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DOE OSTI2021

Climate and multiple dimensions of plant diversity regulate ecosystem carbon exchange along an elevational gradient

The impacts of warming on communities and ecosystems are predicted to be significant in mountain ecosystems because physiological processes, including rates of carbon (C) cycling, are often more temperature-sensitive in colder environments. Plant biodiversity can also influence C exchange, yet few studies integrate how biotic and abiotic factors may directly or interactively impact ecosystem Cflux. Here, we examine the link between simultaneous changes in multiple dimensions of plant diversity and peak growing season ecosystem C uptake across a climatic gradient in the Rocky Mountains, Colorado, USA. We found that taxonomic diversity (species richness), functional diversity (functional evenness), and phylogenetic diversity (mean pairwise distance) were significantly and positively related to peak growing sea-son ecosystem C uptake (i.e., net ecosystem exchange) when considered independently. However, when abiotic and biotic factors were integrated in a structural equation model, only plant phylogenetic diversity was significantly related to C uptake. In addition, we found that actual evapotranspiration (AET - a measure that integrates precipitation and temperature) affected ecosystem C exchange indirectly via its impact on the three dimensions of plant diversity that we examined. These findings highlight complex relation-ships among key measures of biodiversity and ecosystem C uptake in a rapidly warming ecosystem, and the possible mechanisms that underlie relationships between biodiversity and ecosystem functioning. They also point to the need for integrating multiple dimensions of biodiversity into studies of community and ecosystem ecology.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Chapter 6: Economic Development: Renewables, Sustainable Economies, & Carbon Offsets

This chapter reviews economic development issues and opportunities that Tribes face in the age of climate change. It includes summaries pertaining to Tribal histories and trauma, harmful federal policies and subsequent land tenure issues, and the surge of economic sovereignty through renewable energy development on Tribal lands, including carbon offset markets. Recommendations are offered to reinforce and expedite Tribal economic self-determination on Tribal lands in the context of climate change. The chapter opens with the narrative of the Ute Mountain Ute Tribe of southwest Colorado, describing how this Tribe developed a large-scale solar economic development project to reduce their Tribal energy bills and decrease their dependence on fossil fuel usage. A researched overview of Economic Development as it relates to Tribes and climate change follows these narratives, beginning with the Key Messages and Recommendation that the authors have identified.

climate change↗

DOE OSTI2024

Deep-Learning-derived Boundary Layer Height from Meteorological Data over the SGP, GOAMAZON, CACTI

The planetary boundary-layer (PBL) height (PBLH) is an important parameter for various meteorological and climate studies. This study presents a multi-structure deep neural network (DNN) model, designed to estimate PBLH by integrating morning temperature profiles with surface meteorological observations. The DNN model is developed by leveraging a rich data set of PBLH derived from long-standing radiosonde records and augmented with high-resolution micropulse lidar and Doppler lidar observations. We access the performance of the DNN with an ensemble of 10 members, each featuring distinct hidden layer structures, which collectively yield a robust 27-year PBLH data set over the Southern Great Plains from 1994 to 2020. The influence of various meteorological factors on PBLH is rigorously analyzed through the importance test. Moreover, the DNN model's accuracy is evaluated against radiosonde observations and juxtaposed with conventional remote-sensing methodologies, including Doppler lidar, ceilometer, Raman lidar, and micropulse lidar. The DNN model exhibits reliable performance across diverse conditions and demonstrates lower biases relative to remote-sensing methods. In addition, the DNN model, originally trained over a plain region, demonstrates remarkable adaptability when applied to the heterogeneous terrains and climates encountered during the GoAmazon (tropical rainforest) and CACTI (middle-latitude mountain) campaigns. These findings demonstrate the effectiveness of deep learning models in estimating PBLH, enhancing our understanding of boundary-layer dynamics with implications for enhancing the representation of PBL in weather forecasting and climate modeling.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Arbuscular mycorrhizal fungal response to fire and urbanization in the Great Smoky Mountains National Park

Wildfires are increasing in frequency and intensity as drier and warmer climates increase plant detrital fuel loads. At the same time, increases in urbanization position 9% of fire-prone land within the United States at the wildland–urban interface. While rarely studied, the compounded effects of urbanization and wildfires may have unknown synergistically negative effects on ecosystems. Previous studies at the wildland–urban interface often focus on aboveground plant communities, but belowground ecosystems may also be affected by this double disturbance. In particular, it is unclear how much fire and urbanization independently or interactively affect nutritional symbioses such as those between arbuscular mycorrhizal (AM) fungi and the majority of terrestrial plants. In November 2016, extreme drought conditions and long-term fire suppression combined to create a wildfire within the Great Smoky Mountains National Park and the neighboring exurban city of Gatlinburg, TN. To understand how the double disturbance of urbanization and fire affected AM fungal communities, we collected fine roots from the 5 dominant understory species in September 2018 at each of 18 sites spanning 3 burn severities in both exurban and natural sites. Despite large variation in burn severity, plant species identity had the largest influence on AM fungi. AM fungal colonization, richness, and composition all varied most among plant species. Fire and urbanization did influence some AM fungal metrics; colonization was lower in burned sites and composition was more variable among exurban locations. There were no interactions among burn severity and urbanization on AM fungi. Our results point to the large influence of plant species identity structuring this obligate nutritional symbiosis regardless of disturbance regime. Therefore, the majority of AM fungal taxa may be buffered from fire-induced ecosystem changes if plant community composition largely remains intact, plant species life history traits allow for AM fungal persistence after fire disturbance, and/or nearby undisturbed habitat can act as an inoculum source for recolonization following fires. Thus, it is critical to maintain natural, undisturbed habitats interspersed within the wildland–urban interface.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Constraining induced seismicity hazard on the Neck of the Desert fault for the proposed Iron Mountain, Utah carbon sequestration project

As significantly more focus is placed on carbon sequestration as a means to help mitigate the progression of climate change, the need to adequately characterize an injection target for its induced seismicity potential becomes more apparent. In the Iron Mountain project in Southern Utah, a single fault is identified in the Neck of the Desert near Iron Mountain. The dip of the fault is unknown, and the geomechanical stability of the fault (i.e., distribution of Coulomb failure functions (CFFs)) is highly dependent upon the dip. For some dips, such as 15 degrees, the hazard from injection is low. For other dips, such as 75 degrees, the hazard is high. Another key consideration is the depth of penetration of the fault. Should the fault not penetrate the stress and pressure perturbed region from injection, it will not be induced to fail. Thus, understanding the dip and the depth of penetration of the fault will greatly improve our understanding of the likelihood of inducing an earthquake.

58 GEOSCIENCES↗

NASA NTRS1981

The influence of initial and surface boundary conditions on a model-generated January climatology

The influence on a model-generated January climate of various surface boundary conditions, as well as initial conditions, was studied by using the GISS coarse-mesh climate model. Four experiments - two with water planets, one with flat continents, and one with mountains - were used to investigate the effects of initial conditions, and the thermal and dynamical effects of the surface on the model generated-climate. However, climatological mean zonal-symmetric sea surface temperature is used in all four runs over the model oceans. Moreover, zero ground wetness and uniform ground albedo except for snow are used in the last experiments.

Wu, K. F.↗

DOE OSTI2021

Root Influences on Mobilization and Export of Mineral-bound Soil Organic Matter

Biogeochemical cycles within mountainous watersheds are key regulators of ecosystem carbon storage and downstream nutrient loadings, and they have shown to be particularly vulnerable to climate change impacts. Increasing temperature and persistent droughts have already dramatically changed vegetation cover across the mountainous western US, with unknown consequences for soil carbon and nutrient cycles belowground. What remains elusive is to what extent associated changes in root-soil interactions may mobilize the vast pool of organic matter (OM) that has been stabilized by associations with minerals for centuries or millennia. Although plant root-driven OM mobilization from minerals may be a central control on carbon loss and nutrient export, such mechanisms are currently missing from conceptual and numerical models. The overall objective of this Exploratory Project is to identify the biogeochemical mechanisms by which roots destabilize mineral-associated organic matter (MAOM) and the cumulative impact on carbon and nutrient fate. To accomplish this goal, we integrated well-controlled laboratory experiments with in-field measurements and a scalable modeling approach. First, we conducted model system experiments to assess the vulnerability of MAOM to exudate-mediated mechanisms. Our results show that common root exudates effectively destabilize MAOM not only through direct, ligand-driven mobilization mechanisms, but also indirect, microbially-mediated mechanisms relying on secondary metabolites and enzymes. We further found that OM bound to poorly crystalline Fe and Al (hydr)oxides is more vulnerable to exudate-induced destabilization than OM bound to more crystalline phases, particularly in response to direct, ligand-promoted mechanisms. These findings demonstrate that the stability of MAOM is not just a function of their inherent properties, but also will depend in large parts on the ability of plant roots and microbes to produce exudates capable of triggering suitable mobilization mechanisms. We further employed a well-controlled rhizobox approach, combining advanced microsensor and mass spectrometry techniques, to resolve spatiotemporal variations in the composition and availability of exudates along single growing roots of grasses. Our results show that the composition of functionally relevant exudate compounds varies at extremely short time scales, seemingly shifting from ligands such as aromatic acids around root tips to less reactive metabolites such as amino acids around mature root segments. These results suggest a prevalence of direct MAOM mobilization mechanisms around the root tip, while indirect MAOM mobilization strategies may dominate around more mature root segments. Additionally, we utilized microsensor measurements in rhizoboxes to parameterize a rhizosphere (hydro)biogeochemistry reactive transport model (eSTOMP-ROOTS). The resulting model was used to assess how root exudations affects the stability of MAOM. Model simulations show that diel pulses of root exudation are strong enough to cause oscillations in biogeochemical conditions—particularly in pH, oxygen concentrations, and microbial activity— that repeatedly disrupt MAOM. Finally, we assessed field-scale impacts of root-driven MAOM destabilization over short and long time scales. A combination of in-field incubations and field-based characterizations showed that MAOM may not only be vulnerable to seasonal variations in root activity, but also to root-driven weathering over pedogenic time scales. In sum, results from our Exploratory Award highlight the strong control plant roots exert on MAOM mobilization and, thus, on the potential for carbon and nutrient export from watersheds.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Differential Impact of Climate Change on the Hydropower Economies of Karakoram and Himalayan River Basins

Water stored in the form of snow and glaciers in the High Mountain Asia (HMA) region regulates the water supply, and resultant water-based economies, that support the livelihoods of millions of people. Trends in the seasonal and long-term melting of snow and glaciers, governed by initial ice reserves, meteorological factors and geographic features, vary across sub-basins in the HMA region. We examined the economic impacts of climate-led changes in river flow in two drainage basins, one each from the Karakoram and Central Himalaya region. We used an integrated assessment framework to estimate the changes in economic value of the hydropower generation from hydropower plants on rivers fed by snow and glacier melt in the two sub-basins. The framework, developed under a NASA High Mountain Asia project, coupled biophysical models (a suite of climate models, snow/glacier-hydrology, and hydropower model) with economic analysis. We compared the differences in estimated river flow over historic and future time using the water balance model in sixteen scenarios (eight climate models and two emissions scenarios) for rivers upstream of hydropower plants in each sub-basin. Using the hydropower model we developed, we estimated the changes in hydropower generation at the Naltar IV hydropower plant, with an 18 MW capacity, located in Hunza, Karakoram, and the Trishuli hydropower plant, with a 19.6 MW capacity, in Trishuli, Central Himalaya. When compared to their baselines, the estimated impact of climate change and temporal variability were higher for the Naltar plant than for the Trishuli plant. Our sensitivity analysis shows that hydropower plants with water storage facilities help reduce the impact of changes, but the estimated impacts are higher for the higher capacity plants. This study provides an example of the differential impacts of climate change on hydropower plants located in rivers fed by varying amounts of snow and glacier melt at different decades in this century. This type of integrated assessment of climate change impact will support the scientific understanding of hydrologic flow and its impacts on a hydropower economy under various climate scenarios, as well as generate information about water resource management in a changing climate.

climate change↗

DOE OSTI2024

Anticipating how rain-on-snow events will change through the 21st century: lessons from the 1997 new year’s flood event

The California-Nevada 1997 New Year’s flood was an atmospheric river (AR)-driven rain-on-snow (RoS) event and remains the costliest in their history. The joint occurrence of saturated soils, rainfall, and snowmelt generated inundation throughout northern California-Nevada. Although AR RoS events are projected to occur more frequently with climate change, the warming sensitivity of their flood drivers across scales remains understudied. We leverage the regionally refined mesh capabilities of the Energy Exascale Earth System Model (RRM-E3SM) to recreate the 1997 New Year’s flood with horizontal grid spacings of 3.5 km across California, with forecast lead times of up to 4 days, and across six warming levels ranging from pre-industrial conditions to +3.5° C. We describe the sensitivity of the flood drivers to warming including AR duration and intensity, precipitation phase, intensity and efficiency, snowpack mass and energy changes, and runoff efficiency. Our findings indicate current levels of climate change negligibly influence the flood drivers. At warming levels ≥ 1.7° C, AR hazard potential increases, snowpack nonlinearly decreases, antecedent soil moisture decreases (except where the snowline retreats), and runoff decreases (except in the southern Sierra Nevada where antecedent snowpack persists). Storm total precipitation increases, but at rates below warming-induced increases in saturation-specific humidity. Warming intensifies short-duration, high-intensity rainfall, particularly where snowfall-to-rainfall transitions occur. This study highlights the nonlinear tradeoffs in 21st-century RoS flood hazards with warming and provides water management and infrastructure investment adaptation considerations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Temperature, Humidity, and Time-Lapse Video Data from Yosemite National Park, Water Year 2024

This dataset contains time-lapse imagery and distributed measurements of air temperature, relative humidity, dew point, and soil temperature across Yosemite National Park from October 2023 to September 2024. Instruments were deployed at 10 sites in two cross-valley transects as part of the DOE Grant: Seasonal Cycles Unravel Mysteries of Missing Mountain Water organized by Jessica Lundquist (University of Washington), Rosemary Carroll (Desert Research Institute), and Ethan Gutmann (National Center for Atmospheric Research). The data are intended to support hydrologic modeling efforts to better resolve the fate of mountain water, and are published to support studies of surface climate or hydrologic processes in complex terrain. Measurements were collected with low-cost data loggers installed 2 m high on evergreen trees or buried just below the soil surface. A time-lapse camera at one site captures valley-scale seasonal snow cover variability.Dataset files are organized by site and variable (air measurements, ground measurements, or time-lapse video). Air and ground measurements are packaged in LoggerData.zip, and time-lapse imagery is compiled into a short video stored in TimelapseVideos.zip. File-level metadata contains details for each file included in the dataset. A data dictionary provides units and descriptions for column or row names in all files. The locations metadata file describes site characteristics, locations, and associated GPS methods.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1996

Estimating Canopy Water Content of Chaparral Shrubs Using Optical Methods

California chaparral ecosystems are exceptionally fire adapted and typically are subject to wildfire at decadal to century frequencies. The hot dry Mediterranean climate summers and the chaparral communities of the Santa Monica Mountains make wildfire one of the most serious economic and life-threatening natural disasters faced by the region. Additionally, the steep fire-burned hillsides are subject to erosion, slumpage, and mud slides during the winter rains. The Santa Monica Mountain Zone (SMMZ) is a 104,000 ha eastwest trending range with 607 m of vertical relief and located in the center of the greater Los Angeles region. A series of fires in the fall of 1993 burned from Simi Valley to Santa Monica within a few hours. Developing techniques to monitor fire hazard and predict the spread of fire is of major concern to the region. One key factor in the susceptibility to fire is the water content of the vegetation canopy. The development of imaging spectrometry and remote sensing techniques may constitute a tool to provide this information.

Ustin, Susan L.↗

NASA NTRS2005

Salt Kinematics and InSAR

As part of a long-term attempt to learn how the climatic and tectonic signal interact to shape a steady state mountain monitored displacement of a markers in SE termination and also near the summit of a small viscous salt fountain extruding onto the Central plateau of Iran. The marker displacements relate to the first InSAR interferograms of salt extrusion (980913 to 990620) calculated Earth tides, winds, air pressures and temperatures. In the first documented staking exercise, hammered wooden stakes vertically through the surgical marl (c. 1 Ocm deep) onto the top of crystalline salt. These stakes installed in an irregular array elongate E-W along the c.50 m high cliff marking the effective SE terminus of the glacier at Qum Kuh(Centra1 Iran) ,just to the E of a NE trending river cliff about 40 m high. We merely measured the distances between pairs of stakes with known azimuth about 2 m apart to calculate sub horizontal strain in a small part of Qum Kuh. Stakes moved and micro strains for up to 46 pairs of stakes (p strain= ((lengthl-length2)/1engthl) x 10-1) was calculated for each seven stake epochs and plotted against their azimuth on simplified array maps. The data fit well the sine curves cxpected of the maximum and minimum strain ellipses. The first documented stakes located on the SE where the InSAR image show -1 1 to 0 mm pink to purple, 0 to lOmm purple to blue, and show high activity of salt in low activity area of the InSAR image (980913 to 990620).Short term micro strains of stake tie lines record anisotropic expansions due to heating and contraction due to cooling. All epochs changed between 7 to 1 17 days (990928 to000 1 16), showed 200 to 400 micro strain lengthening and shortening. The contraction and extension existed in each epoch, but the final strain was extension in E-W in Epoch land 6, contraction in E-W direction during epochs 2-3-4-5 and 7. The second pair of stakes hammered about 20 cm deep into the deep soils(more than 1 m) , near summit, where the colors change between 19 to 29mm in InSAR image(9809 13 to 990620). Additional information is included in the original abstract.

Aftabi, Pedarm↗

NASA NTRS1996

Estimating Canopy Water Content of Chaparral Shrubs Using Optical Methods

ecosystems↗

NASA NTRS2019

Daily evaluation of 26 precipitation datasets using Stage-IV gauge-radar data for the CONUS

New precipitation (P) datasets are released regularly, following innovations in weather forecasting models, satellite retrieval methods, and multi-source merging techniques. Using the conterminous US as a case study, we evaluated the performance of 26 gridded (sub-)daily P datasets to obtain insight into the merit of these innovations. The evaluation was performed at a daily timescale for the period 2008–2017 using the Kling–Gupta efficiency (KGE), a performance metric combining correlation, bias, and variability. As a reference, we used the high-resolution (4 km) Stage-IV gauge-radar P dataset. Among the three KGE components, the P datasets performed worst overall in terms of correlation (related to event identification). In terms of improving KGE scores for these datasets, improved P totals (affecting the bias score) and improved distribution of P intensity (affecting the variability score) are of secondary importance. Among the 11 gauge-corrected P datasets, the best overall performance was obtained by MSWEP V2.2, underscoring the importance of applying daily gauge corrections and accounting for gauge reporting times. Several uncorrected P datasets outperformed gauge-corrected ones. Among the 15 uncorrected P datasets, the best performance was obtained by the ERA5-HRES fourth-generation reanalysis, reflecting the significant advances in earth system modeling during the last decade. The (re)analyses generally performed better in winter than in summer, while the opposite was the case for the satellite-based datasets. IMERGHH V05 performed substantially better than TMPA-3B42RT V7, attributable to the many improvements implemented in the IMERG satellite P retrieval algorithm. IMERGHH V05 outperformed ERA5-HRES in regions dominated by convective storms, while the opposite was observed in regions of complex terrain. The ERA5-EDA ensemble average exhibited higher correlations than the ERA5-HRES deterministic run, highlighting the value of ensemble modeling. The WRF regional convection-permitting climate model showed considerably more accurate P totals over the mountainous west and performed best among the uncorrected datasets in terms of variability, suggesting there is merit in using high-resolution models to obtain climatological P statistics. Our findings provide some guidance to choose the most suitable P dataset for a particular application.

Hylke E. Beck↗

NASA NTRS1996

Geomorphic Processes and Remote Sensing Signatures of Alluvial Fans in the Kun Lun Mountains, China

Remote sensing techniques may be used to assist in regional mapping of geomorphic units related to past climate changes through their sensitivity to roughness and composition. Radar images from the Spaceborne Radar Laboratory and visible-wavelength images from the French SPOT satellite were used to determine remote sensing signatures of alluvial fan units for an area in the Kun Lun Mountains of northwestern China.

remote↗

DOE OSTI2025

East Antarctic Ice Sheet variability in the central Transantarctic Mountains since the mid Miocene

The response of the East Antarctic Ice Sheet to warmer-than-present climate conditions has direct implications for projections of future sea level, ocean circulation, and global radiative forcing. Nonetheless, it remains uncertain whether the ice sheet is likely to undergo net loss due to amplified melting coupled with dynamic instabilities or whether such losses will be balanced, or even offset, by enhanced accumulation under a higher-precipitation regime. The glacial depositional record from the central Transantarctic Mountains (TAM) provides a robust geologic means to reconstruct the past behaviour of the East Antarctic Ice Sheet, including during periods thought to have been warmer than today, such as the mid-Pliocene Warm Period (~3.3–3.0 Ma). This study describes a new surface-exposure-dated moraine record from Otway Massif in the central TAM spanning the last ~9 Myr and synthesises these data in the context of previously published moraine chronologies constrained with cosmogenic nuclides. The resulting record, although fragmentary, represents the majority of direct and unambiguous terrestrial evidence for the existence and size of the East Antarctic Ice Sheet during the last 14 Myr, and it thus provides new insight into the long-term relationship between the ice sheet and global climate. At face value, the existing TAM moraine record does not exhibit a clear signature of the mid-Pliocene Warm Period, thus precluding a definitive verdict on the East Antarctic Ice Sheet's response to this event. In contrast, an apparent hiatus in moraine deposition both at Otway Massif and the neighbouring Roberts Massif suggests that the ice sheet surface in the central TAM was potentially lower than present during the late Miocene and earliest Pliocene.

58 GEOSCIENCES↗

DOE OSTI2021

Response of U.S. West Coast Mountain Snowpack to Local Sea Surface Temperature Perturbations: Insights from Numerical Modeling and Machine Learning

Sea surface temperature (SST) significantly modulates the precipitation and temperature over land, with important consequences on land surface processes such as snowpack. Compared to the impact of remote SST, the effect of nearshore/local SST is less well understood. In this study, the impact of local SST on the mountain snowpack of the U.S. West Coast is investigated using two 6-km regional climate simulations driven by the same lateral boundary conditions but with time-varying versus time-invariant and warmer local SSTs during 2003–15. Results show that local SST warming leads to warmer winter with more precipitation over the mountains. Meanwhile, the removal of SST temporal variability results in reduced temperature variability but increased precipitation variability. As a result, winter snow accumulation decreases by ~200 mm per season in the Cascade Mountains in the north but increases by ~100 mm per season in the Sierra Nevada in the south. Such a dipole response results from the competing effects of precipitation and temperature change at different elevations and are amplified by the enhanced atmospheric river moisture transport. To further delineate the relative contributions of different meteorological factors to the snowpack response, two neural network models were developed to predict the snow behaviors at seasonal and monthly scales. These models reveal the dominant influence of the total amount and the average temperature of precipitation on the snowpack response. Furthermore, these findings highlight the sensitivity of mountain snowpack to local SST in the western United States and underscore the importance of local SST and atmospheric rives to accurate snowpack estimations for water management.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Climate change drives convergent evolution of root traits on Sky Island climate relicts

Roots are essential to the strategies plants use to survive in variable environments, yet we know little of how they vary within species. Experimental conditions demonstrate that intraspecific plant root traits respond strongly to variation in the environment; however, it is unclear when these responses can be characterized as evolution in response to selective pressures of climate change over many generations. Sky Islands are model, natural climate relict ecosystems to examine climate-change driven evolution. Utilizing a common garden with replicate genotypes of Populus angustifolia (Narrowleaf cottonwood) from six Sky Island (SI) populations and nine adjacent Mountain Chain (MC) populations across three genetic provenances, we hypothesized that SI root traits have diverged due to historical isolation in warmer, drier climates. When grown in common conditions, populations originating on SI’s showed convergent evolution across three distinct genetic provenances, which was characterized by 44.16% decreased total root length, 42.64% decreased average root volume, 43.31% decreased root surface area, and significantly less root trait variation, relative to adjacent mountain chains. Convergent evolution of root traits from trees originating on SI’s is correlated with changes in mean annual precipitation and potential evapotranspiration in the field over the past ~ 125 years. These results demonstrate a consistent pattern in root trait evolution at the landscape scale and the role of climate on the evolution of root traits in a genetic and geographic context relevant to climate change.

Convergent evolution↗