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Field-based tree mortality constraint reduces estimates of model-projected forest carbon sinks.

ABSTRACT: Considerable uncertainty and debate exist in projecting the future capacity of forests to sequester atmospheric CO₂. Here we estimate spatially explicit patterns of biomass loss by tree mortality (LOSS) from largely unmanaged forest plots to constrain projected (2015-2099) net primary productivity (NPP), heterotrophic respiration (HR) and net carbon sink in six dynamic global vegetation models (DGVMs) across continents. This approach relies on a strong relationship among LOSS, NPP, and HR at continental or biome scales. The DGVMs overestimated historical LOSS, particularly in tropical regions and eastern North America by as much as 5 Mg ha^-1 y^-1. The modeled spread of DGVM-projected NPP and HR uncertainties was substantially reduced in tropical regions after incorporating the field-based mortality constraint. The observation-constrained models show a decrease in the tropical forest carbon sink by the end of the century, particularly across South America (from 2 to 1.4 PgC y^-1), and an increase in the sink in North America (from 0.8 to 1.1 PgC y^-1). These results highlight the feasibility of using forest demographic data to empirically constrain forest carbon sink projections and the potential overestimation of projected tropical forest carbon sinks.

SUBMITTER: Yu K

PROVIDER: S-EPMC9018757 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature

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Field-based tree mortality constraint reduces estimates of model-projected forest carbon sinks.

Yu Kailiang K Ciais Philippe P Seneviratne Sonia I SI Liu Zhihua Z Chen Han Y H HYH Barichivich Jonathan J Allen Craig D CD Yang Hui H Huang Yuanyuan Y Ballantyne Ashley P AP

Nature communications 20220419 1

Considerable uncertainty and debate exist in projecting the future capacity of forests to sequester atmospheric CO<sub>2</sub>. Here we estimate spatially explicit patterns of biomass loss by tree mortality (LOSS) from largely unmanaged forest plots to constrain projected (2015-2099) net primary productivity (NPP), heterotrophic respiration (HR) and net carbon sink in six dynamic global vegetation models (DGVMs) across continents. This approach relies on a strong relationship among LOSS, NPP, an ...[more]

PMID: 35440564

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Project description:ImportanceThe United States is experiencing a crisis of opioid overdose. In response, the US Department of Health and Human Services has defined a goal to reduce overdose mortality by 40% by 2022.ObjectiveTo identify specific combinations of 3 interventions (initiating more people to medications for opioid use disorder [MOUD], increasing 6-month retention with MOUD, and increasing naloxone distribution) associated with at least a 40% reduction in opioid overdose in simulated populations.Design, setting, and participantsThis decision analytical model used a dynamic population-level state-transition model to project outcomes over a 2-year horizon. Each intervention scenario was compared with the counterfactual of no intervention in simulated urban and rural communities in Massachusetts. Simulation modeling was used to determine the associations of community-level interventions with opioid overdose rates. The 3 examined interventions were initiation of more people to MOUD, increasing individuals' retention with MOUD, and increasing distribution of naloxone. Data were analyzed from July to November 2020.Main outcomes and measuresReduction in overdose mortality, medication treatment capacity needs, and naloxone needs.ResultsNo single intervention was associated with a 40% reduction in overdose mortality in the simulated communities. Reaching this goal required use of MOUD and naloxone. Achieving a 40% reduction required that 10% to 15% of the estimated OUD population not already receiving MOUD initiate MOUD every month, with 45% to 60%% retention for at least 6 months, and increased naloxone distribution. In all feasible settings and scenarios, attaining a 40% reduction in overdose mortality required that in every month, at least 10% of the population with OUD who were not currently receiving treatment initiate an MOUD.Conclusions and relevanceIn this modeling study, only communities with increased capacity for treating with MOUD and increased MOUD retention experienced a 40% decrease in overdose mortality. These findings could provide a framework for developing community-level interventions to reduce opioid overdose death.

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Field-based tree mortality constraint reduces estimates of model-projected forest carbon sinks.

Publications

Field-based tree mortality constraint reduces estimates of model-projected forest carbon sinks.

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