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The connection between soil nitrogen availability, leaf nitrogen, and photosynthetic capacity is not perfectly understood. Because these three components tend to be positively related over large spatial scales, some posit that soil nitrogen positively drives leaf nitrogen, which positively drives photosynthetic capacity. Alternatively, others posit that photosynthetic capacity is primarily driven by aboveground conditions. Here, we examined the physiological responses of a non nitrogen-fixing plant (Gossypium hirsutum) and a nitrogen-fixing plant (Glycine max) in a fully factorial combination of light by soil nitrogen availability to help reconcile these competing hypotheses. Soil nitrogen stimulated leaf nitrogen in both species, but the relative proportion of leaf nitrogen used for photosynthetic processes was reduced under elevated soil nitrogen in all light availability treatments due to greater increases in leaf nitrogen content than chlorophyll and leaf biochemical process rates. Leaf nitrogen content and biochemical process rates in G. hirsutum were more responsive to changes in soil nitrogen than G. max, likely due to strong G. max investments in root nodulation under low soil nitrogen. Nonetheless, whole plant growth was significantly enhanced by increased soil nitrogen in both species. Light availability consistently increased relative leaf nitrogen allocation to leaf photosynthesis and whole plant growth, a pattern that was similar between species. These results suggest that the leaf nitrogen-photosynthesis relationship varies under different soil nitrogen levels and that these species preferentially allocated more nitrogen to plant growth and non-photosynthetic leaf processes, rather than photosynthesis, as soil nitrogen increased.

Representations of interactions between the C and N cycles in terrestrial ecosystems are now implemented in a majority of state-of-the-art Dynamic Global Vegetation Models (C-N models). Standard models for simulating the response of individual processes to changes in N availability have not yet emerged and widely used models have not been tested against the full diversity of empirical data. Large remaining model structural uncertainty has important implications for projections and hindcasts of the land C uptake.Here, we summarise the current state of global land C balance simulations by comparing C-N models to C-only models; summarise data from field surveys and experiments to elucidate the role of soil N in controlling photosynthesis and its acclimation, stoichiometry, allocation, and growth; and demonstrate how optimality principles can guide the representation of acclimation and allocation for simulating ecosystem responses to experimental treatments of CO2 and soil N – consistent with observations. Promising model results are achieved by assuming that the atmospheric environment, including CO2, is the principal driver for photosynthetic capacities and leaf N following optimality theory of photosynthetic acclimation (Prentice et al., 2014). In turn, the functional balance hypothesis (Bloom et al., 1985) yields accurate predictions for how soil N availability and CO2 influence allocation and growth in different tissues.Our results show how confronting new theoretical approaches to simulating ecosystem C-N interactions against the collective constraints from diverse types of observations can guide model development and potentially reduce the large uncertainty in global carbon cycle projections.ReferencesBloom, Arnold J, F Stuart Chapin, and Harold A Mooney. “Resource Limitation in Plants--An Economic Analogy” Annual Review of Ecology and Systematics, 16, no. 1 (1985): 363–92. https://doi.org/10.1146/annurev.es.16.110185.002051.Prentice, I. Colin, Ning Dong, Sean M. Gleason, Vincent Maire, and Ian J. Wright. “Balancing the Costs of Carbon Gain and Water Transport: Testing a New Theoretical Framework for Plant Functional Ecology.” Ecology Letters 17, 1 (2014): 82–91. https://doi.org/10.1111/ele.12211.

Terrestrial ecosystems regulate Earth's climate through water, energy, and biogeochemical transformations. Despite a key role in regulating the Earth system, terrestrial ecology has historically been underrepresented in the Earth system models (ESMs) that are used to understand and project global environmental change. Ecology and Earth system modeling must be integrated for scientists to fully comprehend the role of ecological systems in driving and responding to global change. Ecological insights can improve ESM realism and reduce process uncertainty, while ESMs offer ecologists an opportunity to broadly test ecological theory and increase the impact of their work by scaling concepts through time and space. Despite this mutualism, meaningfully integrating the two remains a persistent challenge, in part because of logistical obstacles in translating processes into mathematical formulas and identifying ways to integrate new theories and code into large, complex model structures. To help overcome this interdisciplinary challenge, we present a framework consisting of a series of interconnected stages for integrating a new ecological process or insight into an ESM. First, we highlight the multiple ways that ecological observations and modeling iteratively strengthen one another, dispelling the illusion that the ecologist's role ends with initial provision of data. Second, we show that many valuable insights, products, and theoretical developments are produced through sustained interdisciplinary collaborations between empiricists and modelers, regardless of eventual inclusion of a process in an ESM. Finally, we provide concrete actions and resources to facilitate learning and collaboration at every stage of data-model integration. This framework will create synergies that will transform our understanding of ecology within the Earth system, ultimately improving our understanding of global environmental change and broadening the impact of ecological research. Accepted version

Earlier spring phenological events have been widely reported in plants under global warming. Recent studies reported a slowdown in the warming-induced advanced spring phenology in temperate regions. However, previous research mainly focused on daily mean temperature, thus neglecting the asymmetric phenological responses to daytime and nighttime temperature. Using long-term records of leaf unfolding in eight deciduous species at 1300 sites across central Europe, we assessed and compared the effects of daytime temperature, nighttime temperature, and photoperiod on leaf unfolding during 1951-1980 and 1981-2013. Although leaf unfolding was advanced by daytime warming during 1951-2013, the advancing responses of leaf unfolding significantly decreased from 1951-1980 to 1981-2013 due to a lower accumulation of chilling units by daytime warming. Nighttime warming delayed leaf unfolding during 1951-1980 but advanced it during 1981-2013 due to a higher accumulation of chilling units by nighttime warming. In contrast, critical daylength and plasticity of leaf unfolding dates remained unchanged between 1951 and 2013. Our study provided evidence that daytime warming instead of nighttime warming accounts for the slowdown in the advancing spring phenology and implied that nighttime warming-induced earlier spring phenology may be buffering the slowdown of the advanced spring phenology by daytime warming. The response of spring phenology to nighttime temperature may override that to daytime temperature under the actual trends in global warming.

Irrigation of farmlands in xeric areas can increase soil salinity, reducing their suitability for food and fiber crops. One way to repurpose these lands is to convert them for use in grazing. To choose the best forage species, it is important to understand the impact of soil salinity on the growth and nutritional quality of potential forage grasses. Here, we grew four perennial C4 grasses: blue grama (Bouteloua gracilis), sideoats grama (Bouteloua curtipendula), little bluestem (Schizachyrium scoparium), and bermudagrass (Cynodon dactylon) in soil treated with four different concentrations (0, 8, 16, and 24 dS/m) of sodium chloride salt (NaCl). We then determined the effects of soil salinity on germination, biomass production, and plant tissue nitrogen content (an indicator of nutritional quality). We found a high degree of variability in salinity responses among species. S. scoparium performed poorly relative to the other species across all metrics. C. dactylon showed high biomass and low sensitivity to soil salinity for each index but had the lowest shoot nitrogen concentration of all species tested. This indicated a tradeoff of tissue quality for quantity. On the other hand, the two Bouteloua species showed opposite results, falling on the shoot quality end of the quantity-quality spectrum and even showing increased nitrogen concentration with increasing soil salinity. Given their complimentary traits, C. dactylon and Bouteloua spp. may be good candidates for interseeding on saline lands. These results indicate that species choice can help mitigate negative impacts of soil salinity on forage production and quality and should be carefully considered by land managers.

Black orthorhombic (B-γ) CsSnI3 with reduced biotoxicity and environmental impact and excellent optoelectronic properties is being considered as a promising eco-friendly candidate for high-performing perovskite solar cells (PSCs). A major challenge in a large-scale implementation of CsSnI3 PSCs includes the rapid transformation of Sn2+ to Sn4+ (within a few minutes) under an ambient-air condition. Here, we demonstrate that ambient-air stable B-γ CsSnI3 PSCs can be fabricated by incorporating N,N'-methylenebis(acrylamide) (MBAA) into the perovskite layer and by using poly(3-hexylthiophene) as the hole transporting material. The lone electron pairs of -NH and -CO units of MBAA are designed to form coordination bonding with Sn2+ in the B-γ CsSnI3, resulting in a reduced defect (Sn4+) density and better stability under multiple conditions for the perovskite light absorber. After a modification, the highest power conversion efficiency (PCE) of 7.50% is documented under an ambient-air condition for the unencapsulated CsSnI3-MBAA PSC. Furthermore, the MBAA-modified devices sustain 60.2%, 76.5%, and 58.4% of their initial PCEs after 1440 h of storage in an inert condition, after 120 h of storage in an ambient-air condition, and after 120 h of 1 Sun continuous illumination, respectively.

Leaf dark respiration (Rd) accounts for approximately 50% of plant respiration. The acclimation of plant respiration to temperature weakens the positive feedback to global warming. Most existing land surface models (LSMs) adopt an empirical leaf respiration scheme with a constant Rd25 (leaf dark respiration rate at 25°C) for each vegetation type, since there is no acceptable theory of Rd acclimation and how it varies temporally and spatially. Here we propose that Rd25 adjusts to prior nighttime temperature (Tnight) to maintain the ratio of Rd to photosynthesis capacity (Vcmax) approximately constant. To test this hypothesis and explore the time scale of acclimation, we predict Rd25 over different time windows and evaluate these predictions using data from 14 sites from two datasets (Boreal Forest Warming at an Ecotone in Danger (B4WarmED) experiment and Leaf Carbon Exchange dataset (LCE)), one of which provides measurements through time and the other across spatial gradients. Predictions that account for the combined effects of Vcmax and Tnight have better predictive power for all species (mean R2=0.4) than considering the effect of one factor alone. Predictions of acclimation on different timescales show that Vcmax and Tnight averaged over the past fortnight explain the most variation in observed Rd25. These results could provide an alternative solution to the leaf respiration schemes used in LSMs.

Global warming has been linked to declines in tree growth. However, it is unclear how the asymmetry in daytime and nighttime warming influences this response. Here, we use 2947 residual tree-ring width chronologies covering 32 species at 2493 sites, between 1901 and 2018, across the Northern Hemisphere, to analyze the effects of daytime and nighttime temperatures, precipitation, and drought stress on the radial growth of trees. We show that drought stress was primarily triggered by daytime rather than nighttime warming. The radial growth of trees was more sensitive to drought stress in warm regions than in cold regions, especially for angiosperms. Our study provides robust evidence that daytime warming is the primary driver of the observed declines in forest productivity related to drought stress and that daytime and nighttime warming should be considered separately when modelling forest-climate interactions and feedbacks in a future, warmer world.

A warmer world could extend the growing seasons for plants. Changes in spring phenology have been studied, yet autumn phenology remains poorly understood. Using >500,000 phenological records of four temperate tree species between 1951 and 2013 in Europe, we show that leaf senescence in warm autumns exhibits stronger climate responses, with a higher phenological plasticity, than in cold autumns, indicating a nonlinear response to climate. The onset of leaf senescence in warm autumns was delayed due to the stronger climate response, primarily caused by night-time warming. However, daytime warming, especially during warm autumns, imposes a drought stress which advances leaf senescence. This may counteract the extension of growing season under global warming. These findings provide guidance for more reliable predictions of plant phenology and biosphere–atmosphere feedbacks in the context of global warming. Autumn leaf senescence has later onset, higher phenological plasticity and a stronger climatic response under warm compared to cold autumns. While night-time warming delays senescence, drought induced by daytime warming advances it, which may lead to loss in growing season under global warming.

The mechanisms responsible for photosynthetic acclimation are not well understood, effectively limiting predictability under future conditions. Least-cost optimality theory can be used to predict the acclimation of photosynthetic capacity based on the assumption that plants maximize carbon uptake while minimizing the associated costs. Here, we use this theory as a null model in combination with multiple datasets of C3 plant photosynthetic traits to elucidate the mechanisms underlying photosynthetic acclimation to elevated temperature and carbon dioxide (CO2 ). The model-data comparison showed that leaves decrease the ratio of the maximum rate of electron transport to the maximum rate of Rubisco carboxylation (Jmax /Vcmax ) under higher temperatures. The comparison also indicated that resources used for Rubisco and electron transport are reduced under both elevated temperature and CO2 . Finally, our analysis suggested that plants underinvest in electron transport relative to carboxylation under elevated CO2 , limiting potential leaf-level photosynthesis under future CO2 concentrations. Altogether, our results show that acclimation to temperature and CO2 is primarily related to resource conservation at the leaf level. Under future, warmer, high CO2 conditions, plants are therefore likely to use less nutrients for leaf-level photosynthesis, which may impact whole-plant to ecosystem functioning.

Plants utilizing C3 physiology have a more difficult time establishing in rooftop environments than plants with more heat and drought adapted constitutions, such as species that employ crassulacean acid metabolism (CAM). CAM species are much less susceptible to limitations of shallow, infertile soil-less media under abiotic and biotic stress. It is thought that soil amendments might improve rooftop media in a way that allows for C3 species to prosper in rooftop environments. While compost is typically added to media to achieve this goal, we hypothesized that the addition of an anthropogenic pyrogenic carbon (PyC) supplement, instead, would enable better organic and mineral sorption and water retention, resulting in improved physiological performance of C3 species. To test this, we grew a C3 legume species, wild indigo (Baptisia tinctoria L R.Br. ex), in control compost-amended media and media amended by PyC on a rooftop in Massachusetts, USA. We found PyC-amended media had greater mean organic and mineral nutrient sorption. We also found 16% greater soil water holding capacity (GWL/ψg) than control media. In addition, wild indigo photosynthetic intrinsic water use efficiency (iWUE) was significantly increased by 19% when grown in PyC-amended as compared to control media. We conclude that amending green roof media with PyC provides greater benefits than compost amendments for colonization of a C3 legume, wild indigo. Our results gathered over seven years suggest that PyC from converted waste stream cardboard could be used to improve the rooftop performance of other leguminous species, including agricultural crops.

Nitrogen (N) limitation has been considered as a constraint on terrestrial carbon uptake in response to rising CO

The maximum rate of Rubisco carboxylation (Vcmax) determines leaf photosynthetic capacity and is a key parameter for estimating the terrestrial carbon cycle, but its spatial information is lacking, hindering global ecological research. Here, we convert leaf chlorophyll content (LCC) retrieved from satellite data to Vcmax, based on plants' optimal distribution of nitrogen between light harvesting and carboxylation pathways. We also derive Vcmax from satellite (GOME-2) observations of sun-induced chlorophyll fluorescence (SIF) as a proxy of leaf photosynthesis using a data assimilation technique. These two independent global Vcmax products agree well (r2=0.79,RMSE=15.46µmol m−2 s−1, P<0.001) and compare well with 3672 ground-based measurements (r2=0.69,RMSE=13.8µmol m−2 s−1 and P<0.001 for SIF; r2=0.55,RMSE=18.28µmol m−2 s−1 and P<0.001 for LCC). The LCC-derived Vcmax product is also used to constrain the retrieval of Vcmax from TROPical Ozone Mission (TROPOMI) SIF data to produce an optimized Vcmax product using both SIF and LCC information. The global distributions of these products are compatible with Vcmax computed from an ecological optimality theory using meteorological variables, but importantly reveal additional information on the influence of land cover, irrigation, soil pH, and leaf nitrogen on leaf photosynthetic capacity. These satellite-based approaches and spatial Vcmax products are primed to play a major role in global ecosystem research. The three remote sensing Vcmax products based on SIF, LCC, and SIF+LCC are available at https://doi.org/10.5281/zenodo.6466968 (Chen et al., 2022), and the code for implementing the ecological optimality theory is available at https://github.com/SmithEcophysLab/optimal_vcmax_R and https://doi.org/10.5281/zenodo.5899564 (last access: 31 August 2022) (Smith et al., 2022).

Under global warming, advances in spring phenology due to the rising temperature have been widely reported. However, the physiological mechanisms underlying the warming-induced earlier spring phenology remain poorly understood. Here, using multiple long-term and large-scale phenological datasets between 1951 and 2018, we show that warmer temperatures during the previous growing season between May and September led to earlier spring phenology in the Northern Hemisphere. We also found that warming-induced increases in maximum photosynthetic rate in the previous year advanced spring phenology, with an average of 2.50 days °C-1. Furthermore, we found a significant decline in the advancing effect of warming during the previous growing season on spring phenology from cold to warm periods over the past decades. Our results suggest that the observed warming-induced earlier spring phenology may be driven by increased photosynthetic carbon assimilation in the previous season, while the slowdown in the advanced spring phenology arise likely from decreased carbon assimilation when warming exceeding the optimal temperatures for photosynthesis. Our study highlights the vital role of photosynthetic carbon assimilation during growing season in spring phenology under global warming.

Co/Pd thin film multilayers show large Perpendicular Magnetic Anisotropy (PMA) which is useful in MRAM devices for perpendicular magnetic recording. Co/Pd systems have been studied extensively through the use of ultrafast optical pump-probe methods in order to measure the Time Resolved Photo-excited Precession of Magnetization (TRPEPM). Most studies have been conducted at high laser fluence (> 1 mJ/cm2), where heating near the curie temperature occurs. In this study, we present low fluence measurements between 0.42 to 3.14 μJ/cm2 in Co/Pd systems with differing Co thickness between 0.4 to 0.74 nm to probe the role of interface anisotropy in low-power excitation.

Plants invest a considerable amount of leaf nitrogen in the photosynthetic enzyme ribulose-1,5-bisphosphate carboxylase-oxygenase (RuBisCO), forming a strong coupling of nitrogen and photosynthetic capacity. Variability in the nitrogen-photosynthesis relationship indicates different nitrogen use strategies of plants (i.e., the fraction nitrogen allocated to RuBisCO; fLNR), however, the reason for this remains unclear as widely different nitrogen use strategies are adopted in photosynthesis models. Here, we use a comprehensive database of in situ observations, a remote sensing product of leaf chlorophyll and ancillary climate and soil data, to examine the global distribution in fLNR using a random forest model. We find global fLNR is 18.2 ± 6.2%, with its variation largely driven by negative dependence on leaf mass per area and positive dependence on leaf phosphorus. Some climate and soil factors (i.e., light, atmospheric dryness, soil pH, and sand) have considerable positive influences on fLNR regionally. This study provides insight into the nitrogen-photosynthesis relationship of plants globally and an improved understanding of the global distribution of photosynthetic potential., The fraction of leaf nitrogen allocated to RuBisCO indicates differing nitrogen use strategies of plants and varies considerably. Here the authors show that this variation is largely driven by leaf thickness and phosphorus content with light intensity, atmospheric dryness and soil pH also having considerable influence.

SummaryShifts in plant phenology under ongoing warming affect global vegetation dynamics and carbon assimilation of the biomes. The response of leaf senescence to climate is crucial for predicting changes in the physiological processes of trees at ecosystem scale. We used long-term ground observations, phenological metrics derived from PhenoCam, and satellite imagery of the Northern Hemisphere to show that the timings of leaf senescence can advance or delay in case of warming occurring at the beginning (before June) or during (after June) the main growing season, respectively. Flux data demonstrated that net photosynthetic carbon assimilation converted from positive to negative at the end of June. These findings suggest that leaf senescence is driven by carbon assimilation and nutrient resorption at different growth stages of leaves. Our results provide new insights into understanding and modelling autumn phenology and carbon cycling under warming scenarios.

International audience; Global vegetation and land-surface models embody interdisciplinary scientific understanding of the behaviour of plants and ecosystems, and are indispensable to project the impacts of environmental change on vegetation and the interactions between vegetation and climate. However, systematic errors and persistently large differences among carbon and water cycle projections by different models highlight the limitations of current process formulations. In this review, focusing on core plant functions in the terrestrial carbon and water cycles, we show how unifying hypotheses derived from eco-evolutionary optimality (EEO) principles can provide novel, parameter-sparse representations of plant and vegetation processes. We present case studiesthat demonstrate how EEO generate parsimonious representations of core, leaf-level processes that are individually testable and supported by evidence. EEO approaches to photosynthesis and primary production, dark respiration, and stomatal behaviour are ripe for implementation in global models. EEO approaches to other important traits, including the leaf economics spectrum and applications of EEO at the community level are active research areas. Independently tested modules emerging from EEO studies could profitably be integrated into modelling frameworks that account for the multiple time scales on which plants and plant communities adjust toenvironmental change.

Arid ecosystems are an important component of the global carbon cycle. In these ecosystems, plant functional types are particularly important in realizing many ecosystem processes such as the dynamics and regulations of net ecosystem exchange of CO2 (NEE) to the changing environment. Here, we measured the diurnal dynamics of NEE in patches of succulent and non-succulent shrubs over two growing seasons (2012 and 2013) in the Alxa Desert, located in northern China. We find that the interannual difference of NEE was greater for the non-succulent shrub than that for he succulent shrub species. Diurnal NEE changes were similar for all species and were more strongly influenced by soil moisture than by temperature. Nonetheless, these environmental factors had a greater influence on non-succulent shrubs than succulent shrubs. Our findings highlight that species with different life history traits have different NEE dynamics and vary by time scales. These dynamics are strongly tied to water availability and plant type-specific water storage capacity, with plants possessing large water storage organs maintaining their physiological functioning better under stressful conditions. Our findings on the interaction between plant type and environment could be used to improve estimates of terrestrial carbon uptake in critical desert ecosystems.

Extracellular matrix (ECsM) bioscaffolds have been successfully used to treat five esophageal adenocarcinoma (EAC) patients following resection of neoplastic mucosal tissue. The present study evaluated the in vitro effect of ECM harvested from nonmalignant, decellularized tissue on EAC cell phenotype to understand the molecular mechanisms underlying the clinical findings. Nonmalignant (Het-1A), metaplastic (CP-A), and neoplastic (SK-GT-4, OE33) esophageal epithelial cells were exposed to ECM degradation products (250 μg/mL) prepared from heterologous urinary bladder tissue or homologous esophageal mucosa tissue, and evaluated for cell morphology, cell function, and EAC signaling pathways. Both the ECM sources downregulated neoplastic cell phenotype, but had distinctive tissue-specific effects. Urinary bladder ECM decreased OE33 and SK-GT-4 metabolism and increased CP-A apoptosis. Esophageal ECM decreased SK-GT-4, CP-A, and Het-1A proliferation; robustly downregulated PI3K-Akt-mTOR, cell cycle/DNA replication signaling, and upregulated autophagy signaling in OE33 cells; and increased cell cycle/DNA replication signaling in Het-1A cells. Both ECM sources decreased OE33 proliferation and phosphorylated AKT in OE33 cells, and in contrast, increased phosphorylated AKT in Het-1A cells. The results support the concept that the biochemical signals in nonmalignant ECM can downregulate neoplastic cell phenotype with minimal, and sometimes opposite, effects on normal cells. PI3K-Akt signaling has been implicated in EAC progression and these ECM-mediated effects may be favorable for an esophageal therapy following cancer resection. IMPACT STATEMENT: Extracellular matrix (ECM) biomaterials were used to treat esophageal cancer patients after cancer resection and promoted regrowth of normal mucosa without recurrence of cancer. The present study investigates the mechanisms by which these materials were successful to prevent the cancerous phenotype. ECM downregulated neoplastic esophageal cell function (proliferation, metabolism), but normal esophageal epithelial cells were unaffected in vitro, and suggests a molecular basis (downregulation of PI3K-Akt, cell cycle) for the promising clinical results. The therapeutic effect appeared to be enhanced using homologous esophageal ECM. This study suggests that ECM can be further investigated to treat cancer patients after resection or in combination with targeted therapy.

Background Breast cancer is the most common invasive cancer among women worldwide. Next-generation sequencing (NGS) has revolutionized the study of cancer across research labs around the globe; however, genomic testing in clinical settings remains limited. Advances in sequencing reliability, pipeline analysis, accumulation of relevant data, and the reduction of costs are rapidly increasing the feasibility of NGS-based clinical decision making. Methods We report the development of MammaSeq, a breast cancer-specific NGS panel, targeting 79 genes and 1369 mutations, optimized for use in primary and metastatic breast cancer. To validate the panel, 46 solid tumors and 14 plasma circulating tumor DNA (ctDNA) samples were sequenced to a mean depth of 2311× and 1820×, respectively. Variants were called using Ion Torrent Suite 4.0 and annotated with cravat CHASM. CNVKit was used to call copy number variants in the solid tumor cohort. The oncoKB Precision Oncology Database was used to identify clinically actionable variants. Droplet digital PCR was used to validate select ctDNA mutations. Results In cohorts of 46 solid tumors and 14 ctDNA samples from patients with advanced breast cancer, we identified 592 and 43 protein-coding mutations. Mutations per sample in the solid tumor cohort ranged from 1 to 128 (median 3), and the ctDNA cohort ranged from 0 to 26 (median 2.5). Copy number analysis in the solid tumor cohort identified 46 amplifications and 35 deletions. We identified 26 clinically actionable variants (levels 1–3) annotated by OncoKB, distributed across 20 out of 46 cases (40%), in the solid tumor cohort. Allele frequencies of ESR1 and FOXA1 mutations correlated with CA.27.29 levels in patient-matched blood draws. Conclusions In solid tumor biopsies and ctDNA, MammaSeq detects clinically actionable mutations (OncoKB levels 1–3) in 22/46 (48%) solid tumors and in 4/14 (29%) of ctDNA samples. MammaSeq is a targeted panel suitable for clinically actionable mutation detection in breast cancer. Electronic supplementary material The online version of this article (10.1186/s13058-019-1102-7) contains supplementary material, which is available to authorized users.

Earth system models (ESMs) use photosynthetic capacity, indexed by the maximum Rubisco carboxylation rate (V cmax), to simulate carbon assimilation and typically rely on empirical estimates, including an assumed dependence on leaf nitrogen determined from soil fertility. In contrast, new theory, based on biochemical coordination and co‐optimization of carboxylation and water costs for photosynthesis, suggests that optimal V cmax can be predicted from climate alone, irrespective of soil fertility. Here, we develop this theory and find it captures 64% of observed variability in a global, field‐measured V cmax dataset for C3 plants. Soil fertility indices explained substantially less variation (32%). These results indicate that environmentally regulated biophysical constraints and light availability are the first‐order drivers of global photosynthetic capacity. Through acclimation and adaptation, plants efficiently utilize resources at the leaf level, thus maximizing potential resource use for growth and reproduction. Our theory offers a robust strategy for dynamically predicting photosynthetic capacity in ESMs.

Nitrogen (N) limitation constrains the magnitude of terrestrial carbon uptake in response to CO2 fertilization and climate change. However, the trajectory of N demand, and how it is influenced by continuing changes in CO2 and climate, is incompletely understood. We estimate recent changes in global canopy N demand based on a well-tested optimality hypothesis for the control of photosynthetic capacity (Vcmax). The predicted global pattern of optimal leaf-level Vcmax is similar to the pattern derived from remotely sensed chlorophyll retrievals. Over the period from 1982 to 2015, rising CO2­ and warming both contributed to decreasing leaf-level N demand. Widespread increases in green vegetation cover over the same period (especially in high latitudes) imply increasing total canopy N demand. The net global trend is, nonetheless, a decrease in total canopy N demand. This work provides a new perspective on the past, present and future of the global terrestrial N cycle.

Plant nitrogen acquisition requires carbon to be allocated belowground to build roots and sustain microbial associations. This carbon cost to acquire nitrogen varies by nitrogen acquisition strategy; however, the degree to which these costs vary due to nitrogen availability or demand has not been well tested under controlled conditions. We grew a species capable of forming associations with nitrogen-fixing bacteria (Glycine max) and a species not capable of forming such associations (Gossypium hirsutum) under four soil nitrogen levels to manipulate nitrogen availability and four light levels to manipulate nitrogen demand in a full-factorial greenhouse experiment. We quantified carbon costs to acquire nitrogen as the ratio of total root carbon to whole-plant nitrogen within each treatment combination. In both species, light availability increased carbon costs due to a larger increase in root carbon than whole-plant nitrogen, while nitrogen fertilization generally decreased carbon costs due to a larger increase in whole-plant nitrogen than root carbon. Nodulation data indicated that G. max shifted relative carbon allocation from nitrogen fixation to direct uptake with increased nitrogen fertilization. These findings suggest that carbon costs to acquire nitrogen are modified by changes in light and nitrogen availability in species with and without associations with nitrogen-fixing bacteria.

Leaf-level gas exchange data support the mechanistic understanding of plant fluxes of carbon and water. These fluxes inform our understanding of ecosystem function, are an important constraint on parameterization of terrestrial biosphere models, are necessary to understand the response of plants to global environmental change, and are integral to efforts to improve crop production. Collection of these data using gas analyzers can be both technically challenging and time consuming, and individual studies generally focus on a small range of species, restricted time periods, or limited geographic regions. The high value of these data is exemplified by the many publications that reuse and synthesize gas exchange data, however the lack of metadata and data reporting conventions make full and efficient use of these data difficult. Here we propose a reporting format for leaf-level gas exchange data and metadata to provide guidance to data contributors on how to store data in repositories to maximize their discoverability, facilitate their efficient reuse, and add value to individual datasets. For data users, the reporting format will better allow data repositories to optimize data search and extraction, and more readily integrate similar data into harmonized synthesis products. The reporting format specifies data table variable naming and unit conventions, as well as metadata characterizing experimental conditions and protocols. For common data types that were the focus of this initial version of the reporting format, i.e., survey measurements, dark respiration, carbon dioxide and light response curves, and parameters derived from those measurements, we took a further step of defining required additional data and metadata that would maximize the potential reuse of those data types. To aid data contributors and the development of data ingest tools by data repositories we provided a translation table comparing the outputs of common gas exchange instruments. Extensive consultation with data collectors, data users, instrument manufacturers, and data scientists was undertaken in order to ensure that the reporting format met community needs. The reporting format presented here is intended to form a foundation for future development that will incorporate additional data types and variables as gas exchange systems and measurement approaches advance in the future. The reporting format is published in the U.S. Department of Energy's ESS-DIVE data repository, with documentation and future development efforts being maintained in a version control system. publishedVersion

Despite widespread evidence that biological invasion influences both the biotic and abiotic soil environments, the extent to which these two pathways underpin the effects of invasion on plant traits and performance remains unknown. Leveraging a long-term (14-year) field experiment, we show that an allelochemical-producing invader affects plants through biotic mechanisms, altering the soil fungal community composition, with no apparent shifts in soil nutrient availability. Changes in belowground fungal communities resulted in high costs of nutrient uptake for native perennials and a shift in plant traits linked to their water and nutrient use efficiencies. Some plants in the invaded community compensate for the disruption of nutritional symbionts and reduced nutrient provisioning by sanctioning more nitrogen to photosynthesis and expending more water, which demonstrates a trade-off in trait investment. For the first time, we show that the disruption of belowground nutritional symbionts can drive plants towards alternative regions of their trait space in order to maintain water and nutrient economics.

Past research has shown that plants possess the capacity to alter their instantaneous response of photosynthesis to temperature in response to a longer-term change in temperature (i.e. acclimate). This acclimation is typically the result of processes that influence net photosynthesis (Anet), including leaf biochemical processes such as the maximum rate of Rubisco carboxylation (Vcmax) and the maximum rate of photosynthetic electron transport (Jmax), stomatal conductance (gs) and dark respiration (Rd). However, these processes are rarely examined in the field or in concert with other environmental factors, such as precipitation amount. Here, we use a fully factorial warming (active heating up to +4 °C; mean = +3.1 °C) by precipitation (−50 % ambient to 150 % ambient) manipulation experiment in an old-field ecosystem in the north-eastern USA to examine the degree to which Ulmus americana saplings acclimate through biochemical and stomatal adjustments. We found that rates of Anet at ambient CO2 levels of 400 µmol mol−1 (A400) did not differ across climate treatments or with leaf temperatures from 20 to 30 °C. Canopy temperatures rarely reached above 30 °C in any treatment, suggesting that seasonal carbon assimilation was relatively homeostatic across all treatments. Assessments of the component processes of A400 revealed that decreases in gs with leaf temperature from 20 to 30 °C were balanced by increases in Vcmax, resulting in stable A400 rates despite concurrent increases in Rd. Photosynthesis was not affected by precipitation treatments, likely because the relatively dry year led to small treatment effects on soil moisture. As temperature acclimation is likely to come at a cost to the plant via resource reallocation, it may not benefit plants to acclimate to warming in cases where warming would not otherwise reduce assimilation. These results suggest that photosynthetic temperature acclimation to future warming will be context-specific and that it is important to consider assimilatory benefit when assessing acclimation responses.

The mechanisms responsible for photosynthetic acclimation are not well understood, effectively limiting predictability under future conditions. Least-cost optimality theory can be used to predict the acclimation of photosynthetic capacity based on the assumption that plants maximize carbon uptake while minimizing the associated costs. Here, we use this theory as a null model in combination with multiple datasets of C

Photosynthetic 'least-cost' theory posits that the optimal trait combination for a given environment is that where the summed costs of photosynthetic water and nutrient acquisition/use are minimised. The effects of soil water and nutrient availability on photosynthesis should be stronger as climate-related costs for both resources increase. Two independent datasets of photosynthetic traits, Globamax (1509 species, 288 sites) and Glob13C (3645 species, 594 sites), were used to quantify biophysical and biochemical limitations of photosynthesis and the key variable Ci /Ca (CO2 drawdown during photosynthesis). Climate and soil variables were associated with both datasets. The biochemical photosynthetic capacity was higher on alkaline soils. This effect was strongest at more arid sites, where water unit-costs are presumably higher. Higher values of soil silt and depth increased Ci /Ca , likely by providing greater H2 O supply, alleviating biophysical photosynthetic limitation when soil water is scarce. Climate is important in controlling the optimal balance of H2 O and N costs for photosynthesis, but soil properties change these costs, both directly and indirectly. In total, soil properties modify the climate-demand driven predictions of Ci /Ca by up to 30% at a global scale.

Realistic representations of plant carbon exchange processes are necessary to reliably simulate biosphere-atmosphere feedbacks. These processes are known to vary over time and space, though the drivers of the underlying rates are still widely debated in the literature. Here, we measured leaf carbon exchange in >500 individuals of 98 species from the Neotropics to high boreal biomes to determine the drivers of photosynthetic and dark respiration capacity. Covariate abiotic (long- and short-term climate) and biotic (plant type, plant size, ontogeny, water status) data were used to explore significant drivers of temperature-standardized leaf carbon exchange rates. Using model selection, we found the previous week's temperature and soil moisture at the time of measurement to be a better predictor of photosynthetic capacity than long-term climate, with the combination of high recent temperatures and low soil moisture tending to decrease photosynthetic capacity. Non-trees (annual and perennials) tended to have greater photosynthetic capacity than trees, and, within trees, adults tended to have greater photosynthetic capacity than juveniles, possibly as a result of differences in light availability. Dark respiration capacity was less responsive to the assessed drivers than photosynthetic capacity, with rates best predicted by multi-year average site temperature alone. Our results suggest that, across large spatial scales, photosynthetic capacity quickly adjusts to changing environmental conditions, namely light, temperature, and soil moisture. Respiratory capacity is more conservative and most responsive to longer-term conditions. Our results provide a framework for incorporating these processes into large-scale models and a data set to benchmark such models.