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Summary Reflectance spectroscopy is a rapid method for estimating traits and discriminating species. Spectral libraries from herbarium specimens represent an untapped resource for generating broad phenomic datasets across space, time, and taxa.We conducted a proof‐of‐concept study using trait data and spectra from herbarium specimens up to 179 yr old, alongside data from recently dried and pressed leaves. We validated model accuracy and transferability for trait prediction and taxonomic discrimination.Trait models from herbarium spectra predicted leaf mass per area (LMA) withR² = 0.94 and %RMSE = 4.86%. Models for LMA prediction were transferable between herbarium and pressed spectra, achievingR² = 0.88, %RMSE = 8.76% for herbarium to pressed spectra, andR² = 0.76, %RMSE = 10.5% for the reverse transfer. Discriminant models classified leaf spectra from 25 species with 74% accuracy, and classification probabilities were significantly associated with several herbarium specimen quality metrics.The results validate herbarium spectral data for trait prediction and taxonomic discrimination, and demonstrate that trait modeling can benefit from the complementary use of pressed‐leaf and herbarium‐leaf spectral datasets. These promising advancements help to justify the spectral digitization of plant biodiversity collections and support their application in broad ecological and evolutionary investigations. 

Abstract The stability of forest productivity is a widely studied phenomenon often associated with tree species diversity. Yet, drivers of stability in forest structure and its consequences for forest productivity remain poorly understood. Using a large (10 ha) young tree diversity experiment, we evaluated how forest structure and multiple dimensions of diversity and composition are related to remotely sensed structural metrics and their stability through the growing season. We then examined whether structural stability (SS) across the growing season (April–October) could explain overyielding (i.e., the net biodiversity effect, NBE) in annual wood productivity. Using Uncrewed Aerial Vehicle‐Light Detecting and Ranging (UAV‐LiDAR), we surveyed experimental tree communities eight times at regular intervals from before bud break to after leaf senescence to derive metrics associated with canopy height heterogeneity, fractional plant cover, and forest structural complexity (based on fractal geometry). The inverse coefficients of variation for each of these three metrics through the season were used as measures of SS. These metrics were then coupled with annual tree inventories to evaluate their relationships with the NBE. Our findings indicate that wood volume and, to some extent, multiple dimensions of diversity and composition (i.e., taxonomic, phylogenetic, and functional) explain remotely sensed metrics of forest structure and their SS. Increases in wood volume as well as functional and phylogenetic diversity and variability (a measure of diversity independent of species richness) were linked to higher SS of forest complexity and canopy height heterogeneity. We further found that higher SS of forest complexity and fractional plant cover were associated with increased overyielding, which was mostly attributable to the complementarity effect. Structural equation models indicate that the stability of structural complexity explains more variation in NBE among plots than dimensions of diversity or variability, highlighting its value as an informative metric that likely integrates multiple drivers associated with overyielding. This study highlights the potential to integrate remote sensing and ecology to disentangle the role of forest SS in shaping ecological processes. 

Abstract Anthropogenic climate change, particularly changes in temperature and precipitation, affects plants in multiple ways. Because plants respond dynamically to stress and acclimate to changes in growing conditions, diagnosing quantitative plant‐environment relationships is a major challenge. One approach to this problem is to quantify leaf responses using spectral reflectance, which provides rapid, inexpensive, and nondestructive measurements that capture a wealth of information about genotype as well as phenotypic responses to the environment. However, it is unclear how warming and drought affect spectra. To address this gap, we used an open‐air field experiment that manipulates temperature and rainfall in 36 plots at two sites in the boreal‐temperate ecotone of northern Minnesota, USA. We collected leaf spectral reflectance (400–2400 nm) at the peak of the growing season for three consecutive years on juveniles (two to six years old) of five tree species planted within the experiment. We hypothesized that these mid‐season measurements of spectral reflectance capture a snapshot of the leaf phenotype encompassing a suite of physiological, structural, and biochemical responses to both long‐ and short‐time scale environmental conditions. We show that the imprint of environmental conditions experienced by plants hours to weeks before spectral measurements is linked to regions in the spectrum associated with stress, namely the water absorption regions of the near‐infrared and short‐wave infrared. In contrast, the environmental conditions plants experience during leaf development leave lasting imprints on the spectral profiles of leaves, attributable to leaf structure and chemistry (e.g., pigment content and associated ratios). Our analyses show that after accounting for baseline species spectral differences, spectral responses to the environment do not differ among the species. This suggests that building a general framework for understanding forest responses to climate change through spectral metrics may be possible, likely having broader implications if the common responses among species detected here represent a widespread phenomenon. Consequently, these results demonstrate that examining the entire spectrum of leaf reflectance for environmental imprints in contrast to single features (e.g., indices and traits) improves inferences about plant‐environment relationships, which is particularly important in times of unprecedented climate change. 

Tracking biodiversity across biomes over space and time has emerged as an imperative in unified global efforts to manage our living planet for a sustainable future for humanity. We harness the National Ecological Observatory Network to develop routines using airborne spectroscopic imagery to predict multiple dimensions of plant biodiversity at continental scale across biomes in the US. Our findings show strong and positive associations between diversity metrics based on spectral species and ground-based plant species richness and other dimensions of plant diversity, whereas metrics based on distance matrices did not. We found that spectral diversity consistently predicts analogous metrics of plant taxonomic, functional, and phylogenetic dimensions of biodiversity across biomes. The approach demonstrates promise for monitoring dimensions of biodiversity globally by integrating ground-based measures of biodiversity with imaging spectroscopy and advances capacity toward a Global Biodiversity Observing System. 

Measuring the chemical traits of leaf litter is important for understanding plants’ influence on nutrient cycles, including through nutrient resorption and litter decomposition, but conventional leaf trait measurements are often destructive and labor-intensive. Here, we develop and evaluate the performance of partial least-squares regression models that use reflectance spectra of intact or ground leaves to estimate leaf litter traits, including carbon and nitrogen concentration, carbon fractions, and leaf mass per area (LMA). Our analyses included more than 300 samples of senesced foliage from 11 species of temperate trees, including both needleleaf and broadleaf species. Across all samples, we could predict each trait with moderate-to-high accuracy from both intact-leaf litter spectra (validation R² = 0.543–0.941; %root mean squared error (RMSE) = 7.49–18.5) and ground-leaf litter spectra (validation R² = 0.491–0.946; %RMSE = 7.00–19.5). Notably, intact-leaf spectra yielded better predictions of LMA. Our results support the feasibility of building models to estimate multiple chemical traits from leaf litter of a range of species. In particular, intact-leaf spectral models allow non-destructive trait estimation in a matter of seconds, which could enable researchers to measure the same leaves over time in studies of nutrient resorption. 

Abstract We introduce a new “ecosystem‐scale” experiment at the Cedar Creek Ecosystem Science Reserve in central Minnesota, USA to test long‐term ecosystem consequences of tree diversity and composition. The experiment—the largest of its kind in North America—was designed to provide guidance on forest restoration efforts that will advance carbon sequestration goals and contribute to biodiversity conservation and sustainability.The new Forest and Biodiversity (FAB2) experiment uses native tree species in varying levels of species richness, phylogenetic diversity and functional diversity planted in 100 m²and 400 m²plots at 1 m spacing, appropriate for testing long‐term ecosystem consequences. FAB2 was designed and established in conjunction with a prior experiment (FAB1) in which the same set of 12 species was planted in 16 m²plots at 0.5 m spacing. Both are adjacent to the BioDIV prairie‐grassland diversity experiment, enabling comparative investigations of diversity and ecosystem function relationships between experimental grasslands and forests at different planting densities and plot sizes.Within the first 6 years, mortality in 400 m²monoculture plots was higher than in 100 m²plots. The highest mortality occurred inTilia americanaandAcer negundomonocultures, but mortality for both species decreased with increasing plot diversity. These results demonstrate the importance of forest diversity in reducing mortality in some species and point to potential mechanisms, including light and drought stress, that cause tree mortality in vulnerable monocultures. The experiment highlights challenges to maintaining monoculture and low‐diversity treatments in tree mixture experiments of large extent.FAB2 provides a long‐term platform to test the mechanisms and processes that contribute to forest stability and ecosystem productivity in changing environments. Its ecosystem‐scale design, and accompanying R package, are designed to discern species and lineage effects and multiple dimensions of diversity to inform restoration of ecosystem functions and services from forests. It also provides a platform for improving remote sensing approaches, including Uncrewed Aerial Vehicles (UAVs) equipped with LiDAR, multispectral and hyperspectral sensors, to complement ground‐based monitoring. We aim for the experiment to contribute to international efforts to monitor and manage forests in the face of global change. 

Abstract Greater tree diversity often increases forest productivity by increasing the fraction of light captured and the effectiveness of light use at the community scale. However, light may shape forest function not only as a source of energy or a cause of stress but also as a context cue: Plant photoreceptors can detect specific wavelengths of light, and plants use this information to assess their neighborhoods and adjust their patterns of growth and allocation. These cues have been well documented in laboratory studies, but little studied in diverse forests. Here, we examined how the spectral profile of light (350–2200 nm) transmitted through canopies differs among tree communities within three diversity experiments on two continents (200 plots each planted with one to 12 tree species, amounting to roughly 10,000 trees in total), laying the groundwork for expectations about how diversity in forests may shape light quality with consequences for forest function. We hypothesized—and found—that the species composition and diversity of tree canopies influenced transmittance in predictable ways. Canopy transmittance—in total and in spectral regions with known biological importance—principally declined with increasing leaf area per ground area (LAI) and, in turn, LAI was influenced by the species composition and diversity of communities. For a given LAI, broadleaved angiosperm canopies tended to transmit less light with lower red‐to‐far‐red ratios than canopies of needle‐leaved gymnosperms or angiosperm‐gymnosperm mixtures. Variation among communities in the transmittance of individual leaves had a minor effect on canopy transmittance in the visible portion of the spectrum but contributed beyond this range along with differences in foliage arrangement. Transmittance through mixed species canopies often deviated from expectations based on monocultures, and this was only partly explained by diversity effects on LAI, suggesting that diversity effects on transmittance also arose through shifts in the arrangement and optical properties of foliage. We posit that differences in the spectral profile of light transmitted through diverse canopies serve as a pathway by which tree diversity affects some forest ecosystem functions. 

Biodiversity is ultimately the outcome of millions of years of evolution; however, due to increasing human domination of the Earth, biodiversity in its multiple dimensions is changing rapidly. Here, we present “phylogenetic completeness” (PC) as a concept and method for safeguarding Earth's evolutionary heritage by maintaining all branches of the tree of life. Using data for five major terrestrial clades, we performed a global evaluation of the PC approach and compared the results to an approach in which species are conserved or lost at random. We demonstrate that under PC, for a given number of species extinctions, it is possible to maximize the protection of evolutionary innovations in every clade. The PC approach is flexible, may be used to conduct a phylogenetic audit of biodiversity under different conservation scenarios, complements existing conservation efforts, and is linked to the post‐2020 UN Convention on Biodiversity targets. 

Abstract High alpine regions are threatened but understudied ecosystems that harbor diverse endemic species, making them an important biome for testing the role of environmental factors in driving functional trait‐mediated community assembly processes. We tested the hypothesis that plant community assembly along a climatic and elevation gradient is influenced by shifts in habitat suitability, which drive plant functional, phylogenetic, and spectral diversity. In a high mountain system (2400–3500 m) Región Metropolitana in the central Chilean Andes (33°S, 70°W). We surveyed vegetation and spectroscopic reflectance (400–2400 nm) to quantify taxonomic, phylogenetic, functional, and spectral diversity at five sites from 2400 to 3500 m elevation. We characterized soil attributes and processes by measuring water content, carbon and nitrogen, and net nitrogen mineralization rates. At high elevation, colder temperatures reduced available soil nitrogen, while at warmer, lower elevations, soil moisture was lower. Metrics of taxonomic, functional, and spectral alpha diversity peaked at mid‐elevations, while phylogenetic species richness was highest at low elevation. Leaf nitrogen increased with elevation at the community level and within individual species, consistent with global patterns of increasing leaf nitrogen with colder temperatures. The increase in leaf nitrogen, coupled with shifts in taxonomic and functional diversity associated with turnover in lineages, indicate that the ability to acquire and retain nitrogen in colder temperatures may be important in plant community assembly in this range. Such environmental filters have important implications for forecasting shifts in alpine plant communities under a warming climate.