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Long-term records of burned area are needed to understand wildfire dynamics, assess fire impacts on ecosystems and air quality, and improve fire forecasts. Here we fuse multiple streams of remote sensing data to create a 24-year (1997–2020) dataset of monthly burned area as a component of the 5th version of the Global Fire Emissions Database (GFED5). During 2001–2020, we use the Moderate Resolution Imaging Spectroradiometer (MODIS) MCD64A1 burned area product and correct for the errors of commission and omission. Adjustment factors are estimated based on region, land cover, and tree cover fraction, using spatiotemporally aligned burned area from Landsat or Sentinel-2. Burned area in cropland, peatland, and deforestation regions is estimated from MODIS active fire detections. Along Track Scanning Radiometer (ATSR) and Visible and Infrared Scanner (VIRS) active fire data are used to extend the time series back to 1997. Global annual burned area is estimated to be 774 ± 63 Mha yr−1 during 2001–2020 or 5.9 ± 0.5 % of ice-free land. Burned area declined by 1.21 ± 0.66 % yr−1, a cumulative decrease of 24.2 ± 13.2 % over 20 years. The global reduction is primarily driven by decreases in fire within savannas, grasslands, and croplands. Forest, peat, and deforestation fires did not exhibit long-term trends. GFED5 global burned area is 93 % higher than MCD64A1, 61 % higher than GFED4s, and in closer agreement with burned area products from higher-resolution satellite sensors. These data may reduce discrepancies between fire emission estimates from top-down and bottom-up approaches, and improve understanding of global fire impacts on the carbon cycle and climate system.

Recent long and intensive wildfire seasons in many regions have highlighted the urgency to understand the shift in worldwide fire regimes, raising the question if human induced climate change has played a role therein. However, attributing changes in fire to anthropogenic climate change is difficult, since possible signals are confounded by multiple drivers including fire weather, fuel availability and sources of ignition. Therefore, fire indices or individual input variables are often used as proxies. There have been some attempts to model drivers of recent trends in fire, though assessment of overall anthropogenic climate change is still lacking. Recent integration of fire models into ISIMIP now allow us to perform a fire impact attribution analysis using multiple coupled fire-vegetation models. Here, we combine both ISIMIP factual and counterfactual simulations with remote sensed observations to understand how burnt area has changed over the historical period due to a changing climate.

Fire-enabled dynamic global vegetation models (DGVMs) can be used to study how fire activity responds to its main drivers, including climate/weather, vegetation and human activities, at coarse spatial scales. Such models can also be used to examine the effects of fire on vegetation, and, when embedded in Earth system models, investigate the feedback of fire on the climate system. Thus they are valuable tools for studying wildfires. Accordingly, the Fire Model Intercomparison Project (FireMIP) was established to evaluate and utilise these models using consistent protocols.Here we present the second round of FireMIP simulations to focus historic wildfire drivers (1901 to present). A six-member ensemble of simulations from fire-enabled DGVMs was compared to remotely-sensed burnt area observations and to the previous round of historical FireMIP simulations. We found that the model skill when simulating spatial patterns of burnt area shows modest improvements compared to the previous FireMIP round, and that the simulations mostly reproduce the decreasing trend in global burnt area found over the last two decades. However, whilst the broad global patterns are reasonable, there are considerable discrepancies with regards to regional agreement and timing of burnt area. Furthermore, the models show diverging trends in the pre-satellite era.To investigate further and inform future model development, we explored the residuals between simulated burnt area from the FireMIP models and remotely-sensed burnt area as a function of climate, vegetation, anthropogenic and topographic variables using generalised additive models (GAMs). We found some common responses across the models, with many over-predicting fire activity in arid/low productivity areas and all models under-predicting at low road density. However, with respect to other variables, such as wind speed and cropland fraction, the models residuals showed divergent responses. It is anticipated that these results should aid further development of global fire models in terms of driving variables, process representations and model structure.

This paper describes the rationale and the protocol of the first component of the third simulation round of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3a, www.isimip.org) and the associated set of climate-related and direct human forcing data (CRF and DHF, respectively). The observation-based climate-related forcings for the first time include high-resolution observational climate forcings derived by orographic downscaling, monthly to hourly coastal water levels, and wind fields associated with historical tropical cyclones. The DHFs include land use patterns, population densities, information about water and agricultural management, and fishing intensities. The ISIMIP3a impact model simulations driven by these observation-based climate-related and direct human forcings are designed to test to what degree the impact models can explain observed changes in natural and human systems. In a second set of ISIMIP3a experiments the participating impact models are forced by the same DHFs but a counterfactual set of atmospheric forcings and coastal water levels where observed trends have been removed. These experiments are designed to allow for the attribution of observed changes in natural, human and managed systems to climate change, rising CH4 and CO2 concentrations, and sea level rise according to the definition of the Working Group II contribution to the IPCC AR6.

Widespread changes in the intensity and frequency of fires across the globe are altering the terrestrial carbon (C) sink1–4. Although the changes in ecosystem C have been reasonably well quantified for plant biomass pools5–7, an understanding of the determinants of fire-driven changes in soil organic C (SOC) across broad environmental gradients remains unclear, especially in global drylands3,4,7–9. Here, we combined multiple datasets and original field sampling of fire manipulation experiments to evaluate where and why fire changes SOC the most, built a statistical model to estimate historical changes in SOC, and compared these estimates to simulations from ecosystem models. We found that drier ecosystems experienced larger relative changes in SOC than humid ecosystems—in some cases exceeding losses from plant biomass pools—primarily explained by high fire-driven declines in tree biomass inputs in dry ecosystems. Ecosystem models provided more mixed insight into potential SOC changes because many models underestimated the SOC changes in drier ecosystems. Upscaling our statistical model predicted that soils in 1.57 million km2 savanna-grassland regions experiencing declines in burned area over the past ca. two decades may have 23% more SOC, equating to 1.78 PgC in topsoils. Consequently, ongoing declines in fire frequencies have likely created an extensive carbon sink in the soils of global drylands that may have been underestimated by ecosystem models.

Human activity has fundamentally altered wildfire on Earth, creating serious consequences for human health, global biodiversity, and climate change. However, it remains difficult to predict fire interactions with land use, management, and climate change, representing a serious knowledge gap and vulnerability. We used expert assessment to combine opinions about past and future fire regimes from 98 wildfire researchers. We asked for quantitative and qualitative assessments of the frequency, type, and implications of fire regime change from the beginning of the Holocene through the year 2300. Respondents indicated that direct human activity was already influencing wildfires locally since at least ~12,000 years BP, though natural climate variability remained the dominant driver of fire regime until around 5000 years BP. Responses showed a ten-fold increase in the rate of wildfire regime change during the last 250 years compared with the rest of the Holocene, corresponding first with the intensification and extensification of land use and later with anthropogenic climate change. Looking to the future, fire regimes were predicted to intensify, with increases in fire frequency, severity, and/or size in all biomes except grassland ecosystems. Fire regime showed quite different climate sensitivities across biomes, but the likelihood of fire regime change increased with higher greenhouse gas emission scenarios for all biomes. Biodiversity, carbon storage, and other ecosystem services were predicted to decrease for most biomes under higher emission scenarios. We present recommendations for adaptation and mitigation under emerging fire regimes, concluding that management options are seriously constrained under higher emission scenarios.Competing Interest StatementThe authors have declared no competing interest. Introduction Methods and materials Results and discussion Timing and type of future fire regime change Consequences of fire regime change Our capacity to prevent, control, or adapt to future fire regimes Charting a course in a world of uncertainty Expert assessment application in fire management

Fire is a crucial factor in terrestrial ecosystems playing a role in disturbance for vegetation dynamics. Process-based fire models quantify fire disturbance effects in stand-alone dynamic global vegetation models (DGVMs) and their advances have incorporated both descriptions of natural processes and anthropogenic drivers. Nevertheless, these models show limited skill in modeling fire events at the global scale, due to stochastic characteristics of fire occurrence and behavior as well as the limits in empirical parameterizations in process-based models. As an alternative, machine learning has shown the capability of providing robust diagnostics of fire regimes. Here, we develop a deep-learning-based fire model (DL-fire) to estimate daily burnt area fraction at the global scale and couple it within JSBACH4, the land surface model used in the ICON ESM. The stand-alone DL-fire model forced with meteorological, terrestrial and socio-economic variables is able to simulate global total burnt area, showing 0.8 of monthly correlation (rm) with GFED4 during the evaluation period (2011-15). The performance remains similar with the hybrid modeling approach JSB4-DL-fire (rm=0.79) outperforming the currently used uncalibrated standard fire model in JSBACH4 (rm=-0.07). We further quantify the importance of each predictor by applying layer-wise relevance propagation (LRP). Overall, land properties, such as fuel amount and water content in soil layers, stand out as the major factors determining burnt fraction in DL-fire, paralleled by meteorological conditions over tropical and high latitude regions. Our study demonstrates the potential of hybrid modeling in advancing fire prediction in ESMs by integrating deep learning approaches in physics-based dynamical models.

A 43-year-old woman with a medical history of splenectomy for immune thrombocytopenic purpura was diagnosed with bacteremia. Her initial complaints were fever and more importantly painful extremities that appeared cyanotic. During her hospitalisation, she never developed cardiocirculatory failure but presented acute kidney injury (AKI) with oliguria. Laboratory investigations confirmed AKI with serum creatinine 2.55 mg/dL which peaked at 6.49 mg/dL. There was also evidence for disseminated intravascular coagulation (DIC) with decreased platelet count, low fibrinogen levels, and high D-dimer levels. There were no signs of haemolytic anaemia. The initial ADAMTS13 activity was low (17%) but slowly recovered. Renal function progressively improved with supportive therapy, as opposed to the progressing skin necrosis. The association of DIC and low ADAMTS13 activity may have contributed to the severity of microthrombotic complications, even in the absence of thrombotic microangiopathy as thrombotic thrombocytopenic purpura (TTP) or pneumococcal-associated haemolytic uremic syndrome (pa-HUS).

International audience; A 53-year-old woman with a history of acute myeloid leukaemia received a second allogeneic haematopoietic stem cell transplant and was prescribed, among other medications, acyclovir and letermovir (480-mg daily oral dose) for prophylaxis of, respectively, herpes simplex and cytomegalovirus infection. The patient was admitted in the intensive care unit for dyspnoea and oliguria. Laboratory investigations revealed acute kidney injury but also a severe and progressive lactic acidosis. Liver function tests were within normal range. The combination of lactic acidosis, hypoglycaemia and acylcarnitine profile in plasma raised the suspicion of mitochondrial toxicity. Letermovir therapy was interrupted, and determination of plasma letermovir pharmacokinetics revealed a prolonged terminal half-life (38.7 h) that was not significantly influenced by continuous venovenous haemofiltration. Exploration for genetic polymorphisms revealed that the patient was SLCO1B1*5/*15 (c.521T>C homozygous carrier and c.388A>G heterozygous carrier) with a predicted nonfunctional organic anion transporting polypeptide 1B1 protein. The relationship between letermovir accumulation and development of lactic acidosis requires further observations.

Magistritöö Aianduse õppekaval Kaasaegne põllumajandus liigub aasta-aastalt mahepõllumajanduse, loodust säästvate ja keskkonnasõbralike süsteemide suunas. Tänapäeva keskkonnamõju vähendamiseks ja kestlikuma tuleviku nimel on just biostimulandid need, mida saab ebasoodsates tingimustes tõhusalt kasutada taimede kasvu ja arengu soodustamiseks. Merevetikad mõjutavad soodsalt taime mikrofloorat, parandavad risosfääris elavaid eluvorme, suurendavad taime toimetulekut biootilise ja abiootilise stressiga. Käesoleva töö eesmärgiks oli välja selgitada erinevate merevetikaekstrakti sisaldavate biostimulantidega kastmise mõju aed-raudürdi (Verbena x hybrida) sordi Lanai ´Scarlet with Eye` kasvule ja õitsemisele. Katses kasutati erinevaid merevetikaid sisaldavaid biostimulante nagu Allgrow, Basfoliar Aktiv, Folicist ja Phylgreen. Allgrow on elusatest mikrovetikatest koosnev biostimulant. Basfoliar Aktiv on kombinatsioon makroelementidest ja merevetika (Ecklonia maxima) ekstraktist. Phylgreen on 100% külmtöödeldud pruunvetika (Ascophyllum nodosum) ekstrakt. Folicist sisaldab pruunvetika (Ascophyllum nodosum) ja taimset hariliku lutserni (Medicago sativa) ekstrakti. Katses kasutatud biostimulante anti taimedele läbi kastmise. Katse alguses olid taimed esimesed 3 kuud kasvuhoones ja hiljem (juuni keskpaigast) avamaal kuni katse lõpuni. Katsetulemustest selgus, et neljast kasutatud biostimulandist suurendas oluliselt taimede kasvu Allgrow ja Basfoliar Aktiv. Folicisti ja Phylgreeni kasutamine ei avaldanud taimede kasvule ega õitsemisele olulist statistilist mõju. Kogutud andmete põhjal võib aed-raudürdi kasvu ja õitsemise parandamiseks soovitada biostimulante Allgrow ja Basfoliar Aktiv. Modern agriculture is moving year-by-year towards organic farming, nature saving and environmentally friendly systems. In order to reduce today`s environmental impact and for a more sustainable future, are biostimulants that can be effectively used to promote plant growth and development under adverse conditions. The aim of the current study was to determine the effect of different algae based biostimulants on the growth and flowering of garden verbena (Verbena x hybrida) cv Lanai `Scarlet with Eye`. The different algae based biostimulants in the experiment were Allgrow, Basfoliar Aktiv, Folicist and Phylgreen. Allgrow contains live microalgae. Basfoliar Aktiv is a combination of macro elements and seaweed (Ecklonia maxima) extract. Phylgreen is a 100% cold processed brown seaweed (Ascophyllum nodosum) extract. Folicist is a combination of brown seaweed (Ascophyllum nodosum) and plant based alfaalfa (Medicago sativa) extracts. The plants were watered with biostimulants according to the manufacturer's recommendations and grown in greenhouse (the first three months) and open field (from mid June) conditions. The results showed that Allgrow and Basfoliar Aktiv significantly increased the plant growth whereas Folicist and Phylgreen had no significant influence on growth and flowering of garden verbenas. Based on the results of the current study Allgrow and Basfoliar Aktive can be recommended for garden verbenas to improve their growth and flowering.

A 53-year-old woman with a history of acute myeloid leukemia received a second allogenic hematopoietic stem cell transplant (HSCT) and was prescribed, among other medications, acyclovir and letermovir (480 mg daily oral dose) for prophylaxis of respectively herpes simplex and cytomegalovirus infection. The patient was admitted in the intensive care unit (ICU) for dyspnea and oliguria. Laboratory investigations revealed acute kidney injury, but also a severe and progressive lactic acidosis. Liver function tests were within normal range. The combination of lactic acidosis, hypoglycaemia and acylcarnitine profile in plasma suspected a mitochondrial toxicity. Letermovir therapy was interrupted and determination of plasma letermovir pharmacokinetics revealed a prolonged terminal half-life (40.7 h) that was not significantly influenced by continuous venovenous hemofiltration. Exploration for genetic polymorphisms revealed that the patient was SLCO1B1*5/*15 (c.521T>C homozygous carrier and c.388A>G heterozygous carrier) with a predicted non-functional OATP1B1 protein. The relationship between letermovir accumulation and development of lactic acidosis requires further observations.

Purpose Investigate safety and tolerability of adrecizumab, a humanized monoclonal adrenomedullin antibody, in septic shock patients with high adrenomedullin. Methods Phase-2a, double-blind, randomized, placebo-controlled biomarker-guided trial with a single infusion of adrecizumab (2 or 4 mg/kg b.w.) compared to placebo. Patients with adrenomedullin above 70 pg/mL

El fuego ha ocurrido naturalmente en los ecosistemas, volviéndose incluso esencial para la evolución de la biodiversidad en algunos de ellos. Pero, así como hay ecosistemas que literalmente surgen de las cenizas, existen otros que, por el contrario, se ven gravemente afectados por las conflagraciones. La intervención humana, sumada a las altas temperaturas derivadas del cambio climático, están creando el cóctel perfecto para que los incendios forestales sean cada vez más voraces. ¿Cuál es la chispa que inició todo?