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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. 

Abstract 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.