Every field carries a memory.
Of rain-soaked mornings and harvest dusk. Of hooves and hands, of markets and subsidies, of continuity. To convert farmland into forest is not a neutral act—it is a trade. And trades demand choices. When we plant trees where livestock once grazed, we don’t just grow timber—we give something up.
This is the heart of opportunity cost.
In Chapter 8 of Applied Environmental Economics, the authors confront this trade directly: they model what is lost—in income, productivity, and tradition—when land used for agriculture is shifted to woodland.
It’s an economic chapter, yes. But also a human one. Because land is more than a ledger entry. It is livelihood.
What Is Opportunity Cost?
In economics, opportunity cost is what you forego by choosing one option over another. If a hectare of land can produce £300 in sheep farming profits each year, and you turn it into woodland, that £300 becomes your opportunity cost.
It’s the ghost value of the road not taken.
But in the real world, estimating this is not simple. Farms are not uniform. Landscapes vary. Prices shift. And some losses are financial, while others are harder to name.
That’s why this chapter matters. It builds a model—spatial, empirical, and dynamic—to estimate the true opportunity cost of afforestation, field by field.
Farming Types and Profit Models
The researchers focus on two dominant farming types in Wales: sheep farms and dairy farms. These are not just economic categories—they are cultural pillars of rural life.
Using detailed data from the Farm Business Survey of Wales (FBSW), the authors develop multi-stage models that estimate farm income per hectare. These models account for:
- Livestock numbers.
- Crop types and yields.
- Input costs (e.g. feed, labor).
- Subsidies and grants.
- Local environmental and climatic conditions.
They then cluster farms based on income patterns and land use profiles. This allows them to group similar farms together and understand what makes one more or less profitable than another—even across diverse geographies.
From Accounts to Landscapes
But these aren’t just spreadsheet models. Using Geographical Information Systems (GIS), the authors map their findings across Wales. Each 1 km² cell is assigned a predicted income value based on its characteristics.
The result is a visual map of agricultural profitability. It shows where farming thrives—and where it struggles. Where opportunity costs are high—and where they’re surprisingly low.
This spatial insight is essential. It allows decision-makers to target afforestation efforts in areas where the cost of converting farmland is minimal—thereby increasing the net benefit of woodland creation.
Shadow Values and Social Perspective
Importantly, the chapter doesn’t stop at farm-gate income (what the farmer earns). It goes further to calculate shadow values—adjusted figures that reflect the social value of production.
This means removing distortions caused by subsidies, taxes, or market failures. For instance, a farm might seem profitable thanks to government payments—but from a purely economic standpoint, society may be subsidizing an inefficient use of land.
By stripping away these subsidies, the shadow value provides a cleaner picture: what is this land really worth, in productive output alone?
And sometimes, the answer is sobering.
When the Ground Gives Less
In many upland areas of Wales, especially sheep-dominated regions, the models reveal marginal profitability—even when subsidies are included. In some places, the opportunity cost of switching to woodland is near zero.
This changes everything.
It means that, in some regions, converting farmland to forest is not just environmentally wise—it’s economically sound. Not because we devalue farming, but because we recognize when the land is quietly asking for something different.
The Emotional Undercurrent
Beneath the equations runs an emotional current. Farming is not merely economics. It’s generational. It’s identity. And yet, the landscape is changing—ecologically, economically, climatically.
By modelling opportunity costs carefully, the authors avoid oversimplification. They don’t say “replace farms with forests.” They say: understand the trade-offs. Let data guide—not dictate—decisions.
Because a well-informed choice is not cold. It is kind.
Closing Reflections
Opportunity cost is often thought of as what we give up. But sometimes, it’s also what we’re finally ready to let go of—so something new can grow.
In this chapter, we see how economics can serve humility. How models can respect memory. And how a field, long sown with labor, might one day bloom again—this time in leaves, shade, and carbon.
But only if we understand what we’re giving up.
And only if what we gain, in return, is worth it.