Photosystem II (PSII) is among the most thermally sensitive components of photosynthesis, and emerging evidence suggests that plants in diverse biomes face an increasing risk of PSII damage under future climate change. However, uncertainties in the distribution and drivers of PSII thermal tolerance (T-crit) limit our ability to predict thermal risk in plant communities across spatial scales. Here, we evaluate whether intraspecific variation in T-crit corresponds to leaf reflectance spectra (400-2,500 nm) to identify mechanisms associated with T-crit in field conditions and assess the potential of its estimation using remote sensing platforms. We measured T-crit using temperature response curves of minimal fluorescence (F-o) along with corresponding leaf reflectance spectra in two foundation tree species: Populus fremontii (US Southwest) and Metrosideros polymorpha (Hawai'i). P. fremontii was sampled under both moderate (<40 degrees C) and extreme (>45 degrees C) heat. Consistent spectral signatures of T-crit emerged across species and sampling conditions, with the strongest signatures in P. fremontii under extreme heat. In P. fremontii, spectra captured up to roughly half of T-crit variation and allowed T-crit estimation (R-2 = 0.24-0.30; RMSE < 1.0 degrees C) and classification of high-versus low-T-crit (71%-77% accuracy). Across both species, T-crit tended to increase with spectral indices reflecting higher chlorophyll content and lower carotenoids, nonphotochemical quenching, and leaf water content. These findings suggest that variation in PSII thermal tolerance is linked to fundamental biochemical properties of leaves, which are reflected in their optical traits. As climate extremes intensify, spectral screening and scaling of T-crit via remote sensing may support improved conservation, management, and risk assessment in vulnerable ecosystems.

Forests in the Southwestern United States are experiencing increasing stress as climate extremes intensify, yet many monitoring systems still emphasize abrupt canopy loss rather than gradual physiological and structural decline. Here we introduce EcoTrend, a multi-sensor framework that quantifies intra-annual and inter-annual trend-slope change at 10\,m resolution by integrating Sentinel-2 optical greenness (NDVI) and Sentinel-1 radar backscatter metrics (RVI). Applied across the main forested areas in Arizona for 2022–2024, EcoTrend reveals a pronounced decline during the 2022 megadrought, widespread recovery in 2023 following exceptional winter precipitation, and a heterogeneous stabilization phase in 2024. Comparisons with Hansen Global Forest Change, TWIG fuel-treatment records, and USFS aerial and ground surveys (AGS) show that EcoTrend captures early-stage decline and partial canopy degradation that are often missed by traditional loss-focused products and coarse survey delineations. These results highlight EcoTrend’s potential as an operational early-warning approach for mapping emerging stress and tracking fine-scale recovery trajectories to support adaptive forest management under accelerating climate variability.

BACKGROUND AND AIMS:Tropical 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. METHODS:We 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 RESULTS:Optimum 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. CONCLUSIONS:This 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.

Scaling theory allows us to predict animal impacts on seed distribution, zoogeochemistry, pathogen movement, and vegetation structure over space and time. Here we have both reviewed this literature and suggested future directions to scale such work over space and time and apply it to such disparate fields as ecosystem ecology, paleontology and remote sensing. This chapter is accepted in the forthcoming volume entitled “Scaling in Biology: A New Synthesis (In Press) SFI Press, Editors: Enquist, Kempes, O’Connor.”

Globally, vegetation biodiversity is expected to decline as the rate of plant adaptation struggles to keep pace with rising temperatures. To support conservation efforts through remote sensing, we disentangled the nested effects of genetic and environmental influences on reflectance spectra, leveraging spectroscopy to assess plant adaptations to temperature. Specifically, we quantified the relative effect of plasticity and heritability on Populus fremontii (Fremont cottonwood) leaf reflectance using clonal replicates propagated from 16 populations and grown across three common gardens spanning a mean annual temperature gradient representing the thermal range of P. fremontii. We used variance partitioning to decompose phenotypic variation expressed in the leaf spectra into genotypic and environmental components to estimate broad-sense heritability. Heritability was strongly expressed in the spectral red edge ( 680–750 nm) and shortwave infrared ( 1400–3000 nm), though the heritability peak in the red edge was sensitive to extreme temperatures. By comparing distances of group centroids in principal component space, we determined that P. fremontii intraspecific spectral variation was shaped by the interaction between common garden site conditions and source population. Support vector machine models indicated pronounced environmental influence on spectral variation, as P. fremontii source population and garden location were classified at 71.8

The assimilation, retention, and release of nutrients by animals fundamentally shapes their physiology and contributions to ecological processes (e.g., zoogeochemistry). Yet, information on the transit of nutrients through the bodies of large mammals remains scarce. Here, we examined how sodium (Na), a key element for animal health and ecosystem functioning, travels differently through fecal and urinary systems of cows (Bos taurus) and horses (Equus ferus caballus). We provided a large dose of Na and compared its timing of release in feces and urine to that of nonabsorbable markers. Na excretion by urine occurred approximately twice as fast as excretion by feces, yet both were shorter than indigestible particle markers. These differences correspond to rapid absorption of Na in the upper gastrointestinal tract and transport by blood to the kidneys (urine Na excretion) or resecretion of Na into the lower intestinal tract (fecal Na excretion). Interestingly, for cows, we found a second peak of Na excretion in urine and feces > 96 h after dosage. This result may indicate that surplus Na can be rapidly absorbed and stored in specific body cells (e.g., skin), from which it is later released. Using a propagule dispersal model, we found that the distance of cattle- and horse-driven nutrient dispersal by urine was 31% and 36% less than the fecal pathway and 60% and 41% less than the particle marker pathway, which is commonly used to estimate nutrient dispersal. Future physiological and zoogeochemical studies should resolve different pathways of nutrient retention and release from large mammals.

Sodium (Na) is an essential nutrient for animals, but not for most plants. Consequently, herbivores may confront a mismatch between forage availability and metabolic requirement. Recent work suggests that larger-bodied mammals may be particularly susceptible to Na deficits, yet it is unknown whether Na availability constrains the density or distribution of large herbivores at broad scales. Here we show that plant-Na availability varies >1,000-fold across sub-Saharan Africa and helps explain continent-scale patterns of large-herbivore abundance. We combined field data with machine-learning approaches to generate high-resolution maps of plant Na, which revealed multi-scale gradients arising from sea-salt deposition, hydrology, soil chemistry and plant traits. Faecal Na concentration was positively correlated with modelled dietary Na, supporting the prediction that variation in plant Na is a major determinant of herbivore Na intake. Incorporating plant-Na availability improved model predictions of large-herbivore population density, especially for megaherbivore species, which are depressed in very-low-Na regions (<100 mg kg-1), consistent with Na limitation. Our study offers an explanation for the scarcity of megaherbivores in parts of Central and West Africa, which has major ecological ramifications given the strong influence of large herbivores on ecosystem functioning and the profound human-induced changes to Na availability in Africa and beyond.

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 two Populus species ( P . fremontii , P . angustifolia ) and their naturally occurring hybrids using leaf‐level visible through shortwave infrared (VSWIR; 400–2500 nm) reflectance. As F 1 hybrids 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 in P. fremontii drought 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 of P. fremontii from 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.

Tropical planted and regrowth forests (TPRFs) are one of the most low-cost components for recovering biomass-stored carbon in the tropics. Nevertheless, challenges persist in pinpointing which elevational ranges exhibit the largest carbon accumulation rate ( 7 rapid ) due to the highly inconsistent previous assessments. This prevents the selection of optimal locations for implementing large-scale reforestation in the tropics. Here, we proposed a refined approach that used a carbon accumulation threshold (<80% of the maximum value) to quantify 7 rapid in TPRFs at various elevations. We find that 7 rapid increases with elevations from 300 to 1,000 m and declines at elevations >1,000 m. TPRFs at elevations 1,000 m exhibit three times more 7 rapid than lowland TPRFs. This optimal elevation, highly dependent on background temperatures, varies slightly but significantly across different mountains. These findings provide guidelines for policy- makers to determine the optimal elevations from regional to continental scales when implementing reforestation initiatives in the tropics.

Baleen whales migrate from productive high-latitude feeding grounds to usually oligotrophic tropical and subtropical reproductive winter grounds, translocating limiting nutrients across ecosystem boundaries in their bodies. Here, we estimate the latitudinal movement of nutrients through carcasses, placentas, and urea for four species of baleen whales that exhibit clear annual migration, relying on spatial data from publicly available databases, present and past populations, and measurements of protein catabolism and other sources of nitrogen from baleen whales and other marine mammals. Migrating gray, humpback, and North Atlantic and southern right whales convey an estimated 3784 tons N yr-1 and 46,512 tons of biomass yr-1 to winter grounds, a flux also known as the "great whale conveyor belt"; these numbers might have been three times higher before commercial whaling. We discuss how species recovery might help restore nutrient movement by whales in global oceans and increase the resilience and adaptative capacity of recipient ecosystems.

How tropical forest leaves respond to climate change has important implications for the global carbon cycle and biodiversity. Climate change could impact the energy balance properties of tropical forest canopies through (a) long-term trait changes and (b) abrupt disruptions/damage to leaf/photosynthetic machinery. We assessed the radiative and evaporative impacts of two recently proposed impacts of climate change on tropical forest canopies: (a) long-term leaf darkening and (b) leaf death through high temperature extremes. We darkened leaves to absorb 138 Wm-2 more energy in the upper canopy of a seasonally dry tropical moist forest in Panama. 20% of this extra energy went toward heating leaves by similar to 4 degrees C, 3% went toward warming the air, and 77% went toward evaporative cooling. This leaf warming led to the appearance of necrosis across 9 +/- 5% of the leaf area on certain species. In contrast, brightening leaves decreased energy absorbed by an average of 58 Wm-2, which mainly reduced evaporation (88%) with only 12% reducing leaf temperatures (and no change in sensible heat flux). This asymmetrical result suggests leaves may be close to hydraulic limitations to support transpirational cooling toward the end of the dry season. Similar albedo increases in a model (CLM 4.0) did not diverge between brightening and darkening leaves and generally showed sensible heat flux to dominate although there were strong geographic trends. Heat death in leaves generally heated nearby leaves (by an average of similar to 1.35 degrees C) and air temperature (by 0.5 degrees C) but less than hypothesized because leaf albedo increased. Overall, our canopy top experiments question important potential climate feedbacks but need further study.

It has been hypothesized that the extinction of the dinosaurs, and later the Pleistocene megafauna, created a darker forest subcanopy benefiting large-seeded plants. Larger seeds and their fruit, in turn, opened a dietary niche space for animals thus strongly shaping the ecology of the Cenozoic, including our fruit-eating primate ancestors. In this paper, we develop a mechanistic model where we replicate the conditions of tropical forests of the early Paleocene, with small animal body and small seed size, and the Holocene, with small animal body and large seed size. We first calibrate light levels in our model using stable carbon isotope ratios from fossil leaves and estimate a decrease of understory light of c. 90 mu mol m-2 s-1 (a 19% decrease) from the Cretaceous to the Paleocene. Our model predicts a rapid increase in seed size during the Paleocene that eventually plateaued or declined slightly. Specifically, we find a dynamic feedback where increased animal sizes opened the understory causing negative feedback by increasing subcanopy light penetration that limited maximum seed size, matching the actual trend in angiosperm seed sizes in mid/high latitude ecosystems. Adding the ability of larger animals to increase ecosystem fertility to the model, further increased mean animal body size by 17% and mean seed size by 90%. Our model is a drastic simplification and there are many remaining uncertainties, but we show that ecological dynamics can explain seed size trends without adding external factors such as 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 species Populus fremontii were 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.

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.

Supplementary feeding of garden birds and gamebirds is a common practice worldwide. Bird feed is rich in phosphorus (P), which plays a key role in animal health and ecosystem function. However, much of the P in bird feed originates from mined rock deposits, which is then transported thousands of kilometers to feeder stations, where it represents an external source of nutrients for recipient ecosystems. Here, we demonstrate that diffusion of P by birds and other animals from feeder stations to ecosystems can represent a nontrivial contribution to local biogeochemical cycles. Using the UK as a case study, we show that supplementary bird feeding supplies 2.4 (range: 1.9–3.0) gigagrams of P per year across the UK, a flux similar in magnitude to atmospheric deposition. Phosphorus provided to garden birds alone is equal to that supplied through the application of garden fertilizers. In natural and semi-natural ecosystems, additional feeder-derived P inputs may exacerbate eutrophication at the local scale and adversely impact biodiversity.

Earth’s ecosystems are characterized by numerous gradients related to the distribution of environmental conditions and resources. Niche theory predicts that animals will evolve traits to exploit changing resource availability and environmental conditions across these gradients. Much work has been done examining how animal traits like body mass and diet change across gradients from regional to global scales. Environmental and resource gradients in the vertical dimension tend to exhibit strong changes over relatively short distances due to the influence of elevation and vegetation. Vegetation structure may be an especially important vertical axis as it contributes to strong gradients in micro- climate, food resources, and predation risk. To investigate interrelationships between the vertical niche and its presumed drivers, we use functional traits, phylogenies, and predation risk to predict the vertical foraging niche for 4,828 mammals and 9,437 birds globally. To provide biogeographic context to the predictive analysis, we use species ranges to map geographic distributions of the vertical foraging niche and relationships between the niche and its presumed drivers. Linking trait databases with species range maps revealed distinct global distributions of vertical foraging niches for mammals and birds. The most important predictors of these niches varied by taxon but there were several systematic relationships. Diet, body mass, and phylogeny were strong predictors of vertical foraging niche across mammal and bird species. Percent fruit in diet exhibited progressively more positive relationships with higher canopy foraging positions. Predation pressure was relatively unimportant in predicting most vertical foraging niches for birds and mammals but displayed a positive trend with arboreal foraging. Geographic hotspots for the importance of fruit in both mammal and bird diets included the Andes-Amazon transition zone, the Amazon Basin, and New Guinea. Our results provide support for the theory of resource driven vertical niche partitioning but also reveal that vertical niches are strongly associated with phylogeny, suggesting niche conservatism in numerous mammal and bird families. Geographic patterns in variable importance values suggest multiple mechanisms behind spatial structure in eco- evolutionary relationships, including latitudinal gradients in vegetation structure and composition, historical patterns of island isolation (in Southeast Asia), and the influence of habitat heterogeneity driven by tectonic processes (in South America). ### Competing Interest Statement The authors have declared no competing interest.

Background Vegetation structure is increasingly recognized as a key variable to explain ecosystems states and dynamics. New Remote Sensing tools are available to complement labor intensive field investigations and consider the global biogeography of this parameter. Objectives We propose to model the processes explaining the interaction between vegetation structure and animal community assembly globally, while requiring minimal computing power, based on the most fundamentals assumptions. Methods We integrate spaceborne (GEDI: Global Ecosystem Dynamics Investigation) and ground based (TLS: Terrestrial Laser Scanning) Lidar data in the Madingley general ecosystem model. We compare the outcome of this integration to previous version and to the TetraDensity estimate of animal biomass and Elton traits database for arboreality. Results Animal biomass density simulated by Madingley is closer to global estimates when integrating vegetation structure. The strength of this effect increases with higher cohort body mass and varies with local environmental conditions and stochastic processes. Simulated proportion of arboreality across cohorts is consistently higher than observations. This is consistent with the divergence of biases between model and database. Conclusions Our results concur with our hypotheses about the role of vegetation structure on animal community assembly, as it reduces total animal biomass abundance. However, assessing the accuracy of its relative weight is challenging. While we have global products about arboreality and animal biomass density, they represent modern day ecosystem state, including anthropogenic activity, while Madingley simulates potential ecosystem optimum. Therefore, we call for further research in this field and for challenging modelling attempts to compare with.

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.

Improving tropical forest current biomass estimates can help more accurately evaluate ecosystem services in tropical forests. The Global Ecosystem Dynamics Investigation (GEDI) lidar provides detailed 3D forest structure and height data, which can be used to improve above‐ground biomass estimates. However, there is still debate on how best to predict tropical forest biomass using GEDI data. Here we compare stand biomass predicted by GEDI data with the observed data of 2,102 inventory plots in tropical forests and find that adding a remotely sensed (RS) trait map of leaf mass area (LMA) significantly (P < 0.001) improves field biomass predictions, but by only a small amount (r2 = 0.01). However, it may also help reduce the bias of the residuals because there was a negative relationship between both LMA (r2 of 0.34) and percentage of phosphorus (%P, r2 = 0.31) and residuals. Leaf spectral data (400–1,075 nm) from 523 individual trees along a Peruvian tropical forest elevation gradient predicted Diameter at Breast height (DBH) (the critical measurement underlying plot biomass) with an r2 = 0.01 and LMA predicts DBH with an r2 = 0.04. Other data sets may offer further improvements and max temperature (Tmax) predicts Amazonian biomass residuals with an r2 of 0.76 (N = 66). Finally, for a network of net primary production (NPP) and gross primary production (GPP) plots (N = 21), leaf traits predicted with remote sensing are better at predicting fluxes than structure variables. Overall, trait maps, especially future improved ones produced by Surface Biology Geology, may improve biomass and carbon flux predictions by a small but significant amount.

AbstractGlobally, vegetation biodiversity is expected to decline as the rate of plant adaptation struggles to keep pace with rising temperatures. To support conservation efforts through remote sensing, we disentangled the nested effects of genetic and environmental influences on reflectance spectra, leveraging spectroscopy to assess plant adaptations to temperature. Specifically, we quantified the relative effect of plasticity and heritability onPopulus fremontii(Fremont cottonwood) leaf reflectance using clonal replicates propagated from 16 populations and grown across three common gardens spanning a mean annual temperature gradient representing the thermal range ofP. fremontii. We used variance partitioning to decompose phenotypic variation expressed in the leaf spectra into genotypic and environmental components to estimate broad-sense heritability. Heritability was strongly expressed in the spectral red edge (∼680-750nm) and shortwave infrared (∼1400-3000nm), though the heritability peak in the red edge was sensitive to extreme temperatures. By comparing distances of group centroids in principal component space, we determined thatP. fremontiiintraspecific spectral variation was shaped by the interaction between common garden site conditions and source population. Support vector machine models indicated pronounced environmental influence on spectral variation, asP. fremontiisource population and garden location were classified at 71.8% and 92.6% accuracy, respectively. These findings emphasize the utility of reflectance data in separating genetic and environmental influences on plant phenotypes, offering a pathway to scale these insights across broader landscapes and aid in the conservation and management of vulnerable ecosystems in a warming climate.