Research to Confront Climate Change Complexity: Intersectionality, Integration, and Innovative Governance.

Climate impacts increasingly unfold in interlinked systems of people, nature, and infrastructure. The cascading consequences are revealing sometimes surprising connections across sectors and regions, and prospects for climate responses also depend on complex, difficult-to-understand interactions. In this commentary, we build on the innovations of the United States Fifth National Climate Assessment to suggest a framework for understanding and responding to complex climate challenges.

Examining Interactions Between and Among Predictors of Net Ecosystem Exchange: A Machine Learning Approach in a Semi-arid Landscape.

Net ecosystem exchange (NEE) is an essential climate indicator of the direction and magnitude of carbon dioxide (CO) transfer between land surfaces and the atmosphere. Improved estimates of NEE can serve to better constrain spatiotemporal characteristics of terrestrial carbon fluxes, improve verification of land models, and advance monitoring of Earth's terrestrial ecosystems. Spatiotemporal NEE information developed by combining ground-based flux tower observations and spatiotemporal remote sensing datasets are of potential value in benchmarking land models.