Current Affairs 26 February 2026
Content Rajasthan Scraps Two-Child Norm for Local Body and Panchayat Elections After Three Decades Eurasian Diving Duck’s Presence in Kaziranga National Park Triggers Climate Change Concern How Are Indian Firms Training Large Language Models (LLMs)? What Are Carbon Capture and Utilisation (CCU) Technologies? Temperature Spikes Lead to Change in El Niño Labelling Tigers Are Behaving Differently: State of India’s Environment Report 2026 SOE 2026: Extinction Tracker — Anthropocene and Accelerating Biodiversity Loss Rajasthan scraps two-child norm for local body, panchayat polls after three decades A. Issue in Brief Ahead of civic polls, the Rajasthan Cabinet approved removal of the two-child norm that disqualified individuals with more than two children from contesting panchayat and municipal elections. The restriction, introduced in 1995 under the Bhairon Singh Shekhawat government, will be amended through changes to the Rajasthan Panchayati Raj Act, 1994 (Section 19) and Rajasthan Municipalities Act, 2009 (Section 24). The State cited declining fertility rates — from 3.6 (1991–94) to 2.0 currently — as justification for repeal. Relevance GS II – Polity & Constitution Articles 243F & 243V: State power to prescribe disqualification for local bodies. Articles 14 & 21: Equality and reproductive autonomy. Judicial precedent: Javed vs State of Haryana (2003). Tension between social reform and individual rights. B. Static Background The two-child norm was adopted by several States in the 1990s as a population control measure linked to local governance eligibility. The Supreme Court in Javed vs State of Haryana upheld similar provisions in Haryana, ruling that disqualification did not violate fundamental rights. India’s Total Fertility Rate (TFR) declined to 2.0 (NFHS-5, 2019–21), below replacement level (2.1). Rajasthan’s TFR has also fallen significantly over the past three decades, reflecting demographic transition. C. Key Dimensions 1. Constitutional & Legal Dimension Disqualification criteria relate to Article 243F (Panchayats) and Article 243V (Municipalities), allowing States to prescribe eligibility conditions. Critics argue the norm indirectly infringed Article 14 (equality) and Article 21 (reproductive autonomy) by penalising personal choices. Removal signals shift toward aligning electoral eligibility with contemporary demographic realities. 2. Demographic Context India has entered the late demographic transition phase, with declining fertility and increasing median age. With TFR at 2.0, population stabilisation policies are moving from coercive norms to rights-based family planning approaches. 3. Governance & Democratic Principles Disqualification sometimes led to concealment of births or abandonment of children to retain eligibility. Removal may broaden political participation at grassroots level. 4. Political & Social Debate Supporters view repeal as recognition of demographic maturity and democratic inclusivity. Critics argue rollback may dilute population stabilisation messaging amid national debates on demographic balance. 5. Comparative State Experience States such as Haryana, Madhya Pradesh, Andhra Pradesh, Odisha earlier implemented similar norms; some later diluted or repealed them. Evidence suggests such norms had limited impact on fertility decline, which is driven more by education, urbanisation and women’s empowerment. D. Critical Analysis Population Control vs Rights-Based Approach Coercive eligibility restrictions risk undermining reproductive rights and bodily autonomy. Fertility decline in India largely attributed to female literacy, access to contraception and economic transition, not electoral disqualification rules. Democratic Legitimacy Local self-government institutions under the 73rd and 74th Constitutional Amendments aim to enhance inclusive grassroots representation. Eligibility restrictions unrelated to governance capacity may conflict with democratic ethos. Gendered Impact Women often bore disproportionate burden due to patriarchal family structures controlling reproductive decisions. Norm incentivised son preference in some cases, potentially aggravating sex ratio distortions. E. Way Forward Strengthen voluntary, rights-based population stabilisation strategies focusing on education, maternal health and access to contraception. Promote demographic literacy aligned with evidence-based policy rather than political rhetoric. Ensure local governance reforms prioritise capacity, transparency and accountability, not demographic eligibility. Integrate demographic planning with ageing population preparedness and labour force strategy. F. Exam Orientation Prelims Pointers Two-child norm introduced in Rajasthan in 1995. Amendments proposed to Section 19 (Panchayati Raj Act, 1994) and Section 24 (Municipalities Act, 2009). India’s TFR: 2.0 (NFHS-5). SC upheld similar norms in Javed vs State of Haryana (2003). Practice Question (15 Marks) “Coercive population control measures often conflict with democratic and reproductive rights.” Examine the constitutional and socio-demographic implications of the two-child norm in local governance in India.(250 Words) Eurasian diving duck’s presence in Kaziranga National Park triggers climate change concern A. Issue in Brief The 7th Waterbird Census (Jan 4–11, 2026) in Kaziranga National Park and Tiger Reserve recorded the first-ever sighting of the smew (Mergellus albellus) in the Kaziranga landscape. The census documented 105,540 individual waterbirds across 107 species, slightly lower by 6,522 individuals and 17 species compared to 2025. The sighting of the smew, a Eurasian diving duck, signals both wetland health and possible climate-driven range shifts. Relevance GS III – Environment & Biodiversity Wetland ecosystems and migratory bird conservation. Central Asian Flyway dynamics. IUCN threat categories and biodiversity monitoring. GS III – Climate Change Climate-driven range shifts in species. Arctic warming and altered migratory patterns. Wetlands as climate buffers. B. Static Background Kaziranga landscape spans 1,302 sq. km., including Laokhowa and Burhachapori Wildlife Sanctuaries, designated Important Bird Areas (IBAs). Kaziranga is globally renowned for the Indian one-horned rhinoceros, but also forms part of the Central Asian Flyway (CAF) for migratory birds. The smew (Mergellus albellus) breeds in the Eurasian taiga and winters in temperate wetlands; global population estimated at ~130,000, declining due to habitat loss and pollution. Waterbird censuses help monitor migratory patterns, wetland productivity, and IUCN-listed species trends. C. Key Findings of Waterbird Census 2026 Species & Population Trends Total count: 105,540 birds across 107 species. 18 species fall under Critically Endangered, Endangered, Vulnerable or Near Threatened IUCN categories. Top abundant species: bar-headed goose, northern pintail, lesser whistling duck. Wetland-wise Abundance Wetland Bird Count Species Diversity Rowmari Beel 15,661 77 species Donduwa Beel 14,469 71 species Katakhal 4,979 — Sohola 3,612 69 species Khalihamari 3,463 — Survey covered 166 wetlands across 10 ranges, with participation of 120 enumerators and 50 volunteers. D. Ecological & Climate Analysis 1. Smew as Ecological Indicator Smew prefers fish-rich, sheltered wetlands, indicating healthy aquatic ecosystems. Its arrival suggests floodplain resilience but also reflects north-to-south distributional shifts, potentially driven by warming temperatures. 2. Climate-Driven Range Shifts Migratory birds increasingly alter wintering ranges due to Arctic warming and altered precipitation regimes. Climate change affects food availability, ice cover, and wetland hydrology along flyways. 3. Wetland Vulnerability Kaziranga wetlands face pressures from oil pollution, encroachment, hunting and sedimentation. Floodplain ecosystems require connectivity to maintain nutrient cycles and migratory stopovers. 4. Numerical Dip: Alarm or Variation? Decline of 6,522 individuals and 17 species from 2025 may reflect interannual variability rather than systemic decline. However, long-term trend monitoring is essential to distinguish climate impacts from natural fluctuation. Broader Significance Kaziranga’s IBAs form critical nodes in the Central Asian Flyway, which supports over 30% of global waterbird species. Conservation of refuelling sites is vital as migratory birds depend on sequential wetlands across continents. Climate change could convert some wintering grounds into transitional or unsuitable habitats. E. Way Forward Strengthen wetland protection under Ramsar Convention framework and expand community-led anti-encroachment drives. Integrate climate modelling into migratory bird conservation planning for dynamic flyway management. Enhance monitoring of invasive species and water quality to sustain fish populations supporting diving ducks. Promote transboundary cooperation across Central Asian Flyway nations for coordinated conservation. F. Exam Orientation Prelims Pointers Kaziranga landscape area: 1,302 sq. km. 2026 census: 105,540 birds; 107 species. Smew global population: ~130,000. Central Asian Flyway connects Arctic to Indian subcontinent. 18 species recorded fall under IUCN threat categories. Practice Question (15 Marks) “Migratory birds are sentinels of climate change.” Examine how wetland degradation and climate variability are influencing migratory bird patterns in India, with reference to recent findings from Kaziranga.(250 Words) How are Indian firms training LLMs? A. Issue in Brief At the AI Impact Summit, Bengaluru-based startup Sarvam AI released two Large Language Models (LLMs) trained on 35 billion and 105 billion parameters, optimised for Indian languages. Training LLMs domestically faces structural barriers — high GPU costs, electricity demand, limited Indian-language datasets, and capital scarcity. The IndiaAI Mission seeks to reduce entry barriers by subsidising compute access and building shared AI infrastructure. Relevance GS Paper III – Science & Technology Artificial Intelligence and Large Language Models. Compute infrastructure, semiconductor dependence. Mixture of Experts (MoE) architecture efficiency. B. Static Background Large Language Models (LLMs) are deep neural networks trained on massive datasets using GPU clusters, often costing millions of dollars in hardware and power. Frontier global models (e.g., GPT-4-class systems) reportedly use hundreds of billions to over a trillion parameters, requiring enormous compute budgets. IndiaAI Mission (2024) allocated ₹10,372 crore to support compute infrastructure, datasets, skilling and innovation. India hosts 22 scheduled languages, but digital representation remains skewed toward English and a few dominant languages. C. Why is training an LLM on Indian soil with Indian capital a challenge? 1. Compute & Infrastructure Constraints LLM training requires large GPU clusters; high-end GPUs (e.g., H100-class) cost tens of thousands of dollars per unit, with thousands required for large-scale runs. Electricity and cooling costs significantly raise total expenditure, making domestic training capital-intensive. Dependence on imported semiconductors and exposure to export controls limits access to cutting-edge chips. 2. Data Scarcity & Linguistic Imbalance Internet training corpora are dominated by English, European and East Asian languages; Indian languages remain underrepresented. Limited high-quality annotated datasets reduce model performance or require token-heavy translation into English, increasing inference cost. Machine translation pipelines add latency and computational overhead, reducing efficiency. 3. Capital & Business Viability Venture capital in India remains smaller relative to U.S./China AI ecosystems. Absence of immediate monetisation pathways for multilingual LLMs makes large training runs financially risky. Domestic firms lack scale comparable to Big Tech, limiting experimentation capacity. 4. Transparency & Open Ecosystem Gaps While Sarvam AI claims “from–scratch” training and open-source intent, limited availability on global platforms constrains independent validation. Open scrutiny is critical for benchmarking credibility and fostering ecosystem trust. D. How has the IndiaAI Mission subsidised LLM training? Shared Compute Infrastructure Establishment of common compute clusters, lowering entry barriers for startups and research institutions. Subsidised GPU access reduces upfront capital requirement for training runs. Financial & Institutional Support Dedicated funding pool of ₹10,372 crore for AI innovation, including datasets and skilling. Support for academic-industry collaborations (e.g., IIT-incubated ventures like BharatGen, which trained a 17-billion-parameter multilingual model). DPI-based Approach Leveraging India’s Digital Public Infrastructure (DPI) ecosystem (Aadhaar, UPI, ONDC datasets) for domain-specific AI applications. Encouraging sector-focused LLMs in education, healthcare, governance, rather than competing immediately with frontier global models. E. Why is Mixture of Experts (MoE) architecture cheaper? Traditional Dense Models In conventional LLMs, all parameters are activated during inference, making each query computationally expensive. Larger parameter counts proportionally increase compute demand and inference cost. MoE Architecture Advantage Mixture of Experts (MoE) activates only a subset of parameters (“experts”) per query. Reduces active compute requirement, lowering energy consumption and latency. Enables models with large total parameters to operate at cost closer to smaller models. Cost & Efficiency Gains MoE significantly reduces training and inference expenditure, maintaining output quality while optimising resource usage. Particularly suited for resource-constrained ecosystems like India, where compute cost sensitivity is high. F. Critical Analysis Strategic Trade-offs Smaller parameter models (e.g., 105B vs trillion-parameter frontier models) may offer contextual alignment but lack depth of global paid models. Focusing on accuracy and alignment for Indian context may be strategically wiser than racing for scale. Digital Sovereignty Imperative Training on Indian soil enhances data sovereignty, linguistic inclusion and geopolitical autonomy. Dependence on foreign LLM APIs risks economic outflows and regulatory vulnerability. Ecosystem Risks Subsidies without market-driven use cases risk inefficient capital allocation. Overemphasis on foundational models may neglect applied AI layers where economic returns are faster. G. Way Forward Expand subsidised GPU clusters with long-term semiconductor ecosystem strategy under India Semiconductor Mission. Invest in high-quality multilingual corpora across 22 scheduled languages, including low-resource dialects. Encourage modular AI stack: smaller efficient LLMs + domain-specific fine-tuning. Promote open benchmarking and peer validation to build global credibility. Align AI compute strategy with renewable energy expansion to reduce training carbon footprint. H. Exam Orientation Prelims Pointers LLMs trained using GPU clusters. IndiaAI Mission allocation: ₹10,372 crore. MoE activates only fraction of parameters during inference. Sarvam AI models: 35B & 105B parameters. BharatGen model: 17B parameters. Practice Question (15 Marks) “Building foundational AI models within India is essential for digital sovereignty but economically challenging.” Discuss the structural constraints in domestic LLM training and evaluate how policy interventions like the IndiaAI Mission can bridge the gap.(250 Words) What are carbon capture and utilisation technologies? A. Issue in Brief Carbon Capture and Utilisation (CCU) technologies capture CO₂ from industrial sources or air and convert it into fuels, chemicals, building materials or polymers, embedding carbon into economic value chains. India is the world’s third-largest CO₂ emitter, with emissions concentrated in power, cement, steel and chemicals — sectors classified as hard-to-abate. Scaling CCU in India faces three major risks: cost competitiveness, infrastructure gaps, and regulatory uncertainty, limiting investor confidence and market demand. Relevance GS III – Environment & Climate Change Industrial decarbonisation in hard-to-abate sectors. India’s Net Zero target (2070). Circular carbon economy. GS III – Economy & Industry Cement and steel emissions (~15% global CO₂). Green hydrogen integration. Cluster-based industrial deployment. B. Static Background Carbon Capture and Storage (CCS): CO₂ captured and permanently stored underground. Carbon Capture and Utilisation (CCU): CO₂ captured and reused as industrial input. India’s Net Zero target: 2070. Global CO₂ emissions exceed 37 billion tonnes annually. Cement and steel sectors together account for nearly 15% of global CO₂ emissions. India’s Draft CCUS Roadmap (2030) by the Ministry of Petroleum & Natural Gas identifies industrial clusters suitable for deployment. C. How can CCU reduce carbon dioxide emissions? 1. Industrial Emission Abatement Captures CO₂ from point sources (cement kilns, steel furnaces, refineries) before atmospheric release. Particularly relevant for process emissions (e.g., limestone calcination in cement), where electrification alone cannot eliminate CO₂. 2. Carbon as Feedstock Converts CO₂ into synthetic fuels (e-methanol), urea, polymers, lightweight concrete blocks, olefins, reducing fossil feedstock demand. When combined with green hydrogen, CO₂-derived fuels can close the carbon loop in hard-to-electrify sectors like aviation. 3. Bio-CCU and Circular Economy Integrates with biogas and biomass streams, converting CO₂ into bio-alcohols and specialty chemicals, improving waste valorisation. Enables transition from linear “extract-use-dispose” model to circular carbon economy. D. Global Policy Frameworks EU Bioeconomy Strategy Promotes sustainable use of biological resources and supports CCU as part of low-carbon industrial transformation. Links CO₂ utilisation with bio-based materials and industrial decarbonisation targets under EU Green Deal. EU Circular Economy Action Plan (2020) Integrates CCU into circular production systems, reducing reliance on virgin fossil inputs. Encourages eco-design, carbon-neutral materials and life-cycle emissions accounting. Other Global Examples U.S.: Section 45Q tax credits incentivise CCU and CCS deployment. Belgium: ArcelorMittal–Mitsubishi–D-CRBN project converts CO₂ into carbon monoxide for steel production. UAE: Al Reyadah integrates CCU with enhanced oil recovery and chemical production using green hydrogen. E. Where does India stand? Department of Science & Technology has developed R&D roadmap for CCU technologies. Draft CCUS 2030 roadmap identifies sectoral pilots. Industry pilots: Organic Recycling Systems Limited (ORSL) piloting Bio-CCU platform. F. Critical Challenges in Scaling CCU in India 1. Cost Competitiveness CCU remains energy-intensive, raising production costs compared to fossil-derived alternatives. Without carbon pricing or tax credits, CCU products struggle in price-sensitive markets. 2. Infrastructure Readiness Requires industrial clusters, CO₂ transport pipelines, and hydrogen integration, unevenly developed across India. Lack of integrated CCU hubs limits economies of scale. 3. Regulatory & Market Uncertainty Absence of clear certification standards for CO₂-derived products deters investment. No comprehensive carbon pricing or compliance mechanism to create demand pull. G. How can India scale up CCU technology? Policy Incentives Introduce production-linked incentives (PLI) or tax credits for CCU products, similar to U.S. 45Q model. Develop carbon pricing or tradable credit mechanisms to internalise environmental cost. Cluster-Based Deployment Create industrial CCU hubs in steel–cement belts (e.g., eastern India) to enable shared pipelines and hydrogen supply. Integrate CCU into National Hydrogen Mission for green hydrogen-based CO₂ conversion. Standards & Certification Develop national standards for CO₂-derived fuels, polymers and building materials, enabling export competitiveness. Establish lifecycle emissions accounting framework aligned with EU carbon border adjustment norms. Innovation & Public–Private Partnerships Expand DST-funded research testbeds and scale pilot projects to commercial demonstration. Leverage India’s chemical and refinery ecosystem for rapid scale-up. H. Strategic Significance CCU bridges decarbonisation and industrial growth, supporting India’s Make in India and net-zero commitments. Provides pathway for hard-to-abate sectors where electrification alone is insufficient. Aligns with global shift toward circular carbon economy. I. Exam Orientation Prelims Pointers CCU ≠ CCS (utilisation vs storage). India’s Net Zero target: 2070. India = 3rd largest CO₂ emitter globally. EU Circular Economy Action Plan: 2020. U.S. 45Q tax credit supports CCU/CCS. Practice Question (15 Marks) “Carbon Capture and Utilisation offers a bridge between industrial growth and climate responsibility.” Discuss its potential and limitations in the Indian context, and outline policy measures needed for scaling CCU technologies. Temperature spikes lead to change in El Nino labelling A. Issue in Brief A study published in Nature Geoscience links the recent global temperature surge (2023–2025) to a combination of anthropogenic climate change and transition from a prolonged La Niña (2020–2023) to El Niño (2023). Earth’s energy imbalance — the gap between incoming solar radiation and outgoing heat — sharply increased in 2022, trapping more heat in the climate system. Scientists estimate nearly three-fourths of the recent energy imbalance increase is attributable to long-term greenhouse gas accumulation combined with ENSO phase transition. The National Oceanic and Atmospheric Administration (NOAA) updated its classification thresholds for El Niño–La Niña events due to rapid ocean warming. Relevance GS I – Geography (Climatology) ENSO (El Niño–La Niña cycle). Sea surface temperature anomalies. Earth’s energy imbalance (W/m²). GS III – Environment & Climate Change Anthropogenic warming + natural variability interaction. Ocean heat absorption (~90% excess heat). Extreme weather intensification. B. Static Background El Niño–Southern Oscillation (ENSO) is a natural ocean–atmosphere cycle in the equatorial Pacific affecting global weather patterns. El Niño: Warmer-than-average sea surface temperatures (SSTs) in central/eastern Pacific → raises global temperatures. La Niña: Cooler-than-average SSTs → temporarily suppresses global temperature rise. Earth’s energy imbalance is measured in watts per square metre (W/m²); persistent positive imbalance indicates accumulating heat in oceans. About 90% of excess heat from global warming is absorbed by oceans. C. Key Dimensions ENSO Phase Shift and Temperature Spike Period ENSO Phase Climate Impact 2020–2023 “Triple-dip” La Niña Suppressed surface warming; deeper ocean heat storage 2023–2025 El Niño transition Amplified surface warming; record temperatures From early 2023, global average temperatures jumped above the long-term warming trend. The unusual three-year La Niña delayed heat release, followed by rapid warming during El Niño onset. Earth’s Energy Imbalance Study estimates ~75% of recent imbalance rise linked to combined human-driven warming and ENSO shift. About 23% of the imbalance attributed specifically to prolonged La Niña dynamics. Slightly more than 50% of warming contribution traced to greenhouse gases from coal, oil and gas combustion. Reclassification of ENSO Events Due to overall ocean warming, NOAA altered SST baselines for declaring ENSO phases. Likely outcome: More events classified as La Niña and fewer as El Niño, because baseline warming shifts temperature thresholds. Reflects climate change altering natural variability parameters. D. Critical Analysis Interaction of Natural Variability and Anthropogenic Forcing ENSO cycles are natural, but baseline warming intensifies their impacts, creating higher temperature peaks during El Niño years. The “triple-dip” La Niña stored heat at deeper layers, releasing it during El Niño, compounding warming. Implications for Climate Modelling Altered ENSO thresholds complicate long-term climate projections and risk misinterpretation of short-term temperature spikes. Climate communication must distinguish between trend (anthropogenic warming) and variability (ENSO-driven fluctuations). Extreme Weather Consequences El Niño increases risks of heatwaves, droughts in India and Australia, floods in South America, and marine heatwaves. Ocean warming intensifies coral bleaching, glacier melt and tropical cyclone intensity. Broader Drivers of Temperature Spike Scientists also examine reduced sulphur emissions from shipping (post-IMO regulations), volcanic activity and solar variability as contributing factors. However, greenhouse gas concentration remains primary driver; CO₂ levels exceed 420 ppm, highest in human history. Indian Context El Niño historically correlates with weak southwest monsoon, impacting agriculture and food inflation. Rising baseline temperatures intensify heatwave frequency, particularly in northern and central India. India’s vulnerability underscores importance of climate adaptation and emission mitigation under its Nationally Determined Contributions (NDCs). E. Way Forward Accelerate decarbonisation to reduce long-term energy imbalance through renewable transition and energy efficiency. Strengthen early-warning systems for ENSO-linked extreme weather, integrating IMD forecasting with disaster preparedness. Enhance ocean monitoring networks in the Indo-Pacific to improve predictive modelling of ENSO–climate interactions. Improve public climate literacy distinguishing natural cycles from anthropogenic trends. F. Exam Orientation Prelims Pointers ENSO = El Niño + La Niña cycle in equatorial Pacific. “Triple-dip” La Niña: 2020–2023. Energy imbalance = difference between incoming solar radiation and outgoing heat. ~75% of recent imbalance rise linked to GHG + ENSO shift. NOAA revised ENSO classification thresholds due to ocean warming. Practice Question (15 Marks) “El Niño and La Niña are natural climatic phenomena, yet their impacts are intensifying in a warming world.” Discuss how anthropogenic climate change interacts with ENSO cycles and its implications for global and Indian climate stability. Tigers are behaving differently: State of India’s Environment report 2026 A. Issue in Brief The State of India’s Environment 2026 (SOE 2026) released by the Centre for Science and Environment highlights behavioural shifts in India’s tiger populations linked to ecological degradation and habitat saturation. Between January–June 2025, at least 43 human deaths occurred near tiger reserves (compared to 44 during the same period in 2024), with instances of partial consumption of victims reported. Approximately 40% of tiger habitats across 20 states are shared with nearly 60 million people, intensifying human–tiger interface zones. Relevance GS III – Environment & Biodiversity Human–wildlife conflict dynamics. Wildlife Protection Act, 1972. Project Tiger and NTCA governance. GS III – Ecology Invasive species (Lantana camara). Habitat fragmentation and carrying capacity. Predator–prey dynamics. B. Static Background India hosts over 3,000 tigers (All India Tiger Estimation 2022), accounting for nearly 75% of the global wild tiger population. The National Tiger Conservation Authority (NTCA) oversees Project Tiger (launched 1973) with 50+ tiger reserves. Tiger conservation success has led to population recovery but also territorial saturation within core reserves, pushing dispersal into buffer and revenue lands. Human–wildlife conflict is recognised under the Wildlife Protection Act, 1972 and mitigated via compensation and conflict response protocols. C. Key Dimensions 1. Rising Human–Tiger Interactions Tigers rarely become habitual man-eaters; attacks typically rise when individuals are injured, old, prey-deprived, or forced into proximity with humans. Saturation of core reserves compels dispersing sub-adult tigers into agro-pastoral landscapes, increasing encounter probability. In 2025 (Jan–June), 4 of 43 attacks involved partial consumption, indicating altered feeding responses in select cases. 2. Habitat Transformation and Invasive Species The invasive plant Lantana camara, introduced in the 19th century, now occupies nearly 50% of forest, scrubland and village commons areas. Lantana suppresses native grasses, reducing availability of wild herbivores such as chital and sambar. Dense lantana thickets provide low-visibility, predator-friendly cover, enabling ambush hunting near livestock-grazing zones. 3. Prey Shift: From Wild Ungulates to Cattle Domestic cattle offer higher caloric returns compared to smaller wild prey species. In reserves like Bandhavgarh Tiger Reserve and Tadoba-Andhari Tiger Reserve, tigers increasingly utilise lantana-dominated patches outside core zones as refuges and hunting grounds. Compensation mechanisms for livestock depredation may reduce local resentment but inadvertently normalise tiger presence in village economies. 4. Behavioural Ecology Shift Experts note potential loss of innate fear of humans, especially among younger dispersing individuals raised near human-modified landscapes. Ecological overcrowding, fragmentation and anthropogenic pressure create adaptive behavioural responses in apex predators. Such shifts reflect ecological plasticity but increase conflict risk and management complexity. D. Critical Analysis Conservation Paradox Tiger population growth signals conservation success, yet habitat carrying capacity limitations produce ecological spillover effects. Protection-centric strategy without landscape-level habitat expansion risks conflict escalation. Invasive Species Governance Gap Despite ecological threat, lantana management remains fragmented and underfunded. Removal is labour-intensive and requires long-term restoration of native grasses and prey base. Socio-economic Interface Livestock compensation schemes mitigate hostility but may create “human subsidy dependence”, altering predator behaviour. Nearly 60 million people sharing tiger landscapes indicates structural coexistence challenge rather than isolated incidents. Climate and Ecological Stress Climate variability alters prey distribution and water availability, potentially intensifying territorial competition. Fragmented corridors restrict safe dispersal, pushing tigers into peri-urban and agricultural spaces. E. Way Forward Shift from reserve-centric conservation to landscape-level ecological planning, strengthening wildlife corridors and buffer management. Large-scale lantana eradication and grassland restoration to rebuild wild prey base and reduce cattle predation. Community-based coexistence models integrating early warning systems, predator-proof livestock enclosures and rapid compensation delivery. Scientific monitoring of behavioural ecology through camera traps, GPS collars and conflict mapping analytics. Align tiger conservation with sustainable land-use planning, balancing ecological carrying capacity with human settlement expansion. F. Exam Orientation Prelims Pointers 43 human deaths (Jan–June 2025) near tiger reserves. 40% of tiger territory shared with 60 million people. Lantana camara occupies ~50% of affected forest landscapes. India hosts ~75% of global wild tiger population. Practice Question (15 Marks) “India’s tiger conservation success has created new ecological and socio-economic challenges.” Examine how habitat degradation and invasive species are altering predator behaviour and suggest measures for sustainable human–wildlife coexistence. SOE 2026: Extinction Tracker — Anthropocene & Accelerating Biodiversity Loss A. Issue in Brief SOE 2026 – Extinction Tracker highlights accelerating species loss globally, with updated data from the International Union for Conservation of Nature (IUCN) Red List. Study in Global Change Biology projects ~8,000 vertebrate species could face unsuitable thermal conditions across 52% of their range under worst-case climate scenarios. IUCN Red List now covers 169,420 species, of which 47,187 are threatened with extinction, signalling systemic biodiversity collapse. Nearly 38% of global tree species and 11.5% of assessed bird species are threatened, reflecting cross-taxa ecological stress. Relevance GS III – Environment & Biodiversity IUCN Red List (169,420 species; 47,187 threatened). Climate–biodiversity nexus. Functional extinction (coral reefs). B. Static Background Anthropocene Epoch: Proposed geological epoch denoting dominant human influence on Earth systems; linked to accelerated extinction rates 100–1,000 times background levels. Convention on Biological Diversity (CBD), 1992: Global framework for conservation, sustainable use and benefit sharing. Kunming–Montreal Global Biodiversity Framework (2022): “30×30 Target” — protect 30% land and sea by 2030. IPBES Global Assessment (2019): Warned that 1 million species face extinction risk globally. India hosts ~8% of global biodiversity across 4 biodiversity hotspots. C. Key Dimensions Global Extinction Signals Taxa / Region Key Finding Data Evidence Vertebrates Extreme heat vulnerability 8,000 species at risk; 30,000 assessed Corals Functional extinction Florida reef-builders collapsed Arctic Seals IUCN status downgrade Hooded seal → Endangered Birds Systemic decline 1,256 of 11,185 (11.5%) threatened Trees Silent crisis 38% species threatened Fungi Under-recognised loss 411 at risk out of 1,300 assessed African freshwater fish Habitat + overfishing 26% of 3,200 species threatened D. Critical Analysis Climate–Biodiversity Nexus Extreme heat and altered precipitation regimes shrink thermal niches, especially for amphibians and reptiles with narrow tolerance bands. Arctic warming occurring nearly four times faster than global average undermines ice-dependent species such as seals. Ecosystem Collapse vs Species Loss “Functional extinction” of staghorn (Acropora cervicornis) and elkhorn (Acropora palmata) corals indicates ecosystem service failure, not merely species decline. Coral reefs support 25% of marine biodiversity; collapse disrupts fisheries, tourism and coastal protection. Habitat & Land Use Pressure Agricultural expansion, urbanisation and logging drive tree species extinction; threatened trees now exceed threatened vertebrates combined. Island ecosystems exhibit disproportionate extinction rates due to invasive species and habitat isolation. Governance Deficits Despite CBD commitments, global biodiversity finance gap estimated at ~$700 billion annually. Protected areas often lack effective management and connectivity corridors. Indian Context Species such as the Great Indian Bustard and Gangetic Dolphin remain critically endangered due to habitat fragmentation and infrastructure expansion. India’s climate vulnerability amplifies biodiversity stress in the Himalayas, Western Ghats and coastal zones. E. Way Forward Implement 30×30 Target with ecological corridors and community-led conservation models. Integrate biodiversity accounting into national income frameworks via natural capital valuation. Strengthen climate mitigation to limit warming below 1.5°C, reducing thermal stress on species. Expand Red List assessments for fungi, invertebrates and freshwater taxa to reduce conservation blind spots. Enhance global biodiversity finance through debt-for-nature swaps and blended climate–nature funds. F. Exam Orientation Prelims Pointers IUCN Red List: 169,420 species assessed; 47,187 threatened. Extreme heat may impact 8,000 vertebrate species. 38% of global tree species threatened. African freshwater fish: 26% threatened. Coral functional extinction differs from species extinction. Practice Question (15 Marks) “Biodiversity loss in the Anthropocene represents not only an ecological crisis but a governance failure.” Examine the drivers of accelerating species extinction and suggest policy measures to reconcile development with conservation.