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Summary The partitioning of photosynthate among various forest carbon pools is a key process regulating long‐term carbon sequestration, with allocation to aboveground woody biomass carbon (AGBC) in particular playing an outsized role in the global carbon cycle due to its slow residence time. However, directly estimating the fraction of gross primary productivity (GPP) that goes to AGBC has historically been difficult and time‐consuming, leaving us with persistent uncertainties.We used an extensive dataset of tree‐ring chronologies co‐located at flux towers to assess the coupling between AGBC and GPP, calculate the fraction of fixed carbon that is allocated to AGBC, and understand the drivers of variability in this fraction.We found that annual AGBC and GPP were rarely correlated, and that annual AGBC represented only a small fraction (c. 9%) of fixed carbon. This fraction varied considerably across sites and was driven by differences in stand density and site climate. Annual AGBC was suppressed byc. 30% during drought and remained below average for years afterward.These results imply that assumptions of relatively stationary allocation of GPP to woody biomass and other plant tissues could lead to systematic biases in modeled carbon accumulation in different plant pools and thus in carbon residence time. 

Forests around the world are experiencing changes due to climate variability and human land use. How these changes interact and influence the vulnerability of forests are not well understood. In the eastern United States, well‐documented anthropogenic disturbances and land‐use decisions, such as logging and fire suppression, have influenced forest species assemblages, leading to a demographic shift from forests dominated by xeric species to those dominated by mesic species. Contemporarily, the climate has changed and is expected to continue to warm and produce higher evaporative demand, imposing stronger drought stress on forest communities. Here, we use an extensive network of tree‐ring records from common hardwood species across ~100 sites and ~1300 trees in the eastern United States to examine the magnitude of growth response to both wet and dry climate extremes. We find that growth reductions during drought exceed the positive growth response to pluvials. Mesic species such asLiriodendron tulipiferaandAcer saccharum, which are becoming more dominant, are more sensitive to drought than more xeric species, such as oaks (Quercus) and hickory (Carya), especially at moderate and extreme drought intensities. Although more extreme droughts produce a larger annual growth reduction, mild droughts resulted in the largest cumulative growth decreases due to their higher frequency. When using global climate model projections, all scenarios show drought frequency increasing substantially (3–9 times more likely) by 2100. Thus, the ongoing demographic shift toward more mesic species in the eastern United States combined with drier conditions results in larger drought‐induced growth declines, suggesting that drought will have an even larger impact on aboveground carbon uptake in the future in the eastern United States. 

Summary A new proliferation of optical instruments that can be attached to towers over or within ecosystems, or ‘proximal’ remote sensing, enables a comprehensive characterization of terrestrial ecosystem structure, function, and fluxes of energy, water, and carbon. Proximal remote sensing can bridge the gap between individual plants, site‐level eddy‐covariance fluxes, and airborne and spaceborne remote sensing by providing continuous data at a high‐spatiotemporal resolution. Here, we review recent advances in proximal remote sensing for improving our mechanistic understanding of plant and ecosystem processes, model development, and validation of current and upcoming satellite missions. We provide current best practices for data availability and metadata for proximal remote sensing: spectral reflectance, solar‐induced fluorescence, thermal infrared radiation, microwave backscatter, and LiDAR. Our paper outlines the steps necessary for making these data streams more widespread, accessible, interoperable, and information‐rich, enabling us to address key ecological questions unanswerable from space‐based observations alone and, ultimately, to demonstrate the feasibility of these technologies to address critical questions in local and global ecology. 

Abstract An exponential rise in the atmospheric vapour pressure deficit (VPD) is among the most consequential impacts of climate change in terrestrial ecosystems. Rising VPD has negative and cascading effects on nearly all aspects of plant function including photosynthesis, water status, growth and survival. These responses are exacerbated by land–atmosphere interactions that couple VPD to soil water and govern the evolution of drought, affecting a range of ecosystem services including carbon uptake, biodiversity, the provisioning of water resources and crop yields. However, despite the global nature of this phenomenon, research on how to incorporate these impacts into resilient management regimes is largely in its infancy, due in part to the entanglement of VPD trends with those of other co‐evolving climate drivers. Here, we review the mechanistic bases of VPD impacts at a range of spatial scales, paying particular attention to the independent and interactive influence of VPD in the context of other environmental changes. We then evaluate the consequences of these impacts within key management contexts, including water resources, croplands, wildfire risk mitigation and management of natural grasslands and forests. We conclude with recommendations describing how management regimes could be altered to mitigate the otherwise highly deleterious consequences of rising VPD. 

Abstract Process-based models of tree-ring width are used both for reconstructing past climates and for projecting changes in growth due to climate change. Since soil moisture observations are unavailable at appropriate spatial and temporal scales, these models generally rely on simple water budgets driven in part by temperature-based potential evapotranspiration (PET) estimates, but the choice of PET model could have large effects on simulated soil moisture, moisture stress, and radial growth. Here, I use four different PET models to drive the VS-Lite model and evaluate the extent to which they differ in both their ability to replicate observed growth variability and their simulated responses to projected 21st century warming. Across more than 1200 tree-ring width chronologies in the conterminous United States, there were no significant differences among the four PET models in their ability to replicate observed radial growth, but the models differed in their responses to 21st century warming. The temperature-driven empirical PET models (Thornthwaite and Hargreaves) simulated much larger warming-induced increases in PET and decreases in soil moisture than the more physically realistic PET models (Priestley–Taylor and Penman–Monteith). In cooler and more mesic regions with relatively minimal moisture constraints to growth, the models simulated similarly small reductions in growth with increased warming. However, in dry regions, the Thornthwaite- and Hargreaves-driven VS-Lite models simulated an increase in moisture stress roughly double that of the Priestley–Taylor and Penman–Monteith models, which also translated to larger simulated declines in radial growth under warming. While the lack of difference in the models’ ability to replicate observed radial growth variability is an encouraging sign for some applications (e.g. attributing changes in growth to specific climatic drivers), the large differences in model responses to warming suggest that caution is needed when applying the temperature-driven PET models to climatic conditions with large trends in temperature.