Extensive global wetland loss over the past three centuries.

Wetlands have long been drained for human use, thereby strongly affecting greenhouse gas fluxes, flood control, nutrient cycling and biodiversity1,2. Nevertheless, the global extent of natural wetland loss remains remarkably uncertain3. Here, we reconstruct the spatial distribution and timing of wetland loss through conversion to seven human land uses between 1700 and 2020, by combining national and subnational records of drainage and conversion with land-use maps and simulated wetland extents. We estimate that 3.4 million km2 (confidence interval 2.9-3.8) of inland wetlands have been lost since 1700, primarily for conversion to croplands. This net loss of 21% (confidence interval 16-23%) of global wetland area is lower than that suggested previously by extrapolations of data disproportionately from high-loss regions. Wetland loss has been concentrated in Europe, the United States and China, and rapidly expanded during the mid-twentieth century. Our reconstruction elucidates the timing and land-use drivers of global wetland losses, providing an improved historical baseline to guide assessment of wetland loss impact on Earth system processes, conservation planning to protect remaining wetlands and prioritization of sites for wetland restoration4.

Tree water uptake patterns across the globe.

Plant water uptake from the soil is a crucial element of the global hydrological cycle and essential for vegetation drought resilience. Yet, knowledge of how the distribution of water uptake depth (WUD) varies across species, climates, and seasons is scarce relative to our knowledge of aboveground plant functions. With a global literature review, we found that average WUD varied more among biomes than plant functional types (i.e. deciduous/evergreen broadleaves and conifers), illustrating the importance of the hydroclimate, especially precipitation seasonality, on WUD. By combining records of rooting depth with WUD, we observed a consistently deeper maximum rooting depth than WUD with the largest differences in arid regions - indicating that deep taproots act as lifelines while not contributing to the majority of water uptake. The most ubiquitous observation across the literature was that woody plants switch water sources to soil layers with the highest water availability within short timescales. Hence, seasonal shifts to deep soil layers occur across the globe when shallow soils are drying out, allowing continued transpiration and hydraulic safety. While there are still significant gaps in our understanding of WUD, the consistency across global ecosystems allows integration of existing knowledge into the next generation of vegetation process models.

Empirical evidence and theoretical understanding of ecosystem carbon and nitrogen cycle interactions.

Interactions between carbon (C) and nitrogen (N) cycles in terrestrial ecosystems are simulated in advanced vegetation models, yet methodologies vary widely, leading to divergent simulations of past land C balance trends. This underscores the need to reassess our understanding of ecosystem processes, given recent theoretical advancements and empirical data. We review current knowledge, emphasising evidence from experiments and trait data compilations for vegetation responses to CO2 and N input, alongside theoretical and ecological principles for modelling. N fertilisation increases leaf N content but inconsistently enhances leaf-level photosynthetic capacity. Whole-plant responses include increased leaf area and biomass, with reduced root allocation and increased aboveground biomass. Elevated atmospheric CO2 also boosts leaf area and biomass but intensifies belowground allocation, depleting soil N and likely reducing N losses. Global leaf traits data confirm these findings, indicating that soil N availability influences leaf N content more than photosynthetic capacity. A demonstration model based on the functional balance hypothesis accurately predicts responses to N and CO2 fertilisation on tissue allocation, growth and biomass, offering a path to reduce uncertainty in global C cycle projections.

Quantifying effects of cold acclimation and delayed springtime photosynthesis resumption in northern ecosystems.

Land carbon dynamics in temperate and boreal ecosystems are sensitive to environmental change. Accurately simulating gross primary productivity (GPP) and its seasonality is key for reliable carbon cycle projections. However, significant biases have been found in early spring GPP simulations of northern forests, where observations often suggest a later resumption of photosynthetic activity than predicted by models. Here, we used eddy covariance-based GPP estimates from 39 forest sites that differ by their climate and dominant plant functional types. We used a mechanistic and an empirical light use efficiency (LUE) model to investigate the magnitude and environmental controls of delayed springtime photosynthesis resumption (DSPR) across sites. We found DSPR reduced ecosystem LUE by 30-70% at many, but not all site-years during spring. A significant depression of LUE was found not only in coniferous but also at deciduous forests and was related to combined high radiation and low minimum temperatures. By embedding cold-acclimation effects on LUE that considers the delayed effects of minimum temperatures, initial model bias in simulated springtime GPP was effectively resolved. This provides an approach to improve GPP estimates by considering physiological acclimation and enables more reliable simulations of photosynthesis in northern forests and projections in a warming climate.

Diagnosing evapotranspiration responses to water deficit across biomes using deep learning.

Accounting for water limitation is key to determining vegetation sensitivity to drought. Quantifying water limitation effects on evapotranspiration (ET) is challenged by the heterogeneity of vegetation types, climate zones and vertically along the rooting zone. Here, we train deep neural networks using flux measurements to study ET responses to progressing drought conditions. We determine a water stress factor (fET) that isolates ET reductions from effects of atmospheric aridity and other covarying drivers. We regress fET against the cumulative water deficit, which reveals the control of whole-column moisture availability. We find a variety of ET responses to water stress. Responses range from rapid declines of fET to 10% of its water-unlimited rate at several savannah and grassland sites, to mild fET reductions in most forests, despite substantial water deficits. Most sensitive responses are found at the most arid and warm sites. A combination of regulation of stomatal and hydraulic conductance and access to belowground water reservoirs, whether in groundwater or deep soil moisture, could explain the different behaviors observed across sites. This variety of responses is not captured by a standard land surface model, likely reflecting simplifications in its representation of belowground water storage.

Application of the rapid leaf A-Ci response (RACiR) technique: examples from evergreen broadleaved species.

Using steady-state photosynthesis-intercellular CO2 concentration (A-Ci) response curves to obtain the maximum rates of ribulose-1,5-bisphosphate carboxylase oxygenase carboxylation (Vcmax) and electron transport (Jmax) is time-consuming and labour-intensive. Instead, the rapid A-Ci response (RACiR) technique provides a potential, high-efficiency method. However, efficient parameter settings of RACiR technique for evergreen broadleaved species remain unclear. Here, we used Li-COR LI-6800 to obtain the optimum parameter settings of RACiR curves for evergreen broadleaved trees and shrubs. We set 11 groups of CO2 gradients ([CO2]), i.e. R1 (400-1500 ppm), R2 (400-200-800 ppm), R3 (420-20-620 ppm), R4 (420-20-820 ppm), R5 (420-20-1020 ppm), R6 (420-20-1220 ppm), R7 (420-20-1520 ppm), R8 (420-20-1820 ppm), R9 (450-50-650 ppm), R10 (650-50 ppm) and R11 (650-50-650 ppm), and then compared the differences between steady-state A-Ci and RACiR curves. We found that Vcmax and Jmax calculated by steady-state A-Ci and RACiR curves overall showed no significant differences across 11 [CO2] gradients (P > 0.05). For the studied evergreens, the efficiency and accuracy of R2, R3, R4, R9 and R10 were higher than the others. Hence, we recommend that the [CO2] gradients of R2, R3, R4, R9 and R10 could be applied preferentially for measurements when using the RACiR technique to obtain Vcmax and Jmax of evergreen broadleaved species.

Environmental controls on the light use efficiency of terrestrial gross primary production.

Gross primary production (GPP) by terrestrial ecosystems is a key quantity in the global carbon cycle. The instantaneous controls of leaf-level photosynthesis are well established, but there is still no consensus on the mechanisms by which canopy-level GPP depends on spatial and temporal variation in the environment. The standard model of photosynthesis provides a robust mechanistic representation for C3 species; however, additional assumptions are required to "scale up" from leaf to canopy. As a consequence, competing models make inconsistent predictions about how GPP will respond to continuing environmental change. This problem is addressed here by means of an empirical analysis of the light use efficiency (LUE) of GPP inferred from eddy covariance carbon dioxide flux measurements, in situ measurements of photosynthetically active radiation (PAR), and remotely sensed estimates of the fraction of PAR (fAPAR) absorbed by the vegetation canopy. Focusing on LUE allows potential drivers of GPP to be separated from its overriding dependence on light. GPP data from over 100 sites, collated over 20 years and located in a range of biomes and climate zones, were extracted from the FLUXNET2015 database and combined with remotely sensed fAPAR data to estimate daily LUE. Daytime air temperature, vapor pressure deficit, diffuse fraction of solar radiation, and soil moisture were shown to be salient predictors of LUE in a generalized linear mixed-effects model. The same model design was fitted to site-based LUE estimates generated by 16 terrestrial ecosystem models. The published models showed wide variation in the shape, the strength, and even the sign of the environmental effects on modeled LUE. These findings highlight important model deficiencies and suggest a need to progress beyond simple "goodness of fit" comparisons of inferred and predicted carbon fluxes toward an approach focused on the functional responses of the underlying dependencies.

When things get MESI: The Manipulation Experiments Synthesis Initiative-A coordinated effort to synthesize terrestrial global change experiments.

Responses of the terrestrial biosphere to rapidly changing environmental conditions are a major source of uncertainty in climate projections. In an effort to reduce this uncertainty, a wide range of global change experiments have been conducted that mimic future conditions in terrestrial ecosystems, manipulating CO2 , temperature, and nutrient and water availability. Syntheses of results across experiments provide a more general sense of ecosystem responses to global change, and help to discern the influence of background conditions such as climate and vegetation type in determining global change responses. Several independent syntheses of published data have yielded distinct databases for specific objectives. Such parallel, uncoordinated initiatives carry the risk of producing redundant data collection efforts and have led to contrasting outcomes without clarifying the underlying reason for divergence. These problems could be avoided by creating a publicly available, updatable, curated database. Here, we report on a global effort to collect and curate 57,089 treatment responses across 3644 manipulation experiments at 1145 sites, simulating elevated CO2 , warming, nutrient addition, and precipitation changes. In the resulting Manipulation Experiments Synthesis Initiative (MESI) database, effects of experimental global change drivers on carbon and nutrient cycles are included, as well as ancillary data such as background climate, vegetation type, treatment magnitude, duration, and, unique to our database, measured soil properties. Our analysis of the database indicates that most experiments are short term (one or few growing seasons), conducted in the USA, Europe, or China, and that the most abundantly reported variable is aboveground biomass. We provide the most comprehensive multifactor global change database to date, enabling the research community to tackle open research questions, vital to global policymaking. The MESI database, freely accessible at doi.org/10.5281/zenodo.7153253, opens new avenues for model evaluation and synthesis-based understanding of how global change affects terrestrial biomes. We welcome contributions to the database on GitHub.

Subtotal Fenestrating Cholecystectomy: A Safe and Effective Approach to the Difficult Gallbladder.

INTRODUCTION: Subtotal laparoscopic cholecystectomy (SUB) is an alternative to total laparoscopic cholecystectomy (TOT) when the critical view of safety (CVS) cannot be achieved. Little is known about the clinical factors and postoperative outcomes associated with SUB. The objective was to determine predictive factors and outcomes of SUB as compared to TOT. METHODS: Clinical data from patients admitted from our emergency department to the acute care surgery service who underwent SUB or TOT by an acute care surgery surgeon for acute biliary disease (2017-2019) were reviewed. Wilcoxon rank-sum and Fisher's exact tests were used. RESULTS: 355 patients underwent cholecystectomy for acute cholecystitis; 28 were SUB (7.9%). SUB patients were more likely to be older (57 versus 43 y; P = 0.015), male (60.7% versus 39.3%; P < 0.001), have a history of cirrhosis or liver disease (14.3% versus 2.1%; P = 0.007), and have a higher Charlson-Comorbidity Index (1 versus 0, P = 0.041). SUB had greater leukocytosis (14.6 versus 10.9; P < 0.001), higher total bilirubin (0.9 versus 0.6; P = 0.021), and a higher Tokyo grade (2 versus 1; P < 0.001), and had operative findings including gallbladder decompression (82.1% versus 23.2%; P < 0.001) and inability to achieve the CVS (78.6% versus 3.4%; P < 0.001). SUB patients had an increased length of stay (4 versus 2 d; P < 0.001) and more 1-y readmissions. No major vascular injuries occurred in either group with one biliary injury in the TOT group. CONCLUSIONS: SUB patients present with more significant markers of biliary disease and have more complicated intraoperative and postoperative courses. However, the lack of biliary or vascular injuries suggests that SUB may represent a safe alternative when the CVS cannot be achieved.

Photosynthetic acclimation and sensitivity to short- and long-term environmental changes in a drought-prone forest.

Future climate will be characterized by an increase in frequency and duration of drought and warming that exacerbates atmospheric evaporative demand. How trees acclimate to long-term soil moisture changes and whether these long-term changes alter trees' sensitivity to short-term (day to months) variations of vapor pressure deficit (VPD) and soil moisture is largely unknown. Leaf gas exchange measurements were performed within a long-term (17 years) irrigation experiment in a drought-prone Scots pine-dominated forest in one of Switzerland's driest areas on trees in naturally dry (control), irrigated, and 'irrigation-stop' (after 11 years of irrigation) conditions. Seventeen years of irrigation increased photosynthesis (A) and stomatal conductance (gs) and reduced gs sensitivity to increasing VPD and soil drying. Following irrigation-stop, gas exchange decreased only after 3 years. After 5 years, maximum carboxylation (Vcmax) and electron transport (Jmax) rates in irrigation-stop recovered to similar levels as to before the irrigation-stop. These results suggest that long-term release from soil drought reduces the sensitivity to VPD and that atmospheric constraints may play an increasingly important role in combination with soil drought. Moreover, our study indicates that structural adjustments lead to an attenuation of initially strong leaf-level acclimation to strong multiple-year drought.

Disentangling the role of photosynthesis and stomatal conductance on rising forest water-use efficiency.

Multiple lines of evidence suggest that plant water-use efficiency (WUE)-the ratio of carbon assimilation to water loss-has increased in recent decades. Although rising atmospheric CO2 has been proposed as the principal cause, the underlying physiological mechanisms are still being debated, and implications for the global water cycle remain uncertain. Here, we addressed this gap using 30-y tree ring records of carbon and oxygen isotope measurements and basal area increment from 12 species in 8 North American mature temperate forests. Our goal was to separate the contributions of enhanced photosynthesis and reduced stomatal conductance to WUE trends and to assess consistency between multiple commonly used methods for estimating WUE. Our results show that tree ring-derived estimates of increases in WUE are consistent with estimates from atmospheric measurements and predictions based on an optimal balancing of carbon gains and water costs, but are lower than those based on ecosystem-scale flux observations. Although both physiological mechanisms contributed to rising WUE, enhanced photosynthesis was widespread, while reductions in stomatal conductance were modest and restricted to species that experienced moisture limitations. This finding challenges the hypothesis that rising WUE in forests is primarily the result of widespread, CO2-induced reductions in stomatal conductance.

Eco-evolutionary optimality as a means to improve vegetation and land-surface models.

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 studies that demonstrate how EEO generates 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 to environmental change.

Challenges in Predicting Discharge Disposition for Trauma and Emergency General Surgery Patients.

BACKGROUND: Changes in discharge disposition and delays in discharge negatively impact the patient and hospital system. Our objectives were1 to determine the accuracy with which trauma and emergency general surgery (TEGS) providers could predict the discharge disposition for patients and2 determine the factors associated with incorrect predictions. METHODS: Discharge dispositions and barriers to discharge for 200 TEGS patients were predicted individually by members of the multidisciplinary TEGS team within 24 h of patient admission. Univariate analyses and multivariable logistic least absolute shrinkage and selection operator regressions determined the associations between patient characteristics and correct predictions. RESULTS: A total of 1,498 predictions of discharge disposition were made by the multidisciplinary TEGS team for 200 TEGS patients. Providers correctly predicted 74% of discharge dispositions. Prediction accuracy was not associated with clinical experience or job title. Incorrect predictions were independently associated with older age (OR 0.98; P < 0.001), trauma admission as compared to emergency general surgery (OR 0.33; P < 0.001), higher Injury Severity Scores (OR 0.96; P < 0.001), longer lengths of stay (OR 0.90; P < 0.001), frailty (OR 0.43; P = 0.001), ICU admission (OR 0.54; P < 0.001), and higher Acute Physiology and Chronic Health Evaluation II scores (OR 0.94; P = 0.006). CONCLUSION: The TEGS team can accurately predict the majority of discharge dispositions. Patients with risk factors for unpredictable dispositions should be flagged to better allocate appropriate resources and more intensively plan their discharges.

Electronic Medical Record Versus Bedside Assessment: How to Evaluate Frailty in Trauma and Emergency General Surgery Patients?

BACKGROUND: Screening patients for frailty is traditionally done at the bedside. However, recent electronic medical record (EMR)-based, comorbidity-focused frailty assessments have been developed. Our objective was to determine how a common bedside frailty assessment, the trauma and emergency surgery (TEGS) frailty index (FI), compares to an EMR-based frailty assessment in predicting geriatric TEGS outcomes. MATERIALS AND METHODS: We retrospectively reviewed our quality improvement project database consisting of TEGS patients ≥ 65 y old. Patients were screened with the TEGS FI, a 15-question bedside assessment, including comorbidities, physical activity, emotional health, and nutrition. Six of 15 items were retrievable from the enterprise data warehouse (EDW), storing all EMR data from Northwestern Memorial Hospital, and use to calculate the EDW frailty score. Patient characteristics and outcomes were compared between different groups. RESULTS: Two hundred thirty-six geriatric TEGS patients were included, of which 75 (31.8%) were TEGS FI frail and 60 (25.4%) were EDW frail. TEGS FI frail patients had increased length of stay (LOS), loss of independence (LOI), and complications compared to TEGS FI nonfrail patients. EDW frail patients had higher LOS and complications than EDW nonfrail patients but similar LOI. TEGS FI and EDW frail patients had similar outcomes except TEGS FI-only patients more often have LOI. CONCLUSIONS: Bedside frailty assessments and EMR-based assessments are both effective in identifying geriatric TEGS patients at risk for increased LOS and complications. However, bedside frailty screening was better at identifying patients who have LOI and may be a more appropriate choice when screening for frailty.

Simulation-Based Course Improves Resident Comfort, Knowledge, and Ability to Manage Surgical Intensive Care Unit Patients.

BACKGROUND: Simulation-based education can augment residents' skills and knowledge. We assessed the effectiveness of a simulation-based course for surgery interns designed to improve their comfort, knowledge, and ability to manage common surgical critical care (SCC) conditions. MATERIALS AND METHODS: For 2 y, all first year residents (n = 31) in general surgery, urology, interventional radiology, and the integrated plastics, vascular, and cardiothoracic surgery training programs at our institution participated in a simulation-based course emphasizing evidence-based management of SCC conditions. Precourse and postcourse surveys and multiple-choice tests, as well as summative simulation tests, assessed interns' comfort, knowledge, and ability to manage SCC conditions. Changes in these measures were assessed with Wilcoxon matched-pairs signed rank tests. Factors associated with summative performance were determined by linear regression. RESULTS: The course consisted of four simulation-based teaching sessions in year 1 and six in year 2. The course taught seven of the 18 core SCC conditions in the Surgical Council on Resident Education general surgery curriculum in year 1 and 10 in year 2. Interns' self-reported comfort, knowledge, and ability to manage each condition taught in the course increased (P < 0.02). Their knowledge of each condition, as assessed by written tests, also increased (P < 0.02). Their summative simulation test performance correlated with the number of course sessions attended (P < 0.03) and status as general surgery residents (P < 0.01). CONCLUSIONS: A simulation-based SCC training course for surgery interns that emphasizes evidence-based management of SCC conditions improves interns' comfort, knowledge, and ability to manage these conditions.

Holocene peatland and ice-core data constraints on the timing and magnitude of CO2 emissions from past land use.

CO2 emissions from preindustrial land-use change (LUC) are subject to large uncertainties. Although atmospheric CO2 records suggest only a small land carbon (C) source since 5,000 y before present (5 kyBP), the concurrent C sink by peat buildup could mask large early LUC emissions. Here, we combine updated continuous peat C reconstructions with the land C balance inferred from double deconvolution analyses of atmospheric CO2 and [Formula: see text]C at different temporal scales to investigate the terrestrial C budget of the Holocene and the last millennium and constrain LUC emissions. LUC emissions are estimated with transient model simulations for diverging published scenarios of LU area change and shifting cultivation. Our results reveal a large terrestrial nonpeatland C source after the Mid-Holocene (66 [Formula: see text] 25 PgC at 7-5 kyBP and 115 [Formula: see text] 27 PgC at 5-3 kyBP). Despite high simulated per-capita CO2 emissions from LUC in early phases of agricultural development, humans emerge as a driver with dominant global C cycle impacts only in the most recent three millennia. Sole anthropogenic causes for particular variations in the CO2 record ([Formula: see text]20 ppm rise after 7 kyBP and [Formula: see text]10 ppm fall between 1500 CE and 1600 CE) are not supported. This analysis puts a strong constraint on preindustrial vs. industrial-era LUC emissions and suggests that upper-end scenarios for the extent of agricultural expansion before 1850 CE are not compatible with the C budget thereafter.

Quantifying soil moisture impacts on light use efficiency across biomes.

Terrestrial primary productivity and carbon cycle impacts of droughts are commonly quantified using vapour pressure deficit (VPD) data and remotely sensed greenness, without accounting for soil moisture. However, soil moisture limitation is known to strongly affect plant physiology. Here, we investigate light use efficiency, the ratio of gross primary productivity (GPP) to absorbed light. We derive its fractional reduction due to soil moisture (fLUE), separated from VPD and greenness changes, using artificial neural networks trained on eddy covariance data, multiple soil moisture datasets and remotely sensed greenness. This reveals substantial impacts of soil moisture alone that reduce GPP by up to 40% at sites located in sub-humid, semi-arid or arid regions. For sites in relatively moist climates, we find, paradoxically, a muted fLUE response to drying soil, but reduced fLUE under wet conditions. fLUE identifies substantial drought impacts that are not captured when relying solely on VPD and greenness changes and, when seasonally recurring, are missed by traditional, anomaly-based drought indices. Counter to common assumptions, fLUE reductions are largest in drought-deciduous vegetation, including grasslands. Our results highlight the necessity to account for soil moisture limitation in terrestrial primary productivity data products, especially for drought-related assessments.

Ecosystem responses to elevated CO2 governed by plant-soil interactions and the cost of nitrogen acquisition.

Contents Summary 507 I. Introduction 507 II. The return on investment approach 508 III. CO2 response spectrum 510 IV. Discussion 516 Acknowledgements 518 References 518 SUMMARY: Land ecosystems sequester on average about a quarter of anthropogenic CO2 emissions. It has been proposed that nitrogen (N) availability will exert an increasingly limiting effect on plants' ability to store additional carbon (C) under rising CO2 , but these mechanisms are not well understood. Here, we review findings from elevated CO2 experiments using a plant economics framework, highlighting how ecosystem responses to elevated CO2 may depend on the costs and benefits of plant interactions with mycorrhizal fungi and symbiotic N-fixing microbes. We found that N-acquisition efficiency is positively correlated with leaf-level photosynthetic capacity and plant growth, and negatively with soil C storage. Plants that associate with ectomycorrhizal fungi and N-fixers may acquire N at a lower cost than plants associated with arbuscular mycorrhizal fungi. However, the additional growth in ectomycorrhizal plants is partly offset by decreases in soil C pools via priming. Collectively, our results indicate that predictive models aimed at quantifying C cycle feedbacks to global change may be improved by treating N as a resource that can be acquired by plants in exchange for energy, with different costs depending on plant interactions with microbial symbionts.

Ensemble reconstruction constraints on the global carbon cycle sensitivity to climate.

The processes controlling the carbon flux and carbon storage of the atmosphere, ocean and terrestrial biosphere are temperature sensitive and are likely to provide a positive feedback leading to amplified anthropogenic warming. Owing to this feedback, at timescales ranging from interannual to the 20-100-kyr cycles of Earth's orbital variations, warming of the climate system causes a net release of CO(2) into the atmosphere; this in turn amplifies warming. But the magnitude of the climate sensitivity of the global carbon cycle (termed gamma), and thus of its positive feedback strength, is under debate, giving rise to large uncertainties in global warming projections. Here we quantify the median gamma as 7.7 p.p.m.v. CO(2) per degrees C warming, with a likely range of 1.7-21.4 p.p.m.v. CO(2) per degrees C. Sensitivity experiments exclude significant influence of pre-industrial land-use change on these estimates. Our results, based on the coupling of a probabilistic approach with an ensemble of proxy-based temperature reconstructions and pre-industrial CO(2) data from three ice cores, provide robust constraints for gamma on the policy-relevant multi-decadal to centennial timescales. By using an ensemble of >200,000 members, quantification of gamma is not only improved, but also likelihoods can be assigned, thereby providing a benchmark for future model simulations. Although uncertainties do not at present allow exclusion of gamma calculated from any of ten coupled carbon-climate models, we find that gamma is about twice as likely to fall in the lowermost than in the uppermost quartile of their range. Our results are incompatibly lower (P < 0.05) than recent pre-industrial empirical estimates of approximately 40 p.p.m.v. CO(2) per degrees C (refs 6, 7), and correspondingly suggest approximately 80% less potential amplification of ongoing global warming.

Environmental versus phylogenetic controls on leaf nitrogen and phosphorous concentrations in vascular plants.

Global patterns of leaf nitrogen (N) and phosphorus (P) stoichiometry have been interpreted as reflecting phenotypic plasticity in response to the environment, or as an overriding effect of the distribution of species growing in their biogeochemical niches. Here, we balance these contrasting views. We compile a global dataset of 36,413 paired observations of leaf N and P concentrations, taxonomy and 45 environmental covariates, covering 7,549 sites and 3,700 species, to investigate how species identity and environmental variables control variations in mass-based leaf N and P concentrations, and the N:P ratio. We find within-species variation contributes around half of the total variation, with 29%, 31%, and 22% of leaf N, P, and N:P variation, respectively, explained by environmental variables. Within-species plasticity along environmental gradients varies across species and is highest for leaf N:P and lowest for leaf N. We identified effects of environmental variables on within-species variation using random forest models, whereas effects were largely missed by widely used linear mixed-effect models. Our analysis demonstrates a substantial influence of the environment in driving plastic responses of leaf N, P, and N:P within species, which challenges reports of a fixed biogeochemical niche and the overriding importance of species distributions in shaping global patterns of leaf N and P.