Updated respiration routines alter spatio-temporal patterns of carbon cycling in a global land surface model

We updated the routines used to estimate leaf maintenance respiration (MR) in the Energy Land Model (ELM) using a comprehensive global respiration data base. The updated algorithm includes a temperature acclimating base rate, an updated instantaneous temperature response, and new plant functional type specific parameters. The updated MR algorithm resulted in a very large increase in global MR of 16.1 Pg (38%), but the signal was not geographically uniform. The increase was concentrated in the tropics and humid warm-temperate forests. The increase in MR led to large but proportionally smaller decreases in global net primary production (19%) and in average global leaf area index (15%). The effect on global gross primary production (GPP) was a more modest 5.7 Pg (4%). A detailed site level analysis also demonstrated a wide range of effects the updated algorithm can have on the seasonal cycle of GPP. Output from the updated and old models did not differ markedly in how closely they matched a suite of benchmarks. Given the substantial impact on the land surface carbon cycle, a neutral influence on model benchmarks, and better alignment with empirical evidence, an MR algorithm similar to the one presented here should be adopted into ELM

Terrestrial biosphere models need better representation of vegetation phenology: results from the North American Carbon Program Site Synthesis

Phenology, by controlling the seasonal activity of vegetation on the land surface, plays a fundamental role in regulating photosynthesis and other ecosystem processes, as well as competitive interactions and feedbacks to the climate system. We conducted an analysis to evaluate the representation of phenology, and the associated seasonality of ecosystem-scale CO2 exchange, in 14 models participating in the North American Carbon Program Site Synthesis. Model predictions were evaluated using long-term measurements (emphasizing the period 2000-2006) from 10 forested sites within the AmeriFlux and Fluxnet-Canada networks. In deciduous forests, almost all models consistently predicted that the growing season started earlier, and ended later, than was actually observed; biases of 2 weeks or more were typical. For these sites, most models were also unable to explain more than a small fraction of the observed interannual variability in phenological transition dates. Finally, for deciduous forests, misrepresentation of the seasonal cycle resulted in over-prediction of gross ecosystem photosynthesis by +160 ± 145 g C m-2 y-1 during the spring transition period, and +75 ± 130 g C m-2 y-1 during the autumn transition period (13% and 8% annual productivity, respectively) compensating for the tendency of most models to under-predict the magnitude of peak summertime photosynthetic rates. Models did a better job of predicting the seasonality of CO2 exchange for evergreen forests. These results highlight the need for improved understanding of the environmental controls on vegetation phenology, and incorporation of this knowledge into better phenological models. Existing models are unlikely to predict future responses of phenology to climate change accurately, and therefore will misrepresent the seasonality and interannual variability of key biosphere-atmosphere feedbacks and interactions in coupled global climate models.Engineering and Applied SciencesOrganismic and Evolutionary Biolog

The Community Land Model version 5 : description of new features, benchmarking, and impact of forcing uncertainty

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

2016 International Land Model Benchmarking (ILAMB) Workshop Report

As earth system models (ESMs) become increasingly complex, there is a growing need for comprehensive and multi-faceted evaluation of model projections. To advance understanding of terrestrial biogeochemical processes and their interactions with hydrology and climate under conditions of increasing atmospheric carbon dioxide, new analysis methods are required that use observations to constrain model predictions, inform model development, and identify needed measurements and field experiments. Better representations of biogeochemistryclimate feedbacks and ecosystem processes in these models are essential for reducing the acknowledged substantial uncertainties in 21st century climate change projections

Climate control of terrestrial carbon exchange across biomes and continents

Peer reviewe

Angiopoietin-1 and angiopoietin-2 as clinically informative prognostic biomarkers of morbidity and mortality in severe sepsis.

OBJECTIVE: To determine the utility of angiopoietin-1 and angiopoietin-2 as potentially novel biomarkers of morbidity and mortality in patients with severe sepsis. DESIGN: Multicenter longitudinal cohort study. SETTING: Three tertiary hospital intensive care units in Hamilton, Ontario, Canada. PATIENTS: A total of 70 patients with severe sepsis were enrolled within 24 hrs of meeting the inclusion criteria for severe sepsis and followed until day 28, hospital discharge, or death. INTERVENTIONS: Clinical data and plasma samples were obtained at intensive care unit admission for all 70 patients and then daily for 1 wk and weekly thereafter for a subset of 43 patients. Levels of angiopoietin-1 and angiopoietin-2 in stored plasma samples were measured and compared with clinical characteristics, including the primary outcomes of 28-day mortality and morbidity measured by the Multiple Organ Dysfunction score. MEASUREMENTS AND MAIN RESULTS: Lower angiopoietin-1 plasma levels (≤ 5.5 ng/mL) at admission were associated with increased likelihood of death (relative risk 0.49 [95% confidence interval of 0.25-0.98], p = .046). Lower angiopoietin-1 levels remained a significant predictor of 28-day mortality in a multiple logistic regression model (adjusted odds ratio of 0.282 [95% confidence interval of 0.086-0.93], p = .037). Analysis of serial data using linear mixed models confirmed that sepsis survivors had higher levels of angiopoietin-1 (p = .012) and lower daily levels of angiopoietin-2 (p = .022) than nonsurvivors. Furthermore, survivors had higher peak angiopoietin-1 levels (median 13 vs. 10 ng/mL, p = .019) and lower nadir angiopoietin-2 levels (median 2.8 vs. 6.2 ng/mL, p = .013) than nonsurvivors. A score incorporating angiopoietin-1 and angiopoietin-2 and three other markers of endothelial activation discriminated with high accuracy between fatal and nonfatal cases (c-index of 0.80 [95% confidence interval of 0.69-0.90], p < .001). Plasma levels of angiopoietin-2 correlated with clinical markers of organ dysfunction and molecular markers of endothelial cell activation. CONCLUSIONS: Angiopoietin-1 levels at admission and both angiopoietin-1 and angiopoietin-2 levels measured serially correlated with 28-day mortality in severe sepsis. Angiopoietin-2 levels also correlated with organ dysfunction/injury and a validated clinical sepsis score. These results suggest the use of angiopoietins as clinically informative biomarkers of disease severity and patient outcome in severe sepsis

Rectal and Naris Swabs: Practical and Informative Samples for Analyzing the Microbiota of Critically Ill Patients

Perturbation of the microbiome has been correlated with various infectious and inflammatory diseases and is common in critically ill patients. Stool is typically used to sample the microbiota in human observational studies; however, it is often unavailable for collection from critically ill patients, reducing its utility as a sample type to study this population. Our research identified alternatives to stool for sampling the microbiota during critical illness. Rectal and naris swabs were practical alternatives for use in these patients, as they were observed to be more reliably obtained than stool, were suitable for culture-independent analysis, and successfully captured within- and between-patient microbiota differences.Commensal microbiota are immunomodulatory, and their pathological perturbation can affect the risk and outcomes of infectious and inflammatory diseases. Consequently, the human microbiota is an emerging diagnostic and therapeutic target in critical illness. In this study, we compared four sample types—rectal, naris, and antecubital swabs and stool samples—for 16S rRNA gene microbiota sequencing in intensive care unit (ICU) patients. Stool samples were obtained in only 31% of daily attempts, while swabs were reliably obtained (≥97% of attempts). Swabs were compositionally distinct by anatomical site, and rectal swabs identified within-patient temporal trends in microbiota composition. Rectal swabs from ICU patients demonstrated differences from healthy stool similar to those observed in comparing stool samples from ICU patients to those from the same healthy controls. Rectal swabs are a useful complement to other sample types for analysis of the intestinal microbiota in critical illness, particularly when obtaining stool may not be feasible or practical