The three-dimensional construction of leaves is coordinated with water use efficiency in conifers.

Conifers prevail in the canopies of many terrestrial biomes, holding a great ecological and economic importance globally. Current increases in temperature and aridity are imposing high transpirational demands and resulting in conifer mortality. Therefore, identifying leaf structural determinants of water use efficiency is essential for predicting physiological impacts due to environmental variation. Using synchrotron-generated microtomography imaging, we extracted leaf volumetric anatomy and stomatal traits in 34 species across conifers with a special focus on Pinus, the richest conifer genus. We show that intrinsic water use efficiency (WUEi ) is positively driven by leaf vein volume. Needle-like leaves of Pinus, as opposed to flat leaves or flattened needles of other genera, showed lower mesophyll porosity, decreasing the relative mesophyll volume. This led to increased ratios of stomatal pore number per mesophyll or intercellular airspace volume, which emerged as powerful explanatory variables, predicting both stomatal conductance and WUEi . Our results clarify how the three-dimensional organisation of tissues within the leaf has a direct impact on plant water use and carbon uptake. By identifying a suite of structural traits that influence important physiological functions, our findings can help to understand how conifers may respond to the pressures exerted by climate change.

Structural and functional leaf diversity lead to variability in photosynthetic capacity across a range of Juglans regia genotypes.

Similar to other cropping systems, few walnut cultivars are used as scion in commercial production. Germplasm collections can be used to diversify cultivar options and hold potential for improving crop productivity, disease resistance and stress tolerance. In this study, we explored the anatomical and biochemical bases of photosynthetic capacity and response to water stress in 11 Juglans regia accessions in the U.S. department of agriculture, agricultural research service (USDA-ARS) National Clonal Germplasm. Net assimilation rate (An ) differed significantly among accessions and was greater in lower latitudes coincident with higher stomatal and mesophyll conductances, leaf thickness, mesophyll porosity, gas-phase diffusion, leaf nitrogen and lower leaf mass and stomatal density. High CO2 -saturated assimilation rates led to increases in An under diffusional and biochemical limitations. Greater An was found in lower-latitude accessions native to climates with more frost-free days, greater precipitation seasonality and lower temperature seasonality. As expected, water stress consistently impaired photosynthesis with the highest % reductions in lower-latitude accessions (A3, A5 and A9), which had the highest An under well-watered conditions. However, An for A3 and A5 remained among the highest under dehydration. J. regia accessions, which have leaf structural traits and biochemistry that enhance photosynthesis, could be used as commercial scions or breeding parents to enhance productivity.

Maximum CO2 diffusion inside leaves is limited by the scaling of cell size and genome size.

Maintaining high rates of photosynthesis in leaves requires efficient movement of CO2 from the atmosphere to the mesophyll cells inside the leaf where CO2 is converted into sugar. CO2 diffusion inside the leaf depends directly on the structure of the mesophyll cells and their surrounding airspace, which have been difficult to characterize because of their inherently three-dimensional organization. Yet faster CO2 diffusion inside the leaf was probably critical in elevating rates of photosynthesis that occurred among angiosperm lineages. Here we characterize the three-dimensional surface area of the leaf mesophyll across vascular plants. We show that genome size determines the sizes and packing densities of cells in all leaf tissues and that smaller cells enable more mesophyll surface area to be packed into the leaf volume, facilitating higher CO2 diffusion. Measurements and modelling revealed that the spongy mesophyll layer better facilitates gaseous phase diffusion while the palisade mesophyll layer better facilitates liquid-phase diffusion. Our results demonstrate that genome downsizing among the angiosperms was critical to restructuring the entire pathway of CO2 diffusion into and through the leaf, maintaining high rates of CO2 supply to the leaf mesophyll despite declining atmospheric CO2 levels during the Cretaceous.

Spatiotemporal Coupling of Vessel Cavitation and Discharge of Stored Xylem Water in a Tree Sapling.

Water discharge from stem internal storage compartments is thought to minimize the risk of vessel cavitation. Based on this concept, one would expect that water storage compartments involved in the buffering of xylem tensions empty before the onset of vessel cavitation under drought stress, and potentially refill after soil saturation. However, scant in vivo data exist that elucidate this localized spatiotemporal coupling. In this study on intact saplings of American chestnut (Castanea dentata), x-ray computed microtomography (microCT) showed that the xylem matrix surrounding vessels releases stored water and becomes air-filled either concurrent to or after vessel cavitation under progressive drought stress. Among annual growth rings, the xylem matrix of the current year remained largely water-filled even under severe drought stress. In comparison, microtomography images collected on excised stems showed that applied pressures of much greater than 0 MPa were required to induce water release from the xylem matrix. Viability staining highlighted that water release from the xylem matrix was associated primarily with emptying of dead fibers. Refilling of the xylem matrix and vessels was detected in intact saplings when the canopy was bagged and stem water potential was close to 0 MPa, and in leafless saplings over the winter period. In conclusion, this study indicates that the bulk of water stored in the xylem matrix is released after the onset of vessel cavitation, and suggests that capillary water contributes to overall stem water storage under drought but is not used primarily for the prevention of drought-induced vessel cavitation in this species.

Diurnal Variation in Nonstructural Carbohydrate Storage in Trees: Remobilization and Vertical Mixing.

Nonstructural carbohydrate (NSC) storage plays a critical role in tree function and survival, but understanding and predicting local NSC storage dynamics is challenging because NSC storage pools are dispersed throughout the complex architecture of trees and continuously exchange carbon between source and sink organs at different time scales. To address these knowledge gaps, characterization and understanding of NSC diel variation are necessary. Here, we analyzed diurnal NSC dynamics in the overall architecture of almond (Prunus dulcis) trees. We also analyzed the allocation of newly assimilated carbon using isotopic labeling. We show that both components of NSC (i.e. soluble carbohydrates and starch) are highly dynamic at the diurnal time scale and that these trends are influenced by tissue type, age, and/or position within the canopy. In leaves, starch reserves can be depleted completely during the night, while woody tissue starch levels may vary by more than 50% over a daily cycle. Recently assimilated carbon showed a dispersed downward allocation across the entire tree. NSC diurnal fluctuations within the tree's structure in combination with dispersed carbon allocation patterns provide evidence for the presence of vertical mixing and suggest that the xylem acts as a secondary NSC redistribution pathway.

Beyond Porosity: 3D Leaf Intercellular Airspace Traits That Impact Mesophyll Conductance.

The leaf intercellular airspace (IAS) is generally considered to have high conductance to CO2 diffusion relative to the liquid phase. While previous studies accounted for leaf-level variation in porosity and mesophyll thickness, they omitted 3D IAS traits that potentially influence IAS conductance (gIAS). Here, we reevaluated the standard equation for gIAS by incorporating tortuosity, lateral path lengthening, and IAS connectivity. We measured and spatially mapped these geometric IAS traits for 19 Bromeliaceae species with Crassulacean acid metabolism (CAM) or C3 photosynthetic pathways using x-ray microcomputed tomography imaging and a novel computational approach. We found substantial variation in porosity (0.04-0.73 m3 m-3), tortuosity (1.09-3.33 m2 m-2), lateral path lengthening (1.12-3.19 m m-1), and IAS connectivity (0.81-0.97 m2 m-2) across all bromeliad leaves. The revised gIAS model predicted significantly lower gIAS in CAM (0.01-0.19 mol m-2 s-1 bar-1) than in C3 (0.41-2.38 mol m-2 s-1 bar-1) plants due to a coordinated decline in these IAS traits. Our reevaluated equation also generally predicted lower gIAS values than the former one. Moreover, we observed high spatial heterogeneity in these IAS geometric traits throughout the mesophyll, especially within CAM leaves. Our data show that IAS traits that better capture the 3D complexity of leaves strongly influence gIAS and that the impact of the IAS on mesophyll conductance should be carefully considered with respect to leaf anatomy. We provide a simple function to estimate tortuosity and lateral path lengthening in the absence of access to imaging tools such as x-ray microcomputed tomography or other novel 3D image-processing techniques.

Extreme mid-winter drought weakens tree hydraulic-carbohydrate systems and slows growth.

Rising temperatures and extended periods of drought compromise tree hydraulic and carbohydrate systems, threatening forest health globally. Despite winter's biological significance to many forests, the effects of warmer and dryer winters on tree hydraulic and carbohydrate status have largely been overlooked. Here we report a sharp and previously unknown decline in stem water content of three conifer species during California's anomalous 2015 mid-winter drought that was followed by dampened spring starch accumulation. Recent precipitation and seasonal vapor pressure deficit (VPD) anomaly, not absolute VPD, best predicted the hydraulic patterns observed. By linking relative water content and hydraulic conductivity (Kh ), we estimated that stand-level Kh declined by 52% during California's 2015 mid-winter drought, followed by a 50% reduction in spring starch accumulation. Further examination of tree increment records indicated a concurrent decline of growth with rising mid-winter, but not summer, VPD anomaly. Thus, our findings suggest a seasonality to tree hydraulic and carbohydrate declines, with consequences for annual growth rates, raising novel physiological and ecological questions about how rising winter temperatures will affect forest vitality as climate changes.

In vivo quantification of plant starch reserves at micrometer resolution using X-ray microCT imaging and machine learning.

Starch is the primary energy storage molecule used by most terrestrial plants to fuel respiration and growth during periods of limited to no photosynthesis, and its depletion can drive plant mortality. Destructive techniques at coarse spatial scales exist to quantify starch, but these techniques face methodological challenges that can lead to uncertainty about the lability of tissue-specific starch pools and their role in plant survival. Here, we demonstrate how X-ray microcomputed tomography (microCT) and a machine learning algorithm can be coupled to quantify plant starch content in vivo, repeatedly and nondestructively over time in grapevine stems (Vitis spp.). Starch content estimated for xylem axial and ray parenchyma cells from microCT images was correlated strongly with enzymatically measured bulk-tissue starch concentration on the same stems. After validating our machine learning algorithm, we then characterized the spatial distribution of starch concentration in living stems at micrometer resolution, and identified starch depletion in live plants under experimental conditions designed to halt photosynthesis and starch production, initiating the drawdown of stored starch pools. Using X-ray microCT technology for in vivo starch monitoring should enable novel research directed at resolving the spatial and temporal patterns of starch accumulation and depletion in woody plant species.

Excess Diffuse Light Absorption in Upper Mesophyll Limits CO2 Drawdown and Depresses Photosynthesis.

In agricultural and natural systems, diffuse light can enhance plant primary productivity due to deeper penetration into and greater irradiance of the entire canopy. However, for individual sun-grown leaves from three species, photosynthesis is actually less efficient under diffuse compared with direct light. Despite its potential impact on canopy-level productivity, the mechanism for this leaf-level diffuse light photosynthetic depression effect is unknown. Here, we investigate if the spatial distribution of light absorption relative to electron transport capacity in sun- and shade-grown sunflower (Helianthus annuus) leaves underlies its previously observed diffuse light photosynthetic depression. Using a new one-dimensional porous medium finite element gas-exchange model parameterized with light absorption profiles, we found that weaker penetration of diffuse versus direct light into the mesophyll of sun-grown sunflower leaves led to a more heterogenous saturation of electron transport capacity and lowered its CO2 concentration drawdown capacity in the intercellular airspace and chloroplast stroma. This decoupling of light availability from photosynthetic capacity under diffuse light is sufficient to generate an 11% decline in photosynthesis in sun-grown but not shade-grown leaves, primarily because thin shade-grown leaves similarly distribute diffuse and direct light throughout the mesophyll. Finally, we illustrate how diffuse light photosynthetic depression could overcome enhancement in canopies with low light extinction coefficients and/or leaf area, pointing toward a novel direction for future research.

Storage Compartments for Capillary Water Rarely Refill in an Intact Woody Plant.

Water storage is thought to play an integral role in the maintenance of whole-plant water balance. The contribution of both living and dead cells to water storage can be derived from rehydration and water-release curves on excised plant material, but the underlying tissue-specific emptying/refilling dynamics remain unclear. Here, we used x-ray computed microtomography to characterize the refilling of xylem fibers, pith cells, and vessels under both excised and in vivo conditions in Laurus nobilis In excised stems supplied with water, water uptake exhibited a biphasic response curve, and x-ray computed microtomography images showed that high water storage capacitance was associated with fiber and pith refilling as driven by capillary forces: fibers refilled more rapidly than pith cells, while vessel refilling was minimal. In excised stems that were sealed, fiber and pith refilling was associated with vessel emptying, indicating a link between tissue connectivity and water storage. In contrast, refilling of fibers, pith cells, and vessels was negligible in intact saplings over two time scales, 24 h and 3 weeks. However, those compartments did refill slowly when the shoot was covered to prevent transpiration. Collectively, our data (1) provide direct evidence that storage compartments for capillary water refill in excised stems but rarely under in vivo conditions, (2) highlight that estimates of capacitance from excised samples should be interpreted with caution, as certain storage compartments may not be utilized in the intact plant, and (3) question the paradigm that fibers play a substantial role in daily discharge/recharge of stem capacitance in an intact tree.

Long-term climate and competition explain forest mortality patterns under extreme drought.

Rising temperatures are amplifying drought-induced stress and mortality in forests globally. It remains uncertain, however, whether tree mortality across drought-stricken landscapes will be concentrated in particular climatic and competitive environments. We investigated the effects of long-term average climate [i.e. 35-year mean annual climatic water deficit (CWD)] and competition (i.e. tree basal area) on tree mortality patterns, using extensive aerial mortality surveys conducted throughout the forests of California during a 4-year statewide extreme drought lasting from 2012 to 2015. During this period, tree mortality increased by an order of magnitude, typically from tens to hundreds of dead trees per km2 , rising dramatically during the fourth year of drought. Mortality rates increased independently with average CWD and with basal area, and they increased disproportionately in areas that were both dry and dense. These results can assist forest managers and policy-makers in identifying the most drought-vulnerable forests across broad geographic areas.

Spring bud growth depends on sugar delivery by xylem and water recirculation by phloem Münch flow in Juglans regia.

MAIN CONCLUSION: During spring, bud growth relies on long-distance transport of remotely stored carbohydrates. A new hypothesis suggests this transport is achieved by the interplay of xylem and phloem. During the spring, carbohydrate demand of developing buds often exceeds locally available storage, thus requiring the translocation of sugars from distant locations like limbs, stems and roots. Both the phloem and xylem have the capacity for such long-distance transport, but their functional contribution is unclear. To address this ambiguity, the spatial and temporal dynamics of carbohydrate availability in extension shoots of Juglans regia L. were analyzed. A significant loss of extension shoot carbohydrates in remote locations was observed while carbohydrate availability near the buds remained unaffected. This pattern of depletion of carbohydrate reserves supports the notion of long-distance translocation. Girdling and dye perfusion experiments were performed to assess the role of phloem and xylem in the transport of carbohydrate and water towards the buds. Girdling caused a decrease in non-structural carbohydrate concentration above the point of girdling and an unexpected concurrent increase in water content associated with impeded xylem transport. Based on experimental observations and modeling, we propose a novel mechanism for maintenance of spring carbohydrate translocation in trees where xylem transports carbohydrates and this transport is maintained with the recirculation of water by phloem Münch flow. Phloem Münch flow acts as a pump for generating water flux in xylem and allows for transport and mobilization of sugars from distal locations prior to leaves photosynthetic independence and in the absence of transpiration.

The bias of a two-dimensional view: comparing two-dimensional and three-dimensional mesophyll surface area estimates using noninvasive imaging.

The mesophyll surface area exposed to intercellular air space per leaf area (Sm ) is closely associated with CO2 diffusion and photosynthetic rates. Sm is typically estimated from two-dimensional (2D) leaf sections and corrected for the three-dimensional (3D) geometry of mesophyll cells, leading to potential differences between the estimated and actual cell surface area. Here, we examined how 2D methods used for estimating Sm compare with 3D values obtained from high-resolution X-ray microcomputed tomography (microCT) for 23 plant species, with broad phylogenetic and anatomical coverage. Relative to 3D, uncorrected 2D Sm estimates were, on average, 15-30% lower. Two of the four 2D Sm methods typically fell within 10% of 3D values. For most species, only a few 2D slices were needed to accurately estimate Sm within 10% of the whole leaf sample median. However, leaves with reticulate vein networks required more sections because of a more heterogeneous vein coverage across slices. These results provide the first comparison of the accuracy of 2D methods in estimating the complex 3D geometry of internal leaf surfaces. Because microCT is not readily available, we provide guidance for using standard light microscopy techniques, as well as recommending standardization of reporting Sm values.

Wildfire and drought dynamics destabilize carbon stores of fire-suppressed forests.

Widespread fire suppression and thinning have altered the structure and composition of many forests in the western United States, making them more susceptible to the synergy of large-scale drought and fire events. We examine how these changes affect carbon storage and stability compared to historic fire-adapted conditions. We modeled carbon dynamics under possible drought and fire conditions over a 300-year simulation period in two mixed-conifer conditions common in the western United States: (1) pine-dominated with an active fire regime and (2) fir-dominated, fire suppressed forests. Fir-dominated stands, with higher live- and dead-wood density, had much lower carbon stability as drought and fire frequency increased compared to pine-dominated forest. Carbon instability resulted from species (i.e., fir's greater susceptibility to drought and fire) and stand (i.e., high density of smaller trees) conditions that develop in the absence of active management. Our modeling suggests restoring historic species composition and active fire regimes can significantly increase carbon stability in fire-suppressed, mixed-conifer forests. Long-term management of forest carbon should consider the relative resilience of stand structure and composition to possible increases in disturbance frequency and intensity under changing climate.

AI-enabled biosensing for rapid pathogen detection: From liquid food to agricultural water.

Rapid pathogen detection in food and agricultural water is essential for ensuring food safety and public health. However, complex and noisy environmental background matrices delay the identification of pathogens and require highly trained personnel. Here, we present an AI-biosensing framework for accelerated and automated pathogen detection in various water samples, from liquid food to agricultural water. A deep learning model was used to identify and quantify target bacteria based on their microscopic patterns generated by specific interactions with bacteriophages. The model was trained on augmented datasets to maximize data efficiency, using input images of selected bacterial species, and then fine-tuned on a mixed culture. Model inference was performed on real-world water samples containing environmental noises unseen during model training. Overall, our AI model trained solely on lab-cultured bacteria achieved rapid (< 5.5 h) prediction with 80-100% accuracy on the real-world water samples, demonstrating its ability to generalize to unseen data. Our study highlights the potential applications in microbial water quality monitoring during food and agricultural processes.

A workflow for segmenting soil and plant X-ray computed tomography images with deep learning in Google's Colaboratory.

X-ray micro-computed tomography (X-ray µCT) has enabled the characterization of the properties and processes that take place in plants and soils at the micron scale. Despite the widespread use of this advanced technique, major limitations in both hardware and software limit the speed and accuracy of image processing and data analysis. Recent advances in machine learning, specifically the application of convolutional neural networks to image analysis, have enabled rapid and accurate segmentation of image data. Yet, challenges remain in applying convolutional neural networks to the analysis of environmentally and agriculturally relevant images. Specifically, there is a disconnect between the computer scientists and engineers, who build these AI/ML tools, and the potential end users in agricultural research, who may be unsure of how to apply these tools in their work. Additionally, the computing resources required for training and applying deep learning models are unique, more common to computer gaming systems or graphics design work, than to traditional computational systems. To navigate these challenges, we developed a modular workflow for applying convolutional neural networks to X-ray µCT images, using low-cost resources in Google's Colaboratory web application. Here we present the results of the workflow, illustrating how parameters can be optimized to achieve best results using example scans from walnut leaves, almond flower buds, and a soil aggregate. We expect that this framework will accelerate the adoption and use of emerging deep learning techniques within the plant and soil sciences.

Improving the environmental profile of wood panels via co-production of ethanol and acetic acid.

The oriented strand board (OSB) biorefinery is an emerging technology that could improve the building, transportation, and chemical sectors' environmental profiles. By adding a hot water extraction stage to conventional OSB panel manufacturing, hemicellulose polysaccharides can be extracted from wood strands and converted to renewably sourced ethanol and acetic acid. Replacing fossil-based gasoline and acetic acid has the potential to reduce greenhouse gas (GHG) emissions, among other possible impacts. At the same time, hemicellulose extraction could improve the environmental profile of OSB panels by reducing the level of volatile organic compounds (VOCs) emitted during manufacturing. In this study, the life cycle significance of such GHG, VOC, and other emission reductions was investigated. A process model was developed based on a mix of laboratory and industrial-level mass and energy flow data. Using these data a life cycle assessment (LCA) model was built. Sensitive process parameters were identified and used to develop a target production scenario for the OSB biorefinery. The findings suggest that the OSB biorefinery's deployment could substantially improve human and ecosystem health via reduction of select VOCs compared to conventionally produced OSB, gasoline, and acetic acid. Technological advancements are needed, however, to achieve desirable GHG reductions.

Digitally deconstructing leaves in 3D using X-ray microcomputed tomography and machine learning.

PREMISE: X-ray microcomputed tomography (microCT) can be used to measure 3D leaf internal anatomy, providing a holistic view of tissue organization. Previously, the substantial time needed for segmenting multiple tissues limited this technique to small data sets, restricting its utility for phenotyping experiments and limiting our confidence in the inferences of these studies due to low replication numbers. METHODS AND RESULTS: We present a Python codebase for random forest machine learning segmentation and 3D leaf anatomical trait quantification that dramatically reduces the time required to process single-leaf microCT scans into detailed segmentations. By training the model on each scan using six hand-segmented image slices out of >1500 in the full leaf scan, it achieves >90% accuracy in background and tissue segmentation. CONCLUSIONS: Overall, this 3D segmentation and quantification pipeline can reduce one of the major barriers to using microCT imaging in high-throughput plant phenotyping.

Embracing 3D Complexity in Leaf Carbon-Water Exchange.

Leaves are a nexus for the exchange of water, carbon, and energy between terrestrial plants and the atmosphere. Research in recent decades has highlighted the critical importance of the underlying biophysical and anatomical determinants of CO2 and H2O transport, but a quantitative understanding of how detailed 3D leaf anatomy mediates within-leaf transport has been hindered by the lack of a consensus framework for analyzing or simulating transport and its spatial and temporal dynamics realistically, and by the difficulty of measuring within-leaf transport at the appropriate scales. We discuss how recent technological advancements now make a spatially explicit 3D leaf analysis possible, through new imaging and modeling tools that will allow us to address long-standing questions related to plant carbon-water exchange.

Frost Induces Respiration and Accelerates Carbon Depletion in Trees.

Cellular respiration depletes stored carbohydrates during extended periods of limited photosynthesis, e.g. winter dormancy or drought. As respiration rate is largely a function of temperature, the thermal conditions during such periods may affect non-structural carbohydrate (NSC) availability and, ultimately, recovery. Here, we surveyed stem responses to temperature changes in 15 woody species. For two species with divergent respirational response to frost, P. integerrima and P. trichocarpa, we also examined corresponding changes in NSC levels. Finally, we simulated respiration-induced NSC depletion using historical temperature data for the western US. We report a novel finding that tree stems significantly increase respiration in response to near freezing temperatures. We observed this excess respiration in 13 of 15 species, deviating 10% to 170% over values predicted by the Arrhenius equation. Excess respiration persisted at temperatures above 0 °C during warming and reoccurred over multiple frost-warming cycles. A large adjustment of NSCs accompanied excess respiration in P. integerrima, whereas P. trichocarpa neither excessively respired nor adjusted NSCs. Over the course of the years included in our model, frost-induced respiration accelerated stem NSC consumption by 8.4 mg (glucose eq.) cm(-3) yr(-1) on average in the western US, a level of depletion that may continue to significantly affect spring NSC availability. This novel finding revises the current paradigm of low temperature respiration kinetics.