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

Tree cover restoration is widely promoted for atmospheric CO2 removal, but its net climate impact depends on both carbon sequestration and biophysical effects such as albedo change. Because tree cover often lowers albedo relative to open land covers, the resulting increase in absorbed solar radiation can cause warming that partially or wholly offsets carbon storage benefits. Prior global analyses often omitted or coarsely represented albedo, limiting reliable identification of climate-positive restoration opportunities. This study aims to quantify, map, and integrate albedo-driven radiative forcing with potential carbon storage, producing spatially explicit estimates of net climate impact (in CO2e) from restoring tree cover. The goals are to identify where restoration is likely climate-positive, assess biome-level patterns, refine published restoration opportunity maps by accounting for albedo, and evaluate albedo offsets for actual on-the-ground projects.

Most prior assessments either omitted albedo or used coarse proxies (e.g., latitudinal or biome exclusions) or uniform deductions where large albedo changes were expected. Some recent spatially explicit studies showed large albedo offsets for Canadian restoration and in global drylands. Albedo offsets are expected to be strongest where solar input is high, where snow or other bright surfaces occur, and where forest carbon accumulation is slow. However, local variability in albedo responses to land cover change can be large, motivating refined, spatially explicit mapping. Earlier work emphasized boreal albedo concerns, but emerging analyses indicate substantial constraints in drylands as well.

- Albedo change mapping for 24 transitions: Built global 0.05° maps of TOA radiative forcing from albedo change for each transition from four open classes (open shrubland, grassland, cropland, cropland/natural vegetation mosaic) to six woody classes (woody savanna, evergreen needleleaf, evergreen broadleaf, deciduous needleleaf, deciduous broadleaf, mixed forest). Monthly blue-sky albedo differences were calculated using the Gao et al. albedo atlas, combined with average monthly snow cover (MODIS) and beam/diffuse radiation (NCEP/NCAR). Six radiative kernels (CAM, CAM5/CESM, ECHAM, HadGEM2, HadGEM3, CACKv1.0) converted albedo changes to TOA RF. Kernel-median values were used per pixel, with min/max provided for uncertainty. - Conversion to CO2e: Annualized TOA RF was scaled to the globe and converted to CO2e using the IPCC logarithmic RF–CO2 relationship, then normalized by the mean fraction of a CO2 pulse remaining after 100 years using an impulse response function to represent atmospheric decay. - Most likely transition map: A neighborhood analysis (nested grids and regional/biome summaries) assigned each pixel a most likely open starting class and forest end class, producing a composite potential albedo change (CO2e) map independent of current land cover where predictions were feasible. - Net climate impact: Combined the potential albedo CO2e map with a published maximum potential biomass carbon storage map (above- and belowground only) to estimate maximum net climate impact (maximum CO2e) of restoration over longer horizons. Also produced an alternative net climate impact layer truncating high biomass values to the 85th percentile of ESA-CCI AGB within ecoregions for sensitivity. - Opportunity map refinement: Overlaid net climate impact and albedo offset on three global opportunity maps (Griscom; Bastin subset to <25% current tree cover but suitable to >25%; Walker R/H and R/L categories) to quantify area with substantial albedo offset (>50%) and resulting changes in total maximum CO2e. - On-the-ground projects: Compiled project locations from China’s Grain for Green and the Restor platform. Assessed overlap with net climate-positive/negative pixels and albedo offset bins for 815,654 project pixels. - Temporal dynamics: Modeled hypothetical scenarios of differing rates/timing for albedo vs carbon change (fast/slow carbon accumulation; albedo reaching maximum earlier by 50% or 80%; albedo offsets of 10%, 50%, 100%) using a Chapman–Richards growth curve and impulse response for atmospheric CO2 to explore time-dependent net outcomes. - Uncertainty: Quantified spread across radiative kernels (min–max) and tested sensitivity to the carbon dataset (ESA-truncated Walker).

- Albedo-induced CO2e from likely transitions ranges from 28 to −469 Mg CO2e ha−1 (90% CI), with a median of −120 Mg CO2e ha−1, indicating albedo-driven warming is common, especially in arid and higher latitude regions, though modest cooling can occur in parts of the tropics. - Maximum net climate impact (maximum CO2e) combining albedo and carbon ranges from 803 to −454 Mg CO2e ha−1 (90% CI), with a median of 100 Mg CO2e ha−1 versus 220 Mg CO2e ha−1 when considering carbon alone—i.e., median benefits are reduced to 44% by albedo. - Median albedo offset is 52% globally, meaning albedo typically halves maximum carbon storage benefits. - Biome patterns: Drylands contain the highest shares of net climate-negative areas. Temperate grasslands/savannas/shrublands: 72% climate-negative; 83% substantial (>50%) offset. Mediterranean forests/woodlands/scrub: 60% climate-negative; 76% substantial offset. Tropical/subtropical grasslands/savannas/shrublands: 38% climate-negative; 46% substantial offset. Boreal forests: 34% climate-negative but 72% substantial offset. Tropical/subtropical moist broadleaf forests: 3% climate-negative; 6% substantial offset. All biomes include some climate-positive locations. - Refining opportunity maps: • Griscom (828 Mha): 94% net positive; 18% substantial offset; total maximum CO2e reduced 20% (318 → 254 Pg CO2e). • Bastin subset (916 Mha): 71% net positive; 48% substantial offset; total maximum CO2e reduced 53% (214 → 101 Pg CO2e). Targeting only areas without substantial offset (52% area, 476 Mha) yields higher maximum CO2e (127 Pg) than restoring the full area. • Walker (889 Mha): 54% net positive; 65% substantial offset; total maximum CO2e reduced 81% (186 → 35 Pg CO2e). Focusing on areas without substantial offset (311 Mha, 35%) yields 90 Pg CO2e (2.5× more than restoring the full area). - On-the-ground projects (815,654 pixels): 84% are in net climate-positive locations; 29% have substantial (>50%) albedo offset; 66% have at least 20% offset. Only 45% overlap at least one opportunity map, indicating a mismatch between potential maps and actual project siting. - Uncertainty: Across radiative kernels, uncertainties in net climate impact are generally ±15% of the median except at high latitudes; 9% of land transitions across the 50% offset threshold, while 71% are consistent (≥ or < 50%) across kernels. Using an ESA-truncated biomass layer reduces global median net benefit by 14% (100 → 86 Mg CO2e ha−1) without materially changing the spatial pattern of net-negative areas or substantial offsets.

Integrating albedo change with carbon storage shows that albedo commonly erodes the climate benefits of tree cover restoration, often by about half, and can reverse them in large portions of drylands and parts of the boreal zone. This refines earlier emphasis on boreal albedo effects by highlighting even greater net-negative prevalence across dryland biomes. Nevertheless, climate-positive opportunities exist within every biome, reinforcing the need for spatially explicit siting. The refined analyses of opportunity maps demonstrate that accounting for albedo can dramatically reduce estimated benefits and suitable area, but also that higher total climate benefits can be achieved by restoring less area if net-negative zones are avoided. Actual project locations are largely in climate-positive areas, suggesting some implicit or explicit consideration of conditions favorable to positive net outcomes, though many still incur substantial albedo offsets. These results directly address the study goal by identifying where restoration is likely net climate-positive and by providing practical maps and tools to guide siting and portfolio design for maximum climate benefit.

Tree cover restoration can deliver meaningful climate mitigation when implemented in climate-positive locations, but albedo change commonly offsets a large fraction of carbon benefits and can render many areas climate-negative—especially in drylands and parts of the boreal. This study provides global, spatially explicit maps of albedo-induced forcing, net climate impact, and albedo offset, enabling robust screening and prioritization. Applying these tools to published opportunity maps and to real-world projects shows that benefits are often overestimated if albedo is ignored (up to 81% reduction) and that targeting areas without substantial albedo offset can increase overall mitigation while restoring less land. Future work should develop temporally explicit albedo–carbon trajectories, finer-resolution analyses that capture topography and local variability, and broader accounting of additional biophysical processes and durability to better estimate full net climate impacts.

- Biogeophysical scope: The analysis focuses on surface albedo and carbon storage; it does not quantify other climate-relevant processes (e.g., evapotranspiration, surface roughness, cloud adjustments, volatile organic compounds, methane emissions), and employs instantaneous rather than effective radiative forcing in kernels. - Data uncertainties: Potential misclassification in MODIS land cover, snow cover, and radiation datasets; sensitivity to carbon storage datasets (maximum biomass may be overestimated in some regions); assumptions in assigning most likely transitions via neighborhood analysis. - Temporal simplifications: Net climate impact is framed as a maximum (longer-term) value; time-varying dynamics of albedo and carbon changes are uncertain and region-specific, though scenario tests suggest many locations retain their sign of net impact. - Spatial resolution: Nominal ~500 m mapping may not capture fine-scale variability due to topography, aspect, and microclimate. - Future change: Shifts in snow cover, aridity, growth rates, timber markets, and management regimes could alter both albedo and carbon outcomes; disturbance risks (e.g., wildfire, insects) and permanence are not explicitly modeled. - Practical constraints: Competing land uses and social priorities limit realizable mitigation relative to maximum estimates.