What the Land Sector and Removals Guidance Means for Ag Supply Chains

The GHG Protocol Land Sector and Removals (LSR) Standard and accompanying Guidance represent a major shift in how companies account for land-sector emissions, removals, and related value chain impacts.

In Part 1 of this wide-ranging conversation, Regrow sat down with Zander Dale of Schneider Electric (SE) Advisory Services to discuss what the changes mean in practice, how companies should prepare, and why higher-confidence land-sector data matters beyond compliance.

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Regrow: The Land Sector and Removals Standard (LSRS) and accompanying Guidance take effect January 1, 2027, after five years of development and input from hundreds of international experts and pilot companies. What's the single biggest gap in corporate land-sector accounting this standard closes?

Zander: For me, the biggest gap it closes is the lack of a consistent way to bring land-sector emissions and removals into the corporate GHG inventory.

Land-sector accounting has always been a tricky area. Agricultural emissions, land use change, soil carbon, biomass carbon, biogenic products and removals have tended to be treated inconsistently, reported only partially, or handled outside the core inventory altogether. What I see with clients is that this makes it hard to compare performance, set credible targets, or show whether land-based interventions are actually reducing emissions or increasing removals.

The Standard changes that by giving us a much more structured way to account for land management, land use change, land occupation, leakage, biogenic product emissions and CO₂ removals.

If you've got material land-sector exposure, the practical implication is simple: land impacts can't sit in a grey area any more.

They need to be mapped, quantified, reported and governed with the same discipline as any other material source.

The way I'd frame it to clients is that this is less a reporting update and more an inventory design challenge. The first question isn't "what factor should we use?" - it's "where do land impacts actually sit in our value chain, how much traceability do we really have, and what evidence stands behind the numbers we're reporting?"

Regrow: How does the Guidance help companies solve that inventory design challenge? Will it create greater consistency across different reporting requirements like SBTi FLAG or CSRD?

Zander: What the Guidance really does is give companies a common accounting foundation that can feed several reporting and target-setting requirements at once.

Frameworks like SBTi FLAG, CSRD, CDP and the broader reporting requirements each have their own purpose, and they don't all ask the same questions in the same way. But they increasingly rely on the same thing: credible, decision-useful land-sector data. The Guidance helps you build that foundation by clarifying the accounting categories, spatial boundaries, traceability expectations, data quality, uncertainty and reporting treatment.

That matters because, in my experience, companies often end up building separate datasets for each need, one for the GHG inventory, one for FLAG, one for CSRD, one for supplier engagement, another for procurement or product footprinting. It's inconsistent, and it makes assurance far harder than it needs to be.

The better approach is to build a single land-sector data architecture that can serve multiple outputs.

It should be robust enough for inventory reporting, flexible enough for target tracking, and practical enough to inform supplier engagement and real business decisions. Seen that way, the Guidance is very useful, because it helps you move from fragmented reporting to one coherent system.

Regrow: Staying with FLAG for a moment, once a company has set or validated FLAG targets, what are the next steps to move from target-setting into delivery?

Zander: Validation's a milestone, not the finish line. The real work is turning a validated target into a delivery plan you can actually stand behind.

This is demonstrated by the latest SBTi Net-Zero 2.0 guidance and strategy from the Science Based Targets Initiative... we are seeing a big push from setting targets to action and delivery.

In practice, that usually means finding the hotspots behind the target, shoring up your supplier and commodity data, building category-level reduction plans, bringing internal stakeholders along, and screening value-chain intervention opportunities, with some governance wrapped around it all to track progress.

It's the point where technical target-setting and practical delivery meet. That second point is where most of my time is going currently!

Regrow: We're chatting in July 2026. That means we're only about five months until the effective date. What should someone reading this be doing today to prepare?

Zander: Time is certainly flying! I'd use this window to run a proper readiness assessment. The aim isn't to perfect every calculation straight away, it's to get a clear view of applicability, materiality, data gaps and governance needs.

A sensible first step is to work out where land-sector activities actually sit across the business and value chain, owned or controlled land, purchased agricultural commodities, bioenergy, biomaterials, food and feed products, and any removals activity you've got planned. Then map those against the relevant accounting categories: land use change, land management net biogenic CO₂ emissions, production emissions, land occupation, leakage, biogenic product emissions and removals.

The next thing I'd look at is traceability. Do you know the country of origin, the sourcing region, the supplier, the land management unit? That'll vary a lot by commodity and geography, and that's fine at this stage. The point is to see where the gaps are and prioritize them.

There are five things I'd focus on right now:

• Confirm whether land-sector activities are significant and document any exclusions.
• Map material commodities, geographies, suppliers and business units.
• Identify where current emission factors combine categories that may now need to be reported separately.
• Assess the level of traceability available by commodity and sourcing region.
• Build a phased improvement roadmap, prioritising the largest emissions sources, highest-risk commodities and areas where interventions are planned.

The golden rule is don't wait for perfect data, but equally, don't rush into overconfident claims before the evidence base is strong enough to carry them.

Regrow: Let's stay with that shift from theory to practice. Many companies may understand the accounting requirements conceptually, but struggle to translate them into action. How should companies move from LSRS readiness into a phased land-sector strategy?

Zander: The big shift is to stop treating LSRS as a one-off reporting exercise. It should become the basis for a practical implementation roadmap.

A good roadmap usually pulls together the material activities, the big data gaps, and your priority commodities and geographies, and then the supplier engagement, intervention screening, MRV and governance that hold it all together.

Sequencing is everything: start where it's most material and most decision-relevant, and build out from there.

Done well, the accounting should influence sourcing, supplier engagement and investment choices, not just sit in a compliance report.

Regrow: Sequencing by materiality makes sense for the inventory. How do you see that same logic changing the way companies design and prioritize regenerative agriculture programs specifically?

Zander: It should push regenerative agriculture programs to become far more evidence-led and far less claims-led.

A lot of companies have built their programs around practice-adoption metrics, hectares enrolled, farmers engaged, cover crops planted, tillage reduced. Those are useful, but they're not the same as quantified GHG outcomes. The Standard raises the requirement here by making organizations distinguish practice adoption from emissions reductions, removals, gross carbon stock change and net stored carbon. That should change how programs are designed.

You have to think much harder about traceability, baseline conditions, spatial boundaries, empirical data, model calibration, uncertainty and ongoing monitoring.

And you need to be honest about what a program is really for, reducing emissions, increasing removals, building resilience, supporting biodiversity, or some mix of all of those.

Take a company supporting cover crops, reduced tillage, nutrient optimization and agroforestry. It can't just turn "regenerative acres" into a climate claim. It needs to define the sourcing boundary, quantify the emissions and carbon stock changes, monitor them over time, and check whether any removals actually meet the requirements on traceability, uncertainty and storage.

The upside, and this is the part I like, is that better accounting helps you prioritize the programs that actually matter. It shows you where intervention potential is highest, where supplier engagement is most needed, and where the evidence is strong enough to support reporting and target progress.

Regrow: Let's pull that upside thread more. Beyond achieving compliance, what business decisions become possible when companies have higher-confidence land-sector data?

Zander: Higher-confidence data turns the inventory into a strategic tool rather than just a reporting output, and that's where it gets interesting.

Once you've got a clearer picture of your land-sector impacts, you can make much better calls on sourcing, supplier engagement, investment and risk. You can compare commodities and regions credibly, identify the hotspots, see where traceability needs to improve, and back the interventions that are actually likely to deliver.

It also stops you making bad decisions. A company might cut its reported land use change emissions just by changing a sourcing assumption, but that doesn't reduce real-world land pressure at all.

Good data gives you confidence that reported reductions reflect real-world mitigation, not just a change in assumptions, boundaries or calculation methods.

Commercially, that feeds procurement strategy, supplier segmentation, product footprinting, resilience planning and customer engagement. And it makes the internal business case far stronger, because the conversation shifts from "we need this for compliance" to "this helps us understand risk, allocate capital, engage suppliers and hit our targets more credibly."

Regrow: And if that's the strategic upside, how should sustainability teams be making that case internally to get the investment approved?

Zander: That is a really important question. I would start by moving the conversation away from reporting and reputation. That is often where companies limit the business case too early. The stronger argument is that land-sector data and insetting can support real commercial value.

That value shows up in avoided compliance risk, stronger supply chain resilience, better supplier relationships, more informed procurement decisions, less duplicated effort, a lower cost of decarbonisation, and reduced reliance on external carbon credits over time. Framed properly, this becomes a strategic investment in value-chain resilience and target delivery, rather than another piece of reactive climate spend.

Want more insights? In Part 2, we dive into questions of methodology: what determines when to opt for Tier 3 modeling, what good accounting looks like in practice, and how to evaluate and deploy digital MRV platforms.