India’s tiger population has trebled in sixteen years. Over the same period, the real purchasing power of Project Tiger’s budget has fallen by 38 percent. A data-driven examination of what conservation science costs to operate at scale — and what happens to monitoring systems, habitat management technology, and ecological research when the funding does not keep pace with the science.
There is an equation at the heart of large-scale wildlife conservation that is simple in principle and demanding in practice: the effectiveness of any conservation programme is a direct function of the scientific infrastructure sustaining it. Camera-trap grids must be deployed, maintained, and analysed. Patrol data must be collected digitally, transmitted in real time, and interpreted against spatial threat models. Genetic samples must be processed in laboratories equipped for wildlife forensics. Prey density must be assessed through systematic transect surveys. Habitat quality must be monitored against invasive species encroachment, fire regime change, and vegetation succession. Each of these activities has a unit cost — per reserve, per square kilometre, per survey cycle. And when the funding available does not match the science required, the quality of conservation outcomes degrades in measurable, documentable ways.
This is the lens through which NSH examines Project Tiger’s budget trajectory — not as a political or governance question, but as a science funding question of the same category as asking whether India’s space programme has adequate resources to execute its launch schedule, or whether its pharmaceutical research infrastructure is funded at the level its scientific ambitions require. The answer, for India’s tiger conservation science, is: not adequately, and the gap is widening.
The Real-Terms Decline: What the Numbers Show
A rigorous analysis published in Down To Earth in June 2026 provides the most authoritative quantification of Project Tiger’s funding trajectory at constant prices. The analysis applies the Consumer Price Index to convert nominal budget allocations into their real purchasing power at 2008-09 prices — the standard methodology used by economists to compare spending across time periods. The finding is precise and significant: while nominal expenditure on Project Tiger and its successor scheme in 2025-26 stands at ₹290 crore — approximately double the 2008-09 level in absolute rupees — the inflation-adjusted value is only ₹95 crore, compared to ₹154.7 crore in 2008-09. India’s tiger conservation programme is operating with 38 percent less real purchasing power than it commanded seventeen years ago.
The nominal timeline reveals the volatility within this decline. Allocations peaked at ₹370 crore in 2016-17 — their highest nominal level — before declining through successive years to ₹195 crore in the pandemic year of 2020-21, recovering partially to ₹252 crore in 2021-22, falling again to ₹220 crore in 2022-23, and then rising incrementally to the current ₹290 crore. In real terms, even the 2016-17 peak was only ₹121.3 crore at 2008-09 prices — lower than the 2008-09 baseline. The programme has not achieved its 2008-09 real-terms funding level at any point in the past decade.
The denominator has moved in the opposite direction. The number of conservation units under active scientific management has risen from 38 in 2008-09 to over 60 today, including 58 notified tiger reserves and additional conservation landscapes under NTCA oversight. In real per-unit terms, the available science and management budget has contracted even more steeply than the aggregate figures suggest. As the Down To Earth analysis concluded: ‘The allocation available per unit has moved in the opposite direction [to the number of units]. Nominal spending per unit has fluctuated over time, but inflation-adjusted spending per unit has gradually declined.’
PROJECT TIGER FUNDING TRAJECTORY — NOMINAL VS REAL TERMS
| Financial Year | Scheme | Allocation ₹ cr (nominal) | ₹ cr at 2008-09 prices* |
| 2008–09 | Project Tiger (standalone) | 154.7 | 154.7 ← baseline |
| 2016–17 | Project Tiger (standalone) | 370 | ~121.3 |
| 2019–20 | Project Tiger + Elephant | 314 | ~114.5 |
| 2020–21 | Project Tiger (standalone) | 195 | ~68.5 |
| 2022–23 | Project Tiger + Elephant | 220 | ~71.5 |
| 2023–24 | Project Tiger & Elephant (merged) | 240 | ~76.2 |
| 2024–25 | Project Tiger & Elephant (merged) | 245 | ~75.9 |
| 2025–26 | Project Tiger & Elephant (merged) | 290 | ~95.1 ← 38% below baseline |
* Approximate real values calculated using CPI, base year 2008-09 = 100, CPI approximately 305 in 2025-26. Sources: Down To Earth (June 2026), Parliamentary Budget Documents, NTCA Annual Reports. Pre-2023 figures are Project Tiger standalone; post-merger figures are combined Tiger & Elephant allocations.
At constant 2008-09 prices, Project Tiger’s effective budget in 2025-26 is ₹95 crore — 38 percent below its 2008-09 level of ₹154.7 crore, even as the number of reserves has grown from 38 to 58 and the scientific monitoring demands have multiplied.
What Conservation Science Actually Costs
To understand why this funding contraction matters scientifically, it is necessary to map what India’s tiger conservation system must fund at the operational level. The NTCA’s science and management mandate across 58 reserves encompasses five major categories of scientific expenditure, each with rising unit costs driven by technological advancement and geographic expansion.
The first and most fundamental is monitoring infrastructure. The All India Tiger Estimation, conducted quadrennially, is the world’s largest wildlife monitoring exercise. AITE 2022 deployed over 32,000 camera traps across 141,587 sampling units covering 667,000 square kilometres — a scientific operation of extraordinary scale and complexity. Each census cycle costs tens of crore in equipment, training, data processing, and analytical computing. Between census cycles, the M-STrIPES system — the Monitoring System for Tigers, Intensive Protection and Ecological Status — provides the continuous monitoring backbone, digitising daily patrol data from thousands of forest guards across all 58 reserves using GPS-enabled mobile devices integrated with remote sensing and GIS platforms. The system generates real-time spatial data on patrol coverage, wildlife sightings, and threat incidents. Its maintenance, software development, and staff training are recurring scientific costs that do not diminish between census cycles.
The second major cost category is wildlife forensics and genetics. India’s national DNA database for tigers, maintained jointly by WII and NTCA, uses microsatellite and mitochondrial DNA analysis to identify individual animals from scat, hair, and tissue samples, resolve mortality cause-of-death investigations, detect poaching through sample matching, and assess population-level genetic diversity. Each sample processed through this system carries a laboratory cost; the database’s scientific value compounds over time as the genetic record accumulates. Genetic monitoring of corridor connectivity — identifying whether tigers from different reserves are successfully interbreeding — is a critical long-term science investment that requires both continuous sampling and sophisticated analytical capacity.
Third is habitat quality assessment — the scientific measurement of what the forest is actually providing for tigers and their prey. This includes systematic vegetation transects for assessment of lantana and other invasive species burden, prey density estimation through distance sampling, waterhole productivity monitoring, and remote sensing analysis of forest cover change. The NTCA’s 2022 Status of Tigers technical volume confirmed that habitat quality assessments now form an integral part of tiger reserve evaluation — a scientific advance over earlier census cycles that counted tigers without systematically measuring the quality of the habitat supporting them. The sixth census (AITE 2026) has expanded these parameters further.
Fourth is anti-poaching technology, which has undergone substantial scientific advancement. Beyond M-STrIPES patrol monitoring, NTCA reserves now deploy a suite of technologies including the e-Eye thermal camera surveillance system (launched at Corbett in 2016 and now expanded to multiple reserves), providing night-vision capability for detecting human intrusions in darkness; the CaTRAT (Camera Trap Data Repository and Analysis Tool) platform, which uses artificial intelligence and neural network models to automate the identification of individual tigers from camera-trap images, dramatically reducing the analytical time required for individual recognition; and TrailGuard AI, a real-time camera alert system that processes images at the edge — within the camera unit itself — and transmits notifications to rangers’ smartphones within approximately 30 seconds of detecting a tiger or human intruder. Fifth is scientific capacity building — the training of field biologists, wildlife veterinarians, and data analysts whose skills translate conservation science into management outcomes.
TIGER CONSERVATION SCIENCE: THE TECHNOLOGY INVENTORY
▸ M-STrIPES — GPS/GPRS real-time patrol monitoring across all 58 reserves, launched 2010
▸ 32,000+ camera traps deployed for AITE 2022 — world’s largest wildlife monitoring network
▸ CaTRAT AI — neural network individual tiger identification from stripe patterns, eliminating manual sorting
▸ e-Eye thermal cameras — night surveillance at reserve perimeters, Corbett and expanding
▸ TrailGuard AI — edge-computing camera system transmitting tiger/intruder alerts in ~30 seconds
▸ WII-NTCA National Tiger DNA Database — genetic identity, forensic cause-of-death, corridor connectivity
▸ AITE 2026 — first census to systematically include habitat quality parameters (invasive species burden, prey indices)
▸ 141,587 sampling units across 667,000 sq km evaluated in AITE 2022 alone
The Merger’s Scientific Implications
In April 2023, Project Tiger and Project Elephant were formally merged into a single centrally sponsored scheme under the Integrated Development of Wildlife Habitats umbrella. From a scientific management perspective, the merger raises a specific concern that is distinct from questions of political or institutional accountability: the elimination of species-specific budget sub-heads reduces the granularity of performance monitoring available to conservation scientists and reserve managers.
When Project Tiger carried a distinct budget line, it was possible — through parliamentary data, audit reports, and NTCA documentation — to track the relationship between funding levels and specific conservation outcomes: tiger population trends, monitoring coverage, anti-poaching incident rates, and habitat management outputs. The merged scheme’s combined budget for two ecologically distinct flagship species, managed across overlapping but scientifically different landscapes, makes this outcome attribution significantly more difficult. Tiger and elephant conservation science, while sharing some methodological infrastructure (camera-trap monitoring, DNA forensics, corridor assessment), have different species-specific requirements — tigers require individual identification through stripe-pattern AI, elephants require acoustic monitoring and movement corridor GPS telemetry — and a merged budget with no formal sub-allocation formula cannot guarantee that each species’ scientific monitoring needs are adequately resourced.
The September 2024 Union Cabinet approval of the IDWH scheme for the 15th Finance Commission cycle allocated ₹1,575 crore (central share) to Project Tiger over the multi-year period. While this sounds substantial, distributed across 58 tiger reserves, the annual per-reserve central allocation averages approximately ₹5-7 crore — a figure that must cover both capital expenditure (camera equipment, vehicles, technology systems) and recurring scientific operations (monitoring, data processing, staff training, forensic analysis). For a reserve like Nagarjunasagar-Srisailam, covering 3,296 square kilometres across five districts of two states, this per-unit allocation is scientifically thin by any rigorous assessment standard.
The Science-Funding Feedback Loop
The relationship between conservation funding and conservation science outcomes is not linear but multiplicative, and the direction of the multiplier depends on whether the system is in a virtuous or a vicious cycle. In a well-funded system, good monitoring data informs targeted management interventions, which improve habitat quality, which supports prey density, which enables tiger population growth, which generates further scientific data validating the interventions and justifying continued investment. This is the virtuous cycle that produced India’s documented tiger recovery from 1,411 in 2006 to 3,682 in 2022.
In an underfunded system, the cycle reverses. Monitoring coverage thins as camera batteries are not replaced, as M-STrIPES devices are not upgraded, as patrol routes are not fully covered because vehicles are in disrepair. Data gaps emerge in the scientific record. Poaching incidents that would have been detected go unrecorded. Habitat degradation from invasive species — lantana advancing into cleared grasslands between management cycles — goes unmeasured until the next census reveals the damage. The DNA database accumulates samples but forensic analysis is delayed because laboratory capacity is insufficient. Anti-poaching technology deployed three years ago becomes outdated relative to the capabilities now available but unfunded for upgrade.
A 2024 management evaluation by NTCA itself identified persistent scientific management gaps across the reserve network, including inadequate monitoring coverage in some reserves, insufficient prey base assessment frequency, and challenges in maintaining the technological infrastructure of the M-STrIPES system in remote terrain. These are not administrative failures. They are the direct, measurable scientific consequences of operating an expanding conservation programme on a contracting real-terms budget.
The sixth census (AITE 2026) will generate its headline population number in 2027. But it is also generating, for the first time at national scale, systematic habitat quality data — invasive species burden indices, prey density assessments, corridor functionality scores — that will allow conservation scientists to measure not just how many tigers India has but what quality of ecological system is sustaining them. If the budget available to act on those findings remains at its current real-terms level, the sixth census’s expanded scientific scope may produce insights that India lacks the resources to act upon. That is a science policy failure of a particular kind: investing in the diagnosis while underfunding the treatment.
The International Comparison
The scientific case for adequate conservation funding is reinforced by comparative analysis. The 2023 peer-reviewed study in Tropical Conservation Science comparing tiger conservation programme funding across India, Nepal, and Bangladesh found that Nepal’s tiger population doubled between 2010 and 2022 — from 121 to 355 — in significant part because its conservation management adopted a sustainable financing model that ring-fenced conservation revenue from national park entry fees and tourist receipts for direct reinvestment in monitoring and management. India’s tiger reserves generate substantial tourism revenue — Corbett, Ranthambore, Bandhavgarh, and Nagarhole collectively receive hundreds of thousands of visitors annually — but this revenue flows to state consolidated funds rather than being systematically reinvested in reserve-level scientific management.
Nepal’s model is not directly transferable to India’s federal system, but it illustrates a principle that conservation economists have documented across multiple contexts: conservation programmes achieve the best science-to-outcome ratios when funding is stable, predictable, and ring-fenced against competing budget pressures — rather than subject to annual allocation volatility and real-terms erosion. India’s Project Tiger has achieved its remarkable population outcomes despite funding volatility, not because of adequate provision. The scientific question for the next decade is whether that achievement can be sustained, and whether the sixth census’s new habitat quality data can be acted upon, on a budget that has consistently provided less real purchasing power per reserve than it did when the reserve network was less than half its current size.
–Manideep Madavaram
