Updated 12 October 2026 · By Pete Bromfield, former Head of Maths with IB examining experience

Is deforestation in [a country] slowing down?

AI SLAI HLAA SL Accessible Also in: Statistics, Modelling

Research question

Is there a significant trend in annual tree-cover loss in [a country] since 2001, and did loss change after a specific policy or event?

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Why it makes a good exploration

Satellite data now measures forest loss every year. Testing a trend, and whether a policy made a difference, is a real environmental-statistics question you can answer with open data.

The mathematics you'll need

Time-series plots and linear regression
Significance of a trend (correlation test)
Comparing means before and after an event (t-test)
Percentage change

Modelling the data, step by step

This idea usually needs a straight-line model. See it worked step by step, with a criterion tip at every step: Straight line y = mx + c.

Model your own data Paste it from Desmos, GeoGebra or a spreadsheet and get the same play-by-play with your numbers. New to modelling? Start with the modelling workflow. Writing it up? The IA modelling planner comments on each paragraph as you draft — it never writes it for you.

The statistics, step by step

Worked with every number shown, with what examiners look for and the common mistakes: t-test: two-sample and paired · Pearson's correlation and regression. Then run the same steps on your own data in Analyse my data, or start from the statistics workflow.

Where the data comes from

Annual tree-cover loss by country from Global Forest Watch.

Global Forest Watch open data — Annual tree-cover loss by country since 2001, from Landsat imagery.

Real data for this idea

Primary source: Global Forest Watch: Open data portal. Search for “tree cover loss” and use the country statistics: hectares lost per year from 2001. Licence: CC BY 4.0 for the tree-cover loss data.
Readable chart: Our World in Data: Tree cover loss. Use it to see the pattern; download your numbers from the primary source or the chart's own download. Cite as: Our World in Data, ‘Tree cover loss’, CC BY 4.0. Original source: Global Forest Watch (2025).

Links checked October 2026; we link to the data and never copy it. More free data sets.

A possible outline

Explain what “tree-cover loss” does and does not measure.
Plot and describe the series.
Test for a trend.
Compare before and after a policy.
Reflect on regrowth, plantations and satellite limitations.

Pitfalls that cost marks

Equating tree-cover loss with deforestation without comment.
Choosing a policy date after seeing the data.
Ignoring outlier years (fires).

Showing personal engagement

Choose a country connected to you or your diet (soy, palm oil, beef).
Compare two countries.
Discuss what would count as success.

See Criterion C: personal engagement for what examiners look for.

Which course is it for?

Course	Fit	Maths to lean on
AA SL	Good fit	Time-series plots and linear regression; Significance of a trend (correlation test)
AA HL	Not a natural fit	The mathematics is mainly from the AI course; at AA HL the exploration would need an AA-level approach (calculus, proof or probability theory) to reach the top of Criterion E.
AI SL	Good fit	Time-series plots and linear regression; Significance of a trend (correlation test)
AI HL	Fits, but add an HL technique	Time-series plots and linear regression; Significance of a trend (correlation test)

Level: Accessible. A good first extended piece of maths, with room to go deeper. See how the IA differs between AA and AI, SL and HL.

How this idea reaches the top bands

Reflection (D)

For this idea, start with the weak points: equating tree-cover loss with deforestation without comment; and choosing a policy date after seeing the data. Say how each one affects your answer.

Use of mathematics (E)

SL: time-series plots and linear regression; significance of a trend (correlation test); comparing means before and after an event (t-test); percentage change, each explained in your own words and carried out correctly.

How environment explorations reach the top bands in general: Environment & climate IA ideas. Guides: A · B · C · D · E · self-grade sheet.

Taking it further

Model cumulative loss and estimate remaining forest under different scenarios.

Extending it for HL

Add an HL technique the question genuinely needs: what an HL environment exploration adds.

See a complete IA, marked

When can we launch? Modelling the tide at our sailing club's slipway (AA SL) is a complete environment exploration, marked on every criterion.

Frequently asked questions

Which IB Maths course is this IA idea for?

It works for AI SL, AI HL and AA SL. We rate it Accessible: a good first extended piece of maths, with room to go deeper.

What mathematics does this IA use?

Time-series plots and linear regression, significance of a trend (correlation test), comparing means before and after an event (t-test) and percentage change.

Where can I get data for this IA?

Annual tree-cover loss by country from Global Forest Watch. Checked sources and tools: Global Forest Watch, Our World in Data and Global Forest Watch open data.

Turn this idea into your IA

The planner opens with “Is deforestation in [a country] slowing down?” filled in: the question, the maths and the data sources.

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