Effect of Slope Position on Soil Properties and Types Along an Elevation Gradient of Arasbaran Forest, Iran

Sustainable development by forest managing need to identify forest ecosystem elements. Forest soil is the most important element of forest ecosystem that has key roles in forest managing. Therefore, studying of soil properties and evolution under different environmental conditions is necessary for sustainable management of forest ecosystems. Spatial variation of soil properties is significantly influenced by some environmental factors that slope position is one of them. The aim of this study was evaluating effects of slope position on forest soil change which was carried out in Arasbaran forest, North-West of Iran. Nine soil profiles were dug, described and sampled in three different parts of an altitudinal transect with same environmental conditions and different slope positions. Then soil samples were analysed physicaly and chemicaly and so classified based on Soil Taxonomy 2014. Also according to obtained results One-way analysis of variance was used to test relations of soil properties and slope positions. This results revealed significant effect of slope positions on thickness of the soil profile and solum, clay, organic carbon and total nitrogen percentages and cation exchange capacity at 5% level of confidence which lead to change of type, depth and sequence of soil horizons along altitudinal transect. Finally, it has found that slope position not only has important role in soil properties changes and soil evolution but also it can't be refused the various role and influence of same forest stand in different slope positions. Therefore various soils such as Inceptisols, Alfisols and Molisols were observed under different slope positions. Then it can be achieved that, because of special forest vegetation, soil evolution along altitudinal transect of forest ecosystems are differing from other ecosystems. Thus, for forest soil management program it is necessary to consider both of topography and vegetation effect over the area, even if one of them is constant

Estimativa da composição elementar de solos do Azerbaijão oeste, Irã, utilizando-se modelos espectrais de infravermelho

[Abstract] Characterizing the elemental composition provides useful information about the weathering degree of soils. In Miandoab County, Northern Iran, this characterization was missing, and thus the objectives of this work were to evaluate the weathering degrees for the most typical soils in the area from their elemental compositions, and to estimate this elemental composition using Fourier transform infrared spectroscopy and Random Forest models. Five soil profiles, including Aridisols and Inceptisols, were selected as the most representative of the area. Major elemental oxides were determined in each genetic horizon by X-ray fluorescence, showing that these soils were at early developmental stages. Only Al2O3 and CaO were accurately estimated, with R2 values of 0.8, and out-of-bag mean square errors of 0.2 and 1.1, respectively. The other oxides were not predicted satisfactorily, probably due to small differences in their elemental compositions. Random Forest provided the important spectral bands related to the content of each element. For Al2O3, these bands were between 500 and 650 cm-1, which represent out-of-plane OH bending vibrations and Al-O gibbsite and alumino-silicate vibrations. For CaO, the most important bands are related to carbonate content. A combination of Fourier transform infrared spectra and Random Forest models can be used as a rapid and low-cost technique to estimate the elemental composition of arid and semi-arid soils of Northern Iran.[Resumo] A caracterização da composição elementar fornece informações úteis para caracterizar o grau de alteração dos solos. Em Miandoab, norte do Irã, esta caracterização não existe. Os objetivos deste trabalho foram avaliar o grau de intemperismo dos solos típicos da região usando a sua composição elementar e estimar esta composição usando espectroscopia infravermelha com transformada de Fourier (FTIR) e modelos Random Forest (RF). Foram selecionados cinco perfis de solo, incluindo Aridisolos e Inceptisolos, como os mais representativos da área. Os principais óxidos elementares foram determinados por fluorescência de raios-X em cada horizonte genético, mostrando que estes solos estavam em um estágio de baixo grau de desenvolvimento. Apenas o Al2O3 e o CaO foram estimados com precisão, com valores de R2 de 0,8 e erro quadrático médio nos dados utilizados para validação de 0,2 e 1,1, respectivamente, enquanto os outros óxidos não foram preditos satisfatoriamente, provavelmente devido às pequenas diferenças na sua composição. O modelo Random Forest forneceu importantes bandas espectrais relacionadas com o conteúdo de cada elemento. Para o Al2O3, estes atingiram a região 500 a 650 cm-1, o que foi atribuído a vibrações de flexão de OH e vibrações de Al-O de gibbsita e alumino-silicatos. Para o CaO, as bandas mais importantes estavam relacionadas ao teor de carbonatos. Os resultados indicam que uma combinação de espectros infravermelha de transformada de Fourier e modelos Random Forest pode ser usada como uma técnica rápida e de baixo custo para estimar a composição elementar de solos do norte do Irã

Climate change impact on bioclimatic deficiency, using microLEIS DSS in Ahar soils, Iran

Regional impact studies of the future climate change effects are necessary because projected changes in meteorological variables differ from one region to another, and different climate systems can react in varied ways to the same changes. In this study, the effects of climate change on bioclimatic deficiency were compared in two cultivation methods (irrigated and rainfed) in a semi-arid region, Ahar (East Azarbaijan, IRAN). The agricultural land uses selected for evaluation were wheat (Triticum aestivum), alfalfa (Medicago sativa), sugar beet (Beta vulgaris), potato (Solanum tuberosum), and maize (Zea mays). In this way, Terraza model included in the land evaluation decision support system, called MicroLEIS DSS, was used. Terraza gives a quantitative prediction of a site bioclimatic deficiency. Soil morphological and analytical data were obtained from 44 sampling points based on a grid survey. Agro-climatic data, referred to temperature and precipitation, were collected from weather stations located in Ahar region, which benefits from more than 20 consecutive years of weather data. A future scenario of climate change was calculated according to the Intergovernmental Panel on Climate Change (IPCC) on regions of Asia under scenario A1FI (highest future emission) for 2080s. Although, increasing of precipitation being available by climate change in the future scenario, humidity index will be reduced because of high temperature. The results showed that climate change is likely to cause severe water stress in irrigated cultivation of alfalfa, sugar beet, potato, and maize, the use of irrigation methods being essential to maintain agricultural productivity. Although irrigation is indicated as very important in this regime of semi-arid agriculture, cultivation of rainfed wheat can be possible instead of the irrigated one. Also, it is revealed that climate perturbation effects on rainfed conditions are more serious than those on the irrigated conditions in the area.The authors wish to thank Tabriz University for funding this research work, a dissertation of Ph. D. program undertaken by Farzin Shahbazi. They also thank Consejo Superior de Investigaciones Científicas (CSIC), Instituto de Recursos Naturales y Agrobiología de Sevilla (IRNAS), Sevilla, Spain for their sincere cooperation during the candidate’ s sabbatical studies.Peer Reviewe

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

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

Soil erosion assessment and monitoring by using ImpelERO model in east Azerbaijan province, Iran.

4 pages, 3 figures, 1 table, 10 references. Este trabajo está incluido en el capítulo Symposium 3.2.1.: Highland agriculture and conservation of soil and water. el congreso tuvo lugar en Brisbane, Australia, 1-6 Agosto, 2010.Soil erosion continues to be a major concern for the development of sustainable agricultural management systems. Neural networks, as an artificial intelligence technology, have grown rapidly over the past few years and have an ability to deal with nonlinear multivariate systems. An integrated Model to Predict European Land use named ImpelERO is a decision trees/neural network hybrid model. This paper focuses on the possibility of model application in an area of west Asia by recalibration and generalization. The overall approach of ImpelERO model was applied in 14 natural regions from the east Azerbaijan province, Iran. Results showed that vulnerability indexes vary from 0.03 to 1.32 while risk classes will be very small (V1), small (V2), moderate (V3), large (V4), and very large (V5) in an area extension of 1080, 1860, 1184, 2981, and 1772 hectares, respectively. Lands belong to Zargar and Dizanlou natural regions because of topographical limitation factors are established with a very large risk class. Long term productivity reduction for time horizons 2020, 2050 and 2100 indicutes that management planning is necessary to minimize soil loss rate.Peer reviewe

Land use planning in Ahar area (Iran) using MicroLEIS DSS

10 pages, 6 figures, 8 tables, 26 references.The decision support system, MicroLEIS DSS, was applied to evaluate the land use planning in Ahar area, East Azarbaijan. In this way 6 agro-ecological land evaluation models constituents of this DSS software were selected in order to make strategies related to land evaluation at a regional level, such as segregation of agricultural lands, restoration of marginal areas, diversification of crop rotation, and identification of vulnerability areas. Results obtained from each evaluation models are presented and discussed in this research work. Soil morphological and analytical data were collected from 44 soil profiles representative of the study area and stored in SDBm plus database. Three control sections: 0-50, 25-50, and 0-100 cm were calculated by ‘soil layer generator’ to apply and run the models. Results show that in Ahar area, 45% of the total extension was classified as good capability land for agricultural uses. However, almost 12% of total area must be reforested by suitable shrub species, and not dedicated to agriculture, to minimize the land degradation. Additionally, soils with vertic properties used to present an excellent capability for most of the traditional crops. Wheat-alfalfa-soybean was selected as the best crop rotation. In summary, MicroLEIS DSS tool appears to be useful in semi-arid regions, such as East Azarbaijan (Iran), to formulate sustaining agro-ecological systems.Peer reviewe

Alcor and Aljarafe models application for exploring the agro-ecological limits of sustainability in Ahar area (Iran)

Comunicación oral y póster presentados en la citada conferencia, sesión 3, celebrada del 21-24, septiembre, 2009, en Bratislava, Slovakia.Peer reviewe