RESUMEN

This study investigated whether variations in climate and ocean drivers on global, regional, and local scales affected macrozooplankton communities in a coastal protected area in Tamandaré Bay (northeastern Brazil). For this purpose, bimonthly field campaigns were carried out from June 2013 to August 2019. A significant tipping point (point of change, p < 0.001), with an abrupt increase in SST, was detected in the TSA (Tropical South Atlantic) index. This indicates the existence of a climate regime shift in the Tropical South Atlantic during the 2015/16 El Niño (EN) event. Extreme rainfall events were observed in Tamandaré Bay after this EN event, in 2017, 2018, and in 2019 (and more recently, in 2022). This extreme rainfall led to low-salinity events, increased variability in salinity, and significantly lower abundances in the period after the strong EN event, for socioeconomically relevant penaeid shrimp postlarvae and several other zooplankton groups (e.g., copepods, appendicularians, anomuran hermit crab larvae, and chaetognaths). We found a significant relationship between SSTs in the TSA region and penaeid shrimp recruitment in the study area, located leewards of the TSA index area. The decline in shrimp postlarvae and other macrozooplankton may be due to a combination of factors, such as climate and ocean shifts (atmospheric easterly waves disturbances, winds, precipitation, salinity) and possibly increasing marine pollution (related to extreme rainfall events, that convey macro- and microplastics, and pollutants from the continent). Cnidarian medusae and fish eggs were among the few "winners" of this ecosystem regime shift. Changes in climate, ocean, macrozooplankton, and shrimp postlarvae abundance evidence a relevant climate, ocean and ecosystem regime shift in this region with a tipping point during 2015/16 "Godzilla" El Niño. Possible future consequences in the context of persistent warming in the TSA region and the currently ongoing record strength 2023/24 EN event are discussed.

RESUMEN

Climate change is no longer a hypothetical problem in the Caribbean but a new reality to which regional public health systems must adapt. One of its significant impacts is the increased transmission of infectious diseases, such as dengue fever, which is endemic in the region, and the presence of the Aedes aegypti mosquito vector responsible for transmitting the disease. (1) Methods: To assess the association between climatic factors and human dengue virus infections in the Caribbean, we conducted a systematic review of published studies on MEDLINE and Web of Science databases according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria. (2) Results: In total, 153 papers were identified, with 27 studies selected that met the inclusion criteria ranging from the northern and southern Caribbean. Rainfall/precipitation and vapor pressure had a strong positive association with dengue incidence, whereas the evidence for the impact of temperatures was mixed. (3) Conclusions: The interaction between climate and human dengue disease in the Caribbean is complex and influenced by multiple factors, including waste management, infrastructure risks, land use changes, and challenged public health systems. Thus, more detailed research is necessary to understand the complexity of dengue within the wider Caribbean and achieve better dengue disease management.

RESUMEN

Hantavirus pulmonary syndrome (HPS) is an American emerging disease caused by the rodent-borne virus genus Orthohantavirus (Family: Hantaviridae: Order: Elliovirales Class: Bunyaviricetes). In Argentina, almost half of the HPS infections occur in the northwestern endemic region. In this study, we monitored rodent abundance during 2022 and 2023 in three sites with different sampling methods (removal trapping, live trapping and hunted rodents by domestic cats) to evaluate their relationship with human infections. We found a similar pattern of variation in rodent abundance across time, and particularly a synchronous rise of rodent abundance that anticipated an HPS outbreak in 2023. Our dynamic regression models revealed a positive relationship between HPS cases and rodent abundance with a three-month lag, as well as rainfall with an eight-month lag. Our results provide a framework for the planning and implementation of public health prevention campaigns based on climatology and rodent monitoring. Domestic cats bringing rodents into houses can be an overlooked risk factor, particularly if viral shedding of infected rodents is magnified by stress. HPS is a disease of public health concern due to its high mortality rate, the lack of a specific therapeutic treatment and no vaccine. Thus, prevention of infections is of the utmost importance.

RESUMEN

Fire occurrence, intensity, and spread are highly influenced by climatic variables. This study investigates the correlation between burned area, precipitation, and temperature in Rondônia, an agricultural frontier in the southwestern Brazilian Legal Amazon, from 2001 to 2022. The analysis utilized climatological data from the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) and MODIS product MOD11A1.061 for temperature, along with MODIS product MCD64A1 for burned area. The study was conducted on a monthly scale, employing the cross-correlation function to determine the lagged effects of temperature and precipitation on burned areas. Trend analysis was performed using the Mann-Kendall test, with the magnitude of trends estimated by Sen's Slope. Results indicated a significant negative correlation between burned areas and precipitation, with a 2-month lag and an R2 of - 0.51. In contrast, temperature exhibited a significant positive correlation with burned areas, showing a 1-month lag and an R2 of 0.55. Trend analysis revealed a decrease in precipitation by - 0.0542 mm.month-1, temperature increased by 0.006 °C.month-1, while burned areas decreased by - 111.13 km2.month-1. These findings underscore the intricate relationship between climate variables and fire occurrences, highlighting the urgent need for policies addressing climate change and environmental degradation in the Amazon.

Asunto(s)

RESUMEN

Plague is a deadly zoonosis that still poses a threat in many regions of the world. We combined epidemiologic, host, and vector surveillance data collected during 1961-1980 from the Araripe Plateau focus in northeastern Brazil with ecologic, geoclimatic, and Yersinia pestis genomic information to elucidate how these factors interplay in plague activity. We identified well-delimited plague hotspots showing elevated plague risk in low-altitude areas near the foothills of the plateau's concave sectors. Those locations exhibited distinct precipitation and vegetation coverage patterns compared with the surrounding areas. We noted a seasonal effect on plague activity, and human cases linearly correlated with precipitation and rodent and flea Y. pestis positivity rates. Genomic characterization of Y. pestis strains revealed a foundational strain capable of evolving into distinct genetic variants, each linked to temporally and spatially constrained plague outbreaks. These data could identify risk areas and improve surveillance in other plague foci within the Caatinga biome.

Asunto(s)

RESUMEN

Monitoring erosion is an important part of understanding the causes of this geotechnical and geological phenomenon. In order to monitor them, it is necessary to develop equipment that is sophisticated enough to resist the sun and water without damage, that is self-mechanized, and that can support the amount of data collected. This article introduces a rain-triggered field erosion monitoring device composed of three main modules: control, capture, and sensing. The control module comprises both hardware and firmware with embedded software. The capture module integrates a camera for recording, while the sensing module includes rain sensors. By filming experimental soil samples under simulated rain events, the device demonstrated satisfactory performance in terms of activation and deactivation programming times, daytime image quality without artificial lighting, and equipment protection. The great differences about this monitoring device are its ease of use, low cost, and the quality it offers. These results suggest its potential effectiveness in capturing the progression of field erosive processes.

RESUMEN

Mosquito-borne diseases constitute a significant global impact on public and animal health. Climatic variables are recognized as major drivers in the mosquitoes' life history, principally rainfall and temperature, which directly influence mosquito abundance. Likewise, urbanization changes environmental conditions, and understanding how environmental variables and urbanization influence mosquito dynamics is crucial for the integrated management of mosquito-borne diseases, especially in the context of climate change. In this study, our aim was to observe the effect of temperature, rainfall, and the percentage of impervious surface on the abundance of mosquito species over a temporal scale of one complete year of fortnightly samplings, spanning from June 2021 to June 2022 in Yucatan, Mexico. We selected nine localities along an urbanization gradient (three natural, three rural, and three urban) from Mérida City to Reserva de la Biosfera Ría Celestún. Using BG-traps, mosquitoes were collected biweekly at each locality. Additionally, we estimated the percentage of impervious surface. Daily data of the maximum, mean and minimum temperatures, diurnal temperature range and rainfall were accumulated weekly. We calculated the accumulated quantities of temperatures and rainfall and lagged from one to four weeks before sampling for each locality. Generalized linear mixed models were then performed to study the influence of environmental variables and percentage of impervious surfaces on each of the 15 most abundant species. A total of 131,525 mosquitoes belonging to 11 genera and 49 species were sampled with BG-Sentinel traps baited with BG-lure and dry ice. The most frequently significative variable is the accumulated precipitation four weeks before the sampling. We observed a positive relationship between Cx. quinquefasciatus and Cx. thriambus with the diurnal temperature range. For Ae. aegypti, we observed a positive relationship with minimum temperature. Conversely, the percentage of impervious surface serves as a proxy of anthropogenic influence and helped us to distinguishing species exhibiting habitat preference for urban and rural environments, versus those preferring natural habitats. Our results characterize the species-specific effects of environmental variables (temperature, rainfall and impervious surface) on mosquito abundance.

Asunto(s)

RESUMEN

Global warming is changing precipitation patterns, particularly harming communities in low-and-middle income countries (LMICs). Whilst the long-term effects of being exposed to rainfall shocks early in life on school-achievement tests are well-established, there is little population-based evidence from LMICs on the mechanisms through which these shocks operate. Executive functions (EFs) are key for children's learning abilities. This paper analyses the effects of early exposure to rainfall shocks on four foundational cognitive skills (FCSs), including EFs that have been found to be key predictors of educational success. These skills were measured via a series of tablet-based tasks administered in Peru as part of the Young Lives longitudinal study (YLS). We combine the YLS data with gridded data on monthly precipitation to generate monthly, community-level rainfall shock estimates. The key identification strategy relies on temporary climatic shocks being uncorrelated with other latent determinants of FCSs development. Our results show significant negative effects of early life exposure to rainfall shocks on EFs-especially, on working memory-measured in later childhood. We also find evidence of rainfall shocks decreasing households' abilities to invest in human capital, which may affect both FCSs and domain-specific test scores. Finally, there is suggestive, but not conclusive, evidence that a conditional-cash-transfer program providing poor households with additional financial resources might partially offset the effects of the rainfall shocks.

Asunto(s)

RESUMEN

The present study describes the seasonal and circadian variations of the major compounds from Lippia alba leaves. SPSS was used to identify, quantify, and associate the variations in the secondary metabolites of this species through HPLC/DAD analysis of the leaves hydroethanolic extracts of six selected L. alba specimens. For the circadian study, the samples were collected at four different daily hours in each year's season. For the seasonal study, the samples were collected monthly from the same individuals for two consecutive years (2018 and 2019). These samples were analyzed and quantified using a validated HPLC method for flavonoids, iridoids, and phenyl ethanoid glycoside. Mussaenoside, acteoside, and tricin-7-O-diglucuronide showed a moderate positive correlation between their biosynthesis and the precipitation index, while epi-loganin had a moderate negative correlation. Acteoside showed a moderate positive correlation between the minimum registered temperature and its production. Compared with previous studies, a drastic reduction (about 95 %) in the production of tricin-7-O-diglucuronide compared with previous study and this difference could be attributed to the plant's aging. Thus, the data demonstrated that lower temperatures and high rainfall could favor the production of the major L. alba active compounds (acteoside and tricin-7-O-diglucuronide) and that older plants harm their production.

Asunto(s)

RESUMEN

This study analyzed the meteorological and hydrological droughts in a typical basin of the Brazilian semiarid region from 1994 to 2016. In recent decades, this region has faced prolonged and severe droughts, leading to marked reductions in agricultural productivity and significant challenges to food security and water availability. The datasets employed included a digital elevation model, land use and cover data, soil characteristics, climatic data (temperature, wind speed, solar radiation, humidity, and precipitation), runoff data, images from the MODIS/TERRA and AQUA sensors (MOD09A1 and MODY09A1 products), and soil water content. A variety of methods and products were used to study these droughts: the meteorological drought was analyzed using the Standardized Precipitation Index (SPI) derived from observed precipitation data, while the hydrological drought was assessed using the Standardized Soil Index (SSI), the Nonparametric Multivariate Standardized Drought Index (NMSDI), and the Parametric Multivariate Standardized Drought Index (PMSDI). These indices were determined using water balance components, including streamflow and soil water content, from the Soil Water Assessment Tool (SWAT) model, and evapotranspiration data from the Surface Energy Balance Algorithm for Land (SEBAL). The findings indicate that the methodology effectively identified variations in water dynamics and drought periods in a headwater basin within Brazil's semiarid region, suggesting potential applicability in other semiarid areas. This study provides essential insights for water resource management and resilience building in the face of adverse climatic events, offering a valuable guide for decision-making processes.

Asunto(s)

RESUMEN

Central America and the Caribbean are regularly battered by megadroughts, heavy rainfall, heat waves, and tropical cyclones. Although 21st-century climate change is expected to increase the frequency, intensity, and duration of these extreme weather events (EWEs), their incidence in regional protected areas (PAs) remains poorly explored. We examined historical and projected EWEs across the region based on 32 metrics that describe distinct dimensions (i.e., intensity, duration, and frequency) of heat waves, cyclones, droughts, and rainfall and compared trends in PAs with trends in unprotected lands. From the early 21st century onward, exposure to EWEs increased across the region, and PAs were predicted to be more exposed to climate extremes than unprotected areas (as shown by autoregressive model coefficients at p < 0.05 significance level). This was particularly true for heat waves, which were projected to have a significantly higher average (tested by Wilcoxon tests at p < 0.01) intensity and duration, and tropical cyclones, which affected PAs more severely in carbon-intensive scenarios. PAs were also predicted to be significantly less exposed to droughts and heavy rainfall than unprotected areas (tested by Wilcoxon tests at p < 0.01). However, droughts that could threaten connectivity between PAs are increasingly common in this region. We estimated that approximately 65% of the study area will experience at least one drought episode that is more intense and longer lasting than previous droughts. Collectively, our results highlight that new conservation strategies adapted to threats associated with EWEs need to be tailored and implemented promptly. Unless urgent action is taken, significant damage may be inflicted on the unique biodiversity of the region.

Ciclones, olas de calor, sequías y lluvias intensas son eventos comunes en Centroamérica y el Caribe, cuya frecuencia, intensidad y duración se espera aumente durante el siglo XXI a causa del cambio climático. Sin embargo, en la actualidad, se desconoce cuál será la incidencia de estos eventos meteorológicos extremos (EME) dentro de las áreas protegidas. En este estudio examinamos la exposición histórica y futura a los extremos climáticos y comparamos el grado de exposición dentro y fuera de las áreas protegidas de toda la región por medio de 32 métricas que describen distintas dimensiones (intensidad, duración y frecuencia) de las olas de calor, los ciclones, las sequías y las precipitaciones. Los resultados indican que a medida que aumente el número de EME, las áreas protegidas estarán más expuestas a los extremos climáticos que las áreas no protegidas. Esto es especialmente cierto en el caso de las olas de calor, que, según las proyecciones, tendrán una intensidad y una duración medias significativamente mayores, y de los ciclones tropicales, que afectarán más gravemente a las zonas protegidas en los escenarios intensivos en carbono. Nuestros resultados también indican que las zonas protegidas estarán significativamente menos expuestas a sequías o lluvias torrenciales que las zonas no protegidas. Sin embargo, las sequías que podrían amenazar la conectividad entre áreas protegidas son cada vez más frecuentes en esta región. Se estima que aproximadamente el 65% del área de estudio experimentará al menos un episodio de sequía más intenso y duradero que las sequías anteriores. En conjunto, nuestros resultados ponen de relieve la necesidad de diseñar y aplicar con prontitud nuevas estrategias de conservación adaptadas a las amenazas asociadas a los EWE. A menos que se tomen medidas urgentes, la biodiversidad única de la región podría sufrir daños considerables.

Asunto(s)

RESUMEN

The study of rainfall thresholds is vital in understanding the factors that trigger landslides, being one of the criteria applied to landslide early warning systems that aim to mitigate their consequences. These thresholds enable the prediction of landslide occurrences as a function of rainfall measurements. This work presents an overview of the parameters involved in defining rainfall thresholds based on scientific articles published between 2008 and 2021 that discuss the subject through statistical or physical methods. These articles provided data such as publication information, threshold types, details on the data used in the works, methodology, and application of the threshold in early warning systems. There was a significant increase in research papers on this theme during this period, possibly due to the strategies advocated by the Sendai Framework. However, some regions of the world severely affected by landslides are barely mentioned in these studies. The results indicate specific trends, such as those found in the methods used to define rainfall thresholds and the parameters relating to the database when a statistical approach was used. Certain deficiencies were found, such as those concerning geological-geotechnical conditions for categorizing thresholds, the time scales of rainfall data, rain gauge density, and the criteria to define the accumulated rainfall period to be considered.

RESUMEN

Modeling soil moisture as a function of meteorological data is necessary for agricultural applications, including irrigation scheduling. In this study, empirical water balance models and empirical compartment models are assessed for estimating soil moisture, for three locations in Colombia. The daily precipitation and average, maximum and minimum air temperatures are the input variables. In the water balance type models, the evapotranspiration term is based on the Hargreaves model, whereas the runoff and percolation terms are functions of precipitation and soil moisture. The models are calibrated using field data from each location. The main contributions compared to closely related studies are: i) the proposal of three models, formulated by combining an empirical water balance model with modifications in the precipitation, runoff, percolation and evapotranspiration terms, using functions recently proposed in the current literature and incorporating new modifications to these terms; ii) the assessment of the effect of model parameters on the fitting quality and determination of the parameters with higher effects; iii) the comparison of the proposed empirical models with recent empirical models from the literature in terms of the combination of fitting accuracy and number of parameters through the Akaike Information Criterion (AIC), and also the Nash-Sutcliffe (NS) coefficient and the root mean square error. The best models described soil moisture with an NS efficiency higher than 0.8. No single model achieved the highest performance for the three locations.

RESUMEN

This work is a case study whose objective is prediction of irrigation needs of corn crops in different regions of Ecuador; being this a fundamental basic food for the country's economy, as in the remaining countries of the Andean area. The proposed methodology seeks to help improving the quality of corn crop. Specifically, we propose the application of regression models, within the framework of Functional Data Analysis (FDA), to predict the amount of rainfall (scalar response variable) in the places with the highest production of corn in Ecuador, as a function of functional covariates such as temperature and wind speed. From the estimation of the amount of rainfall, effective precipitation is calculated. This is the fraction of water used by the crops, from which the value of real evapotranspiration or ETc is obtained and, more importantly, the irrigation requirements at each stage of the corn crop, for its adequate physiological development. Application of regression models based on functional basis, Functional Principal Components (FPC) or Functional Partial Least Squares (FPLS) for scalar response variable, allows us to use the information of variables such as wind speed and temperature (of functional nature) in a better way than using multivariate models, for predicting the amount of rainfall, obtaining, as a result, very explicative models, defined by a high goodness of fit (R2=0.97, with 6 significant parameters and an error of 0.14) and practical utility. The model has been also applied to North Peru regions, obtaining rainfall prediction errors between 9% and 22%. Thus, the geographical limitations of the model could be the Andean regions with similar climate. In addition, this study proposes the application of FDA exploratory analysis and FDA outlier detection techniques as a common and useful practice in the specific domain of rainfall prediction studies, prior to applying the regression models.

RESUMEN

Despite recent advances in modeling forest-rainfall relationships, the current understanding of changes in observed rainfall patterns resulting from historical deforestation remains limited. To address this knowledge gap, we analyzed how 40 years of deforestation has altered rainfall patterns in South America as well as how current Amazonian forest cover sustains rainfall. First, we develop a spatiotemporal neural network model to simulate rainfall as a function of vegetation and climate inputs in South America; second, we assess the rainfall effects of observed deforestation in South America during the periods 1982-2020 and 2000-2020; third, we assess the potential rainfall changes in the Amazon biome under two deforestation scenarios. We find that, on average, cumulative deforestation in South America from 1982 to 2020 has reduced rainfall over the period 2016-2020 by 18% over deforested areas, and by 9% over non-deforested areas across South America. We also find that more recent deforestation, that is, from 2000 to 2020, has reduced rainfall over the period 2016-2020 by 10% over deforested areas and by 5% over non-deforested areas. Deforestation between 1982 and 2020 has led to a doubling in the area experiencing a minimum dry season of 4 months in the Amazon biome. Similarly, in the Cerrado region, there has been a corresponding doubling in the area with a minimum dry season of 7 months. These changes are compared to a hypothetical scenario where no deforestation occurred. Complete conversion of all Amazon forest land outside protected areas would reduce average annual rainfall in the Amazon by 36% and complete deforestation of all forest cover including protected areas would reduce average annual rainfall in the Amazon by 68%. Our findings emphasize the urgent need for effective conservation measures to safeguard both forest ecosystems and sustainable agricultural practices.

Asunto(s)

RESUMEN

OBJECTIVES: This study aimed to analyse hospitalisations for respiratory diseases in the Western Region of Bahia, Northeast Brazil, from 2010 to 2019, and to explore possible correlations with meteorological data. STUDY DESIGN: This descriptive, epidemiological, ecological study analysed data from 37 municipalities in the Western Bahia health macro-region, defined according to geographical, administrative, demographic, epidemiological, social and cultural criteria, and accounting for availability of health resources. METHODS: Hospitalisation data for respiratory diseases, including total admissions and disease frequency, mean and prevalence, were obtained from DATASUS (Ministry of Health). The data were evaluated by sex, age group and city. Statistical tests, such as the Chi-squared test and analysis of variance, were used for data analysis. Meteorological data were compared using the t-test and Mann-Whitney test. Correlations between health indicators and weather data were assessed using the Pearson and Spearman correlation coefficients. RESULTS: Over the investigated period, there were 536,195 hospitalisation records in the region, with respiratory diseases accounting for 17.1% of admissions. Notably, 40% of respiratory hospitalisations were among children aged 0-9 years. The most prevalent respiratory conditions were pneumonia and asthma, which together constituted 73% of all respiratory hospitalisations. A significant negative correlation was observed between respiratory diseases and rainfall (r = -0.70, P = 0.011). CONCLUSIONS: Pneumonia and asthma remain important causes of hospitalisation among children in the Western Bahia Region. The study findings suggest that respiratory diseases are influenced by rainfall, possibly due to increased atmospheric pollutants during time of low rainfall. These findings emphasise the importance of environmental factors in the development and exacerbation of respiratory diseases.

Asunto(s)

RESUMEN

This article proposes a new class of nonhomogeneous Poisson spatiotemporal model. In this approach, we use a state-space model-based prior distribution to handle the scale and shape parameters of the Weibull intensity function. The proposed prior distribution enables the inclusion of changes in the behavior of the intensity function over time. In defining the spatial correlation function of the model, we include anisotropy via spatial deformation. We estimate the model parameters from a Bayesian perspective, employ the Markov chain Monte Carlo approach, and validate this estimation procedure through a simulation exercise. Finally, the extreme rainfall in the southern semiarid region in northeastern Brazil is analyzed using the R10mm index. The proposed model showed better fit and prediction ability than did other nonhomogeneous Poisson spatiotemporal models available in the literature. This improvement in performance is mainly due to the flexibility of the intensity function that is achieved by allowing the incorporation, in time, of the climatic characteristics of this region.

Asunto(s)

RESUMEN

Flowering and fruiting phenology have been infrequently studied in the ever-wet hyperdiverse lowland forests of northwestern equatorial Amazonía. These Neotropical forests are typically called aseasonal with reference to climate because they are ever-wet, and it is often assumed they are also aseasonal with respect to phenology. The physiological limits to plant reproduction imposed by water and light availability are difficult to disentangle in seasonal forests because these variables are often temporally correlated, and both are rarely studied together, challenging our understanding of their relative importance as drivers of reproduction. Here we report on the first long-term study (18 years) of flowering and fruiting phenology in a diverse equatorial forest, Yasuní in eastern Ecuador, and the first to include a full suite of on-site monthly climate data. Using twice monthly censuses of 200 traps and >1000 species, we determined whether reproduction at Yasuní is seasonal at the community and species levels and analyzed the relationships between environmental variables and phenology. We also tested the hypothesis that seasonality in phenology, if present, is driven primarily by irradiance. Both the community- and species-level measures demonstrated strong reproductive seasonality at Yasuní. Flowering peaked in September-November and fruiting peaked in March-April, with a strong annual signal for both phenophases. Irradiance and rainfall were also highly seasonal, even though no month on average experienced drought (a month with <100 mm rainfall). Flowering was positively correlated with current or near-current irradiance, supporting our hypothesis that the extra energy available during the period of peak irradiance drives the seasonality of flowering at Yasuní. As Yasuní is representative of lowland ever-wet equatorial forests of northwestern Amazonía, we expect that reproductive phenology will be strongly seasonal throughout this region.

La fenología de floración y fructificación ha sido poco estudiada en los bosques bajos, lluviosos e hiperdiversos de la Amazonía noroccidental. Estos bosques neotropicales son típicamente llamados no estacionales debido a su clima siempre lluvioso y se asume que son no estacionales con respecto a la fenología. Los límites fisiológicos a la reproducción de las plantas impuestos por la disponibilidad de agua y luz en estos bosques son difíciles de desentrañar debido a que estas variables están a menudo correlacionadas temporalmente y las dos se estudian usualmente por separado, lo que desafía nuestra comprensión de su importancia relativa como desencadenantes de la reproducción. Este es el primer estudio de largo plazo (18 años) de la fenología de floración y fructificación en un bosque hiperdiverso de la Amazonía noroccidental ecuatorial, Yasuní, ubicado al este de Ecuador, y el primero en incluir un completo set de datos climáticos mensuales. Usando censos quincenales de 200 trampas y > 1000 especies, examinamos si la reproducción en Yasuní es estacional a nivel de comunidad y de especies y analizamos las relaciones de las variables ambientales con la fenología. También nos interesaba probar si la estacionalidad en la fenología, en caso de que esté presente está causada por la irradiancia. Tanto a nivel de comunidad como de especies, los datos demuestran una fuerte estacionalidad reproductiva en Yasuní. La floración alcanzó un máximo en septiembre-noviembre y la fructificación alcanzó un máximo en marzo-abril, con una fuerte y consistente señal anual en las dos fenofases. A su vez, la irradiancia y la lluvia fueron también marcadamente estacionales, aunque ningún mes en promedio experimentó sequía (i.e. <100 mm de lluvia). La floración fue positivamente correlacionada con la irradiación, apoyando nuestra hipótesis de que la energía extra disponible durante los periodos de mayor irradiación causa la estacionalidad de la floración en Yasuní. Debido a que Yasuní representa a los bosques ecuatoriales lluviosos de tierras bajas de la Amazonía noroccidental, esperamos que la fenología reproductiva sea fuertemente estacional a lo largo de esta región.

Asunto(s)

RESUMEN

The paper presents a high-resolution (-3km) gridded dataset for daily precipitation across Cuba for 1961-2008, called CubaPrec1. The dataset was built using the information from the data series of 630 stations from the network operated by the National Institute of Water Resources. The original station data series were quality controlled using a spatial coherence process of the data, and the missing values were estimated on each day and location independently. Using the filled data series, a grid of 3 × 3 km spatial resolution was constructed by estimating daily precipitation and their corresponding uncertainties at each grid box. This new product represents a precise spatiotemporal distribution of precipitation in Cuba and provides a useful baseline for future studies in hydrology, climatology, and meteorology. The data collection described is available on zenodo: https://doi.org/10.5281/zenodo.7847844.

RESUMEN

Floods have caused socio-economic and environmental damage globally and, thus, require research. Several factors influence flooding events, such as extreme rainfall, physical characteristics, and local anthropogenic factors; therefore, such factors are essential for mapping flood risk areas and enabling measures that mitigate the damage they cause. This study aimed to map and analyze regions susceptible to flood risk in three different study areas belonging to the same Atlantic Forest biome, in which flood disasters are recurrent. Due to the presence of numerous factors, a multicriteria analysis using the Analytical Hierarchical Process was conducted. First, a geospatial database was composed of layers of elevation, slope, drainage distance, soil drainage, soil hydrological group, precipitation, relief, and land use and cover. Flood risk maps for the study area were then generated, and patterns in the study areas were verified, with the greatest influence being exerted by intense precipitation on consecutive days, elevation at the edges of the channel with low altimetric variation and a flat combination, densely built areas close to the banks of the main river, and an expressive water mass in the main watercourse. The results demonstrate that these characteristics together can indicate the occurrence of flooding events.

Asunto(s)