Variation In Climatic Variables Research Articles

Vineyard Microclimatic Zoning as a Tool to Promote Sustainable Viticulture under Climate Change

Understanding microclimate spatial variability is crucial for sustainable and optimised grape production within vineyard plots. By employing a combination of a microclimate model (NicheMapR) and multiple climate data sources, this study aimed to achieve microclimatic analysis in two vineyard plots, Quinta do Bomfim (northern Portugal) and Herdade do Esporão (southern Portugal). This approach provides an innovative 10 m spatial resolution for climate variables. This study incorporated local station hourly data with quantile mapping bias correction on the ERA5-land data. The microclimate model output was employed to perform bias correction on a EURO-CORDEX model ensemble. Climate extreme and bioclimatic indices specifically targeted to viticulture were calculated for each vineyard plot. The 10 m scale was analysed to identify potential shifts in temperature extremes, precipitation patterns, and other crucial climatic variables for grape cultivation within each specific plot. The significance of microclimate analyses was higher in areas with intricate topography, while in areas with smooth slopes, the variation of climatic variables was determined to be negligible. There was a projected increase in the median temperature of approximately 3.5 °C and 3.6 °C and a decrease in precipitation of approximately 98 mm and 105 mm in Quinta do Bomfim and Herdade do Esporão, respectively, when comparing a future scenario for the period 2071–2100 against the historical period (1981–2010). Hence, this study offers a comprehensive and future-oriented method for analysing microclimates in vineyard plots. By incorporating geospatial data, ERA5-land data, and the microclimate NicheMapR model, this research aimed to enhance the understanding of current microclimates and future climate scenarios for viticulturists.

The impact of climate change on the Palestinian sectoral reallocation of labor

ABSTRACT The research leverages yearly variations in climate variables, such as rainfall and temperature, across the West Bank from 1999 to 2018 to assess their influence on individuals’ decisions to stay in the agricultural sector. The main findings suggest that an increase in rainfall in the previous year is associated with a higher proportion of workers in the agricultural sector, especially in regions where agriculture is the primary economic activity. Temperature variation is also an important factor. An increase in the maximum temperature will generally have a negative effect on the supply of labor in the agricultural sector, while an increase in the minimum temperature may have a positive effect. However, this effect varies across different regions of the West Bank, reflecting the diverse agricultural practices and irrigation methods employed. The study also examines two potential mechanisms through which climate change affects labor decisions: agricultural labor migration to the Israeli labor market and how climate shocks affect agricultural wages.

Analysis of Climate Variable and Fisherman Perception on Climate Change Divers in Negombo Lagoon Area


 
 
 Climate change has undoubtedly become one of the most contentious issues in the international environmental debates and has escalated the impacts on fishery industries and fishing communities globally. This study was conducted to quantify the variations in climate variables, and coastal vegetation that may affect the fisheries industry due to climate change over past three decades in the Negombo lagoon area. Further, the knowledge and awareness of fisheries and associated communities on climate change was investigate. To understand the dynamics of the precipitation and temperature, monthly data for 30 years (1989-2022) were collected from the Department of Meteorology and 19 Module Bio-climatic Variables (MBV) were calculated to determine the climatologycal variation. The change in the coastal vegetation was analyzed using the Landsat 8 satellite using ArcGIS 10.8. A questionnaire survey and a focus group discussion were carried out as assess the knowledge, awareness and impact of climate change in the fisheries community (n=80). The mean annual and minimum and maximum precipitation ranged from 118.6 mm-268.6 and 0.6 mm - 826.6 mm. The mean, maximum, and minimum temperatures varied from 28.8o C- 32.3o C, 33o C-34o C and 29o C-30o C. Out of 19 MBV variables, 9 variables had increasing trends while 3 variables had decreasing trend. The change percentage of coastal vegetation cover from 1992-2002, 2002-2012, 2012-2022 was observed as 35.71%, 4.99% and 6.13%. As per the peoples‘ knowledge of climate change, it was highlighted that around 50% of respondents does not have a proper idea on what is climate change (40% of respondents stated that the variation of precipitation and wind is the climate change drivers; Further, 40% of respondents attested that land use change with time has accelerated climate change while 30% of respondents mentioned that lack of coastal awareness and restoration programs is the second main reason for accelerated climate change that affect the fishery industry). The outcomes of the focus group discussion revealed that fishing activities are heavily affected by climate change drivers, and some engage in alternative jobs in extreme climatic conditions to feed their families. Finally, fishery communities highlighted the need for the government and other responsible authorities to take necessary actions to adapt and strengthen the resilience to climate change. This study corroborates the timely and topical obligation for sustainable fisheries management action planning for the Negombo area.
 Keywords: Climate change, Coastal mangrove vegetation-precipitation-temperature change, Fisheries communities, Knowledge, Awareness, Negombo
 
 

Assessment of Changes in Climatic Variables in Hadeja-Nguru Wetlands

The study assessed the changes in climatic variables in Hadeja Nguru wetland. Parameters evaluated includes; variations in climatic variables over a 40-year window (1979-2019) Data on climatic variables on daily basis were obtained for a period 40years and Satellite imageries of the study area were officially downloaded from the United State Geological Survey website. Paired sample T-test and chi-square test of association were used in assessing the variation in climatic factors. Result showed that indicated sparse distribution as a major effect of climate change. Decreased in crops production, land shade, destruction of harvested crops, increase in insect population and shortened seed germination period were thought to be the consequences of reduction in rainfall, excessive rainfall, irregular rainfall pattern and increase in temperatures, Food scarcity, reduction in income due to depletion of crops were also pinpointed as impacts of climate change.. Maximum and minimum temperatures, precipitation, wind speed, relative humidity and solar intensity between 1979 and 2019 were 40.07 and 36.46, 1180.36mm and 58.18mm, 2.97m/s and 2.29m/s, 0.33g/kg and 0.22g/kg and 23.68w/m2 and 20.70w/m2 respectively. There was also a significant Chi-square value (33.481a) between respondents’ effect of climate change and increase in farm sizes. The paper concluded that there were fluctuations in climatic variables. There is the need to put in place right policies to protect and preserve wetlands to enhance their sustainability and resilience to climatic changes and variability.

Assessment of impact of climate change on the streamflow of Idamalayar River Basin, Kerala

Abstract This study investigates the impacts of climate change on water availability in the Idamalayar basin, Kerala. Soil and Water Assessment Tool (SWAT), Hydrologic Engineering Centre – Hydrologic Modelling System (HEC-HMS), and bias-corrected climate change data were used to simulate future streamflows. The performances of SWAT and HEC-HMS were assessed using four statistical indices (R2, Nash–Sutcliffe efficiency, percentage bias, and RSR). SWAT slightly outperformed HEC-HMS. The CMIP6 general circulation models (GCMs) were selected using PROMETHEE-2. The variations in climate variables and streamflows were studied for three future periods, i.e., near-future (2031–2040), mid-future (2051–2060), and far-future (2071–2080) under three shared socio-economic pathway (SSP) scenarios (SSP126, SSP245, and SSP585). The projections of GCMs show different patterns in variation of precipitation. Generally, there is a slight increase in annual precipitation. However, there was a notable decline in peak in July. An additional peak was often seen in October. The maximum and minimum temperatures showed a decreasing trend. The average annual streamflow reduction under SSP126 was approximately 25.63, 27.92, and 26.24% in the near, mid, and far future, respectively. Under SSP245, the average decrease was 30.71, 16.06, and 19.06% for the near, mid and far future, respectively. For SSP585, there was 12.73% increase in the far-future period.

Dynamic distribution modelling using a native invasive species, the mountain pine beetle

Efforts to minimize impacts of highly mobile insect pests in a warming environment are complicated by the dynamicity and uncertainty of their distributions. Tools that aid such management efforts are urgently required for successful outcomes. Dynamic species distribution models (DSDM) represent temporal variations in the environment that match the timing and location of species occurrence leading to improved predictions of species distributions while reducing over prediction. In contrast, static SDMs treat the environment and ecological niche of the species as essentially invariant, such as climatic data averaged over long reference periods, which can result in inaccurate assessments of a species' ecological niche. We modified the traditional static SDM framework such that it incorporates both dynamic biotic and abiotic predictors to account for temporal variability in the environment. We used the native-invasive mountain pine beetle (MPB; Dendroctonus ponderosae, Hopkins) as a model species. MPB is an irruptive forest insect native to western North America; however, epidemic populations have recently crossed the Rocky Mountains and invaded the province of Alberta, Canada, giving rise to concern that the beetle will spread into the transcontinental boreal forest. We compared the ability of static and dynamic SDMs to predict the potential distribution of MPB, including the impact of host tree availability, degree of native-novel host tree introgression and interannual variation in climatic variables. Evaluation results using independent test data revealed higher predictive capacity by DSDMs when compared with SDMs. DSDMs provided robust temporal trends of MPB potential distributions while generating predictions that support the known MPB distributional shifts. The DSDM framework will help species distribution modellers in understanding the distributional dynamics of mobile species in climatically variable regions.

Forecasting Climate Variability in Nepal

Climate variability is noted a critical issue in Nepal. This paper investigates empirically and analytically whether climate variability exists or not in different altitudes, whether its direction moves and what will be its future direction. In this study, we used a time series forecasting model based on the secondary data of hydrology and metrology collected from the Department of Hydrology and Metrology, the Government of Nepal. As a result, this paper found climate variability in the different parts of Nepal where variations of climatic variables (temperature and rainfall precipitation) are found all months of the year. In the estimation, on average temperature rising per annum is by 20 C from 1975 to 2012. However, declining rainfall per annum was noticed. Additionally, the estimated forecasting of temperature variation over the next 40 years would be 60c over. In the case of rainfall forecast, it would be constant and results from drought at high altitude and flood at low altitude. Therefore, climate variability may be a big threat in the next 40 years across the country, of Nepal. The result may be valuable input to the policymakers and farmers for economics as usual.

Climate Scenarios for Coastal Flood Vulnerability Assessments: A Case Study for the Ligurian Coastal Region

Extreme sea levels and coastal flooding are projected to be among the most uncertain and severe consequences of climate change. In response, a wide development of coastal vulnerability assessment methodologies has been observed in research to support societal resilience to future coastal flood risks. This work aims to explore the scope of application of index-based methodologies for coastal vulnerability assessment, in terms of their suitability to convey information on variations in climate variables potentially leading to sea-level changes and inundation. For this purpose, the InVEST Coastal Vulnerability model was coupled for the first time with the ERA5 reanalysis and used to develop a case study assessment of the biophysical exposure component of vulnerability to coastal flooding for Liguria, an Italian coastal region facing the Mediterranean Sea. Different scenarios of wind speed and wave power were created in order to test the sensitivity of this approach to climate data inputs. The results support the applicability of this approach to provide a preliminary grasp of local vulnerability to coastal inundation. Yet, this work also highlights how the method’s data aggregation and indicator computation processes result in its insensitivity to wind and wave variations, and therefore in its unsuitability to reproduce climate scenarios. The implications of these findings for research methodology and regarding the operationalisation of vulnerability assessment results are discussed.

STATISTICAL DOWNSCALED LOCAL CLIMATE MODEL FOR FUTURE RAINFALL CHANGES ANALYSIS: A CASE STUDY OF HYOGO PREFECTURE, JAPAN

<p>For decades, climate models have been used to understand the present and historical climates, especially global climate models (GCMs). They are used to understand the interaction between climate system processes and forecast future climates. However, the issue of low resolution and accuracy often lead to inadequacy in capturing the variations in climate variables related to impact assessment. In order to capture the local climate changes in Hyogo Prefecture of Western Japan, a local climate modelling based on Second Generation Canadian Earth System Model (CanESM2) was applied using the statistical downscaling technique. Representative Concentration Pathway (RCP) 4.5 and 8.5 scenario were used in generating future climate models. The reliability of models was tested with Linear Regression, Pearson correlation, and Cronbach Alpha. Moderate relationship between rainfall data and both RCP scenarios was found in all chosen stations. Spatial analysis outcome showed that there is a possibility of increase in annual rainfall in Hyogo prefecture, where the increase is significant in Northern region. There is a possibility of increase in maximum and minimum temperature in four selected stations due to the increase of greenhouse gas emissions.</p>

Climate change and urban flooding in South-South Nigeria from 1990 - 2020

Flooding is one of the disasters that are common in our towns and villages. It occurs as a result of heavy or continuous rainfall over a period of time. Occurrence of flood damages our valuable infrastructure such as buildings, roads, bridges, and schools, churches etc. The study area being a coastal region is confronted with frequent flooding and the extent of damage, and contributing factors has not been fully studied, particularly in applying remote sensing and geographic information system. Also, very little information is known about the combine impacts of urbanization and climate change on urban flooding in the area. Hence this study was aimed at evaluating the impact of climate change and urban development on urban flooding in South – South Nigeria using geospatial techniques. Datasets utilized for the study includes; land use/ land cover derived from Landsat satellite data, soil map, slope model, soil infiltration rate, impervious surface derived from vegetation indices, distance from river, precipitation, and surface temperature data. These datasets were processed into common coordinate system. Landsat data of four epochs (1990 – 2020) was used to map urbanization. Accordingly, the variations in climate variables were investigated using NiMET reported and the satellite derived values. Flood vulnerability zones was determined using multi-criteria analysis implemented in ArcGIS weighted overlay tool. The study observed that urbanization increases from 1990 to 2020, which also increase impervious surfaces, making the area more vulnerable to flooding. In addition, wetland and vegetation cover are being replaced by built-up thereby decreasing the ability of wetland to retained flood water. The lowest rainfall was in 1990 with value 293.70mm and the highest was in 2000 with value 454.90mm. There is general variation of rainfall and temperature from 1990 – 2020 due to climate change. Total built-up at risk was 8873.55ha with most of them situated along the river banks. Geospatial technology is suitable for urban flood vulnerability modeling. For further study, it is recommended that high spatial resolution image should be use to map trends in urbanization. In addition, drainage density should be integrated in flood vulnerability modeling.

Effects of exogenous melatonin on body mass and thermogenesis in red-backed vole (Eothenomys miletus) between Kunming and Dali regions.

Melatonin (MEL) is an indole hormone synthesized and secreted by the pineal gland at night, which is involved in the regulation of body mass and thermogenesis in small mammals. To test the effects of exogenous MEL on body mass and thermogenic ability in two different red-backed vole (Eothenomys miletus) populations from two different regions (Kunming [KM] and Dali [DL]) with different annual variation in climatic variables, such as temperature, sunshine and rainfall. we traced the changes of energy balance in E. miletus from KMand DL, which were placed at 25 ± 1°C with photoperiod of 12 L:12 D, intraperitoneal injection of MEL was performed daily for 28 days. The results showed that body mass and food intake were significantly decreased, while resting metabolic rate (RMR) and nonshivering thermogenesis (NST) were significantly increased after MEL injection; Contents of total protein, mitochondrial protein, the activities of cytochrome C oxidase (COX) and α-glycerophosphate oxidase (α-PGO) in liver and brown adipose tissue (BAT) were enhanced; the activity of thyroxin 5'-deiodinase (T4 5'-DII) and uncoupling protein 1 (UCP1) in BAT were also increased. Serum leptin, triiodothyronine (T3 ) levels and T3 /T4 ratio were significantly increased, thyroxine (T4 ) levels was significantly decreased. Moreover, body mass and food intake in E. miletus from KM were higher than those from DL, but RMR and NST were lower than those from DL. Changes of body mass, food intake and thermogenic activity of KM were higher than those of DL when exposed to injection of MEL, indicating that E. miletus in KM were more sensitive to MEL. Furthermore, MEL was involved in the regulation of body mass and thermogenesis in E. miletus between KM and DL.

Assessment of changes in climatic variables in hadeja-nguru wetlands

The study assessed the changes in climatic variables in Hadeja Nguru wetland. Parameters evaluated includes; variation in climatic variables over a 40-year window (1979-2019) Data on climatic variables on daily basis were obtained for a period 40years and Satellite imageries of the study area were officially downloaded from the United State Geological Survey website. Paired sample T-test and chi-square test of association were used in assessing the variation in climatic factors. Result showed that indicated sparse distribution as a major effect of climate change. Decreased production in crops, land shade, damaged of harvested crops, increase in insect population, shortening the time of germinating seeds were thought to be the consequences of reduction in rainfall, excessive rainfall, irregular rain pattern and increase in temperatures respectively, Food scarcity, reduction in income due to depletion of crops were also pinpointed as impacts of climate change. Information on climate change and its impact were obtained majorly from radio, while major mitigating strategy for changing climatic variables. Maximum and minimum temperatures, precipitation, wind speed, relative humidity and solar intensity between 1979 and 2019 were 40.07℃ and 36.46℃, 1180.36mm and 58.18mm, 2.97m/s and 2.29m/s, 0.33g/kg and 0.22g/kg and 23.68w/m2 and 20.70w/m2 respectively. There was also a significant Chi-square value (33.481a) between respondents’ effect of climate change and increase in farm sizes. It is therefore concluded that there has been fluctuations in climatic variables. There is the need to put in place right policies to protect and preserve wetlands to enhance their sustainability and resilience to climatic changes and variability.

Climate change impacts on staple crops: Assessment of smallholder farmers’ adaptation methods and barriers

Crops in Sub-Saharan African countries are generally more vulnerable to climate change with considerable impacts on yields. In this study, the impacts of climate change on selected root crops, cereals and vegetables were examined with the practice of adaptation as well as barriers hindering the adoption of selected adaptation options in selected farming communities in Ogun state, Nigeria. The climate dataset ranging from 1982 to 2020 and crop yield data ranging from 1996 to 2020 were used in this study. The social data was collected through a structured questionnaire administered among a total of 120 rural farmers purposively selected for the study. The data collected were analysed and presented using descriptive statistics, bivariate correlations and regression statistics. The results showed a high variation in climatic variables together with an obvious anomaly index with severity. The correlation results indicate a strong relationship between rainfall minimum/maximum temperatures and most crops, with R > 0.60, at p > 0.05. The results of multiple regression showed R2 ≤ 0.64 values for all crops at p < 0.05. This result implies that climate parameters accounted for significant percentage of the changes in yields. The results also showed low practice of adaptation among rural farmers and the major barrier hindering the practice of adaptation is lack of capital, including financial, physical, and human capital, which was responsible for 70% of the hurdles to climate change adaptation measures implementation. The key findings here are that the cropping system has been impacted by climate change and that the adaptive capacity of rural farmers in the study area is generally low. The study concludes that although climate change is obvious, there is generally a need to enhance the adaptation options available to smallholder farmers in the region.

Spatiotemporal Variability in Water-Use Efficiency in Tianshan Mountains (Xinjiang, China) and the Influencing Factors

Water-use efficiency (WUE) is a crucial physiological index in carbon–water interactions and is defined as the ratio of vegetation productivity to water loss. The variation in climatic variables and drought have the most significant effects on WUE and evapotranspiration (ET). Nevertheless, how WUE varies with climate factors and drought processes in the Tianshan Mountains (TMS) is still poorly understood. In the present work, we analyzed the spatiotemporal variations in WUE, and investigated the correlations between WUE, climate factors, and drought, in the study area. The results showed that, in the TMS during 2000–2020, annual net primary productivity (NPP) ranged from 147.9 to 189.4 gC·m−2, annual ET was in the range of 212.5–285.8 mm, and annual WUE ranged from 0.66 to 0.78 gC·kg−1·H2O. Both NPP and ET exhibited an increasing trend with some fluctuation, whereas WUE showed the opposite tendency during the study period. The obtained results demonstrated that the decrease in WUE was primarily because of the increase in ET. There were obvious differences in WUE, under different land-use types, caused by NPP and ET. However, the interannual variation in WUE showed small fluctuations and the dynamic process of WUE in each land-use type showed good consistency. Temperature and wind speed had a positive influence on WUE in the middle and eastern regions of the TMS. Precipitation also played a mainly positive role in enhancing WUE, especially on the northern slope of the TMS. There was strong spatial heterogeneity of the correlation coefficient (0.68, p &lt; 0.05) between WUE and the temperature vegetation drought index (TVDI). Moreover, the slopes of WUE and TVDI showed good consistency in terms of spatial distribution, suggesting that drought had a significant impact on ecosystem WUE. This work will enhance the understanding of WUE variation, and provide scientific evidence for water resource management and sustainable utilization in the study area.

Mexican agricultural frontier communities differ in forest dynamics with consequences for conservation and restoration

AbstractForest regrowth is key to achieve restoration commitments, but a general lack of understanding when it occurs and how long secondary forests persist hampers effective upscaling. We quantified spatiotemporal forest dynamics in a recently colonized agricultural frontier in southern Mexico, and tested how temporal variation in climate, and cross‐community variation in land ownership, land quality and accessibility affect forest disturbance, regrowth and secondary forest persistence. We consistently found more forest loss than regrowth, resulting in a net decrease of 45% forest cover (1991–2016) in the study region. Secondary forest cover remained relatively constant while secondary forest persistence increased, suggesting that farmers are moving away from shifting cultivation. Temporal variation in disturbance was explained by annual variation in climatic variables and key policy and market interventions. We found large differences in forest characteristics across communities, and these were explained by differences in land ownership and soil quality. Forests were better conserved on communal land, while secondary forest was more persistent when farms were larger and soil quality is better. At the pixel‐level both old forest and secondary forests were better represented on low‐quality lands indicating agricultural concentration on productive land. Both old forest and secondary forest were less common close to the main road, where secondary forests were also less persistent. We demonstrate the suitability of timeseries analyses to quantify forest disturbance and regrowth and we analyse drivers across time and space. Communities differ in forest dynamics, indicating different possibilities, needs and interests. We warrant that stimulating private land ownership may cause remaining forest patches to be lost and that conservation initiatives should benefit the whole community. Forest regrowth competes with agricultural production and ensuring farmers have access to restoration benefits is key to restoration success.

Exploring the links between variations in snow cover area and climatic variables in a Himalayan catchment using earth observations and CMIP6 climate change scenarios

The spatial extent of the Snow Cover Area (SCA) of the Bhagirathi River Basin (BRB) has changed in recent decades, impacting the hydrology of the region. Previous studies examining variations in SCA in the region have yet been limited to the effects of terrain variables, namely elevation, slope and aspect, without considering the influence of climate variability. This study first investigates temporal changes in SCA and Terrestrial Water Storage (TWS) in the BRB during the period 2001–2019, which were calculated using satellite images from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Gravity Recovery and Climate Experiment (GRACE), respectively, and their linkages to variation in climatic variables, and then examines how future climate change could impact on the SCA of the basin and its implications for water resources.A trend analysis revealed an increase in the SCA during the study period, correlating with an increase in precipitation and TWS over the basin. Statistically significant positive correlation were detected between the post-monsoon (r = 0.49, p < 0.05) and winter (r = 0.54, p < 0.05) SCA and precipitation, while a negative correlation was identified between SCA and Tmax during the post-monsoon (r = -0.53, p < 0.05) and winter (r = -0.69, p < 0.05) seasons. Climate change scenarios, obtained from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and downscaled over the study region, project an increase in both maximum and minimum temperature, and precipitation for the pre-monsoon and winter seasons in the 2030 s under two Shared Socio-economic Pathway (SSP) greenhouse gas (GHG) emission scenarios: SSP245 and SSP585. These scenarios, together with a Multiple-Linear Regression (MLR) model developed on the basis of the relationships identified between variations in SCA and climatic variables, indicate a reduction in the SCA at 4000 + m altitudes in all seasons under both scenarios, thereby resulting a decline in the Bhagirathi river flow in spite of a projected increase in precipitation. This study demonstrates the impact of projected changes in climate on the SCA of a Himalayan catchment, and the potential implications for regions where snowmelt is important to streamflow regimes.

Development of regional climate model for Hyogo prefecture, Japan using statistical downscaling method on CanESM2 RCP2.6, 4.5 and 8.5 scenarios

For decades, climate models have been used to understand the present and historical climates, especially global climate models (GCMs). They are used to understand the interaction between climate system processes and forecast future climates. However, the issue of low resolution and accuracy often lead to inadequacy in capturing the variations in climate variables related to impact assessment. In order to capture the local climate changes in Hyogo Prefecture, a regional climate modelling based on Second Generation Canadian Earth System Model (CanESM2) was applied using the statistical downscaling technique. Representative Concentration Pathway (RCP) 2.6, 4.5 and 8.5 were used in generating future climate models. The reliability of three models was tested with linear regression, Pearson correlation, probability density function (PDF) and Cronbach Alpha. A moderate relationship between rainfall data and RCP4.5 was found in all chosen stations. Spatial analysis outcome showed that there is a possibility of decreased annual rainfall in the North-eastern (which city/town) and South-western (which city/town?) regions in Hyogo Prefecture.

Analysis of long term trends of rainfall and temperature of Andit tid watershed, central highland of Ethiopia

The impacts of climate change and climate variability on human life led the scientific community to monitor the behavior of weather and climate variables. As a responsible body in the present study, trends and variations in climatic variables (i.e. rainfall, air temperature and soil temperature) were analyzed on monthly, seasonal (Belg, summer, spring and winter) and annual time scales for Andit tid watershed, central highland of Ethiopia. This was done using non-parametric statistical techniques, i.e. the Mann–Kendall (MK), over a period of 24 years. To detect the inhomogeneity of the data, autocorrelation has been taken into account using the Hamed and Rao method. The trend analysis revealed that monthly, seasonal and annual rainfall did show statistically insignificant decreasing trend at (P&lt;0.05) level of significant. Annually, noticeable trend increase was found in maximum air temperature and noticeable decrease in minimum air temperature from the non-parametric statistical tests at a (P&lt;0.05) level of significance. With this circumstance, the mean temperature showed insignificant increasing trend at (P&lt;0.05). This type of analysis of several climatic variables at watershed level is helpful for the planning and management of water resources and the development of adaptation strategies in adverse climatic conditions.

Seasonal variability in multimedia transport and fate of benzo[a]pyrene (BaP) affected by climatic factors

The impact of meteorological factors on the transport behavior and distribution of volatile and semi-volatile organic pollutants has become an area of increasing concern. Here, we analyzed seasonal variation in climatic variables including wind, temperature, and precipitation to quantitatively assess the impact of these factors on the multimedia transport and fate of BaP in the continental region of China using a Berkeley-Trent (BETR) model. The advective rates of air exhibited an increasing trend of autumn (1.830 mol/h) < summer (1.975 mol/h) < winter (2.053 mol/h) < spring (2.405 mol/h) in association with increasing wind speed, indicating that lower atmospheric BaP concentrations are present in regions with high wind speeds and advective rates. The air-soil transport rates (0.08–45.55 mol/h) in winter were higher than in summer (0.07–32.41 mol/h), while low winter temperatures accelerate BaP accumulation in terrestrial ecosystems due to cold deposition. Cold deposition effects were more evident in northern regions than in southern regions. Further, increasing precipitation enhanced air-soil and soil-freshwater transport rates with the correlation coefficients of r = 0.445 and r = 0.598 respectively, while decreasing the air-vegetation transport rates (r = 0.475), thereby contributing to the accumulation of BaP in soils and freshwaters. In the light of the potential dispersion of BaP pollution at regional and global scales affected by these key climatic factors, this indirectly indicated the impact of future climate change on the BaP transport. Thus, flexible policy interventions should be enacted to slow future climate change.

Determination of intraspecific variation in seed weight, leaf functional traits, and sapling size of Betula ermanii using a common garden experiment

ABSTRACT Habitat loss of forest tree species distributed in cold temperate and alpine zones is a serious issue in the context of global warming. Considering that intraspecific variation is essential for adaptation to changing environments, intraspecific variation in seed weight, leaf traits, and sapling size of a sub-alpine broad-leaved tree species, Betula ermanii, was examined in this study using seeds collected from 11 populations across its natural distribution. Seeds were sown in seed beds, and containerized seedlings were grown in a greenhouse with a uniform environment (a common garden experiment). The effects of four climate variables, i.e. warmth index (WI), minimum temperature of the coldest month (TMC), summer precipitation (PRS), and maximum snow depth (MSD) were evaluated on seed weight, leaf functional traits, and sapling size using a generalized linear mixed model (GLMM). Positive latitudinal clines were detected for seed weight, whereas negative clines were detected for both specific leaf area and leaf nitrogen. These clines were not consistent with the general trends observed in previous studies. The reasons might be partly explained by geographic variation in climatic variables and nutrient availability. The findings obtained from this study should be useful for conservation of mountainous forest ecosystems in the age of climate change.