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When does proactive management outperform reforestation?
Explore how climate and management interact to shape forest carbon recovery.
The following scenarios were generated using Forest Carbon Lite (FCL). They show where active forest management (AFM) can outperform reforestation and where it cannot. Each projection uses validated FullCAM growth functions with site-specific forest parameters, ensuring consistency with Australia’s national carbon accounting framework.
Key insight
Key insight
Management intensity is the most critical decision variable.
With light management, reforestation outperforms AFM in 95 per cent of scenarios.
With moderate to intensive management, AFM wins 95 per cent of scenarios.
Climate context
Climate context
Our 'current' scenarios represent historical baselines (no warming). 'Paris +1.5 °C' reflects the world today, while '+2 °C' and “+3 °C” represent likely and severe future conditions. These comparisons show not only what is possible, but what we’ve already lost.
Example scenarios
Example scenarios
Click on image to view related plots.
When does AFM outperform reforestation?
When does AFM outperform reforestation?
Active forest management (AFM) can match or exceed reforestation carbon outcomes when site conditions align. High-potential degraded forests respond strongly to management, while low-potential sites benefit more from reforestation. The answer depends on management capacity. With light management (minimal intervention), reforestation adds more carbon than AFM in 95% of scenarios. With moderate to intensive management, AFM adds more carbon in 95% of scenarios. The decision threshold sits at moderate management intensity.
Reforestation advantage
Reforestation advantage
Light management offers only modest gains. Across all forest types and climates, reforestation from bare ground accumulates more carbon over 25 years than light AFM can add to degraded forests. This remains true even in high-biomass eucalypt systems.
Figure 1. Degraded eucalypt open forest, Paris +1.5 °C, light management. The figure shows reforestation accumulates roughly twice the carbon added through light management.
Reforestation dominates when intervention is minimal
AFM advantage
AFM advantage
In high-biomass degraded forests, intensive management can add more carbon than reforestation builds from zero. Despite lower starting stocks, the existing forest structure provides both carbon foundation and biological infrastructure, accelerating response.
Figure 2: Degraded eucalypt tall open forest, Paris +1.5 °C, intensive management.
Intensive management nearly doubles carbon gains relative to reforestation, leveraging existing forest structure and root systems.
Intensive AFM restores carbon faster and further in degraded eucalypt forests.
The tipping point: moderate management
The tipping point: moderate management
Moderate management marks the decision threshold. Below this level, reforestation leads. Above it, management dominates. The crossover varies by forest type: earlier in low-biomass systems like acacia woodlands, later in tall eucalypt forests.
Figure 3: Acacia Woodland, Paris +1.5 °C, Moderate Management
At moderate intervention levels, AFM and reforestation converge, illustrating the decision threshold where outcomes balance.
The optimal strategy depends on forest type and management intensity.
How does climate change affect all strategies?
How does climate change affect all strategies?
Warming reduces productivity across all forests through heat stress, water limitation, and disturbance. Yet managed forests show stronger resilience. Under our model, degraded eucalypt open forest with intensive management loses 28 per cent of its carbon gain potential from historical baseline to +3 °C – compared with a 35 per cent decline for reforestation.
Figure 4: EOFD intensive management across climate scenarios.
Both reforestation and management decline under warming, but managed forests maintain a relative advantage in carbon gain.
Both strategies weaken under warming, but management retains a relative advantage.
Cost of inaction
Cost of inaction
Degraded forests left unmanaged continue to lose carbon as regeneration fails and mortality rises. Under likely +2 °C warming, a degraded tall eucalypt forest loses 12 per cent of its carbon over 25 years. Under +3 °C warming, losses rise to 19 per cent.
Figure 5: Degraded eucalypt tall open forest, do-nothing scenario.
Without management, degraded forests continue to lose carbon, shifting from potential sinks to net emission sources.
Doing nothing turns degraded forests into net emitters.
Forest type determines carbon potential
Forest type determines carbon potential
Maximum biomass potential varies six-fold across Australian forests , from 49 t/ha in acacia woodlands to 290 t/ha in tall eucalypts. Our model shows, management advantage scales directly with biomass potential: high-biomass forests deliver far greater carbon returns per hectare and per management dollar invested.
Figure 6: Comparing 3 forest types, Paris +1.5 °C, intensive management.
High-biomass forests show the greatest carbon returns per hectare and per management dollar, making them priority restoration targets.
High-biomass degraded forests are the most efficient targets for climate-positive investment.
Summary
Summary
These scenarios show that restoring carbon in existing forests can be as powerful as planting new ones, when guided by active, evidence-based management. High-biomass degraded forests deliver the greatest carbon returns, highlighting the importance of managing what we already have. At the Foundation, we see this as a path to climate resilience grounded in science, stewardship and care for Country.
Explore the data yourself
Explore the data yourself
This analysis represents an early exploration of Forest Carbon Lite’s scenario capability using representative datasets.
A broader rollout will expand forest types, climates, and management intensities to refine national-scale insights.
Technical notes and assumptions
Forest Carbon Lite (FCL v0.1) uses validated Australian growth functions from FullCAM to project carbon outcomes across forest types, management intensities and climate futures. The model separates management and climate effects to avoid double-counting and applies conservative assumptions for each: growth improvements of 10 %, 20 % and 35 % for light, moderate and intensive management, and productivity reductions aligned with temperature increases of +1.5 °C to +3 °C.
FCL is designed for comparative analysis, not as a regulatory or crediting tool. Results show relative carbon performance between strategies over a 25-year timeframe and should be interpreted as indicative rather than predictive. Natural variability, catastrophic disturbance and soil processes are simplified to keep the model transparent and fast.
The full methodology, datasets and codebase are documented in Forest Carbon Lite Simulator: A Transparent Model for Restoration and Management Decision Support under Climate Change (v0.1 – Professional Review Draft), and available on GitHub – forestsystemtransformation/forest-carbon-lite.
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