RESUMO
Resumen Introducción: Los mamíferos marinos se ven afectados por diversas amenazas que deben identificarse para los esfuerzos de mitigación. Objetivo: Cuantificar visualmente las amenazas a los mamíferos marinos en Colombia e identificar acciones de mitigación. Métodos: Georreferenciamos las amenazas con base en la literatura, cubriendo 35 especies en el período 1991-2020, y las superpusimos en mapas de distribución de especies. Resultados: 22 especies presentaron al menos una amenaza. La captura incidental y las interacciones con los artes de pesca afectaron a 16 especies, seguidas de la captura directa (8 especies), el tráfico/tránsito de embarcaciones (6 especies) y la alteración de la física oceánica (6 especies). Las especies más afectadas, en cuanto a mayor diversidad de amenazas, son: ballena jorobada (Megaptera novaeangliae), manatí antillano del Caribe (Trichechus manatus), el tucuxi marino (Sotalia guianensis) y el delfín nariz de botella (Tursiops truncatus). Casi todo el territorio marino de Colombia presenta algún grado de riesgo para los mamíferos marinos. Las áreas de alto riesgo son Buenaventura, Guapi, Golfo de Cupica y Tumaco en el Pacífico; y Golfo de Urabá, Golfo de Darién, Golfo de Morrosquillo, frente a Barranquilla, Ciénaga Grande de Santa Marta y Golfo de Coquivacoa en el Caribe. Conclusión: Los mamíferos marinos en Colombia se encuentran actualmente en riesgo debido a varias amenazas, especialmente relacionadas con actividades de pesca, caza/captura y transporte marítimo, principalmente en las zonas costeras. Se necesitan acciones urgentes de evaluación y gestión en las diez áreas de alto riesgo identificadas en este estudio.
Abstract Introduction: Marine mammals are affected by diverse threats that must be identified for mitigation efforts. Objective: To visually quantify threats to marine mammals in Colombia, and to identify mitigation actions. Methods: We georeferenced threats based on the literature, covering 35 species in the period 1991-2020, and superimposed them on species range maps. Results: 22 species had at least one threat. Bycatch and interactions with fishing gear affected 16 species, followed by direct capture (8 species), vessel traffic/transit (6 species) and alteration of ocean physics (6 species). The most affected species, in terms of the greatest diversity of threats, are: humpback whale (Megaptera novaeangliae), Caribbean West Indian manatee (Trichechus manatus), marine tucuxi (Sotalia guianensis) and bottlenose dolphin (Tursiops truncatus). Nearly all of Colombia's marine territory presents some degree of risk for marine mammals. High-risk areas are Buenaventura, Guapi, Cupica Gulf and Tumaco in the Pacific; and Urabá Gulf, Darién Gulf, Morrosquillo Gulf, off Barranquilla, Ciénaga Grande de Santa Marta and Coquivacoa Gulf in the Caribbean. Conclusion: Marine mammals in Colombia are currently at risk due to several threats, especially related to fishing, hunting/capture and shipping activities, mainly in coastal areas. Urgent evaluation and management actions are needed in the ten high-risk areas identified in this study.
Assuntos
Animais , Fauna Marinha , Localização Geográfica de Risco , Mamíferos/classificação , ColômbiaRESUMO
Through the application of intelligent systems in driver assistance systems, the experience of traveling by road has become much more comfortable and safe. In this sense, this paper then reports the development of an intelligent driving assistant, based on vehicle telemetry and road accident risk map analysis, whose responsibility is to alert the driver in order to avoid risky situations that may cause traffic accidents. In performance evaluations using real cars in a real environment, the on-board intelligent assistant reproduced real-time audio-visual alerts according to information obtained from both telemetry and road accident risk map analysis. As a result, an intelligent assistance agent based on fuzzy reasoning was obtained, which supported the driver correctly in real-time according to the telemetry data, the vehicle environment and the principles of secure driving practices and transportation regulation laws. Experimental results and conclusions emphasizing the advantages of the proposed intelligent driving assistant in the improvement of the driving task are presented.
Assuntos
Condução de Veículo , Telemetria/métodos , Acidentes de Trânsito , Automóveis , Humanos , Medição de Risco , Fatores de Risco , SegurançaRESUMO
Agricultural production in the Pampas region is one of the most important economic activities in Argentina. However, the possible environmental effects related to the growth of this activity in the last years have not been studied enough. Particularly, the effects of pesticides mixtures are a topic of great concern both for society and regulatory authorities worldwide, given the possible additive and synergistic relationships between these chemicals and their possible effects on aquatic biota. Based on a concentration addition model, this study developed an Ecological Risk Assessment (ERA) of pesticides from freshwater ecosystems in the Pampas region. For this purpose, reported pesticides concentrations available in public bibliography and a Risk Quotients (RQs) approach were used. A cumulative risk map was established to display RQs for current use pesticides (CUPs) and legacy chemicals. The ΣRQs were calculated for 66 sites, using available reported measured environmental concentrations (MECs) and predicted no effect concentrations (PNECs) of pesticides. While ΣRQ for only CUPs resulted in a high and very high risk (ΣRQâ¯>â¯1) for 29% of the sites, when legacy pesticides were incorporated this percentage reached the 41% of the sites, increasing significantly the absolute values of RQ. Herbicides like glyphosate and atrazine contributed considerably to the ΣRQCUPs while organochlorines were the major contributors for ΣRQs when legacy pesticides were incorporated. Moreover, some active ingredients (acetochlor, carbendazim and fenitrothion) which are approved for their use in Argentina but banned in EU showed high contribution to ΣRQCUPs. The present study is the first attempt to develop an ERA in surface water of the Pampas region of Argentina and it provides a starting point for a more comprehensive pesticides monitoring and a further risk assessment program.
Assuntos
Monitoramento Ambiental , Praguicidas/análise , Poluentes Químicos da Água/análise , Argentina , Ecossistema , Medição de RiscoRESUMO
We jointly estimated relative risk for dengue and Zika virus disease (Zika) in Colombia, establishing the spatial association between them at the department and city levels for October 2015-December 2016. Cases of dengue and Zika were allocated to the 87 municipalities of 1 department and the 293 census sections of 1 city in Colombia. We fitted 8 hierarchical Bayesian Poisson joint models of relative risk for dengue and Zika, including area- and disease-specific random effects accounting for several spatial patterns of disease risk (clustered or uncorrelated heterogeneity) within and between both diseases. Most of the dengue and Zika high-risk municipalities varied in their risk distribution; those for Zika were in the northern part of the department and dengue in the southern to northeastern parts. At city level, spatially clustered patterns of dengue high-risk census sections indicated Zika high-risk areas. This information can be used to inform public health decision making.
Assuntos
Dengue/epidemiologia , Infecção por Zika virus/epidemiologia , Adolescente , Adulto , Distribuição por Idade , Teorema de Bayes , Criança , Pré-Escolar , Colômbia/epidemiologia , Dengue/história , Dengue/virologia , Vírus da Dengue , Feminino , Geografia Médica , História do Século XXI , Humanos , Lactente , Recém-Nascido , Masculino , Pessoa de Meia-Idade , Prevalência , Medição de Risco , Fatores de Risco , Adulto Jovem , Zika virus , Infecção por Zika virus/história , Infecção por Zika virus/virologiaRESUMO
The study of pest distributions in space and time in agricultural systems provides important information for the optimization of integrated pest management programs and for the planning of experiments. Two statistical problems commonly associated to the space-time modelling of data that hinder its implementation are the excess of zero counts and the presence of missing values due to the adopted sampling scheme. These problems are considered in the present article. Data of coffee berry borer infestation collected under Colombian field conditions are used to study the spatio-temporal evolution of the pest infestation. The dispersion of the pest starting from initial focuses of infestation was modelled considering linear and quadratic infestation growth trends as well as different combinations of random effects representing both spatially and not spatially structured variability. The analysis was accomplished under a hierarchical Bayesian approach. The missing values were dealt with by means of multiple imputation. Additionally, a mixture model was proposed to take into account the excess of zeroes in the beginning of the infestation. In general, quadratic models had a better fit than linear models. The use of spatially structured parameters also allowed a clearer identification of the temporal increase or decrease of infestation patterns. However, neither of the space-time models based on standard distributions was able to properly describe the excess of zero counts in the beginning of the infestation. This overdispersed pattern was correctly modelled by the mixture space-time models, which had a better performance than their counterpart without a mixture component.
O estudo da distribuição de pragas em espaço e tempo em sistemas agrícolas fornece informação importante para a otimização de programas de manejo integrado de pragas e para o planejamento de experimentos. Dois problemas estatísticos comumente associados à modelagem espaço-temporal desse tipo de dados que dificultam sua implementação são o excesso de zeros nas contagens e a presença de dados faltantes devido ao esquema de amostragem adotado. Esses problemas são considerados no presente artigo. Para estudar a evolução da infestação da broca do café a partir de focos iniciais de infestação foram usados dados de infestação da praga coletados em condições de campo na Colômbia. Foram considerados modelos com tendência de crescimento da infestação linear e quadrática, assim como diferentes combinações de efeitos aleatórios representando variabilidade espacialmente estruturada e não estruturada. As análises foram feitas sob uma abordagem Bayesiana hierárquica. O método de imputação múltipla foi usado para abordar o problema de dados faltantes. Adicionalmente, foi proposto um modelo de mistura para levar em consideração o excesso de zeros nas contagens no início da infestação. Em geral, os modelos quadráticos tiveram um melhor ajuste que os modelos lineares. O uso de parâmetros espacialmente estruturados permitiu uma identificação mais clara dos padrões temporais de acréscimo ou decréscimo na infestação. No entanto, nenhum dos modelos espaço-tempo baseados em distribuições padrões descreveu, apropriadamente, o excesso de zeros no início da infestação. Esse padrão de sobredispersão foi corretamente modelado pelos modelos de mistura espaço-tempo, os quais tiveram um melhor desempenho que seus homólogos sem mistura.
RESUMO
The study of pest distributions in space and time in agricultural systems provides important information for the optimization of integrated pest management programs and for the planning of experiments. Two statistical problems commonly associated to the space-time modelling of data that hinder its implementation are the excess of zero counts and the presence of missing values due to the adopted sampling scheme. These problems are considered in the present article. Data of coffee berry borer infestation collected under Colombian field conditions are used to study the spatio-temporal evolution of the pest infestation. The dispersion of the pest starting from initial focuses of infestation was modelled considering linear and quadratic infestation growth trends as well as different combinations of random effects representing both spatially and not spatially structured variability. The analysis was accomplished under a hierarchical Bayesian approach. The missing values were dealt with by means of multiple imputation. Additionally, a mixture model was proposed to take into account the excess of zeroes in the beginning of the infestation. In general, quadratic models had a better fit than linear models. The use of spatially structured parameters also allowed a clearer identification of the temporal increase or decrease of infestation patterns. However, neither of the space-time models based on standard distributions was able to properly describe the excess of zero counts in the beginning of the infestation. This overdispersed pattern was correctly modelled by the mixture space-time models, which had a better performance than their counterpart without a mixture component.
O estudo da distribuição de pragas em espaço e tempo em sistemas agrícolas fornece informação importante para a otimização de programas de manejo integrado de pragas e para o planejamento de experimentos. Dois problemas estatísticos comumente associados à modelagem espaço-temporal desse tipo de dados que dificultam sua implementação são o excesso de zeros nas contagens e a presença de dados faltantes devido ao esquema de amostragem adotado. Esses problemas são considerados no presente artigo. Para estudar a evolução da infestação da broca do café a partir de focos iniciais de infestação foram usados dados de infestação da praga coletados em condições de campo na Colômbia. Foram considerados modelos com tendência de crescimento da infestação linear e quadrática, assim como diferentes combinações de efeitos aleatórios representando variabilidade espacialmente estruturada e não estruturada. As análises foram feitas sob uma abordagem Bayesiana hierárquica. O método de imputação múltipla foi usado para abordar o problema de dados faltantes. Adicionalmente, foi proposto um modelo de mistura para levar em consideração o excesso de zeros nas contagens no início da infestação. Em geral, os modelos quadráticos tiveram um melhor ajuste que os modelos lineares. O uso de parâmetros espacialmente estruturados permitiu uma identificação mais clara dos padrões temporais de acréscimo ou decréscimo na infestação. No entanto, nenhum dos modelos espaço-tempo baseados em distribuições padrões descreveu, apropriadamente, o excesso de zeros no início da infestação. Esse padrão de sobredispersão foi corretamente modelado pelos modelos de mistura espaço-tempo, os quais tiveram um melhor desempenho que seus homólogos sem mistura.