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Abstract Understanding how vegetation responds to drought is fundamental for understanding the broader implications of climate change on foundation tree species that support high biodiversity. Leveraging remote sensing technology provides a unique vantage point to explore these responses across and within species.We investigated interspecific drought responses of twoPopulusspecies (P.fremontii,P.angustifolia) and their naturally occurring hybrids using leaf‐level visible through shortwave infrared (VSWIR; 400–2500 nm) reflectance. AsF₁hybrids backcross with either species, resulting in a range of backcross genotypes, we heretofore refer to the two species and their hybrids collectively as ‘cross types’. We additionally explored intraspecific variation inP. fremontiidrought response at the leaf and canopy levels using reflectance data and thermal unmanned aerial vehicle (UAV) imagery. We employed several analyses to assess genotype‐by‐environment (G × E) interactions concerning drought, including principal component analysis, support vector machine and spectral similarity index.Five key findings emerged: (1) Spectra of all three cross types shifted significantly in response to drought. The magnitude of these reaction norms can be ranked from hybrids>P. fremontii>P. angustifolia, suggesting differential variation in response to drought; (2) Spectral space among cross types constricted under drought, indicating spectral—and phenotypic—convergence; (3) Experimentally, populations ofP. fremontiifrom cool regions had different responses to drought than populations from warm regions, with source population mean annual temperature driving the magnitude and direction of change in VSWIR reflectance. (4) UAV thermal imagery revealed that watered, warm‐adapted populations maintained lower leaf temperatures and retained more leaves than cool‐adapted populations, but differences in leaf retention decreased when droughted. (5) These findings are consistent with patterns of local adaptation to drought and temperature stress, demonstrating the ability of leaf spectra to detect ecological and evolutionary responses to drought as a function of adaptation to different environments.Synthesis.Leaf‐level spectroscopy and canopy‐level UAV thermal data captured inter‐ and intraspecific responses to water stress in cottonwoods, which are widely distributed in arid environments. This study demonstrates the potential of remote sensing to monitor and predict the impacts of drought on scales varying from leaves to landscapes. 

Abstract Recently classified as a unique species by the IUCN, African forest elephants (Loxodonta cyclotis) are critically endangered due to severe poaching. With limited knowledge about their ecological role due to the dense tropical forests they inhabit in central Africa, it is unclear how the Afrotropics are influenced by elephants. Although their role as seed dispersers is well known, they may also drive large‐scale processes that determine forest structure through the creation of elephant trails and browsing the understory, allowing larger, carbon‐dense trees to succeed. Multiple scales of lidar were collected by NASA in Lopé National Park, Gabon from 2015 to 2022. Utilizing two airborne lidar datasets in an African forest elephant stronghold, detailed canopy structural information was used in conjunction with elephant trail data to determine how forest structure varies on and off trails. Forest along elephant trails displayed different structural characteristics than forested areas off trails, with lower canopy height, canopy cover, and different vertical distribution of plant density. Less plant area density was found on trails at 1 m in height, while more vegetation was found at 12 m, compared to off trail locations. Trails in forest areas with previous logging history had lower plant area in the top of the canopy. Forest elephants can be considered as “logging light” ecosystem engineers, affecting canopy structure through browsing and movement. Both airborne lidar scales were able to capture elephant impact along trails, with the high‐resolution discrete return lidar performing higher than waveform lidar. 

Plants respond to rapid environmental change in ways that depend on both their genetic identity and their phenotypic plasticity, impacting their survival as well as associated ecosystems. However, genetic and environmental effects on phenotype are difficult to quantify across large spatial scales and through time. Leaf hyperspectral reflectance offers a potentially robust approach to map these effects from local to landscape levels. Using a handheld field spectrometer, we analyzed leaf‐level hyperspectral reflectance of the foundation tree species Populus fremontii in wild populations and in three 6‐year‐old experimental common gardens spanning a steep climatic gradient. First, we show that genetic variation among populations and among clonal genotypes is detectable with leaf spectra, using both multivariate and univariate approaches. Spectra predicted population identity with 100% accuracy among trees in the wild, 87%–98% accuracy within a common garden, and 86% accuracy across different environments. Multiple spectral indices of plant health had significant heritability, with genotype accounting for 10%–23% of spectral variation within populations and 14%–48% of the variation across all populations. Second, we found gene by environment interactions leading to population‐specific shifts in the spectral phenotype across common garden environments. Spectral indices indicate that genetically divergent populations made unique adjustments to their chlorophyll and water content in response to the same environmental stresses, so that detecting genetic identity is critical to predicting tree response to change. Third, spectral indicators of greenness and photosynthetic efficiency decreased when populations were transferred to growing environments with higher mean annual maximum temperatures relative to home conditions. This result suggests altered physiological strategies further from the conditions to which plants are locally adapted. Transfers to cooler environments had fewer negative effects, demonstrating that plant spectra show directionality in plant performance adjustments. Thus, leaf reflectance data can detect both local adaptation and plastic shifts in plant physiology, informing strategic restoration and conservation decisions by enabling high resolution tracking of genetic and phenotypic changes in response to climate change. 

Increasing heatwaves are threatening forest ecosystems globally. Leaf thermal regulation and tolerance are important for plant survival during heatwaves, though the interaction between these processes and water availability is unclear. Genotypes of the widely distributed foundation tree speciesPopulus fremontiiwere studied in a controlled common garden during a record summer heatwave—where air temperature exceeded 48 °C. When water was not limiting, all genotypes cooled leaves 2 to 5 °C below air temperatures. Homeothermic cooling was disrupted for weeks following a 72-h reduction in soil water, resulting in leaf temperatures rising 3 °C above air temperature and 1.3 °C above leaf thresholds for physiological damage, despite the water stress having little effect on leaf water potentials. Tradeoffs between leaf thermal safety and hydraulic safety emerged but, regardless of water use strategy, all genotypes experienced significant leaf mortality following water stress. Genotypes from warmer climates showed greater leaf cooling and less leaf mortality after water stress in comparison with genotypes from cooler climates. These results illustrate how brief soil water limitation disrupts leaf thermal regulation and potentially compromises plant survival during extreme heatwaves, thus providing insight into future scenarios in which ecosystems will be challenged with extreme heat and unreliable soil water access. 

Leaf-level reflectance data from multiple genotypes nested within multiple populations each grown in 2-3 common gardens. Both population provenances and common garden locations span the climate gradient of Arizona, USA. 

Summary Populus fremontiiis among the most dominant, and ecologically important riparian tree species in the western United States and can thrive in hyper‐arid riparian corridors. Yet,P. fremontiiforests have rapidly declined over the last decade, particularly in places where temperatures sometimes exceed 50°C.We evaluated high temperature tolerance of leaf metabolism, leaf thermoregulation, and leaf hydraulic function in eightP. fremontiipopulations spanning a 5.3°C mean annual temperature gradient in a well‐watered common garden, and at source locations throughout the lower Colorado River Basin.Two major results emerged. First, despite having an exceptionally highT_crit(the temperature at which Photosystem II is disrupted) relative to other tree taxa, recent heat waves exceededT_crit, requiring evaporative leaf cooling to maintain leaf‐to‐air thermal safety margins. Second, in midsummer, genotypes from the warmest locations maintained lower midday leaf temperatures, a higher midday stomatal conductance, and maintained turgor pressure at lower water potentials than genotypes from more temperate locations.Taken together, results suggest that under well‐watered conditions,P. fremontiican regulate leaf temperature belowT_critalong the warm edge of its distribution. Nevertheless, reduced Colorado River flows threaten to lower water tables below levels needed for evaporative cooling during episodic heat waves. 

Abstract. Accurate assessment of leaf functional traits is crucial for a diverse range of applications from crop phenotyping to parameterizing global climate models. Leaf reflectance spectroscopy offers a promising avenue to advance ecological and agricultural research by complementing traditional, time-consuming gas exchange measurements. However, the development of robust hyperspectral models for predicting leaf photosynthetic capacity and associated traits from reflectance data has been hindered by limited data availability across species and environments. Here we introduce the Global Spectra-Trait Initiative (GSTI), a collaborative repository of paired leaf hyperspectral and gas exchange measurements from diverse ecosystems. The GSTI repository currently encompasses over 7500 observations from 397 species and 41 sites gathered from 36 published and unpublished studies, thereby offering a key resource for developing and validating hyperspectral models of leaf photosynthetic capacity. The GSTI database is developed on GitHub (https://github.com/plantphys/gsti, last access: 4 January 2026) and published to ESS-DIVE https://doi.org/10.15485/2530733, Lamour et al., 2025). It includes gas exchange data, derived photosynthetic parameters, and key leaf traits often associated with traditional gas exchange measurements such as leaf mass per area and leaf elemental composition. By providing a standardized repository for data sharing and analysis, we present a critical step towards creating hyperspectral models for predicting photosynthetic traits and associated leaf traits for terrestrial plants. 

Abstract Background and AimsTropical forests exchange more carbon dioxide (CO2) with the atmosphere than any other terrestrial biome. Yet, uncertainty in the projected carbon balance over the next century is roughly three times greater for the tropics than other for ecosystems. Our limited knowledge of tropical plant physiological responses, including photosynthetic, to climate change is a substantial source of uncertainty in our ability to forecast the global terrestrial carbon sink. MethodsWe used a meta-analytic approach, focusing on tropical photosynthetic temperature responses, to address this knowledge gap. Our dataset, gleaned from 18 independent studies, included leaf-level light-saturated photosynthetic (Asat) temperature responses from 108 woody species, with additional temperature parameters (35 species) and rates (250 species) of both maximum rates of electron transport (Jmax) and Rubisco carboxylation (Vcmax). We investigated how these parameters responded to mean annual temperature (MAT), temperature variability, aridity and elevation, as well as also how responses differed among successional strategy, leaf habit and light environment. Key ResultsOptimum temperatures for Asat (ToptA) and Jmax (ToptJ) increased with MAT but not for Vcmax (ToptV). Although photosynthetic rates were higher for ‘light’ than ‘shaded’ leaves, light conditions did not generate differences in temperature response parameters. ToptA did not differ with successional strategy, but early successional species had ~4 °C wider thermal niches than mid/late species. Semi-deciduous species had ~1 °C higher ToptA than broadleaf evergreen species. Most global modelling efforts consider all tropical forests as a single ‘broadleaf evergreen’ functional type, but our data show that tropical species with different leaf habits display distinct temperature responses that should be included in modelling efforts. ConclusionsThis novel research will inform modelling efforts to quantify tropical ecosystem carbon cycling and provide more accurate representations of how these key ecosystems will respond to altered temperature patterns in the face of climate warming.