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Abstract According to classic stomatal optimization theory, plant stomata are regulated to maximize carbon assimilation for a given water loss. A key component of stomatal optimization models is marginal water‐use efficiency (mWUE), the ratio of the change of transpiration to the change in carbon assimilation. Although the mWUE is often assumed to be constant, variability of mWUE under changing hydrologic conditions has been reported. However, there has yet to be a consensus on the patterns of mWUE variabilities and their relations with atmospheric aridity. We investigate the dynamics of mWUE in response to vapor pressure deficit (VPD) and aridity index using carbon and water fluxes from 115 eddy covariance towers available from the global database FLUXNET. We demonstrate a non‐linear mWUE‐VPD relationship at a sub‐daily scale in general; mWUE varies substantially at both low and high VPD levels. However, mWUE remains relatively constant within the mid‐range of VPD. Despite the highly non‐linear relationship between mWUE and VPD, the relationship can be informed by the strong linear relationship between ecosystem‐level inherent water‐use efficiency (IWUE) and mWUE using the slope,m*. We further identify site‐specificm* and its variability with changing site‐level aridity across six vegetation types. We suggest accurately representing the relationship between IWUE and VPD using Michaelis–Menten or quadratic functions to ensure precise estimation of mWUE variability for individual sites. 

Eddy covariance measurement systems provide direct observation of the exchange of greenhouse gases between ecosystems and the atmosphere, but have only occasionally been intentionally applied to quantify the carbon dynamics associated with specific climate mitigation strategies. Natural climate solutions (NCS) harness the photosynthetic power of ecosystems to avoid emissions and remove atmospheric carbon dioxide (CO2), sequestering it in biological carbon pools. In this perspective, we aim to determine which kinds of NCS strategies are most suitable for ecosystem-scale flux measurements and how these measurements should be deployed for diverse NCS scales and goals. We find that ecosystem-scale flux measurements bring unique value when assessing NCS strategies characterized by inaccessible and hard-to-observe carbon pool changes, important non-CO2 greenhouse gas fluxes, the potential for biophysical impacts, or dynamic successional changes. We propose three deployment types for ecosystem-scale flux measurements at various NCS scales to constrain wide uncertainties and chart a workable path forward: “pilot”, “upscale”, and “monitor”. Together, the integration of ecosystem-scale flux measurements by the NCS community and the prioritization of NCS measurements by the flux community, have the potential to improve accounting in ways that capture the net impacts, unintended feedbacks, and on-the-ground specifics of a wide range of emerging NCS strategies. 

Abstract The leaf economics spectrum 1,2 and the global spectrum of plant forms and functions 3 revealed fundamental axes of variation in plant traits, which represent different ecological strategies that are shaped by the evolutionary development of plant species 2 . Ecosystem functions depend on environmental conditions and the traits of species that comprise the ecological communities 4 . However, the axes of variation of ecosystem functions are largely unknown, which limits our understanding of how ecosystems respond as a whole to anthropogenic drivers, climate and environmental variability 4,5 . Here we derive a set of ecosystem functions 6 from a dataset of surface gas exchange measurements across major terrestrial biomes. We find that most of the variability within ecosystem functions (71.8%) is captured by three key axes. The first axis reflects maximum ecosystem productivity and is mostly explained by vegetation structure. The second axis reflects ecosystem water-use strategies and is jointly explained by variation in vegetation height and climate. The third axis, which represents ecosystem carbon-use efficiency, features a gradient related to aridity, and is explained primarily by variation in vegetation structure. We show that two state-of-the-art land surface models reproduce the first and most important axis of ecosystem functions. However, the models tend to simulate more strongly correlated functions than those observed, which limits their ability to accurately predict the full range of responses to environmental changes in carbon, water and energy cycling in terrestrial ecosystems 7,8 . 

Abstract. Long-term environmental research networks are one approach toadvancing local, regional, and global environmental science and education. Aremarkable number and wide variety of environmental research networks operatearound the world today. These are diverse in funding, infrastructure,motivating questions, scientific strengths, and the sciences that birthed andmaintain the networks. Some networks have individual sites that wereselected because they had produced invaluable long-term data, while othernetworks have new sites selected to span ecological gradients. However, alllong-term environmental networks share two challenges. Networks must keeppace with scientific advances and interact with both the scientific communityand society at large. If networks fall short of successfully addressing thesechallenges, they risk becoming irrelevant. The objective of this paper is toassert that the biogeosciences offer environmental research networks a numberof opportunities to expand scientific impact and public engagement. Weexplore some of these opportunities with four networks: the InternationalLong-Term Ecological Research Network programs (ILTERs), critical zoneobservatories (CZOs), Earth and ecological observatory networks (EONs),and the FLUXNET program of eddy flux sites. While these networks were foundedand expanded by interdisciplinary scientists, the preponderance of expertise andfunding has gravitated activities of ILTERs and EONs toward ecology andbiology, CZOs toward the Earth sciences and geology, and FLUXNET towardecophysiology and micrometeorology. Our point is not to homogenize networks,nor to diminish disciplinary science. Rather, we argue that by more fullyincorporating the integration of biology and geology in long-termenvironmental research networks, scientists can better leverage networkassets, keep pace with the ever-changing science of the environment, andengage with larger scientific and public audiences.