Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world\u27s major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (−0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km² resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e., offset) between in-situ soil temperature measurements, based on time series from over 1200 1-km² pixels (summarized from 8500 unique temperature sensors) across all the world’s major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in-situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Global maps of soil temperature.

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0-5 and 5-15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed

ESTRUTURA DA VEGETAÇÃO DE TRÊS ÁREAS DE FLORESTA ESTACIONAL NOS ESTADOS DE GOIÁS, MINAS GERAIS E TOCANTINS

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Triple-Frequency Doppler Retrieval of Characteristic Raindrop Size

A retrieval for characteristic raindrop size and width of the drop size distribution (DSD) based on triple-frequency vertical Doppler radar measurements is developed. The algorithm exploits a statistical relation that maps measurements of the differential Doppler velocities at X and Ka and at Ka and W bands into the two aforementioned DSD moments. The statistical mapping has been founded on 7,900 hr of disdrometer-observed DSDs and their simulated Doppler velocities. Additionally, a retrieval of D-m based only on DDVX-W measurements is also presented, and its performance is compared to the analogous algorithm exploiting DDVKa-W data. The retrievals are tested using triple-frequency radar data collected during a recent field campaign held at the Juelich Observatory for Cloud Evolution (JOYCE, Germany) where in situ measurements of the DSD were carried out only few meters away from the vertically pointing radars. The triple-frequency retrieval is able to obtain D-m with an uncertainty below 25% for D-m ranging from 0.7 to 2.4 mm. Compared to previously published dual-frequency retrievals, the third frequency does not improve the retrieval for small D-m (< 1.4 mm). However, it significantly surpasses the DDVKa-W algorithm for larger D-m (20% versus 50% bias at 2.25 mm). Also compared to DDVX-W method, the triple-frequency retrieval is found to provide an improvement of 15% in terms of bias for D-m = 2.25 mm. The triple-frequency retrieval of sigma(m) performs with an uncertainty of 20-50% for 0.2 < sigma(m) < 1.3 mm, with the best performance for 0.25 < sigma(m) < 0.8 mm

Triple‐Frequency Doppler Retrieval of Characteristic Raindrop Size

A retrieval for characteristic raindrop size and width of the drop size distribution (DSD) based on triple-frequency vertical Doppler radar measurements is developed. The algorithm exploits a statistical relation that maps measurements of the differential Doppler velocities at X and Ka and at Ka and W bands into the two aforementioned DSD moments. The statistical mapping has been founded on 7,900 hr of disdrometer-observed DSDs and their simulated Doppler velocities. Additionally, a retrieval of Dm based only on DDVX−W measurements is also presented, and its performance is compared to the analogous algorithm exploiting DDVKa−W data. The retrievals are tested using triple-frequency radar data collected during a recent field campaign held at the Juelich Observatory for Cloud Evolution (JOYCE, Germany) where in situ measurements of the DSD were carried out only few meters away from the vertically pointing radars. The triple-frequency retrieval is able to obtain Dm with an uncertainty below 25% for Dm ranging from 0.7 to 2.4 mm. Compared to previously published dual-frequency retrievals, the third frequency does not improve the retrieval for small Dm (< 1.4 mm). However, it significantly surpasses the DDVKa−W algorithm for larger Dm (20% versus 50% bias at 2.25 mm). Also compared to DDVX−W method, the triple-frequency retrieval is found to provide an improvement of 15% in terms of bias for Dm = 2.25 mm. The triple-frequency retrieval of m performs with an uncertainty of 20–50% for 0.2 < m < 1.3 mm, with the best performance for 0.25 < m < 0.8 mm

Triple-Frequency Doppler Retrieval of Characteristic Raindrop Size

A retrieval for characteristic raindrop size and width of the drop size distribution (DSD) based on triple-frequency vertical Doppler radar measurements is developed. The algorithm exploits a statistical relation that maps measurements of the differential Doppler velocities at X and Ka and at Ka and W bands into the two aforementioned DSD moments. The statistical mapping has been founded on 7,900 hr of disdrometer-observed DSDs and their simulated Doppler velocities. Additionally, a retrieval of (Formula presented.) based only on (Formula presented.) measurements is also presented, and its performance is compared to the analogous algorithm exploiting (Formula presented.) data. The retrievals are tested using triple-frequency radar data collected during a recent field campaign held at the Juelich Observatory for Cloud Evolution (JOYCE, Germany) where in situ measurements of the DSD were carried out only few meters away from the vertically pointing radars. The triple-frequency retrieval is able to obtain (Formula presented.) with an uncertainty below 25% for (Formula presented.) ranging from 0.7 to 2.4 mm. Compared to previously published dual-frequency retrievals, the third frequency does not improve the retrieval for small (Formula presented.) ((Formula presented.) mm). However, it significantly surpasses the (Formula presented.) algorithm for larger (Formula presented.) (20% versus 50% bias at 2.25 mm). Also compared to (Formula presented.) method, the triple-frequency retrieval is found to provide an improvement of 15% in terms of bias for (Formula presented.) mm. The triple-frequency retrieval of (Formula presented.) performs with an uncertainty of 20–50% for (Formula presented.) mm, with the best performance for (Formula presented.) mm

Fitossociologia de uma Floresta Estacional Decídual em Unaí, MG.

Were performed an arboreal inventory of Deciduous Forests fragments in Unaí-MG through out sampling of 36 plots of 500 m². The plots made contact with others phygsionomioes and some of then were allocated in areas with human use. All trees with circumference at 1,30 of  soil height ≥ 15 cm  were sampled and subsequently the data converted to diameter. The density, frequency, dominance and value of the importance of the species, besides the estimated richness, collector-curve, diametric classes and dendrograms were calculated. Of the 116 species listed, Myracrodruon urundeuva Allemão, Anadenanthera peregrine (L.) Speg., Ficus sp. L. e Senegalia polyphylla (DC.) Britton &amp; Rose had the highest values of importance. The Shannon-Weaver diversity index was 3.53 with 1095.55 ind./ha and 24.88m² / ha of basal area. The results indicate a high floristic-structural heterogeneity due to a relationship with other phytophysiognomies and anthropic pressure. These are the main reasons for an estimated high speed (152 species)