Summary We modeled hydraulic stress in ponderosa pine seedlings at multiple scales to examine its influence on mortality and forest extent at the lower treeline in the northern Rockies. We combined a mechanistic ecohydrologic model with a vegetation dynamic stress index incorporating intensity, duration and frequency of hydraulic stress events, to examine mortality from loss of hydraulic conductivity. We calibrated our model using a glasshouse dry‐down experiment and tested it using in situ monitoring data on seedling mortality from reforestation efforts. We then simulated hydraulic stress and mortality in seedlings within the Bitterroot River watershed of Montana. We show that cumulative hydraulic stress, its legacy and its consequences for mortality are predictable and can be modeled at local to landscape scales. We demonstrate that topographic controls on the distribution and availability of water and energy drive spatial patterns of hydraulic stress. Low‐elevation, south‐facing, nonconvergent locations with limited upslope water subsidies experienced the highest rates of modeled mortality. Simulated mortality in seedlings from 2001 to 2015 correlated with the current distribution of forest cover near the lower treeline, suggesting that hydraulic stress limits recruitment and ultimately constrains the low‐elevation extent of conifer forests within the region.

Multiply By To obtain foot (ft) 0.3048 meter (m) mile (mi) 1.609 kilometer (km) Datum Vertical coordinate information is referenced to the North American Vertical Datum of 1988 (NAVD 88). Horizontal coordinate information is referenced to the North American Datum of 1983 (NAD 83) within the various State plane coordinate systems. Elevation, as used in this report, refers to the orthometric height, defined as a distance along a plumb line, from any objective point to the reference height of the vertical datum.

<p>Drought is among the most damaging environmental phenomena, affecting agricultural productivity, wildfire risks,  hydropower production, water quantity and quality, public health, ecosystem integrity, and recreation. Streamflow drought, where the streamflow declines below a threshold defining anomalously low flows, is one measure of hydrologic drought that can be interpreted as an integrative measure of the availability of water for specific uses. Early warning of streamflow drought onset, severity, spatial extent, and duration is needed to support improved water resource management. Streamflow drought forecasting is particularly important in the western United States where a changing climate threatens already-scarce water resources.</p><p>The U.S. Geological Survey is  applying a variety of machine learning and artificial intelligence modeling methods to predict streamflow drought in a 40-year retrospective analysis at 425 USGS stream gage locations within and surrounding the Colorado River basin. In this presentation, we briefly provide an overview of these approaches, then primarily focus on results from random forest binary classification models for streamflow drought onset and duration. For this study, streamflow drought is defined using seasonally variable streamflow exceedance thresholds developed from the Weibull distribution of observed flows or zero-flow durations from 1981-2020. We trained a large set of random forest models (n =72) , each of which predicts daily streamflow drought onset and duration probabilities at a particular forecast horizon and severity level. The models are trained using past observations of daily streamflow drought and a predictor dataset of daily hydrometeorological variables and static basin characteristics We combine the results of these models to provide holistic forecasts. In addition to streamflow drought prediction performance, we evaluate the opportunities for transitioning this modeling framework to operational forecasting and consider future directions for providing actionable forecasts to regional and national stakeholders.</p>

<p><span>More frequent hydrologic stress events associated with increasing air temperatures and declining precipitation </span><span>in the western U.S</span><span> are </span><span>resulting in more frequent and larger forest fires and</span><span> tree die offs. </span><span>It is also producing drier and hotter soils that are gradually becoming inadequate for seedlings, reducing</span><span> the probability of recruitment </span><span>and forest recovery</span> <span>and increasing the probability of permanent forest loss. </span></p><p> <span>We use a spatially-distributed ecohydrologic model (Ech2o-SPAC) to simulate the spatial distribution of soil moisture and the conditions that generate water stress in plants at high resolution and regional extents. </span><span>The model </span><span>represent</span><span>s</span><span> water stress in seedlings from a mechanistic point of view by simulating the water potential within the vascular system of seedlings. When the water potential within seedlings is very low, cavitation events </span><span>that reduce water transport </span><span>in the hydraulic column </span><span>occur, which</span><span> generate </span><span>hydraulic </span><span>stress. Time series of </span><span>cavitation-induced </span><span>low hydraulic conductivity events are combined into an index that integrates their intensity, duration and frequency to generate a dynamic stress index. The spatially distributed nature of the model permits to obtain </span><span>maps </span><span>of the dynamic stress index </span><span>that can be directly related to the </span><span>probability of </span><span>seedling mortality and its influence on the regeneration potential of the lower treeline. </span></p><p><span>The model was calibrated for </span><span><em>Pinus ponderosa</em></span><span> seedlings using a glasshouse drought experiment and was tested using in situ monitoring data on seedling</span> <span>mortality from reforestation efforts. </span><span>T</span><span>he calibrated model </span><span>was used </span><span>to simulate </span><span>water-induced</span><span> stress and mortality in seedlings </span><span>in </span><span>western Montana. Results show that low elevation, south facing, non-convergent </span><span>topographic </span><span>locations with high atmospheric demand and limited upslope water subsidies experienced the highest rates of modeled mortality. Furthermore, modeled drought mortality in seedlings from 2001-2015 correlated with the current distribution of forest cover near the lower treeline suggest that drought limits recruitment and ultimately constrains the low elevation extent of conifer forests within the region. </span><span>Extrapolation of the results show that many low elevation forest regions in the western US may have crossed climatic thresholds that prevent recruitment and will probably not recover after disturbance.</span></p>

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