Rainy Period Research Articles

A Study on the Construction and Evaluation of the Water Resource Reutilization System for Farmland Diversion and Drainage

Water is an essential resource for both rural and agricultural areas; it can be wisely distributed and used in the field to protect daily life, production, the natural environment, and the safety and stability of regional drainage and flood control systems. Our research selected a typical plains rural river network area with agriculture as the main industry to investigate the most effective method of farmland diversion and drainage. We comprehensively planned and transformed the water system flow, water conservation engineering, and the ecological environment in the irrigation area through the reutilization system. The reutilization system’s operation and scheduling design is implemented for four specific periods: the water replenishment cycle, agricultural irrigation, agricultural drainage and the rainy period of the flood season. The research period ranges from 2020 to 2023 after the completion of the system. We used monitoring, the recording of hydraulic equipment parameters and data collection to evaluate the balance of water supply and demand in the study area. At the same time, we have tracked and evaluated the four aspects of water quality enhancement, water conservation and flood control, and agricultural irrigation. The results show that the total agricultural water consumption decreased by 2.9%, and the amount of water saved increased by 9.6%. The current segment creates the rivers’ embankment standards. With a 92% irrigation guarantee rate, the current section forms and the embankment standards of the rivers satisfy the design storage volume and the flood level of one in twenty years. The water quality of all the rivers in the area has decreased by 5~10% compared to the average concentration prior to establishment. This study verifies the comprehensive effect and the suitability of the system by comparing the before and after effects, and provides a scientific basis for the method of efficient recycling and utilization of water resources in the rural plains river network area; we also propose the guidance of increasing the digital twin control and long-term operation mechanism to ensure the long-term stable operation of the technology.

Pesticides in surface and groundwater in three micro-basins of the São Lourenço River, state of Mato Grosso, Brazil: grab and passive sampling

ABSTRACT This study aimed to assess the occurrence of pesticides in São Lourenço River basin, next to soybean, corn and cotton plantation, using complementarily grab and passive sampling techniques. São Lourenço River is an important affluent of Paraguay River which run to the Pantanal, the greatest wetland in the world with high environmental importance to the region. Methods for determining pesticides retained in the solid phase of passive samples and grab samples were developed and validated, which showed good precision and accuracy for the determination of 30 and 34 pesticides, respectively. A total of 72 surface and 55 groundwater samples using grab sampling and 137 surface water passive samples using POCIS were collected over a 1-year period. Pesticides atrazine, azoxystrobin, carbendazim, carbofuran, cyproconazole, clomazone, chlorantraniliprole, chlorpyrifos, difenoconazole, malathion, and metolachlor were detected in the three types of samples. Eleven pesticides were detected at concentrations ranging from 0.0132 to 1.31 µg L−1 for grab samples (surface waters), 0.0132 to 0.986 µg L−1 in shallow groundwater and 0.0011 a 0.204 µg L−1 in surface waters using passive samplers. The passive sampling technique applied to surface water confirmed the presence of the 15 analytes detected by grab sampling, allowed the identification of another 7 pesticides which were not detected in grab samples, and increased the incidence of detection of the analytes. While at least one pesticide was detected in 34% of grab samples, in the POCIS samplers the detection frequency was 95%. POCIS also provided a better temporal understanding of contamination levels showing that the higher detections and concentrations occurred in the rainy period and the period of more intensive application. Therefore, passive sampling showed to be highly effective for detecting pesticides at low concentrations as a complement to grab sampling, indicating that the joint use of both sampling strategies provides consistent monitoring data.

Groundwater quality evaluation of the weathering mantle in crystalline basement aquifer system, southern Brazil.

Groundwater is the main source of water for more than 2 billion people worldwide. In southern Brazil, the Crystalline Basement Aquifer System is composed of strategic groundwater reservoirs. Groundwater is mostly taken from shallow wells, and it is often used without any treatment, which poses a risk to public health. The present study aims to evaluate shallow groundwater quality and the geochemistry of shallow and deep groundwater located in the municipality of Canguçu, southern Brazil. The physicochemical and microbiological parameters of groundwater samples collected from shallow wells were monitored and analyzed using ANOVA variance analysis and water quality index (CCME WQI) approaches. Also, the results were compared with secondary data from deep wells. The monitored shallow wells had thermotolerant coliforms, Escherichia coli, pH, potassium, manganese, iron, and nitrate in disagreement with the guidelines of the World Health Organization. Moreover, variance analysis showed that the parameters temperature, dissolved oxygen, pH, chloride, and magnesium were the most influenced by seasonal variations. According to the CCME WQI, most samples had good quality (60%), 28% had fair quality, and 12% had poor quality. In addition, the field campaigns with higher precipitation rates also presented fair quality. Therefore, most of the shallow groundwater quality is affected by surface pollutants from the urban area, aggravated in rainy periods. Whereas deep groundwater is influenced by geochemistry mechanisms. The results revealed the risk of water consumption for public health and the urgent need for better maintenance of these wells and water treatment implementation.

Factores que afectan la tasa de gestación con embriones cebú producidos in vitro en trópico

Objective. To study the factors affecting the success of embryo transfers (ET). Materials and methods. 1087 ET in zebu cattle were analyzed. The considered extrinsic factors of the donor cows were the cattle production unit from which they were sourced (n=13), amount of transfers in the unit (1 time, >1 time), geographical zone (n=4), period (dry or rainy) and year season; and the intrinsic factors were the breed of the bull and DC, semen, embryo quality and embryo developmental stage. Statistics were compiled with ci2 for the analysis of the main effects, and correlations were estimated through a multivariate clustering analysis. Results. The general pregnancy rate was 37.99±1.47, and there were differences (p<0.05) observed among the CPU (2.78–75%). The PR was higher in the dry than in the rainy period (44.55 vs 31.28%), and in fall and winter (p<0.05) than spring and summer (42.76, 43.98, 37.57 and 29.77%, respectively), and there were differences observed between the geographical zones as well (p<0.05). The PR was higher with excellent-quality embryos (p<0.05) than with good-quality embryos (38.9 vs. 26.3%). The period and year season had an effect over the RC (p<0.05), and the grouping analysis showed a correlation (r>0.90) between the period and year season during Oocyte pick-up (OPU) over the PR; moreover, semen, EQ and EDS had larger associations with the PR (r>0.80). Conclusions. Environmental conditions at the moment of OPU and EQ are factors worth considering in embryo transfer programs with zebu cattle using in vitro produced embryos in tropical conditions.

The role of the environment and connectivity on multiple facets of local fish diversity in tropical headwater streams

Abstract The identification of multiple facets of biodiversity (e.g., phylogenetic and functional) can help to understand how evolutionary and ecological mechanisms shape the assembly of biological communities. Here, we employed multiple regressions and variance partitions to investigate the effects of environmental conditions, connectivity and space on aspects of the functional and phylogenetic facets of fish fauna in tropical headwater streams of the Xingu River basin, in Eastern Amazonia. We found that the functional and phylogenetic diversities of fish communities are related to local environmental conditions and stream connectivity in the drainage network, with marked differences occurring between the rainy and dry periods. Furthermore, we discovered that functional uniqueness was influenced mainly by environmental factors, whereas phylogenetic uniqueness had a more complex relationship with the influence of local environmental factors and connectivity. Our findings indicate that the fish assemblages of small headwater streams of the Xingu River basin share a close phylogenetic history. This is probably because of the climatic and environmental stability experienced by Amazonian ichthyofauna over evolutionary time. Our findings emphasise the role of niche‐based processes in shaping the unique functional composition of fish assemblages in headwater streams, and highlight the importance of environmental heterogeneity in maintaining the ecological integrity of these freshwater ecosystems.

Outbreak of Alternaria Black Spot of Pomegranate (Punica granatum L.) in Italy as a Consequence of Unusual Climatic Conditions.

Alternaria black spot of pomegranate (Punica granatum) was reported for the first time in Italy. In spring 2023, an outbreak of this disease was noticed in commercial pomegranate 'Wonderful' orchards of the municipality of Misterbianco (Sicily), following an unusually rainy period. A total of 30 randomly selected Alternaria isolates recovered from typical necrotic spots of leaves and fruits were characterized. Based on the colony morphology on solid agar media (PDA and MEA), isolates were separated into three distinct morphotypes (1, 2, and 3). The first two morphotypes comprised only isolates from fruits, while morphotype 3 comprised only isolates from leaves. Multigene phylogenetic analysis of four DNA regions, including internal transcribed spacer (ITS), translation elongation factor 1-α (EF-1α), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), and a SCAR marker (OPA10-2), identified the isolates of morphotypes 1 and 2 as Alternaria alternata and morphotype 3 isolates as A. arborescens. In pathogenicity tests on unwounded leaves and fruit, the isolates of all three morphotypes produced symptoms on the leaves of three pomegranate cultivars, 'Acco', 'Wonderful', and 'Etna'. The symptoms on 'Acco' leaves were the least severe. Conversely, the fruits of 'Acco' were the most susceptible. The isolates of morphotypes 2 and 3 were not pathogenic on the fruits of 'Wonderful' and 'Etna'. This is the first report of Alternaria black spot in Italy and of A. arborescens associated with Alternaria black spot of pomegranate worldwide.

Leptoglossus occidentalis Heidemann, 1910 (Hemiptera Coreidae) in Türkiye Its distribution, life cycle, and fungal associations

In this study, the distribution, life cycle and associations with fungi of the alien invasive species Leptoglossus occidentalis Heidemann, 1910 (Hemiptera: Coreidae) in Türkiye were investigated. During the study between 2019 and 2021, we found that the pest has spread almost all over Türkiye. We recorded the presence of the species in 35 provinces. The biological data obtained in the study were divided into ecologically similar sub-regions (Ankara-Çankırı-Kırşehir, Artvin, Isparta-Burdur, Izmir-Aydın-Manisa-Muğla-Antalya) in order to reveal the life cycle of the species. Additionally, host plant and insect samples were examined for the presence of Diplodia sapinea (Fr.) Fuckel (pine shoot blight agent) and entomopathogenic fungi species through morphological and molecular identification methods. Consequently, we found that L. occidentalis has two generations in Türkiye. Timing of the first flight was in early May-mid June and the second generation was from mid-July to late August. Although D. sapinea was detected in some of the sampled host plant tissues, it could not be isolated from L. occidentalis individuals. Accordingly, we did not find any evidence that L. occidentalis vectors D. sapinea although the insect and the fungus cooccurs in sampling areas. On the other hand, its vector potential cannot be ruled out especially during rainy periods. This potential remains as a hypothesis for future studies. Although we detected 25 fungal species isolated from L. occidentalis adults, none of them were entomopathogenic fungal species.

Assessment of Water Quality of the Sao Goncalo River in the Urban Section of Sao Domingos do Norte-Es

The Water Quality Index (WQI) gathers information on physical-chemical and bacteriological parameters. This article analyzed, monthly for one year, water samples collected at the source and downstream of the São Gonçalo River in the municipality of São Domingos do Norte, at Espírito Santo. The average accumulated precipitation of the month that preceded the collection was grouped into dry and rainy periods. Precipitation data allowed classification into dry and rainy periods (p-value 0.0084). The WQI values were calculated and statistically evaluated regarding the collection point and precipitation (p-value 0.0125). In dry periods, the WQI presented lower values than in rainy periods. It was observed that at the source of the river, the WQI value was higher than downstream from the urban center due to anthropological action. Finally, the research allowed the identification of the temporal and spatial variation of the water body resulting from contamination by sewage contribution.

Habitat use by a bird community in a Caatinga area: habitat seasonality and overlap

Habitat degradation is one of the main drivers of biodiversity loss, a phenomenon that significantly manifests in the Caatinga domain, where extensive habitat areas undergo modifications. Therefore, understanding how organisms select their habitats becomes crucial for effective conservation management. In this context, the present study aims to analyze habitat use, seasonality, and overlap within a bird community in an area located within the Caatinga domain, specifically at Fazenda Aba. Twelve monthly expeditions were conducted using the point-count method to estimate usage areas, habitat intensity, and overlap during both dry and rainy periods. Usage areas were measured using the Minimum Convex Polygon (MCP 100%) method, while the Kernel 95% estimator was employed to assess habitat intensity. Overlap was calculated using the Utilization Distribution Overlap Index (UDOI). The results revealed comprehensive use of the study area by the bird community, with more pronounced usage intensity in riparian forest environments. Additionally, an increase in usage areas was observed during the rainy period compared to the dry season, reflecting greater overlap during the scarcity season. It is suggested that riparian forest habitats play a fundamental role in maintaining avifauna, especially during droughts, promoting seasonal movements of species that tend to shift to areas with higher resource availability, resulting in convergence of utilized areas.

Integrating deep learning and regression models for accurate prediction of groundwater fluoride contamination in old city in Bitlis province, Eastern Anatolia Region, Türkiye

Groundwater resources in Bitlis province and its surroundings in Türkiye’s Eastern Anatolia Region are pivotal for drinking water, yet they face a significant threat from fluoride contamination, compounded by the region’s volcanic rock structure. To address this concern, fluoride levels were meticulously measured at 30 points in June 2019 dry period and September 2019 rainy period. Despite the accuracy of present measurement techniques, their time-consuming nature renders them economically unviable. Therefore, this study aims to assess the distribution of probable geogenic contamination of groundwater and develop a robust prediction model by analyzing the relationship between predictive variables and target contaminants. In this pursuit, various machine learning techniques and regression models, including Linear Regression, Random Forest, Decision Tree, K-Neighbors, and XGBoost, as well as deep learning models such as ANN, DNN, CNN, and LSTM, were employed. Elements such as aluminum (Al), boron (B), cadmium (Cd), cobalt (Co), chromium (Cr), copper (Cu), iron (Fe), manganese (Mn), nickel (Ni), phosphorus (Pb), lead (Pb), and zinc (Zn) were utilized as features to predict fluoride levels. The SelectKbest feature selection method was used to improve the accuracy of the prediction model. This method identifies important features in the dataset for different values of k and increases model efficiency. The models were able to produce more accurate predictions by selecting the most important variables. The findings highlight the superior performance of the XGBoost regressor and CNN in predicting groundwater quality, with XGBoost consistently outperforming other models, exhibiting the lowest values for evaluation metrics like mean squared error (MSE), mean absolute error (MAE), and root mean squared error (RMSE) across different k values. For instance, when considering all features, XGBoost attained an MSE of 0.07, an MAE of 0.22, an RMSE of 0.27, a MAPE of 9.25%, and an NSE of 0.75. Conversely, the Decision Tree regressor consistently displayed inferior performance, with its maximum MSE reaching 0.11 (k = 5) and maximum RMSE of 0.33 (k = 5). Furthermore, feature selection analysis revealed the consistent significance of boron (B) and cadmium (Cd) across all datasets, underscoring their pivotal roles in groundwater contamination. Notably, in the machine learning framework evaluation, the XGBoost regressor excelled in modeling both the “all” and “rainy season” datasets, while the convolutional neural network (CNN) outperformed in the “dry season” dataset. This study emphasizes the potential of XGBoost regressor and CNN for accurate groundwater quality prediction and recommends their utilization, while acknowledging the limitations of the Decision Tree Regressor.

Effects of Different Seasons on Milk Quality: A Study on Two Cattle Breeds in Rainy and Drought Contexts

The primary focus of dairy farming in the central region of Peru centers on producers. However, there is limited information on how different altitudinal zones, particularly during rainy and dry seasons, affect milk production. The present study aimed to investigate the effects of the rainy and dry seasons on the physicochemical properties of milk from Brown Swiss and Holstein cattle. A total of sixty cows were selected for the study, comprising 30 Brown Swiss and 30 Holstein. The study was conducted across two distinct seasons, including rainy and dry seasons. All animals received the same semi-intensive management and were fed ryegrass and balanced feed. Each animal provided 500 ml of milk for analysis in the morning. The milk was transported at a temperature of 2 °C, where they were analyzed with the Lactoscan equipment to evaluate protein, lactose, fat, total solids, milk density, freezing point, salts, and pH. Significant differences were observed in the interaction between Brown Swiss and Holstein breeds across different seasons, including rainy and dry periods. Significant differences were observed in protein content, showing a positive effect in the interaction “rain: Brown” a value of 3.50 ± 0.36, while “rain: Holstein” showed 3.14 ± 0.05. Statistical differences were observed in the interactions for lactose content, with rain: Brown at 4.82% and dry: Holstein at 4.37%. Similarly, there were significant differences in fat content and total solids for rain interaction of rain: Holsten, and dry: Brown. Nevertheless, no differences were observed in terms of milk density, freezing point, salts, and pH. It is concluded that there was an influence of the interaction between breed physiology and seasonal conditions on milk composition. The results also highlight the impact of season-specific environmental factors on the quality of milk.

Urea fertilization for potentializing beef cattle performance in agroforestry systems in the humid tropics

AbstractThis study hypothesized that urea fertilization could optimize animal performance in an agroforestry system. This study evaluated how increasing rates of N fertilization (0, 100, 200, and 400 kg N ha−1 year−1) using urea (CH4N2O) affected forage mass, nutritive value, and beef cattle (Bos indicus) performance in an agroforestry system with Massai grass (Megathyrsus maximus Jacq. cv. Massai) and legume tree (Mimosa caesalpiniifolia Benth.), in the humid tropic region of Brazil, over 2‐year period. The experiment was carried out in a randomized complete block design with four treatments (N fertilizer rates) and three replications. Forage mass was positive and linearly affected by N fertilization (p = .0236, R2 = 0.92), ranging from 1297 to 1583 kg DM ha−1 under 0 and 400 kg N ha−1 year−1, respectively. There was greater average forage mass during the rainy period (1826 kg ha−1) (p < .05). Crude protein in green forage mass increased linearly (p = .0041, R2 = 0.91) in function of the N applied. Cattle average daily gain showed a positive quadratic response to the rates of N applied (p = .0298, R2 = 0.97), ranging from 0.46 kg to 0.68 kg animal day−1; and the gain per area increased linearly from 1.84 to 2.68 kg LW ha−1 day−1 (p = .0640, R2 = 0.96). The findings indicate that applying 200 kg N ha−1 year−1, split‐applied during the rainy season, would yield acceptable outcomes in terms of forage mass, nutritive value, and animal performance for this type of agroforestry system.

Characterization of the Temperament and Reactivity of Nelore Cattle (Bos indicus) Associated with Behavior Scores during Corral Management in the Humid Tropics.

The evaluation of the reactivity and distress of cattle during corral management, by means of subjective scores, aims at the standardization of behavioral indicators, through non-invasive methods, in addition to enabling the development of more appropriate management practices, thus promoting the comfort and well-being of these animals. Therefore, in this study, we aimed to characterize the temperament and distress of cattle managed in a corral using behavioral indicators during the rainiest period. For this, the experiment was conducted on a property located in the municipality of Mojuí dos Campos, during the rainiest quarter (February-April). Thus, 30 male cattle, not castrated, approximately 29 months of age, clinically healthy, and weighing 310 + 20 kg, were divided into three rearing systems: silvopastoral (SP), traditional (SS), and integrated (SI) systems. There were 10 animals per system. Physiological parameters were collected to evaluate rectal temperature (RT) and respiratory rate (RR), as well as body surface temperature (BST), through thermal windows (head and flank infrared temperature and rump infrared temperature). To evaluate temperament and reactivity, scores indicative of corral behavior were used, namely escape speed (ES), tension score (SS_1), tension score (SS_2), reactivity scale (RS), movement score (MS), and temperament scale (TS). The results showed that there was a thermal amplitude of 5.9 °C on average and 8.6 °C at maximum when comparing the structure of the corral and the trees. In addition, the comparisons between the production systems for the behavioral variables did not differ at the 5% significance level, except for ES, where the traditional system differed from the integrated system and the silvopastoral system, showing intermediate average values for both. In addition, there was a positive correlation between the variables RT and RR (r = 0.72; p < 0.01), RR and SS_2 (r = 0.38; p = 0.04), flank infrared temperature and MS (r = 0.47; p = 0.01), rump infrared temperature and RS (r = 0.37; p = 0.04), SS_1 and RS (r = 0.41; p = 0.02), SS_1 and SS_2 (r = 0.39; p = 0.03), RS and SS_2 (r = 0.58; p = 0.00), RS and MS (r = 0.50; p = 0.01), RS and TS (r = 0.61; p = 0.00), SS_2 and MS (r = 0.51; p = 0.00), SS_2 and TS (r = 0.47; p = 0.01), and MS and TS (r = 0.44; p = 0.02), and a negative correlation between ES and TS (r = -0.42; p = 0.02). The rainy season had a major influence on the evaluation of temperature and distress levels during handling in the corral, as evidenced by the association between physiological and behavioral parameters.

An Iterative 3D Correction plus 2D Inversion Procedure to Remove 3D Effects from 2D ERT Data along Embankments.

This paper addresses the problem of removing 3D effects as one of the most challenging problems related to 2D electrical resistivity tomography (ERT) monitoring of embankment structures. When processing 2D ERT monitoring data measured along linear profiles, it is fundamental to estimate and correct the distortions introduced by the non-uniform 3D geometry of the embankment. Here, I adopt an iterative 3D correction plus 2D inversion procedure to correct the 3D effects and I test the validity of the proposed algorithm using both synthetic and real data. The modelled embankment is inspired by a critical section of the Parma River levee in Colorno (PR), Italy, where a permanent ERT monitoring system has been in operation since November 2018. For each model of the embankment, reference synthetic data were produced in Res2dmod and Res3dmod for the corresponding 2D and 3D models. Using the reference synthetic data, reference 3D effects were calculated to be compared with 3D effects estimated by the proposed algorithm at each iteration. The results of the synthetic tests showed that even in the absence of a priori information, the proposed algorithm for correcting 3D effects converges rapidly to ideal corrections. Having validated the proposed algorithm through synthetic tests, the method was applied to the ERT monitoring data in the study site to remove 3D effects. Two real datasets from the study site, taken after dry and rainy periods, are discussed here. The results showed that 3D effects cause about ±50% changes in the inverted resistivity images for both periods. This is a critical artifact considering that the final objective of ERT monitoring data for such studies is to produce water content maps to be integrated in alarm systems for hydrogeological risk mitigation. The proposed algorithm to remove 3D effects is thus a rapid and validated solution to satisfy near-real-time data processing and to produce reliable results.

Ecología trófica de Brycon henni (Pisces: Bryconidae) en afluentes de los Ríos Nare y Guatapé, cuenca del río Magdalena, Colombia

Understanding the trophic ecology of fish and how they use resources in space and time is important to support conservation and management actions. The trophic ecology of Brycon henni in the Nare and Guatapé rivers, Magdalena river basin, Colombia was determined. Five field samplings were carried out between October 2007 and January 2010, in rainy, dry, and dry-to-rainy transition periods. Stomachs of 262 specimens were collected. A Kruskall-Wallis analysis and a Mann-Whitney pairwise comparison test was performed to detect differences in the alimentary importance index of each food category between sex, size class, hydrological period and basins (Nare vs Guatapé). The Levin’s Measure of Niche Breadth and the Morisita’s Diet Overlapping Index were calculated to establish differences between size class in the different hydrological periods. Vegetable material was the most important food item, followed by Insecta, and fish. Individuals from Guatapé basin consumed more plant material and fish and fewer insects. We observed increased consumption of plant material and fish in ontogeny. Levin's niche breadth was lower and diet overlapping between individuals of length classes was higher during rainy period because the diet was mainly based on plant material. The diet of B. henni was composed mainly of plant material and Insects, and to a lesser extent from other groups such as fish, crustaceans and arachnids.

Enhancing water management in smart agriculture: A cloud and IoT-Based smart irrigation system

It is widely acknowledged that traditional agricultural practices must effectively address the increasing global demand for food while facing water scarcity and climate change challenges. The imperative for environmentally sustainable agricultural approaches has never been more urgent. In response, IoT-based Smart Agriculture has emerged as a promising solution. Smart Agriculture can significantly bolster agricultural development by integrating renewable energy sources, particularly in arid regions with abundant sunlight. Real-time control systems utilizing big data acquisition and processing are pivotal in this advancement. This study introduces a cloud-based smart irrigation system to connect numerous small-scale smart farms and centralize pertinent data. The system optimizes irrigation water usage through comprehensive big data collection, storage, and analysis. Leveraging the insights from this data can facilitate informed decision-making regarding water management, thereby fostering conservation efforts, particularly in arid regions. Additionally, this research explores weather prediction services to enhance irrigation control, particularly during intermittent rainy periods, within a real-world testbed powered by solar energy. The testbed incorporates a sophisticated big data management system. It showcases a Smart Farm prototype leveraging the Internet of Things, embedded systems, low-cost Wireless Sensor Networks, NI CompactRIO controller, and Cloud Computing. Encouragingly, the results demonstrate tangible improvements in water conservation. Furthermore, the deployment methodology outlined in this study provides a clear roadmap that can be readily adapted for similar research endeavors.© 2023 Elsevier Inc. All rights reserved.

Excessive Eutrophication as a Chemical Barrier for Fish Fauna Dispersion: A Case Study in the Emblematic Tietê River (São Paulo, Brazil)

The Tietê River receives most of the effluents and diffuse wastes from the São Paulo metropolis (21.9 million inhabitants). The study aimed to assess the extent to which environmental changes affected the fish fauna. We compared, in rainy and dry seasons, three sites in Tietê and three in tributaries with much better water quality conditions. No physical barriers exist between the sites. Fish were sampled with gillnets (exposed overnight) and the assemblage’s ecological attributes calculated. Water depth, transparency, temperature, electrical conductivity, dissolved oxygen, turbidity, total dissolved solids, pH, redox potential, total phosphorus, total nitrogen, and chlorophyll were simultaneously determined. Low oxygen concentrations (near zero in the rainy period), and the opposite for nutrients and total solids, separated the predominantly hypereutrophic Tietê from the tributaries (PCA). Differences in the fish assemblages were also evidenced (nMDS), including a higher richness per sample in tributaries (11 to 14 spp.) compared to Tietê (3 to 4 spp.). Siluriformes with accessory breathing dominated in Tietê and the highly tolerant detritivorous Prochilodus lineatus (the main commercial fish) was the only species found in all sites. The species correlated positively with oxygen in the tributaries and with turbidity, redox potential, and nutrients in Tietê (DistLM) (rainy season). Recovery measures are urgently required.

Seasonal Variation of VS at Shallow Depth and Nonlinear Behavior of Soil Based on the ARGONET Vertical Array Data

Ground acceleration time histories from earthquakes recorded by the ARGONET vertical array in Cephalonia, Greece, in the period from July 2016 to April 2022, are analyzed seeking evidence for nonlinear behavior of the shallow soil layers. Shear waves velocity, VS, between the shallowest sensor pair of the vertical array, i.e., within the top 5.6 m of the soil column, is derived for each earthquake record using the method of interferometry by deconvolution. The temporal variation of VS values is compared with indicators related to soil moisture and this leads to the identification of a clear difference in the level of the measured values between periods of intense rainfall and the dry summer months. Lower velocities, even lower than the level of VS during rainy periods (7-13% of the annual average), are obtained based on the strongest records of the analyzed sample. These low velocities are considered as indicators of nonlinear soil behavior, the threshold onset of which is difficult to determine without prior correction for the seasonal variation. The applied method can provide a detailed description of VS changes even during a single earthquake. Examples are provided on how nonlinear soil behavior may be manifested by a sudden VS value drop at the arrival of the strongest seismic phases.

Green Roofs on Shipping Containers: How Substrate Thickness Affects Thermal Performance

Green roofs have become a popular sustainable solution in urban areas, and in recent years, shipping containers have gained popularity as a sustainable alternative for housing. A promising proposal is to combine these two solutions. This research aims to analyze the thermal behavior of experimental modules of scale constructions. Four modules were constructed with different substrate thicknesses (4, 6, 8, and 12 cm) to verify the impact on thermal behavior and provide guidance for this technology. Additionally, another module was built without a green roof for control purposes. The indoor and outdoor air temperatures and humidities, soil moistures, and temperatures between green roof layers were recorded in a tropical climate in summer. The behavior was similar between the different thicknesses for the whole period but with significant differences in the indoor temperature amplitudes (13.8 °C for the thinner substrate, 9.7 °C for the thicker one, and 38.7 °C for the bare roof). This study also revealed considerable heat conduction between the side walls and the slab, which resulted in an upward heat flow to the substrate during a day with a clear sky, which is the opposite of what is observed in conventional roofs. During the night and rainy periods, temperatures tend to become closer between the roof’s layers when the substrate dissipates the energy absorbed throughout the day.

Survival dynamics of stick insect and the impact of environmental factors on natural fungal infection during the rainy season.

Phasmatodea, commonly known as stick insects, are recognized as noteworthy pests globally, impacting agriculture and forest ecosystems. Among them, the outbreak of Ramulus mikado has emerged as a notable concern in East Asian forests. Recently, Metarhizium phasmatodeae has been identified as utilizing stick insects as hosts. We have observed evidence of this entomopathogenic fungus infecting stick insects. Given the increase in these occurrences during the rainy period, this study investigated the relationship between the survival of R. mikado and the M. phasmatodeae infection during the rainy seasons of 2022 and 2023. We collected stick insects in two representative forests of the Republic of Korea and examined insect survival, fungal infection, and various environmental factors. No infections were detected in specimens collected in June before the rainy season, but from July onwards, both the mortality of R. mikado and the fungal infection substantially increased. By the last sampling date of each year, 75% (2022), 71.4% (2023) of the specimens were infected, and over 90% of the total individuals succumbed as a result. Fungi isolated from deceased R. mikado were successfully identified as M. phasmatodeae using morphological and taxonomic approaches. Various statistical analyses, including principal component analysis and modeling, revealed a robust association between fungal infection and the survival of stick insects. The results highlight the correlation between mass deaths of stick insects and fungal infection, particularly during the summer rainy season. These findings offer valuable insights for forecasting R. mikado population in the upcoming year and developing effective pest control strategies.