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At least 37 records · Page 2

Quantitative trait locus mapping combined with variant and transcriptome analyses identifies a cluster of gene candidates underlying the variation in leaf wax between upland and lowland switchgrass ecotypes

Switchgrass (Panicum virgatum L.) is a promising warm-season candidate energy crop. It occurs in two ecotypes, upland and lowland, which vary in a number of phenotypic traits, including leaf glaucousness. To initiate trait mapping, two F 2 mapping populations were developed by crossing two different F 1 sibs derived from a cross between the tetraploid lowland genotype AP13 and the tetraploid upland genotype VS16, and high-density linkage maps were generated. Quantitative trait locus (QTL) analyses of visually scored leaf glaucousness and of hydrophobicity of the abaxial leaf surface measured using a drop shape analyzer identified highly significant colocalizing QTL on chromosome 7K (Chr07K). Using a multipronged approach, we identified a cluster of genes including Pavir.7KG077009, which encodes a Type III polyketide synthase-like protein, and Pavir.7KG013754 and Pavir.7KG030500, two highly similar genes that encode putative acyl-acyl carrier protein (ACP) thioesterases, as strong candidates underlying the QTL. The lack of homoeologs for any of the three genes on Chr07N, the relatively low level of identity with other switchgrass KCS proteins and thioesterases, as well as the organization of the surrounding region suggest that Pavir.7KG077009 and Pavir.7KG013754/Pavir.7KG030500 were duplicated into a fast-evolving chromosome region, which led to their neofunctionalization. Furthermore, sequence analyses showed all three genes to be absent in the two upland compared to the two lowland accessions analyzed. This study provides an example of and practical guide for trait mapping and candidate gene identification in a complex genetic system by combining QTL mapping, transcriptomics and variant analysis.

59 BASIC BIOLOGICAL SCIENCES↗

DUET - Distribution of Understory using Elliptical Transport: A mechanistic model of leaf litter and herbaceous spatial distribution based on tree canopy structure

Heterogeneity in surface fuels produced by overstory trees and understory vegetation is a major driver of fire behavior and ecosystem dynamics. Previous attempts at predicting tree leaf and needle litter accumulation over time have been constrained in scope to probabilistic models that consider a limited number of key factors influencing tree litter dispersal patterns and decomposition processes. Here we present a mechanistic model for estimating variation in surface fuels called the Distribution of Understory using Elliptical Transport (DUET). DUET uses a pre-generated voxelated canopy array and distributes the leaf litter from the trees in an elliptical shape based on tree species characteristics, wind data, and location-specific features. DUET then calculates grass growth between trees and around the litter patterns and sets moisture levels based on relative humidity. In this study, we use DUET to simulate spatial distributions of leaf litter and illustrate model sensitivity to several parameters, providing inputs for testing fuel spatial heterogeneity impacts on fire behavior using process-based models.

54 ENVIRONMENTAL SCIENCES↗

Reassessing the roles of PIN proteins and anticlinal microtubules during pavement cell morphogenesis

The leaf epidermis is a biomechanical shell that influences the size and shape of the organ. Its morphogenesis is a multiscale process in which nanometer-scale cytoskeletal protein complexes, individual cells, and groups of cells pattern growth and define macroscopic leaf traits. Interdigitated growth of neighboring cells is an evolutionarily conserved developmental strategy. Understanding how signaling pathways and cytoskeletal proteins pattern cell walls during this form of tissue morphogenesis is an important research challenge. The cellular and molecular control of a lobed cell morphology is currently thought to involve PIN-FORMED (PIN)-type plasma membrane efflux carriers that generate subcellular auxin gradients. Auxin gradients were proposed to function across cell boundaries to encode stable offset patterns of cortical microtubules and actin filaments between adjacent cells. Many models suggest that long-lived microtubules along the anticlinal cell wall generate local cell wall heterogeneities that restrict local growth and specify the timing and location of lobe formation. Here we used Arabidopsis reverse genetics and multivariate long-term time-lapse imaging to test current cell shape control models. We found that neither PIN proteins nor microtubules along the anticlinal wall predict the patterns of lobe formation. In fields of lobing cells, anticlinal microtubules are not correlated with cell shape and are unstable at the time scales of cell expansion. Our analyses indicate that anticlinal microtubules have multiple functions in pavement cells, and that lobe initiation is likely controlled by complex interactions among cell geometry, cell wall stress patterns, and transient microtubule networks that span the anticlinal and periclinal walls.

59 BASIC BIOLOGICAL SCIENCES↗

The impact of habitat fragmentation on domatia-dwelling mites and a mite-plant-fungus tritrophic interaction

Abstract Context Habitat fragmentation is a leading threat to biodiversity, yet the impacts of fragmentation on most taxa, let alone interactions among those taxa, remain largely unknown. Objectives We studied how three consequences of fragmentation—reduced patch connectivity, altered patch shape, and edge proximity—impact plant-dwelling mite communities and mite-plant-fungus interactions within a large-scale habitat fragmentation experiment. Methods We sampled mite communities from the leaves of Quercus nigra (a plant species that has foliar domatia which harbor fungivorous and predacious mites) near and far from edge within fragments of varying edge-to-area ratio (shape) and connectivity via corridors. We also performed a mite-exclusion experiment across these fragmentation treatments to test the effects of mite presence and fungal hyphal abundance on leaf surfaces. Results Habitat edges influenced the abundance and richness of leaf-dwelling mites; plants closer to the edge had higher mite abundance and species richness. Likewise, hyphal counts were higher on leaves near patch edges. Despite both mite and fungal abundance being higher at patch edges, leaf hyphal counts were not impacted by mite abundance on those leaves. Neither patch shape nor connectivity influenced mite abundance, mite species richness, or the influence of mites on leaf surface fungal abundance. Conclusion Our results suggest that mites and foliar fungi may be independently affected by edge-structured environmental gradients, like temperature, rather than trophic effects. We demonstrate that large-scale habitat fragmentation and particularly edge effects can have impacts on multiple levels of microscopic communities, even in the absence of cascading trophic effects.

60 APPLIED LIFE SCIENCES↗

Mycorrhiza Better Predict Soil Fungal Community Composition and Function than Aboveground Traits in Temperate Forest Ecosystems

Forests in the northeastern US are experiencing shifts in community composition due to the northward migration of warm-adapted tree species and certain species’ declines (for example, white ash and eastern hemlock) due to invasive insects. Changes in belowground fungal communities and associated functions will inevitably follow. Therefore, we sought to investigate the relative importance of two important tree characteristics—mycorrhizal type [ectomycorrhizal (EcM) or arbuscular mycorrhizal (AM)] and leaf habit (deciduous or evergreen) on soil fungal community composition and organic matter cycling. We sampled soil in the organic and mineral horizons beneath two AM-associated (Fraxinus americana and Thuja occidentalis) and two ECM-associated tree species (Betula alleghaniensis and Tsuga canadensis), with an evergreen and deciduous species in each mycorrhizal group. To characterize fungal communities and organic matter decomposition beneath each tree species, we sequenced the ITS1 region of fungal DNA and measured the potential activity of carbon- and nitrogen-targeting extracellular enzymes. Each tree species harbored distinct fungal communities, supporting the need to consider both mycorrhizal type and leaf habit. However, between tree characteristics, mycorrhizal type better predicted fungal communities. Across fungal guilds, saprotrophic fungi were the most important group in shaping fungal community differences in soils beneath all tree species. The effect of leaf habit on carbon- and nitrogen-targeting hydrolytic enzymes depended on tree mycorrhizal association in the organic horizon, while oxidative enzyme activities were higher beneath EcM-associated trees across both soil horizons and leaf habits.

54 ENVIRONMENTAL SCIENCES↗

Mycorrhiza better predict soil fungal community composition and function than aboveground traits in temperate forest ecosystems

We sampled soil in the organic and mineral horizons beneath two AM-associated (Fraxinus americana, Thuja occidentalis) and two ECM-associated tree species (Betula alleghaniensis, and Tsuga canadensis), with an evergreen and deciduous species in each mycorrhizal group. To characterize fungal communities and organic matter decomposition beneath each tree species, we sequenced the ITS1 region of fungal DNA and measured the potential activity of carbon and nitrogen-targeting extracellular enzymes. Each tree species harbored distinct fungal communities, supporting the need to consider both mycorrhizal type and leaf habit. However, between tree characteristics, mycorrhizal type better predicted fungal communities. Across fungal guilds, saprotrophic fungi were the most important group in shaping fungal community differences in soils beneath all tree species. The effect of leaf habit on carbon and nitrogen-targeting hydrolytic enzymes depended on tree mycorrhizal association in the organic horizon, while oxidative enzyme activities were higher beneath EcM-associated trees across both soil horizons and leaf habits. These data include extracellular hydrolytic and oxidative enzyme activities, ITS sequencing fungal community data, soil carbon to nitrogen, and soil pH. Site level data include climate (mean annual temperature, precipitation), elevation, and soil series and order information.

54 ENVIRONMENTAL SCIENCES↗

Imprint of tree species mycorrhizal association on microbial‐mediated enzyme activity and stoichiometry

Abstract Understanding the effects of tree species and their mycorrhizal association on soil processes is critical for predicting the ecosystem consequences of species shifts owing to global change and forest management decisions. While it is well established that forests dominated by different mycorrhizal types can vary in how they cycle carbon (C), nitrogen (N) and phosphorus (P), the degree to which these patterns are driven by microbial‐mediated enzyme activity (EA) and ecoenzymatic stoichiometry (ES) remains elusive. Here, we synthesized the effects of mycorrhizal association on seven soil enzymes involved in microbial C, N and P acquisition and ES using data from 56 peer‐reviewed papers. We found that relative to soil in ectomycorrhizal (EcM) trees, soil in arbuscular mycorrhizal (AM) trees exhibited greater activity of some C acquisition enzymes (e.g. beta‐glucosidase; BG) and higher ecoenzymatic ratios of BG/NAG (N‐acetyl‐glucosaminidase) and BG/AP (acid phosphatase). These results supported that AM trees had rapid C and nutrient turnover rates, inorganic nutrient economics and high soil microbial C limitation. We also found evidence for an organic nutrient economy and greater soil microbial demand for nutrients in EcM trees compared to AM trees. In addition, the effect of mycorrhizal association on the activity of certain soil enzymes and enzymatic stoichiometry (i.e. BG and BG/NAG ratio) appeared to be associated with the differences in soil pH, phylogenetic group (i.e. conifers and broadleaves) and leaf habit (i.e. evergreen and deciduous) between AM and EcM trees. The results from the global meta‐analysis suggested that soil EA and ES appear to play critical roles in shaping the differences in the nutrient economy between AM and EcM tree species, but leaf morphology and soil conditions should be considered in evaluations of soil processes in forests of different mycorrhizal associations. Given that most of the studies in the database were from the temperate and subtropical regions, further research in other biomes is needed to elucidate the underlying mechanisms driving the mycorrhizal effect at the global scale. Read the free Plain Language Summary for this article on the Journal blog.

54 ENVIRONMENTAL SCIENCES↗

TH-AB-202-09: Direct-Aperture Optimization for Combined MV+kV Dose Planning in Fluoroscopic Real-Time Tumor-Tracking Radiation Therapy

Purpose: Real-time kV fluoroscopic tumor tracking has the benefit of direct tumor position monitoring. However, there is clinical concern over the excess kV imaging dose cost to the patient when imaging in continuous fluoroscopic mode. This work addresses this specific issue by proposing a combined MV+kV direct-aperture optimization (DAO) approach to integrate the kV imaging beam into a treatment planning such that the kV radiation is considered as a contributor to the overall dose delivery. Methods: The combined MV+kV DAO approach includes three algorithms. First, a projected Quasi-Newton algorithm (L-BFGS) is used to find optimized fluence with MV+kV dose for the best possible dose distribution. Then, Engel’s algorithm is applied to optimize the total number of monitor units and heuristically optimize the number of apertures. Finally, an aperture shape optimization (ASO) algorithm is applied to locally optimize the leaf positions of MLC. Results: Compared to conventional DAO MV plans with continuous kV fluoroscopic tracking, combined MV+kV DAO plan leads to a reduction in the total number of MV monitor units due to inclusion of kV dose as part of the PTV, and was also found to reduce the mean and maximum doses on the organs at risk (OAR). Compared to conventional DAO MV plan without kV tracking, the OAR dose in the combined MV+kV DAO plan was only slightly higher. DVH curves show that combined MV+kV DAO plan provided about the same PTV coverage as that in the conventional DAO plans without kV imaging. Conclusion: We report a combined MV+kV DAO approach that allows real time kV imager tumor tracking with only a trivial increasing on the OAR doses while providing the same coverage to PTV. The approach is suitable for clinic implementation.

60 APPLIED LIFE SCIENCES↗

Dynamics of Spin Polarization in Tilted Polariton Rings

We have observed the effect of pseudomagnetic field originating from the polaritonic analog of spin-orbit coupling [transverse electric and transverse magnetic (TE-TM) splitting] on a polariton condensate in a ring-shaped microcavity. The effect gives rise to a stable four-leaf pattern around the ring as seen from the linear polarization measurements of the condensate photoluminescence. This pattern is found to originate from the interplay of the cavity potential, energy relaxation, and TE-TM splitting in the ring. Our observations are compared to the dissipative one-dimensional spinor Gross-Pitaevskii equation with the TE-TM splitting energy, which shows good qualitative agreement.

CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS↗

Climate sensitive size-dependent survival in tropical trees

Survival rates of large trees determine forest biomass dynamics. Survival rates of small trees are linked to mechanisms that maintain biodiversity across tropical forests. How species survival rates change with size offers insight into the links between biodiversity and ecosystem function across tropical forests. We tested patterns of size-dependent tree survival across the tropics using data from 1781 species and over two million individuals to assess whether tropical forests can be characterized by size-dependent life-history survival strategies. We found species were classifiable into four “survival modes” that explain life-history variation that shapes carbon-cycling and the relative abundances within forests. Frequently collected functional traits, such as wood density, leaf mass per area, and seed mass, were not generally predictive of species’ survival modes. Mean annual temperature and cumulative water deficit predicted the proportion of biomass of survival modes, indicating important links between evolutionary strategies, climate, and carbon cycling. The application of survival modes in demographic simulations predicted biomass change across forest sites. Our results reveal globally identifiable size-dependent survival strategies that differ across diverse systems in a consistent way. The abundance of survival modes and interaction with climate ultimately determine forest structure, carbon storage in biomass, and future forest trajectories.

Johnson, Daniel J.↗

Leaf habit affects the distribution of drought sensitivity but not water transport efficiency in the tropics

Abstract Considering the global intensification of aridity in tropical biomes due to climate change, we need to understand what shapes the distribution of drought sensitivity in tropical plants. We conducted a pantropical data synthesis representing 1117 species to test whether xylem‐specific hydraulic conductivity (K S ), water potential at leaf turgor loss (Ψ TLP ) and water potential at 50% loss of K S (Ψ P50 ) varied along climate gradients. The Ψ TLP and Ψ P50 increased with climatic moisture only for evergreen species, but K S did not. Species with high Ψ TLP and Ψ P50 values were associated with both dry and wet environments. However, drought‐deciduous species showed high Ψ TLP and Ψ P50 values regardless of water availability, whereas evergreen species only in wet environments. All three traits showed a weak phylogenetic signal and a short half‐life. These results suggest strong environmental controls on trait variance, which in turn is modulated by leaf habit along climatic moisture gradients in the tropics.

54 ENVIRONMENTAL SCIENCES↗

Modeling Profiles of Micrometeorological Variables in a Tropical Premontane Rainforest Using Multi-Layered CLM (CLM-ML)

This study updates the multi-layered Community Land Model (CLM-ml) for hillslopes and compares predictions from against observations collected in tropical montane rainforest, Costa Rica. Modifications are made in order to capture a wider array of vertical leaf area distributions, predict CO 2 profiles, account for soil respiration, and adjust wind forcings for difficult topographic settings. Test results indicate that the modified multi-layer CLM model can successfully replicate the shape of various micrometeorological profiles (humidity, CO 2 , temperature, and wind speed) under the canopy. In the single-layer models (CLM4.5 and CLM5), excessive day-to-night differences in leaf temperature and leaf wetness were originally noted, but CLM-ml significantly improved these issues, decreasing the amplitudes of diurnal cycles by 67% and 47%. Sub-canopy considerations, such as canopy shapes and turbulent transfer parameters, also played a significant role in model performance. More importantly, unlike single layer models, the results that CLM-ml produces can be compared to variables measured within the canopy to provide far more detailed diagnostic information. Further observations and model developments, aimed at reflecting surface heterogeneity, will be necessary to adequately capture the complexity and the features of the tropical montane rainforest.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Genetic variation at transcription factor binding sites largely explains phenotypic heritability in maize

Abstract Comprehensive maps of functional variation at transcription factor (TF) binding sites (cis-elements) are crucial for elucidating how genotype shapes phenotype. Here, we report the construction of a pan-cistrome of the maize leaf under well-watered and drought conditions. We quantified haplotype-specific TF footprints across a pan-genome of 25 maize hybrids and mapped over 200,000 variants, genetic, epigenetic, or both (termed binding quantitative trait loci (bQTL)), linked tocis-element occupancy. Three lines of evidence support the functional significance of bQTL: (1) coincidence with causative loci that regulate traits, includingvgt1,ZmTRE1and the MITE transposon nearZmNAC111under drought; (2) bQTL allelic bias is shared between inbred parents and matches chromatin immunoprecipitation sequencing results; and (3) partitioning genetic variation across genomic regions demonstrates that bQTL capture the majority of heritable trait variation across ~72% of 143 phenotypes. Our study provides an auspicious approach to make functionalcis-variation accessible at scale for genetic studies and targeted engineering of complex traits.

Genetics & Heredity↗

Investigating the Diurnal Radiative, Turbulent, and Biophysical Processes in the Amazonian Canopy‐Atmosphere Interface by Combining LES Simulations and Observations

Abstract We investigate the atmospheric diurnal variability inside and above the Amazonian rainforest for a representative day during the dry season. To this end, we combine high‐resolution large‐eddy simulations that are constrained and evaluated against a comprehensive observation set, including CO 2 concentrations, gathered during GoAmazon2014/15. We design systematic numerical experiments to quantify whether a multilayer approach in solving the explicit canopy improves our canopy‐atmosphere representation. We particularly focus on the relationship between photosynthesis and plant transpiration, and their distribution at leaf and canopy scales. We found the variability of photosynthesis drivers like vapor pressure deficit and leaf temperature to be about 3 times larger for sunlit leaves compared to shaded leaves. This leads to a large spread on leaf stomatal conductance values with minimum and maximum values varying more than 100%. Regarding the turbulent structure, we find wind‐driven stripe‐like shapes at the canopy top and structures resembling convective cells at the canopy. Wind‐related variables provide the best spatiotemporal agreement between model and observations. The potential temperature and heat flux profiles agree with an observed decoupling near the canopy top interface, although with less variability and cold biases of up to 3 K. The increasing complexity on the biophysical processes leads to the largest disagreements for evaporation, CO 2 plant assimilation and soil efflux. The model is able to capture the correct dependences and trends with the magnitudes still differing. We finally discuss the need to revise leaf and soil models and to complete the observations at leaf and canopy levels.

54 ENVIRONMENTAL SCIENCES↗

Tracking seasonal variability in plant traits from spaceborne PRISMA and NEON AOP across forest types and ecoregions

Plant traits serve as critical indicators of how plants adapt to environmental changes and influence ecosystem functions. While airborne hyperspectral remote sensing effectively maps plant traits through detailed reflectance properties, it is limited by cost and scale, making large-scale and temporal studies challenging. The recently launched spaceborne hyperspectral imager, PRecursore IperSpettrale della Missione Applicativa (PRISMA), offers frequent, large scale and high-fidelity observations on a spatial resolution of 30 m and a revisit time of around 29 days, making it suitable for large-scale seasonal trait mapping. However, their potential remains largely unexplored. This study developed a multi-stage framework by leveraging the PRISMA spaceborne hyperspectral data and National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP) hyperspectral data to investigate the seasonal dynamics of four key plant traits — chlorophyll content, carotenoid content, equivalent water thickness, and nitrogen content — across eleven NEON sites representing diverse forest types and ecoregions in the contiguous U.S. Our results demonstrated that PRISMA hyperspectral data can reliably track seasonal variability in plant traits, achieving overall R 2 values ranging from 0.78 to 0.88 and normalized root mean square error (NRMSE) values ranging from 5.4% to 8.4% for the four traits. Seasonal patterns revealed bell-shaped trajectories for chlorophyll and carotenoids, while equivalent water thickness decreased steadily across most sites, driven by structural changes during leaf maturation and senescence. Nitrogen content exhibited less pronounced seasonal variation but followed expected nutrient resorption patterns. Analysis of environmental drivers showed that seasonal variability is primarily controlled by solar radiation and day length in northern sites, vapor pressure in semi-arid regions, and temperature in mid-southeastern sites. Spatial variability, meanwhile, was primarily driven by soil properties, particularly during the peak growing season. However, the influence of soil variables slightly declines toward the end of the season at several sites, as climatic factors become more prominent. This study highlights the capability of PRISMA, and potentially other similar spaceborne hyperspectral data for large-scale, time-series plant trait mapping and provides valuable insights into the interactions between plant traits and environmental factors. In conclusion, these findings contribute to advancing our understanding of plant functional ecology and improving predictions of ecosystem responses to environmental changes.

Environmental drivers↗

Convergence in the temperature response of leaf respiration across biomes and plant functional types

Plant respiration constitutes a massive carbon flux to the atmosphere, and a major control on the evolution of the global carbon cycle. It therefore has the potential to modulate levels of climate change due to the human burning of fossil fuels. Neither current physiological nor terrestrial biosphere models adequately describe its short-term temperature response, and even minor differences in the shape of the response curve can significantly impact estimates of ecosystem carbon release and/or storage. Given this, it is critical to establish whether there are predictable patterns in the shape of the respiration–temperature response curve, and thus in the intrinsic temperature sensitivity of respiration across the globe. By analyzing measurements in a comprehensive database for 231 species spanning 7 biomes, we demonstrate that temperature-dependent increases in leaf respiration do not follow a commonly used exponential function. Instead, we find a decelerating function as leaves warm, reflecting a declining sensitivity to higher temperatures that is remarkably uniform across all biomes and plant functional types. Such convergence in the temperature sensitivity of leaf respiration suggests that there are universally applicable controls on the temperature response of plant energy metabolism, such that a single new function can predict the temperature dependence of leaf respiration for global vegetation. This simple function enables straightforward description of plant respiration in the land-surface components of coupled earth system models. Our cross-biome analyses shows significant implications for such fluxes in cold climates, generally projecting lower values compared with previous estimates.

54 ENVIRONMENTAL SCIENCES↗

Hysteresis area at the canopy level during and after a drought event in the Central Amazon

Understanding forest water limitation during droughts within a warming climate is essential for accurate predictions of forest-climate interactions. In hyperdiverse ecosystems like the Amazon forest, the mechanisms shaping hysteresis patterns in transpiration relative to environmental factors are not well understood. From this perspective, we investigated these dynamics by conducting in situ leaf-level measurements throughout and after the 2015 El Niño-Southern Oscillation (ENSO) drought. Our findings indicate a substantial increase in the hysteresis area (H area ) among transpiration (E), vapor pressure deficit (VPD), and stomatal conductance (g s ) at canopy level during the ENSO peak, attributed to both temporal lag and differences in magnitude between g s and VPD peaks. Specifically, the canopy species Pouteria anomala exhibited an increased H area , due to earlier maximum g s rates leading to a greater temporal lag with VPD compared to the post-drought period. Additionally, leaf water potential (ψ L ) and canopy temperature (T canopy ) showed larger H area during the ENSO peak compared to post-drought conditions across all studied species, suggesting that stomatal closure, particularly during the afternoon, acts to minimize water loss and may explain the counterclockwise hysteresis observed between ψ L and T canopy . Here, the pronounced H area during the drought points to a potential imbalance between water supply and demand, underlining the role of stomatal behavior of isohydric species in response to drought.

54 ENVIRONMENTAL SCIENCES↗

The three major axes of terrestrial ecosystem function

The leaf economics spectrum and the global spectrum of plant forms and functions revealed fundamental axes of variation in plant traits, which represent different ecological strategies that are shaped by the evolutionary development of plant species. Ecosystem functions depend on environmental conditions and the traits of species that comprise the ecological communities. However, the axes of variation of ecosystem functions are largely unknown, which limits our understanding of how ecosystems respond as a whole to anthropogenic drivers, climate and environmental variability. Here we derive a set of ecosystem functions from a dataset of surface gas exchange measurements across major terrestrial biomes. We find that most of the variability within ecosystem functions (71.8%) is captured by three key axes. The first axis reflects maximum ecosystem productivity and is mostly explained by vegetation structure. The second axis reflects ecosystem water-use strategies and is jointly explained by variation in vegetation height and climate. The third axis, which represents ecosystem carbon-use efficiency, features a gradient related to aridity, and is explained primarily by variation in vegetation structure. We show that two state-of-the-art land surface models reproduce the first and most important axis of ecosystem functions. However, the models tend to simulate more strongly correlated functions than those observed, which limits their ability to accurately predict the full range of responses to environmental changes in carbon, water and energy cycling in terrestrial ecosystems.

54 ENVIRONMENTAL SCIENCES↗