Abstract: It is well recognized that natural land is of great importance, and measures of the value of natural lands are required when making data-driven policy decisions between land development and land preservation. One of the most important values of natural land areas is the recreational services provided. In this study, we apply the travel cost method to estimate the recreation use value provided by the natural land in New England. Specifically, this study calculates the total consumer surplus for hunting, fishing, and wildlife-watching in the New England region. We also investigate whether and how people from households of different race and surroundings have different recreational habits. Using data from the National Survey of Fishing, Hunting, & Wildlife-Associated Recreation, we found that New England natural lands provide a remarkable amount of recreation use value—$88 billion per year to U.S. citizens who partake in wildlife-related activities, accordingly to the travel cost method. Our estimates can serve as input for economic projection and policy analysis models and allow more equitable and appropriate data-driven policy decisions.

Abstract: If goals set under the Paris Agreement are met, the world may hold warming well below 2°C; however, parties are not on track to deliver these commitments, increasing focus on policy implementation to close the gap between ambition and action. Recently, the US government passed its most prominent piece of climate legislation to date—the Inflation Reduction Act of 2022 (IRA)—designed to invest in a wide range of programs that, among other provisions, incentivize clean energy and carbon management, encourage electrification and efficiency measures, reduce methane emissions, promote domestic supply chains, and address environmental justice concerns. IRA’s scope and complexity make modeling important to understand impacts on emissions and energy systems. We leverage results from nine independent, state-of-the-art models to examine potential implications of key IRA provisions, showing economy-wide emissions reductions between 43 and 48% below 2005 levels by 2035.

This multimodel analysis provides a range of decision-relevant information. For example, international policy-makers and negotiators need to track progress toward Paris Agreement pledges, and assessing IRA’s impacts is important to monitor US efforts and to provide a template for measuring the performance of other sectors and jurisdictions. Federal and state policy-makers can use this IRA analysis to compare updated baselines with policy targets—for emissions, electric vehicle deployment, and others—to understand the magnitude of additional policies and private-sector actions needed to narrow implementation gaps. Electric companies need to know how long IRA incentives will be available, because these subsidies can continue until electricity emissions are below 25% of their 2022 levels, which requires national models to evaluate. Industry- and technology-specific deployment can support investors, technology developers, researchers, and companies to quantify market opportunities.

Abstract: As authors of Meiler et al. (2022), we welcome Zehr and Riemann's (2023) comment and discussion. We agree, of course, with the general statement that “quantification of gene copy numbers is valuable in marine microbial ecology” and wish to clarify that one of the purposes of Meiler et al. (2022) was to address the specific challenge of using a compilation of quantitative polymerase chain reaction (qPCR) nifH data to evaluate the skill of biogeochemical models. In that particular case, the data were most helpful in constraining the range of diazotrophs, but several sources of uncertainty limited more detailed quantitative evaluations. This was not intended to imply a lack of value or promise for such applications of qPCR data: we believe that testing and constraining biogeochemical and ecological models will be an important application of qPCR data, yet the quantitative interface between molecular data and biogeochemical models remains at its infancy.

In the following, we first provide a background perspective for the Meiler et al. (2022) study, pointing out why observations and simulations are rooted in different currencies. We then discuss in more detail some of the specific points raised by Zehr and Riemann (2023) and highlight why further efforts toward intercalibration of currencies used to measure and simulate marine microbial populations is particularly significant if we are to fully exploit the data in biogeochemical and climate modeling applications. We end by summarizing some potentially fruitful avenues for future effort stimulated by this dialog.