Search

Amit Sharma, Rajesh Ramanathan, Marc Posner, Robert A Fisher Hume-Lee Transplant Center, Virginia Commonwealth University, Richmond, VA, USA Abstract: Pediatric kidney transplantation is the preferred treatment for children with end-stage renal disease. The most common indications for transplantation in children are renal developmental anomalies, obstructive uropathy, and focal segmental glomerulosclerosis. Living donor kidney transplants are often performed pre-emptively and offer excellent graft function. Policy changes in deceased-donor kidney allocation have increased the proportion of such transplants in pediatric recipients. Adequate pretransplant workup along with evaluation of urologic abnormalities is imperative in achieving good outcomes. Overall, patient and graft outcomes after kidney transplantation have improved, with five-year deceased donor and living donor graft survivals of 78.8% and 84.3%, respectively. Improvements in induction and maintenance immunosuppression have contributed to the gradual improvement in outcomes. Unique challenges in pediatric recipients include increased graft thrombosis, adverse growth, and abnormal development relating to immunosuppression, increased rejection due to nonadherence, increased susceptibility to opportunistic infections, and post-transplant malignancy. This review focuses on the current practices and outcomes in pediatric kidney transplantation in North America. We discuss the indications for transplantation, the evaluation process, some key surgical and immunologic considerations, and the common risk factors for graft dysfunction. Keywords: pediatric kidney transplantation, end-stage renal disease, dialysis, organ donors, immunosuppression

Most Earth system models (ESMs) do not explicitly represent the carbon (C) costs of plant nutrient acquisition, which leads to uncertainty in predictions of the current and future constraints to the land C sink. We integrate a plant productivity-optimizing nitrogen (N) and phosphorus (P) acquisition model (fixation & uptake of nutrients, FUN) into the energy exascale Earth system (E3SM) land model (ELM). Global plant N and P uptake are dynamically simulated by ELM-FUN based on the C costs of nutrient acquisition from mycorrhizae, direct root uptake, retranslocation from senescing leaves, and biological N fixation. We benchmarked ELM-FUN with three classes of products: ILAMB, a remotely sensed nutrient limitation product, and CMIP6 models; we found significant improvements in C cycle variables, although the lack of more observed nutrient data prevents a comprehensive level of benchmarking. Overall, we found N and P co-limitation for 80% of land area, with the remaining 20% being either predominantly N or P limited. Globally, the new model predicts that plants invested 4.1 Pg C yr-1 to acquire 841.8 Tg N yr-1 and 48.1 Tg P yr-1 (1994-2005), leading to significant downregulation of global net primary production (NPP). Global NPP is reduced by 20% with C costs of N and 50% with C costs of NP. Modeled and observed nutrient limitation agreement increases when N and P are considered together (r 2 from 0.73 to 0.83).

Live fuel moisture content (LFMC) plays a critical role in wildfire dynamics, but little is known about responses of LFMC to multivariate climate change, e.g., warming temperature, CO2 fertilization, and altered precipitation patterns, leading to a limited prediction ability of future wildfire risks. Here, we use a hydrodynamic demographic vegetation model to estimate LFMC dynamics of chaparral shrubs, a dominant vegetation type in fire-prone southern California. We parameterize the model based on observed shrub allometry and hydraulic traits and evaluate the model's accuracy through comparisons between observed and simulated LFMC of three plant functional types (PFTs) under current climate conditions. Moreover, we estimate the number of days per year of LFMC below 79% (which is a critical threshold for wildfire danger rating of southern California chaparral shrubs) from 1960 to 2099 for each PFT and compare the number of days below the threshold for medium and high greenhouse gas emission scenarios (RCP4.5 and 8.5). We find that climate change could lead to more days per year (5.2%-14.8% increase) with LFMC below 79% between the historical (1960-1999) and future (2080-2099) periods, implying an increase in wildfire danger for chaparral shrubs in southern California. Under the high greenhouse gas emission scenario during the dry season, we find that the future LFMC reductions mainly result from a warming temperature, which leads to 9.1%-18.6% reduction in LFMC. Lower precipitation in the spring leads to a 6.3%-8.1% reduction in LFMC. The combined impacts of warming and precipitation change on fire season length are equal to the additive impacts of warming and precipitation change individually. Our results show that the CO2 fertilization will mitigate fire risk by causing a 3.5%-4.8% increase in LFMC. Our results suggest that multivariate climate change could cause a significant net reduction in LFMC and thus exacerbate future wildfire danger in chaparral shrub systems.

Forest disturbance and regrowth are key processes in forest dynamics, but detailed information on these processes is difficult to obtain in remote forests such as the Amazon. We used chronosequences of Landsat satellite imagery (Landsat 5 Thematic Mapper and Landsat 7 Enhanced Thematic Mapper Plus) to determine the sensitivity of surface reflectance from all spectral bands to windthrow, clear-cut, and clear-cut and burned (cut + burn) and their successional pathways of forest regrowth in the Central Amazon. We also assessed whether the forest demography model Functionally Assembled Terrestrial Ecosystem Simulator (FATES) implemented in the Energy Exascale Earth System Model (E3SM) Land Model (ELM), ELM-FATES, accurately represents the changes for windthrow and clear-cut. The results show that all spectral bands from the Landsat satellites were sensitive to the disturbances but after 3 to 6 years only the near-infrared (NIR) band had significant changes associated with the successional pathways of forest regrowth for all the disturbances considered. In general, the NIR values decreased immediately after disturbance, increased to maximum values with the establishment of pioneers and early successional tree species, and then decreased slowly and almost linearly to pre-disturbance conditions with the dynamics of forest succession. Statistical methods predict that NIR values will return to pre-disturbance values in about 39, 36, and 56 years for windthrow, clear-cut, and cut + burn disturbances, respectively. The NIR band captured the observed, and different, successional pathways of forest regrowth after windthrow, clear-cut, and cut + burn. Consistent with inferences from the NIR observations, ELM-FATES predicted higher peaks of biomass and stem density after clear-cuts than after windthrows. ELM-FATES also predicted recovery of forest structure and canopy coverage back to pre-disturbance conditions in 38 years after windthrows and 41 years after clear-cut. The similarity of ELM-FATES predictions of regrowth patterns after windthrow and clear-cut to those of the NIR results suggests the NIR band can be used to benchmark forest regrowth in ecosystem models. Our results show the potential of Landsat imagery data for mapping forest regrowth from different types of disturbances, benchmarking, and the improvement of forest regrowth models.

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.

Land surface models (LSMs) are a vital tool for understanding, projecting, and predicting the dynamics of the land surface and its role within the Earth system, under global change. Driven by the need to address a set of key questions, LSMs have grown in complexity from simplified representations of land surface biophysics to encompass a broad set of interrelated processes spanning the disciplines of biophysics, biogeochemistry, hydrology, ecosystem ecology, community ecology, human management, and societal impacts. This vast scope and complexity, while warranted by the problems LSMs are designed to solve, has led to enormous challenges in understanding and attributing differences between LSM predictions. Meanwhile, the wide range of spatial scales that govern land surface heterogeneity, and the broad spectrum of timescales in land surface dynamics, create challenges in tractably representing processes in LSMs. We identify three “grand challenges” in the development and use of LSMs, based around these issues: managing process complexity, representing land surface heterogeneity, and understanding parametric dynamics across the broad set of problems asked of LSMs in a changing world. In this review, we discuss progress that has been made, as well as promising directions forward, for each of these challenges.

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 Community Land Model (CLM) is the land component of the Community Earth System Model (CESM) and is used in several global and regional modeling systems. In this paper, we introduce model developments included in CLM version 5 (CLM5), which is the default land component for CESM2. We assess an ensemble of simulations, including prescribed and prognostic vegetation state, multiple forcing data sets, and CLM4, CLM4.5, and CLM5, against a range of metrics including from the International Land Model Benchmarking (ILAMBv2) package. CLM5 includes new and updated processes and parameterizations: (1) dynamic land units, (2) updated parameterizations and structure for hydrology and snow (spatially explicit soil depth, dry surface layer, revised groundwater scheme, revised canopy interception and canopy snow processes, updated fresh snow density, simple firn model, and Model for Scale Adaptive River Transport), (3) plant hydraulics and hydraulic redistribution, (4) revised nitrogen cycling (flexible leaf stoichiometry, leaf N optimization for photosynthesis, and carbon costs for plant nitrogen uptake), (5) global crop model with six crop types and time-evolving irrigated areas and fertilization rates, (6) updated urban building energy, (7) carbon isotopes, and (8) updated stomatal physiology. New optional features include demographically structured dynamic vegetation model (Functionally Assembled Terrestrial Ecosystem Simulator), ozone damage to plants, and fire trace gas emissions coupling to the atmosphere. Conclusive establishment of improvement or degradation of individual variables or metrics is challenged by forcing uncertainty, parametric uncertainty, and model structural complexity, but the multivariate metrics presented here suggest a general broad improvement from CLM4 to CLM5.

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.

Global temperature rise and extremes accompanying drought threaten forests and their associated climatic feedbacks. Our ability to accurately simulate drought-induced forest impacts remains highly uncertain in part owing to our failure to integrate physiological measurements, regional-scale models, and dynamic global vegetation models (DGVMs). Here we show consistent predictions of widespread mortality of needleleaf evergreen trees (NET) within Southwest USA by 2100 using state-of-the-art models evaluated against empirical data sets. Experimentally, dominant Southwest USA NET species died when they fell below predawn water potential (pd) thresholds (April-August mean) beyond which photosynthesis, hydraulic and stomatal conductance, and carbohydrate availability approached zero. The evaluated regional models accurately predicted NET pd, and 91% of predictions (10 out of 11) exceeded mortality thresholds within the twenty-first century due to temperature rise. The independent DGVMs predicted ≥50% loss of Northern Hemisphere NET by 2100, consistent with the NET findings for Southwest USA. Notably, the global models underestimated future mortality within Southwest USA, highlighting that predictions of future mortality within global models may be underestimates. Taken together, the validated regional predictions and the global simulations predict widespread conifer loss in coming decades under projected global warming.

Although plant photosynthetic capacity as determined by the maximum carboxylation rate (i.e., Vc,max25) and the maximum electron transport rate (i.e., Jmax25) at a reference temperature (generally 25 °C) is known to vary considerably in space and time in response to environmental conditions, it is typically parameterized in Earth system models (ESMs) with tabulated values associated with plant functional types. In this study, we have developed a mechanistic model of leaf utilization of nitrogen for assimilation (LUNA) to predict photosynthetic capacity at the global scale under different environmental conditions. We adopt an optimality hypothesis to nitrogen allocation among light capture, electron transport, carboxylation and respiration. The LUNA model is able to reasonably capture the measured spatial and temporal patterns of photosynthetic capacity as it explains ∼55% of the global variation in observed values of Vc,max25 and ∼65% of the variation in the observed values of Jmax25. Model simulations with LUNA under current and future climate conditions demonstrate that modeled values of Vc,max25 are most affected in high-latitude regions under future climates. ESMs that relate the values of Vc,max25 or Jmax25 to plant functional types only are likely to substantially overestimate future global photosynthesis.

Hepatocellular carcinoma (HCC) represents an increasing fraction of liver transplant indications; the role of living donor liver transplant (LDLT) remains unclear. In the Adult-to-Adult Living Donor Liver Transplantation Cohort Study, patients with HCC and an LDLT or deceased donor liver transplant (DDLT) for which at least one potential living donor had been evaluated were compared for recurrence and posttransplant mortality rates. Mortality from date of evaluation of each recipient's first potential living donor was also analyzed. Unadjusted 5-year HCC recurrence was significantly higher after LDLT (38%) than DDLT (11%), (p = 0.0004). After adjustment for tumor characteristics, HCC recurrence remained significantly different between LDLT and DDLT recipients (hazard ratio (HR) = 2.35; p = 0.04) for the overall cohort but not for recipients transplanted following the introduction of MELD prioritization. Five-year posttransplant survival was similar in LDLT and DDLT recipients from time of transplant (HR = 1.32; p = 0.27) and from date of LDLT evaluation (HR = 0.73; p = 0.36). We conclude that the higher recurrence observed after LDLT is likely due to differences in tumor characteristics, pretransplant HCC management and waiting time.

CeRhIn5 has an unusual transition at a critical pressure of ∼15 kbar. Specificheat data show a gradual change in the zero-field 'magnetic' anomaly from one typical of antiferromagnetic (AF) ordering at ambient pressure to one that is more characteristic of a Kondo-singlet ground state at 21 kbar. However, at 15 kbar there is a discontinuous change from an AF ground state to a superconducting ground state, with evidence of a weak thermodynamic first-order transition. For pressures near 12 kbar, there is a pressure-dependent, second-order transition. The low-energy excitations above 15 kbar are characteristic of superconductivity with line nodes in the energy gap, and with extended gapless behaviour at intermediate pressures less than 21 kbar.

CeRhIn5 is known to show an unusual transition at a critical pressure of ∼15 kbar. Specific-heat data show a gradual change in the zero-field "magnetic" specific-heat anomaly from one typical of antiferromagnetic (AF) ordering at ambient pressure to one more characteristic of a Kondo singlet ground state at 21 kbar. However, at 15 kbar there is a discontinuous change from an AF ground state to a superconducting ground state, and evidence of a weak thermodynamic first-order transition. Above the critical pressure, the low-energy excitations are characteristic of superconductivity with line nodes in the energy gap, and, at intermediate pressures, of extended gaplessness. © 2003 Elsevier Science B.V. All rights reserved.

CeRhIn5 is known to show an unusual transition at a critical pressure of ∼15 kbar. Specific-heat data show a gradual change in the zero-field "magnetic" specific-heat anomaly from one typical of antiferromagnetic ordering at ambient pressure to one more characteristic of a Kondo singlet ground state at 21 kbar. However, at 15 kbar there is a discontinuous change from an antiferromagnetic ground state to a superconducting ground state, and evidence of a weak thermodynamic first-order transition. Above the critical pressure, the low-energy excitations are characteristic of superconductivity with line nodes in the energy gap, and, at intermediate pressures, of extended gaplessness. © 2002 Plenum Publishing Corporation.

We report a new family of Ce-based heavy-fermion compounds whose electronic specific heat coefficients range from about 400 to over 700mJ/mol-Ce K2. Crystals in this family form as CenTmIn3n-2m, where T = Rh or Ir, n = 1 or 2, and m = 1, with a tetragonal structure that can be viewed as m-layers of CeIn3 units stacked sequentially along the c-axis with intervening m-layers of TIn2. Ambient and high-pressure studies show that the quasi-2D layers of CeIn3 produce unconventional superconducting and magnetic ground states. This family should enable new understanding of the relationship between magnetism and superconductivity in heavy-fermion materials and more generally of why heavyfermion superconductivity prefers to develop in one structure type and not another. © 2001 Elsevier Science B.V. All rights reserved.

Measurements of the temperature-dependent specific heat and thermal expansion coefficient near a T=0 magnetic-nonmagnetic boundary, accessed in CeRh2Si2 by application of pressure and in CeRh2-xRuxSi2 at ambient pressure by chemical substitution, emphasize the role of disorder in producing non-Fermi-liquid behavior. Interestingly, superconductivity also develops near this boundary in some crystallographically-ordered Ce-based heavy-fermion compounds. [CeRh2-xRuxSi2, specific heat, thermal expansion, susceptibility, non-Fermi-liquid]. © 1998, The Japan Society of High Pressure Science and Technology. All rights reserved.

A zero-temperature magnetic-nonmagnetic phase boundary is accessed in CeRh2Si2 by application of pressure and in CeRh2−xRuxSi2 at ambient pressure for x ≈ 1.0. A comparison of specific heat and resistivity measurements in the two cases emphasizes the importance of disorder in producing non-Fermi-liquid-like behavior in these as well as in other Ce-based systems. © 1997 American Physical Society.

A zero-temperature magnetic-nonmagnetic phase boundary is accessed in CeRh2Si2 by application of pressure and in CeRh2−xRuxSi2 at ambient pressure for x ≈ 1.0. A comparison of specific heat and resistivity measurements in the two cases emphasizes the importance of disorder in producing non-Fermi-liquid-like behavior in these as well as in other Ce-based systems. © 1997 American Physical Society.

The compound YbBiPt exhibits an extremely large low-temperature C/T (γ∼8 J K-2 mol-1/Yb) which, if due solely to a renormalized effective mass, would make this material the heaviest correlated electron system known to date. In the Kondo model, the very large γ corresponds to a small characteristic energy scale that is expected to be pressure dependent. We have studied the effect of chemical pressure on YbBiPt single crystals by heat-capacity measurements on Y and Lu-doped samples. We have also made preliminary low-temperature measurements under hydrostatic pressure of the heat capacity (300 mK≤T≤2 K, up to 8 kbar) and resistance (30 mK≤T≤1 K, at 16 kbar).

The specific heat, C, of (U0.97Th0.03)Be13 has been measured for 0.1≤T≤1K and 1.6≤P≤7.7 kbar, and for 0.1≤T≤20K with P=0. For T>8K both the pure and Th substituted samples have essentially the same C. The peaks in C/T at 0.33 and 0.54K for P=0 are suppressed and shifted to lower T by pressure. Anomalies in C/T can be correlated to corresponding rapid changes in magnetic susceptibility, χ Rapid suppression of the peaks and shift of Tc to lower values is in marked contrast to the behavior found for pure UBe13 whose single peak amplitude decreases approximately linearly with P to about 60% at 9.3 kbar. The broad “shoulder” in C/T near 2K that is found for UBe13, but not for any other heavy-fermion compound, HFC, is commpletely suppressed in the Th substituted sample. © 1987 The Japan Society of Applied Physics.