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Abstract Traits with intuitive names, a clear scope and explicit description are essential for all trait databases. The lack of unified, comprehensive, and machine-readable plant trait definitions limits the utility of trait databases, including reanalysis of data from a single database, or analyses that integrate data across multiple databases. Both can only occur if researchers are confident the trait concepts are consistent within and across sources. Here we describe the AusTraits Plant Dictionary (APD), a new data source of terms that extends the trait definitions included in a recent trait database, AusTraits. The development process of the APD included three steps: review and formalisation of the scope of each trait and the accompanying trait description; addition of trait metadata; and publication in both human and machine-readable forms. Trait definitions include keywords, references, and links to related trait concepts in other databases, enabling integration of AusTraits with other sources. The APD will both improve the usability of AusTraits and foster the integration of trait data across global and regional plant trait databases.

Abstract Understanding the biophysical limitations on forest carbon across diverse ecological regions is crucial for accurately assessing and managing forest carbon stocks. This study investigates the role of climate and disturbance on the spatial variation of two key forest carbon pools: aboveground carbon (AGC) and soil organic carbon (SOC). Using plot‐level carbon pool estimates from Nepal's national forest inventory and structural equation modelling, we explore the relationship of forest carbon stocks to broad‐scale climatic water and energy availability and fine‐scale terrain and disturbance. The forest AGC and SOC models explained 25% and 59% of the observed spatial variation in forest AGC and SOC, respectively. Among the evaluated variables, disturbance exhibited the strongest negative correlation with AGC, while the availability of climatic energy demonstrated the strongest negative correlation with SOC. Disturbances such as selective logging and firewood collection result in immediate forest carbon loss, while soil carbon changes take longer to respond. The lower decomposition rates in the high‐elevation region, due to lower temperatures, preserve organic matter and contribute to the high SOC stocks observed there. These results highlight the critical role of climate and disturbance regimes in shaping landscape patterns of forest carbon stocks. Understanding the underlying drivers of these patterns is crucial for forest carbon management and conservation across diverse ecological zones including the Central Himalayas.

Abstract Patient‐derived cancer organoids (PDOs) hold considerable promise for personalizing therapy selection and improving patient outcomes. However, it is challenging to generate PDOs in sufficient numbers to test therapies in standard culture platforms. This challenge is particularly acute for pancreatic ductal adenocarcinoma (PDAC) where most patients are diagnosed at an advanced stage with non‐resectable tumors and where patient tissue is in the form of needle biopsies. Here the development and characterization of microfluidic devices for testing therapies using a limited amount of tissue or PDOs available from PDAC biopsies is described. It is demonstrated that microfluidic PDOs are phenotypically and genotypically similar to the gold‐standard Matrigel organoids with the advantages of 1) spheroid uniformity, 2) minimal cell number requirement, and 3) not relying on Matrigel. The utility of microfluidic PDOs is proven by testing PDO responses to several chemotherapies, including an inhibitor of glycogen synthase kinase (GSKI). In addition, microfluidic organoid cultures are used to test effectiveness of immunotherapy comprised of NK cells in combination with a novel biologic. In summary, our microfluidic device offers considerable benefits for personalizing oncology based on cancer biopsies and may, in the future, be developed into a companion diagnostic for chemotherapy or immunotherapy treatments.

Tropical forests take up more carbon (C) from the atmosphere per annum by photosynthesis than any other type of vegetation. Phosphorus (P) limitations to C uptake are paramount for tropical and subtropical forests around the globe. Yet the generality of photosynthesis-P relationships underlying these limitations are in question, and hence are not represented well in terrestrial biosphere models. Here we demonstrate the dependence of photosynthesis and underlying processes on both leaf N and P concentrations. The regulation of photosynthetic capacity by P was similar across four continents. Implementing P constraints in the ORCHIDEE-CNP model, gross photosynthesis was reduced by 36% across the tropics and subtropics relative to traditional N constraints and unlimiting leaf P. Our results provide a quantitative relationship for the P dependence for photosynthesis for the front-end of global terrestrial C models that is consistent with canopy leaf measurements.

The forest–atmosphere exchange of carbon and water is regulated by meteorological conditions as well as canopy properties such as leaf area index (LAI, m2 m−2), photosynthetic capacity (PC μmol m−2 s−1), or surface conductance in optimal conditions (Gs,opt, mmol m−2 s−1), which can vary seasonally and inter-annually. This variability is well understood for deciduous species but is poorly characterized in evergreen forests. Here, we quantify the seasonal dynamics of a temperate evergreen eucalypt forest with estimates of LAI, litterfall, carbon and water fluxes, and meteorological conditions from measurements and model simulations. We merged MODIS Enhanced Vegetation Index (EVI) values with site-based LAI measurements to establish a 17-year sequence of monthly LAI. We ran the Community Atmosphere Biosphere Land Exchange model (CABLE-POP (version r5046)) with constant and varying LAI for our site to quantify the influence of seasonal canopy dynamics on carbon and water fluxes. We observed that the peak of LAI occurred in late summer–early autumn, with a higher and earlier peak occurring in years when summer rainfall was greater. Seasonality in litterfall and allocation of net primary productivity (FNPP) to leaf growth (af, 0–1) drove this pattern, suggesting a complete renewal of the canopy before the timing of peak LAI. Litterfall peaked in spring, followed by a high af in summer, at the end of which LAI peaked, and PC and Gs,opt reached their maximum values in autumn, resulting from a combination of high LAI and efficient mature leaves. These canopy dynamics helped explain observations of maximum gross ecosystem production (FGEP) in spring and autumn and net ecosystem carbon loss in summer at our site. Inter-annual variability in LAI was positively correlated with Net Ecosystem Production (FNEP). It would be valuable to apply a similar approach to other temperate evergreen forests to identify broad patterns of seasonality in leaf growth and turnover. Because incorporating dynamic LAI was insufficient to fully capture the dynamics of FGEP, observations of seasonal variation in photosynthetic capacity, such as from solar-induced fluorescence, should be incorporated in land surface models to improve ecosystem flux estimates in evergreen forests.

Abstract Comprehensive forest carbon accounting requires reliable estimation of soil organic carbon (SOC) stocks. Despite being an important carbon pool, limited information is available on SOC stocks in global forests, particularly for forests in mountainous regions, such as the Central Himalayas. The availability of consistently measured new field data enabled us to accurately estimate forest soil organic carbon (SOC) stocks in Nepal, addressing a previously existing knowledge gap. Our method involved modelling plot-based estimates of forest SOC using covariates related to climate, soil, and topographic position. Our quantile random forest model resulted in the high spatial resolution prediction of Nepal’s national forest SOC stock together with prediction uncertainties. Our spatially explicit forest SOC map showed the high SOC levels in high-elevation forests and a significant underrepresentation of these stocks in global-scale assessments. Our results offer an improved baseline on the distribution of total carbon in the forests of the Central Himalayas. The benchmark maps of predicted forest SOC and associated errors, along with our estimate of 494 million tonnes (SE = 16) of total SOC in the topsoil (0–30 cm) of forested areas in Nepal, carry important implications for understanding the spatial variability of forest SOC in mountainous regions with complex terrains.

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.

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.

Abstract In 2019, south-eastern Australia experienced its driest and hottest year on record, resulting in massive canopy dieback events in eucalypt dominated forests. A subsequent period of high precipitation in 2020 provided a rare opportunity to quantify the impacts of extreme drought and consequent recovery. We quantified canopy health and hydraulic impairment (native percent loss of hydraulic conductivity, PLC) of 18 native tree species growing at 15 sites that were heavily impacted by the drought both during and 8–10 months after the drought. Most species exhibited high PLC during drought (PLC:65.1 ± 3.3%), with no clear patterns across sites or species. Heavily impaired trees (PLC > 70%) showed extensive canopy browning. In the post-drought period, most surviving trees exhibited hydraulic recovery (PLC:26.1 ± 5.1%), although PLC remained high in some trees (50–70%). Regained hydraulic function (PLC

The Millennium Drought lasted more than a decade and is notable for causing persistent shifts in the relationship between rainfall and runoff in many southeastern Australian catchments. Research to date has successfully characterised where and when shifts occurred and explored relationships with potential drivers, but a convincing physical explanation for observed changes in catchment behaviour is still lacking. Originating from a large multi-disciplinary workshop, this paper presents and evaluates a range of hypothesised process explanations of flow response to the Millennium Drought. The hypotheses consider climatic forcing, vegetation, soil moisture dynamics, groundwater, and anthropogenic influence. The hypotheses are assessed against evidence both temporally (e.g. why was the Millennium Drought different to previous droughts?) and spatially (e.g. why did rainfall–runoff relationships shift in some catchments but not in others?). Thus, the strength of this work is a large-scale assessment of hydrologic changes and potential drivers. Of 24 hypotheses, 3 are considered plausible, 10 are considered inconsistent with evidence, and 11 are in a category in between, whereby they are plausible yet with reservations (e.g. applicable in some catchments but not others). The results point to the unprecedented length of the drought as the primary climatic driver, paired with interrelated groundwater processes, including declines in groundwater storage, altered recharge associated with vadose zone expansion, and reduced connection between subsurface and surface water processes. Other causes include increased evaporative demand and harvesting of runoff by small private dams. Finally, we discuss the need for long-term field monitoring, particularly targeting internal catchment processes and subsurface dynamics. We recommend continued investment in the understanding of hydrological shifts, particularly given their relevance to water planning under climate variability and change.

Phosphorus (P) limitation is pervasive in tropical forests. Here the authors analyse the dependence of photosynthesis on leaf N and P in tropical forests, and show that incorporating leaf P constraints in a terrestrial biosphere model enhances its predictive power.

Carbon and water cycle dynamics of vegetation are controlled primarily by photosynthesis and stomatal conductance (gs). Our goal is to improve the representation of these key physiological processes within the JULES land surface model, with a particular focus on refining the temperature sensitivity of photosynthesis, impacting modelled carbon, energy and water fluxes. We test (1) an implementation of the Farquhar et al. (1980) photosynthesis scheme and associated plant functional type-dependent photosynthetic temperature response functions, (2) the optimality-based gs scheme from Medlyn et al. (2011) and (3) the Kattge and Knorr (2007) photosynthetic capacity thermal acclimation scheme. New parameters for each model configuration are adopted from recent large observational datasets that synthesise global experimental data. These developments to JULES incorporate current physiological understanding of vegetation behaviour into the model and enable users to derive direct links between model parameters and ongoing measurement campaigns that refine such parameter values. Replacement of the original Collatz et al. (1991) C3 photosynthesis model with the Farquhar scheme results in large changes in GPP for the current day, with ∼ 10 % reduction in seasonal (June–August, JJA, and December–February, DJF) mean GPP in tropical forests and ∼ 20 % increase in the northern high-latitude forests in JJA. The optimality-based gs model decreases the latent heat flux for the present day (∼ 10 %, with an associated increase in sensible heat flux) across regions dominated by needleleaf evergreen forest in the Northern Hemisphere summer. Thermal acclimation of photosynthesis coupled with the Medlyn gs scheme reduced tropical forest GPP by up to 5 % and increased GPP in the high-northern-latitude forests by between 2 % and 5 %. Evaluation of simulated carbon and water fluxes by each model configuration against global data products shows this latter configuration generates improvements in these key areas. Thermal acclimation of photosynthesis coupled with the Medlyn gs scheme improved modelled carbon fluxes in tropical and high-northern-latitude forests in JJA and improved the simulation of evapotranspiration across much of the Northern Hemisphere in JJA. Having established good model performance for the contemporary period, we force this new version of JULES offline with a future climate scenario corresponding to rising atmospheric greenhouse gases (Shared Socioeconomic Pathway (SSP5), Representative Concentration Pathway 8.5 (RCP8.5)). In particular, these calculations allow for understanding of the effects of long-term warming. We find that the impact of thermal acclimation coupled with the optimality-based gs model on simulated fluxes increases latent heat flux (+50 %) by the year 2050 compared to the JULES model configuration without acclimation. This new JULES configuration also projects increased GPP across tropical (+10 %) and northern-latitude regions (+30 %) by 2050. We conclude that thermal acclimation of photosynthesis with the Farquhar photosynthesis scheme and the new optimality-based gs scheme together improve the simulation of carbon and water fluxes for the current day and have a large impact on modelled future carbon cycle dynamics in a warming world.

Global terrestrial models currently predict that the Amazon rainforest will continue to act as a carbon sink in the future, primarily owing to the rising atmospheric carbon dioxide (CO2) concentration. Soil phosphorus impoverishment in parts of the Amazon basin largely controls its functioning, but the role of phosphorus availability has not been considered in global model ensembles—for example, during the Fifth Climate Model Intercomparison Project. Here we simulate the planned free-air CO2 enrichment experiment AmazonFACE with an ensemble of 14 terrestrial ecosystem models. We show that phosphorus availability reduces the projected CO2-induced biomass carbon growth by about 50% to 79 ± 63 g C m−2 yr−1 over 15 years compared to estimates from carbon and carbon–nitrogen models. Our results suggest that the resilience of the region to climate change may be much less than previously assumed. Variation in the biomass carbon response among the phosphorus-enabled models is considerable, ranging from 5 to 140 g C m−2 yr−1, owing to the contrasting plant phosphorus use and acquisition strategies considered among the models. The Amazon forest response thus depends on the interactions and relative contributions of the phosphorus acquisition and use strategies across individuals, and to what extent these processes can be upregulated under elevated CO2.

Plant water-use efficiency (WUE, the carbon gained through photosynthesis per unit of water lost through transpiration) is a tracer of the plant physiological controls on the exchange of water and carbon dioxide between terrestrial ecosystems and the atmosphere. At the leaf level, rising CO2 concentrations tend to increase carbon uptake (in the absence of other limitations) and to reduce stomatal conductance, both effects leading to an increase in leaf WUE. At the ecosystem level, indirect effects (e.g. increased leaf area index, soil water savings) may amplify or dampen the direct effect of CO2 . Thus, the extent to which changes in leaf WUE translate to changes at the ecosystem scale remains unclear. The differences in the magnitude of increase in leaf versus ecosystem WUE as reported by several studies are much larger than would be expected with current understanding of tree physiology and scaling, indicating unresolved issues. Moreover, current vegetation models produce inconsistent and often unrealistic magnitudes and patterns of variability in leaf and ecosystem WUE, calling for a better assessment of the underlying approaches. Here, we review the causes of variations in observed and modelled historical trends in WUE over the continuum of scales from leaf to ecosystem, including methodological issues, with the aim of elucidating the reasons for discrepancies observed within and across spatial scales. We emphasize that even though physiological responses to changing environmental drivers should be interpreted differently depending on the observational scale, there are large uncertainties in each data set which are often underestimated. Assumptions made by the vegetation models about the main processes influencing WUE strongly impact the modelled historical trends. We provide recommendations for improving long-term observation-based estimates of WUE that will better inform the representation of WUE in vegetation models.

The temperature response of photosynthesis is one of the key factors determining predicted responses to warming in global vegetation models (GVMs). The response may vary geographically, owing to genetic adaptation to climate, and temporally, as a result of acclimation to changes in ambient temperature. Our goal was to develop a robust quantitative global model representing acclimation and adaptation of photosynthetic temperature responses. We quantified and modelled key mechanisms responsible for photosynthetic temperature acclimation and adaptation using a global dataset of photosynthetic CO2 response curves, including data from 141 C3 species from tropical rainforest to Arctic tundra. We separated temperature acclimation and adaptation processes by considering seasonal and common-garden datasets, respectively. The observed global variation in the temperature optimum of photosynthesis was primarily explained by biochemical limitations to photosynthesis, rather than stomatal conductance or respiration. We found acclimation to growth temperature to be a stronger driver of this variation than adaptation to temperature at climate of origin. We developed a summary model to represent photosynthetic temperature responses and showed that it predicted the observed global variation in optimal temperatures with high accuracy. This novel algorithm should enable improved prediction of the function of global ecosystems in a warming climate.

Increasing atmospheric CO2 stimulates photosynthesis which can increase net primary production (NPP), but at longer timescales may not necessarily increase plant biomass. Here we analyse the four decade-long CO2-enrichment experiments in woody ecosystems that measured total NPP and biomass. CO2 enrichment increased biomass increment by 1.05 ± 0.26 kg C m-2 over a full decade, a 29.1 ± 11.7% stimulation of biomass gain in these early-secondary-succession temperate ecosystems. This response is predictable by combining the CO2 response of NPP (0.16 ± 0.03 kg C m-2 y-1) and the CO2-independent, linear slope between biomass increment and cumulative NPP (0.55 ± 0.17). An ensemble of terrestrial ecosystem models fail to predict both terms correctly. Allocation to wood was a driver of across-site, and across-model, response variability and together with CO2-independence of biomass retention highlights the value of understanding drivers of wood allocation under ambient conditions to correctly interpret and predict CO2 responses.

Climate change is projected to increase the imbalance between the supply (precipitation) and atmospheric demand for water (i.e., increased potential evapotranspiration), stressing plants in water-limited environments. Plants may be able to offset increasing aridity because rising CO2 increases water use efficiency. CO2 fertilization has also been cited as one of the drivers of the widespread “greening” phenomenon. However, attributing the size of this CO2 fertilization effect is complicated, due in part to a lack of long-term vegetation monitoring and interannual- to decadal-scale climate variability. In this study we asked the question of how much CO2 has contributed towards greening. We focused our analysis on a broad aridity gradient spanning eastern Australia's woody ecosystems. Next we analyzed 38 years of satellite remote sensing estimates of vegetation greenness (normalized difference vegetation index, NDVI) to examine the role of CO2 in ameliorating climate change impacts. Multiple statistical techniques were applied to separate the CO2-attributable effects on greening from the changes in water supply and atmospheric aridity. Widespread vegetation greening occurred despite a warming climate, increases in vapor pressure deficit, and repeated record-breaking droughts and heat waves. Between 1982–2019 we found that NDVI increased (median 11.3 %) across 90.5 % of the woody regions. After masking disturbance effects (e.g., fire), we statistically estimated an 11.7 % increase in NDVI attributable to CO2, broadly consistent with a hypothesized theoretical expectation of an 8.6 % increase in water use efficiency due to rising CO2. In contrast to reports of a weakening CO2 fertilization effect, we found no consistent temporal change in the CO2 effect. We conclude rising CO2 has mitigated the effects of increasing aridity, repeated record-breaking droughts, and record-breaking heat waves in eastern Australia. However, we were unable to determine whether trees or grasses were the primary beneficiary of the CO2-induced change in water use efficiency, which has implications for projecting future ecosystem resilience. A more complete understanding of how CO2-induced changes in water use efficiency affect trees and non-tree vegetation is needed.

The importance of phosphorus (P) in regulating ecosystem responses to climate change has fostered P-cycle implementation in land surface models, but their CO2 effects predictions have not been evaluated against measurements. Here, we perform a data-driven model evaluation where simulations of eight widely used P-enabled models were confronted with observations from a long-term free-air CO2 enrichment experiment in a mature, P-limited Eucalyptus forest. We show that most models predicted the correct sign and magnitude of the CO2 effect on ecosystem carbon (C) sequestration, but they generally overestimated the effects on plant C uptake and growth. We identify leaf-to-canopy scaling of photosynthesis, plant tissue stoichiometry, plant belowground C allocation, and the subsequent consequences for plant-microbial interaction as key areas in which models of ecosystem C-P interaction can be improved. Together, this data-model intercomparison reveals data-driven insights into the performance and functionality of P-enabled models and adds to the existing evidence that the global CO2-driven carbon sink is overestimated by models. [ABSTRACT FROM AUTHOR]

Aim: Increased tree mortality linked to droughts and fires is occurring across temperate regions globally. Vegetation recovery has been widely reported; however, less is known about how disturbance may alter forests structurally and functionally across environmental gradients. We examined whether dry forests growing on low‐fertility soils were more resilient to coupled extreme drought and severe fire owing to lower tree mortality rates, higher resprouting success and persistence of juveniles relative to wetter forests on more fertile soils. Location: Fire‐tolerant eucalypt forests of temperate southeastern Australia. Time period: 2020–2023. Major taxa studied: Eucalyptus, Corymbia, Angophora. Methods: Demographic surveys of tree mortality and regeneration in all combinations of dry/wet forest, fertile/less fertile substrates exposed to extreme drought and fire were conducted. We used Bayesian regression modelling to compare tree mortality, diameter, response traits, population structure and occurrence of fire scars between substrates/forest types. Results: Overall mortality (20%–33%) and topkill (34%–41%) were within historically reported ranges for various forests and soil types. However, we observed an atypical trend of increased mortality and topkill in the largest trees, particularly when they had structural damage from past fires. Trees in wet forests on more fertile soils had the highest levels of mortality. Numbers of persistent resprouting juveniles were highest in dry forests on low‐fertility soils. Dry forests growing on low‐fertility soils appear more resilient to compound disturbances due to lower rates of mortality and higher rates of juvenile persistence. Wet forests on more fertile soils may experience greater demographic change due to higher mortality of small and large trees. Main conclusions: Mesic forests on relatively fertile soils were found to be at relatively high risk of demographic change from compound disturbances. Combined, fire and drought are likely to reduce the number of large trees in affected areas, with consequences for forest carbon cycling and storage. [ABSTRACT FROM AUTHOR]

NK cell-mediated cytotoxicity is a critical element of our immune system required for protection from microbial infections and cancer. NK cells bind to and eliminate infected or cancerous cells via direct secretion of cytotoxic molecules toward the bound target cells. In this review, we summarize the current understanding of the molecular regulations of NK cell cytotoxicity, focusing on lytic granule development and degranulation processes. NK cells synthesize apoptosis-inducing proteins and package them into specialized organelles known as lytic granules (LGs). Upon activation of NK cells, LGs converge with the microtubule organizing center through dynein-dependent movement along microtubules, ultimately polarizing to the cytotoxic synapse where they subsequently fuse with the NK plasma membrane. From LGs biogenesis to degranulation, NK cells utilize several strategies to protect themselves from their own cytotoxic molecules. Additionally, molecular pathways that enable NK cells to perform serial killing are beginning to be elucidated. These advances in the understanding of the molecular pathways behind NK cell cytotoxicity will be important to not only improve current NK cell-based anti-cancer therapies but also to support the discovery of additional therapeutic opportunities.

Between late 2015 and early 2016, more than 7,000 ha of mangrove forest died along the coastline of the Gulf of Carpentaria, in northern Australia. This massive die-off was preceded by a strong 2015/2016 El Niño event, resulting in lower precipitation, a drop in sea level and higher than average temperatures in northern Australia. In this study, we investigated the role of hydraulic failure in the mortality and recovery of the dominant species, Avicennia marina, 2 years after the mortality event. We measured predawn water potential (Ψpd) and percent loss of stem hydraulic conductivity (PLC) in surviving individuals across a gradient of impact. We also assessed the vulnerability to drought-induced embolism (Ψ50) for the species. Areas with severe canopy dieback had higher native PLC (39%) than minimally impacted areas (6%), suggesting that hydraulic recovery was ongoing. The high resistance of A. marina to water-stress-induced embolism (Ψ50 = −9.6 MPa), indicates that severe water stress (Ψpd < −10 MPa) would have been required to cause mortality in this species. Our data indicate that the natural gradient of water-stress enhanced the impact of El Niño, leading to hydraulic failure and mortality in A. marina growing on severely impacted (SI) zones. It is likely that lowered sea levels and less frequent inundation by seawater, combined with lower inputs of fresh water, high evaporative demand and high temperatures, led to the development of hyper-salinity and extreme water stress during the 2015/16 summer.

Abstract Stomatal conductance schemes that optimize with respect to photosynthetic and hydraulic functions have been proposed to address biases in land‐surface model (LSM) simulations during drought. However, systematic evaluations of both optimality‐based and alternative empirical formulations for coupling carbon and water fluxes are lacking. Here, we embed 12 empirical and optimization approaches within a LSM framework. We use theoretical model experiments to explore parameter identifiability and understand how model behaviors differ in response to abiotic changes. We also evaluate the models against leaf‐level observations of gas‐exchange and hydraulic variables, from xeric to wet forest/woody species spanning a mean annual precipitation range of 361–3,286 mm yr−1. We find that models differ in how easily parameterized they are, due to: (a) poorly constrained optimality criteria (i.e., resulting in multiple solutions), (b) low influence parameters, (c) sensitivities to environmental drivers. In both the idealized experiments and compared to observations, sensitivities to variability in environmental drivers do not agree among models. Marked differences arise in sensitivities to soil moisture (soil water potential) and vapor pressure deficit. For example, stomatal closure rates at high vapor pressure deficit range between −45% and +70% of those observed. Although over half the new generation of stomatal schemes perform to a similar standard compared to observations of leaf‐gas exchange, two models do so through large biases in simulated leaf water potential (up to 11 MPa). Our results provide guidance for LSM development, by highlighting key areas in need for additional experimentation and theory, and by constraining currently viable stomatal hypotheses.

Land surface models underpin coupled climate model projections of droughts and heatwaves. However, the lack of simultaneous observations of individual components of evapotranspiration, concurrent with root-zone soil moisture, has limited previous model evaluations. Here, we use a comprehensive set of observations from a water-limited site in southeastern Australia including both evapotranspiration and soil moisture to a depth of 4.5 m to evaluate the Community Atmosphere-Biosphere Land Exchange (CABLE) land surface model. We demonstrate that alternative process representations within CABLE had the capacity to improve simulated evapotranspiration, but not necessarily soil moisture dynamics–highlighting problems of model evaluations against water fluxes alone. Our best simulation was achieved by resolving a soil evaporation bias, using a more realistic initialisation of the groundwater aquifer state and higher vertical soil resolution informed by observed soil properties, and further calibrating soil hydraulic conductivity. Despite these improvements, the role of the empirical soil moisture stress function in influencing the simulated water fluxes remained important: using a site-calibrated function reduced the soil water stress on plants by 36 % during drought and 23 % at other times. These changes in CABLE not only improve the seasonal cycle of evapotranspiration but also affect the latent and sensible heat fluxes during droughts and heatwaves. The range of parameterisations tested led to differences of ∼150 W m−2 in the simulated latent heat flux during a heatwave, implying a strong impact of parameterisations on the capacity for evaporative cooling and feedbacks to the boundary layer (when coupled). Overall, our results highlight the opportunity to advance the capability of land surface models to capture water cycle processes, particularly during meteorological extremes, when sufficient observations of both evapotranspiration fluxes and soil moisture profiles are available.

Understanding the biophysical limitations on forest carbon across diverse ecological regions is crucial for accurately assessing and managing forest carbon stocks. This study investigates the role of climate and disturbance on the spatial variation of two key forest carbon pools: aboveground carbon (AGC) and soil organic carbon (SOC). Using plot‐level carbon pool estimates from Nepal's national forest inventory and structural equation modelling, we explore the relationship of forest carbon stocks to broad‐scale climatic water and energy availability and fine‐scale terrain and disturbance. The forest AGC and SOC models explained 25% and 59% of the observed spatial variation in forest AGC and SOC, respectively. Among the evaluated variables, disturbance exhibited the strongest negative correlation with AGC, while the availability of climatic energy demonstrated the strongest negative correlation with SOC. Disturbances such as selective logging and firewood collection result in immediate forest carbon loss, while soil carbon changes take longer to respond. The lower decomposition rates in the high‐elevation region, due to lower temperatures, preserve organic matter and contribute to the high SOC stocks observed there. These results highlight the critical role of climate and disturbance regimes in shaping landscape patterns of forest carbon stocks. Understanding the underlying drivers of these patterns is crucial for forest carbon management and conservation across diverse ecological zones including the Central Himalayas. [ABSTRACT FROM AUTHOR]

The forest–atmosphere exchange of carbon and water is regulated by meteorological conditions as well as canopy properties such as leaf area index (LAI, m2 m−2), photosynthetic capacity (PC μmol m−2 s−1), or surface conductance in optimal conditions (Gs,opt, mmol m−2 s−1), which can vary seasonally and inter-annually. This variability is well understood for deciduous species but is poorly characterized in evergreen forests. Here, we quantify the seasonal dynamics of a temperate evergreen eucalypt forest with estimates of LAI, litterfall, carbon and water fluxes, and meteorological conditions from measurements and model simulations. We merged MODIS Enhanced Vegetation Index (EVI) values with site-based LAI measurements to establish a 17-year sequence of monthly LAI. We ran the Community Atmosphere Biosphere Land Exchange model (CABLE-POP (version r5046)) with constant and varying LAI for our site to quantify the influence of seasonal canopy dynamics on carbon and water fluxes. We observed that the peak of LAI occurred in late summer–early autumn, with a higher and earlier peak occurring in years when summer rainfall was greater. Seasonality in litterfall and allocation of net primary productivity (FNPP) to leaf growth (af, 0–1) drove this pattern, suggesting a complete renewal of the canopy before the timing of peak LAI. Litterfall peaked in spring, followed by a high af in summer, at the end of which LAI peaked, and PC and Gs,opt reached their maximum values in autumn, resulting from a combination of high LAI and efficient mature leaves. These canopy dynamics helped explain observations of maximum gross ecosystem production (FGEP) in spring and autumn and net ecosystem carbon loss in summer at our site. Inter-annual variability in LAI was positively correlated with Net Ecosystem Production (FNEP). It would be valuable to apply a similar approach to other temperate evergreen forests to identify broad patterns of seasonality in leaf growth and turnover. Because incorporating dynamic LAI was insufficient to fully capture the dynamics of FGEP, observations of seasonal variation in photosynthetic capacity, such as from solar-induced fluorescence, should be incorporated in land surface models to improve ecosystem flux estimates in evergreen forests. [ABSTRACT FROM AUTHOR]

Shifts in the timing, intensity and/or frequency of climate extremes, such as severe drought and heatwaves, can generate sustained shifts in ecosystem function with important ecological and economic impacts for rangelands and managed pastures. The Pastures and Climate Extremes experiment (PACE) in Southeast Australia was designed to investigate the impacts of a severe winter/spring drought (60% rainfall reduction) and, for a subset of species, a factorial combination of drought and elevated temperature (ambient +3°C) on pasture productivity. The experiment included nine common pasture and Australian rangeland species from three plant functional groups (C3 grasses, C4 grasses and legumes) planted in monoculture. Winter/spring drought resulted in productivity declines of 45% on average and up to 74% for the most affected species (Digitaria eriantha) during the 6-month treatment period, with eight of the nine species exhibiting significant yield reductions. Despite considerable variation in species’ sensitivity to drought, C4 grasses were more strongly affected by this treatment than C3 grasses or legumes. Warming also had negative effects on cool-season productivity, associated at least partially with exceedance of optimum growth temperatures in spring and indirect effects on soil water content. The combination of winter/spring drought and year-round warming resulted in the greatest yield reductions. We identified responses that were either additive (Festuca), or less-than-additive (Medicago), where warming reduced the magnitude of drought effects. Results from this study highlight the sensitivity of diverse pasture species to increases in winter and spring drought severity similar to those predicted for this region, and that anticipated benefits of cool-season warming are unlikely to be realized. Overall, the substantial negative impacts on productivity suggest that future, warmer, drier climates will result in shortfalls in cool-season forage availability, with profound implications for the livestock industry and natural grazer communities.