate change. Forest degradation differs from deforestation in that it occurs gradually but still makes major contributions to global carbon emissions and ecological disturbance. Innovations in monitoring methods, ecological restoration techniques, and policies are among the ways to tackle this problem. This paper presents current trends in the areas of remote sensing, LiDAR, artificial intelligence, genomic assessments, and adaptive management, like climate-smart forestry and Ecosystem-Based Adaptation, in the field of forest conservation. In addition, policies such as the REDD+ mechanism, national forest policy, and carbon financing are explored along with some illustrative examples from around the world and India. It is seen that although there have been significant advances in technology, which help with detection and predictive analytics in the field of forest management, the actual process of mitigation needs proper policy-making and active involvement of local communities as well as region-specific approaches.
Location: T E 15 New Biology building
Literature cited 1: Aitken S.N. and Whitlock M.C. (2013). Assisted gene flow to facilitate local adaptation to climate change. Annual Review of Ecology, Evolution, and Systematics, 44: 367–388. DOI: https://doi.org/10.1146/annurev-ecolsys-110512-135747 Anamaghi S., Khorchani M., Fares S. and Corona P. (2025). Research efforts and gaps in the assessment of forest system resilience to natural or human-induced disturbances. Environmental Research Communications, 7(2): 022001. https:// doi.org/ 10.1088/ 2515-7620/adabc1 DOI: https://doi.org/10.1088/2515-7620/adb130
Literature cited 2: Anderegg W.R., Kane J.M. and Anderegg L.D. (2013). Consequences of widespread tree mortality triggered by drought and temperature stress. Nature climate change, 3(1): 30-36. DOI: https://doi.org/10.1038/nclimate1635 Bastos A., Friedlingstein P., Sitch S., Chen C., Mialon A., Wigneron J. P., Knox S., Wang Y., Nabel J.E.M.S. and others. (2023). Impacts of climate extremes and land-use change on terrestrial carbon dynamics. Nature Reviews Earth and Environment, 4(2): 84–99. https://doi.org/10.1038/s43017022-00369-5

ID: 66744
Title: Ecological Niche modelling for Predicting Suitable Habitat for Conservation of Vulnerable Tree Species Buchnania lanzan (Spreng.) in Degraded Ecosystem of Vindhya region of Uttar Pradesh, India
Author: Kaushal Singh, Swetendra K. Trigunayat, Arbind Gupta, Rajeev Umrao, Vivek Vaishnav, Manish Kumar Singh
Editor: Richa Misra
Year: 2026
Publisher: Indian Council of Forestry Research & Education.
Source: ENVIS, CES & EWRG, CES
Reference: The Indian Forester Vol. 152 (6A) June 26 Pg No. 83-98 (2026)
Subject: Ecological Niche modelling for Predicting Suitable Habitat for Conservation of Vulnerable Tree Species Buchnania lanzan (Spreng.) in Degraded Ecosystem of Vindhya region of Uttar Pradesh, India
Keywords: Ecological niche, Conservation, Climate change, Vindhya region.
Abstract: A study was carried out to predict the future distribution range of Chironji (Buchanania lanzan) and characterization of ecological niche in the degraded ecosystem of Vindhya region of Uttar Pradesh. Two different ecological niche models (BioClim and MaxEnt) were applied to determine future species distribution ranges and identify limiting bioclimatic variables for real occurrence data of 57 locations. The GeoCAT and Digital Elevation Model (DEM) were used to find out the population size and topography. Results of the study showed soil pH varied from 6.46 to 7.92, Nitrogen from low (213 kg/ha) to medium (389 kg/ha), Phosphorus was medium (13.50-22.50 kg/ha), and Potassium low (84 kg/ha) to high (662 kg/ha), with 210m to 520m elevation and population size 4.515km2 (Extent of Occurrence) and 23 km2 (Area of Occupancy) with Mahua (Madhuka longifolia var. latifolia), Tendu (Diospuros melanoxylon), and Sal (Shorea robusta) as associates. The distribution ranges were found with 80% overlap between the baseline (2030) and predicted (2100) habitat suitability for the focal species, which were primarily determined by the mean temperature of the warmest quarter (Bio_10) and precipitation of the driest quarter (Bio_17) that emerged to be the most sensitive with the contribution of 29.5% and 22.3% respectively. The present (2030) and future (2100) projections suggest 13.73% low suitable, 86.27% medium suitable and 1.52% low suitable, 98.48% medium suitable area respectively for the distribution and cultivation of the chironji. The findings of the study provide insight into the suitable habitats of B. lanzan for its promotion and conservation in Banda, Hamirpur, Kaushambi, Bhadohi, Prayagraj, and Chitrakoot forest divisions of Uttar Pradesh.
Location: T E 15 New Biology building
Literature cited 1: Adhikari D., Barik S.K. and Upadhaya K. (2012). Habitat distribution modelling for reintroduction of Ilex khasiana Purk., a critically endangered tree species of northeastern India. Ecological Engineering, 40: 37-43. DOI: https://doi.org/10.1016/j.ecoleng.2011.12.004 Araujo M.B., Cabeza M., Thuiller W., Hannah L. and Williams P.H. (2004). Would climate change drive species out of reserves? An assessment of existing reserve-selection methods. Global Change Biology, 10(9): 1618–1626. DOI: https://doi.org/10.1111/j.1365-2486.2004.00828.x
Literature cited 2: Austin M.P. and Niel K.P. (2011). Improving species distribution models for climate change studies: variable selection and scale. Journal of Biogeography, 38: 1–8. DOI: https://doi.org/10.1111/j.1365-2699.2010.02416.x Avani P., Bauri F.K. and Sarkar S.K. (2015). Chironji: A golden nut fruit of Indian tribes. In III International Symposium on Underutilized Plant Species, 1241: 37-42. DOI: https://doi.org/10.17660/ActaHortic.2019.1241.6

ID: 66743
Title: Ecological Rehabilitation of Red Mud Dump at Hindalco Industries Limited, Muri, Jharkhand: Vegetation Establishment, Biodiversity Recovery, and Growth Performance
Author: Parikshit Abhimanyu Pawar, Vanshika Kaushik, Syed Arif Wali, J.V. Sharma
Editor: Richa Misra
Year: 2026
Publisher: Indian Council of Forestry Research & Education.
Source: ENVIS, CES & EWRG, CES
Reference: The Indian Forester Vol. 152 (6A) June 26 Pg No. 74-82 (2026)
Subject: Ecological Rehabilitation of Red Mud Dump at Hindalco Industries Limited, Muri, Jharkhand: Vegetation Establishment, Biodiversity Recovery, and Growth Performance
Keywords: Red mud rehabilitation, Red mud pond (RMP), Ecological restoration, Bauxite residue, Soil amelioration, Plant survival, Vegetation structure, GBH, Biodiversity recovery.
Abstract: Red mud, the highly alkaline bauxite residue generated during alumina refining, poses formidable challenges to vegetation establishment owing to extreme pH (>=11), elevated electrical conductivity, high exchangeable sodium, and near-zero organic matter (Nayak et al., 2024). The present study documents the large-scale ecological rehabilitation of red mud disposal areas at Hindalco Industries Limited, Muri, Jharkhand, where The Energy and Resources Institute (TERI) has undertaken restoration of 99 acres since 2021, of which 50 acres (20.24 ha) have been planted. An integrated amendment strategy combining gypsum, farmyard manure (FYM), fly ash, and mycorrhiza was applied to ameliorate baseline conditions (pH 11.1; EC 5.7 dS m-1; OC 0.4%). A multi-tier, multi-species plantation of 44 tree species, 10 shrub species, and 6 grass species was established. Of 20,116 plants established across RMP 3 and RMP 4 areas, 16,588 survived (overall survival rate 82.46%). Biodiversity assessment of 54 species (44 tree, 10 shrub) and 5,183 individuals recorded a Shannon-Wiener diversity index of 3.23 and Simpson diversity index of 0.944, indicating high vegetation diversity and low species dominance. A vegetation inventory of 3,595 tree individuals recorded a mean height of 1.89 m (SD = 0.95 m) and mean GBH of 8.63 cm (SD = 5.62 cm). Two-way ANOVA confirmed highly significant differences in growth performance among species (F = 74.51 for height, F = 69.14 for GBH; both p < 0.001) after accounting for plantation area. Babool (Vachellia nilotica) and Subabul (Leucaena leucocephala) emerged as the topperforming species by composite growth index and are recommended for priority deployment in red mud rehabilitation. Natural regeneration of ten plant species and return of diverse fauna confirm progressive ecological recovery. The study provides a replicable, evidence-based model for rehabilitation of industrial red mud wastelands.
Location: T E 15 New Biology building
Literature cited 1: Bradshaw A. (1997). Restoration of mined lands: using natural processes. Ecological engineering, 8(4): 255-269. DOI: https://doi.org/10.1016/S0925-8574(97)00022-0 Indian Minerals Yearbook (2023). Indian Bureau of Mines, Ministry of Mines, Government of India.
Literature cited 2: Jones B.E.H. and Haynes R.J. (2011). Bauxite processing residue: a critical review of its formation, properties, storage, and revegetation. Critical Reviews in Environmental Science and Technology, 41(3): 271-315. DOI: https://doi.org/10.1080/10643380902800000 Nayak K.C., Pathania A. and Pathania A.R. (2024). Red mud: Characteristics, utilization and environmental remediation strategies in the aluminium industry. Materials Today: Proceedings. DOI: 10.1016/j.matpr.2024.05.026. DOI: https://doi.org/10.1016/j.matpr.2024.05.026

ID: 66742
Title: Vegetation Dynamics in Silica Mines Degraded Lands after Thirty Years of Restoration
Author: Sanjay Singh, Anubha Srivastav, Alok Yadav, Satya Vrat Singh
Editor: Richa Misra
Year: 2026
Publisher: Indian Council of Forestry Research & Education.
Source: ENVIS, CES & EWRG, CES
Reference: The Indian Forester Vol. 152 (6A) June 26 Pg No. 65-73 (2026)
Subject: Vegetation Dynamics in Silica Mines Degraded Lands after Thirty Years of Restoration
Keywords: Biodiversity Indices, Eco-restoration, Silica Mine Spoils, Species Richness, Vindhyan Hill Tract.
Abstract: Silica mining in the Shankargarh region of Prayagraj, India, has caused extensive land degradation and biodiversity loss over four decades. This study evaluates the ecological recovery of these mine spoils thirty years after the initiation of strategic ecorestoration. Using a successional restoration framework, fifteen resilient native species were introduced alongside moisture conservation techniques. Comparative analysis of vegetation dynamics across three strata (herbs, shrubs, and trees) revealed significant ecological uplift. Post-restoration, species richness surged across all layers, with the herbaceous understory showing the most dramatic increase (from 22 to 107 species). True Diversity (D) effectively doubled in the tree layer (from 8.50 to 17.29) and increased nearly five-fold in the herbs (from 16.59 to 75.19). Concomitant improvements in soil health, including a reduction in pH (6.5 to 6.2) and increased Electrical Conductivity (0.13 to 0.18 dS/m), signify the re-establishment of a functional, nutrient-cycling ecosystem. These results provide a robust scientific framework for the sustainable restoration of silica-mined landscapes in tropical dry deciduous regions.
Location: T E 15 New Biology building
Literature cited 1: Bandyopadhyay S. and Maiti S.K. (2022). Steering restoration of coal mining degraded ecosystem to achieve sustainable development goal-13 (climate action): United Nations decade of ecosystem restoration (2021–2030). Environmental Science and Pollution Research, 29: 88383-88409. https://doi.org/10.1007/s11356-022-23699-x DOI: https://doi.org/10.1007/s11356-022-23699-x Barnes B.V., Zak D.R., Denton S.R. and Spurr S.H. (1998). Forest Ecology. 4th Edition, Wiley and Sons, New York.
Literature cited 2: Bora A. and Bhattacharya M. (2017). Phyto-diversity and community structure of tree species in a tropical forest. Journal of Applied and Natural Science, 9(2): 1180-1185. Bradshaw A.D. and Chadwick M.J. (1980). The Reconstruction of Land. Blackwell Scientific Publication, Oxford.

ID: 66741
Title: An Empirical Analysis on Extent of Adoption of Drought Management Strategies in Different Vulnerable Districts of Tamil Nadu, India
Author: G. Balaganesh, Ravinder Malhotra, R. Sendhil
Editor: Richa Misra
Year: 2026
Publisher: Indian Council of Forestry Research & Education.
Source: ENVIS, CES & EWRG, CES
Reference: The Indian Forester Vol. 152 (6A) June 26 Pg No. 57-64 (2026)
Subject: An Empirical Analysis on Extent of Adoption of Drought Management Strategies in Different Vulnerable Districts of Tamil Nadu, India
Keywords: Drought management strategies, Crop and dairy, Intensity of adoption.
Abstract: Adoption of drought management strategies becomes essential to reduce the adverse effects of drought. This study has developed a new extent (intensity) of adoption, using crop and dairy drought management strategies in different vulnerable districts of Tamil Nadu, India. Most of the studies have measured the intensity of adoption in either crop or dairy separately, but not combined. In addition, there is no appropriate measurement for extent of adoption. Hence, this study fulfils this research gap using gross intensity of adoption. There were 6, 7 and 5 paddy strategies identified in high (Ramanathapuram), moderate (Nagapattinam) and less vulnerable districts (Erode), respectively, whereas six dairy strategies were found in each district. The high-level and low-level adopters were significantly different in all the districts. The study found that paddy intensity of adoption was highest in Ramanathapuram (0.58), followed by Erode (0.47) due to more adoption of drought management strategies in crops. In contrast, the dairy intensity of adoption was highest in Erode (0.50), followed by Nagapattinam (0.46) because of more adoption of drought management strategies in dairy. The gross intensity of adoption was highest in Erode (0.52), followed by Ramanathapuram (0.51), whereas least was observed in Nagapattinam (0.44). This shows that households in Erode have more intensity to adopt the management strategies in comparison to the other two districts. This could be attributed to the prevailing drought condition in Ramanathapuram and combination of frequent occurrences of cyclones and prevailing drought situation in Nagapattinam. Adoption could be improved by reducing the adoption gap and increasing awareness through various programmes.
Location: T E 15 New Biology building
Literature cited 1: Ajaykumar R. and Krishnasamy S.M. (2018). Effect of PPFM and PGRs on crop growth rate in transplanted rice under moisture stress condition. Journal of Pharmacognosy and Phytochemistry, 7(4): 2366-2368. Asfaw S., Shiferaw B., Simtowe F. and Haile M.B. (2011). Agricultural technology adoption, seed access constraints and commercialization in Ethiopia. Journal of Development and Agricultural Economics, 3(9): 436-447.
Literature cited 2: Awotide B.A., Abdoulaye T., Alene A. and Manyong V.M. (2014). Assessing the extent of adoption and determinants of improved cassava varieties in South-Western Nigeria. Journal of Development and Agricultural Economics, 6(9): 376-385. DOI: https://doi.org/10.5897/JDAE2014.0559 Balaganesh G., Malhotra R. and Sendhil R. (2025). Development of household vulnerability index to climate change induced drought: empirical evidence from rural farm households in Tamil Nadu, India. Environment, Development and Sustainability. https://doi.org/10.1007/s10668‐025‐06095‐6 DOI: https://doi.org/10.1007/s10668-025-06095-6

ID: 66740
Title: Urban Green Infrastructure for Carbon Sequestration: Integrating Land Restoration, Biodiversity Conservation and Climate Mitigation
Author: Abhishek Nandal, Surender Singh Yadav, Priyanka Sharma, Kailash Chand Meena, Sakshi Saini, Gaurav Mishra, Amrender Singh Rao
Editor: Richa Misra
Year: 2026
Publisher: Indian Council of Forestry Research & Education.
Source: ENVIS, CES & EWRG, CES
Reference: The Indian Forester Vol. 152 (6A) June 26 Pg No. 49-56 (2026)
Subject: Urban Green Infrastructure for Carbon Sequestration: Integrating Land Restoration, Biodiversity Conservation and Climate Mitigation
Keywords: Urban Green Infrastructure (UGI), Carbon sequestration, Land restoration, Biodiversity conservation, Climate mitigation.
Abstract: Urban regions account for around 70% of worldwide Carbon dioxide (CO ) 2 emissions despite comprising less than 2% of the land; yet urban green infrastructure (UGI) remains inadequately employed as a climate mitigation approach. This paper formulates a cohesive framework that identifies carbon sequestration, land restoration, and biodiversity conservation as interconnected elements of urban climate initiatives. Using peer-reviewed literature, it demonstrates that UGI types vary in carbon storage capacity; however, results are significantly affected by species composition, soil health, management approaches, and urban environmental limitations. Land restoration strategies, such as brown field rehabilitation, phytoremediation, and soil supplements, coupled with biodiversity-focused design that prioritizes native species and ecological linkages, are recognized as essential for enduring carbon sequestration. Case studies from Singapore, Medellín, New York City, and several Indian cities illustrate that UGI can yield quantifiable climatic and ancillary benefits, such as urban cooling, storm water management, and biodiversity restoration, when underpinned by sustained governance and oversight. Nonetheless, fragmented planning, insufficient funding, the absence of uniform carbon accounting, and equity issues, including green gentrification, hinder broader implementation. The article advocates for enforceable planning objectives, standardized monitoring, reporting, and verification mechanisms, incorporation into national climate programs, and equity safeguards to facilitate scalable and equitable implementation.
Location: T E 15 New Biology building
Literature cited 1: Behera S.K., Mishra S., Sahu N., Manika N., Singh S.N., Anto S., Kumar R., Husain R., Verma A.K. and Pandey N. (2022). Assessment of carbon sequestration potential of tropical tree species for urban forestry in India. Ecological Engineering, 181: 106692. DOI: https://doi.org/10.1016/j.ecoleng.2022.106692 Bherwani H., Banerji T. and Menon R. (2024). Role and value of urban forests in carbon sequestration: Review and assessment in Indian context. Environment, Development and Sustainability, 26(1): 603–626. DOI: https://doi.org/10.1007/s10668-022-02725-5
Literature cited 2: Cambou A., Chevallier T., Barthès B.G., Derrien D., Cannavo P., Bouchard A., Allory V., Schwartz C. and Vidal-Beaudet L. (2023). The impact of urbanization on soil organic carbon stocks and particle size and density fractions. Journal of Soils and Sediments, 23(2): 792–803. DOI: https://doi.org/10.1007/s11368-022-03352-3 Celletti S., Poreba L., Wawer R., Padoan E., Comis S., Bartosiewicz B. and Schiavon M. (2025). The potential of nature-based solutions for urban soils: Focus on green infrastructure and bioremediation. Frontiers in Environmental Science, 13. DOI: https://doi.org/10.3389/fenvs.2025.1634662

ID: 66739
Title: Forest Carbon Sequestration by a Pine (Pinus roxburghii) dominant landscape of Uttarakhand and its climate change implications
Author: Harshi Jain, Manoj Kumar, Subrata Nandy
Editor: Richa Misra
Year: 2026
Publisher: Indian Council of Forestry Research & Education.
Source: ENVIS, CES & EWRG, CES
Reference: The Indian Forester Vol. 152 (6A) June 26 Pg No. 35-48 (2026)
Subject: Forest Carbon Sequestration by a Pine (Pinus roxburghii) dominant landscape of Uttarakhand and its climate change implications
Keywords: Forest carbon stock, Aboveground biomass, Machine learning, Random Forest, Remote sensing, Satellite-derived variables, Vegetation indices.
Abstract: This study assesses the forest carbon sequestration in a Chir pine (Pinus roxburghii) dominated landscape of the Almora Forest Division, Uttarakhand, India, and examines its implications for climate change mitigation. Given the spatial heterogeneity of forest ecosystems and the limitations of conventional field-based methods, an integrated approach combining field observations, multi-source satellite data, and machine learning was adopted to generate wall-to-wall estimates of aboveground carbon (AGC). A total of 40 sample plots (0.1 ha each) were established across the study area, where tree-level measurements were used to estimate aboveground biomass (AGB) through volumetric and allometric equations, subsequently converted to carbon stock using a standard factor (0.47). Satellite-derived variables from Sentinel-1 (SAR), Sentinel-2 (optical) and topographic variables derived from SRTM data were utilized as predictors in Random Forest algorithm for modeling AGB/AGC estimation. The results revealed substantial spatial variability in AGC, ranging from 47 to 121 Mg ha-1, with a mean value of 75.21 Mg ha-1. The integration of optical and radar data provided complementary insights into vegetation structure and condition, enhancing model robustness. The findings underscore the significance of Chir pine forests as regional carbon reservoirs despite their relatively lower biomass compared to broadleaf systems. The study demonstrates the effectiveness of machine learning and remote sensing integration for largescale carbon mapping and highlights its potential for supporting climate change mitigation strategies, carbon accounting frameworks, and sustainable forest management in Himalayan ecosystems.
Location: T E 15 New Biology building
Literature cited 1: Bombelli A., Avitabile V., Balzter H. and Wulder M. (2009). Assessment of the status of the development of the standards for the Terrestrial Essential Climate Variables-T12-BIOMASS. Global Terrestrial Observing System, FAO. Bondeau A., Smith P.C., Zaehle S., Schaphoff S., Lucht W., Cramer W., Gerten D., LOTZE-CAMPEN H., Muller C. and Reichstein M. (2007). Modelling the role of agriculture for the 20th century global terrestrial carbon balance. Global Change Biology, 13(3): 679–706. DOI: https://doi.org/10.1111/j.1365-2486.2006.01305.x
Literature cited 2: Breiman L. (2001). Random forests. Machine Learning, 45(1): 5–32. https://doi.org/10.1023/A:1010933404324 DOI: https://doi.org/10.1023/A:1010933404324 Brogaard S. and Olafsdottir R. (1997). Ground-truths or Ground-lies?: Environmental sampling for remote sensing application exemplified by vegetation cover data. Phys. Geogr., (1):1402–9006.