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Anthropogenic climate change is projected to drive increases in climate extremes and climate-sensitive ecosystem disturbances such as wildfire with enormous economic impacts. Understanding spatial and temporal patterns of risk to property values from climate-sensitive disturbances at national and regional scales and from multiple disturbances is urgently needed to inform risk management and policy efforts. Here, we combine models for three major climate-sensitive disturbances (i.e., wildfire, climate stress-driven tree mortality, and insect-driven tree mortality), future climate projections of these disturbances, and high-resolution property values data to quantify the spatiotemporal exposure of property values to disturbance across the contiguous United States (US). We find that property values exposed to these climate-sensitive disturbances increase sharply in future climate scenarios, particularly in existing high-risk regions of the western US, and that novel exposure risks emerge in some currently lower-risk regions such as the southeast and Great Lakes regions. Climate policy that drives emissions towards low-to-moderate climate futures avoids large increases in disturbance risk exposure compared to high emissions scenarios. Our results provide an important large-scale assessment of climate-sensitive disturbance risk to property values to help inform land management and climate adaptation efforts.

Stable isotope ratios of H (δ²H), O (δ¹⁸O), and C (δ¹³C) are linked to key biogeochemical processes of the water and carbon cycles; however, the degree to which isotope-associated processes are reflected in macroscale ecosystem flux observations remains unquantified. Here through formal information assessment, new measurements ofδ¹³C of net ecosystem exchange (NEE) as well asδ²H andδ¹⁸O of latent heat (LH) fluxes across the United States National Ecological Observation Network (NEON) are used to determine conditions under which isotope measurements are informative of environmental exchanges. We find all three isotopic datasets individually contain comparable amounts of information aboutNEEandLHfluxes as wind speed observations. Such information from isotope measurements, however, is largely unique. Generally,δ¹³C provides more information aboutLHas aridity increases or mean annual precipitation decreases.δ²H provides more information aboutLHas temperatures or mean annual precipitation decreases, and also provides more information aboutNEEas temperatures decrease. Overall, we show that the stable isotope datasets collected by NEON contribute non-trivial amounts of new information about bulk environmental fluxes useful for interpreting biogeochemical and ecohydrological processes at landscape scales. However, the utility of this new information varies with environmental conditions at continental scales. This study provides an approach for quantifying the value adding non-traditional sensing approaches to environmental monitoring sites and the patterns identified here are expected to aid in modeling and data interpretation efforts focused on constraining carbon and water cycles’ mechanisms.

Intraspecific variation in functional traits may mediate tree species' drought resistance, yet whether trait variation is due to genotype (G), environment (E), or G×E interactions remains unknown. Understanding the drivers of intraspecific trait variation and whether variation mediates drought response can improve predictions of species' response to future drought.

Climate change‐triggered forest die‐off is an increasing threat to global forests and carbon sequestration but remains extremely challenging to predict. Tree growth resilience metrics have been proposed as measurable proxies of tree susceptibility to mortality. However, it remains unclear whether tree growth resilience can improve predictions of stand‐level mortality. Here, we use an extensive tree‐ring dataset collected at ~3000 permanent forest inventory plots, spanning 13 dominant species across the US Mountain West, where forests have experienced strong drought and extensive die‐off has been observed in the past two decades, to test the hypothesis that tree growth resilience to drought can explain and improve predictions of observed stand‐level mortality. We found substantial increases in growth variability and temporal autocorrelation as well declining drought resistance and resilience for a number of species over the second half of the 20th century. Declining resilience and low tree growth were strongly associated with cross‐ and within‐species patterns of mortality. Resilience metrics had similar explicative power compared to climate and stand structure, but the covariance structure among predictors implied that the effect of tree resilience on mortality could partially be explained by stand and climate variables. We conclude that tree growth resilience offers highly valuable insights on tree physiology by integrating the effect of stressors on forest mortality but may have only moderate potential to improve large‐scale projections of forest die‐off under climate change.

Forest productivity projections remain highly uncertain, notably because underpinning physiological controls are delicate to disentangle. Transient perturbation of global climate by large volcanic eruptions provides a unique opportunity to retrospectively isolate underlying processes. Here, we use a multi‐proxy dataset of tree‐ring records distributed over the Northern Hemisphere to investigate the effect of eruptions on tree growth and photosynthesis and evaluate CMIP6 models. Tree‐ring isotope records denoted a widespread 2–4 years increase of photosynthesis following eruptions, likely as a result of diffuse light fertilization. We found evidence that enhanced photosynthesis transiently drove ring width, but the latter further exhibited a decadal anomaly that evidenced independent growth and photosynthesis responses. CMIP6 simulations reproduced overall tree growth decline but did not capture observed photosynthesis anomaly, its decoupling from tree growth or the climate sensitivities of either processes, highlighting key disconnects that deserve further attention to improve forest productivity projections under climate change.

Forests may help climate mitigation if they can store carbon for centuries

Trees are long‐lived organisms, exhibiting temporally complex growth arising from strong climatic “memory.” But conditions are becoming increasingly arid in the western USA. Using a century‐long tree‐ring network, we find altered climate memory across the entire range of a widespread western US conifer: growth is supported by precipitation falling further into the past (+15 months), while increasingly impacted by more recent temperature conditions (−8 months). Tree‐ring datasets can be biased, so we confirm altered climate memory in a second, ecologically‐sampled tree‐ring network. Predicted drought responses show trees may have also become more sensitive to repeat drought. Finally, plots near sites with relatively longer precipitation memory and shorter temperature memory had significantly lower recent mortality rates (R² = 0.61). We argue that increased drought frequency has altered climate memory, demonstrate how non‐stationarity may arise from failure to account for memory, and suggest memory length may be predictive of future tree mortality.

Climate change is stressing many forests around the globe, yet some tree species may be able to persist through acclimation and adaptation to new environmental conditions. The ability of a tree to acclimate during its lifetime through changes in physiology and functional traits, defined here as its acclimation potential, is not well known.

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Understanding the driving mechanisms behind existing patterns of vegetation hydraulic traits and community trait diversity is critical for advancing predictions of the terrestrial carbon cycle because hydraulic traits affect both ecosystem and Earth system responses to changing water availability. Here, we leverage an extensive trait database and a long-term continental forest plot network to map changes in community trait distributions and quantify “trait velocities” (the rate of change in community-weighted traits) for different regions and different forest types across the United States from 2000 to the present. We show that diversity in hydraulic traits and photosynthetic characteristics is more related to local water availability than overall species diversity. Finally, we find evidence for coordinated shifts toward communities with more drought-tolerant traits driven by tree mortality, but the magnitude of responses differs depending on forest type. The hydraulic trait distribution maps provide a publicly available platform to fundamentally advance understanding of community trait change in response to climate change and predictive abilities of mechanistic vegetation models.