Carbon stocks and potential sequestration of Uruguayan soils: a road map to a comprehensive characterization of temporal and spatial changes to assess carbon footprint

Carbon net emission is a critical aspect of the environmental footprint in agricultural systems. However, the alternatives to describe soil organic carbon (SOC) changes associated with different agricultural management practices/land uses are limited. Here we provide an overview of carbon (C) stocks of non-forested areas of Uruguay to estimate SOC changes for different soil units affected by accumulated effects of crop and livestock production systems in the last decades. For this, we defined levels based on SOC losses relative to the original (reference) SOC stocks: 25% or less, between 25% and 50%, and 50% or more. We characterized the reference SOC stocks using three approaches: (1) an equation to derive the potential SOC capacity based on the clay and fine silt soil content, (2) the DayCent model to estimate the SOC stocks based on climate, soil texture and C inputs from the natural grasslands of the area, (3) an estimate of SOC using a proxy derived from remote sensing data (i.e., the Ecosystem Services Supply Index) that accounts for differences in C inputs. Depending on the used reference SOC, the soil units had different distributions of SOC losses within the zones defined by the thresholds. As expected, the magnitude of SOC changes observed for the different soil units was related to the relative frequency of annual crops, however, the high variability observed along the gradient of land uses suggests a wide space for increasing SOC with agricultural management practices. The assessment of the C stock preserved (CSP) belowground and the potential for increasing C accumulation or sequestration (CAP) are critical components of the C footprint of a given system. Thus, we propose a methodological road map to derive indicators of CSP and CAP at the farm level combining both, biogeochemical simulation models and conceptual models based on remote sensing data. We recognize at least three critical issues that require scientific and political consensus to implement the use of this propose: (1) how to define reference C stocks, (2) how to estimate current C stocks over large areas and in heterogeneous agricultural landscapes, and (3) what is a reasonable/acceptable threshold of C stocks reduction

Early mobilisation in critically ill COVID-19 patients: a subanalysis of the ESICM-initiated UNITE-COVID observational study

Background Early mobilisation (EM) is an intervention that may improve the outcome of critically ill patients. There is limited data on EM in COVID-19 patients and its use during the first pandemic wave. Methods This is a pre-planned subanalysis of the ESICM UNITE-COVID, an international multicenter observational study involving critically ill COVID-19 patients in the ICU between February 15th and May 15th, 2020. We analysed variables associated with the initiation of EM (within 72 h of ICU admission) and explored the impact of EM on mortality, ICU and hospital length of stay, as well as discharge location. Statistical analyses were done using (generalised) linear mixed-effect models and ANOVAs. Results Mobilisation data from 4190 patients from 280 ICUs in 45 countries were analysed. 1114 (26.6%) of these patients received mobilisation within 72 h after ICU admission; 3076 (73.4%) did not. In our analysis of factors associated with EM, mechanical ventilation at admission (OR 0.29; 95% CI 0.25, 0.35; p = 0.001), higher age (OR 0.99; 95% CI 0.98, 1.00; p ≤ 0.001), pre-existing asthma (OR 0.84; 95% CI 0.73, 0.98; p = 0.028), and pre-existing kidney disease (OR 0.84; 95% CI 0.71, 0.99; p = 0.036) were negatively associated with the initiation of EM. EM was associated with a higher chance of being discharged home (OR 1.31; 95% CI 1.08, 1.58; p = 0.007) but was not associated with length of stay in ICU (adj. difference 0.91 days; 95% CI − 0.47, 1.37, p = 0.34) and hospital (adj. difference 1.4 days; 95% CI − 0.62, 2.35, p = 0.24) or mortality (OR 0.88; 95% CI 0.7, 1.09, p = 0.24) when adjusted for covariates. Conclusions Our findings demonstrate that a quarter of COVID-19 patients received EM. There was no association found between EM in COVID-19 patients' ICU and hospital length of stay or mortality. However, EM in COVID-19 patients was associated with increased odds of being discharged home rather than to a care facility. Trial registration ClinicalTrials.gov: NCT04836065 (retrospectively registered April 8th 2021)

Data_Sheet_1_Carbon stocks and potential sequestration of Uruguayan soils: a road map to a comprehensive characterization of temporal and spatial changes to assess carbon footprint.DOCX

Carbon net emission is a critical aspect of the environmental footprint in agricultural systems. However, the alternatives to describe soil organic carbon (SOC) changes associated with different agricultural management practices/land uses are limited. Here we provide an overview of carbon (C) stocks of non-forested areas of Uruguay to estimate SOC changes for different soil units affected by accumulated effects of crop and livestock production systems in the last decades. For this, we defined levels based on SOC losses relative to the original (reference) SOC stocks: 25% or less, between 25% and 50%, and 50% or more. We characterized the reference SOC stocks using three approaches: (1) an equation to derive the potential SOC capacity based on the clay and fine silt soil content, (2) the DayCent model to estimate the SOC stocks based on climate, soil texture and C inputs from the natural grasslands of the area, (3) an estimate of SOC using a proxy derived from remote sensing data (i.e., the Ecosystem Services Supply Index) that accounts for differences in C inputs. Depending on the used reference SOC, the soil units had different distributions of SOC losses within the zones defined by the thresholds. As expected, the magnitude of SOC changes observed for the different soil units was related to the relative frequency of annual crops, however, the high variability observed along the gradient of land uses suggests a wide space for increasing SOC with agricultural management practices. The assessment of the C stock preserved (CSP) belowground and the potential for increasing C accumulation or sequestration (CAP) are critical components of the C footprint of a given system. Thus, we propose a methodological road map to derive indicators of CSP and CAP at the farm level combining both, biogeochemical simulation models and conceptual models based on remote sensing data. We recognize at least three critical issues that require scientific and political consensus to implement the use of this propose: (1) how to define reference C stocks, (2) how to estimate current C stocks over large areas and in heterogeneous agricultural landscapes, and (3) what is a reasonable/acceptable threshold of C stocks reduction.</p

Image_2_Carbon stocks and potential sequestration of Uruguayan soils: a road map to a comprehensive characterization of temporal and spatial changes to assess carbon footprint.TIF

Carbon net emission is a critical aspect of the environmental footprint in agricultural systems. However, the alternatives to describe soil organic carbon (SOC) changes associated with different agricultural management practices/land uses are limited. Here we provide an overview of carbon (C) stocks of non-forested areas of Uruguay to estimate SOC changes for different soil units affected by accumulated effects of crop and livestock production systems in the last decades. For this, we defined levels based on SOC losses relative to the original (reference) SOC stocks: 25% or less, between 25% and 50%, and 50% or more. We characterized the reference SOC stocks using three approaches: (1) an equation to derive the potential SOC capacity based on the clay and fine silt soil content, (2) the DayCent model to estimate the SOC stocks based on climate, soil texture and C inputs from the natural grasslands of the area, (3) an estimate of SOC using a proxy derived from remote sensing data (i.e., the Ecosystem Services Supply Index) that accounts for differences in C inputs. Depending on the used reference SOC, the soil units had different distributions of SOC losses within the zones defined by the thresholds. As expected, the magnitude of SOC changes observed for the different soil units was related to the relative frequency of annual crops, however, the high variability observed along the gradient of land uses suggests a wide space for increasing SOC with agricultural management practices. The assessment of the C stock preserved (CSP) belowground and the potential for increasing C accumulation or sequestration (CAP) are critical components of the C footprint of a given system. Thus, we propose a methodological road map to derive indicators of CSP and CAP at the farm level combining both, biogeochemical simulation models and conceptual models based on remote sensing data. We recognize at least three critical issues that require scientific and political consensus to implement the use of this propose: (1) how to define reference C stocks, (2) how to estimate current C stocks over large areas and in heterogeneous agricultural landscapes, and (3) what is a reasonable/acceptable threshold of C stocks reduction.</p

Image_1_Carbon stocks and potential sequestration of Uruguayan soils: a road map to a comprehensive characterization of temporal and spatial changes to assess carbon footprint.TIF

Carbon net emission is a critical aspect of the environmental footprint in agricultural systems. However, the alternatives to describe soil organic carbon (SOC) changes associated with different agricultural management practices/land uses are limited. Here we provide an overview of carbon (C) stocks of non-forested areas of Uruguay to estimate SOC changes for different soil units affected by accumulated effects of crop and livestock production systems in the last decades. For this, we defined levels based on SOC losses relative to the original (reference) SOC stocks: 25% or less, between 25% and 50%, and 50% or more. We characterized the reference SOC stocks using three approaches: (1) an equation to derive the potential SOC capacity based on the clay and fine silt soil content, (2) the DayCent model to estimate the SOC stocks based on climate, soil texture and C inputs from the natural grasslands of the area, (3) an estimate of SOC using a proxy derived from remote sensing data (i.e., the Ecosystem Services Supply Index) that accounts for differences in C inputs. Depending on the used reference SOC, the soil units had different distributions of SOC losses within the zones defined by the thresholds. As expected, the magnitude of SOC changes observed for the different soil units was related to the relative frequency of annual crops, however, the high variability observed along the gradient of land uses suggests a wide space for increasing SOC with agricultural management practices. The assessment of the C stock preserved (CSP) belowground and the potential for increasing C accumulation or sequestration (CAP) are critical components of the C footprint of a given system. Thus, we propose a methodological road map to derive indicators of CSP and CAP at the farm level combining both, biogeochemical simulation models and conceptual models based on remote sensing data. We recognize at least three critical issues that require scientific and political consensus to implement the use of this propose: (1) how to define reference C stocks, (2) how to estimate current C stocks over large areas and in heterogeneous agricultural landscapes, and (3) what is a reasonable/acceptable threshold of C stocks reduction.</p

Statistical analysis of large simulated yield datasets for studying climate change effects

Chapitre 11Statistical analysis of large simulated yield datasets for studying climate change effect

Co-infection and ICU-acquired infection in COIVD-19 ICU patients: a secondary analysis of the UNITE-COVID data set

Background: The COVID-19 pandemic presented major challenges for critical care facilities worldwide. Infections which develop alongside or subsequent to viral pneumonitis are a challenge under sporadic and pandemic conditions; however, data have suggested that patterns of these differ between COVID-19 and other viral pneumonitides. This secondary analysis aimed to explore patterns of co-infection and intensive care unit-acquired infections (ICU-AI) and the relationship to use of corticosteroids in a large, international cohort of critically ill COVID-19 patients.Methods: This is a multicenter, international, observational study, including adult patients with PCR-confirmed COVID-19 diagnosis admitted to ICUs at the peak of wave one of COVID-19 (February 15th to May 15th, 2020). Data collected included investigator-assessed co-infection at ICU admission, infection acquired in ICU, infection with multi-drug resistant organisms (MDRO) and antibiotic use. Frequencies were compared by Pearson's Chi-squared and continuous variables by Mann-Whitney U test. Propensity score matching for variables associated with ICU-acquired infection was undertaken using R library MatchIT using the "full" matching method.Results: Data were available from 4994 patients. Bacterial co-infection at admission was detected in 716 patients (14%), whilst 85% of patients received antibiotics at that stage. ICU-AI developed in 2715 (54%). The most common ICU-AI was bacterial pneumonia (44% of infections), whilst 9% of patients developed fungal pneumonia; 25% of infections involved MDRO. Patients developing infections in ICU had greater antimicrobial exposure than those without such infections. Incident density (ICU-AI per 1000 ICU days) was in considerable excess of reports from pre-pandemic surveillance. Corticosteroid use was heterogenous between ICUs. In univariate analysis, 58% of patients receiving corticosteroids and 43% of those not receiving steroids developed ICU-AI. Adjusting for potential confounders in the propensity-matched cohort, 71% of patients receiving corticosteroids developed ICU-AI vs 52% of those not receiving corticosteroids. Duration of corticosteroid therapy was also associated with development of ICU-AI and infection with an MDRO.Conclusions: In patients with severe COVID-19 in the first wave, co-infection at admission to ICU was relatively rare but antibiotic use was in substantial excess to that indication. ICU-AI were common and were significantly associated with use of corticosteroids