Carbon Cycle Science in Support of Decision Making

Key Finding 2

Integrating data on human drivers of the carbon cycle into Earth system and ecosystem models improves representation of carbon-climate feedbacks and increases the usefulness of model output to decision makers (high confidence).

Description of evidence base

For Key Finding 2, the impacts of human management activities on carbon stocks have been analyzed and documented for entity-scale greenhouse gas estimation of agricultural activities (Eve et al., 2014). This information is being integrated into models for use by agricultural land managers. For U.S. forests, attribution of human and natural influences (e.g., harvesting, natural disturbance, and forest age) has been successfully disaggregated using field data and models (Woodall et al., 2015) to help inform decision makers. Finally, to better represent human drivers on climate, carbon stocks, and commodity production and consumption at the global scale, human drivers representing land management are being integrated into Earth System Models (ESMs); Drewniak et al., 2013), and the management of land, energy, and fossil fuels is included in Integrated Assessment Models (IAMs; Chaturvedi et al., 2013; Le Page et al., 2016). As human drivers continue to be included in scientific research models, these models will continue to better represent actual local and global dynamics, thereby becoming more useful for decision making.

Major uncertainties

While inclusion of human drivers in estimates of carbon cycle fluxes and stock changes often results in more useful information for decision making, it also can result in a higher number of model parameters, which can increase statistical uncertainty and variability of model results. However, this increased statistical uncertainty does not necessarily reduce the usefulness of findings for decision making, particularly if the uncertainty is a uniform bias or a broader confidence interval surrounding a stable trend.

Assessment of confidence based on evidence and agreement, including short description of nature of evidence and level of agreement

Continued inclusion of human drivers within ecosystem models and ESMs will better represent the influence of human activities on the carbon cycle, thereby improving the usefulness of results to decision makers.

Summary sentence or paragraph that integrates the above information

Inclusion of human drivers in carbon cycle models increases the accuracy of models and generates model output that is more useful for decision making. For Key Finding 2, statistical uncertainty may increase or decrease based on the change in model complexity.

Key Finding 3

Attribution, accounting, and projections of carbon cycle fluxes increase the usefulness of carbon cycle science for decision-making purposes (very high confidence).

Description of evidence base

Carbon cycle fluxes by themselves, both observed and estimated, are useful to understand carbon cycle processes but not particularly useful for decision making. Changes in net emissions associated with changes in human activities in the past, present, and future are particularly useful. Placing emissions in the context of a baseline or business-as-usual scenario, compared to alternative or new management, is necessary. For Key Finding 3, it is the relative change in carbon stocks and emissions associated with activities, along with tracing these activities to their functions in human well-being, that is most needed by decision makers (see Ch. 6: Social Science Perspectives on Carbon). This information often is embedded in science-based models, but to be useful it must be aggregated or synthesized using established carbon accounting protocols.

Carbon accounting of direct and indirect impacts of bioenergy production and consumption has been analyzed (Adler et al., 2007) and included in energy and natural resource economic models (Frank et al., 2011; Mu et al., 2015). While carbon accounting in forestry has a long history of development (Schlamadinger and Marland 1996), there remain issues and debate around the effects of wildfire management on net emissions (Campbell et al., 2012; Hurteau and North 2009) and the use of wood products to offset emissions (Lippke et al., 2011; McKinley et al., 2011). Much of the debate surrounds a relatively new finding that conducting carbon accounting and life cycle analysis at the landscape scale is more representative of the net impact of policies and practices on carbon stocks than doing so at a field or plot scale (Galik and Abt 2012; Johnson 2009). Skog et al. (2014) provides a recent summary of practices that are most effective for reducing net emissions. Developing consistency in accounting and projections across the energy and land sector, along with the tools needed to represent upstream, downstream, and landscape­scale impacts, would be useful for decision making.

Major uncertainties

Representation of net carbon fluxes will become more accurate with the inclusion of established carbon accounting methods. This is evident in the science publication record that illustrates convergence of net emissions estimates associated with changes in management.

Assessment of confidence based on evidence and agreement, including short description of nature of evidence and level of agreement

Estimating net carbon emissions using established and state-of-the-art carbon accounting methods will increase the usefulness of carbon cycle science results for decision makers. Conducting more research in this area, particularly among researchers involved in carbon accounting and basic carbon cycle science, will be essential to generating science-based findings useful for decision making.

Estimated likelihood of impact or consequence, including short description of basis of estimate

Improvements in projection capabilities very likely will help guide decisions associated with energy, land use, and the carbon cycle. Increased use and development of accounting and attribution methods also are highly likely to improve the understanding of changes in carbon stocks and emissions and the application of this understanding to decision making.

Summary sentence or paragraph that integrates the above information

For Key Finding 3, different methods of carbon accounting result in different estimates of carbon stocks and emissions, thereby resulting in inconsistent science results. Use of established carbon accounting methods by researchers in carbon cycle science research will increase consistency in carbon emissions estimates associated with given activities, thereby providing more useful information to decision makers and more useful metrics for comparison within the research community.

Key Finding 4

Developing stronger linkages among research disciplines for Earth system processes, carbon management, and carbon prediction, with a focus on consistent and scalable datasets as model inputs, will improve joint representation of natural and managed systems needed for decision making (high confidence).

Description of evidence base

Integration and coordination among global climate models, land models, and IAMs are occurring. National land management models and natural resource economic models also are becoming increasingly integrated. However, there remains a gap between global climate and IAMs and national land-use and economic models. The latter are used more often for decision making, but the former are critical in understanding global feedbacks among carbon, climate, economics, and land-use change. For Key Finding 4, increased communication and links between global drivers and subnational dynamics that impact carbon (Beach et al., 2015; de Vries et al., 2013; Kraucunas et al., 2014; Verburg et al., 2009) could help develop comprehensive science-based systems to better inform decision making. Efforts like this will depend on cross-sectoral and cross-scale research to better understand how to integrate or link needed components and scales.

Major uncertainties

Uncertainties exist in successful development of models across scales (e.g., local, regional, continental, and global).

Assessment of confidence based on evidence and agreement, including short description of nature of evidence and level of agreement

A more complete picture of carbon dynamics across scales, using more realistic representation of actual stocks and emissions, will increase the accuracy of carbon models and their use by decision makers.

Estimated likelihood of impact or consequence, including short description of basis of estimate

The likelihood of impacts is high, although developing links between national- and global-scale data and models can be challenging, and success is less certain.

Summary sentence or paragraph that integrates the above information

For Key Finding 4, connections between global biogeochemistry and climate models with subnational land management models will be useful to understand the feedbacks between global carbon cycles and carbon management activities. Linking models or model output and input is often challenging and includes a level of inherent uncertainty.