The impact of seasonal weather variation on mycotoxins: maize crop in 2014 in northern Italy as a case study

2020 ◽  
Vol 13 (1) ◽  
pp. 25-36 ◽  
Author(s):  
M. Camardo Leggieri ◽  
A. Lanubile ◽  
C. Dall’Asta ◽  
A. Pietri ◽  
P. Battilani
Keyword(s):  
Climate Variability ◽  
Large Scale ◽  
Meteorological Data ◽  
Cropping System ◽  
Northern Italy ◽  
Fusarium Spp ◽  
Geographic Scale ◽  
Limit Of Quantification ◽  
Maize Crop ◽  
The Impact

The occurrence of mycotoxins differs greatly from year to year and this variation has been attributed to climate variability. The aim of this study was to consider the variability of fungal infection and mycotoxin contamination on a small geographic scale as a possible result of local weather conditions. The presence of Fusarium spp. and Aspergillus spp. and their related mycotoxins was investigated in 51 maize fields grown in 2014 in the Emilia Romagna region, in northern Italy; information regarding the cropping system was collected for all the fields. Samples collected at harvest were analysed for fumonisins, aflatoxins and trichothecenes. Hourly meteorological data were collected from nine stations and fields were clustered with the stations based on the shortest distance principle. Fusarium spp. and Aspergillus spp. incidence varied between 17.6-46.0% and 0.6-6.3%, respectively. Fumonisins ranged between 1,718 and 106,054 μg/kg and aflatoxin B1 between <limit of quantification and 93.8 μg/kg, with a wide variability also with short distanced fields. Deoxynivalenol was detected with a considerable incidence (59%), but only three samples exceeded 1,750 μg/kg. Therefore, climate variability and related uncertainties, commonly stressed on a large scale, are not only a matter for policymakers, but also for farmers facing every day the impact on fungi and mycotoxin occurrence.

scholarly journals Teleconnection between the Asian Polar Vortex and surface PM2.5 in China

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Lihua Zhou ◽  
Jing Zhang ◽  
Xiaohui Zheng ◽  
Siguang Zhu ◽  
Yueming Hu
Keyword(s):  
Large Scale ◽  
Meteorological Data ◽  
Fine Particulate Matter ◽  
Polar Vortex ◽  
Atmospheric Circulations ◽  
Fine Particulate ◽  
Heavy Pollution ◽  
Pollution Emissions ◽  
The Impact ◽  
East West

Abstract Atmospheric fine particulate matter (PM2.5) pollutions are of particular concern because of their direct and indirect harm to humans and organisms. China has suffered from severe air pollution for the past ten years, related to heavy pollution emissions and compounded by the effects of atmospheric circulation. This study applied statistical methods, observational data of ground pollutants, and meteorological data to analyze the impact of large-scale atmospheric circulations on PM2.5 pollution over China. Empirical orthogonal function (EOF) analysis was used to evaluate the main PM2.5 patterns and total contributions of the leading four EOFs. The results indicate that the total contributions of the leading four EOFs accounted for 50.5% of the total variance, reflecting four main types of PM2.5 pollution, namely, overall pollution phase, north–south phase, east–west phase and north–center–south phase, with contributions of 28.4%, 9.7%, 6.5% and 5.9%, respectively. We selected indices of the Asian Polar Vortex (APV) to analyze the impact of large-scale atmospheric circulations on PM2.5 pollution over China. The most pronounced APV control occurred in Beijing and its surroundings, specifically, along the Bohai Sea and the Northeast Plain.

scholarly journals Influence of ENSO and tropical Atlantic climate variability on flood characteristics in the Amazon basin

2020 ◽  
Author(s):  
Jamie Towner ◽  
Andrea Ficchí ◽  
Hannah L. Cloke ◽  
Juan Bazo ◽  
Erin Coughlan de Perez ◽  
...  
Keyword(s):  
Climate Variability ◽  
Early Warning ◽  
Large Scale ◽  
Amazon Basin ◽  
Early Warning Systems ◽  
Discharge Data ◽  
Flood Magnitude ◽  
Highly Correlated ◽  
The Impact ◽  
Flood Characteristics

Abstract. Flooding in the Amazon basin is frequently attributed to modes of large-scale climate variability, but little attention is paid to how these modes influence the timing and duration of floods despite their importance to early warning systems and the significant impacts that these flood characteristics can have on communities. In this study, river discharge data from the Global Flood Awareness System (GloFAS 2.1) and observed data at 58 gauging stations are used to examine whether positive/negative phases of several Pacific and Atlantic indices significantly alter the characteristics of river flows throughout the Amazon basin (1979–2015). Results show significant changes in both flood magnitude and duration, particularly in the north-eastern Amazon for negative ENSO years when the SST anomaly is positioned in the central tropical Pacific. This response is not identified for the eastern Pacific index, highlighting how the response can differ between ENSO types. Although flood magnitude and duration were found to be highly correlated, the impacts of large-scale climate variability on these characteristics are non-linear; some increases in annual flood maxima coincide with decreases in flood duration. The impact of flood timing however does not follow any notable pattern for all indices analysed. Finally, observed and simulated changes are found to be much more highly correlated for negative ENSO years compared to the positive phase, meaning that GloFAS struggles to accurately simulate the differences in flood characteristics between El Niño and neutral years. These results have important implications for both the social and physical sectors working towards the improvement of early warning action systems for floods.

scholarly journals Water Resource Management: Moving from Single Risk-Based Management to Resilience to Multiple Stressors

2021 ◽  
Vol 13 (15) ◽  
pp. 8609
Author(s):  
Sarah Bunney ◽  
Elizabeth Lawson ◽  
Sarah Cotterill ◽  
David Butler
Keyword(s):  
Resource Management ◽  
Water Resource ◽  
Water Demand ◽  
Water Resource Management ◽  
Large Scale ◽  
Multiple Stressors ◽  
Meteorological Data ◽  
Average Rainfall ◽  
The Uk ◽  
The Impact

Water resource management in the UK is multifaceted, with a complexity of issues arising from acute and chronic stressors. Below average rainfall in spring 2020 coincided with large-scale changes to domestic water consumption patterns, arising from the first UK-wide COVID-19 lockdown, resulting in increased pressure on nationwide resources. A sector wide survey, semi-structured interviews with sector executives, meteorological data, water resource management plans and market information were used to evaluate the impact of acute and chronic threats on water demand in the UK, and how resilience to both can be increased. The COVID-19 pandemic was a particularly acute threat: water demand increased across the country, it was unpredictable and hard to forecast, and compounding this, below average rainfall resulted in some areas having to tanker in water to ‘top up’ the network. This occurred in regions of the UK that are ‘water stressed’ as well as those that are not. We therefore propose a need to look beyond ‘design droughts’ and ‘dry weather average demand’ to characterise the management and resilience of future water resources. As a sector, we can learn from this acute threat and administer a more integrated approach, combining action on the social value of water, the implementation of water trading and the development of nationwide multi-sectoral resilience plans to better respond to short and long-term disruptors.

scholarly journals Perception of Climate Variability and Its Impact by Smallholders in Pastoral Systems of Abudwak District, Galmudug State, Somalia

2022 ◽  
Author(s):  
Mohamed Yonis Abdullah ◽  
Shafii Abdullahi Mohamed
Keyword(s):  
Climate Variability ◽  
Meteorological Data ◽  
Pastoral Systems ◽  
Climate Change And Variability ◽  
Significant Variability ◽  
The People ◽  
Pastoral Communities ◽  
Local Livelihood ◽  
The Impact ◽  
Different Levels

Abstract it is true in all the regions of the country; there is no stable and reliable documented meteorological data for reasonable tracking of the climate change and variability. Thus, this study explores the perception of significant variability in climate and related impact on local livestock holders among smallholders in pastoral systems of Abudwak district, Somalia. We drew on empirical data obtained from pastoral communities surveys conducted in 4 villages, 169 pastoral associations. Using this data, this study analyses smallholders' perception of climate variability and its associated impact on local livelihood, and the effect of several household on perception. Respondents interviewed during the study period, however, believed that there has been significant variability in the rainfall and temperature patterns for the last twenty years and considered climate variability as a salient risk to their future livelihoods and economic development. Likewise, the general perception of the people is that both rainfall and temperature have highly been fluctuating for decades now became unpredictable with less rainfall in shorter duration and warmer temperature over year now than usual. Different levels of perception were expressed in terms of climate variability and the impact on traditional rain-fed. Age, education level, livestock holding, access to climate information and extension services significantly affected perception levels.

scholarly journals Effect of Climate Change on Maize Productivity: Panel Data Analysis

2020 ◽  
pp. 41-45
Author(s):  
Parthasarathi Gurusamy ◽  
Balasubramanian Rudrasamy
Keyword(s):  
Regression Analysis ◽  
Panel Data ◽  
Climate Variability ◽  
Tamil Nadu ◽  
Crop Production ◽  
Panel Data Analysis ◽  
Panel Regression ◽  
Maize Crop ◽  
North East ◽  
The Impact

Aim: The maize is widely grown all parts of the world and it is consumed by all people. This paper studies the impact of climate variability on yield of maize crop in Tamil Nadu using Panel regression analysis.      Study Design: Rainfall (max and min), Temperature (max and min) and yield details were collected from the Indian Meteorological Department and crop production reports respectively used for analysis.  Place and Duration: Tamil Nadu, India. Methodology: Panel data model was used to estimate crop production functions. Results and Conclusion: The study focused on the impact of climate variability on yield of maize crop in Tamil Nadu using Panel regression analysis. The high rainfall leads to The effect of NEM rainfall on maize yield is dependent on the level of NEM temperature and vice-versa. This is probably because of the fact that in most of the districts in Tamil Nadu, maize is grown as a rainfed crop in north-east monsoon season with lower temperature and hence increase in temperature together with good amount of rainfall would lead to higher yield of maize.

scholarly journals Microhabitat Variability in Human Evolution

2021 ◽  
Vol 9 ◽  
Author(s):  
Robert Patalano ◽  
Rebecca Hamilton ◽  
Emma Finestone ◽  
Noel Amano ◽  
Phoebe Heddell-Stevens ◽  
...  
Keyword(s):  
Climate Variability ◽  
Large Scale ◽  
Vegetation Change ◽  
Spatial Scales ◽  
Regional Climate ◽  
Environmental Complexity ◽  
Linear Behavior ◽  
Climate Shifts ◽  
Landscape Response ◽  
The Impact

Climate variability and hominin evolution are inextricably linked. Yet, hypotheses examining the impact of large-scale climate shifts on hominin landscape ecology are often constrained by proxy data coming from off-site lake and ocean cores and temporal offsets between paleoenvironmental and archaeological records. Additionally, landscape response data (most commonly, records of vegetation change), are often used as a climate proxy. This is problematic as it assumes that vegetation change signifies global or regional climate shifts without accounting for the known non-linear behavior of ecological systems and the often-significant spatial heterogeneity in habitat structure and response. The exploitation of diverse, rapidly changing habitats by Homo by at least two million years ago highlights that the ability to adapt to landscapes in flux had emerged by the time of our genus’ African origin. To understand ecosystem response to climate variability, and hominin adaptations to environmental complexity and ecological diversity, we need cross-disciplinary datasets in direct association with stratified archaeological and fossil assemblages at a variety of temporal and spatial scales. In this article, we propose a microhabitat variability framework for understanding Homo’s adaptability to fluctuating climates, environments, and resource bases. We argue that the exploitation of microhabitats, or unique ecologically and geographically defined areas within larger habitats and ecoregions, was a key skill that allowed Homo to adapt to multiple climates zones and ecoregions within and beyond Africa throughout the Pleistocene.

scholarly journals The Impact of El Niño–Southern Oscillation (ENSO) on Temperature: A Case Study in Kuching, Sarawak

2021 ◽  
Vol 6 (1) ◽  
pp. 289-297
Author(s):  
Ricky Anak Kemarau ◽  
Oliver Valentine Eboy
Keyword(s):  
El Niño ◽  
Urban Areas ◽  
Large Scale ◽  
Building Materials ◽  
El Nino ◽  
Southern Oscillation ◽  
Meteorological Data ◽  
El Niño Southern Oscillation ◽  
El Nino Southern Oscillation ◽  
The Impact

The El Niño–Southern Oscillation (ENSO) event is a climate event that has an impact on the world climate. The effects of ENSO are often associated with prolonged droughts and floods since 1980 following global climate change. In addition to causing flooding and drought. Indirectly, the occurrence of ENSO causes health problems, environmental destruction, affecting economic activities such as agriculture and fisheries. Many studies on ENSO have been conducted. However, there is still a lack of research on the effect of ENSO on temperature in local knowledge areas, especially urban areas because the urban environment especially building materials that can absorb and release heat. In addition, previous studies have focused on large-scale areas. Beside that there still gap to understand and increase knowledge about the effect of ENSO on local temperatures, especially in urban areas. This study uses meteorological data and Oceanic Nino Index (ONI) from 1988 to 2019. This study found that the occurrence of ENSO has an effect on the value of daily temperature but differs based on the value of the ONI index. In addition, this study uses linear regression in predicting the effect of ENSO on temperature. The results of this study are useful to those responsible for understanding the impact of ENSO on temperature in urban areas to provide infrastructure in reducing the impact of ENSO as well as adjustment measures during the occurrence of ENSO.

scholarly journals Impacts of climate variability and land-use change on hydrology in the period 1981-2009 in the central highlands of Vietnam

2015 ◽  
Vol 17 (4) ◽  
pp. 870-881 ◽  
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Climate Variability ◽  
Assessment Tool ◽  
Meteorological Data ◽  
Land Use Changes ◽  
Hydrological Regime ◽  
Hydrological Response ◽  
Central Highlands ◽  
The Impact

<div> <p>In this study, we investigated the separate and combined impacts of climate and land-use changes on hydrological response in the Central Highlands of Vietnam during the period 1981-2009. The Mann-Kendall and Pettit tests were applied to detect the trends in the hydro-meteorological data. The Soil and Water Assessment Tool (SWAT) was setup in the region, and evaluation based on daily data highlights the models adequacy. From this, the responses of hydrology to climate variability and land-use changes were considered. Overall, variability in climate seems to strongly drive the variability in the hydrological response in comparison to alternations in the hydrological regime due to land-use change during the period 1981-2009. The results indicate that land-use change had a minor impact on the annual flow (0.4% reduction), whilst the impact from climate variability had been more significant (13.5% change). Under the impact of coupled climate variability and land-use change, the annual streamflow increased by 13.1%.</p> </div> <p>&nbsp;</p>

scholarly journals Gendered Perceptions of Climate Variability and Change among Local Communities Living around Queen Elizabeth National Park in Uganda

2021 ◽  
Vol 4 (4) ◽  
Author(s):  
F. S. Nalwanga ◽  
M. Sowman ◽  
P. I. Mukwaya ◽  
P Musali ◽  
A. Nimusiima ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
National Park ◽  
Quantitative Methods ◽  
Meteorological Data ◽  
Local Communities ◽  
Climate Variability And Change ◽  
Men And Women ◽  
Flooding Events ◽  
The Impact

Climate change affects both men and women which, in turn, shapes their varied and contrasting perceptions of climate variability and change. This paper examined the gendered perceptions of climate variability and change among local communities in Queen Elizabeth National Park in Uganda.The objectives are threefold: - identify climatic shocks faced by the local communities; examine the perceptions of men and women of climate variability and change; and to compare their perceptions with empirical meteorological data. This study employed both qualitative and quantitative methods, with data collected from 215 respondents using survey, interviews and focused group discussions. From the findings, indicators of climate variability and change included reduced flooding events, occurrence of human diseases, increasing crop pests and diseases, dry spells and intensity of rains. There was increasing significant temperatures while rainfall was declining. Both male and female significantly associated with increasing temperatures and reduced flooding events. While climatic shocks affected both males and females, the impact was more pronounced depending on distinct livelihood activities and roles and responsibilities undertaken. The study concluded that people’s perceptions of climate change should be taken on by the government and integrated in the national climate programs that support people’s livelihoods and survival mechanisms.

scholarly journals Improved large-scale hydrological modelling through the assimilation of streamflow and downscaled satellite soil moisture observations

2015 ◽  
Vol 12 (10) ◽  
pp. 10559-10601 ◽  
Author(s):  
P. Lopez Lopez ◽  
N. Wanders ◽  
J. Schellekens ◽  
L. J. Renzullo ◽  
E. H. Sutanudjaja ◽  
...  
Keyword(s):  
Soil Moisture ◽  
High Resolution ◽  
Data Assimilation ◽  
Spatial Resolution ◽  
Large Scale ◽  
Hydrological Model ◽  
Meteorological Data ◽  
Added Value ◽  
Coarse Resolution ◽  
The Impact

Abstract. The coarse spatial resolution of global hydrological models (typically > 0.25°) limits their ability to resolve key water balance processes for many river basins and thus compromises their suitability for water resources management, especially when compared to locally-tuned river models. A possible solution to the problem may be to drive the coarse resolution models with locally available high spatial resolution meteorological data as well as to assimilate ground-based and remotely-sensed observations of key water cycle variables. While this would improve the resolution of the global model, the impact of prediction accuracy remains largely an open question. In this study we investigate the impact of assimilating streamflow and satellite soil moisture observations on the accuracy of global hydrological model estimations, when driven by either coarse- or high-resolution meteorological observations in the Murrumbidgee river basin in Australia. To this end, a 0.08° resolution version of the PCR-GLOBWB global hydrological model is forced with downscaled global meteorological data (from 0.5° downscaled to 0.08° resolution) obtained from the WATCH Forcing Data methodology applied to ERA-Interim (WFDEI) and a local high resolution gauging station based gridded dataset (0.05°). Downscaled satellite derived soil moisture (from approx. 0.5° downscaled to 0.08° resolution) from AMSR-E and streamflow observations collected from 23 gauging stations are assimilated using an ensemble Kalman filter. Several scenarios are analysed to explore the added value of data assimilation considering both local and global meteorological data. Results show that the assimilation of soil moisture observations results in the largest improvement of the model estimates of streamflow. The joint assimilation of both streamflow and downscaled soil moisture observations leads to further improvement in streamflow simulations (20 % reduction in RMSE). Furthermore, results show that the added contribution of data assimilation, for both soil moisture and streamflow, is more pronounced when the global meteorological data are used to force the models. This is caused by the higher uncertainty and coarser resolution of the global forcing. We conclude that it is possible to improve PCR-GLOBWB simulations forced by coarse resolution meteorological data with assimilation of downscaled spaceborne soil moisture and streamflow observations. These improved model results are close to the ones from a local model forced with local meteorological data. These findings are important in light of the efforts that are currently done to go to global hyper-resolution modelling and can help to advance this research.

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