Biodiversity credits and DNA reference libraries

Biodiversity credits: where markets meet monitoring, DNA reference libraries are a high-leverage investment

Biodiversity credits are moving quickly from concept notes to implementation—and East African savannas are where some of the hardest questions are being tested.

The promise is simple: markets can channel finance toward measurable, verifiable biodiversity outcomes at landscape scales. But the challenge is just as clear: unlike with carbon credits, biodiversity "units" can be counted in so many ways.

Since a credit is only as credible as the monitoring behind it, a theme that keeps emerging from technical and policy discussions involves trying to figure out whether DNA-powered approaches can help. In principle, any DNA we detect in the environment can help make biodiversity surveys more reliable and harder to game. But all DNA-based approaches rely on unseen infrastructure that most people never consider: reference DNA libraries that must be constructed based on verifiably identified specimens. When biodiversity targets are poorly covered by these libraries, even the most sophisticated survey methods can collapse into reports that are frustratingly full of "unknowns."

That message came through repeatedly at recent meetings in Nairobi, Kenya. Last week, Dr. Mary Burak (Senior Postdoc, Genomic Opportunities Lab) attended both the Business for Conservation Conference and the Global Conservation Technology & Drone Forum. A recurring question she encountered in conversations with practitioners, business leaders, and researchers went like this: what would it take to use DNA as "creditable" in savanna biodiversity programs—and who is going to build the databases we need to get there?

What would it take to make DNA evidence "creditable" in savanna biodiversity programs—and who is going to build the databases we need to get there?

Because translating complex biodiversity data into actionable information is one of our team's core strengths, we wanted to share this post as a practical summary of the field. We will outline how biodiversity credits work, how programs affecting East African savannas are typically structured, and when DNA can add real value. You will discover that DNA reference libraries are currently an undervalued and high-leverage investment that savvy leaders are making—they recognize that you can't make DNA creditable without it.

​The key question we reveal for anyone who wants to participate in this market: what is the return on investment you can expect from building the reference libraries that underpin success—and how long will it take for the investment to increase the value of your monitoring services or offset programs?

What biodiversity credits are—and how they work

Biodiversity credits (also called nature credits) are intended to represent a purchase of quantified, verified contributions to biodiversity. A challenge in this marketplace is that, unlike carbon credits that are largely based on the measurement of one universal metric (e.g., ton of carbon dioxide), biodiversity credits have to measure changes relative to a baseline condition. This can be done by assessing some a combination of:

• habitat condition and integrity (e.g., vegetation structure, degradation, fragmentation),
• species presence or abundance (e.g., keystone or threatened species),
• landscape connectivity (e.g., movement corridors, animal-tracking),
• threat reduction and durability (e.g., risk mitigation, permanence).

In practice, most of the emerging credit systems follow the same logical scheme:

1. Define the site and "what is being improved" (e.g., a conservancy, community rangeland, corridor, or protected area buffer).
2. Set the baseline: the starting condition or species assemblage.
3. Specify interventions (e.g., fire management, rotational grazing plans, invasive species control, anti-poaching measures, water management).
4. Monitor outcomes over time and compare them with the baseline value.
5. Verify and issue credits, often involving risk deductions and audits.
6. Sell credits into voluntary markets or results-based finance arrangements.

The "credit" may look more like a contract that guarantees outcomes than like a commodity. But the direction the field is moving appears to be something like this:

​more standardization → stronger measurement, reporting, verification (MRV) → higher scrutiny requiring claims to be verified

​How biodiversity credits are typically structured for East African savannas

Biodiversity credits are being explored worldwide, but they’ve become a particularly hot topic in savannas—including across much of East Africa—partly as a response to hard lessons learned in the development of markets for carbon credits. In places, carbon credit schemes have incentivized tree-planting programs across ecosystems that are not naturally forested. The intent is understandable since trees soak up and store carbon that we need to get out of the atmosphere so it can't cause as much warming. But the outcome is unintentionally harmful: savannas are globally important ecosystems in their own right, and converting lands from savanna to forest will eliminate habitat for endangered species like elephants, rhinos, and giraffes and all the other species that depend on savannas as well.​

East African savannas are among the last strongholds of Grevy's zebra, the largest species of wild equid and the most threatened of the three zebra species alive today.

Against this backdrop, emerging biodiversity credit approaches in East African savannas tend to focus on landscapes that are shaped by pastoralism, wildlife migration, and mixed land uses. Programs often coalesce around the unique biodiversity value—and governance structures—that leaders see in lands that have been set aside as wildlife conservancies or used as community rangelands.

Designing effective programs in these areas requires grappling with two issues at the same time:

1. Ecological variability: rainfall swings, fire regimes, grazing pressure, and seasonal movements drive rapid, natural change—so indicators and baselines must be chosen carefully.
2. Governance complexity: land and resource rights, benefit-sharing, and human–wildlife conflict aren’t side issues; they determine whether conservation outcomes (and credit integrity) can be sustained.

Consequently, typical savanna biodiversity credit programs often include:

Defined landscape & governance units

• A conservancy or community land-management unit, sometimes linking corridors between protected areas.
• Clear rules around land use such as grazing plans, seasonal access, settlement zoning, and wildlife movement.

Baseline data & threat models

• Baseline habitat condition and a prioritized list of species or habitat qualities to target for improvement (i.e., the ‘biodiversity’ that will be valued).
• A threat model to address, such as overgrazing, woody encroachment, invasive species, fence barriers, poaching, water quality and access, and human–wildlife conflict.

Intervention plans

• fire management
• rangeland restoration plans
• invasive/encroachment control
• corridor protection
• fence modification
• ranger programs and conflict mitigation

Measurement, reporting, & verification (MRV) plans

• remote sensing to track vegetation condition, bare ground, fragmentation, fire scars
• field surveys such as transects or aerial counts of wildlife
• camera traps and/or ranger patrols

The market strategy is important to keep in mind here: plans culminate in a MRV "stack" that represents a key part of the product that will be sold. Buyers are willing to pay for outcomes that they can trust, and a seller's credibility is increasingly tied to their ability to show clearcut evidence, repeatability, and independent verification of the biodiversity value they provide.

What DNA technologies can contribute & why they’re an attractive option

​Although DNA tools are not yet a standard measurement requirement for biodiversity credits, they’re well-positioned to strengthen MRV in several high-value ways—especially wherever traditional surveys are costly, challenging, or prone to observer biases that can reduce repeatability and verifiability. Let’s consider a few specific applications that appear increasingly powerful and may soon become common in the marketplace.

1) Waterhole eDNA: detecting wildlife where they come to drink
Savanna wildlife concentrates around water. That makes waterholes unusually efficient places to sample biodiversity using trace amounts of the DNA they leave behind.

How it helps:

• We can use DNA to detect a wide range of vertebrates (and potentially other taxa) from water samples when they come to drink or cool off.
• We can use these data to complement camera traps or ranger surveys, helping reduce blind spots and increase repeatability when it comes to species that are cryptic, nocturnal, or rare.
• We can create repeatable sampling protocols that are easier and cheaper to standardize across a wide variety of sites.

A waterhole at Mpala Research Centre is frequented by the regions diverse wildlife, especially in the dry seasons when alternative sources of water are scarce.

Note that this example focuses on waterholes in East Africa, but the idea of sampling wildlife DNA in places that we know attract wildlife from across the region applies broadly. Other concentrated biodiversity hotspots that a credit program might consider include: 

• Hummingbirds at flowers
• Fish on coral reefs
• Scavengers at carcasses

When we sample it from places where specific components of biodiversity are known concentrate, we can sequence DNA from species that occur across a target area.

The strategy thus provides market value:

• It increases confidence in claims that a target species is present (or absent at baseline).
• Helps document the return of species after management changes.
• Supports more frequent monitoring without proportional increases in field costs or effort.

2) Scat genetics and bushmeat identification: verification and enforcement
Forensic identification of materials that animals leave behind provides evidence of where they occur. For example, when an animal poops in the field, DNA from its scat can be used to confirm its species occurs in the area. It thus provides MRV value for biodiversity monitoring. Likewise, the ability to genetically test bushmeat or other wildlife products—whether obtained and sold legally or illegally--can strengthen the credibility of MRV surrounding interventions or enforcement aimed at reducing pressure on wild populations.

How it helps:

• Confirms the presence of target species even when sightings are rare.
• Strengthens evidence around the distribution and density of threatened species.
• Supports anti-poaching and illegal offtake monitoring with harder-to-dispute data.

Market value:

• Improves credibility with buyers that exceedingly rare species can be monitored using alternative approaches to the traditional monitoring strategies that require more labor costs than the market will bear.
• Adds an integrity layer to claims about threat reduction—especially where illegal offtake is identified as a threat and buyers want to see enforcement as a key intervention.

3) Dietary DNA: detecting changes in food webs and ecosystem functioning
Fundamentally, biodiversity is more than the sum of species present in an area. It includes ecological diversity and thus commitments to conserving or improving the biodiversity value of an area require attention to how the ecosystems of that area function. In savannas, this includes attention to grazing dynamics, predator–prey balance, and resilience.

Dietary DNA recovered from animal feces can reveal the composition of wildlife diets and how they change over time. This kind of information most directly tells us about the complexity of food webs when components of the system might be at risk of collapse.

Dr. Mary Burak leads a workshop training researchers from Save the Elephants (STE) and the National Museums of Kenya (NMK) to build plant DNA barcode libraries. These libraries will be used to precisely document the botanical diversity of elephant diets in the Samburu region of Kenya.

🔗 Behind the scenes with STE

Yet we can use the information in more creative ways as well. Much like we can use our knowledge of how animals behave around waterholes to sample DNA of species that we might not otherwise observe, we can take advantage of all the efforts animals put into hunting and foraging for food species to complement the results of of our field surveys. Common animals in our study areas can be used like 'citizen scientists' insofar as they put in a lot of effort searching the environment for species that we might not see and then they 'tell us' about what they found when they leave behind scat for us to sample. 
​
How it helps:

• Detects shifts in diet breadth or reliance on certain plant or prey species.
• Can act as a proxy for changes in resource availability and thus ecosystem condition.
• Complements field survey data by enabling the detection of rare or cryptic food species.

Market value:

• Supports "function-based" narratives and indicators that are useful distinguishing credit products.
• Adds evidence that management is improving ecological processes, not only producing isolated sightings of a few 'charismatic' or otherwise conspicuous species.

Scientific resources:
🔗 Sampling and interpreting dietary DNA is a core strength of the Genomic Opportunities Lab
🔗 Linking diet switching to reproductive performance across populations of two critically endangered mammalian herbivores

Why we need reference libraries: the hidden infrastructure enabling credible DNA-based data

Ultimately, DNA-based biodiversity monitoring is only as good as the reference libraries used to identify DNA sequences. The sequencing technology itself only allows us to string together lists of nucleic acids—the A’s, T’s, C’s, and G’s that comprise the universal genetic code. We then need to do the harder work of identifying each resulting sequence—literally millions of them in a single analysis—so we can verifiably the kinds of plant or animal DNA that occurred in a sample.

Across emerging biodiversity MRV efforts, a few approaches to building libraries are gaining traction:

• Targeted library construction that is tied to the credit methodology of a site (i.e., invest in building a local database that covers all taxa you expect to measure).
• Voucher-backed sequences with strong metadata obtained from institutions (i.e., museum specimens with clear sampling locations, dates, identifiers, and identifications).
• Gap analyses to quantify identify taxa that can vs. cannot currently be identified reliably using publicly available data (i.e., planning to minimize investment in library construction by instead accepting coarse identifications and providing results with uncertainty).

🔗 Press coverage of why DNA reference libraries matter for monitoring 
🔗 Contract & train with us at the Genomic Opportunities Lab
🔗 Ways to support enhanced access to Genomic Opportunities in conservation

The core challenge that people face when they would like to incorporate DNA-based technologies into their credit program is that unknown sequences may appear in their results—and these kinds of results can stoke uncertainty that leads to discounts in the marketplace.

If a significant fraction of sequences cannot be confidently assigned, the program risks:

• weak claims (“we detected biodiversity changes but can’t say if they were good”)
• conservative auditors (“the credit’s value is developing but not yet established”)
• reputational loss among buyers (“if they can’t tell us what they are protecting, how can we know it’s not just greenwashing?”)

In other words: evaluating reference coverage is not merely an academic exercise in perfectionism. It determines pricing and credibility. It is what allows prospective buyers to differentiate your premium product from all the others.

Where we face challenges, we also find opportunities

The need to develop reference libraries as a shared asset makes the effort valuable. But someone has to make the initial investment before that value can be realized.

Reference libraries share many characteristics with commonly recognized public goods. Everyone benefits from access to these kinds of data—especially when communities are expected to make consequential decisions that hinge on the quality of them—but individuals bear the costs of providing them. That’s why early movers—pioneering programs or consortia that coordinate sequencing of voucher specimens—can create outsized value for the global community. 

In the context of biodiversity credit programs, the costs of building robust reference libraries may be viewed as investments. Some investment costs can be recouped. There is a lot of opportunity for early investors to distinguish the quality of their products from the products of others. While the reference sequences themselves carry no real commercial value—they merely indicate species identity and carry no patent-worthy gene information--their potential to provide superior MRV can be translated into a stronger position in the biodiversity credit marketplace for those who lead in their development.

As species of the savanna are emerging as targets of biodiversity credit programs, it's no wonder that the ability to credibly document their distributions and their roles in food webs is a hot topic—it's bridging the academic, business, and conservation-based NGO sectors across East Africa.

The investor’s question: what is the return on generating reference barcode coverage?

For anyone who wants to participate in an emerging biodiversity credit market, the "return" on investing in DNA reference libraries is not going to come from a direct new revenue stream. It will show up as improved credit quality via superior MRV, which can translate into higher value in several ways:
​
1) Higher assignment rates → stronger, more specific claims
Do you think buyers will be more impressed by waterhole DNA sequence that is best identified as "unknown vertebrate" or "critically endangered Grevy’s zebra"? Those results support very different narratives. Better reference coverage increases species-level resolution, confidence scoring, repeatability, and verification outcomes. This is a clear value proposition, as it allows for stronger claims, premium market positioning, and lower risks of reputational damage from unverifiable or disputed results.

2) Lower uncertainty → less discounting and fewer buffers
Where uncertainty deductions may apply, reference gaps become a reason for auditors to discount the biodiversity value of a program. The pathway from investments in DNA libraries to value is thus through improvements in data coverage to reduce uncertainty. This potentially allows a credit program to justify tighter confidence intervals around biodiversity estimates, avoid undervalued interpretations of results, and issue credits with fewer caveats.

3) Cheaper scaling of monitoring over time
Once reference libraries and protocols are in place, genetic monitoring can become a scalable routine. In this way, value is gained as MRV costs decline and thus allow more frequent monitoring to better document trends, broader spatial coverage of sampling, and faster detection of negative changes—so programs find out in time to adapt before they the declining integrity of issued credits gets them in trouble.
 
4) Differentiation: moving beyond "habitat-only" to "biodiversity-evidenced" credits
Many early biodiversity credit programs leaned heavily on remote sensing and habitat indices to document 'biodiversity' trends. Habitat quality and quantity are certainly relevant to biodiversity, but they are not one and the same. Using DNA can help a program credibly claim a more direct connection between habitat and biodiversity outcomes—or make the decision to focus on biodiversity outcomes per se. The value pathway appears as one program distinguishes itself from others in ways that increase buyer confidence and willingness to pay—the perception that a program is engaging in greenwashing by measuring one thing and claiming its another can be overcome.

5) Reduced reputational and verification risk
Buyers face the risk that a product they purchase will be defective—in this case a biodiversity credit program might be end up in ecological collapse. Savvy buyers do not want to be fooled by unscrupulous programs that might be trying to take advantage of them in an industry that has historically been characterized by lax regulations. Likewise, the developers and monitors of biodiversity credit programs face the existential risk that their MRV strategy fails or leads them into a quagmire of disputed claims. Thus, the value pathway emerges as better reference coverage reduces risk while strengthen the veracity of claims.

A practical way of thinking about ROI

A key issue that leaders in the biodiversity credit marketplace should be considering is when the potential for improvements to their DNA libraries provides enough value added that it supports the decision to invest in it.

Key questions to ask about the value proposition for your program might include:

• Does it flip confidence in results from "unconfirmed" to "verified" for your priority species?
• Does it enable tests that can be repeated broadly and routinely, rather serving merely as a high-tech add-on?
• Does it reduce the likelihood that an auditor will require additional expensive surveys for verification?
• Does it allow you to credibly add a new indicator set to your targets—like amphibians, small carnivores, or key plants that just wouldn't show up in your traditional camera-trapping surveys—allowing you to distinguish your credits from a more commonplace alternative?

If the answer is yes to any of the above, investing reference coverage is not just a good deed—it’s a marketable investment that you need to make in your product.

What all readers should know

If you are considering engaging in biodiversity credits—as a land manager, program designer, buyer, or investor—a key take-away you need to remember is this:

Funding a targeted reference library for the taxa that your program’s MRV depends upon could increase the credibility, resolution, and scalability of your monitoring.

​But by how much? Perhaps a lot, if it translates into fewer verification constraints, lower uncertainty discounts, and a more valuable, trusted, and defensible credit.

In emerging markets, that could make the difference between a program that demonstrates outcomes convincingly versus one that can only speak in terms of its aspirations.

🔗​ Join us in funding DNA reference libraries for conservation

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