Rising atmospheric CO(2 )levels place terrestrial ecosystems under novel environmental conditions, and research in field settings is key to understanding how real plant communities will respond. Despite decades of progress in elevated CO2 (eCO(2)) experiments, major gaps persist in our knowledge of plant responses to interacting influences of climate change, especially in areas outside North America and Western Europe. With a goal to expand access to field-based eCO(2) research, we designed, built, and tested TinyCO(2), a low-cost field experiment for climate change research on plants. TinyCO(2) features sixteen 0.62-m(2) plot areas, half with ambient and half with elevated (+200 ppm) CO2 concentrations, and is suitable for short-stature plants (<= 0.5 m in height). Using a proportional-integral control algorithm and constant sampling of air within the plots, TinyCO(2) achieves consistent elevation of [CO2] averaging +196.9 ppm. During testing, 95.1% of measured CO2 concentrations fell within 20% of the setpoint (ambient CO2 + 200 ppm). A streamlined design and efficient use of instrumentation reduced the cost of the system to roughly one-fifth of the cost of similar experiments from the past 30 years ($13.68 vs. $64.65 ppm-1 m(-2), adjusted to 2024 USD). Our results demonstrate a system capable of precise and accurate field-based CO2 elevation for significantly reduced cost. We envision the TinyCO(2) design being implemented in a multitude of field-based eCO(2) studies, perhaps as part of a globally distributed collaborative network experiment.

Grapevine (Vitis vinifera L.) stomata are highly sensitive to atmospheric changes and influence the tradeoff between water and carbon, as estimated by intrinsic water use efficiency (iWUE). The aim of this study was to examine how elevated CO2 concentrations and water deficit affect the iWUE and whole plant evapotranspiration of two grapevine varieties (cv. Cabernet Sauvignon and cv. Chardonnay). Dormant cuttings were collected from a vineyard in Temecula Valley, CA, and were grown in a growth chamber under one of two CO2 treatments: near ambient (410 ppm) or elevated (700 ppm). After 8 weeks of vegetative growth, grapevines were subjected to a well-watered (25% soil water content [SWC]) or gradual water-deficit treatment implemented over 12 days. We measured leaf gas exchange, including photosynthesis (Anet), stomatal conductance (gs), intercellular carbon (Ci), and calculated iWUE (Anet/gs), as well as daily cumulative evapotranspiration per unit leaf area (g cm−2 day−1). Vines were harvested to determine total dry weight, root mass fraction, and nitrogen content. We found that elevated CO2 and water deficit interactively increased the iWUE for both varieties, with Cabernet Sauvignon having 20% greater iWUE than Chardonnay at ~5% SWC. Chardonnay exhibited greater maximum conductance, and 43% more water transpired than Cabernet Sauvignon under a well-watered treatment. Chardonnay plants were also more impacted by elevated CO2 and water-deficit treatment than Cabernet Sauvignon, exhibiting greater stomatal sensitivity under these treatments. At ambient CO2, water deficit negatively impacted Chardonnay’s photosynthesis than Cabernet Sauvignon. However, this effect was not observed at elevated CO2. This study elucidates the intraspecific differences in stomatal behaviour, productivity, and water use of two V. vinifera L. genotypes (Cabernet Sauvignon and Chardonnay), under elevated CO2 concentrations and short-term water deficit.

Plants differ widely in how soil drying affects stomatal conductance (gs) and leaf water potential (ψleaf), and in the underlying physiological controls. Efforts to breed crops for drought resilience would benefit from a better understanding of these mechanisms and their diversity. We grew 12 diverse genotypes of common bean (Phaseolus vulgaris L.) and four of tepary bean (P. acutifolius; a highly drought resilient species) in the field under irrigation and post-flowering drought, and quantified responses of gs and ψleaf, and their controls (soil water potential [ψsoil], evaporative demand [Δw] and plant hydraulic conductance [K]). We hypothesised that (i) common beans would be more "isohydric" (i.e., exhibit strong stomatal closure in drought, minimising ψleaf decline) than tepary beans, and that genotypes with larger ψleaf decline (more "anisohydric") would exhibit (ii) smaller increases in Δw, due to less suppression of evaporative cooling by stomatal closure and hence less canopy warming, but (iii) larger K declines due to ψleaf decline. Contrary to our hypotheses, we found that half of the common bean genotypes were similarly anisohydric to most tepary beans; canopy temperature was cooler in isohydric genotypes leading to smaller increases in Δw in drought; and that stomatal closure and K decline were similar in isohydric and anisohydric genotypes. gs and ψleaf were virtually insensitive to drought in one tepary genotype (G40068). Our results highlight the potential importance of non-stomatal mechanisms for leaf cooling, and the variability in drought resilience traits among closely related crop legumes.

Maize (Zea mays), a major food crop worldwide, is susceptible to infection by the saprophytic fungus Aspergillus flavus that can produce the carcinogenic metabolite aflatoxin (AF) especially under climate change induced abiotic stressors that favor mold growth. Several studies have used “-omics” approaches to identify genetic elements with potential roles in AF resistance, but there is a lack of research identifying the involvement of small RNAs such as microRNAs (miRNAs) in maize-A. flavus interaction. In this study, we compared the miRNA profiles of three maize lines (resistant TZAR102, moderately resistant MI82, and susceptible Va35) at 8 h, 3 d, and 7 d after A. flavus infection to investigate possible regulatory antifungal role of miRNAs. A total of 316 miRNAs (275 known and 41 putative novel) belonging to 115 miRNA families were identified in response to the fungal infection across all three maize lines. Eighty-two unique miRNAs were significantly differentially expressed with 39 miRNAs exhibiting temporal differential regulation irrespective of the maize genotype, which targeted 544 genes (mRNAs) involved in diverse molecular functions. The two most notable biological processes involved in plant immunity, namely cellular responses to oxidative stress (GO:00345990) and reactive oxygen species (GO:0034614) were significantly enriched in the resistant line TZAR102. Coexpression network analysis identified 34 hubs of miRNA-mRNA pairs where nine hubs had a node in the module connected to their target gene with potentially important roles in resistance/susceptible response of maize to A. flavus. The miRNA hubs in resistance modules (TZAR102 and MI82) were mostly connected to transcription factors and protein kinases. Specifically, the module of miRNA zma-miR156b-nb – squamosa promoter binding protein (SBP), zma-miR398a-3p – SKIP5, and zma-miR394a-5p – F-box protein 6 combinations in the resistance-associated modules were considered important candidates for future functional studies.

Proximal remote sensing offers a powerful tool for high-throughput phenotyping of plants for assessing stress response. Bean plants, an important legume for human consumption, are often grown in regions with limited rainfall and irrigation and are therefore bred to further enhance drought tolerance. We assessed physiological (stomatal conductance and predawn and midday leaf water potential) and ground- and tower-based hyperspectral remote sensing (400 to 2,400 nm and 400 to 900 nm, respectively) measurements to evaluate drought response in 12 common bean and 4 tepary bean genotypes across 3 field campaigns (1 predrought and 2 post-drought). Hyperspectral data in partial least squares regression models predicted these physiological traits (R2 = 0.20 to 0.55; root mean square percent error 16% to 31%). Furthermore, ground-based partial least squares regression models successfully ranked genotypic drought responses similar to the physiologically based ranks. This study demonstrates applications of high-resolution hyperspectral remote sensing for predicting plant traits and phenotyping drought response across genotypes for vegetation monitoring and breeding population screening.

Remote sensing instruments enable high-throughput phenotyping of plant traits and stress resilience across scale. Spatial (handheld devices, towers, drones, airborne, and satellites) and temporal (continuous or intermittent) tradeoffs can enable or constrain plant science applications. Here, we describe the technical details of TSWIFT (Tower Spectrometer on Wheels for Investigating Frequent Timeseries), a mobile tower-based hyperspectral remote sensing system for continuous monitoring of spectral reflectance across visible-near infrared regions with the capacity to resolve solar-induced fluorescence (SIF). We demonstrate potential applications for monitoring short-term (diurnal) and long-term (seasonal) variation of vegetation for high-throughput phenotyping applications. We deployed TSWIFT in a field experiment of 300 common bean genotypes in two treatments: control (irrigated) and drought (terminal drought). We evaluated the normalized difference vegetation index (NDVI), photochemical reflectance index (PRI), and SIF, as well as the coefficient of variation (CV) across the visible-near infrared spectral range (400 to 900 nm). NDVI tracked structural variation early in the growing season, following initial plant growth and development. PRI and SIF were more dynamic, exhibiting variation diurnally and seasonally, enabling quantification of genotypic variation in physiological response to drought conditions. Beyond vegetation indices, CV of hyperspectral reflectance showed the most variability across genotypes, treatment, and time in the visible and red-edge spectral regions. TSWIFT enables continuous and automated monitoring of hyperspectral reflectance for assessing variation in plant structure and function at high spatial and temporal resolutions for high-throughput phenotyping. Mobile, tower-based systems like this can provide short- and long-term datasets to assess genotypic and/or management responses to the environment, and ultimately enable the spectral prediction of resource-use efficiency, stress resilience, productivity and yield.

1. Day-to-day synchrony between flower opening and pollinator activity is important for maximizing plant fitness. A succulent, Bulbine frutescens (L.) Willd., is an ideal model for studying synchrony in response to daily weather as it flowers year-round. Additionally, it has self-incompatible flowers that open for just one day, making it essential that flower opening matches pollinator activity. 2. Observations were made on urban plants in California, USA, with validation measurements in the native range in South Africa. Independent observations indicated that flowers open primarily after favourable conditions the previous day, specifically air temperatures above 15 degrees C. Solar radiation was experimentally shown to have limited, but significant effects. Pollinators, mostly bee species, had similar temperature thresholds to flowers. 3. Developmental constraints on flowers were hypothesized to delay opening by a day. Flower bud growth was closely related to temperature, with warm days resulting in sufficient growth for buds to become competent to open the following day. Laboratory experiments demonstrated that competent flowers were suppressed from opening until at least 16 h was accumulated in which temperatures were above 12 degrees C; thus, on many cool days, sufficient development to cause flower opening would only occur a day after favourable weather. 4. Based upon regression models of pollinator and flower response to weather, fitness was estimated as a function of synchrony, over 20 years of weather from California and across the natural range in South Africa. Flowers responding to either the previous day's or current day's weather resulted in similar predicted fitness, with flower response to the current day's weather leading to a slightly higher cost, that is, flowers opened when pollinators would be absent. 5. Multiple temperature responsive constraints on bud growth and development result in delays in flower opening, such that flower opening occurs the day after favourable weather. Given the high correlation between daily temperatures in USA and South African winter-rainfall environments, behaviour predicting the following day's weather results in high fitness. Many pollinators share similar temperature thresholds for activity, thus diverse plants may have evolved predictive behaviour maximizing daily synchrony between pollinators and flower opening.

Historical photographs are windows into the past. By comparing historical and modern photographs we can measure change; but how do we find the original camera location to repeat a photograph? Historical, geographic, topographic, and other clues may be used, but we lack a numerical method suitable for any user to find the general location of a historical photograph. We derive a geometric method that can be applied in the field or prior. The method uses measurements of at least three points of reference (POR) in the historical photograph and corresponding geographic locations measured via a compass or on a map. rePhoto, an open-source R package that applies the method and outputs spatial KML files for use with Google Earth, is provided. The geometric method was tested on 20 photographs with known locations and validated by independent users. The effectiveness of the method varied among users, but overall predicted a search area containing the original camera location 70% of the time (the prediction accuracy) and typically predicted search areas 99.5% smaller than the total region evaluated by the method. The method was robust regardless of whether three or four POR were used, and worked well even when POR were more than 30 km away. The proposed method only works for photographs with at least three identifiable geographic POR, thus other methods are illustrated for use more generally. California and the western USA have numerous iconic historical photographs, for which many locations could be found and re-photographed using methods described here.

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.

Leaves balance CO2 and radiative absorption while maintaining water transport to maximise photosynthesis. Related species with contrasting leaf anatomy can provide insights into inherent and stress-induced links between structure and function for commonly measured leaf traits for important crops. We used two walnut species with contrasting mesophyll anatomy to evaluate these integrated exchange processes under non-stressed and drought conditions using a combination of light microscopy, X-ray microCT, gas exchange, hydraulic conductance, and chlorophyll distribution profiles through leaves. Juglans regia had thicker palisade mesophyll, higher fluorescence in the palisade, and greater low-mesophyll porosity that were associated with greater gas-phase diffusion (gIAS ), stomatal and mesophyll (gm ) conductances and carboxylation capacity. More and highly-packed mesophyll cells and bundle sheath extensions (BSEs) in Juglans microcarpa led to higher fluorescence in the spongy and in proximity to the BSEs. Both species exhibited drought-induced reductions in mesophyll cell volume, yet the associated increases in porosity and gIAS were obscured by declines in biochemical activity that decreased gm . Inherent differences in leaf anatomy between the species were linked to differences in gas exchange, light absorption and photosynthetic capacity, and drought-induced changes in leaf structure impacted performance via imposing species-specific limitations to light absorption, gas exchange and hydraulics.

More frequent, intense, and more extended droughts and heatwaves are challenging agricultural productivity and management. This study introduces a new modeling approach to represent the impact of heat and water stress on energy and mass fluxes from orchards. A photosynthesis model that explicitly accounts for dynamic responses of Rubisco and RuBP limitations to stress was linked to the Advanced Canopy-Atmosphere-Soil Algorithm (ACASA). ACASA is a multilayer soil-vegetation-atmosphere numerical model based on higher-order closure of turbulence equations to calculate plant-atmosphere exchanges of carbon dioxide, water, and heat. Field measurements of leaf area index, stomatal conductance, and photosynthesis were performed to estimate model parameters. Model results were compared to data from an eddy covariance flux tower deployed at an almond orchard. Overall, this new approach, ACASA-DynPM, is in closer agreement with observations of H, lambda E, and F, compared to ACASA. On days of high temperatures and water stress, ACASA-DynPM outperforms ACASA. Thus, we argue that accounting for plant physiological stress might be especially relevant when estimating energy and mass fluxes over intensively irrigated agricultural regions. Such biases can have implications for the modeled degree of crop stress and water demands, and eventually, it can impact climate regional estimates when coupled with an atmospheric model.

Climate change adaptation requires building agricultural system resilience to warmer, drier climates. Increasing temporal plant diversity through crop rotation diversification increases yields of some crops under drought, but its potential to enhance crop drought resistance and the underlying mechanisms remain unclear. We conducted a drought manipulation experiment using rainout shelters embedded within a 36-year crop rotation diversity and no-till experiment in a temperate climate and measured a suite of soil and crop developmental and eco-physiological traits in the field and laboratory. We show that diversifying maize-soybean rotations with small grain cereals and cover crops mitigated maize water stress at the leaf and canopy scales and reduced yield losses to drought by 17.1 ± 6.1%, while no-till did not affect maize drought resistance. Path analysis showed a strong correlation between soil organic matter and lower maize water stress despite no significant differences in soil organic matter between rotations or tillage treatments. This positive relationship between soil organic matter and maize water status was not mediated by higher soil water retention or infiltration as often hypothesized, nor differential depth of root water uptake as measured with stable isotopes, suggesting that other mechanisms are at play. Crop rotation diversification is an underappreciated drought management tool to adapt crop production to climate change through managing for soil organic matter.

Aspergillus flavus is a facultative pathogen capable of producing aflatoxins (AF), potent carcinogens that accumulate in corn kernels, peanuts, cottonseed and tree nuts. To understand resistance mechanisms in corn to AF accumulation we performed a high-throughput genomics study using an in vitro kernel screening assay with A. flavus 3357, resistant corn hybrid TZAR102 and susceptible corn hybrid Va35. Furthermore, we incorporated gene expression data with genomic data to perform redundancy analysis (RDA). We determined that corn genotype, fungal treatment and duration of infection significantly co-vary to influence the overall gene expression patterns. We performed gene ontology enrichment analysis on highly significant genes and found enrichment of pathways linked to fungal and microbial responses such as Pathogenesis-related (PR) proteins. To determine additional genes of interest using field and gene expression data, we linked genome-wide association analysis results with gene expression data, allowing us to detect significant expression quantitative trait loci (eQTL). Our results showed that resistance to aflatoxin contamination is a polygenic trait and found significant association between specific flavonoid biosynthetic pathway genes and infection by A. flavus. Additional experiments including functional genomics analyses and fungal bioassays to identify the role of flavonoids and their contribution to corn resistance to A. flavus growth and AF production will also be presented.

Maintaining high rates of photosynthesis in leaves requires efficient movement of CO 2 from the atmosphere to the mesophyll cells inside the leaf where CO 2 is converted into sugar. CO 2 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 CO 2 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 CO 2 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 CO 2 diffusion into and through the leaf, maintaining high rates of CO 2 supply to the leaf mesophyll despite declining atmospheric CO 2 levels during the Cretaceous.

Sap velocity measurements are useful in fields ranging from plant water relations to hydrology at a variety of scales. Techniques based on pulses of heat are among the most common methods to measure sap velocity, but most lack ability to measure velocities across a wide range, including very high, very low and negative velocities (reverse flow). We propose a new method, the double-ratio method (DRM), which is robust across an unprecedented range of sap velocities and provides real-time estimates of the thermal diffusivity of wood. The DRM employs one temperature sensor upstream (proximal) and two sensors downstream (distal) to the source of heat. This facilitates several theoretical, heat-based approaches to quantifying sap velocity. We tested the DRM using whole-tree lysimetry in Eucalyptus cypellocarpa L.A.S. Johnson and found strong agreement across a wide range of velocities.

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 likely 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.

Sap velocity measurements are useful in fields ranging from plant water relations to hydrology at a range of scales. Heat-pulse based techniques are among the most common methods to measure sap velocity, but most lack the ability to measure velocities across a wide range, including very high, very low and negative velocities (reverse flow). We propose a new method, the double-ratio method (DRM), which is robust across an unprecedented range of sap velocities and can provide real-time estimates of the thermal diffusivity of wood. The DRM employs one temperature sensor proximal and two distal to the heat pulse probe and facilitates several theoretical, heat-based approaches to quantifying sap velocity. We tested the DRM using whole-tree lysimetry in Eucalyptus cypellocarpa and found strong agreement across a wide range of velocities.

High CO2 concentrations stimulate net photosynthesis by increasing CO2 substrate availability for Rubisco, simultaneously suppressing photorespiration. Previously, we reported that silencing the chloroplast vesiculation (cv) gene in rice increased source fitness, through the maintenance of chloroplast stability and the expression of photorespiration-associated genes. Because high atmospheric CO2 conditions diminished photorespiration, we tested whether CV silencing might be a viable strategy to improve the effects of high CO2 on grain yield and N assimilation in rice. Under elevated CO2, OsCV expression was induced, and OsCV was targeted to peroxisomes where it facilitated the removal of OsPEX11-1 from the peroxisome and delivered it to the vacuole for degradation. This process correlated well with the reduction in the number of peroxisomes, the decreased catalase activity and the increased H2O2 content in wild-type plants under elevated CO2. At elevated CO2, CV-silenced rice plants maintained peroxisome proliferation and photorespiration and displayed higher N assimilation than wild-type plants. This was supported by higher activity of enzymes involved in NO3- and NH4+ assimilation and higher total and seed protein contents. Co-immunoprecipitation of OsCV-interacting proteins suggested that, similar to its role in chloroplast protein turnover, OsCV acted as a scaffold, binding peroxisomal proteins.