although Husson et al. [2024] do not mention it) evolution trajectories are not linear but sigmoidal, varying to some extent depending on soil (and NCP/ES) types and climates<fnref n="56" />. Husson in Ver de Terre Production [2023] emphasizes that RA is inherently adaptive. Practices cannot be fixed and must evolve throughout the regeneration process. The key questions then become: “How can cropping systems be adapted to changing environmental conditions?” and “when can and should soil tillage and the use of external inputs be reduced or eliminated?” since tillage, synthetic fertilizers or pesticides are not absolutely excluded<fnref n="57" />, when considering very degraded soils. A degree of gradualness (rather than brutal change) is then required as they are threshold effects below and above which a set of practices can be undertaken or abandoned. Rather the focus should be on monitoring and adapting based on indicators, not enforcing uniform practices Husson et al. [2024].

## 10.4 Managing the evolution of (risk changing) production factors through the Eh-Ph couple

All agricultural practices can be seen through the lens of the homeostasis of the soil plant microorganism system, as they affect one way or another the electrochemical conditions of soils, either temporarily or more durably.

Crop diversification (including leguminous and AF) being the short term or medium main goal, we will focus on this one first. The type of crops grown and their sequence in rotations have a strong influence on soil Eh and pH, as biomass production and the amount returned to the soil greatly affect its organic matter content, which as we already explained serves as an electron reservoir and buffers Eh and pH fluctuations.

It is particularly important to consider the resource-use strategies employed by different plant species: resource-conserving plants, characterized by slow growth, high C/N ratio roots, and low root exudation (of amino acid-rich compounds), support a different microbiome than “exploring” plants. The latter, with faster growth, high photosynthesis, and high root exudation of low C/N compounds (primary metabolites: sugars, organic acids), promote a microbiome with more taxa involved in organic matter mineralization.

The extent to which livestock—especially ruminants—are reintegrated into the system can significantly enrich the soil with anaerobic taxa, thereby influencing how organic matter is transformed.

The other three are conventional agricultural practices, not regenerative in themselves, but part of a broader toolkit of risk changing<fnref n="58" />) production factors.

<footnote n="56">⁵⁶In favourable climates (high and regular rainfall, high but not extreme temperatures), soil evolution tends to be rapid. In more challenging climates (low rainfall, long dry seasons, extreme temperatures), soil evolution is slower.</footnote>

<footnote n="57">⁵⁷Providing an opportunity to surpass the sectarian squabbles between OF and SCA.</footnote>

<footnote n="58">⁵⁸We here borrow the term from Baumgärtner [2007]</footnote>
Soil tillage, as well as cart traffic and machinery passage, affect Eh and pH mainly by altering soil structure. Soil bulk density and aggregate size strongly influence the depth at which oxygen can diffuse. Tillage also affects pore continuity — positively in the short term but negatively in the medium term (especially when aggregate structural stability is low) — leading to anoxic conditions that are harmful to plants in wet conditions.

Irrigation or drainage, when feasible, strongly and rapidly affect Eh conditions, since oxygen diffuses 10,000 times more slowly in water than in air.

Calcium or magnesium amendments (lime, limestone, dolomite) can be applied to increase the pH of acidic soils whereas organic amendments have a more lasting effect on regulating Eh and pH, while also improving soil structure. Irrigation or drainage, when feasible, strongly and rapidly affect Eh conditions, since oxygen diffuses 10,000 times more slowly in water than in air.

## 10.5 Increased resilience and functional integrity at all scales: ecological states and indicators

In light of the above, we believe our initial hypothesis “Nature resilience as a standardized a system-level ultimate outcome?” should be further refined as follows: “Nature resilience and functional integrity as a standardized continuum of healthier ecological state outcomes at ecosystem(s) and biosphere-levels?” We shall now explore how intermediate and ultimate outcomes (or indicators thereof, ecological states as we shall see very shortly) should be measured.

### 10.5.1 Soil organic matter, the mother of all functional integrity indicators (at farm- to system-level), but a lagging one

In this paragraph, we quote Husson et al. [2024] in extenso without quotation marks — translation being taken into account. The authors contend that agriculture can be deemed regenerative only if the level of endogenous fertility of soils can be situated along trajectories. The notion of a soil's endogenous fertility aligns with that of soil health, in that both refer to its long-term ability to function as a living system capable of sustaining plant biomass productivity while also maintaining the ecological functions of the cultivated ecosystem over time (the notion of function integrity). These functions include contributing to the preservation of air, water, soil, and biodiversity resources, as well as overall health. Primary productivity and other ecosystem functions are highly dependent on these functions, as confirmed by Oldfield et al. [2019].

While many indicators relating to these various functions exist and may be more or less relevant to local pedoclimatic conditions and technical itineraries, Husson et al. [2024] mention two macro proxies that work well for soils containing 10% to 40% clay, which
includes the majority of cultivated areas in France<fnref n="59" />: the soil organic matter-to-clay ratio (“SOM”%/clay%) and the Visual Evaluation of Soil Structure (“VESS”). These serve as aggregate indicators of biological activity and the soil’s physico-chemical properties. The authors then define thresholds that can be used to characterize environmental conditions, which in turn determine the context-specific potential of systems and practices, as well as the technical and economic constraints for their implementation. While these indicators are firstly local (at farm-level), they can be aggregated at system-level, as we shall soon see.

It is noteworthy that SOM, soil carbon or soil health indicators indeed help confirm or
detect land change structural changes and functionality of the ecosystem processes, but
they demonstrate slower, more incremental changes than other (leading) ecological health
indicators, hence they are lagging indicators [Savory Institute, 2025]. They are typically
assessed every couple of years.

10.5.2 Other leading and lagging ecosystem health indicators, salient points from a Savory Institute's case study

While Husson et al. [2024] "only" mention soil indicators despite establishing a holistic paradigm, The US-based Savory institute has developed a science-based monitoring protocol that tracks ecosystem health and provides feedback to land managers — the EOV (standing for Ecological Outcome Verification) empirically-based data collection protocol. The Savory Institute raison d'être is "Regenerating the world's grasslands". The Institute promotes and implements Holistic Management, a decision-making framework developed by Allan Savory in the 1960s in the context of Holistic Planned Grazing<fnref n="60" />. This approach is designed to mimic the natural grazing patterns of wild herbivores to restore degraded landscapes.

This framework exemplifies a paradigm that resists the normalization or prescriptions of agricultural practices in favor of a principles-based, context-sensitive approach much like Husson et al. [2024]. EOV focuses on four ecosystem processes — water cycle, mineral cycle, energy flow<fnref n="61" />, and community dynamics — all part of the overall functional integrity. EOV measures tangible ecological outcomes — not just inputs or practices — through indicators that reflect the health and resilience of the landscape. Each implementation is ecoregion-specific, recognizing the diversity of environmental, cultural, and economic conditions that shape land management. The framework is designed to provide ongoing feedback to land managers, enabling adaptive decision-making and iterative learning,

<footnote n="59">⁵⁹Note that this seems to also be the case for Europe (https://esdac.jrc.ec.europa.eu/content/topsoil-physical-properties-europe-based-lucas-topsoil-data) and the US (https://daac.ornl.gov/cgi-bin/) as well. We have not explored other regions of the world.</footnote>

<footnote n="60">⁶⁰A method that integrates ecological, economic, and social factors to improve land health and productivity.</footnote>

<footnote n="61">⁶¹ie. the carbon cycle.</footnote>
much in the spirit of Husson et al. [2024]. It is not a certification tool but a learning mech-
anism, supporting land stewards in making informed, regenerative choices. In this way,
EOV moves away from rigid standards toward flexible, evidence-informed, and locally
grounded systems that empower practitioners and prioritize ecological function Savory
Institute [2025].

In practice, areas monitored under the EOV scheme are separated into broad ecological
regions, or ecoregions, ie. geographically and biodiversity-specific distinct assemblages
of natural communities and species combining the influences of climate, geology, and
landforms. Their defined degree of brittleness dictates the region's response to manage-
ment tools. Once each region's uniqueness, the impact of human influence through past
management and the functioning of the ecological region are understood, it is possible to
recognize the challenges and opportunities for regeneration, the possible ecological states
(which differ in terms of vegetation structure, state of the soil surface, productivity, and
ecosystem processes) and transition paths leading to them. The role of management tools
and natural processes in moving from one state to another is important.

Dynamic reference areas are established as the closest example of the desired future re-
source base in a particular environment for a given context. Indeed, best-known expres-
sion of biodiversity, site stability, and ecosystem function for a given ecoregion are used as
benchmarks. They are used to develop an evaluation matrix — Ecological Health Index
(or EHI score) — on the basis of leading ecological indicators for the specific ecoregion
and to update the boundaries of what can be achieved. The monitoring of regenera-
tion is analyzed by assessing the leading indicators on the Ecological Health Matrix.
These indeed have predictive value about the direction of changes and are very useful
for informing management. These indicators can in fact be split between biodiversity
indicators (live canopy abundance, microfauna, warm season grasses, cool season grasses,
forbs and legumes, trees and shrubs, contextually desirable species, contextually undesir-
able species), biodiversity-influenced ecosystem supporting indicators (litter abundance,
litter decomposition, dung decomposition) and abiotic indicators (bare soil, soil capping,
wind erosion, water erosion). Other than soil indicators, lagging indicators are either
biodiversity indicators (foliar cover of perennials plants by species, cover percentage by
functional groups, species richness) or biodiversity-influenced ecosystem supporting indi-
cators (litter cover, water infiltration) or structural indicators of land condition (bare soil
cover).

10.5.3 The “carbon farming/restoration for profit” ecosystem’s approach,
limits and opportunities from another case study

We interviewed a commercial manager at Agreena, a European agri-fintech company selling or intermediating Verified Carbon Units (VCUs) — ie. carbon credits, under the market-leading Verra VM0042 methodology. Under this methodology, projects developers
are allowed to use a mix of process-based models and sampling to estimate soil SOC
changes for emissions of VCUs.

Agreena has developed a satellite-based system for monitoring and modeling regenera-
tive transitions in agriculture. Following its acquisition of Hummingbird Technologies,
Agreena leverages advanced remote sensing and AI to automate the detection and analy-
sis of agricultural practices at the parcel level. Initially deployed in the UK and Ukraine,
the system integrates satellite imagery (including archives) with administrative data (e.g.,
CAP declarations, farm IDs, legal entities, and geolocated addresses) to identify and
screen fields.

It infers key agronomic parameters such as crop type, cover duration, tillage depth (up to 2.3 meters), and presence of cover crops. Using the farmer's validation, local biophysical parameters (e.g., temperature, rainfall, soil type, and regional soil organic matter levels), and regionally standardized fertilization and fuel consumption (reducing the reporting burden on farmers), they build the process-based SOC change transition model.

While we have not explored all the technicalities of both the model and its interaction
with the methodology, a couple of elements stand out. First, the only ecological health
indicator of interest to project developers — SOC — cannot be acquired by satellite
imagery (for reasons that are beyond the scope of this thesis). In addition, SOC has an
inherent lag in proving regeneration is indeed occurring, thus being of limited information
for decision-making. Husson et al. [2024]’s three conventional risk changing productions
factors also cannot be acquired from space. Only boots on the ground can provide such
information. Second, the process probably involves a high degree of standardization,
with the risk of overshadowing the hetereogeneity of regeneration paths. However, some
of Agreena’s data acquisition techniques could probably be leveraged to gather relevant
leading EOV ecological health indicators, of which the quality of vegetation cover and
semi-natural habitats.

Finally, it is worth highlighting that pastures are not currently within Agreena's business
plans, as by design, they do not benefit from the expected decrease in fossil fuels and
synthetic nitrogen fertilizers coming from respectively reduced tillage and cover crop -
which are a significant contributor to carbon offsets produced by their RA projects.

10.6 A research agenda for broader Nature-Positive insurance solutions?

10.6.1 Extending the framework to any Nature-Positive insurance solutions

The generality of the Husson et al. [2024] and the EOV scheme suggest our framing of
a new universal (agronomic<sup>62</sup>) paradigm for nature-positive RA (re)insurance solutions

<footnote n="62"><sup>62</sup>"technical" would replace "agronomic".</footnote>
could be deployed on any degraded ecosystem, as long as they are ecosystem-specific (defining ecoregions, the region/ecosystem specificity, the relevant ecological variables, the potential transition paths). As a consequence, an insurer or reinsurer looking at pushing a nature-positive agenda may need to target a relevant (to him?) type of degraded ecosystem whether natural (grassland, crop land, forests, deserts, etc...) or human-modified (e.g., urban green spaces, reclaimed industrial sites, or managed landscapes).

The EOV blueprint also shows a significant degree of process engineering to manage both the ecosystem complexity and uncertainty around the regeneration/transition phase towards healthier ecological states, involving multiple leading or lagging ecological variables or indicators (biodiversity, biodiversity-influenced ecosystem supporting service, abiotic or structural) together with an uncertain time scale and nonlinear phenomena at work. It is not for us to say whether grasslands are rather simple or complex within the ecosystem complexity spectrum, but it is easy to envisage even more complexity and uncertainty beyond our limited understanding. In any case, it becomes clear that the outcomes of such framework may be amenable to standardization, but not the process.

### 10.6.2 Combining the art and science of risk to enhance and add time in Baumgärtner's model

However, the insurance sector (especially on the life & health side of the business?) should have the skillset to analyze the multiple dimensions (including time) of this ecological problem and frame it within an extended and more complex version of Baumgärtner [2007]'s model. Indeed, the model's input is the level of biodiversity, the model's output the level of ecosystem services, a more or less complete indication of the ecosystem's ecological state, as we have suggested previously. By his own account: "one could easily generalize the analysis so that the stochastic production of the ecosystem service depends also on inputs other than biodiversity, say labor, capital, fertilizer or chemical pest control" and in fact on any of the indicator listed above or Husson et al. [2024] risk changing production factors. One of the challenges would thus lie in adding a time dimension to a currently "static" model, to account for milestones on regeneration paths. Another would be to include multiple ecosystem services as outputs to the model.

### 10.6.3 Unlocking capital for nature: leveraging standardized ecological states trajectories for capital insurance

The analysis of the Tahoe Donner Association case study showed that specific forestry practices resulted in a reduction of the risk premium charged by insurers for the wildfire peril. Although we did not use these exact same terms, it is in fact the relatively better ecological state — in steady state — of the forest (versus similar and in vicinity forests) as a result of practices, and thus the lower likelihood of wildfire risk resulting in undesirable consequences for this forest specifically, that was recognized and priced in by insurers.
We can see it as a form of ecological/natural capital insurance<fnref n="63" /> (against a specific peril) that could work also for healthy or already regenerated ecosystems. Indeed, RA is often associated with change and transition but several production models (permaculture<fnref n="64" />, agroforestry, organic farming, conservation agriculture) can claim the label without any modification to their practices [Duru et al., 2022].

While the Tahoe Donner Association case study features a noteworthy outcome, it happened well after the specific desirable forestry practices were undertaken. Insurance (in the form of yearly renewable “operational insurance” for natural catastrophes perils) in this case was not a catalyst for a better ecological state of the managed ecosystem and did not help the ecosystem managers to finance the incremental costs of changing practices (versus baseline)<fnref n="65" />. However, ex post, with the hindsight of the Tahoe Donner Association case study, should managers of an ecologically similar forest consider the implementation of similar risk changing practices, they could (theoretically) borrow money against the expected risk premium reduction.

The EOV scheme opens further avenues for more impactful insurance solutions which could help bridging the financing gap. Governments, corporations, financial institutions, NGOs are indeed all reluctant to finance ecological-related projects because of the inherently unpredictable and dynamic nature of ecosystems and the impact it may have on investment [United Nations Environment Programme, 2023]. And yet, regeneration can be framed within classes of transition paths (despite not being in "steady state" yet) with intermediate leading indicators of the ecosystem's ecological health along the way to full regeneration. Technically, this reduces unpredictability to shorter time frames and narrower ecological state outcome distributions<fnref n="66" />, addressing one of the hurdles to nature restoration investment intrinsic risk aversion (as highlighted by SCOR in the context of the NatReCo initiative). A clearer understanding of the intermediary ecological health of the ecosystem could help better price operational insurance during the regeneration process, resulting in additional insurance cover.

It is hard to imagine how a form of “capital insurance” — like NatReCo’s model — would not also benefit. With “standardized” ecological states trajectories for a given ecosystem — along with probabilities of successfully transitioning from one ecological state to another — then it may become possible to pool (i) what we might call “ecological

<footnote n="63">⁶³Insurance being based on values insured (in monetary terms), there remain a question on whether the values reflected the value of the ecological capital of the forest (rather than its direct economic value).</footnote>

<footnote n="64">⁶⁴Permaculture can allow for the elimination of synthetic inputs in vegetable farming due to the possibility of massive inputs of exogenous organic matter to the farm and a very high diversity of crops on small plots and possibly manual weeding. While very congruent with Soloviev and Landua [2016]’s regenerative mindset, it is not economically and technically transferable to large-scale farming systems and falls into the “distributed agroecology” category.</footnote>

<footnote n="65">⁶⁵It would nonetheless have resulted in lower capital reserving for insurers (versus baseline), freeing capital to insure more such projects, a desirable situation.</footnote>

<footnote n="66">⁶⁶Ecosystems will arguably remain dynamic by nature, but the concept of dynamically adjusted EOV reference areas can also help manage uncertainty.</footnote>
knowledge risk,” or more precisely, ecological uncertainty and/or (ii) what we might call “ecosystem functional evolution uncertainty”. This refers to the risk of temporary or total failure in the regeneration process. In this context, insurance would be designed to cover the costs required to correct for this “ecological knowledge uncertainty” or “ecosystem evolution risk” (nature’s act of god). Indeed, on average, such failures should be rare and would likely only result in limited additional CAPEX compared to the total capital expenditures of the regeneration project. In addition, a clearer understanding of the intermediary ecological health of the ecosystem should also help better ascertain the path towards reduced reliance on other risk changing factors (fertilizers, pesticides mostly). It is known to be a significant lever to increase medium term profitability, not the least because of market price volatility [Boston Consulting Group, 2023].

The same goes with carbon credit insurance. As we will explain later, we would not advise following this path unless under very specific conditions.
# 11 Shaping the contours of holistically Nature-Positive Regenerative Agriculture framework?

Our work opens the door to establishing a universal paradigm for RA — one that, while grounded in ecosystem management sciences, can also incorporate an insurance-oriented perspective by qualitatively and quantitatively framing the risks and uncertainties tied to the range of potential degraded ecosystem-specific non-linear time-dependent regeneration trajectories towards healthier ecological states, measured by both leading and lagging biodiversity, biodiversity-influenced ecosystem services or biotic/abiotic indicators, and supported by “man-made” risk changing factors. As we have indicated, the EOV blueprint for grasslands may hold promise for adaptation across other natures of degraded ecosystems (cropland, wetlands, forests, etc...), subject to further research tailored to each specific context.

## 11.1 Unresolved Nature-Positivity human dimensions, in search for a truly “nature-based” SCOR-centric way forward

However, this universal paradigm would only check the box for a narrowly-defined, nature-positive form of regenerative agriculture — one focused primarily on biodiversity and the biosphere. In essence, this “technical” RA model offers a solution to a problem framed purely in agronomical and ecological terms — not to be mistaken with agroecological terms as it does not specify the role of humans, technical capital and technology within that solution. As such, it could just as easily preserve the status quo as it could completely overturn it.

Yet, once we bring humans into the equation, the full scope of nature-positivity becomes riddled with tensions — ranging from divergent worldviews and ontologies to deep-rooted issues of power and equity. These distributive tensions manifest across multiple layers: within agrarian systems (land access, usage rights, access to capital resources between landowners and tenants), within the broader agrifood sector (governance, transfer pricing, decision-making between the production system and the distribution system), between agriculture and the non-agricultural sectors (looking for agriculture as an offset terrain for their own nature loss impacts), between agrifood/retailers and consumers and even between the Global South and Global North.

Therefore, it is now necessary to open up a new perspective — a different interpretive lens — capable of articulating the human, political, and ecological dimensions in a meaningful way for a global resinsurer, guided still by Cuckston [2022].
## 11.2 Rethinking the problem from the perspective of SCOR

Following a consistent framing used throughout the thesis, we now shift to a SCOR-centric perspective.

First, SCOR as a global reinsurer is itself nested within the distributive dimensions of society, much like any other corporation. Any attempt to integrate and solve the distributions inequalities would carry the risk of being considered arbiter and stakeholder, raising important questions about positionality and legitimacy to do so.

Second, it would be unreasonable to expect a global reinsurer to resolve the structural inefficiencies or inequalities embedded in the political, social, and economic organization of society. These challenges extend far beyond the agency of any single institution, let alone a reinsurer. As an illustration, the income gap between farm and non-farm workers analyzed in Dorin [2020] is not (at least directly, if at all) within SCOR's mandate.

Finally, all risk exposures stemming for systemic nature loss should inform our nature-positive framework, whether it is direct physical risks (P&C activities) or indirect human health risks (L&H activities).

## 11.3 Nature-Positive food systems: ecosystem health and human health, two sides of the same coin

To set the scene, it is worth quoting — in extenso — Dorin [2020] about the consequences of the search for economies of scale not only in agriculture but all along the commodity or value chain: “... this specialization, industrialization and commodification of biomass production has led to: an upstream deconstruction of the vast diversity of agricultural productions, and a downstream reconstruction or reformulation of an apparent diversity of final products, by combining industrially produced standardized materials (calories, plant or animal proteins, fats, fibers, vitamins, etc.). In such a process, most of the added value is captured downstream of the ‘commodity chain’ (food processing and distribution).”

Industrialized food systems promote ultra-processed foods that are low-cost but nutritionally poor [Duru and Therond, 2024, Duru et al., 2024] and now make up a significant portion of diets [Duru et al., 2024]. The food system encourages agricultural simplification upstream leading to a loss of nutrient diversity in food [Duru and Therond, 2024, Duru et al., 2024]. A diet made of ultra-processed foods leads to gut dysbiosis [Duru, 2022], which is linked to a wide range of chronic diseases (obesity, diabetes, cardiovascular diseases), undermining preventive health<fnref n="67" /> by failing to support microbiome diversity and resilience [Duru and Therond, 2024]. Once again, it is worth quoting — in extenso — Duru [2022] and ponder the following: “A Western-style diet has likely contributed to

<footnote n="67">⁶⁷Note: a French hydrological engineer, Louis-Claude Vincent, founded in the late 1960s a contested theory purporting to manage human health through the lens of homeostasis, see Castell [2023].</footnote>
its impoverishment, and this depleted microbiota, transmitted across generations, may
become irreversible<fnref n="68" />”.

Vidal [2023] stresses that while only 8% of biomass produced for food relies on pollination, these 8% are the difference between a healthy and bad diet. In another context where access to diversified food is also an issue — in India — hundreds of farmers operating the most synthetic inputs intensive farming operations in the world commit suicide every day due to over-indebtedness, while malnutrition and health costs have increased dramatically [Dorin, 2022].

In other words, everything is linked: ecosystem health and human health. Therefore, “transforming the objective outcomes of agriculture to encompass environmental and human health objectives is a first, and necessary, step in realigning food across multiple global goals” [DeClerck et al., 2023]. Unless the ecosystem is so severely degraded that it demands high-risk investments only large agrifood corporations can afford, a global reinsurer managing morbity, longevity and morbidity exposures should refrain from supporting projects that reinforce systemic lock-in — namely, the concentration of power in food processing and distribution — even if transforming the agrifood system lies beyond its direct mandate.

As a general rule, the broader version of RA should be grounded in Husson et al. [2024]'s primarily theoretical framing<fnref n="69" /> of a truly agronomically sound regeneration and support one of the operational dimensions introduced within the EOV — namely “Land to Market.” This would align with the visions articulated in Soloviev and Landua [2016]'s deepest RA forms. "Land to Market" functions as a regenerative sourcing solution, directly linking verified regenerative producers with brands and consumers, thereby fostering regenerative enterprise systems and regenerative producer webs.

11.4 What to do of technology?

Another fundamental question is how to navigate the spectrum between "nature-based" (or “low tech”) and technology-based solutions. While we have encountered this polarity in various contexts, we have not come across a comprehensive analysis of the terms and tensions shaping this debate. Taking on that challenge in full would be overly ambitious here. However, we can attempt to sketch a broad outline of the landscape.

First, we should avoid the overly simplistic conclusion that technological innovation in agriculture and RA must be rejected outright for fear of derailing the transition to agroecological practices at scale. On the contrary, we hope to have shown that the complexity

<footnote n="68">⁶⁸Interestingly, this extract is followed by: “This perspective invites a clearer definition of what constitutes a healthy microbiota. While the short-term effects of diet on microbiota composition are beginning to be understood, the long-term effects still require further study. In this regard, research on ecological restoration may offer valuable insights.”</footnote>

<footnote n="69">⁶⁹Albeit grounded in extensive agricultural experience around the world.</footnote>
of nature-positive RA insurance solutions — especially from the vantage point of a global reinsurer — calls for deeper investigation. Technology should make a difference in deepening our understanding of ecosystem dynamics — particularly regeneration and restoration — as well as the risks and uncertainties they entail, despite possible nature loss “scope 3 risk”. And even if "nature-based" solutions prove to be the most effective path forward, the role of a global reinsurer is to hedge against uncertainty. In that sense, technology may serve as a hedge against total ecosystems collapse — what one might call the ‘Elon Musk Mars put option’ (see *Musk's Mission to Mars*,” [Financial Times, 2025]). Less speculatively, some authors argue that agroecological principles can be merged with the technology pathway of progress [Duru et al., 2022], suggesting it is not necessarily binarily one or the other.

Dorin [2020] acknowledges the “fascinating and beneficial technical progress of the last century” in agriculture but cautions against the Descolian naturalist ontology that shapes its foundations: the “powerful formatting of thinking” inherited from the “positivist and mechanistic reductionism applied to the living world, focusing on non-human factors, linked by linear causalities, rather than systems made up of non-human — and human — factors constantly interacting and evolving together.”

First, while much attention is given to robotics, digital tools, and genetics, these innovations are often promoted by proponents of intensified agriculture, rather than by those advocating for AE approaches. This creates a risk of unintended consequences: if these technologies are only viable in simplified environments, their adoption could inadvertently drive further landscape simplification, undermining ecological diversity and resilience. The current deployment of these technologies tends to occur in highly simplified agricultural landscapes — monocultures of crops like maize or soy — rather than in the complex, diversified systems typical of AE [Couvet, 2023]. In a different context, Dorin [2020] stresses that India has completely failed to replicate the OECD CA model (the so-called Lewis Path), because of fundamentally different historical, demographic, and ecological conditions than those prevailing after World War II in OECD countries (abundant and cheap fossil energy, large-scale land consolidation, strong state support and infrastructure, low population pressure on land). The system being locked into a cycle of shrinking farms, rising costs, and low returns, leading to a socioeconomic and environmental crisis — what Dorin calls the agrarian crisis. In yet another illustration of this risk, the head of AgroSolutions explained how marginal pastures in entire regions of Southern France were turned in the 1990s into farmland thanks to the progress of chemistry for agriculture. These areas are currently in an agronomic deadlock given now more stringent chemical inputs EU regulation.

Nonetheless, echoing debates around generative AI, “we cannot and should not ignore these tools. We must find ways to appropriate and adapt them. Therefore, civil society and experts must remain vigilant. It is crucial to assess the social and environmental
sibilities to farmers, rather than decarbonizing their own operations. The certification
ecosystem is also under scrutiny. Several major certifiers have faced controversies over
the robustness of their methodologies (including on additionality), raising doubts about
the credibility of the credits being issued. Meanwhile, the limited upside on Verified
Carbon Unit ("VCU") prices creates incentives to produce low-cost credits at scale —
potentially encouraging the conventionalization of carbon farming and undermining its
ecological ambition.

That said, SCA-inspired RA is where capital is flowing and where technology-driven so-
lutions for nature are actively being developed and engineered. The challenge — and
opportunity — for (re)insurers and capital providers is to keep informed about tech-
nological advances and apply discernment when supporting SCA-inspired RA or carbon
farming projects — ensuring they are contextually relevant and ecologically sound, rather
than endorsing the ecosystem or excluding it indiscriminately. One criteria could be to
sponsor carbon farming only for very degraded ecosystems. As Husson et al. [2024] ex-
plain, below a SOM threshold, the regeneration is very uncertain, investments high and
risks elevated. Only large agrifood corporations (or even the state) may have the balance
sheet to run these projects.
# 12 SCOR in Regenerative Agriculture: outline of a strategy

## 12.1 Regenerative Agriculture economics, the art and science of accounting

So far, we only discussed the agronomic and organizational dimensions of a truly regenerative agriculture, but not its economic dimension. Obviously, the economic performance is largely a function of the ecological performance, but there are also several other purely “economic” and market-driven parameters to consider. Regenerative Agriculture is indeed purported to offer an opportunity to reduce reliance on costly "man-made" risk changing factors (fertilizers, pesticides, etc...), optimize livestock/farming organic recycling (a form of circular economy), stabilize and increase yields under more unstable and degraded climate conditions, diversify revenues (through product diversification) including by tapping nascent markets and payments for environmental services (for either carbon or biodiversity) and finally retain more food production and distribution added value upstream. Stakeholders should and may well also one day value the ecological capital rebuilt through Regenerative Agriculture as a key component of the farm operations' balance sheet.

However, at the end of the day, farmers operate farms to earn a living now and face a capital allocation decision under uncertainty — namely whether they should invest in RA and if so to which extent. Besides liquidity/funding constraints, a key barrier to adoption is the essentially uncertain and risky trade-off<sup>70</sup> between short-term loss and long-term gains (short-term versus long-term productivity, short-term adaptation to climate shocks versus sustainable adaptation to climate change, etc...)[Dabalen et al., 2024].

While farmers do know their own business economics and have a certain level of information relative to investment opportunities and expectations — subject to the above —, capital providers and (re)insurers face a different situation. They need to assess the relative risk between farms shifting (or not) to regenerative agriculture as (a limited amount of) capital should naturally flow to less capital-intensive and risky projects first. Indeed, (re)insurers need to make sure they provide insurance capital to projects ticking the boxes of the presented framework, and within this spectrum, those displaying “best-in-class” risk profiles. Indeed, the more successful the projects — the less risky the projects are —, the more (re)insurers can build reserves over time and offer further insurance capital to more challenging or "marginal" projects.

<footnote n="70"><sup>70</sup>This trade-off being typically starker for smallholders in African countries [Dabalen et al., 2024].</footnote>
RA can involve small farms<fnref n="71" />, mixed farms<fnref n="72" /> or crop farms<fnref n="73" /> [Boston Consulting Group, 2023] and different levels of implementation (basic, intermediate, advanced) [Boston Consulting Group, 2023] or investment (none, limited, full)<fnref n="74" /> [Deloitte Netherlands, 2025]. Crop type grown or grassland type may influence the regeneration risk profile, as may the land or ecosystem degradation level, the weight of expected (if any) payment for ecosystem services<fnref n="75" /> in the revenues profile, the opportunity cost of growing legumes given the subsidies provided by public authorities, the new market risk exposure, green loans' availability and so on and so on... Three reports either purporting to make the economic business case for RA or assessing the costs and benefits of transitioning to "sustainable agriculture" in EU were explored. Unfortunately, none provided the level of detail or robustness need to draw firm conclusions. Arguably, it is a difficult exercise as practices can be combined or stacked (with different timeframes), on all or part of the farm, etc...

Moret-Bailly and Muro [2024] do have very wide investment range (and seemingly asymmetric distribution) for practices covered, include incremental costs of transition, but do not have expected extra benefits in monetary terms. "RA" standalone practice assessment is not usable. For oilseeds and cereals, Boston Consulting Group [2023] presents — for basic and intermediate implementation — profit waterfall chart between implementation start and 6 years later but provide little information on associated investments. It is stated that the basic implementation requires no structural change, yet the investment for direct seeding equipment would be about 2000 euros/ha. It is thus difficult to compare reduced tillage and cover cropping on an incremental return basis. For 6 RA practices and 34 crop country combinations across 12 crops (including high and low yield density crops) and 10 countries, Deloitte Netherlands [2025] assess the average yearly net profit impact of implementation. Investment cost and operational costs are added, following creative accounting principles. Net profit impacts are not rebased for ex ante profit, thus not reflecting inherently stronger economics for high yield density crops such as potato. Investment figures are north of BCG's. Finally, grasslands are not assessed quantitatively in either Moret-Bailly and Muro [2024] or Boston Consulting Group [2023] and it is an afterthought in Deloitte Netherlands [2025].

Despite the confusion, one conclusion seems to stand out: although reduced tillage would result in the highest incremental profit per hectare, half of the incremental profit would be achievable at virtually no investment cost for either cover cropping or undersown cropping, two agrobiodiversity principles recommended by Husson et al. [2024]. This assumes the comparison of these practices on a standalone basis makes sense, as they are

<footnote n="71">⁷¹In Germany, small farms range up to 50 hectares, with a 50/50 split between cropland and grassland.</footnote>

<footnote n="72">⁷²Average 300 hectares in size and are composed, on average, of two-thirds cropland and one-third grassland, including grazing land or cattle and grassland for feed.</footnote>

<footnote n="73">⁷³Average size of 1,000 hectares, and consists entirely of cropland, with no livestock.</footnote>

<footnote n="74">⁷⁴Essentially the idea is the same. As you move towards the RA “intensity” spectrum, more upfront investments are required.</footnote>

<footnote n="75">⁷⁵Currently limited to carbon credits.</footnote>
often mentioned as put in place (to some extent) jointly, and that there are no hidden
/opportunity) cost. Notwithstanding these caveats, we hypothesize that there is a bias
in no-till and direct drilling equipment cost per hectare as the weight of crop farms (i.e.
large farms) relative to all farms would tend to result in an underestimation of the actual
capital cost for medium sized farms — such effect would not or to a much lesser extent be
at play with cover crop or undersown cropping. Finally, “biodiversity-enhancing features”
(i.e., SNH) are explored in Moret-Bailly and Muro [2024] and Deloitte Netherlands [2025]
and are less-capital intensive than reduced tillage (respectively 250 EUR/ha versus 336
EUR/ha and 104 EUR/ha versus 122 EUR/ha) to be compared with Faure and Mouysset
[2025], 50 EUR/ha insurance value of SNH (equivalent to a 2 to 5 year payback period).
The value of SNH (versus reduced tillage) may well be underestimated for medium size
farms due the same bias.

Time horizons associated to each investment class of RA practice are all but anecdotical
if lower risk/uncertainty regeneration trajectories are to be targeted first.

12.2 The poster child of investable and insurable Regenerative Agriculture

Taking into account all the findings we have presented, we can outline the desirable
features for an investable and/or insurable RA project.

We would advise to avoid overly simplified and very degraded large-scale cropland under
challenging climate conditions, as it would be more capital-intensive and risky. These
projects could still be supported with a view that the land sharing / land sparing debate
is unlikely to ever be settled. More realistically, LSP landscapes cannot fundamentally
change overnight and a functional RA approach does make sense as a starter.

Our preference would however go for less capital-intensive, less risky and less degraded
ecosystems under temperate climate conditions. These projects have a higher chance of
successful regeneration and/or may be at risk of falling in the very degraded ecosystem
category, resulting in their regeneration being in the end even more costly and uncertain.
We thus disagree with Moret-Bailly and Muro [2024] statement that: “funding for costly
practices could at first focus on particularly degraded or vulnerable agricultural land”. It
is more prudent to save (at lower cost) what can still be rather than risk more capital in
ecosystems that may no longer be salvageable.

Ideally, the project should already be benefitting from some agroecological infrastructures
or semi-natural habitats and some form of LSH fragmentation. Indeed, one of the key
takeaways from Husson et al. [2024] is that changes should be gradual rather than brutal.
It is a very relevant point beyond ecological management: business performance being
already uncertain in steady state (illustrated by the need for a portfolio of risk-changing
factors), changes should be introduced smoothly <fnref n="76" />, even if negative externalities remain
for a period of time. Otherwise, it would likely be more challenging to isolate the effects
of changes (versus baseline) and build ecological informational knowledge fundamental
to adaptive management. While we have not explored the (time-varying) presence of
regeneration leading indicators as a function of ecosystem type and degradation level, we
would contend that overly simplified and degraded cropland would feature fewer (lead-
ing) indicators (other than often delayed SOM) to inform ecosystem management and
regeneration derisking. The extent to which this statement may be true shall be further
explored.

Taking all this into account, degraded pastures in OECD countries may well be the sweet
spot for investors and insurers, not only because they seem to offer more leading indica-
tors of recovery and limit the "worldview inadequacy to local context" risk. They indeed
also require rather lower investment (other than more costly agroforestry infrastructure).
And in pastures context, agroforestry induces little opportunity cost in the form of lost
productivity (currently limiting investment in cropland) but derisks future revenues by
virtue of diversification. Ideally, we would rather be in a situation where we could hypoth-
esize momentum regeneration in pastures to gradually spill over to surrounding croplands.
Indeed, implementation of more complex crop rotation can be derisked by proximity with
pastures (addressing the “opportunity cost of legumes” [Boston Consulting Group, 2023])
and livestock looking for additional fodder to implement adaptive mowing or grazing
and further derisk pastures’ regeneration.

Within this category, we would rather see the project being part of province or regional
scale regeneration program uplift to leverage diversification of regeneration transition
paths [Savory Institute, 2025] and aim for regional enhanced resilience as a systemic
ecological state. Therefore, for a given insurance capital offered, we would rather see 10
renegeration projects within the scope of insured assets rather than only a few, to build
more qualitative and quantitative knowledge on regeneration. It probably means that
average farm size (or relevant regeneration plot) should not exceed a certain threshold
(50 hectares?).

Since the development of agroecological models is not only hindered by agronomic and
economic barriers to adoption but also imply advancing ecological knowledge, particularly
regarding biodiversity, and increasing landscape complexity [Couvet, 2023] and reorgani-
zation of land parcels and decisions regarding crop rotation and planting schedules, often
extending beyond the boundaries of a single farm[Husson et al., 2024], we would advocate
targeting regions facing an agronomical deadlock rather than currently highly profitable
high yielding crop producing regions. Mediterranean regions have no choice and are first

<footnote n="76">⁷⁶As Boston Consulting Group [2023] argues: “At the outset, the focus needs to be on encouraging them to make no-regret moves to achieve early successes while reducing any perceived risks to a minimum.” High cost investment do not always fit within this acute assessment.</footnote>
impacted by climate change. (Re)insurers would have a vested interest in promoting
farming approaches that provide barriers to the progress of detrimental consequences of
climate change towards the northernmost regions of Europe or the US<sup>77</sup>, not just for
agriculture, but by protecting watershed and catchment areas with high industrial P&C
exposures.

As "there are no formal requirements towards suppliers signaling clear evolving mar-
ket demands for regenerative practices, monetisation of ecosystem services is still in its
infancy, and financial sector investments in mostly short-term yields are insufficient to
finance the longer-term transition" [Deloitte Netherlands, 2025], it would make sense to
target regions that not only have no choice, but are also less integrated to the agrifood
system and have higher unemployment rates. It would align better with Soloviev and
Landua [2016]'s regenerative enterprises systems and producer webs.

Finally, discussions are currently underway in Brussels to introduce a new target: achiev-
ing 30% RA by 2030, in addition to (and not replacing) the existing 25% OF target,
which may/could include a restructuring of the CAP. A common definition of RA is also
being developed — which would include a requirement of at least 10% semi-natural habi-
tat per square kilometer, such as grasslands [Vidal, 2023]. We hypothesize that any such
regulatory support — typically on a per square kilometer basis — would have higher
ecological return, everything else being equal, in the context of pastures.

<footnote n="77"><sup>77</sup>A symetric case could be made in the Southern hemisphere.</footnote>
# 13 Conclusion

Nature-Positive Regenerative Agriculture which insurers and reinsurers could support starts with an exploration of the nature and nature-positivity concepts, offering a glimpse as to the complexity of the topic. The nature-positive literature illustrates the underlying western-centric worldviews/ontologies at work supporting the international public policy agenda. Cuckston [2022] proposes a pragmatic solution to circumvent the fundamental and inherent contradiction in unlocking capital for nature. It consists in assuming an exclusively global reinsurer-centric approach to nature loss systemic risk, in terms of impacts to its own and clients' business interests. Even within this frame, for a global reinsurer claiming to combine the art and science of risk to protect people, families and societies, the lure of a business opportunity (restoring nature) is fraught with an ocean of risks: focus loss risk, "underwritten risk" risk, moral hazard risk, "technosolutionism bias" risk, nature loss risk, greenwashing risk, sciencewashing risk, opportunity cost risk, existential risk, misleading investors risk.

Two main lineages of the “regeneration” concept in agriculture, organic farming and soil conservation agriculture, were first explored. Both emerged in the Global North where chemical/industrial agriculture spread the fastest and the furthest. Both further consolidated as alternative practices and sciences to conventional agriculture to address the environmental limits of the latter. Two meta-analyses conducted in 2020 by respectively Schreefel et al. [2020] and Newton et al. [2020] about Regenerative Agriculture agree that both organic farming and conventional agriculture are fungible in Regenerative Agriculture (or conversely Regenerative Agriculture can embark both) around the agronomic goal of regenerating the soil, its fertility and health, all of which are fundamental to a well-functioning cultivated ecosystem. These two papers, through different approaches, shed light on a fundamental feature of regenerative agriculture, its apparent aspiration to scale up from the physical and ecological base compartment of agricultural production since the dawn of age — the soil — to a broader object, beyond the farm level potentially as far reaching as the whole food-system, having economic, social and ecological benefits — the three dimensions of the conventional sustainability narrative.

Given the lack of convergence on the exact dimensions and the reach of this RA scale up, the third “umbrella” alternative sustainable agriculture narrative to conventional agriculture — namely agroecology — was then explored. As a result, we further framed the (inherently open to interpretation) RA scale up aspiration from the soil to a broader or holistic object, as being how social, technical and economic structures are organized within the ecological Matryoshka dolls continuum (cultivated ecosystems / “natural” ecosystems / biosphere), for the purpose of rendering more or less global services beyond mere food production, which necessarily raises the question of (conflicting) ontologies. The third pillar of agroecology — namely biodiversity — was then questioned through the lens of the longstanding and central land sharing / land sparing discussion in conservation and
agricultural policy. The analysis of this at times very technical discussion demonstrated both the evolving understanding of biodiversity as a key driver to “naturally” functioning cultivated ecosystems within acceptable planetary boundaries and the various uncertainties and implications of land use strategies, including the “distributive” dimensions. Environmental issues are not just ecological or technical problems — they are deeply political and distributive in nature as environmental policy steering often result in uneven distributions of benefits and burdens.

Through this same distributive lens, the last alternative sustainable agriculture narrative, sustainable intensification, was shown to embark a form of technological determinism supporting its deployment and prone to strategic alliances within the land sharing / land sparing discussion between key stakeholders of the prevailing sociotechnical regime and conservation NGOs. Further to the fall out of fashion of sustainable intensification, RA was then reframed as the potential new unsustainable sustainable agriculture narrative, caught between previous alternative sustainable narratives seeing it as a new platform to reclaim relevance and running the risk of being co-opted or “carbon-captured” by the dominant and most powerful voice within the Regenerative Agriculture "discourse coalition". Through a similar lens, it became clear that agroecology, perhaps the most compelling sustainable agriculture narrative — for it is grounded in biodiversity —, was likely to be marginalized due to its normative rejection of the prevailing sociotechnical regime, ultimately surrendering its transformative potential to a co-opted version of itself: ‘junk agroecology’.

Amidst all these challenges, a truly holistically “nature-positive” and “regenerative” agriculture can neither be defined nor be amenable to practices-based standards, notwithstanding the near impossibility of gathering strong and context-based evidence. Soloviev and Landua [2016]’s framework for different Regenerative Agriculture ambition levels (the deepest of which being transformation of both the agrarian and the agrifood systems) exposes a fundamental flaw in attempting to define and standardize agriculture (and Regenerative Agriculture), in absolute terms and a fortiori in the context of insurance and finance, despite business models calling for such framing.

If anything were to be standardized, it should be the broad principles leading to better ecological states — specifically, those in which nature turns out to be more resilient, and the world remains insurable. This argument stems from the unique vantage point of a global reinsurer, tasked with managing the nested risks of both insured businesses and insurance companies from the business (or ecosystem-level) to ecosystems, societies and the biosphere. It also builds on both our earlier conclusions about what nature-positivity means for a global reinsurer and recent perspectives expressed in leading financial press. The insurance of enhanced ecological states (the gradual and final outcomes of the regeneration process) involves classic moral hazard risk, hence the usual temptation (in agriculture) to set practices-based standards. However, the option value of not setting
practices-based standards (but only broad principles) exceeds the downside in setting
some (nature loss moral hazard risk), especially when there are tensions around the def-
inition of a potentially undefinable object such as Regenerative Agriculture.

Indeed, while standard industrial assets technically warrant framing insurance within a
universe of risk where outcomes and probabilities are known, ecosystems — by nature
and notwithstanding the exact role of man in influencing their evolution — are constantly
evolving, as is our ecological understanding of their functioning. Ecosystems should thus
be framed in a universe of radical uncertainty, where neither the outcomes nor their
probabilities are known, acknowledging decision-making is particularly challenging.

Counterintuitively, radical uncertainty in nature and ecosystems should be seen as an
opportunity rather than a challenge for ecosystems restoration and Regenerative Agri-
culture, as we are no longer able to decide what kind of nature we want but rather we are
now in a situation of negotiation with nature. Soloviev and Landua [2016] call for their
systemic and evolutionary deepest expressions of Regenerative Agriculture to leverage
antifragility defined as “a large step beyond resilience, [...] the property of a system
that actually benefits from disorder and disturbance” in the field of finance. They do so
without drawing the parallel with built-in ecological antifragility in soil, biodiversity and
ecosystems in the form of natural selection of random mutations best suited to survival
and reproduction.

The central role of biodiversity in "self-managing" environmental stochasticity — namely
the variance of a given ecosystem service — was first demonstrated by Baumgärtner [2007]
in a seminal paper. Using a simple yet elegant model under conditions of risk, he showed
that biodiversity could be seen as a form of natural insurance substitutable to other stan-
dard "risk changing" production factors (off-farm inputs) to an extent depending on the
cost of biodiversity, its scarcity and the ecosystem manager's risk aversion. The insurance
value of biodiversity is “its marginal value in its function to reduce the risk premium of
the ecosystem manager's income risk from using ecosystem services under uncertainty.”
An empirical study from Faure and Mouysset [2025] on the insurance value of natural
pest control provided by grassland areas in the context of oilseed rape in western France
highlights the challenge in shifting from passive moral hazard risk (by providing either
affordable synthetic inputs or market-based insurance risk changing factors) to active
and appropriate insurance valuation of biodiversity, due to availability and affordability
considerations. Another insightful case study shows how insurers explicitly accounted
for the wildfire risk reduction benefits of forestry practices (leading to an enhanced eco-
logical state) by using compared historical fire analysis between areas with such fire risk
management “best practices” and baseline conventional areas.

As it happens, Husson et al. [2024] precisely lay the foundations of a universal agronomic
framework for a truly “regenerative” agriculture framework grounded in (agro)biodiversity,
which could support the definition of principles-based standards. To our knowledge, no other authors have so clearly articulated the need to regenerate agriculture by maximizing photosynthesis energy entering the system and managing it through the lens of homeostasis. Building on latest relevant studies, three natures or levels of biodiversity can be relied upon to regenerate the system: crop diversification with or interseeding of legumes, agroforestry, livestock integration, to which semi-natural habitats can justifiably be added — further to research showing their critical role in maintaining ecological functional integrity at all scales. Husson et al. [2024] draw our attention to the non-linear time and climate-dependent regeneration dynamics and calls for adaptive management of agricultural practices — namely other Baumgärtner [2007] risk changing factors — through the homeostasis lens. The authors advocates for gradual rather than brutal approach to regeneration without excluding off-farms inputs (intrants and pesticides) or soil balancing additives (calcium, magnesium, organic amendments or biochar) at the beginning of recovery, especially for very degraded ecosystems in which case investments are riskier.

Husson et al. [2024] confirm soil organic matter is the mother of all indicators of regeneration, enhanced resilience and ecological functional integrity. The Savory Institute — whose raison d’être is to regenerate the world’s grasslands — has developed an Ecological Verification Outcome certification tool which offers valuable operational insights showing the relevance and tangible applicability of Husson et al. [2024] proposed new Regenerative Agriculture framework in the context of insurance. Soil organic matter is indeed critical but there can be other relevant parameters to monitor the improving functional integrity of an ecosystem (ie. its improving ecological states trajectory). There is probably a (modelling) research avenue to frame “ecological knowledge risk” and “ecosystem evolution” uncertainty within ranges of potential degraded ecosystem-specific pedoclimatic-specific non-linear regeneration trajectories towards healthier ecological states, measured by both leading and lagging biodiversity, biodiversity-influenced ecosystem service or biotic/abiotic indicators (of which soil organic matter), and supported more or less durably by other “man-made” risk changing factors.

The EOV blueprint for grasslands may hold promise for adaptation across other natures of degraded ecosystems (cropland, wetlands, forests, etc...) and even artificialized ecosystems, subject to further research tailored to each specific context. With their actuarial firepower, reinsurers and insurers can combine the art and science of risk to extend a generalized version of Baumgärtner [2007]'s model with a time dimension to assess the evolution of ecological states of a given ecosystem but they lack ecological knowledge and expertise to do so. In this context, operational, invested capital and ecological capital<fnref n="78" /> insurance options either indemnity-based or parametric (against named perils or regeneration “acts of god”) should be further explored, with economic/ecological efficiency in

<footnote n="78">⁷⁸of which carbon credits are the obvious subcategory.</footnote>
mind.

In essence, this “technical” Regenerative Agriculture research agenda offers a solution to a problem framed purely in agronomical and ecological terms but not "agroecological" terms as it does not specify the role of humans, technical capital and technology within that solution. Yet, once we bring humans into the equation, the full scope of nature-positivity becomes riddled with tensions — ranging from divergent worldviews and ontologies to deep-rooted issues of power and equity. These distributive tensions manifest across multiple layers: within agrarian systems (land access, usage rights, access to capital resources between landowners and tenants), within the broader agrifood sector (governance, transfer pricing, decision-making between the production system and the distribution system), between agriculture and the non-agricultural sectors (looking for agriculture as an offset terrain for their own nature loss impacts), between agrifood/retailers and consumers and even between the Global South and Global North.

Cuckston [2022] is again our lighthouse, suggesting rethinking the issue from the perspective of a global reinsurer, acknowledging its own position within the distributive dimensions of society, much like any other corporation. Any attempt to integrate and solve the distributions inequalities would carry the risk of being considered arbiter and stakeholder, raising important questions about positionality and legitimacy to do so. It would be unreasonable to expect a global reinsurer to resolve the structural inefficiencies or inequalities embedded in the political, social, and economic organization of society.

There is a way forward however, consisting in looking again at global reinsurers and insurers' risk exposures. The industrialization of agriculture has led to an upstream deconstruction of the vast diversity of agricultural productions, and a downstream reconstruction or reformulation of an apparent diversity of final products, by combining industrially produced standardized materials (calories, plant or animal proteins, fats, fibers, vitamins, etc.). In such a process, most of the added value is captured downstream of the 'commodity chain' [Dorin, 2020]. This transformation favors ultra-processed foods that are nutritionally poor but economically efficient, contributing to widespread dietary simplification. This shift has resulted in a significant loss of nutrient diversity and contributes to gut dysbiosis, a condition linked to chronic diseases such as obesity, diabetes, and cardiovascular issues [Duru, 2022, Duru and Therond, 2024]. The Western-style diet, by depleting microbiome diversity, may cause irreversible harm to human health across generations. Put simply, everything is connected — human health and the health of ecosystems are two sides of the same coin. We cannot hope to restore ecosystems while turning a blind eye to the deep-rooted flaws in our agrifood systems. It lends credit to Soloviev and Landua [2016] deepest expressions of Regenerative Agriculture which the EOV certification exemplifies in promoting a regenerative sourcing solution, directly linking verified regenerative producers with brands and consumers, thereby fostering regenerative enterprise systems and regenerative producer webs.
Navigating between "nature-based" and "tech-based" solutions in agriculture requires nuance. Technology should not be dismissed outright, especially given its potential to enhance understanding of ecosystem (regeneration) dynamics and serve as a safeguard against collapse — what some call the “Elon Musk Mars put option.” However, many innovations are designed for and tailored to industrial agriculture, risking further ecological degradation. In their pursuit of scalability, nature project developers, funders and insurers must critically assess these tools for all their impacts, ensuring they are context-sensitive and do not trigger unintended consequences. For in the end, the prudent bet might be to just let nature take its course, much like agroecology or the more profound versions of Regenerative Agriculture promote decentralized regenerative hubs that foster local knowledge and adaptive governance.

Although carbon farming is promoted as a climate solution, its current implementation faces major structural and scientific challenges. The business model is weak, especially for complex regenerative practices, and soil carbon builds slowly, making (final) outcomes hard to measure and verify. There is also a risk of misuse — where corporates use carbon credits to avoid real emissions cuts — while low credit prices on the back of a (lasting?) global pullback on ESG themes may incentivize ecologically shallow practices. Given these issues, insurance support to soil conservation-inspired regenerative agriculture (if any) should focus on most severely degraded ecosystems where it can be a first step in regeneration.

In outlining the contours of a playground for regenerative agriculture insurance and reinsurance, an economic perspective was also essential. Data is scarce and originates mostly from grey literature. With consistently poor-quality data, we probably derive a conclusion to be further explored: "nature-based" low capital intensity regenerative solutions are not being evaluated on equal footing with technology-driven, higher capital intensity solutions — largely due to a biais arising from the farm size distribution being skewed to the upside, undermining the case for low capital intensity "nature-based" solutions (the economics of which are largely insensitive to farm size).

Finally, supported by our findings, a strategy for investors and (re)insurers to deliver over time the lowest risk / highest ecological and nature positive cumulative return would probably be to first unlock capital and insurance for moderately degraded and less capital-intensive (50 hectares or less?) pastures in agronomic deadlock areas. In any case, more quantitative research combining ecological and actuarial expertise would be required to understand the relationship between the ecosystems' degradation levels, the required regeneration capital investment intensity, the ranges of potential regeneration transition paths and ecological states, and the associated risk profiles from both an ecological and economic standpoints. It would be a prerequesite to frame how and at which scale risk sharing, transfer and trading from ecosystem managers to insurers and reinsurers can occur, as well as how the latter can diversify their ecosystems regeneration exposures
across ecosystem types and regions.
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# 14 List of Acronyms

AI – Artificial Intelligence

AE – Agroecology

AF – Agroforestry

AFD – Agence Française de Développement

BCG – Boston Consulting Group

CA – Conventional Agriculture

CAP – Common Agricultural Policy

CBD – Convention on Biological Diversity

CCMSF – Continuous Cover mix-species forestry

CIC – Community Interest Company

COP – Conference of the Parties

CRCF – Carbon Removals and Carbon Farming (EU regulation)

CSA – Climate Smart Agriculture

CSR – Corporate Social Responsibility

EASAC – European Academies' Science Advisory Council

EIL – Environmental Impairment Liability

EOV – Ecological Outcome Verification

ES – Ecosystem Service

FAO – Food Agriculture Organisation

FST – Farming Systems Trial®

FT – Financial Times

GBF – Global Biodiversity Framework

GEF – Global Environment Fund

GHG – Greenhouse Gas

ISO – International Standards Organization

IPBES – Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services

IUCN – International Union for Conservation of Nature

LSH – Land Sharing

LSP – Land Sparing

LSS – Land Sharing Land Sparing (debate)

MRV – Monitoring Reporting Verification

NABU – Nature and Biodiversity Conservation Union

NCP – Nature's Contributions to People

NGO – Non-Governmental Organizations

NPI – Nature Positive Initiative

OCA – Organic Conservation Agriculture

OECD – Organisation for Economic Co-operation and Development
OF – Organic Farming/agriculture

ONF – Office National des Forêts

ORA – Organic Regenerative Agriculture

P&C – Property & Casualty

PD – Property Damage

PES – Payment for Ecosystem Services

RA – Regenerative Agriculture

RI – Reinsurance

SAI – Sustainable Agriculture / Intensification

SBTN – Science Based Targets Networks

SCA – Soil Conservation Agriculture

SCOR – Société Commerciale de Réassurance

SER – Society of Ecological Restoration

SMART – Specific Measurable Achievable Relevant Time-Based

SOM – Soil Organic Matter

TYFA – Ten Years For Agriculture

TNFD – Task for Nature Financial Disclosures

UN-SEEA – UN System of Environmental-Economic Accounting

UNCCD – UN Convention to Combat Desertification

UNEP – UN Environment Program

USDA – United States Department of Agriculture

WB – World Bank

WEF – World Economic Forum

WTW – Willis Towers Watson

WWF – World Wide Fund for Nature