Explore the vast range of titles available.

Ecosystem models have difficulty predicting plant drought responses, partially from uncertainty in the stomatal response to water deficits in soil and atmosphere. We evaluate a ‘supply–demand’ theory for water-limited stomatal behavior that avoids the typical scaffold of empirical response functions. The premise is that canopy water demand is regulated in proportion to threat to supply posed by xylem cavitation and soil drying. The theory was implemented in a trait-based soil–plant–atmosphere model. The model predicted canopy transpiration (E), canopy diffusive conductance (G), and canopy xylem pressure (P canopy) from soil water potential (P soil) and vapor pressure deficit (D). Modeled responses to D and P soil were consistent with empirical response functions, but controlling parameters were hydraulic traits rather than coefficients. Maximum hydraulic and diffusive conductances and vulnerability to loss in hydraulic conductance dictated stomatal sensitivity and hence the iso- to anisohydric spectrum of regulation. The model matched wide fluctuations in G and P canopy across nine data sets from seasonally dry tropical forest and piñon–juniper woodland with < 26% mean error. Promising initial performance suggests the theory could be useful in improving ecosystem models. Better understanding of the variation in hydraulic properties along the root–stem–leaf continuum will simplify parameterization.

Elevated forest mortality has been attributed to climate change-induced droughts, but prediction of spatial mortality patterns remains challenging. We evaluated whether introducing plant hydraulics and topographic convergence-induced soil moisture variation to land surface models (LSM) can help explain spatial patterns of mortality. A scheme predicting plant hydraulic safety loss from soil moisture was developed using field measurements and a plant physiology–hydraulics model, TREES. The scheme was upscaled to Populus tremuloides forests across Colorado, USA, using LSM-modeled and topography-mediated soil moisture, respectively. The spatial patterns of hydraulic safety loss were compared against aerial surveyed mortality. Incorporating hydraulic safety loss raised the explanatory power of mortality by 40% compared to LSM-modeled soil moisture. Topographic convergence was mostly influential in suppressing mortality in low and concave areas, explaining an additional 10% of the variations in mortality for those regions. Plant hydraulics integrated water stress along the soil–plant continuum and was more closely tied to plant physiological response to drought. In addition to the well-recognized topo-climate influence due to elevation and aspect, we found evidence that topographic convergence mediates tree mortality in certain parts of the landscape that are low and convergent, likely through influences on plant-available water.

This project was supported by the Department of Energy, Office of Science, and Pacific Northwest National Lab’s LDRD program. DDB participation was supported via NSF EF-1340624; EF-1550756, and EAR-1331408, DEB-1824796 and DEB-1833502. CG was supported by a Director’s Fellowship from the Los Alamos National Laboratory and by the Swiss National Science Foundation SNF (PZ00P3_174068). AV was supported by a fellowship from Generalitat Valenciana (BEST/2016/289) and the project Survive-2 (CGL2015-69773-C2-2-P MINECO/FEDER) from the Spanish Government. DSM was supported via NSF IOS-1450679, IOS-1444571, and IOS-1547796.

Forest mortality has been widely observed across the globe during recent episodes of drought and extreme heat events. But the future of forest mortality remains poorly understood. While the direct effects of future climate and elevated CO2 on forest mortality risk have been studied, the role of lateral subsurface water flow has rarely been considered. Here we demonstrated the fingerprint of lateral flow on the forest mortality risk of a riparian ecosystem using a coupled plant hydraulics-hydrology model prescribed with multiple Earth System Model projections of future hydroclimate. We showed that the anticipated water-saving and drought ameliorating effects of elevated CO2 on mortality risk were largely compromised when lateral hydrological processes were considered. Further, we found lateral flow reduce ecosystem sensitivity to climate variations, by removing soil water excess during wet periods and providing additional water from groundwater storage during dry periods. These findings challenge the prevailing expectation of elevated CO2 to reduce mortality risk and highlight the need to assess the effects of lateral flow exchange more explicitly moving forward with forest mortality projections.

Dynamic process-based plant models capture complex physiological response across time, carrying the potential to extend simulations out to novel environments and lend mechanistic insight to observed phenotypes. Despite the translational opportunities for varietal crop improvement that could be unlocked by linking natural genetic variation to first principles-based modeling, these models are challenging to apply to large populations of related individuals. Here we use a combination of model development, experimental evaluation, and genomic prediction in Brassica rapa L. to set the stage for future large-scale process-based modeling of intraspecific variation. We develop a new canopy growth submodel for B. rapa within the process-based model Terrestrial Regional Ecosystem Exchange Simulator (TREES), test input parameters for feasibility of direct estimation with observed phenotypes across cultivated morphotypes and indirect estimation using genomic prediction on a recombinant inbred line population, and explore model performance on an in silico population under non-stressed and mild water-stressed conditions. We find evidence that the updated whole-plant model has the capacity to distill genotype by environment interaction (G×E) into tractable components. The framework presented offers a means to link genetic variation with environment-modulated plant response and serves as a stepping stone towards large-scale prediction of unphenotyped, genetically related individuals under untested environmental scenarios.

This study compares eddy‐covariance measurements of carbon dioxide fluxes at six northern temperate and boreal peatland sites in Canada and the northern United States of America, representing both bogs and fens. The two peatland types had opposite responses of gross ecosystem photosynthesis (GEP) and ecosystem respiration (ER) to inter‐annual fluctuations in water table level. At fens, wetter conditions were correlated with lower GEP and ER, while at bogs wetter conditions were correlated with higher GEP and ER. We hypothesize that these contrasting responses are due to differences in the relative contributions of vascular plants and mosses. The coherence of our results between sites representing a range of average environmental conditions indicates ecosystem‐scale differences in resilience to hydrological changes that should be taken into account when considering the future of peatland ecosystem services such as carbon sequestration under changing environmental conditions.

Agronomists have used statistical crop models to predict yield on a genotype-by-genotype basis. Mechanistic models, based on fundamental physiological processes common across plant taxa, will ultimately enable yield prediction applicable to diverse genotypes and crops. Here, genotypic information is combined with multiple mechanistically based models to characterize photosynthetic trait differentiation among genotypes of . Infrared leaf gas exchange and chlorophyll fluorescence observations are analyzed using Bayesian methods. Three advantages of Bayesian approaches are employed: a hierarchical model structure, the testing of parameter estimates with posterior predictive checks and a multimodel complexity analysis. In all, eight models of photosynthesis are compared for fit to data and penalized for complexity using deviance information criteria (DIC) at the genotype scale. The multimodel evaluation improves the credibility of trait estimates using posterior distributions. Traits with important implications for yield in crops, including maximum rate of carboxylation ( ) and maximum rate of electron transport ( ) show genotypic differentiation. shows phenotypic diversity in causal traits with the potential for genetic enhancement of photosynthesis. This multimodel screening represents a statistically rigorous method for characterizing genotypic differences in traits with clear biophysical consequences to growth and productivity within large crop breeding populations with application across plant processes.

Scaling transpiration from trees to larger areas is a fundamental problem in ecohydrology. For scaling stand transpiration from sap flux sensors we asked if plot representativeness depended on plot size and location, the magnitude of environmental drivers, parameter needs for ecosystem models, and whether the goal was to estimate transpiration per unit ground area (EC), per unit leaf area (EL), or canopy stomatal conductance (GS). Sap flux data were collected in 108 trees with heat dissipation probes, and biometric properties were measured for 752 trees within a 1.44 ha Populus tremuloides stand along an upland‐to‐wetland gradient. EC was estimated for the stand using eight different plot sizes spanning a radius of 2.0–12.0 m. Each estimate of EC was derived from 200 plots placed randomly throughout the stand. We also derived leaf area index (L), canopy closure (PCC), and the canopy average reference stomatal conductance (GSref), which are key parameters used in modeling transpiration and evapotranspiration. With increasing plot size, EC declined monotonically but EL and GSref were largely invariant. Interplot variance of EC also declined with increasing plot size, at a rate that was independent of vapor pressure deficit. Plot representativeness was dependent on location within the stand. Scaling to the stand required three plots spanning the upland to wetland, with one to at most 10 trees instrumented for sap flux. Plots that were chosen to accurately reflect the spatial covariation of L, PCC, and GSref were most representative of the stand.

• Trees may survive prolonged droughts by shifting water uptake to reliable water sources, but it is unknown if the dominant mechanism involves activating existing roots or growing new roots during drought, or some combination of the two. • To gain mechanistic insights on this unknown, a dynamic root-hydraulic modeling framework was developed that set up a feedback between hydraulic controls over carbon allocation and the role of root growth on soil–plant hydraulics. The new model was tested using a 5 yr drought/heat field experiment on an established piñon-juniper stand with root access to bedrock groundwater. • Owing to the high carbon cost per unit root area, modeled trees initialized without adequate bedrock groundwater access experienced potentially lethal declines in water potential, while all of the experimental trees maintained nonlethal water potentials. Simulated trees were unable to grow roots rapidly enough to mediate the hydraulic stress, particularly during warm droughts. Alternatively, modeled trees initiated with root access to bedrock groundwater matched the hydraulics of the experimental trees by increasing their water uptake from bedrock groundwater when soil layers dried out. • Therefore, the modeling framework identified a critical mechanism for drought response that required trees to shift water uptake among existing roots rather than growing new roots.

• Understanding the genetic and physiological basis of abiotic stress tolerance under field conditions is key to varietal crop improvement in the face of climate variability. Here, we investigate dynamic physiological responses to water stress in silico and their relationships to genotypic variation in hydraulic traits of cotton (Gossypium hirsutum), an economically important species for renewable textile fiber production. • In conjunction with an ecophysiological process-based model, heterogeneous data (plant hydraulic traits, spatially-distributed soil texture, soil water content and canopy temperature) were used to examine hydraulic characteristics of cotton, evaluate their consequences on whole plant performance under drought, and explore potential genotype × environment effects. • Cotton was found to have R-shaped hydraulic vulnerability curves (VCs), which were consistent under drought stress initiated at flowering. Stem VCs, expressed as percent loss of conductivity, differed across genotypes, whereas root VCs did not. Simulation results demonstrated how plant physiological stress can depend on the interaction between soil properties and irrigation management, which in turn affect genotypic rankings of transpiration in a time-dependent manner. • Our study shows how a process-based modeling framework can be used to link genotypic variation in hydraulic traits to differential acclimating behaviors under drought.