Variable Climatic Conditions Research Articles

Significant Inverse Influence of Tropical Indian Ocean SST on SIF of Indian Vegetation during the Summer Monsoon Onset Phase

Sea surface temperature (SST) substantially influences the land climate conditions through the co-variability of multiple climate variables, which in turn affect the structural and functional characteristics of terrestrial vegetation. Our study explored the varying responses of vegetation photosynthesis in India to the SST variations in the tropical Indian Ocean during the summer monsoon. To characterise the terrestrial photosynthetic activity, we used solar-induced chlorophyll fluorescence (SIF). Our results demonstrated a significant negative SST-SIF relationship during the onset phase of the summer monsoon: the SIF anomalies in the northern and central Indian regions decrease when strong warm SST anomalies persist in the tropical Indian Ocean. Further, SIF anomalies increase with cold anomalies of SST. However, the negative SST anomalies in the tropical Indian Ocean are less impactful on SIF anomalies relative to the positive SST anomalies. The observed statistically significant SST–SIF link is feasible through atmospheric teleconnections. During monsoon onset, positive SST anomalies in the tropical Indian Ocean favour weakened monsoon flow, decreasing moisture transport from the ocean to the Indian mainland. The resultant water deficiency, along with the high air temperature, created a stress condition and reduced the photosynthetic rate, thus demonstrating negative SIF anomalies across India. Conversely, negative SST anomalies strengthened monsoon winds in the onset period and increased moisture availability across India. Negative air temperature anomalies also dampen water stress conditions and increased photosynthetic activity, resulting in positive SIF anomalies. The identified SST-SIF relationship would be beneficial to generate a simple framework that aids in the detection of the probable impact on vegetation growth across India associated with the rapidly varying climate conditions in the Indian Ocean.

Westerly-monsoon variations since the last deglaciation from semi-arid Ladakh region, Trans Himalaya, India

The semi-arid Ladakh region in the Trans Himalaya forms an environmental boundary between North Atlantic and monsoon forcings. Its location in the transient setting of these two climate systems enables to attest slight changes in the dynamics of these components of atmospheric circulation. Variation in climatic conditions from 19.6 to 6.1 ka using multi-proxy investigation (mineral magnetism, stable carbon isotope, palaeoprecipitation, sediment grainsize end member analysis, clay mineralogy and TOC) is studied from Khalsi palaeolake deposit in Ladakh. Considering the inherent uncertainty of radiocarbon chronology, the present study provides millennial to multi-centennial scale resolution of climate variation from the sediment sequence. The results indicate cold arid climate influenced by Westerly circulation for the last 19.6 to 11.1 ka, thereafter from 11.1 to 7.5 ka, monsoon forcings dominated the climate of the region, following the orbitally controlled solar insolation that influenced the position of ITCZ and formed the key driver of the variability of these atmospheric circulations. A short wet phase from ∼17.4 to 16.5 ka within the dominant Westerly period is attributed to the early wet phase of two-fold H1 event. Westerly regained strength from 7.5 to 6.1 ka during the mid-Holocene coinciding with decreasing insolation, weakening monsoon and enhanced El Niño activities.

GR2L: A robust dual-layer green roof water balance model to assess multifunctionality aspects under climate variability

Urban blue-green infrastructures (BGIs) fulfill a variety of functions that enable cities to cope with climate change and additional urban anthropogenic pressures such as increasing population density, heat island effects, biodiversity loss, and progressive sealing of permeable surfaces. In the urban water cycle, BGIs can play an important role when it comes to both managing and mitigating the direct effects of ever-increasing periods of extended drought as well as the temporary excess of stormwater during and after heavy rainfall events. Although BGIs are multifunctional in principle, the individual infrastructure has to be designed and operated toward achieving a set of specific objectives, e.g., stormwater retention, infiltration, or storage for increased overall water resilience. In this study, we focus on green roofs as a key BGI for water resilient urban spaces. Green roofs have the advantage of unlocking underutilized roof space for urban water management and additional co-functions, avoiding additional urban land use conflicts at ground level. Green roofs are available in a multitude of design types based on the selection of vegetation, the make and thickness of the substrate layer, and the absence or presence of additional retention space. With GR2L, we present a robust dual-layer green roof water balance model that is able to cope with a variety of design aspects and was validated and calibrated using a data set of four green roof types with varying technical specifications and different vegetation cover. We used the calibrated models to assess how different green roof types operate under variable climatic conditions using meteo ensembles that consist of dry and wet years as well as a suite of randomly selected years. Calibration results indicate that a green roof factor (based on the classic crop factor) largely depending on the retention capacity of green roofs, makes the results widely applicable in planning. The results provide information on how green roof designs can be optimized for fulfilling a given set of water balance-driven multifunctionality objectives under varying climatic conditions and enabling an assessment of the performance of existing green roof designs against these conditions.

Herbs-derived phytochemicals - a boon for combating COVID-19.

The online version contains supplementary material available at 10.1007/s42535-023-00601-9.

Impact of regional climate change on the mosquito vector Aedes albopictus in a tropical island environment: La Réunion

The recent expansion of Aedes albopictus across continents in both tropical and temperate regions and the exponential growth of dengue cases over the past 50 years represent a significant risk to human health. Although climate change is not the only factor responsible for the increase and spread of dengue cases worldwide, it might increase the risk of disease transmission at global and regional scale. Here we show that regional and local variations in climate can induce differential impacts on the abundance of Ae. albopictus. We use the instructive example of Réunion Island with its varied climatic and environmental conditions and benefiting from the availability of meteorological, climatic, entomological and epidemiological data. Temperature and precipitation data based on regional climate model simulations (3 km × 3 km) are used as inputs to a mosquito population model for three different climate emission scenarios. Our objective is to study the impact of climate change on the life cycle dynamics of Ae. albopictus in the 2070–2100 time horizon. Our results show the joint influence of temperature and precipitation on Ae. albopictus abundance as a function of elevation and geographical subregion. At low-elevations areas, decreasing precipitation is expected to have a negative impact on environmental carrying capacity and, consequently, on Ae. albopictus abundance. At mid- and high-elevations, decreasing precipitation is expected to be counterbalanced by a significant warming, leading to faster development rates at all life stages, and consequently increasing the abundance of this important dengue vector in 2070–2100.

Performance Analysis of Precipitation Datasets at Multiple Spatio-Temporal Scales over Dense Gauge Network in Mountainous Domain of Tajikistan, Central Asia

Cryospheric and ecological studies become very complicated due to the absence of observed data, particularly in the mountainous regions of Central Asia. Performance analysis of Satellite-Based Precipitation Datasets (SBPD) is very critical before their direct hydro-climatic applications. This study assessed the ground validation of four SBPDs (IMERG, TRMM, PERSIANN-CDR, and PERSIANN-CSS). From January 2000 to December 2013, all SBPD data were analyzed on daily, monthly, seasonal (winter, spring, summer, autumn), and annual scales at the entire spatial domain and point-to-pixel scale. The performance of SBPD was analyzed by using evaluation indices (root mean square error (RMSE), correlation coefficient (CC), bias, and relative bias (r-Bias)) along with categorical indices (false alarm ratio (FAR), probability of detection (POD), success ratio (SR), and critical success index (CSI). Results revealed that: (1) IMERG’s spatiotemporal tracking ability is better as compared to other datasets with appropriate ranges (CC > 0.8 and r-BIAS (±10)). The performance of all SBPDs is more capable on a monthly scale as compared to a daily scale. (2) In terms of POD, the IMERG outperformed all other SBPD on daily and seasonal scales. All SBPD showed underestimations in the summer season, and PERSIANN-CCS showed the most significant underestimation (−70). Moreover, the IMERG signposted the most satisfactory performance in all seasons. (3) All SBPD showed better performance in capturing the light precipitation events as indicated by the Probability Density Function (PDF%). Moreover, the performance of PERSIANN-CDR and TRMM is acceptable at low topography; the performance of PERSIANN-CCS is very poor in diverse topographical and climatic conditions over Tajikistan. Therefore, we advocate the use of daily, monthly, and seasonal estimations of IMERG precipitation product for hydro-climatic applications over the mountainous domain of Central Asia.

The Impacts of Interannual Climate Variability on the Declining Trend in Terrestrial Water Storage over the Tigris–Euphrates River Basin

Abstract The Tigris–Euphrates dryland river basin has experienced a declining trend in terrestrial water storage (TWS) from April 2002 to June 2017. Using satellite observations and a process-based land surface model, we find that climate variations and direct human interventions explain ∼61% (−0.57 mm month−1) and ∼39% (−0.36 mm month−1) of the negative trend, respectively. We further disaggregate the effects of climate variations and find that interannual climate variability contributes substantially (−0.27 mm month−1) to the negative TWS trend, slightly greater than the decadal climate change (−0.25 mm month−1). Interannual climate variability affects TWS mainly through the nonlinear relationship between monthly TWS dynamics and aridity. Slow recovery of TWS during short wetting periods does not compensate for rapid depletion of TWS through transpiration during prolonged drying periods. Despite enhanced water stress, the dryland ecosystems show slightly enhanced resilience to water stress through greater partitioning of evapotranspiration into transpiration and weak surface “greening” effects. However, the dryland ecosystems are vulnerable to drought impacts. The basin shows straining ecosystem functioning after experiencing a severe drought event. In addition, after the onset of the drought, the dryland ecosystem becomes more sensitive to variations in climate conditions. Significance Statement The purpose of the research is to better understand climate impacts on terrestrial water storage over dryland regions with declining water storage. In our study, we disaggregate three components of climate impacts, namely, decadal climate change, interannual variability, and intra-annual variability. We then use observational datasets and a process-based model to quantify their individual effects on water storage. We find that interannual variability is the most significant climatic contributor to the declining water storage, mainly caused by prolonged drought periods and corresponding quick drying rates due to plant transpiration. We also find that the dryland ecosystem is sensitive and vulnerable to severe drought events. This study is important because 1) it provides a framework to investigate climate impacts on water fluxes and storages, 2) it highlights the importance of vegetation dynamics on dryland hydrology, and 3) it emphasizes the negative impacts of extreme hydroclimatological events on ecosystem functioning.

Machine‐Learning Reveals Equifinality in Drivers of Stream DOC Concentration at Continental Scales

AbstractResearch at long‐term catchment monitoring sites has generated a great volume, variety, and velocity of data for analysis of stream water chemistry dynamics. To harness the potential of these big data and extract patterns that are indicative of underlying functional relationships, machine learning tools have advantages over traditional statistical methods, and are increasingly being applied for dimension reduction, feature extraction, and trend identification. Still, as examples of complex systems, catchments are characterized by multivariate factor interactions and equifinality that are not easily identified by most machine‐learning methods. Using dissolved organic carbon (DOC) dynamics as an illustration, we applied a new evolutionary algorithm (EA) to extract geologic, topographic, meteorologic, hydrologic, and land use attributes that were correlated to mean stream DOC concentration in forested catchments distributed across the continental United States. The EA reduced dimensionality of our attribute dataset to identify the combination of factors, and their specific value ranges, that interacted to drive membership in High or Low mean DOC clusters. High mean DOC concentrations were associated with two distinct geographic locations of variable climatic and vegetative conditions, indicating equifinality. Our findings underscore the importance of critical zone structure in mediating hydrological and biogeochemical processes to govern DOC dynamics at the catchment scale. This multi‐scale, pattern‐to‐process approach is being applied to refine hypotheses for process‐based modeling of DOC dynamics in forested headwater streams at catchment to site scales.

Life-cycle traits in the demosponge Hymeniacidon perlevis in a land-based fish farm.

The demosponge Hymeniacidon perlevis is characterized by wide geographic distribution and great adaptability to numerous and highly variable climatic and hydrological conditions. Indeed, the species can colonize many different environments, including several unusual ones, such as concrete drainage conduits of a marine land-based fish farm plant. This research aimed to enhance existing knowledge on the reproductive cycle and growth performance of H. perlevis while also evaluating the impact of a controlled supply of trophic resources, wastewater flow and constant water temperature on these biological traits. Specimens included in this one-year study inhabited drainage conduits of a land-based fish farm. The approach included measurements of sponge biomass and occurrence and abundance of reproductive elements across different seasons and environmental parameters, such as fish biomass, trophic resources, and wastewater flow. Sponge growth and reproductive elements, including oocytes, spermatic cysts, and embryos, were measured monthly in sponges positioned in the drainage conduit, thus with different trophic resources but with constant water temperature. Finally, we used generalized additive models to describe variables that contribute the most to the growth of sponges. Growth performance showed marked variations during the study period. The highest increase in sponge volume was observed from August/September to January/March. The volume of sponges was principally determined by the reduction of reared fish biomass and the increase of pellet amount and wastewater flow. Sponge specimens exhibited an active state during the entire study, as proven by the occurrence of recruits. However, sexual elements were only sporadically observed, thus not permitting the recognition of a true sexual cycle. The results of the present study confirmed that H. perlevis exhibits high flexibility and adaptability to the differential, and somewhat extreme, environmental conditions. Indeed, this species can live, grow and reproduce in the drainage conduits of the fish farm, where the species face constant darkness, water temperature and continuous nutritional supply. In such conditions, H. perlevis display an active state during the entire year, while avoiding stages of decline and long dormancy usually observed in wild populations. It seems plausible that stable environmental conditions induce an almost continuous sexual phase, probably under the control of endogenous factors. No asexual elements were detected, although it was impossible to exclude the contribution of asexual reproduction in the origin of the newly settled sponges, which were repeatedly detected throughout the study. The growth performance seemed linked to the fish farm conditions, thus providing useful indications on the best maintenance conditions for H. perlevis in land-based integrated multitrophic systems, where the species could be used for wastewater treatment.

Environment and Culture: Adaptations that have Shaped Nepal

Nepal has a wide variety of environmental conditions owing to its unique geographical position, wide ranging altitude (59 m to 8848.86 m), and diverse climatic conditions. To adapt to such environmental conditions, different cultural practices have been adopted; specific cultures enabled harmonization with the environment. In this study, I have discussed how different cultural practices came into being because of diverse environmental conditions in Nepal. I have shed light on select cultural practices of different ethnic groups enabling adaptation to the environment. Conversely, I have also provided instances of how cultural practices have shaped the environment settings. To undertake this study, I have employed literature review on ecological anthropology of Nepal. Key Informant Interviews and observations have further complemented the study. The study helps to understand the prominent role of environmental conditions in shaping cultural practice in Nepal. This informs the cultural resilience that Nepalese society have exhibited over time and provides an appreciation of environmental cultural relations.

High-frequency time series comparison of Sentinel-1 and Sentinel-2 satellites for mapping open and vegetated water across the United States (2017–2021)

Frequent observations of surface water at fine spatial scales will provide critical data to support the management of aquatic habitat, flood risk and water quality. Sentinel-1 and Sentinel-2 satellites can provide such observations, but algorithms are still needed that perform well across diverse climate and vegetation conditions. We developed surface inundation algorithms for Sentinel-1 and Sentinel-2, respectively, at 12 sites across the conterminous United States (CONUS), covering a total of >536,000 km2 and representing diverse hydrologic and vegetation landscapes. Each scene in the 5-year (2017–2021) time series was classified into open water, vegetated water, and non-water at 20 m resolution using variables from Sentinel-1 and Sentinel-2, as well as variables derived from topographic and weather datasets. The Sentinel-1 algorithm was developed distinct from the Sentinel-2 model to explore if and where the two time series could potentially be integrated into a single high-frequency time series. Within each model, open water and vegetated water (vegetated palustrine, lacustrine, and riverine wetlands) classes were mapped. The models were validated using imagery from WorldView and PlanetScope. Classification accuracy for open water was high across the 5-year period, with an omission and commission error of only 3.1% and 0.9% for the Sentinel-1 algorithm and 3.1% and 0.5% for the Sentinel-2 algorithm, respectively. Vegetated water accuracy was lower, as expected given that the class represents mixed pixels. The Sentinel-2 algorithm showed higher accuracy (10.7% omission and 7.9% commission error) relative to the Sentinel-1 algorithm (28.4% omission and 16.0% commission error). Patterns over time in the proportion of area mapped as open or vegetated water by the Sentinel-1 and Sentinel-2 algorithms were charted and correlated for a subset of all 12 sites. Our results showed that the Sentinel-1 and Sentinel-2 algorithm open water time series can be integrated at all 12 sites to improve the temporal resolution, but sensor-specific differences, such as sensitivity to vegetation structure versus pixel color, complicate the data integration for mixed-pixel, vegetated water. The methods developed here provide inundation at 5-day (Sentinel-2 algorithm) and 12-day (Sentinel-1 algorithm) time steps to improve our understanding of the short- and long-term response of surface water to climate and land use drivers in different ecoregions.

Novel Lines of Research on the Environmental and Human Health Impacts of Nut Consumption

Nuts have formed part of human diets throughout the ages. In recent decades, research has shown they are key foods in dietary patterns associated with lower chronic disease risk. The current state of climate change, however, has introduced an imperative to review the impact of dietary patterns on the environment with a shift to plant-based diets. Nuts emerge as a significant source of protein in plant-based diets and are a minimally processed and sustainable food. Research in this area is evolving to drive better production methods in varying climate conditions. Nevertheless, nut consumption remains an important contributor to human health. The mechanisms of action can be explained in terms of the nutrients they deliver. Studies of nut consumption have linked components such as monounsaturated fatty acids, plant omega-3 fatty acids, antioxidants, and plant sterols to improved lipoprotein profiles, lower blood pressure, and reduced cardiovascular disease risk. Preliminary research also indicates possible beneficial effects of nut consumption on reproductive health. In any case, the ultimate effects of foods on health are the results of multiple interactive factors, so where nuts fit within dietary patterns is a significant consideration for research translation. This has implications for research methodologies, including categorization within food groups and inclusion in Healthy Dietary Indices. The aim of this narrative review is to outline new focal points for investigation that examine the environmental and some novel human health impacts of nut consumption and discuss future directions for research.

Short-Term PV Power Forecasting Using a Hybrid TVF-EMD-ELM Strategy

This paper discusses the efficient implementation of a new hybrid approach to forecasting short-term PV power production for four different PV plants in Algeria. The developed model incorporates a time-varying filter-empirical mode decomposition (TVF-EMD) and an extreme learning machine (ELM) as an essence regression. The TVF-EMD technique is used to deal with the fluctuation of PV power data by splitting it into a series of more stable and constant subseries. The specified set of features (intrinsic mode functions (IMFs)) is utilized for training and improving our forecasting extreme learning machine model. The adjusted ELM model is used to evaluate prediction efficiency. The suggested TVF-EMD-ELM model is assessed and verified in various Algerian locations with varying climate conditions. In all examined regions, the TVF-EMD-ELM model generates less than 4% error in terms of normalized root mean square error (nRMSE).

Estimation of evapotranspiration in constructed wetlands under diverse climatic conditions.

Constructed wetlands as a form of phytoremediation have proven to be an effective wastewater treatment method. It is a simple, economical, and environmentally friendly method compared to conventional wastewater treatments. In addition to wastewater treatment, constructed wetlands have been used to study hydrometeorological parameters such as evaporation in the vicinity, evapotranspiration (ET), and wastewater loss at a constructed wetland pilot plant at the Uttarakhand Jal Nigam sewage treatment plant at Haridwar. The relation between standard pan evaporation (PE) and ET occurring at the surface of a wetland bed was established at the constructed wetland site. To make the process of measuring ET easier, the relation between PE and ET has been established by the equation [Formula: see text]. The percent loss of water through ET vis-à-vis PE during the summer, post-monsoon, and winter seasons has been estimated to be 21.6%, 6.47%, and 1.16%, respectively. The quantity of wastewater lost in the summer, post-monsoon, and winter seasons was 53.06 m3, 13.87 m3, and 2.79 m3, respectively. The total annual wastewater loss through the pilot-scale constructed wetlands was 69.72 m3. The loss of wastewater per square meter of the planned area of constructed wetland in the temperate zone was estimated as 3.46 m3 per m2 of constructed wetland. ET through wetlands enhanced the circulation of water in the hydrological cycle; therefore, this treatment has been proven to be an environmentally friendly method of wastewater treatment.

From meteorological to agricultural drought: Propagation time and probabilistic linkages

Study regionYangtze River Basin, China Study focusAs agricultural drought originates from meteorological drought, exploring the propagation from meteorological to agricultural drought is an important step in providing early warning of agricultural drought. In this study, Standardized Precipitation Index (SPI) and Improved Soil Moisture Anomaly Percentage Index (ISMAPI) were adopted to indicate meteorological and agricultural droughts, respectively. The propagation time from meteorological drought to agricultural drought was identified, and probabilistic linkages between the two types of drought were investigated using the copula function and Bayesian network. New hydrological insightsThe average propagation time from meteorological to agricultural drought in the Yangtze River Basin (YRB) is 48 d. The propagation times in the summer and autumn are shorter than those in the spring and winter. The occurrence probability of more serious agricultural drought gradually increases with meteorological drought intensity. Agricultural and meteorological drought events were matched using the proposed drought event-matching method. In the YRB, approximately 72.4% of meteorological drought events may translate into agricultural drought events. Generally, an agricultural drought event that has the same drought category as that of the given meteorological drought event is most likely to occur. Regional differences in drought propagation time and occurrence probability of agricultural drought may be related to variations in climatic conditions across regions.

Geochemistry and organic petrography of the Middle Permian Lucaogou alkaline lacustrine oil shale in the southern Junggar Basin, China: Implications for formation conditions and organic matter accumulation

Organic matter (OM) accumulation in terrestrial sediments shows not only a significant carbon sink in the Earth's carbon cycle but an important origin of fossil fuels, which is closely associated with the complex and diverse depositional environments and climate conditions. The Junggar Basin developed the most laterally extensive and thickest alkaline lacustrine sediments as well as the richest hydrocarbon source rock/oil shale interval of all the world during the deposition of the Lucaogou Formation and equivalent units. In this study, the sedimentary succession of 564 m with a mudstone and dolomite matrix of the Lucaogou oil shale from the Qi 1 well located in the southern Junggar Basin was investigated, which can be divided into two members based on lithology. This paper is a synthetic use of major element oxides, trace, and rare-earth elements as well as organic petrography data as proxies to evaluate the provenance, paleotectonic setting, paleoclimate and weathering conditions, paleoenvironment, and paleoproductivity as well as origin and accumulation of OM of the Lucaogou sediments.It is suggested that no recycling sediments in all the studied samples, based on parameters including the Th/Sc vs. Zr/Sc plot, the Chemical Index of Alteration (CIA) being linearly dependent on Weathering Index of Parker (WIP), and the high Index of Compositional Variability. The provenance mainly from intermediate-felsic volcanic rocks (e.g., granodiorite, andesite and dacite) is supported by the bivariate plots of Euanom vs. Th/Sc, La/Th vs. Hf, La/Sc vs. Co/Th, Cr/Th vs. Sc/Th, Y/Ni vs. Cr/V, and Nb/Y vs. Zr/TiO2 as well as triangular diagrams of mafic–felsic–weathering, M+–4Si–R2+ and Rb/V–Zr/Zn–Sc/Nb. The continental island arc is inferred from paleotectonic setting discrimination diagrams (i.e., the La–Th–Sc, Th–Co–Zr/10 and Th–Sc–Zr/10 ternary as well as Ti/Zr vs. La/Sc binary diagrams). The chemical weathering indices (i.e., the CIA, WIP, weathering index (W), Weathering Intensity Scale, Sodium Depletion Index, and Ga/Rb vs. K2O/Al2O3 binary diagram) indicate the paleoclimate conditions were cold/arid with weak chemical weathering in a warming and/or enhanced continental weathering episode. Besides, the Sr/Ba ratios and gallium concentrations indicate the paleosalinity was brackish to hypersaline and was higher in the lower member in relation to that in the upper member. However, the suboxic environment of the benthic water (inferred from the MoEF vs. UEF co-variations and Corg/P ratios as well as large sizes of framboidal pyrites) and the moderate paleoproductivity (evaluated via the Sibio, Babio, and Pbio values, as well as Ni/Al and Cu/Al ratios) caused by predominate algae and bacteria (inferred from the organic petrography) kept stable in the paleolake during this period. The OM accumulation was mainly controlled by the preservation conditions rather than the paleoproductivity and limited detrital inputs/low deposition rates, which was indicated by the plot of Co × Mn values vs. Cd/Mo ratios and the total organic carbon contents being negatively related to stable carbon isotope compositions of OM.

Genome-wide association analysis for drought tolerance and associated traits in faba bean (Vicia faba L.).

Faba bean (Vicia faba L.) is an important high protein legume adapted to diverse climatic conditions with multiple benefits for the overall sustainability of the cropping systems. Plant-based protein demand is being expanded and faba bean is a good candidate to cover this need. However, the crop is very sensitive to abiotic stresses, especially drought, which severely affects faba bean yield and development worldwide. Therefore, identifying genes associated with drought stress tolerance is a major challenge in faba bean breeding. Although the faba bean response to drought stress has been widely studied, the molecular approaches to improve drought tolerance in this crop are still limited. Here we built on recent genomic advances such as the development of the first high-density SNP genotyping array, to conduct a genome-wide association study (GWAS) using thousands of genetic polymorphisms throughout the entire faba bean genome. A worldwide collection of 100 faba bean accessions was grown under control and drought conditions and 10 morphological, phenological and physiological traits were evaluated to identify single nucleotide polymorphism (SNP) markers associated with drought tolerance. We identified 29 SNP markers significantly correlated with these traits under drought stress conditions. The flanking sequences were blasted to the Medicago truncatula reference genomes in order to annotate potential candidate genes underlying the causal variants. Three of the SNPs for chlorophyll content after the stress, correspond to uncharacterized proteins indicating the presence of novel genes associated with drought tolerance in faba bean. The significance of stress-inducible signal transducers provides valuable information on the possible mechanisms underlying the faba bean response to drought stress, thus providing a foundation for future marker-assisted breeding in the crop.

Impact of Chill and Heat Exposures under Diverse Climatic Conditions on Peach and Nectarine Flowering Phenology.

The present study aims to generalize cultivar-specific tree phenology responses to winter and spring temperatures and assess the effectiveness of the Tabuenca test and various chill and heat accumulation models in predicting bloom dates for a wide range of climatic conditions and years. To this end, we estimated the dates of rest completion and blooming and correlated them with observed bloom dates for 14 peach and nectarine cultivars that were evaluated in 11 locations across Europe (Greece, France, Italy, Romania and Spain), within the EUFRIN cultivar testing trial network. Chill accumulation varied considerably among the studied sites, ranging from 45 Chill Portions (CP) in Murcia-Torre Pacheco (Spain) to 97-98 CP in Cuneo (Italy) and Bucharest (Romania). Rest completion occurred latest or was not achieved at all for some cultivars in the southern sites in Murcia. Dormancy release happened earliest in Bucharest and Cuneo, sites where heat accumulation had a strong influence on the regulation of bloom time. Blooming occurred earliest in the moderately cold regions of Lleida (Spain) and Bellegarde (France), and 7-11 days later in the warmer locations of Rome (Italy) and Naoussa (Greece), suggesting that bloom timing is strongly influenced by delayed rest completion in these locations. The Dynamic Model resulted in both more homogeneous chill accumulation across years and better predictions of bloom dates, compared with the Utah, Positive Utah and Chilling Hours models. Prediction of bloom dates was less successful for low-chill cultivars than for medium- and high-chill cultivars. Further climatic and experimental data are needed to make estimates of the climatic needs of peach cultivars more robust and to generate reliable advice for enhancing the resilience of peach production under varying and changing climatic conditions.

Sedimentological and Geochemical Study of Foundation Zone Sediment at Baiji City, North Iraq

The study includes grain size analysis, clay minerals, selected heavy metals, total dissolved solids and chemical properties. The grain size analyses of (78) samples indicate that the upper layers of the floodplain are fine where the lower layers are coarser. The identification of abundance clay minerals are; Kaolinite, Montmorilonite, Illite, Chlorite and Palygorskite. The (pH) of the sediments ranged (7.07–7.33) with average (7.22), the values of (EC) ranged (1.71-6.42) with average (3.45) and the variation may be due to the variation of climate conditions, while the sulfates SO3 between (0.256% –8.985%) with average (1.70), and that may due to presence of primary or secondary gypsum. The (T.S.S) ranged between (0.490%–12.550%) with average (3.42) and organic content range between (0.342%–3.272%) with average (1.55).
 The concentrations of Co, Zn, Sr, Ni, Pb, and Cd in (ppm), indicate that Co, Zn, and Ni elements are higher than the standards in the earth crust while the others within the limits of the earth crust or less than that.

Climate-induced migration among maize farmers in Ghana: A reality or an illusion?

Studies on climate change-migration nexus have generally assumed that all climatic conditions trigger migration in the same direction without a differentiated understanding of which conditions drive migration of rural farmers or otherwise. This study examines climate change-migration nexus in Ghana by using data collected from 500 maize farmers. Observed errors in the data were corrected through a propensity score matching (PSM) technique. Location was endogenously related to migration, with the unobserved errors corrected by implementing a two-stage Heckit probit model. The results show that drought and decrease in rainfall are climatic conditions likely to trigger migration. However, floods and decline in soil fertility are less likely to induce migration. Also, farming experience, access to credit, participation in climate-smart agriculture training, access to extension services, and information from extension agents influenced the present location of maize farmers. These push factors identified were corroborated in focus group discussions. The study recommends that policymakers, development partners, and other relevant stakeholders should first understand and appreciate the deafferented roles of diverse climatic conditions on migrations, and then support farmers to adopt appropriate long-term climate change adaptation strategies to address perennial climatic factors that affect livelihoods. While doing so, short-term measures such as scaling up access to climate services should be devised to adapt to climate change.