Accounting for albedo change to identify climate-positive tree cover restoration

Reforestation is a key strategy for climate change mitigation through carbon sequestration. However, the impact extends beyond carbon; changes in albedo, the fraction of sunlight reflected from the Earth's surface, also play a crucial role. Since trees absorb more solar radiation than many other land covers, reforestation can lead to localized and global warming, potentially negating the cooling benefits of increased carbon storage. Previous assessments have either ignored albedo changes or used coarse approximations, leading to inaccurate estimations of the net climate impact. This study aims to provide a more accurate assessment of the climate mitigation potential of tree cover restoration by explicitly accounting for albedo changes using spatially explicit data. The importance of this accurate assessment lies in directing resources and efforts towards locations where reforestation truly maximizes climate benefits. Failure to account for albedo may lead to ineffective or even counterproductive reforestation efforts, wasting resources and potentially exacerbating climate change.

While the importance of considering albedo changes in climate change mitigation has been acknowledged in previous research, most assessments of tree cover restoration's potential still overlook or inadequately model this crucial factor. Previous efforts have employed simplistic methods, such as relying on latitudes or biome boundaries to exclude potentially problematic areas, or applying uniform deductions to carbon accumulation estimates. Some recent studies utilizing more sophisticated spatial methods have demonstrated the substantial offsetting effect of albedo change on the climate benefits of reforestation in specific regions, such as Canada and global drylands. These studies generally indicate that albedo offsets are highest in sun-drenched locations with persistent snow cover or other highly reflective surfaces, as well as in areas with slow tree carbon accumulation rates. However, the variation in albedo changes and their climate effects can be substantial at local scales, highlighting the need for spatially refined maps to accurately characterize the climate implications of tree cover restoration across diverse landscapes.

The study produced global maps estimating albedo-driven climate forcing from tree cover restoration at a 0.05-degree latitude/longitude resolution. This involved creating 24 maps quantifying changes in top-of-atmosphere radiative forcing (TOA RF) resulting from transitions from four open land cover classes (open shrubland, grasslands, cropland, cropland/natural vegetation mosaics) to six forest classes (woody savanna, evergreen needleleaf, evergreen broadleaf, deciduous needleleaf, deciduous broadleaf, mixed forests). Monthly changes in blue sky albedo were calculated using an albedo atlas, combined with monthly snow cover and radiation data. These were then combined with six radiative kernels from different climate models to estimate TOA RF. The 24 transition maps were combined into a single "potential albedo change map" by predicting the most likely open land and forest class for each pixel using neighborhood analyses of current land cover maps, stratified by ecoregion. This map estimates albedo change-induced CO2e resulting from the most likely transition at each pixel. The potential albedo change map was then combined with a published map of maximum potential carbon storage to predict the net climate benefit of tree cover restoration. This combined map is referred to as the 'potential net climate impact map' and predicts maximum CO2e over longer time periods. Three previously published maps identifying areas for tree cover restoration were then refined using the potential albedo offset map. Finally, albedo offset in actual on-the-ground projects was assessed using data from the Grain for Green program and Restor. The conversion of radiative forcing to CO2e involved using the global annual mean radiative forcing caused by carbon emissions, assuming the albedo-induced changes in radiative forcing are equivalent to the radiative forcing of a pulse of CO2. The CO2e from albedo change was normalized to account for CO2 decay in the atmosphere using an impulse response function.

The study found that albedo-induced CO2e ranged from 28 to 469 Mg CO2e ha⁻¹, with a median of -120 Mg CO2e ha⁻¹, indicating that restoring tree cover generally causes warming, particularly in arid and northern regions. The maximum CO2e ranged from 803 to -454 Mg CO2e ha⁻¹, with a median of 100 Mg CO2e ha⁻¹, less than half the median value considering only carbon (220 Mg CO2e ha⁻¹). A median albedo offset of 52% suggests that accounting for albedo change commonly halves maximum carbon storage. Drylands had a greater proportion of net climate-negative areas compared to boreal regions, contrary to previous assumptions. While 72% of temperate grasslands, savannas, and shrublands would be climate-negative, all biomes contained some climate-positive locations. Applying the albedo offset map to refine three previously published restoration opportunity maps revealed significant reductions in net climate benefit after accounting for albedo change. The Griscom map showed an 18% substantial albedo offset, Bastin map showed a 48% substantial offset, and Walker map showed a 65% substantial offset. In on-the-ground projects, 84% of pixels were in net climate-positive locations, but 29% experienced a substantial albedo offset, and 66% had at least a 20% offset. Uncertainty analysis using multiple radiative kernels showed small uncertainties overall, with most pixels consistent in having either greater or less than 50% albedo offset. Sensitivity analysis using a modified carbon layer decreased the net climate impact globally by 14%, but the extent of net climate-negative areas or areas with substantial albedo offsets did not change substantially.

This research challenges the prevailing focus on boreal regions as the primary concern regarding albedo offsets in reforestation efforts. The findings highlight dryland settings as having a proportionally greater area with net climate-negative impacts, underscoring the potential negative consequences of afforestation in native grasslands. The substantial reductions in the climate benefits of tree cover restoration revealed after accounting for albedo change in existing opportunity maps highlight the need for more refined approaches to identifying suitable locations for reforestation. The inconsistencies between opportunity maps and the actual locations of on-the-ground projects indicate a need for improved alignment between potential and implementation. The significant albedo offsets observed in a substantial portion of ongoing projects emphasizes the necessity of explicitly considering albedo change in project planning to achieve genuine climate change mitigation goals. The study's findings demonstrate that by avoiding net climate-negative areas, higher climate mitigation can be achieved by restoring less area. Although the study focuses on climate change mitigation, it acknowledges the numerous additional benefits of restoring tree cover, such as habitat creation, improved livelihoods, and enhanced hydrological benefits.

This study demonstrates the crucial role of accounting for albedo change in evaluating the climate benefits of tree cover restoration. Dryland regions emerge as areas of particular concern, while the potential for climate-positive outcomes exists across all biomes. The significant reductions in net climate benefits observed when incorporating albedo effects into existing opportunity maps underscore the need for spatially explicit and albedo-aware reforestation strategies. Future research should focus on temporally explicit modeling of albedo and carbon change, higher-resolution analysis in regions with strong albedo changes, and the integration of factors such as methane emissions, surface temperature changes, and cloud formation to achieve a more complete understanding of the net climate impact of tree cover restoration.

The study acknowledges several limitations. Uncertainty exists in land cover classification, snow cover data, and the carbon storage map used. The analysis compares maximum potential carbon storage with maximum albedo change, ignoring the differing timeframes over which these changes occur. Spatially refined estimates are also needed, as the current 500-m resolution may not fully capture local variability due to factors like topography and aspect. Future climate conditions and timber demands may also alter the climate response to tree cover restoration in ways not captured in this study. Finally, the study does not encompass all factors influencing the net climate impact of tree cover restoration, such as methane emissions and changes in cloud formation.