Why the do-ers need a first principles map before they choose a platform, protocol, pathway, or market.
The Pattern We All See (But Rarely Name)
In 2021, at my last day at Nori, a voluntary carbon removal market start-up I helped co-found, I wrote a reflection called Do it. Prove it. Sell it: My Evolving Views on Carbon Accounting
The idea was simple:
If we don’t have a system that makes “doing it” first, that is, clarify a real intervention pathway grounded in reality, then “proving it” becomes an expensive guessing game, and “selling it” collapses into wishful thinking.
Since leaving Nori, “it” has morphed for me as an impact metric from carbon alone, to the quantifiable output from improving an ecosystem service, thereby seeing carbon as more of part of a system rather than the end goal itself.
Four years and dozens of advisements to programs trying to prove and sell ecosystem services programs later, the pattern has only deepened. It’s a square peg, round hole dynamic, and everyone knows it.
Project developers still assume that the standard or protocol must be right, and if reality doesn’t match, then reality, not the standard, needs to bend.
I’ve watched well-intended teams design brilliant Measurement, Monitoring, Reporting and Verification (MMRV) platforms, pick a market pathway, or chase a crediting mechanism before they ever clarified what problem they were solving, what ecological pathway they believed in, or whether the intervention was even feasible in the first place.
It’s not their fault.
The system quietly conditions people to start in the wrong place.
Not with the intervention, or the people affected by it, but with the standard, the market pathway, or the claims they hope to make.
Start with Sell It, and your entire program becomes dependent on someone else’s definitions.
Start with Prove It, and you are designing to satisfy auditors, not farmers.
Start with Do It, and the system becomes legible.
Constraints show up early.
Risks become sortable.
And every option downstream becomes easier, cheaper, and more defensible.
And that’s where the anatomy matters.
If we can understand the anatomy of doing it, then we can recognize the options available to proving and selling it.
The graphic on the left shows how starting with ‘prove it’ or ‘sell it’ collapses the world of what’s feasible. The green circle is the real, do-able intervention. The moment you pick a standard, the world shrinks. The moment you pick a market pathway, it shrinks again.
If the first graphic shows how starting with prove it or sell it shrinks your world,
the second graphic to the right shows the opposite:
When you start with Do It, the world stays big.
Your optionality increases, not decreases.
The green circle at the center represents the real, feasible intervention—the thing that actually improves an ecosystem service.
Surrounding it are the large blue circles:
the core proof pathways you could choose after you know what’s feasible (e.g., LCA modeling, practice-based claims, risk-tiered evidence, supply-shed accounting, sampling, direct measurement, reporting frameworks, scenario modeling).
Outside those are the smaller brown circles:
the many different “sell it” pathways (market mechanisms, certification schemes, consumer-facing claims, procurement alignment, internal value arguments, resilience ROI, crediting, book-and-claim, financing architectures).
Why “Additionality” Breaks the Moment You Touch the Ground
To prove my point on constricting reporting and intervention logic of “doing”, let’s pick on additionality, a beloved term of carbon market enthusiasts. Additionality makes sense as one form for market logic:
We must show the intervention wouldn’t have happened otherwise.
But it breaks when you’re working with real farms, real constraints, real timelines, and real decision logic in a dynamic and ever-changing system.
Farmers will always bring reality back to the surface. I still remember a note that I got from Doug, a farmer who attended a webinar I gave in 2019 when I was trying to explain the Nori program, and eligibility requirements to prospective “suppliers”
“Dear Christophe, This does not really apply to me but I really do not understand why you are hung up on a change of practice to qualify for NRT’s if your market is to store carbon with proven current practices why does prior practice matter? I understand that some of your buyers want to help encourage change, but I would also argue that those who have been doing some of these practices in the past are some of your best allies in instigating change by, example and their leadership in the past by doing what was right before it was ever “cool” or they had any chance to monetize their efforts. I do plan on signing up, but I have a neighbor that has been no-tiling and strip tiling far longer than I who is not because of this reason. His example is the reason that I have tried these practices myself and this is the reason that I feel so strongly about this. I await your response, thank you, Doug”
If the right choice for the farmer is adoption regardless of credit income, is it really “non-additional”?
If the intervention improves resilience, risk, and yield, is it “ineligible” simply because it was smart?
When taken literally, additionality paradoxically punishes real progress and rewards inertia.
This is exactly why starting with the proving framework forces programs into contortions that don’t serve land stewards or system durability.
A do-er knows this.
They feel the mismatch.
What they need is a better starting point.
Additionality is not a moral judgment or a purity test.
It is a framework for attribution, and it makes sense only when you understand the realities of management, agronomy, incentives, and timing.
Treat it as the starting point, and everything collapses under its weight.
Treat it as an output of good design, and it becomes workable, sometimes even elegant.
This is why additionality only becomes coherent after you’ve mapped feasibility, actors, and incentives, not before as an eligibility check.
The Do-ers: The People This Framework Serves
Most ecosystem service programs don’t fail because the science was wrong or the farming practice was flawed. They fail because they were designed backwards.
Teams start by picking a protocol, a verification pathway, or a market mechanism, and only then try to retrofit the actual system, people, data, and ecological realities into it.
That’s the “prove it” or “sell it” mindset: begin with the claim, then force the operation to match it.
But the programs that work, the ones that scale, survive audits, and create value, start somewhere else entirely: with doing.
With understanding the system as it is, not as standards imagine it.
This framework is for the do-ers: the supply chain program managers whose names will end up on the line, the agronomists who must make the practice work, the TA providers who carry farmer trust, the NGO implementers navigating two realities at once, and the scientists translating complexity into something a procurement team can actually use.
Start with “do,” and you keep optionality.
Start with “prove” or “sell,” and the world narrows until nothing fits.
The do-ers don’t need hype.
They need clarity.
They need a way to see the machine they’re trying to influence.
And they need a process that respects the constraints of land, time, evidence, and incentives.
If you are one of these do-ers, this anatomy is for you.
Not as a template to force-fit, but as a way to see the system you’re operating inside, so you can design interventions that actually work under real-world conditions.
Designing from “do” doesn’t just clarify the system, it brings farmers back into the role they should have had all along: co-designers, not rule-takers.
When you start with feasibility, farm-level logic, and real agronomic constraints, farmers gain a seat at the table early in the process. They help define what’s workable, what’s risky, and what rules make sense.
Programs are stronger, and far more durable, when the people who manage the land have a hand in shaping the rules that govern it.
And this matters now more than ever. This moment is especially urgent, with LSRG pilots underway, 45Z reshaping supply systems, and procurement teams being asked to quantify regenerative impact faster than ever.
Below is the anatomy in ten steps that map the real system, reduce risk, and create a path to value without committing prematurely to any market, methodology, or crediting pathway.
The Anatomy of an Ecosystem Service Intervention
1. Landscape Feasibility
Before deciding anything else, ask:
- Can the practice even work here?
- What are the biophysical constraints — water, rotation, labor, timing, equipment?
- What is already happening on the ground?
- What would nature allow or resist?
This step prevents chasing interventions that cannot succeed, no matter how elegant the model or generous the incentive.
It protects do-ers from inheriting impossible mandates.
2. Actor System and Influence Map
Every ecosystem service program sits inside a web of actors:
- farmers
- advisors
- aggregators
- input suppliers
- modelers
- verifiers
- certifiers
- procurement and sustainability teams
Each carries different incentives, risks, and forms of leverage.
Program failure is almost always a function of misalignment, not bad science.
Mapping the actors and their influence reveals where friction will emerge, where trust is thin, and which decisions actually matter.
3. Motivations and Constraints
You cannot design a viable program without understanding:
- what each actor wants
- what they believe
- what they fear
- what they will never do
- what they cannot do
- where their incentives truly lie
This is the first moment where clarity appears.
When do-ers understand motivations, they stop pushing uphill and start shaping interventions that people can and will adopt.
4. Ecological Pathway
What are the actual biophysical mechanisms of change, and do they reliably occur under the conditions we’re working in?
Every intervention has a mechanism:
- nutrient cycling
- moisture retention
- emissions avoidance
- carbon stabilization
- root mass changes
- microbial shifts
- input optimization
This step gives do-ers clarity on why an ecosystem service improvement is expected.
You cannot design incentives, boundaries, or measurement without understanding the chain of ecological cause and effect.
When the ecological pathway is unclear, everything downstream becomes guesswork.
5. Data Inventory and Reality Check
This is where theory meets truth.
- What data exists?
- Who owns it?
- What is accessible?
- What is missing?
- What is locked in PDFs, portal logins, or proprietary tools?
- What formats conflict or fail to connect?
Do-ers need visibility before they commit.
A data inventory exposes whether the proposed program is feasible, what evidence can be gathered, and what burden would fall to whom.
This does not finalize the program — it reveals the real constraints.
6. Evidence Burden & Risk Tier
Not every claim requires credit-level proof.
Evidence expectations should scale with:
- risk
- materiality
- claim type
- audit exposure
- operational relevance
The art is matching the evidence burden to the purpose and to what actors can realistically carry — not defaulting to the strictest market standard.
Evidence is a cost. Spend it where it matters.
7. Boundaries and Attribution
The Greenhouse Gas Protocol frames this as identifying sources, sinks, and removals. That’s useful, but a do-er approach goes deeper. Boundaries define what counts, what doesn’t, and where the system begins and ends.
This includes:
- field vs farm
- farm vs supply shed
- supply shed vs global inventory
- co-mingling
- feed pathways
- shared equipment
- rotational timing
This is also where quantification pathway selection becomes possible.
Define boundaries first, and you maintain control over how change is quantified.
Choose a quantification method first, and the method dictates your boundaries.
Most programs crack under audit because they define boundaries last.
Boundaries define the system.
Data defines what is real.
Evidence burden defines what is defensible.
Successful programs cycle lightly between these three until aligned.
8. Incentives, Value, and Governance
Here, the question becomes:
- What value is created?
- Who captures it?
- Who pays?
- Who takes risk?
- What prevents free riding?
- How will governance evolve as the system matures?
This is the moment where do-ers regain operational sovereignty.
Design the value structure now, before committing to any market.
9. Value Realization (Internal + External)
Not all value is a market credit, nor should it be.
Value can look like:
- reduced risk
- yield stability
- resilience
- cost avoidance
- local water outcomes
- supplier loyalty
- better procurement visibility
- decarbonization that actually matters
When value is diversified, programs become more durable and less dependent on fragile crediting systems.
10. Adaptation, Feedback, and Evolution
Ecosystem service programs are living systems.
They evolve as:
- science updates
- policy shifts
- actor incentives change
- tools improve
- new data becomes available
- risks emerge or disappear
The anatomy loops back on itself.
Steps 5–7 will always be revisited as clarity deepens and operational reality changes.
This framework becomes a reusable decision-support tool, something do-ers can return to each time the system shifts.
Closing thoughts
If you’re one of the people responsible for making this work, the ones who carry the program through uncertainty, audits, constraints, budget cycles, and real-world complexity, this framework is yours. Starting in the right place doesn’t guarantee success, but it reliably avoids the kind of costly rework that derails most ecosystem service programs.
Start with “do,” and you keep options open.
Start with “prove” or “sell,” and you inherit someone else’s constraints.
The anatomy is a way to design ecosystem service interventions that are grounded, resilient, auditable, and aligned with the actual system, not the imagined one.
It gives do-ers a path.
And that’s where all real change begins.
And once you’ve made that map for the do-ers?
Then you can decide how to prove it and whether to sell it.
Not the other way around.
If you’re wrestling with these questions, if you need clarity on where to start, what’s feasible, and what’s worth measuring, we’re happy to explore it with you.
Share a little context here.
If we can help, we will. If we’re not the right people, we’ll tell you.
Either way, you deserve a path grounded in reality.