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This chapter examines the use of Christian scripture by some who doubt the reality, anthropogenesis, or seriousness of climate change. It offers an overview of public opinion surveys and social scientific research on the relationship between religion and climate attitudes in the United States, with a focus on evangelical Christianity as the largest and generally most skeptical religious group. Surveying uses of the Bible by evangelical climate skeptics, the chapter demonstrates various ways in which skeptics—including pastors, policymakers, scholars, and others—draw from scripture to cast doubt on climate science and to advocate against climate action. It outlines the logic behind those uses, explores the limits and contradictions of such logic, and highlights political affinities that may motivate skeptics to interpret and deploy scripture in these ways.

Terrestrial ecosystems play a critical role in the global carbon cycle but have highly uncertain future dynamics. Ecosystem modelling that includes the scaling-up of underlying mechanistic ecological processes has the potential to improve the accuracy of future projections, while retaining key process-level detail. Over the past two decades, multiple modelling advances have been made to meet this challenge, including the Ecosystem Demography (ED) model and its derivatives including ED2 and FATES. Here, we present the global evaluation of the Ecosystem Demography model (ED v3.0), which likes its predecessors features the formal scaling of physiological processes of individual-based vegetation dynamics to ecosystem scales, together with integrated submodules of soil biogeochemistry and soil hydrology, while retaining explicit tracking of vegetation 3-D structure. This new version builds on previous versions and provides the first global calibration and evaluation, global tracking of the effects of climate and land-use change on vegetation 3-D structure, new spin-up process and input datasets, as well as numerous other advances. Model evaluation was performed with respect to a set of important benchmarking datasets, and model estimates were within observational constraints for multiple key variables including: (i) global patterns of dominant plant functional types (broadleaf vs evergreen); (ii) spatial distribution, seasonal cycle, and interannual trends of global Gross Primary Production (GPP); (iii) global interannual variability of Net Biome Production (NBP); and (iv) global patterns of vertical structure including leaf area and canopy height. With this global model version, it is now possible to simulate vegetation dynamics from local to global scales and from seconds to centuries, with a consistent mechanistic modelling framework amendable to data from multiple traditional and new remote sensing sources, including lidar.