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philosophy·14 min read

awareness is not intervention

$2.1 billion in nature tech won't close the funding gap. here's what will.

VCs are salivating over nature tech.

$2.1 billion flowed into nature tech in 2024 alone—a 16% increase from the year before. NatureMetrics raised $25 million for biodiversity monitoring. Superorganism launched a $26 million fund for extinction-prevention technologies. Nala Earth, Flox, Wilder Sensing—the list grows weekly.

And that's just nature tech. Add geospatial AI, location intelligence, and real estate analytics—Orbital ($60M), GeoPhy ($33M), Geolava ($4.3M), xMap, Wherobots—and the data layer becomes a multi-billion-dollar industry.

The promise: eDNA sampling, bioacoustics, AI-powered geospatial analysis, wildfire prediction, flood mapping, climate risk modeling, property valuation, site assessment, location intelligence. Technology that will finally make nature's crisis visible.

The assumption: If we can just measure it better, we'll save it.

The assumption is wrong.


what $2.1 billion could actually protect

Imagine if that $2.1 billion went directly to natural assets instead of software about natural assets.

Land TypePrice/HectarePrice/AcreAnnual (1 year)Decade (10 years)
Tropical forest (remote)$500$2024.2M ha (10.4M ac)42M ha (104M ac)
African savanna$1,000$4052.1M ha (5.2M ac)21M ha (52M ac)
US pastureland$4,745$1,920443K ha (1.1M ac)4.4M ha (11M ac)
US conservation easement$7,000$2,833300K ha (741K ac)3M ha (7.4M ac)
Blended global average$2,000$8091.05M ha (2.6M ac)10.5M ha (26M ac)

That's real land. Real protection. Real progress toward 30x30 and Half Earth—not dashboards about the progress we're not making.


the natural cap rate: infinite returns

But area protected is only part of the story. What about the value of what's protected?

The natural cap rate expresses the relationship between annual ecosystem service value (flows) and real asset cost (stocks). It reveals how dramatically undervalued natural assets are compared to traditional real estate.

Natural Asset TypeNatural Cap RateAnnual ESV per $1 Invested
Riparian wetlands766%$7.66
Forested wetlands493%$4.93
Temperate forests281%$2.81
Coastal systems131%$1.31

Compare that to commercial real estate cap rates of 5-8%. Nature delivers returns that make traditional real estate look anemic. Nature delivers 15x-150x higher yields in ecosystem services.

what $2.1B actually generates

Apply these cap rates to the $2.1 billion:

If Invested InCap RateAnnual ESV Protected10-Year ESV100-Year ESV
Riparian wetlands766%$16.1B/year$161B$1.61T
Forested wetlands493%$10.4B/year$104B$1.04T
Temperate forests281%$5.9B/year$59B$590B
Coastal systems131%$2.75B/year$27.5B$275B
Blended (300%)300%$6.3B/year$63B$630B

One year of nature tech VC funding, redirected to natural assets, would protect $6-16 billion in ecosystem services—every year, in perpetuity.

Over 10 years: $63-161 billion in protected value.

Over 100 years: $630B-1.6 trillion.

Forever? Infinite.

The value of investing in nature = ∞

As cost approaches zero (no rent, no debt, no flipping, no holding nature hostage) and flows continue indefinitely, the natural cap rate approaches infinity.

This isn't poetry. It's math.

$2.1 billion per year buys dashboards. Or it buys $6.3 billion in ecosystem services—every year, forever. Choose.


we've known for 35 years

The IPCC published its first assessment in 1990. Thirty-five years ago, the scientific consensus was already forming: human activity is warming the planet, and the consequences will be severe.

Since then:

  • Six more IPCC assessment reports
  • The Dasgupta Review on the economics of biodiversity
  • IPBES assessments documenting the sixth mass extinction
  • TNFD frameworks for nature-related financial disclosure
  • Thousands of peer-reviewed papers quantifying ecosystem services
  • Steady-state economics, ecological economics, natural capital accounting

We are not suffering from a knowledge deficit. We know exactly what is happening.

The 2025 State of Climate Action report found that no sector is on track to meet global climate goals. Not one of 45 indicators is meeting 2030 targets. Experts warn that "a decade of delay has dangerously narrowed the path to 1.5°C."

The IPBES Transformative Change Assessment (2024) is even more blunt: most previous and current conservation approaches have fundamentally failed.

More data won't change this.


the data layer is not the solution layer

photo by NASA (@nasa) on unsplash
photo by NASA on Unsplash

Here's what the data layer actually does:

TechnologyWhat It Tells You
eDNA samplingWhat species are present (or absent)
BioacousticsWhich birds, bats, and insects you can hear
AI geospatialHow land use is changing from above
Wildfire predictionWhere fire risk is highest
Flood mappingWhich areas will flood
Climate risk modelingHow exposure will change over time
Location intelligenceWhat's near what, who's moving where
Real estate AIWhat properties are worth, what risks they face
GIS platformsWhere everything is, how it relates spatially

Every one of these is diagnostic. They tell you what's wrong—or what's risky, or what's changing.

None of them is therapeutic. They don't make anything better.

Software can diagnose. It takes a mechanism to treat.

A dashboard showing your watershed is degrading doesn't restore the watershed. A bioacoustic sensor detecting declining bird populations doesn't bring the birds back. A climate risk model projecting $50 billion in damages doesn't prevent the damages. A location intelligence platform showing your supply chain's nature exposure doesn't reduce that exposure.

We keep funding the diagnosis while the patient dies on the table.


the open data paradox

Here's the part that makes the VC thesis even stranger: most of this data already exists—for free.

SourceData Available
GBIF3.5 billion biodiversity occurrence records from 2,624 institutions
NASA EarthdataPetabytes of satellite imagery across atmosphere, biosphere, land, ocean
ESA Climate DataMulti-temporal climate datasets via open APIs
Global Forest WatchNear-real-time deforestation alerts
FEMA, USGS, EPAFlood maps, water quality, environmental indicators
OpenStreetMapComplete global vector map, roads, buildings, land use
QGISFull-featured open-source GIS platform
Sentinel HubFree satellite imagery from ESA's Copernicus program
TIGER/CensusDetailed US geographic boundaries, demographics

AI can synthesize these free datasets in minutes. Any company with a decent data engineer can build internal tooling that joins GBIF biodiversity records with NASA land cover data with FEMA flood risk maps with OpenStreetMap vectors. QGIS does what ArcGIS does—for free. Sentinel imagery rivals commercial satellites for most use cases.


the SaaS disruption nobody's talking about

Here's an uncomfortable truth for data-layer startups: the moat is eroding.

Tools like Claude Code and Cursor have turned "vibe coding" from novelty to production workflow. Developers report 2-5x speedups. Anthropic's Claude Code can read full codebases, plan complex changes, write and debug code autonomously, and loop for hours.

What does this mean for nature tech SaaS?

Any company can now replicate 80% of the features of a proprietary data platform in days, not months—using free open-source data. The subscription model that funds these startups is built on a shrinking foundation.

There's a place for subscription-based data services. Expert curation, real-time feeds, compliance packaging—these add value. But the core product ("here's what's wrong with your nature exposure") is becoming commoditized.

The companies that survive will be the ones that connect data to outcomes—not just dashboards.


the location intelligence trap

Real estate AI and location intelligence follow the same pattern. Orbital raises $60M. GeoPhy raises $33M. Geolava, xMap, Aarden—all building "spatial intelligence" for property decisions.

What they deliver:

  • Property valuations with "near 0% error"
  • Site assessment automation
  • Risk scoring from satellite + LiDAR
  • Climate exposure analytics

What they don't deliver: any change to the underlying risk.

Knowing your property sits in a flood zone doesn't prevent the flood. Knowing your supply chain depends on a degrading watershed doesn't restore the watershed. Knowing your portfolio has climate exposure doesn't reduce that exposure.

What Location Intelligence DoesWhat It Doesn't Do
Identifies flood riskFunds flood mitigation
Scores wildfire exposureFunds forest resilience
Maps nature dependenciesFunds ecosystem protection
Quantifies climate riskFunds adaptation

The gap between "knowing" and "doing" is where value evaporates—and where the real opportunity lives.


what we actually need

The problem isn't measuring what's wrong. The problem is funding what's right—perpetually, transparently, accountably.

RequirementWhy It Matters
Perpetual fundingNature doesn't operate on grant cycles. Protection must be continuous.
Permissionless participationAnyone should be able to fund protection—one click, 24/7, globally.
Transparent accountabilityEvery dollar traceable to outcomes, verifiable onchain.
Proactive protectionFund stewardship before loss, not compensation after.
Aligned incentivesEcological health and financial return moving in the same direction.
On-the-ground implementationBoots on land, not just pixels on screens.

This is not a data problem. It's a mechanism problem.


the missing layer

photo by Sicheng Liu (@lsc122746) on unsplash
photo by Sicheng Liu on Unsplash

Think of it this way:

[ DIAGNOSIS ]  →  [ ??? ]  →  [ OUTCOMES ]
  what's wrong       ???       what's better

The data layer fills the diagnosis box. Dashboards, metrics, assessments, predictions, risk models, location intelligence, property analytics, GIS platforms.

Conservation organizations fill the outcomes box. Land trusts, restoration projects, protected areas, stewardship programs.

The middle is empty.

Ensurance is the missing layer.

[ DIAGNOSIS ]  →  [ ENSURANCE ]  →  [ OUTCOMES ]
  what's wrong     mechanisms      what's better
                   that fund it

Ensurance provides the instruments—coins and certificates—that convert awareness into perpetual funding. Not charity. Not offsets. Not deprecating assets. Infrastructure for nature.


how ensurance bridges the gap

Ensurance coins (ERC-20) fund protection broadly. Trade $WATER ABUNDANCE, and proceeds flow to watershed protection. Trade $SNOWPACK, and proceeds fund headwaters resilience. Market activity becomes stewardship funding automatically.

Ensurance certificates (ERC-1155) fund protection specifically. A certificate tied to a named natural asset—a forest, a wetland, a watershed—routes capital directly to its protection. Asset-level accountability, perpetual claims.

Ensurance agents hold capital, issue instruments, and route proceeds. They can act manually (human-directed), automated (scheduled programs), or autonomous (AI-driven). Place, people, or purpose—represented onchain, accountable forever.

Ensurance syndicates coordinate multiple agents toward shared outcomes. A watershed syndicate might include cities, utilities, land trusts, and farmers—each contributing, each benefiting, all coordinated through market mechanisms.

What the Data Layer DoesWhat Ensurance Does
Measures biodiversityFunds biodiversity protection
Predicts wildfire riskFunds forest resilience
Maps flood exposureFunds watershed restoration
Quantifies ecosystem servicesCreates markets for ecosystem services
Generates disclosure dataGenerates protection outcomes
Scores property climate riskFunds risk reduction at source
Identifies nature dependenciesFunds dependency protection

certificates unlock the data

Here's where it gets interesting for data-layer companies.

Ensurance certificates aren't just claims on protection. They're pro-rata claims on the MRV and ecological data from that natural asset.

Hold 100% of a watershed's certificates? You can claim 100% of the monitoring data—biodiversity surveys, water quality metrics, carbon sequestration measurements, ecosystem health indicators. The MRV layer becomes an asset, not an expense.

This inverts the model:

Traditional Data BusinessCertificate-Based Model
Sell subscriptions to dataSell certificates that include data rights
Revenue depends on renewalsValue accrues to the asset
Data is the productData validates the instrument
Customers rent accessHolders own a stake

What this means for NatureMetrics, Pachama, Planet, and every other data platform: you don't have to just sell dashboards. You can integrate with ensurance and sell protection with data attached—via API, white-labeled, to your existing clients.

The data layer becomes a distribution channel for the mechanism layer. Your biodiversity assessment triggers a certificate purchase. Your climate risk score funds watershed restoration. Your location intelligence becomes location action.


the convergence

Data layer companies aren't wrong to build what they're building. Diagnosis matters. You can't manage what you can't measure.

But measurement is the starting point, not the destination.

The convergence looks like this:

LayerFunctionExamples
Data layerWhat's wrongNatureMetrics, Pachama, Planet, Orbital, GeoPhy
Mechanism layerHow to fund what's rightEnsurance
Outcome layerWhat's betterLand trusts, restoration, stewardship

The companies building geospatial AI, location intelligence, real estate analytics, biodiversity monitoring—they should build toward mechanism layers, not just around data layers. The real product isn't the dashboard. The real product is the outcome.

Show us what's wrong → Fund what's right → Show us what's better.

That's the loop. And without the mechanism in the middle, the loop stays open forever.


why this matters now

The 2025 IPBES assessment identified a "closing window of opportunity" to halt and reverse biodiversity loss. Serious risks of crossing irreversible biophysical tipping points—coral reef die-off, Amazon dieback, ice sheet collapse.

The window is closing not because we lack data. The window is closing because we lack mechanisms.

VCs investing in nature tech and geospatial AI: the market opportunity isn't in building another dashboard. It's in building the infrastructure that converts all those dashboards into protection.

Corporations filing TNFD disclosures: you can locate your nature dependencies, evaluate your risks, assess your exposure, and prepare your report. But if you stop at "prepare," you've just published a map of your own failure. Move to solutions. That's the fifth phase. That's LEAPS.

We don't need to know more about the problems. We need mechanisms to implement solutions.

Invest in protection, not awareness. Restoration, not reports. Impact, not indices. On-the-ground implementation, not another dashboard.

The instruments exist. The mechanisms work. The question is whether capital will keep funding diagnosis—or finally fund treatment.


taking action

If you're building data layer tech: Build toward outcomes. Integrate with funding mechanisms. Let your data trigger protection, not just disclosure. Talk to us about API integration.

If you're investing in geospatial/nature tech: Ask what happens after the measurement. Diagnosis without treatment is malpractice.

If you're a corporation with TNFD obligations: Don't stop at LEAP. Add the S. Move from assessment to ensurance.

If you're anyone with capital and concern: The $1 trillion biodiversity funding gap won't close with better dashboards. It closes with better mechanisms.

Explore ensurance coins →

Explore ensurance certificates →

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