Scale,context, and decision making in agricultural adaptation to climate variability and change

This work presents a framework for viewing agricultural adaptation, emphasizing the multiple spatial and temporal scales on which individuals and institutions process information on changes in their environment. The framework is offered as a means to gain perspective on the role of climate variability and change in agricultural adaptation, and developed for a case study of Australian agriculture. To study adaptation issues at the scale of individual farms we developed a simple modelling framework. The model highlights the decision making element of adaptation in light of uncertainty, and underscores the importance of decision information related to climate variability. Model results show that the assumption of perfect information for farmers systematically overpredicts adaptive performance. The results also suggest that farmers who make tactical planting decisions on the basis of historical climate information are outperformed by those who use even moderately successful seasonal forecast information. Analysis at continental scales highlights the prominent role of the decline in economic operating conditions on Australian agriculture. Examples from segments of the agricultural industry in Australia are given to illustrate the importance of appropriate scale attribution in adapting to environmental changes. In particular, adaptations oriented toward short time scale changes in the farming environment (droughts, market fluctuations) can be limited in their efficacy by constraints imposed by broad changes in the soil/water base and economic environment occuring over longer time scales. The case study also makes the point that adaptation must be defined in reference to some goal, which is ultimately a social and political exercise. Overall, this study highlights the importance of allowing more complexity (limited information, risk aversion, cross-scale interactions, mis-attribution of cause and effect, background context, identification of goals) in representing adaptation processes in climate change studies.     

Efficacy of two chemical coagulants and three different filtration media on removal of Aspergillus flavus from surface water

Aquatic fungi are common in various aqueous environments and play potentially crucial roles in nutrient and carbon cycling as well as interacting with other organisms. Species of Aspergillus are the most common fungi that occur in water. The present study was undertaken to elucidate the efficacy of two coagulants, aluminum sulfate and ferric chloride, used at different concentrations to treat drinking water, in removing Aspergillusflavus, as well as testing three different filtration media： sand, activated carbon, and ceramic granules, for their removal of fungi from water. The results revealed that both coagulants were effective in removing fungi and decreasing the turbidity of drinking water, and turbidity decreased with increasing coagulant concentration. Also, at the highest concentration of the coagulants, A. flavus was decreased by 99.6% in the treated water. Among ceramic granules, activated carbon, and sand used as media for water filtration, the sand and activated carbon filters were more effective in removing A.flavus than ceramic granules while simultaneously decreasing the turbidity levels in the test water samples. Post-treatment total organic carbon （TOC） and total nitrogen （TN） concentrations in the experimental water did not decrease; on the contrary, TN concentrations increased with the increasing dosage of coagulants. The filtration process had no effect in reducing TOC and TN in tested water.     

Prevalence of Norovirus Infection in Children and Adults with Acute Gastroenteritis,Tehran, Iran, 2008–2009

Noroviruses are one of important agents that cause acute viral gastroenteritis worldwide. These viruses are belonging to Caliciviridae family and are genetically diverse. To date, there is no valuable data about prevalence of norovirus infection and the dominant genogroup/genotype among Iranian population. The objective of this study was to determine the frequency of norovirus infection in Iranian patients with gastroenteritis referred to three hospitals of Tehran and to specify the dominant genogroup/genotype of this virus among our study population. A total of 293 patients with acute gastroenteritis were included in the study. Detection of norovirus was performed using RT-PCR method and confirmed by direct sequencing with specific designed primers for capsid region of norovirus genome. Phylogenetic analysis was performed using the neighbor-joining method. Norovirus strains identified in our study were subsequently categorized according to previously defined genogroup/genotypes. Of these, norovirus GII was dominant genogroup. Sixty-five percent (17 of 26) of positive samples were determined as GII and 35% (9 of 26) were determined as GI, respectively, in 2008–2009. And among 8 sequenced strains of genogroup II the most frequent genotype was GII.3. The results of this study indicated that norovirus must be considered as one of the infectious causes of acute gastroenteritis among Iranian population. We also found that GII.3 is more prevalent in our study population. To the best of our knowledge there is limited data about the role of noroviruses in children and adults’ acute gastroenteritis among Iranian patients and this prevalence and genotyping report of norovirus infection could be remarkable for further studies.     

Empirical likelihood confidence intervals for adaptive cluster sampling

Adaptive cluster sampling (ACS) is an efficient sampling design for estimating parameters of rare and clustered populations. It is widely used in ecological research. The modified Hansen-Hurwitz (HH) and Horvitz-Thompson (HT) estimators based on small samples under ACS have often highly skewed distributions. In such situations, confidence intervals based on traditional normal approximation can lead to unsatisfactory results, with poor coverage properties. Christman and Pontius (Biometrics 56:503–510, 2000) showed that bootstrap percentile methods are appropriate for constructing confidence intervals from the HH estimator. But Perez and Pontius (J Stat Comput Simul 76:755–764, 2006) showed that bootstrap confidence intervals from the HT estimator are even worse than the normal approximation confidence intervals. In this article, we consider two pseudo empirical likelihood functions under the ACS design. One leads to the HH estimator and the other leads to a HT type estimator known as the Hájek estimator. Based on these two empirical likelihood functions, we derive confidence intervals for the population mean. Using a simulation study, we show that the confidence intervals obtained from the first EL function perform as good as the bootstrap confidence intervals from the HH estimator but the confidence intervals obtained from the second EL function perform much better than the bootstrap confidence intervals from the HT estimator, in terms of coverage rate.     

Modeling carbon sequestration under zero tillage at the regional scale. I. The effect of soil erosion

Zero tillage is recognized as a potential measure to sequester carbon dioxide in soils and to reduce CO₂ emissions from arable lands. An up-scaling approach of the output of the Environmental Policy Integrated Climate (EPIC) model with the information system SLISYS-BW has been used to estimate the CO₂-mitigation potential in the state of Baden-Württemberg (SW-Germany). The state territory of 35,742 km² is subdivided into eight agro-ecological zones (AEZ), which have been further subdivided into a total of 3976 spatial response units. Annual CO₂-mitigation rates where estimated from the changes in soil organic carbon content comparing 30 years simulations under conventional and zero tillage. Special attention was given to the influence of tillage practices on the losses of organic carbon through soil erosion, and consequently on the calculation of CO₂-mitigation rates. Under conventional tillage, mean carbon losses through erosion in the AEZ were estimated to be up to 0.45 Mg C ha⁻¹ a⁻¹. The apparent CO₂-mitigation rate for the conversion from conventional to zero tillage ranges from 0.08 to 1.82 Mg C ha⁻¹ a⁻¹ in the eight AEZ, if the carbon losses through soil erosion are included in the calculations. However, the higher carbon losses under conventional tillage compared to zero tillage are composed of both, losses through enhanced CO₂ emissions, and losses through intensified soil erosion. The adjusted net CO₂-mitigation rates of zero tillage, subtracting the reduced carbon losses through soil erosion, are between 0.07 and 1.27 Mg C ha⁻¹ a⁻¹ and the estimated net mitigation rate for the entire state amounts to 285 Gg C a⁻¹. This equals to 1045 Gg CO₂-equivalents per year with the cropping patterns in the reference year 2000. The results call attention to the necessity to revise those estimation methods for CO₂-mitigation which are exclusively or predominantly based on the measurements of differential changes in total soil organic carbon without taking into account the tillage effects on carbon losses through soil erosion.     

Influence of polymethyl acrylate additive on the formation of particulate matter and NOX emission of a biodiesel–diesel-fueled engine

Environmental Science and Pollution Research - The aim of this study is to investigate the effect of the polymethyl acrylate (PMA) additive on the formation of particulate matter (PM) and nitrogen...     

Impacts of COVID-19 on Sustainable Development Goals and effective approaches to maneuver them in the post-pandemic environment

Environmental Science and Pollution Research - In the pursuit of constructing a sustainable world for all through the instrumental seventeen Sustainable Development Goals, the COVID-19 pandemic...     

COVID-19 and beliefs about tobacco use: an online cross-sectional study in Iran

Environmental Science and Pollution Research - There is mixed evidence surrounding the relationship between tobacco use and COVID-19 infection/progression. The current study investigates beliefs...     

Investigation of the association between pesticide exposure and the prevalence of type 2 diabetes in Shahedieh population in Yazd

Environmental Science and Pollution Research - This study aimed to investigate the effect of exposure to pesticides and the prevalence of type 2 diabetes (T2D). In a cross-sectional study with a...