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ABSTRACT Climate extremes—e.g., drought, atmospheric rivers, heat waves—are increasing in severity and frequency across the western United States of America (USA). Tree‐ring widths reflect the concurrent and legacy effects of such climate extremes, yet our ability to predict extreme tree growth is often poor. Could tree‐ring data themselves identify the most important climate variables driving extreme low‐ and high‐growth states? How does the importance of these climate drivers differ across species and time? To address these questions, we explored the spatial synchrony of extreme low‐ and high‐growth years, the symmetry of climate effects on the probability of low‐ and high‐growth years, and how climate drivers of extreme growth vary across tree species. We compiled ring widths for seven species (four gymnosperms and three angiosperms) from 604 sites in the western USA and classified each annual ring as representing extreme low, extreme high, or nominal growth. We used classification random forest (RF) models to evaluate the importance of 30 seasonal climate variables for predicting extreme growth, including precipitation, temperature, and vapor pressure deficit (VPD) during and up to four years prior to ring formation. For four species (three gymnosperms, one angiosperm) for which climate was predictive of growth, the RF models correctly classified 89%–98% and 80%–95% of low‐ and high‐growth years, respectively. For these species, asymmetric climate responses dominated. Current‐year winter hydroclimate (precipitation and VPD) was most important for predicting low growth, but prediction of high growth required multiple years of favorable moisture conditions, and the occurrence of low‐growth years was more synchronous across space than high‐growth years. Summer climate and temperature (regardless of season) were only weakly predictive of growth extremes. Our results motivate ecologically relevant definitions of drought such that current winter moisture stress exerts a dominant role in governing growth reductions in multiple tree species broadly distributed across the western USA. 

Abstract The National Ecological Observatory Network (NEON) provides over 180 distinct data products from 81 sites (47 terrestrial and 34 freshwater aquatic sites) within the United States and Puerto Rico. These data products include both field and remote sensing data collected using standardized protocols and sampling schema, with centralized quality assurance and quality control (QA/QC) provided by NEON staff. Such breadth of data creates opportunities for the research community to extend basic and applied research while also extending the impact and reach of NEON data through the creation of derived data products—higher level data products derived by the user community from NEON data. Derived data products are curated, documented, reproducibly‐generated datasets created by applying various processing steps to one or more lower level data products—including interpolation, extrapolation, integration, statistical analysis, modeling, or transformations. Derived data products directly benefit the research community and increase the impact of NEON data by broadening the size and diversity of the user base, decreasing the time and effort needed for working with NEON data, providing primary research foci through the development via the derivation process, and helping users address multidisciplinary questions. Creating derived data products also promotes personal career advancement to those involved through publications, citations, and future grant proposals. However, the creation of derived data products is a nontrivial task. Here we provide an overview of the process of creating derived data products while outlining the advantages, challenges, and major considerations. 

Abstract A two decade‐long megadrought, with likely anthropogenic causes, has impacted forest growth and mortality across the southwestern U.S. Given this event, and the future likelihood of similar climate challenges, it is important to understand how different water resources are used by semi‐arid forests in this region. Within the geographic domain of the North American Monsoon climate system, we studied seasonal water‐use in eight differentPinus ponderosamontane forests distributed across a climate gradient with varying contributions from winter and summer precipitation. We collected oxygen isotopes from precipitation, soil, and xylem water during two contrasting hydrologic years to determine how trees differentially use winter versus summer precipitation sources. Most trees switched from using snowmelt water as the primary source during the early‐summer hyper‐arid period, to monsoon rainwater during the late‐summer. However, during the low snowpack year, which represents the most common climate phenomenon during the megadrought, trees at all sites used less summer rain when compared to the higher snowpack year, demonstrating a drought‐induced antecedent influence of winter precipitation on the uptake of summer rain. A possible mechanism to explain the antecedent effect is an earlier snow disappearance during the low snowpack year weakening hydrologic connectivity within the soil profile, decreasing the soil infiltration of summer rains. However, in years with higher snowpack, the snow lasts longer, and this can improve the hydrologic connectivity within the soil profile. As a result, there is more infiltration of summer rains into the soils. This can enhance the maintenance of active shallow fine‐root biomass during the period when snowpack disappears, and monsoon rains have yet to arrive. These findings provide insight into how the seasonal interactions between major seasonal climate systems influence forest tree water use in the face of an extreme megadrought. 

Abstract The US Southwest has been entrenched in a two‐decade‐long megadrought (MD), the most severe since 800 CE, which threatens the long‐term vitality and persistence of regional montane forests. Here, we report that in the face of record low winter precipitation and increasing atmospheric aridity, seasonal activity of the North American Monsoon (NAM) climate system brings sufficient precipitation during the height of the summer to alleviate extreme tree water stress. We studied seasonally resolved, tree‐ring stable carbon isotope ratios across a 57‐year time series (1960–2017) in 17 Ponderosa pine forests distributed across the NAM geographic domain. Our study focused on the isotope dynamics of latewood (LW), which is produced in association with NAM rains. During the MD, populations growing within the core region of the NAM operated at lower intrinsic and higher evaporative water‐use efficiencies (WUE_iand WUE_E, respectively), compared to populations growing in the periphery of the NAM domain, indicating less physiological water stress in those populations with access to NAM moisture. The disparities in water‐use efficiencies in periphery populations are due to a higher atmospheric vapor pressure deficit (VPD) and reduced access to summer soil moisture. The buffering advantage of the NAM, however, is weakening. We observed that since the MD, the relationship between WUE_iand WUE_Ein forests within the core NAM domain is shifting toward a drought response similar to forests on the periphery of the NAM. After correcting for past increases in the atmospheric CO₂concentration, we were able to isolate the LW time‐series responses to climate alone. This showed that the shift in the relation between WUE_iand WUE_Ewas driven by the extreme increases in MD‐associated VPD, with little advantageous influence on stomatal conductance from increases in atmospheric CO₂concentration.