Monitoring reports present growth models as charts. A chart shows that a curve exists and passes near some points. It does not let anyone reproduce the curve, check whether it was fitted appropriately, or see how far the projection runs beyond the data, which is what an assessor needs.
What a Chart Omits
| Present in a typical chart | Usually missing |
|---|---|
| The fitted curve | The function and its parameters |
| Measured points | Which points are measured vs interpolated |
| A trend | The prediction interval |
| An endpoint | Where data ends and extrapolation begins |
The last row is the one that matters most and is almost never shown. A curve drawn continuously from year 0 to year 30, with measurements at years 3, 6 and 10, presents twenty years of extrapolation with the same visual authority as the measured portion.
The Four Things to Add
Mark the data boundary. A vertical line, a change in line style, anything that distinguishes the fitted region from the projected one. This single change does more for transparency than any other.
State the function and parameters. Name the functional form and give the fitted coefficients. Without them the curve cannot be reproduced, and a model nobody can reproduce is an assertion.
Show the prediction interval. Not just the central curve. An interval that widens beyond the last measurement communicates the actual state of knowledge, and it communicates it to readers who will not read the uncertainty section.
Plot residuals. A small residual plot reveals structural misfit that the main chart hides. If residuals trend, the functional form is wrong, and an assessor who sees a clean residual plot stops asking.
Distinguish the Sources of Points
Measured, interpolated and projected values should be visually distinct. Different markers, different shading, whatever the format allows.
This is not decoration. It is the difference between a reader being able to see what the project observed and having to ask. Assessors who have to ask will ask about several other things at the same time.
The Reproducibility Test
Hand the growth-model section to a colleague who did not build it, with the underlying data. Ask them to reproduce the curve.
If they can, the documentation is adequate. If they need to ask which function, which points, or what the parameters were, those questions are exactly the findings the verification will generate, except obtained at no cost and with no permanent record.
Why This Is Worth the Effort
Growth models carry a large share of reported carbon in young projects, because most years are modelled rather than measured. That makes them disproportionately important and disproportionately under-documented relative to their weight in the result.
A project that documents its growth model properly is making a checkable claim about the majority of its reported tonnage. One that presents a chart is asking for that majority to be taken on trust and it is the part of the report where trust is least readily extended.
Turn uncertainty into a plan
Sampling design and growth assumptions decide how much measured carbon survives conservative deduction. TREEO Carbon Simulator models sequestration scenarios and biomass growth before the field season.
