Search Results (302)

Extreme precipitation events severely impact agriculture, reducing yields and land use efficiency. The spatiotemporal distribution of Total Column Water Vapor (TCWV), the primary gaseous form of water, directly influences sustainable agricultural management. This study, through multi-source data fusion, employs methods including the Mann–Kendall test, sliding change-point detection, wavelet transform, pixel-scale trend estimation, and linear regression to analyze the spatiotemporal dynamics of global TCWV from 1959 to 2023 and its impacts on agricultural systems, surpassing the limitations of single-method approaches. Results reveal a global TCWV increase of 0.0168 kg/m²/year from 1959–2023, with a pivotal shift in 2002 amplifying changes, notably in tropical regions (e.g., Amazon, Congo Basins, Southeast Asia) where cumulative increases exceeded 2 kg/m² since 2000, while mid-to-high latitudes remained stable and polar regions showed minimal content. These dynamics escalate weather risks, impacting sustainable agricultural management with irrigation and crop adaptation. To enhance prediction accuracy, we propose a novel hybrid model combining wavelet transform with LSTM, TCN, and GRU deep learning models, substantially improving multidimensional feature extraction and nonstationary trend capture. Comparative analysis shows that WT-TCN performs the best (MAE = 0.170, R² = 0.953), demonstrating its potential for addressing climate change uncertainties. These findings provide valuable applications for precision agriculture, sustainable water resource management, and disaster early warning. Full article

Leptospirosis is a globally significant zoonosis affecting animal health, productivity, and the environment. While typically associated with tropical climates, its persistence in semi-arid regions such as La Laguna, Mexico—characterized by low humidity, high temperatures, and limited water sources—remains poorly understood. Although these adverse environmental conditions theoretically limit the survival of Leptospira, high livestock density and synanthropic reservoirs (e.g., rodents) may compensate, facilitating transmission. In this cross-sectional study, blood sera from 445 dairy cows (28 herds: 12 intensive [MI], 16 semi-intensive [MSI] systems) were analyzed via microscopic agglutination testing (MAT) against 10 pathogenic serovars. Urine samples were cultured for active Leptospira detection. Risk factors were assessed through epidemiological surveys and multivariable analysis. This study revealed an overall apparent seroprevalence of 27.0% (95% CI: 22.8–31.1), with significantly higher rates in MSI (54.1%) versus MI (12.2%) herds (p < 0.001) and an estimated true seroprevalence of 56.3% (95% CI: 50.2–62.1) in MSI and 13.1% (95% CI: 8.5–18.7) in MI herds (p < 0.001). The Sejroe serogroup was isolated from urine in both systems, confirming active circulation. In MI herds, rodent presence (OR: 3.6; 95% CI: 1.6–7.9) was identified as a risk factor for Leptospira seropositivity, while first-trimester abortions (OR:10.1; 95% CI: 4.2–24.2) were significantly associated with infection. In MSI herds, risk factors associated with Leptospira seropositivity included co-occurrence with hens (OR: 2.8; 95% CI: 1.5–5.3) and natural breeding (OR: 2.0; 95% CI: 1.1–3.9), whereas mastitis/agalactiae (OR: 2.8; 95% CI: 1.5–5.2) represented a clinical outcome associated with seropositivity. Despite semi-arid conditions, Leptospira maintains transmission in La Laguna, particularly in semi-intensive systems. The coexistence of adapted (Sejroe) and incidental serogroups underscores the need for targeted interventions, such as rodent control in MI systems and poultry management in MSI systems, to mitigate both zoonotic and economic impacts. Full article

Cancer disparities in low- and middle-income countries (LMICs) arise from multifaceted interactions between environmental exposures, infectious agents, and systemic inequities, such as limited access to care. The exposome, a framework encompassing the totality of non-genetic exposures throughout life, offers a powerful lens for understanding these disparities. In LMICs, populations are disproportionately affected by air and water pollution, occupational hazards, and oncogenic infections, including human papillomavirus (HPV), hepatitis B virus (HBV), Helicobacter pylori (H. pylori), human immunodeficiency virus (HIV), and neglected tropical diseases, such as schistosomiasis. These infectious agents contribute to increased cancer susceptibility and poor outcomes, particularly in immunocompromised individuals. Moreover, climate change, food insecurity, and barriers to healthcare access exacerbate these risks. This review adopts a population-level exposome approach to explore how environmental and infectious exposures intersect with genetic, epigenetic, and immune mechanisms to influence cancer incidence and progression in LMICs. We highlight the critical pathways linking chronic exposure and inflammation to tumor development and evaluate strategies such as HPV and HBV vaccination, antiretroviral therapy, and environmental regulation. Special attention is given to tools such as exposome-wide association studies (ExWASs), which offer promise for exposure surveillance, early detection, and public health policy. By integrating exposomic insights into national health systems, especially in regions such as sub-Saharan Africa (SSA) and South Asia, LMICs can advance equitable cancer prevention and control strategies. A holistic, exposome-informed strategy is essential for reducing global cancer disparities and improving outcomes in vulnerable populations. Full article

Turbidity is a crucial parameter for assessing the ecological health of aquatic ecosystems, particularly in shallow tropical lakes that are subject to climatic variability and anthropogenic pressures. Lake Chapala, the largest freshwater body in Mexico, has experienced persistent turbidity and sediment influx since the 1970s, primarily due to upstream erosion and reduced water inflow. In this study, we utilized Landsat satellite imagery in conjunction with near-synchronous in situ reflectance measurements to monitor spatial and seasonal turbidity patterns between 2023 and 2025. The surface reflectance was radiometrically corrected and validated using spectroradiometer data collected across eight sampling sites in the eastern sector of the lake, the area where the highest rates of horizontal change in turbidity occur. Based on the relationship between near-infrared reflectance and field turbidity, second-order polynomial models were developed for spring, fall, and the composite annual model. The annual model demonstrated acceptable performance (R² = 0.72), effectively capturing the spatial variability and temporal dynamics of the average annual turbidity for the whole lake. Historical turbidity data (2000–2018) and a particular case study in 2016 were used as a reference for statistical validation, confirming the model’s applicability under varying hydrological conditions. Our findings underscore the utility of empirical remote-sensing models, supported by field validation, for cost-effective and scalable turbidity monitoring in dynamic tropical lakes with limited monitoring infrastructure. Full article

Ochroma lagopus, a fast-growing tropical tree species, faces fertilization challenges due to slope heterogeneity in plantations. This study examined 3-year-old Ochroma lagopus at upper and lower slope positions under five treatments: CK (no fertilizer), F1 (600 g/plant), F2 (800 g/plant), F3 (1000 g/plant), and F4 (1200 g/plant) of secondary macronutrient water-soluble fertilizer. Growth parameters and N-P-K stoichiometry were analyzed. Key results: (1) Height increased continuously with fertilizer dosage at both slopes, while DBH peaked and then declined. (2) At upper slopes (nutrient-poor soil), fertilization elevated leaf P but reduced branch N/K and increased root P/K. At lower slopes (nutrient-rich soil), late-stage leaf N increased significantly, with roots accumulating P/K via a “storage strategy”. Stoichiometric thresholds indicated N-K co-limitation (early-mid stage) shifting to P limitation (late stage) on upper slopes and persistent N-K co-limitation on lower slopes. (3) PCA identified F4 (1200 g/plant) and F1 (600 g/plant) as optimal for upper and lower slopes, respectively. This research provides a theoretical basis for precision fertilization in Ochroma lagopus plantations, emphasizing slope-specific nutrient status and element interactions for dosage optimization. Full article

Eutrophication has intensified in lacustrine systems across the American continent, which has been primarily driven by human activities such as intensive agriculture, wastewater discharge, and land-use change. This phenomenon adversely affects water quality, biodiversity, and ecosystem functioning. However, studies addressing the historical evolution of trophic states in lakes and reservoirs remain limited—particularly in tropical and subtropical regions. In this context, sedimentary records serve as invaluable archives for reconstructing the environmental history of water bodies. Paleolimnological approaches enable the development of robust chronologies to further analyze physical, geochemical, and biological proxies to infer long-term changes in primary productivity and trophic status. This review synthesizes the main methodologies used in paleolimnological research focused on trophic state reconstruction with particular attention to the utility of proxies such as fossil pigments, diatoms, chironomids, and elemental geochemistry. It further underscores the need to broaden spatial research coverage, fostering interdisciplinary integration and the use of emerging tools such as sedimentary DNA among others. High-resolution temporal records are critical for disentangling natural variability from anthropogenically induced changes, providing essential evidence to inform science-based lake management and restoration strategies under anthropogenic and climate pressures. Full article

Global climate change has increased the frequency of compound drought–heatwave events (CDHEs), seriously threatening tropical forest ecosystems. However, due to the complex structure of natural tropical forests, related research remains limited. To address this, we focused on rubber plantations on Hainan Island, which have simpler structures, to explore the impacts of CDHEs on their primary productivity. We used Pearson and Spearman correlation analyses to select the optimal combination of drought and heatwave indices. Then, we constructed a Compound Drought–Heatwave Index (CDHI) using Copula functions to describe the temporal patterns of CDHEs. Finally, we applied a Bayes–Copula conditional probability model to estimate the probability of GPP loss under CDHE conditions. The main findings are as follows: (1) The Standardized Precipitation Evapotranspiration Index (SPEI-3) and Standardized Temperature Index (STI-1) formed the best index combination. (2) The CDHI successfully identified typical CDHEs in 2001, 2003–2005, 2010, 2015–2016, and 2020. (3) Temporally, CDHEs significantly increased the probability of GPP loss in April and May (0.58 and 0.64, respectively), while the rainy season showed a reverse trend due to water buffering (lowest in October, at 0.19). (4) Spatially, the northwest region showed higher GPP loss probabilities, likely due to topographic uplift. This study reveals how tropical plantations respond to compound climate extremes and provides theoretical support for the monitoring and management of tropical ecosystems. Full article

Climate models often face challenges in accurately simulating the daily precipitation cycle over tropical land areas, particularly in the Amazon. One contributing factor may be the incomplete representation of the diurnal evolution of shallow cumulus (ShCu) clouds. This study aimed to enhance the understanding of the diurnal cycles of ShCu clouds—from formation to maturation and dissipation—over the Central Amazon (CAMZ). Using observational data from the Green Ocean Amazon 2014 (GoAmazon) campaign and large eddy simulation (LES) modeling, we analyzed the diurnal cycles of six selected pure ShCu cases and their composite behavior. Our results revealed a well-defined cycle, with cloud formation occurring between 10 and 11 local time (LT), maturity from 13 to 15 LT, and dissipation by 17–18 LT. The vertical extent of the liquid water mixing ratio and the intensity of the updraft mass flux were closely associated with increases in turbulent kinetic energy (TKE), enhanced buoyancy flux within the cloud layer, and reduced large-scale subsidence. We further analyzed the diurnal cycles of the convective available potential energy (CAPE), the convective inhibition (CIN), the Bowen ratio (BR), and the vertically integrated TKE in the mixed layer (ITKE-ML), exploring their relationships with the cloud base mass flux (Mb) and cloud depth across the six ShCu cases. ITKE-ML and Mb exhibited similar diurnal trends, peaking at approximately 14–15 LT. However, no consistent relationships were found between CAPE (or BR) and Mb. Similarly, comparisons of the cloud depth with CAPE, BR, ITKE-ML, CIN, and Mb revealed no clear relationships. Smaller ShCu clouds were sometimes linked to higher CAPE and lower CIN. It is important to emphasize that these findings are preliminary and based on a limited sample of ShCu cases. Further research involving an expanded dataset and more detailed analyses of the TKE budget and synoptic conditions is necessary. Such efforts would yield a more comprehensive understanding of the factors influencing ShCu clouds’ vertical development. Full article

Water is scarce in semi-arid regions due to environmental limitations; this situation is aggravated by changes in land use and land cover (LULC). In this respect, the basic ecological functions of Permanent Preservation Areas (PPAs) help to maintain water resources. The aim of this study was to evaluate the relationship between the LULC and water quality in PPAs in a semi-arid watershed, from 2009 to 2016. The following limnological data were analyzed: chlorophyll-a, transparency, total nitrogen and total phosphorus. The changes in LULC were obtained by classifying images from Landsat 5, 7 and 8 into three types: Open Dry Tropical Forest (ODTF), Dense Dry Tropical Forest (DDTF) and Exposed Soil (ES). Spearman correlation and principal component analysis were applied to evaluate the relationships between the parameters. There was a significant positive correlation between DDTF and the best limnological conditions. However, ES showed a significant negative relationship with transparency and a positive relationship with chlorophyll-a, indicating a greater input of sediments and nutrients into the water. The PCA corroborated the results of the correlation. It is therefore essential to prioritize the preservation and restoration of the vegetation in these sensitive areas to ensure the sustainability of water resources. Future studies should assess the impact of specific human activities, such as agriculture, deforestation and livestock farming, on water quality in the PPAs. Full article

Natural wetlands are critical water quality regulators, especially in developing tropical countries. The Lubigi wetland is a large urban wetland in Kampala, the largest city in Uganda in Africa. We studied whether stormwater discharge and wastewater effluent from a nearby stormwater channel and a sewage treatment plant in the western part of the city were cleaned as they flowed through the wetland. Despite the significant pollution, the wetland removed ammonium-nitrogen, orthophosphate, and particulate nutrients during both seasons, achieving removal rates ranging from 50 to 60% for orthophosphate but only 20–40% for ammonium-nitrogen. Overall, seasonal differences in loads and retention rates of nutrient and organic matter inputs were minimal. Interestingly, the wetland mostly released nitrate and nitrite during water passage through the wetland, most likely due to the mineralization of organic nitrogen and agricultural run-off during rainy events in the wet season. However, the limited capacity of the sewage treatment plant and untreated stormwater discharge from the Nsooba main channel reduced the wetland’s ability to clean water. The insufficient carrying capacity of the treatment plant and the release of untreated sewage into the wetland significantly impact the self-purification capacity of the Lubigi wetland. Thus, the concept of Nature-Based Solutions is ineffective if the wetland systems are overloaded. Full article

Solar-powered pumping systems using series pumps are commonly applied in the delivery of water to remote agricultural regions, particularly in hilly tropical terrain. The synchronization of these pumps typically depends on reliable communication; however, dense vegetation, elevation changes, and weather conditions often disrupt signals. To address these limitations, a fully decentralized, communication-free control system is proposed. Each pumping station operates independently while maintaining synchronized operation through emulated neighbor sensing. The system applies a discrete-time control algorithm with virtual sensing that estimates neighboring pump statuses. Each station consists of a solar photovoltaic (PV) array, variable-speed drive, variable inlet valve, reserve tank, and local control unit. The controller adjusts the valve positions and pump power based on real-time water level measurements and virtual neighbor sensing. The simulation results across four scenarios, including clear sky, cloudy conditions, temporary outage, and varied irradiance, demonstrated steady-state operation with no water overflow or shortage and a steady-state error less than 4% for 3 m³ transfer. The error decreased as the average power increased. The proposed method maintained system functionality under simulated power outage and variable irradiance, confirming its suitability for remote agricultural areas where communication infrastructure is limited. Full article

Understanding the seasonal regulation of transpiration and stomatal conductance is critical for evaluating plant water-use strategies in response to environmental variability. This study assessed these physiological traits in three dominant savanna tree species (Piliostigma thonningii (Schumach.) Milne-Redh., Combretum molle R.Br. ex G.Don, and Balanites aegyptiaca (L.) Delile) in Ruma National Park, Kenya. Measurements were taken during wet and dry seasons under varying canopy light conditions (light-exposed vs. shaded leaves) and soil moisture regimes. A randomized design with four treatments and three replicates was employed. Results showed significantly higher transpiration and stomatal conductance during wet seasons, especially in sunlit leaves (p < 0.05). P. thonningii exhibited the highest rates of transpiration (9 mmol m⁻² s⁻¹) and stomatal conductance (~2.2 mmol m⁻² s⁻¹) in light conditions, while B. aegyptiaca maintained consistently low values, reflecting a drought-tolerant strategy. C. molle demonstrated intermediate responses, suggesting a balance between water conservation and resource use. Despite seasonal trends, low R² values indicated that internal physiological regulation outweighed the influence of external climatic drivers. These findings reveal species-specific water-use strategies and highlight the ecological significance of leaf-level responses to light and moisture availability in tropical savannas. The study provides valuable insights for forest management and climate-resilient restoration planning in water-limited ecosystems. Full article

Microplastics (MPs), defined as synthetic polymer particles less than 5 mm in diameter, are widely acknowledged as ubiquitous contaminants in aquatic ecosystems, including freshwater, marine, and polar environments. Global concern with MPs has significantly increased; nevertheless, much of the current knowledge remains fragmented and, at times, limited to specific regions or ecological compartments. This study emphasizes the necessity of a thorough synthesis by critically analyzing global microplastics’ dispersion patterns, ecological consequences, and associated human health concerns. A systematic approach was employed, integrating specific search terms and establishing inclusion and exclusion criteria across various scientific databases to obtain a representative collection of literature. The study covers important topics such as the classification of MPs, their distribution, environmental impacts, and interactions with other pollutants, including heavy metals, pharmaceuticals and endocrine-disrupting chemicals. Particular emphasis is placed on comparing ecosystem-specific vulnerabilities, such as those found in tropical wetlands, marine gyres, and polar systems. The review examines potential human exposure pathways, via contaminated seafood, water, and air, while also compiling new information about cellular and physiological damage, including oxidative stress, inflammation, hormone disruption, and possible genetic effects. This investigation highlights the value of collaborative monitoring, the adoption of biodegradable alternatives, policy development, and interdisciplinary research by integrating knowledge from ecology and public health. The primary objective is to advance ecosystem-specific mitigation techniques and promote evidence-based policy development in addressing this intricate environmental issue. Full article

Understanding how land use and climate change jointly affect water availability is essential for sustainable planning in tropical Andean–Amazonian basins. This study focuses on the Utcubamba River Basin in northeastern Peru, a data-scarce and socioecologically strategic watershed where land transformation and climate variability converge. A multi-temporal land use/land cover (LULC) analysis (1990–2024) was conducted, coupled with hydrological modeling using the SWAT model under historical and future climate scenarios (SSP2–4.5 and SSP5–8.5), including the spatial overlay of the LULC change concentration with key hydrological indicators. LULC classifications revealed forest loss and the expansion of pasture, agriculture, and shrubland areas, particularly in the upper basin. Hydrological projections showed significant changes in water flow, including reductions in minimum monthly flows by up to 73.9% and increases in peak flows by 14.8% under the SSP5–8.5 scenario. The water balance is expected to shift, with increased percolation and reduced lateral flow, suggesting decreased storage capacity. By identifying critical sub-basins where land degradation and water insecurity converge, the study supports adaptive strategies for land restoration, aquifer recharge planning, and ecosystem conservation. Despite limited hydrological infrastructure, the SWAT model effectively simulated water dynamics, aiding climate resilience and water security efforts in the Amazonian Andes. Full article

Flood hazards and their disastrous consequences disrupt economic activity and threaten human lives globally. From a remote sensing perspective, since floods are often triggered by extreme climatic events, such as heavy rainstorms or tropical cyclones, the efficacy of using optical remote sensing data for disaster and damage mapping is significantly compromised. In many flood events, obtaining cloud-free images covering the affected area remains challenging. Nonetheless, considering that floods are the most frequent type of natural disaster on Earth, optical remote sensing data should be fully exploited. In this article, firstly, we will present a critical review of remote sensing data and machine learning methods for global flood-induced damage detection and mapping. We will primarily consider two types of remote sensing data: moderate-resolution multi-spectral data and high-resolution true-color or panchromatic data. Big and semantic databases available for advanced machine learning to date will be introduced. We will develop a set of best-use case scenarios for using these two data types to conduct water-body and built-up area mapping with no to moderate cloud coverage. We will cross-verify traditional machine learning and current deep learning methods and provide both benchmark databases and algorithms for the research community. Last, with this suite of data and algorithms, we will demonstrate the development of a cloud-computing-supported computing gateway, which houses the services of both our remote-sensing-based machine learning engine and a web-based user interface. Under this gateway, optical satellite data will be retrieved based on a global flood alerting system. Near-real-time pre- and post-event flood analytics are then showcased for end-user decision-making, providing insights such as the extent of severely flooded areas, an estimated number of affected buildings, and spatial trends of damage. In summary, this paper’s novel contributions include (1) a critical synthesis of operational readiness in flood mapping, (2) a multi-sensor-aware review of optical limitations, (3) the deployment of a lightweight ML pipeline for near-real-time mapping, and (4) a proposal of the GloFIM platform for field-level disaster support. Full article