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Water deficit in the atmosphere and soil are two key interactive factors that constrain transpiration and vegetation productivity. It is not clear which of these two factors is more important for the water and carbon flux response to drought stress in ecosystems. In this study, field data and numerical modeling were used to isolate their impact on evapotranspiration (ET) and gross primary productivity (GPP) at a tropical forest site in Barro Colorado Island (BCI), Panama, focusing on their response to the drought induced by the El Niño event of 2015–2016. Numerical simulations were performed using a plant hydrodynamic scheme (HYDRO) and a heuristic approach that ignores stomatal sensitivity to leaf water potential in the Energy Exascale Earth System Model (E3SM) Land Model (ELM). The sensitivity of canopy conductance (Gs) to vapor pressure deficit (VPD) obtained from eddy-covariance fluxes and measured sap flux shows that, at both ecosystem and plant scale, soil water stress is more important in limiting Gs than VPD at BCI during the El Niño event. The model simulations confirmed the importance of water stress limitation on Gs, but overestimated the VPD impact on Gs compared to that estimated from the observations. We also found that the predicted soil moisture is less sensitive to the diversity of plant hydraulic traits than ET and GPP. During the dry season at BCI, seasonal ET, especially soil evaporation at VPD > 0.42 kPa, simulated using HYDRO and ELM, were too strong and will require alternative parameterizations.

Tropical forest degradation from logging, fire, and fragmentation not only alters carbon stocks and carbon fluxes, but also impacts physical land surface properties such as albedo and roughness length. Such impacts are poorly quantified to date due to difficulties in accessing and maintaining observational infrastructures, as well as the lack of proper modeling tools for capturing the interactions among biophysical properties, ecosystem demography, canopy structure, and biogeochemical cycling in tropical forests. As a first step to address these limitations, we implemented a selective logging module into the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) by mimicking the ecological, biophysical, and biogeochemical processes following a logging event. The model can specify the timing and aerial extent of logging events, splitting the logged forest patch into disturbed and intact patches; determine the survivorship of cohorts in the disturbed patch; and modifying the biomass and necromass (total mass of coarse woody debris and litter) pools following logging. We parameterized the logging module to reproduce a selective logging experiment at the Tapajós National Forest in Brazil and benchmarked model outputs against available field measurements. Our results suggest that the model permits the coexistence of early and late successional functional types and realistically characterizes the seasonality of water and carbon fluxes and stocks, the forest structure and composition, and the ecosystem succession following disturbance. However, the current version of FATES overestimates water stress in the dry season and therefore fails to capture seasonal variation in latent and sensible heat fluxes. Moreover, we observed a bias towards low stem density and leaf area when compared to observations, suggesting that improvements are needed in both carbon allocation and establishment of trees. The effects of logging were assessed by different logging scenarios to represent reduced impact and conventional logging practices, both with high and low logging intensities. The model simulations suggest that in comparison to old-growth forests the logged forests rapidly recover water and energy fluxes in 1 to 3 years. In contrast, the recovery times for carbon stocks, forest structure, and composition are more than 30 years depending on logging practices and intensity. This study lays the foundation to simulate land use change and forest degradation in FATES, which will be an effective tool to directly represent forest management practices and regeneration in the context of Earth system models.

Plant functional traits determine vegetation responses to environmental variation, but variation in trait values is large, even within a single site. Likewise, uncertainty in how these traits map to Earth system feedbacks is large. We use a vegetation demographic model (VDM), the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), to explore parameter sensitivity of model predictions, and comparison to observations, at a tropical forest site: Barro Colorado Island in Panama. We define a single 12-dimensional distribution of plant trait variation, derived primarily from observations in Panama, and define plant functional types (PFTs) as random draws from this distribution. We compare several model ensembles, where individual ensemble members vary only in the plant traits that define PFTs, and separate ensembles differ from each other based on either model structural assumptions or non-trait, ecosystem-level parameters, which include (a) the number of competing PFTs present in any simulation and (b) parameters that govern disturbance and height-based light competition. While singlePFT simulations are roughly consistent with observations of productivity at Barro Colorado Island, increasing the number of competing PFTs strongly shifts model predictions towards higher productivity and biomass forests. Different ecosystem variables show greater sensitivity than others to the number of competing PFTs, with the predictions that are most dominated by large trees, such as biomass, being the most sensitive. Changing disturbance and height-sorting parameters, i.e., the rules of competitive trait filtering, shifts regimes of dominance or coexistence between early-and late-successional PFTs in the model. Increases to the extent or severity of disturbance, or to the degree of determinism in height-based light competition, all act to shift the community towards early-successional PFTs. In turn, these shifts in competitive outcomes alter predictions of ecosystem states and fluxes, with more early-successional-dominated forests having lower biomass. It is thus crucial to differentiate between plant traits, which are under competitive pressure in VDMs, from those model parameters that are not and to better understand the relationships between these two types of model parameters to quantify sources of uncertainty in VDMs.

There is large uncertainty whether Amazon forests will remain a carbon sink as atmospheric CO2 increases. Hence, we simulated an old-growth tropical forest using six versions of four terrestrial models differing in scale of vegetation structure and representation of biogeochemical (BGC) cycling, all driven with CO2 forcing from the preindustrial period to 2100. The models were benchmarked against tree inventory and eddy covariance data from a Brazilian site for present-day predictions. All models predicted positive vegetation growth that outpaced mortality, leading to continual increases in present-day biomass accumulation. Notably, the two vegetation demographic models (VDMs) (ED2 and ELM-FATES) always predicted positive stem diameter growth in all size classes. The field data, however, indicated that a quarter of canopy trees didn't grow over the 15-year period, and while high interannual variation existed, biomass change was near neutral. With a doubling of CO2, three of the four models predicted an appreciable biomass sink (0.77 to 1.24 Mg ha−1 year−1). ELMv1-ECA, the only model used here that includes phosphorus constraints, predicted the lowest biomass sink relative to initial biomass stocks (+21%), lower than the other BGC model, CLM5 (+48%). Models projections differed primarily through variations in nutrient constraints, then carbon allocation, initial biomass, and density-dependent mortality. The VDM's performance was similar or better than the BGC models run in carbon-only mode, suggesting that nutrient competition in VDMs will improve predictions. We demonstrate that VDMs are comparable to nondemographic (i.e., “big-leaf”) models but also include finer scale demography and competition that can be evaluated against field observations.

The Ecosystem Demography model version 2.2 (ED-2.2) is a terrestrial biosphere model that simulates the biophysical, ecological, and biogeochemical dynamics of vertically and horizontally heterogeneous terrestrial ecosystems. In a companion paper (Longo et al., 2019a), we described how the model solves the energy, water, and carbon cycles, and verified the high degree of conservation of these properties in long-term simulations that include long-term (multi-decadal) vegetation dynamics. Here, we present a detailed assessment of the model's ability to represent multiple processes associated with the biophysical and biogeochemical cycles in Amazon forests. We use multiple measurements from eddy covariance towers, forest inventory plots, and regional remote-sensing products to assess the model's ability to represent biophysical, physiological, and ecological processes at multiple timescales, ranging from subdaily to century long. The ED-2.2 model accurately describes the vertical distribution of light, water fluxes, and the storage of water, energy, and carbon in the canopy air space, the regional distribution of biomass in tropical South America, and the variability of biomass as a function of environmental drivers. In addition, ED-2.2 qualitatively captures several emergent properties of the ecosystem found in observations, specifically observed relationships between aboveground biomass, mortality rates, and wood density; however, the slopes of these relationships were not accurately captured. We also identified several limitations, including the model's tendency to overestimate the magnitude and seasonality of heterotrophic respiration and to overestimate growth rates in a nutrient-poor tropical site. The evaluation presented here highlights the potential of incorporating structural and functional heterogeneity within biomes in Earth system models (ESMs) and to realistically represent their impacts on energy, water, and carbon cycles. We also identify several priorities for further model development.

Earth system models (ESMs) have been developed to represent the role of terrestrial ecosystems on the energy, water, and carbon cycles. However, many ESMs still lack representation of within-ecosystem heterogeneity and diversity. In this paper, we present the Ecosystem Demography model version 2.2 (ED-2.2). In ED-2.2, the biophysical and physiological processes account for the horizontal and vertical heterogeneity of the ecosystem: The energy, water, and carbon cycles are solved separately for a series of vegetation cohorts (groups of individual plants of similar size and plant functional type) distributed across a series of spatially implicit patches (representing collections of microenvironments that have a similar disturbance history).We define the equations that describe the energy, water, and carbon cycles in terms of total energy, water, and carbon, which simplifies the differential equations and guarantees excellent conservation of these quantities in long-term simulation (

Vegetation plays an important role in regulating global carbon cycles and is a key component of the Earth system models (ESMs) that aim to project Earth's future climate. In the last decade, the vegetation component within ESMs has witnessed great progress from simple "big-leaf" approaches to demographically structured approaches, which have a better representation of plant size, canopy structure, and disturbances. These demographically structured vegetation models typically have a large number of input parameters, and sensitivity analysis is needed to quantify the impact of each parameter on the model outputs for a better understanding of model behavior. In this study, we conducted a comprehensive sensitivity analysis to diagnose the Community Land Model coupled to the Functionally Assembled Terrestrial Simulator, or CLM4.5(FATES). Specifically, we quantified the first- and second-order sensitivities of the model parameters to outputs that represent simulated growth and mortality as well as carbon fluxes and stocks for a tropical site with an extent of 1×1°. While the photosynthetic capacity parameter (Vc;max25) is found to be important for simulated carbon stocks and fluxes, we also show the importance of carbon storage and allometry parameters, which determine survival and growth strategies within the model. The parameter sensitivity changes with different sizes of trees and climate conditions. The results of this study highlight the importance of understanding the dynamics of the next generation of demographically enabled vegetation models within ESMs to improve model parameterization and structure for better model fidelity.

Tree mortality is a key driver of forest community composition and carbon dynamics. Strong winds associated with severe convective storms are dominant natural drivers of tree mortality in the Amazon. Why forests vary with respect to their vulnerability to wind events and how the predicted increase in storm events might affect forest ecosystems within the Amazon are not well understood. We found that windthrows are common in the Amazon region extending from northwest (Peru, Colombia, Venezuela, and west Brazil) to central Brazil, with the highest occurrence of windthrows in the northwest Amazon. More frequent winds, produced by more frequent severe convective systems, in combination with well-known processes that limit the anchoring of trees in the soil, help to explain the higher vulnerability of the northwest Amazon forests to winds. Projected increases in the frequency and intensity of convective storms in the Amazon have the potential to increase wind-related tree mortality. A forest demographic model calibrated for the northwestern and the central Amazon showed that northwestern forests are more resilient to increased wind-related tree mortality than forests in the central Amazon. Our study emphasizes the importance of including wind-related tree mortality in model simulations for reliable predictions of the future of tropical forests and their effects on the Earth' system.

A significant fraction of anthropogenic CO2 emissions is assimilated by tropical forests and stored as biomass, slowing the accumulation of CO2 in the atmosphere. Because different plant tissues have different functional roles and turnover times, predictions of carbon balance of tropical forests depend on how earth system models (ESMs) represent the dynamic allocation of productivity to different tree compartments. This study shows that observed allocation of productivity, biomass, and turnover times of main tree compartments (leaves, wood, and roots) are not accurately represented in Coupled Model Intercomparison Project Phase 5 ESMs. In particular, observations indicate that biomass saturates with increasing productivity. In contrast, most models predict continuous increases in biomass with increases in productivity. This bias may lead to an over-prediction of carbon uptake in response to CO2 or climate-driven changes in productivity. Compartment-specific productivity and biomass are useful benchmarks to assess terrestrial ecosystem model performance. Improvements in the predicted allocation patterns and turnover times by ESMs will reduce uncertainties in climate predictions.

This work investigates how the integrated land use of northern South America has affected the present day regional patterns of hydrology. A model of the terrestrial ecosystems (ecosystem demography model 2: ED2) is combined with an atmospheric model (Brazilian Regional Atmospheric Modeling System: BRAMS). Two realizations of the structure and composition of terrestrial vegetation are used as the sole differences in boundary conditions that drive two simulations. One realization captures the present day vegetation condition that includes deforestation and land conversion, the other is an estimate of the potential structure and composition of the region's vegetation without human influence. Model output is assessed for differences in resulting hydrometeorology. The simulations suggest that the history of land conversion in northern South America is not associated with a significant precipitation bias in the northern part of the continent, but has shown evidence of a negative bias in mean regional evapotranspiration and a positive bias in mean regional runoff. Also, negative anomalies in evaporation rates showed pattern similarity with areas where deforestation has occurred. In the central eastern Amazon there was an area where deforestation and abandonment had lead to an overall reduction of above-ground biomass, but this was accompanied by a shift in forest composition towards early successional functional types and grid-average-patterned increases in annual transpiration. Anomalies in annual precipitation showed mixed evidence of consistent patterning. Two focus areas were identified where more consistent precipitation anomalies formed, one in the Brazilian state of Pará where a dipole pattern formed, and one in the Bolivian Gran Chaco, where a negative anomaly was identified. These locations were scrutinized to understand the basis of their anomalous hydrometeorologic response. In both cases, deforestation led to increased total surface albedo, driving decreases in net radiation, boundary layer moist static energy and ultimately decreased convective precipitation. In the case of the Gran Chaco, decreased precipitation was also a result of decreased advective moisture transport, indicating that differences in local hydrometeorology may manifest via teleconnections with the greater region.

Recent efforts to narrow the spread in equilibrium climate sensitivity (ECS) across global climate models have focused on identifying observationally based constraints, which are rooted in empirical correlations between ECS and biases in the models' present-day climate. This study reexamines one such constraint identified from CMIP3 models: the linkage between ECS and net top-of-the-atmosphere radiation biases in the Southern Hemisphere (SH). As previously documented, the intermodel spread in the ECS of CMIP3 models is linked to present-day cloud and net radiation biases over the midlatitude Southern Ocean, where higher cloud fraction in the present-day climate is associated with larger values of ECS. However, in this study, no physical explanation is found to support this relationship. Furthermore, it is shown here that this relationship disappears in CMIP5 models and is unique to a subset of CMIP models characterized by unrealistically bright present-day clouds in the SH subtropics. In view of this evidence, Southern Ocean cloud and net radiation biases appear inappropriate for providing observationally based constraints on ECS. Instead of the Southern Ocean, this study points to the stratocumulus-to-cumulus transition regions of the SH subtropical oceans as key to explaining the intermodel spread in the ECS of both CMIP3 and CMIP5 models. In these regions, ECS is linked to present-day cloud and net radiation biases with a plausible physical mechanism: models with brighter subtropical clouds in the present-day climate show greater ECS because 1) subtropical clouds dissipate with increasing CO2 concentrations in many models and 2) the dissipation of brighter clouds contributes to greater solar warming of the surface.

Crown damage can account for over 23% of canopy biomass turnover in tropical forests and is a strong predictor of tree mortality; yet, it is not typically represented in vegetation models. We incorporate crown damage into the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), to evaluate how lags between damage and tree recovery or death alter demographic rates and patterns of carbon turnover. We represent crown damage as a reduction in a tree's crown area and leaf and branch biomass, and allow associated variation in the ratio of aboveground to belowground plant tissue. We compare simulations with crown damage to simulations with equivalent instant increases in mortality and benchmark results against data from Barro Colorado Island (BCI), Panama. In FATES, crown damage causes decreases in growth rates that match observations from BCI. Crown damage leads to increases in carbon starvation mortality in FATES, but only in configurations with high root respiration and decreases in carbon storage following damage. Crown damage also alters competitive dynamics, as plant functional types that can recover from crown damage outcompete those that cannot. This is a first exploration of the trade-off between the additional complexity of the novel crown damage module and improved predictive capabilities. At BCI, a tropical forest that does not experience high levels of disturbance, both the crown damage simulations and simulations with equivalent increases in mortality does a reasonable job of capturing observations. The crown damage module provides functionality for exploring dynamics in forests with more extreme disturbances such as cyclones and for capturing the synergistic effects of disturbances that overlap in space and time., (© 2022 John Wiley & Sons Ltd.)

Deep-water access is arguably the most effective, but under-studied, mechanism that plants employ to survive during drought. Vulnerability to embolism and hydraulic safety margins can predict mortality risk at given levels of dehydration, but deep-water access may delay plant dehydration. Here, we tested the role of deep-water access in enabling survival within a diverse tropical forest community in Panama using a novel data-model approach. We inversely estimated the effective rooting depth (ERD, as the average depth of water extraction), for 29 canopy species by linking diameter growth dynamics (1990-2015) to vapor pressure deficit, water potentials in the whole-soil column, and leaf hydraulic vulnerability curves. We validated ERD estimates against existing isotopic data of potential water-access depths. Across species, deeper ERD was associated with higher maximum stem hydraulic conductivity, greater vulnerability to xylem embolism, narrower safety margins, and lower mortality rates during extreme droughts over 35 years (1981-2015) among evergreen species. Species exposure to water stress declined with deeper ERD indicating that trees compensate for water stress-related mortality risk through deep-water access. The role of deep-water access in mitigating mortality of hydraulically-vulnerable trees has important implications for our predictive understanding of forest dynamics under current and future climates., (No claim to original US Government works New Phytologist © 2021 New Phytologist Foundation.)

Purpose: Hypomelanosis of Ito (HI) is a skin marker of somatic mosaicism. Mosaic MTOR pathogenic variants have been reported in HI with brain overgrowth. We sought to delineate further the pigmentary skin phenotype and clinical spectrum of neurodevelopmental manifestations of MTOR-related HI., Methods: From two cohorts totaling 71 patients with pigmentary mosaicism, we identified 14 patients with Blaschko-linear and one with flag-like pigmentation abnormalities, psychomotor impairment or seizures, and a postzygotic MTOR variant in skin. Patient records, including brain magnetic resonance image (MRI) were reviewed. Immunostaining (n = 3) for melanocyte markers and ultrastructural studies (n = 2) were performed on skin biopsies., Results: MTOR variants were present in skin, but absent from blood in half of cases. In a patient (p.[Glu2419Lys] variant), phosphorylation of p70S6K was constitutively increased. In hypopigmented skin of two patients, we found a decrease in stage 4 melanosomes in melanocytes and keratinocytes. Most patients (80%) had macrocephaly or (hemi)megalencephaly on MRI., Conclusion: MTOR-related HI is a recognizable neurocutaneous phenotype of patterned dyspigmentation, epilepsy, intellectual deficiency, and brain overgrowth, and a distinct subtype of hypomelanosis related to somatic mosaicism. Hypopigmentation may be due to a defect in melanogenesis, through mTORC1 activation, similar to hypochromic patches in tuberous sclerosis complex., (© 2021. The Author(s).)

Activating PIK3CA mutations are known 'drivers' of human cancer and developmental overgrowth syndromes. We recently demonstrated that the 'hotspot' PIK3CAH1047R variant exerts unexpected allele dose-dependent effects on stemness in human pluripotent stem cells (hPSCs). In this study, we combine high-depth transcriptomics, total proteomics and reverse-phase protein arrays to reveal potentially disease-related alterations in heterozygous cells, and to assess the contribution of activated TGFβ signalling to the stemness phenotype of homozygous PIK3CAH1047R cells. We demonstrate signalling rewiring as a function of oncogenic PI3K signalling strength, and provide experimental evidence that self-sustained stemness is causally related to enhanced autocrine NODAL/TGFβ signalling. A significant transcriptomic signature of TGFβ pathway activation in heterozygous PIK3CAH1047R was observed but was modest and was not associated with the stemness phenotype seen in homozygous mutants. Notably, the stemness gene expression in homozygous PIK3CAH1047R hPSCs was reversed by pharmacological inhibition of NODAL/TGFβ signalling, but not by pharmacological PI3Kα pathway inhibition. Altogether, this provides the first in-depth analysis of PI3K signalling in hPSCs and directly links strong PI3K activation to developmental NODAL/TGFβ signalling. This work illustrates the importance of allele dosage and expression when artificial systems are used to model human genetic disease caused by activating PIK3CA mutations. This article has an associated First Person interview with the first author of the paper., Competing Interests: Competing interests R.K.S. is a consultant for HotSpot Therapeutics (Boston, MA, USA). B.V. is a consultant for Karus Therapeutics (Oxford, UK), iOnctura (Geneva, Switzerland) and Venthera (Palo Alto, CA, USA), and has received speaker fees from Gilead Sciences (Foster City, CA, USA). N.O.C. is a director of Ther-IP Ltd (Edinburgh, UK) and founder, shareholder and advisor for PhenoTherapeutics Ltd (Edinburgh, UK), and a member of the advisory board and shareholder of Amplia Therapeutics Ltd (Melbourne, Australia)., (© 2021. Published by The Company of Biologists Ltd.)

The PIK3CA gene, which encodes the p110α catalytic subunit of PI3 kinase (PI3K), is mutationally activated in cancer and in overgrowth disorders known as PIK3CA -related overgrowth spectrum (PROS). To determine the consequences of genetic PIK3CA activation in a developmental context of relevance to both PROS and cancer, we engineered isogenic human induced pluripotent stem cells (iPSCs) with heterozygous or homozygous knockin of PIK3CA H1047R While heterozygous iPSCs remained largely similar to wild-type cells, homozygosity for PIK3CA H1047R caused widespread, cancer-like transcriptional remodeling, partial loss of epithelial morphology, up-regulation of stemness markers, and impaired differentiation to all three germ layers in vitro and in vivo. Genetic analysis of PIK3CA -associated cancers revealed that 64% had multiple oncogenic PIK3CA copies (39%) or additional PI3K signaling pathway-activating "hits" (25%). This contrasts with the prevailing view that PIK3CA mutations occur heterozygously in cancer. Our findings suggest that a PI3K activity threshold determines pathological consequences of oncogenic PIK3CA activation and provide insight into the specific role of this pathway in human pluripotent stem cells., Competing Interests: Conflict of interest statement: B.V. is a consultant for Venthera (Palo Alto, CA), iOnctura (Geneva, Switzerland), and Karus Therapeutics (Oxford, United Kingdom). N.M. has received consultancy fees from Achilles Therapeutics., (Copyright © 2019 the Author(s). Published by PNAS.)

The impact of increases in drought frequency on the Amazon forest's composition, structure and functioning remain uncertain. We used a process- and individual-based ecosystem model (ED2) to quantify the forest's vulnerability to increased drought recurrence. We generated meteorologically realistic, drier-than-observed rainfall scenarios for two Amazon forest sites, Paracou (wetter) and Tapajós (drier), to evaluate the impacts of more frequent droughts on forest biomass, structure and composition. The wet site was insensitive to the tested scenarios, whereas at the dry site biomass declined when average rainfall reduction exceeded 15%, due to high mortality of large-sized evergreen trees. Biomass losses persisted when year-long drought recurrence was shorter than 2-7 yr, depending upon soil texture and leaf phenology. From the site-level scenario results, we developed regionally applicable metrics to quantify the Amazon forest's climatological proximity to rainfall regimes likely to cause biomass loss > 20% in 50 yr according to ED2 predictions. Nearly 25% (1.8 million km 2 ) of the Amazon forests could experience frequent droughts and biomass loss if mean annual rainfall or interannual variability changed by 2σ. At least 10% of the high-emission climate projections (CMIP5/RCP8.5 models) predict critically dry regimes over 25% of the Amazon forest area by 2100., (© 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.)

The fate of tropical forests under climate change is unclear as a result, in part, of the uncertainty in projected changes in precipitation and in the ability of vegetation models to capture the effects of drought-induced mortality on aboveground biomass (AGB). We evaluated the ability of a terrestrial biosphere model with demography and hydrodynamics (Ecosystem Demography, ED2-hydro) to simulate AGB and mortality of four tropical tree plant functional types (PFTs) that operate along light- and water-use axes. Model predictions were compared with observations of canopy trees at Barro Colorado Island (BCI), Panama. We then assessed the implications of eight hypothetical precipitation scenarios, including increased annual precipitation, reduced inter-annual variation, El Niño-related droughts and drier wet or dry seasons, on AGB and functional diversity of the model forest. When forced with observed meteorology, ED2-hydro predictions capture multiple BCI benchmarks. ED2-hydro predicts that AGB will be sustained under lower rainfall via shifts in the functional composition of the forest, except under the drier dry-season scenario. These results support the hypothesis that inter-annual variation in mean and seasonal precipitation promotes the coexistence of functionally diverse PFTs because of the relative differences in mortality rates. If the hydroclimate becomes chronically drier or wetter, functional evenness related to drought tolerance may decline., (© 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.)

Numerous current efforts seek to improve the representation of ecosystem ecology and vegetation demographic processes within Earth System Models (ESMs). These developments are widely viewed as an important step in developing greater realism in predictions of future ecosystem states and fluxes. Increased realism, however, leads to increased model complexity, with new features raising a suite of ecological questions that require empirical constraints. Here, we review the developments that permit the representation of plant demographics in ESMs, and identify issues raised by these developments that highlight important gaps in ecological understanding. These issues inevitably translate into uncertainty in model projections but also allow models to be applied to new processes and questions concerning the dynamics of real-world ecosystems. We argue that stronger and more innovative connections to data, across the range of scales considered, are required to address these gaps in understanding. The development of first-generation land surface models as a unifying framework for ecophysiological understanding stimulated much research into plant physiological traits and gas exchange. Constraining predictions at ecologically relevant spatial and temporal scales will require a similar investment of effort and intensified inter-disciplinary communication., (© 2017 John Wiley & Sons Ltd.)

Neurofibromatosis type 1 (NF1; OMIM 162200), a dominantly inherited multitumor syndrome, results from mutations in the Neurofibromin 1 (NF1) gene. We present the case of a Hungarian woman with the clinical phenotype of NF1 over her whole body and the clinical features of unilateral overgrowth involving her entire left leg. This unusual phenotype suggested either the atypical form of NF1 or the coexistence of NF1 and overgrowth syndrome. Direct sequencing of the genomic DNA isolated from peripheral blood revealed a novel frameshift mutation (c.5727insT, p.V1909fsX1912) in the NF1 gene. Next-generation sequencing of 50 oncogenes and tumour suppressor genes, performed on the genomic DNAs isolated from tissue samples and peripheral blood, detected only wild-type sequences. Based on these results, we concluded that the patient is affected by an unusual phenotype of NF1, and that the observed unilateral overgrowth of the left leg might be a rare consequence of the identified c.5727insT mutation., (© 2017 British Association of Dermatologists.)

The organization of Rhodopsin-family G protein-coupled receptors (GPCRs) at the cell surface is controversial. Support both for and against the existence of dimers has been obtained in studies of mostly individual receptors. Here, we use a large-scale comparative study to examine the stoichiometric signatures of 60 receptors expressed by a single human cell line. Using bioluminescence resonance energy transfer- and single-molecule microscopy-based assays, we found that a relatively small fraction of Rhodopsin-family GPCRs behaved as dimers and that these receptors otherwise appear to be monomeric. Overall, the analysis predicted that fewer than 20% of ∼700 Rhodopsin-family receptors form dimers. The clustered distribution of the dimers in our sample and a striking correlation between receptor organization and GPCR family size that we also uncover each suggest that receptor stoichiometry might have profoundly influenced GPCR expansion and diversification., (Crown Copyright © 2017. Published by Elsevier Inc. All rights reserved.)

Wilms tumor and nephroblastomatosis are associated with syndromic conditions including hemihyperplasia. Hemihyperplasia is genetically heterogeneous and may be the result of genomic abnormalities seen in Beckwith-Wiedemann syndrome, mosaic chromosome or genomic abnormalities, or somatic point mutations. Somatic missense mutations affecting the PI3K-AKT-MTOR pathway result in segmental overgrowth and are present in numerous benign and malignant tumors. Here, we report a fourth patient with asymmetric overgrowth due to a somatic PIK3CA mutation who had nephroblastomatosis or Wilms tumor. Similar to two of three reported patients with a somatic PIK3CA mutation and renal tumors, he shared a PIK3CA mutation affecting codon 1047, presented at birth with asymmetric overgrowth, and had fibroadipose overgrowth. Codon 1047 is most commonly affected by somatic mutations in PIK3CA-related overgrowth spectrum (PROS). While the fibroadipose overgrowth phenotype appears to be common in individuals with PIK3CA mutations at codon 1047, individuals with a clinical diagnosis of Klippel-Trenaunay syndrome or isolated lymphatic malformation also had mutations affecting this amino acid. Screening for Wilms tumor in individuals with PROS-related hemihyperplasia may be considered and, until the natural history is fully elucidated in larger cohort studies, may follow guidelines for Beckwith-Wiedemann syndrome, or isolated hemihyperplasia. It is not known if the specific PIK3CA mutation, the mosaic distribution, or the clinical presentation affect the Wilms tumor or nephroblastomatosis risk in individuals with PROS. © 2016 Wiley Periodicals, Inc., (© 2016 Wiley Periodicals, Inc.)

Venous malformations (VMs) are painful and deforming vascular lesions composed of dilated vascular channels, which are present from birth. Mutations in the TEK gene, encoding the tyrosine kinase receptor TIE2, are found in about half of sporadic (nonfamilial) VMs, and the causes of the remaining cases are unknown. Sclerotherapy, widely accepted as first-line treatment, is not fully efficient, and targeted therapy for this disease remains underexplored. We have generated a mouse model that faithfully mirrors human VM through mosaic expression of Pik3ca(H1047R), a constitutively active mutant of the p110α isoform of phosphatidylinositol 3-kinase (PI3K), in the embryonic mesoderm. Endothelial expression of Pik3ca(H1047R)resulted in endothelial cell (EC) hyperproliferation, reduction in pericyte coverage of blood vessels, and decreased expression of arteriovenous specification markers. PI3K pathway inhibition with rapamycin normalized EC hyperproliferation and pericyte coverage in postnatal retinas and stimulated VM regression in vivo. In line with the mouse data, we also report the presence of activating PIK3CA mutations in human VMs, mutually exclusive with TEK mutations. Our data demonstrate a causal relationship between activating Pik3ca mutations and the genesis of VMs, provide a genetic model that faithfully mirrors the normal etiology and development of this human disease, and establish the basis for the use of PI3K-targeted therapies in VMs., (Copyright © 2016, American Association for the Advancement of Science.)

There is considerable interest in understanding the fate of the Amazon over the coming century in the face of climate change, rising atmospheric CO 2 levels, ongoing land transformation, and changing fire regimes within the region. In this analysis, we explore the fate of Amazonian ecosystems under the combined impact of these four environmental forcings using three terrestrial biosphere models (ED2, IBIS, and JULES) forced by three bias-corrected IPCC AR4 climate projections (PCM1, CCSM3, and HadCM3) under two land-use change scenarios. We assess the relative roles of climate change, CO 2 fertilization, land-use change, and fire in driving the projected changes in Amazonian biomass and forest extent. Our results indicate that the impacts of climate change are primarily determined by the direction and severity of projected changes in regional precipitation: under the driest climate projection, climate change alone is predicted to reduce Amazonian forest cover by an average of 14%. However, the models predict that CO 2 fertilization will enhance vegetation productivity and alleviate climate-induced increases in plant water stress, and, as a result, sustain high biomass forests, even under the driest climate scenario. Land-use change and climate-driven changes in fire frequency are predicted to cause additional aboveground biomass loss and reductions in forest extent. The relative impact of land use and fire dynamics compared to climate and CO 2 impacts varies considerably, depending on both the climate and land-use scenario, and on the terrestrial biosphere model used, highlighting the importance of improved quantitative understanding of all four factors - climate change, CO 2 fertilization effects, fire, and land use - to the fate of the Amazon over the coming century., (© 2015 John Wiley & Sons Ltd.)

Background: Somatic activating mutations in PIK3CA, which encodes the p110α catalytic subunit of phosphoinositide-3-kinase (PI3K) are frequently found in cancers and have been identified in a spectrum of mosaic overgrowth disorders ranging from isolated digit enlargement to more extensive overgrowth of the body, brain, or vasculature. We aimed to study affected dermal fibroblasts with a view to inform therapeutic studies, and to observe cancer-associated mutations in isolation., Methods: We measured PIP3 concentrations in dermal fibroblasts with endogenous PIK3CA mutations and in wild type fibroblasts using mass spectrometry, and we measured downstream signalling events with ELISA and immunoblotting. Cellular proliferation was evaluated with 5-bromo-2'-deoxyuridine incorporation, and cell size assessed by fluorescence-activated cell sorting (FACS). Glycolysis and mitochondrial tests were performed with an extracellular flux analyser (Seahorse Bioscience, Billerica, MA, USA), and mitochondrial potential was measured by FACS-based JC1 staining. Experiments were repeated after exposure to 5 nmol everolimus for 72 h., Findings: Mutant fibroblasts had two times higher basal PIP3 concentrations than wild-type fibroblasts (p=0·0017), with concomitant AKT and p70S6 activation downstream. The rate of cellular proliferation was higher in mutant cells under low serum conditions, but median cell size was not statistically different. Glycolytic capacity was similar between mutant and wild type fibroblasts, but subtle differences in mitochondrial function were detected with blunted responses to uncoupling agents and reduced membrane potentials. Treatment with everolimus reversed aberrant AKT(ser473) and p70S6 signalling, slowed cellular proliferation, and reversed mitochondrial abnormalities, but was associated, paradoxically, with increases in PIP3 concentrations., Interpretation: These experiments demonstrate activation of the PI3K-AKT pathway in affected fibroblasts with increased proliferation, but no hypertrophy. Moreover, we identified changes in mitochondrial function in keeping with the known propensity of AKT to modulate elements of the Warburg effect. These results suggest that inhibitors of the mammalian target of rapamycin (mTOR) might be beneficial, but these inhibitors will require formal evaluation in clinical trials. More targeted therapy with p110α inhibitors is an enticing future option., Funding: Wellcome Trust, Sackler Fund, National Instititute for Health Research., (Copyright © 2015 Elsevier Ltd. All rights reserved.)