Contemporary forest carbon dynamics in the northern U.S. associated with land cover changes

Wörns, MA; Domke, Grant M.; Woodall, Christopher W.; D’Amato, Anthony W.

doi:10.1016/j.ecolind.2019.105901

Cited by 15 publications

(12 citation statements)

References 49 publications

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“…Estimating the spatial-temporal distributions of forest carbon stocks subject to land cover changes is critical for estimating and reporting GHG emissions [54]. To spatially represent explicit in GEE and has been widely demonstrated to improve the accuracy of maps by combining random subsets of trees to classify the training samples.…”

Section: Carbon Stock and Change Magnitudementioning

confidence: 99%

Section: Carbon Stock and Change Magnitudementioning

confidence: 99%

“…Estimating the spatial-temporal distributions of forest carbon stocks subject to land cover changes is critical for estimating and reporting GHG emissions [54]. To spatially represent explicit forest degradation along with degraded carbon, we generated a carbon map of pine forests using 51 sampled plots from the NFI data and Landsat 2018.…”

Section: Carbon Stock and Change Magnitudementioning

confidence: 99%

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Monitoring Approach for Tropical Coniferous Forest Degradation Using Remote Sensing and Field Data

et al. 2020

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Current estimates of CO2 emissions from forest degradation are generally based on insufficient information and are characterized by high uncertainty, while a global definition of ‘forest degradation’ is currently being discussed in the scientific arena. This study proposes an automated approach to monitor degradation using a Landsat time series. The methodology was developed using the Google Earth Engine (GEE) and applied in a pine forest area of the Dominican Republic. Land cover change mapping was conducted using the random forest (RF) algorithm and resulted in a cumulative overall accuracy of 92.8%. Forest degradation was mapped with a 70.7% user accuracy and a 91.3% producer accuracy. Estimates of the degraded area had a margin of error of 10.8%. A number of 344 Landsat collections, corresponding to the period from 1990 to 2018, were used in the analysis. Additionally, 51 sample plots from a forest inventory were used. The carbon stocks and emissions from forest degradation were estimated using the RF algorithm with an R2 of 0.78. GEE proved to be an appropriate tool to monitor the degradation of tropical forests, and the methodology developed herein is a robust, reliable, and replicable tool that could be used to estimate forest degradation and improve monitoring, reporting, and verification (MRV) systems under the reducing emissions from deforestation and forest degradation (REDD+) mechanism.

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Section: Carbon Stock and Change Magnitudementioning

confidence: 99%

Section: Carbon Stock and Change Magnitudementioning

confidence: 99%

“…Estimating the spatial-temporal distributions of forest carbon stocks subject to land cover changes is critical for estimating and reporting GHG emissions [54]. To spatially represent explicit forest degradation along with degraded carbon, we generated a carbon map of pine forests using 51 sampled plots from the NFI data and Landsat 2018.…”

Section: Carbon Stock and Change Magnitudementioning

confidence: 99%

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Monitoring Approach for Tropical Coniferous Forest Degradation Using Remote Sensing and Field Data

et al. 2020

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“…Forest carbon plays a key role in regulating the climate system (Houghton et al 2012, Williams et al 2012, Reinmann et al 2016, Ma et al 2020, Finzi et al 2020). Forest land use, including timber harvest and conversion for developed uses, has significant impacts on forest carbon dynamics and, thus, future land use has the potential to mitigate or exacerbate climate change (Pan et al 2011, Butler et al 2015, Woodall et al 2015, Le Quéré et al 2018).…”

Section: Introductionmentioning

confidence: 99%

“…If rates and spatial patterns of forest conversion continue as they have from 1990-2010 through 2050, an additional 0.5 million ha of forest land could be lost to development with consequential impacts to carbon storage and sequestration (Thompson et al 2017b). Even more importantly, despite recent reductions in timber harvesting throughout much of southern New England (Kittredge et al 2017), harvesting remains the primary driver of mature tree mortality and carbon loss throughout the region (Canham et al 2013, Harris et al 2016, Thompson et al 2017a, Ma et al 2020). Therefore, it is important to understand how changes in future land-use patterns, including both development and harvesting, affect the total carbon storage in New England’s forests and elsewhere.…”

Section: Introductionmentioning

confidence: 99%

Does land use matter? Carbon consequences of alternative land use futures in New England

MacLean

Duveneck

Plisinski

et al. 2021

Preprint

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Globally, forests play an important role in climate change mitigation. However, land-use impacts the ability of forests to sequester and store carbon. Here we quantify the impacts of five divergent future land-use scenarios on aboveground forest carbon stocks and fluxes throughout New England. These scenarios, four co-designed with stakeholders from throughout the region and the fifth a continuation of recent trends in land use, were simulated by coupling a land cover change model with a mechanistic forest growth model to produce estimates of aboveground carbon over 50 years. Future carbon removed through harvesting and development was tracked using a standard carbon accounting methodology, modified to fit our modeling framework. Of the simulated changes in land use, changes in harvesting had the most profound and immediate impacts on carbon stocks and fluxes. In one of the future land-use scenarios including a rapid expansion of harvesting for biomass energy, this changed New England’s forests from a net carbon sink to a net carbon source in 2060. Also in these simulations, relatively small reductions in harvest intensities (e.g., 10% reduction), coupled with an increased percent of wood going into longer-term storage, led to substantial reductions in net carbon emissions (909 MMtCO2eq) as compared to a continuation of recent trends in land use. However, these projected gains in carbon storage and reduction in emissions from less intense harvesting regimes can only be realized if it is paired with a reduction in the consumption of the timber products, and their replacements, that otherwise would result in additional emissions from leakage and substitution.

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Carbon sequestration scenarios in Portugal: which way to go forward?

Cunha

Campos

David

et al. 2021

Environ Monit Assess

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Background: Assessing carbon storage and sequestration is key for de ning effective conservation actions to mitigate climate change. Forest species changes have direct impacts on carbon stocks and may lead to undesirable climate trade-offs. In this paper, we measure aboveground biomass (AGB) and the impact of forest changes on climate regulation through three land policy scenarios by 2030 in continental Portugal.Results: We found that a High intervention scenario, supported by an important increase in "Other coniferous trees" class, will provide 29.5% more of carbon sequestration, whereas a Low intervention scenario, in which there is a moderate increase in all forest classes, will result in an increase of 5.7%. A business as usual (BAU) scenario, supported by an increase in eucalyptus forests and a decrease in autochthonous species, will decrease carbon sequestration (-2.7%), particularly Lisboa, Algarve and Norte regions. Economic valuation shows that the High intervention scenario will generate the highest economic outcome for climate regulation by 2030. Conclusion:This study provides a spatial-based methodology for monitoring carbon sequestration and new insights about the impact of policies for Green House Gas (GHG) mitigation, supporting the 2030 Sustainable Development Goals achievement.

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Contemporary forest carbon dynamics in the northern U.S. associated with land cover changes

Cited by 15 publications

References 49 publications

Monitoring Approach for Tropical Coniferous Forest Degradation Using Remote Sensing and Field Data

Monitoring Approach for Tropical Coniferous Forest Degradation Using Remote Sensing and Field Data

Does land use matter? Carbon consequences of alternative land use futures in New England

Carbon sequestration scenarios in Portugal: which way to go forward?

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