Pith. sign in

REVIEW 4 major objections 5 minor 46 references

Climate benefits of afforestation and reforestation with varying species mixtures and densities in the north-western boreal lands

T0 review · 4 major / 5 minor · reviewed 2026-08-07 · deepseek-v4-flash

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗

Pith's one-line read Boreal mixed-species, medium-density plantings store 15–30% more carbon than conifer monocultures and keep net cooling when albedo is included.

desk verdict Useful scenario analysis for a policy-relevant region; the carbon modeling is credible, but the albedo-adjusted headline numbers and the abstract's percentages are not supported by the tables as presented. read the letter →

arxiv 2506.03300 v2 pith:A5ZDYQCW submitted 2025-06-03 q-bio.PE q-bio.QM

Enoch Ofosu , Kevin Bradley Dsouza , Daniel Chukwuemeka Amaogu , Jerome Pigeon , Richard Boudreault , Juan Moreno-Cruz , Pooneh Maghoul , Yuri Leonenko This is my paper
classification q-bio.PEq-bio.QM
keywords BorealforestAfforestationReforestationSpeciesmixturePlantingdensitySurfacealbedoCarbonsequestrationTaigaPlains
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

This paper asks which afforestation and reforestation choices in Canada's Taiga Plains actually cool the climate over 250 years. Using linked forest growth and carbon budget models, it compares species mixtures, planting densities, and harvesting–replanting strategies. It finds that medium-density stands (600 to 1400 trees per hectare) with roughly 25 to 40 percent deciduous trees store 15 to 30 percent more net ecosystem carbon than conifer monocultures. When surface albedo change is added, these mixed stands keep a net cooling effect of about 4.6 to 4.7 tonnes of CO2-equivalent per hectare per year, while pure evergreen or pure deciduous stands lose 6 to 20 percent of their climate benefit. The point is a concrete planting prescription for boreal tree-planting programs: favor balanced deciduous–conifer mixtures at intermediate density.

What carries the argument

The load-bearing mechanism is ecological complementarity between fast-growing deciduous species (aspen) and long-lived conifers (black spruce, white spruce, and pine), simulated over 250 years. The modeling chain is a growth-and-yield projection system (GYPSY) that generates species- and density-specific merchantable volume and biomass trajectories, feeding a carbon budget model (CBM-CFS3) that tracks five ecosystem carbon pools under fire, insect, and harvest disturbances. Monthly surface albedo changes are then converted through radiative kernels into CO2-equivalent offsets, so biogeochemical carbon gains and biophysical albedo losses are compared in the same units.

What would settle it

A paired-plot field trial or an updated simulation with warming climate, permafrost thaw, and intensified fire regimes that shows a conifer monoculture or a high-density planting matching or exceeding mixed medium-density stands in net ecosystem carbon and albedo-adjusted forcing by the late twentieth or twenty-first century of the run would falsify the claimed ranking.

Watch

Extended reading notes

Core claim

The paper's central claim is that the climate value of boreal afforestation and reforestation depends more on species composition and planting density than on planting trees alone. Over 250-year simulations, a balanced mix of 25 percent each of black spruce, white spruce, pine, and aspen at medium density reaches roughly 270 t C ha$^{-1}$, compared with about 180 to 190 t C ha$^{-1}$ for spruce or aspen monocultures. The mechanism is complementarity: aspen provides rapid early growth, while conifers provide long-term retention and disturbance resilience. On understocked sites, replanting with such mixtures raises long-term storage by 18 to 30 percent over business-as-usual. Incorporating albedo, mixed stands retain net cooling at about 4.6 to 4.7 t CO$_2$e ha$^{-1}$ yr$^{-1}$, whereas pure stands suffer 6 to 20 percent reductions in climate benefit. Partial harvest followed by replanting sustains ecosystem carbon stocks of roughly 300 to 340 t C ha$^{-1}$ and productivity of 1.6 to 2.0 t C ha$^{-1}$ yr$^{-1}$ without increasing modeled ecological risk.

Load-bearing premise

The 250-year ranking assumes the future climate and disturbance regime stay close to the historical ones used in the simulations, so permafrost thaw, changing fire return intervals, and climate-driven shifts in growth and decomposition are not allowed to alter the trajectories.

Editorial extensions

If this is right

  • For Canada's 2 Billion Trees Program, planting prescriptions should favor balanced deciduous–conifer mixtures at 600 to 1400 trees per hectare over conifer monocultures.
  • Understocked boreal stands of at most 600 trees per hectare are a high-leverage target: replanting them with mixed species raises long-term carbon storage by 18 to 30 percent.
  • Including albedo in carbon accounting changes the ranking: pure evergreen or pure deciduous stands lose 6 to 20 percent of their climate benefit, while mixed stands remain net-cooling.
  • Partial harvesting followed by replanting can sustain or improve ecosystem carbon stocks and productivity without raising modeled ecological risk, making it a viable alternative to clearcut-and-plant.
  • The same mixed-species, intermediate-density logic is proposed for other high-latitude boreal regions, where dense conifer plantations can create net warming through albedo reduction.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • The paper's 4.6 to 4.7 t CO$_2$e ha$^{-1}$ yr$^{-1}$ rate implies a per-hectare ceiling for boreal planting programs; translating it into national climate contributions would require land-availability, cost, and management constraints the paper does not model.
  • If future climate change shortens snow-cover duration or accelerates fire return intervals, the albedo penalty for evergreen monocultures could grow, making the deciduous-rich mixture advantage larger than simulated rather than smaller.
  • The fixed-climate assumption means the strongest untested part of the prescription is late-century behavior: disturbance legacies and decomposition under a warming climate, not early growth, will decide whether the ranking holds.
  • The framework could be extended to compare mixed planting against natural regeneration on abandoned agricultural land, where the starting albedo and soil carbon conditions differ from the Taiga Plains.
Share X Bluesky LinkedIn Reddit HN

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

4 major / 5 minor

Summary. The paper uses the GYPSY growth model and the CBM-CFS3 carbon budget model to simulate 250-year carbon trajectories for afforestation and reforestation scenarios in Canada's Taiga Plains ecoregion, varying species composition (conifer, deciduous, and mixed stands) and planting density (low, medium, high). It then adds surface-albedo radiative forcing via a linear mixture model and radiative kernels, converting albedo changes to CO2-equivalent offsets, and validates above-ground biomass trajectories against independent satellite-derived chronosequences. The headline findings are that medium-density (600–1400 trees/ha) mixed stands with roughly 25–40% deciduous species store 15–30% more net ecosystem carbon than conifer monocultures, that replanting understocked stands gives 18–30% gains, and that, after albedo is included, mixed stands maintain net cooling of about 4.6–4.7 tCO2e ha⁻¹ yr⁻¹ while pure evergreen or deciduous stands lose 6–20% of their climate benefit.

Significance. If the reported numbers hold, the paper provides a directly actionable comparison for a region targeted by Canada's 2 Billion Trees Program and for boreal afforestation generally. The modeling is standard and transparent, and the validation against independent chronosequences is a clear strength: the reported R² of 0.95–0.99 and RMSE of 5–11% give genuine support to the biomass-carbon projections. The explicit coupling of carbon sequestration with albedo-driven radiative forcing is also valuable, as biophysical feedbacks are often omitted from afforestation assessments. However, the quantitative claims in the abstract and results are not fully reproducible from the tables and figures as presented: the percentage gains for mixed stands and replanting do not match the year-250 NEC values in Figs. 2 and 3, and the albedo-adjusted annual values rest on winter-month offsets that are neither shown in Table S2 nor reconciled with the figure captions. These issues are local and correctable rather than fatal, but they are load-bearing for the paper's central message.

major comments (4)
  1. [Results, 'Influence of Species Mix and Density...' and Abstract] The headline percentage claims are not supported by the reported NEC values. The text reports that at medium density the AllMix scenario reaches approximately 270 tC ha⁻¹ at year 250, while 95%SB reaches approximately 180 tC ha⁻¹, 95%SW approximately 140 tC ha⁻¹, and 95%AW approximately 190 tC ha⁻¹. These correspond to increases of about 50% and 93% relative to the two conifer monocultures, not the 15–30% stated in the abstract. Similarly, the abstract's 'Replanting under-stocked stands with such mixtures increased long-term carbon storage by 18 to 30 percent' is inconsistent with Fig. 3(i-a), where the Mixedwood BAU reaches about 50 tC ha⁻¹ and the MX treatment about 250 tC ha⁻¹, a fivefold increase. The authors must either recompute these percentages or state explicitly which reference scenario and time horizon each percentage uses; as written, the abstract and the results text are numerically incompatible with the figures.
  2. [Table S2, Fig. 5 caption, Methods 'Albedo effects estimation'] The albedo-adjusted annual values are not reproducible from the reported data. Table S2 lists monthly albedo offsets only for March–November; December, January, and February are dashes for every scenario and density. The caption of Fig. 5 states that the plotted Net CO2e Sequestration values reflect a '100-year average (March–November)' with December–January–February data 'supplemented from Hasler et al. (2023)', while the Methods say winter gaps were filled 'using their boreal-specific estimates'. These statements are inconsistent: if the December–February values were used, they must be shown, with the assignment rule and uncertainty; if they were not used, then the claimed 4.6–4.7 tCO2e ha⁻¹ yr⁻¹ is a March–November value, not an annual one, and the abstract's 'net cooling' claim is overstated. In a snow-dominated boreal region, winter and early-spring albedo is among the largest biophysical terms, so both the absolute values and the ranking of mixtures versus monocultures could change materially once this gap is closed.
  3. [Results, 'Net climate benefit considering albedo effects' and Table S2] Several monthly albedo offsets are misattributed in the text. The sentence that '40% AW under low density exhibited pronounced cooling offsets in summer months (e.g., July: -0.466 Mg CO2e ha⁻¹ yr⁻¹)' contradicts Table S2, where the low-density 40%AW July value is +0.026 and the -0.466 value belongs to 95%AW. Likewise, the May value of -0.321 is attributed to 40%AW in the text but appears for 95%AW in Table S2. These misreadings mean the narrative about which mixtures produce strong summer cooling is the opposite of what the table shows for the deciduous-rich mixture, and they need to be corrected before the albedo discussion can be trusted.
  4. [Limitations and Future Direction] The 250-year projections assume fixed climatic conditions and historical disturbance regimes; the authors explicitly list future climate change, permafrost thaw, and changing disturbance regimes as unmodeled. Because the recommended strategy is intended to inform multi-decadal afforestation and reforestation policy, the ranking of species mixtures and densities under those changing conditions is an open question. This limitation is acknowledged, but the Abstract and Discussion should qualify the 'maximizes boreal A/R climate value' conclusion explicitly (e.g., 'under the fixed-climate and historical-disturbance scenarios considered'), so that the policy guidance is not stronger than the model evidence.
minor comments (5)
  1. [Validation section] The text in the Validation subsection refers to 'Fig. 11' when describing the chronosequence comparison; the actual figure is numbered Fig. 6.
  2. [Fig. 2(iii) caption] The caption describes the significance matrix as 'pairwise t-test, p < 0.05, with Tukey HSD post-hoc correction'; a Tukey HSD test is not a t-test, and combining the two descriptions is confusing. Please state which post-hoc procedure was actually applied.
  3. [Abstract and Results, 'Net climate benefit considering albedo effects'] The abstract gives 'approximately 4.6 to 4.7 tCO2e ha⁻¹ yr⁻¹' for mixed stands, while the Results report about 4.6 for AllMix and 4.8 for 40% AW under low density; the abstract range omits the 4.8 value and should be reconciled.
  4. [Methods, Eq. (6)] The radiative forcing equation should define ΔAlbedo(s,t) explicitly (e.g., as A_forest(s,t) − A_free(t) or the scenario-minus-baseline albedo difference) so that the sign convention for cooling versus warming is unambiguous.
  5. [Fig. 5 caption] The phrase '100-year average (March–November)' is ambiguous: it could mean an average over the first 100 simulation years, over the full 250-year simulation, or over the nine reported months. The caption and Methods should use the same definition consistently.

Circularity Check

0 steps flagged · score 1.0 of 10

No significant circularity: the carbon projections come from independent process models validated against external chronosequences, and the albedo winter-data gap is a reproducibility concern rather than a circular derivation.

full rationale

The paper's central claim, that medium-density mixed stands with ~25-40% deciduous trees sequester more ecosystem carbon than conifer monocultures and retain net cooling once albedo is included, is not equivalent to its inputs. The carbon trajectories are generated by the GYPSY growth model and the CBM-CFS3 carbon accounting model, both independently developed and parameterized with published yield and inventory data; the paper validates simulated aboveground biomass against external satellite-derived chronosequences (Fig. 6, R² = 0.95-0.99). The albedo offsets are estimated from observed albedo using a linear mixture model (Eq. 5) and converted to radiative forcing via published radiative kernels (Eq. 6); this is calibration from empirical data, not a definitional embedding of the conclusion. The same-group citation [21] supports a background statement about climate-driven shifts in fire and vegetation, and it is not load-bearing for the main result. The Limitations section explicitly notes fixed climatic conditions and the omission of permafrost thaw and changing disturbance regimes, which is an external-validity limitation, not circularity. The Table S2 / Fig. 5 issue is a genuine data-support gap: monthly albedo offsets are listed as missing ('--') for January, February, and December for every scenario, while the Fig. 5 caption states those months were 'supplemented from Hasler et al. (2023)'. This makes the 4.6-4.7 tCO2e ha-1 yr-1 annual figure hard to verify from the reported tables, but it is a reproducibility or reporting concern, not a case of a prediction reducing by construction to its fitted inputs. Overall, no circular derivation chain is exhibited.

Assumptions & free parameters 4 free parameters · 4 assumptions · 0 invented entities

The central claims depend on calibrated growth model parameters, a fitted albedo decomposition, chosen density thresholds, and a fixed-climate assumption. Most are inherited from prior models or fitted to data rather than independently established by this paper.

free parameters (4)
  • GYPSY volume equation constants a, b, c, d = Not reported, empirically derived by GYPSY
    Equation (1) uses these constants to convert diameter and height into volume; they drive all growth trajectories and therefore the carbon differences between species and densities.
  • Intrinsic scenario albedo A_forest(s, t) = Not reported; estimated by least squares per scenario and month from Equation (5)
    The albedo offsets in Table S2 and the net climate benefit figures depend on the fitted intrinsic albedo values for each species mixture scenario.
  • CO2e 100-year horizon factor f_100 = 0.40
    Methods step 6 multiplies radiative forcing by this factor when converting to CO2e; it directly scales the reported net climate benefit numbers.
  • Density class thresholds 600, 1400, 2500 trees per hectare = Low, medium, high thresholds
    The three density categories are defined by these chosen cutoffs, and the central comparison between low, medium, and high density depends on them.
assumptions (4)
  • domain assumption GYPSY growth curves calibrated for Alberta and nearby sites transfer to the Taiga Plains over 250 years
    Methods state GYPSY was calibrated with site-specific data from Taiga Plains studies, but the long-term extrapolation beyond calibration ages is assumed.
  • domain assumption CBM-CFS3 default pool dynamics and decomposition parameters apply to permafrost-affected Taiga Plains soils
    CBM-CFS3 is applied with site-specific adjustments, but soil organic carbon responses on peatland and permafrost landscapes are not independently calibrated in this paper.
  • domain assumption Climate and disturbance regimes remain fixed over the 250-year simulation
    The Limitations section states the study assumes fixed climatic conditions and does not account for permafrost thaw or changing disturbance regimes; the central long-term projections rely on this assumption.
  • domain assumption Surface albedo of a scenario can be inferred from a linear mixture of forest and non-forest albedo
    Equation (5) assumes a linear mixture model with no interactions between forest cover and background albedo, and the fitted forest albedo is then used to compute radiative forcing.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Climate benefits of afforestation and reforestation with varying species mixtures and densities in the north-western boreal lands." pith.science (2026). https://pith.science/paper/A5ZDYQCW

@misc{pith2026250603300,
  author       = {Pith},
  title        = {Pith review of: Climate benefits of afforestation and reforestation with varying species mixtures and densities in the north-western boreal lands},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/A5ZDYQCW}},
  note         = {Machine review of arXiv:2506.03300}
}
read the original abstract

The boreal forest plays a crucial role as a global carbon sink. This study uses two 250-year simulations of Canada's Taiga Plains, an area targeted by the 2 Billion Trees Program to evaluate afforestation and reforestation strategies that vary by species mix, planting density, and surface albedo. Medium density stands, 600 to 1400 trees per hectare, composed of mixed species with approximately 25 to 40 percent deciduous trees sequestered 15 to 30 percent more net ecosystem carbon than conifer monocultures. These benefits stem from a combination of rapid early growth, long-term carbon retention, and enhanced resilience to disturbance. Replanting understocked stands with such mixtures increased long-term carbon storage by 18 to 30 percent relative to prevailing scenarios. When surface albedo was considered, pure evergreen or deciduous stands showed a reduction in climate benefit by 6 to 20 percent, while mixed stands maintained net cooling and achieved the highest sequestration rates, approximately 4.6 to 4.7 tons of carbon dioxide equivalent per hectare per year. Scenarios involving partial harvesting followed by replanting sustained or improved ecosystem carbon stocks, about 300 to 340 tons of carbon per hectare, and productivity, roughly 1.6 to 2.0 tons of carbon per hectare per year, without increasing ecological risk. Overall, integrating fast-growing deciduous species with long-lived conifers at moderate planting densities enhances the climate mitigation potential of boreal afforestation and reforestation efforts and offers guidance for reforestation policy in similar high latitude ecosystems.

Figures

Figures reproduced from arXiv: 2506.03300 by the authors.

Figure 3
Figure 3. Fig.3 [PITH_FULL_IMAGE:figures/full_fig_p007_3.png] view at source ↗
Figure 4
Figure 4. Fig.4 [PITH_FULL_IMAGE:figures/full_fig_p009_4.png] view at source ↗
Figure 5
Figure 5. Fig.5 [PITH_FULL_IMAGE:figures/full_fig_p011_5.png] view at source ↗

Discussion (0). Sign in to comment.

Reference graph

Works this paper leans on

46 extracted references · 46 canonical work pages

  1. [1]

    Broadleaf deciduous trees and deciduous conifers (e.g., larches) were assigned to Aspen. 2. Pines were grouped under Pine. 3. Spruce species were split into Black spruce or White spruce categories based on regional distributions

    work page

  2. [2]

    & Crowther, T

    Bastin, J.-F., Finegold, Y., Garcia, C., Mollicone, D., Rezende, M., Routh, D., ... & Crowther, T. W. (2019). The global tree restoration potential. Science, 365 (6448), 76–79

    work page 2019

  3. [3]

    Scale RF regionally over 25,200 ha. 2. Convert RF to global atmospheric carbon change using: Δ C_CO2e = (2.13 Pg C/ppm * 400 ppm) * [exp(RF_global / 5.35) − 1]

    work page

  4. [4]

    This approach ensured consistency in assigning forest types to each grid cell

    Douglas-fir was mapped to the White Spruce category. This approach ensured consistency in assigning forest types to each grid cell. Cells with invalid forest percentage data were excluded. 17 Albedo Parameter Estimation Monthly albedo and kernel values were extracted and spatially averaged for each grid cell, generating 12-month time series. A linear mixt...

    work page

  5. [5]

    Convert Pg C to Pg CO ₂ using a factor of 3.67. 4. Convert Pg CO ₂ to Mg CO ₂ . 5. Normalize by regional area. 6. Adjust using a 100-year horizon factor (f_100 = 0.40). Validation and Statistics Model predictions were validated against satellite-derived chronosequences and field-based biomass estimates from comparable boreal forests in the Taiga Plains [4...

    work page 2017

  6. [6]

    Government of Canada. (2022). Canada’s 2 Billion Trees Program. Retrieved from https://www.canada.ca/en/services/environment/2-billion-trees.html

    work page 2022

  7. [7]

    C., Leavitt, S

    Cook-Patton, S. C., Leavitt, S. M., Gibbs, D., Harris, N. L., Lister, K., Anderson-Teixeira, K. J., ... & Griscom, B. W. (2020). Mapping carbon accumulation potential from global natural forest regrowth. Nature, 585 (7826), 545–550

    work page 2020

  8. [8]

    A., & Paré, D

    Laganière, J., Angers, D. A., & Paré, D. (2010). Carbon accumulation in agricultural soils after afforestation. Global Change Biology, 16 (1), 439–453

    work page 2010

Show all 46 references
  1. [9]

    S., Lal, R., Apps, M

    Bhatti, J. S., Lal, R., Apps, M. J., & Price, M. A. (2011). Carbon stocks and fluxes in boreal forests. Forest Ecology and Management, 262 (2), 185–197

    2011

  2. [10]

    A., Dymond, C

    Kurz, W. A., Dymond, C. C., Stinson, G., Rampley, G. J., Neilson, E. T., Carroll, A. L., ... & Safranyik, L. (2013). Carbon in Canada’s boreal forest — A synthesis. Environmental Reviews, 21 (4), 260–292

    2013

  3. [11]

    A., Quinton, W

    Carpino, O., Berg, A. A., Quinton, W. L., & Adams, J. R. (2021). Climate change and permafrost thaw-induced boreal forest shifts. Global Change Biology, 27 (6), 1234–1245

    2021

  4. [12]

    F., Allen, C

    Johnstone, J. F., Allen, C. D., Franklin, J. F., Frelich, L. E., Harvey, B. J., Higuera, P. E., ... & Turner, M. G. (2020). Changing disturbance regimes, ecological memory, and forest resilience. Frontiers in Ecology and the Environment, 18 (6), 369–378

    2020

  5. [13]

    Huberman, C., Asselin, H., Bergeron, Y., & Drobyshev, I. (2022). Climate-driven tree migration in the Taiga Plains. Frontiers in Forests and Global Change, 5 , 876123

    2022

  6. [14]

    Truchon-Savard, A., Payette, S., & Bhiry, N. (2019). Snowmelt timing and tree growth in subarctic tundra. Journal of Ecology, 107 (6), 2580–2592

    2019

  7. [15]

    J., Berg, E

    Dial, R. J., Berg, E. E., Timm, K., McMahon, A., & Geck, J. (2024). Snow depth and seedling survival at the Arctic treeline. Ecological Applications, 34 (1), e2945

    2024

  8. [16]

    & Hogg, E

    Aubin, I., Boisvert-Marsh, L., Kebli, H., McKenney, D., Pedlar, J., Lawrence, K., ... & Hogg, E. H. (2018). Tree vulnerability to climate change: Improving exposure-based assessments using traits as indicators. Journal of Applied Ecology, 55 (3), 1224–1233

    2018

  9. [17]

    Gamache, I., & Payette, S. (2005). Latitudinal decline in black spruce regeneration. Écoscience, 12 (3), 330–341. 15. Fricker, J. M., Chen, H. Y. H., & Wang, J. R. (2013). Stand age structural dynamics of boreal forests in central Canada. Open Journal of Ecology, 3 (3), 215–223

    2005

  10. [18]

    Ecosystem Classification Group. (2009). Ecological Regions of the Northwest Territories – Taiga Plains . Government of the Northwest Territories

    2009

  11. [19]

    Government of Northwest Territories. (2009). Taiga Plains Ecoregion Overview . Yellowknife: Environment and Natural Resources

    2009

  12. [20]

    R., Cook-Patton, S

    Drever, C. R., Cook-Patton, S. C., Baisley, P., Messier, C., & D’Orangeville, L. (2025). Prioritizing land for Canada’s 2 Billion Trees Program. Nature Climate Action, 3 , 112–125

    2025

  13. [21]

    Natural Resources Canada. (2022). The State of Canada’s Forests: Annual Report 2022 . Ottawa: Natural Resources Canada

    2022

  14. [22]

    Betts, R. A. (2000). Offset of the potential carbon sink from boreal forestation by decreases in surface albedo. Nature, 408 (6809), 187–190

    2000

  15. [23]

    B., Leonenko, Y., & Moreno-Cruz, J

    Dsouza, K. B., Leonenko, Y., & Moreno-Cruz, J. (2025). Assessing the climate benefits of afforestation in the Canadian Northern Boreal and Southern Arctic. Nature Communications, 16 (1), 1964

    2025

  16. [24]

    F., Nelson, H., & Wright, T

    Treseder, J. F., Nelson, H., & Wright, T. (2022). Indigenous-led forest stewardship. Forest Policy and Economics, 144 , 102828

    2022

  17. [25]

    X., & Yang, Y

    Huang, S., Meng, S. X., & Yang, Y. (2009). A Growth and Yield Projection System (GYPSY) for Alberta’s forests. Alberta Sustainable Resource Development

    2009

  18. [26]

    J., Rampley, G

    Kull, S. J., Rampley, G. J., Morken, S., Metsaranta, J., Neilson, E. T., & Kurz, W. A. (2014). Operational-scale carbon budget modeling for the forest sector: Model rules and calibration procedures for the CBM-CFS3. Natural Resources Canada

    2014

  19. [27]

    G., Conley, A., & Vitt, F

    Pendergrass, A. G., Conley, A., & Vitt, F. M. (2018). Radiative kernels for climate model diagnosis: A framework for quantifying forcing and feedbacks. Journal of Climate, 31 (2), 781–799. 19

    2018

  20. [28]

    T., Bright, R

    Hasler, C. T., Bright, R. M., & Astrup, R. (2023). Converting radiative forcing to CO ₂ -equivalent emissions for land surface changes. Environmental Research Letters, 18 (2), 025008

    2023

  21. [29]

    Bonan, G. B. (2008). Forests and climate change: Forcings, feedbacks, and the climate benefits of forests. Science, 320 (5882), 1444–1449

    2008

  22. [30]

    B., Randerson, J

    Jackson, R. B., Randerson, J. T., Canadell, J. G., Anderson, R. G., Avissar, R., Baldocchi, D. D., ... & Pataki, D. E. (2008). Protecting climate with forests. Environmental Research Letters, 3 (4), 044006

    2008

  23. [31]

    G., Canadell, J

    Anderson, R. G., Canadell, J. G., Randerson, J. T., Jackson, R. B., Hungate, B. A., Baldocchi, D. D., ... & Field, C. B. (2011). Biophysical considerations in forestry for climate protection. Frontiers in Ecology and the Environment, 9 (3), 174–182

    2011

  24. [32]

    M., Zhao, K., Jackson, R

    Bright, R. M., Zhao, K., Jackson, R. B., & Cherubini, F. (2015). Climate change mitigation through afforestation: Trade-offs between albedo and carbon sequestration. Earth System Dynamics, 6 (2), 301–315

    2015

  25. [33]

    C., Estel, S., Pongratz, J., Ceschia, E.,

    Luyssaert, S., Jammet, M., Stoy, P. C., Estel, S., Pongratz, J., Ceschia, E., ... & Zehner, C. (2014). Land management and land-cover change have impacts of similar magnitude on surface temperature. Nature Climate Change, 4 (5), 389–393

    2014

  26. [34]

    H., Raddatz, T., & Claussen, M

    Pongratz, J., Reick, C. H., Raddatz, T., & Claussen, M. (2018). Afforestation reduces climate warming by balancing albedo and carbon sequestration. Global Change Biology, 24 (3), 919–930

    2018

  27. [35]

    J., Ryder, J., Valade, A., Otto, J., & Luyssaert, S

    Naudts, K., Chen, Y., McGrath, M. J., Ryder, J., Valade, A., Otto, J., & Luyssaert, S. (2016). Europe’s forest management did not mitigate climate warming. Science, 351 (6273), 597–600

    2016

  28. [36]

    L., Wheeler, C

    Lewis, S. L., Wheeler, C. E., Mitchard, E. T. A., & Koch, A. (2019). Regenerate natural forests to store carbon. Nature, 568 (7750), 25–28

    2019

  29. [37]

    T., Thompson, J., Arets, E

    Poorter, L., van der Sande, M. T., Thompson, J., Arets, E. J. M. M., Alarcón, A., Álvarez-Sánchez, J., ... & Peña-Claros, M. (2016). Biodiversity enhances carbon storage in tropical forests. Nature, 530 (7589), 212–215

    2016

  30. [38]

    Jandl, R., Ledermann, T., Kindermann, G., Freudenschuss, A., & Gschwantner, T. (2019). Afforestation and its climate change mitigation potential. Current Forestry Reports, 5 (4), 203–213

    2019

  31. [39]

    L., Bebi, P., Duguay-Tetzlaff, A., Waser, L

    Schwaab, J., Davin, E. L., Bebi, P., Duguay-Tetzlaff, A., Waser, L. T., & Haeni, M. (2020). Trade-offs between carbon sequestration and albedo in boreal forests. Environmental Research Letters, 15 (8), 084027

    2020

  32. [40]

    K., & Montenegro, A

    Arora, V. K., & Montenegro, A. (2011). Small temperature benefits provided by realistic afforestation efforts. Nature Geoscience, 4 (8), 514–518

    2011

  33. [41]

    J., Lobell, D

    Bala, G., Caldeira, K., Wickett, M., Phillips, T. J., Lobell, D. B., Delire, C., & Mirin, A. (2007). Combined climate and carbon-cycle effects of large-scale deforestation. Proceedings of the National Academy of Sciences, 104 (16), 6550–6555

    2007

  34. [42]

    J., Creutzig, F., Fuss, S., Minx, J., Gabrielle, B.,

    Smith, P., Davis, S. J., Creutzig, F., Fuss, S., Minx, J., Gabrielle, B., ... & Sharifi, A. (2016). Biophysical and economic limits to negative CO ₂ emissions. Nature Climate Change, 6 (1), 42–50

    2016

  35. [43]

    J., Skakun, R., Filiatrault, M., Beaudoin, A., Gartrell, M., … & van der Sluijs, J

    Castilla, G., Hall, R. J., Skakun, R., Filiatrault, M., Beaudoin, A., Gartrell, M., … & van der Sluijs, J. (2022). The Multisource Vegetation Inventory (MVI): A satellite-based forest inventory for the Northwest Territories Taiga Plains. Remote Sensing, 14 (5), 1108. https://d...

    2022 doi

  36. [44]

    A., White, J

    Tompalski, P., Wulder, M. A., White, J. C., Hermosilla, T., Riofrío, J., & Kurz, W. A. (2024). Developing above-ground biomass yield curves for dominant boreal tree species from time-series remote-sensing data. Forest Ecology and Management, 561 , 121894. https://doi.org/10.10...

    2024

  37. [45]

    Natural Resources Canada. 2018a. Canadian National Fire Database (CNFDB) [website]. Ottawa,ON. https://cwfis.cfs.nrcan.gc.ca/ha/nfdb. Accessed : 26 April. 2026. 46. Parisien, M.-A.; Peters, V.S.; Wang, Y.; Little, J.M.; Bosch, E.M.; Stocks, B.J. 2006. Spatial patterns of fores...

    2026 doi

  38. [47]

    Ministère des Ressources naturelles du Québec. 1997. SYLVA II Version 1.3.2. Ministère des Ressources naturelles du Québec, Québec, (QC). 20 Data Availability The data that support the findings of this study are publicly available to download and are referenced in the bibliogr...

    1997

Pith tools

Reviewed August 7, 2026 · model on record in the stance chip above.