Spatial point process modeling applied to the assessment of risk factors associated to forest wildfires incidence in Castellón, Spain

During the last decades the Mediterranean zone in Europe has experienced an increment in the incidence of forest wildfires. This increase is partly explained by higher mean temperature and lower relative humidity, while socioeconomic change has lead to the abandonment of farms, resulting in an increase in an unusual accumulation of forest fuels, increasing the risk of wildfires. Mapping wildfire risk is highly important because wildfires are known to potentially lead to landscape changes and to modify fire regime by inducing potential changes in vegetation composition. Also, they pose a hazard to human property and life. Maps of wildfire risk based on statistical models provide a measure of uncertainty for the inferences derived from such risk maps, leaving a quantitative error margin for managers and decision takers. Further, some of the model parameters often have a physical or a biological interpretation which can give ecologists and forest engineers answers about scientific questions of interest. In this paper, we analyze the incidence of wildfires in the province of Castellón in Spain in order to identify risk factors associated with wildfire incidences during the years 2001–2006. We used the discrete nature of wildfire events to build such models using point process theory and methods and included information about elevation, slope, aspect, land use and distance to nearest road as covariates in our modeling process. Our results show that wildfire risk in Castellón is associated with all the covariates considered and that three land-use categories have the highest risk of wildfire incidence. Also, wildfire incidences are not independent and some degree of interaction exists, which indicates that the commonly used Poisson point process models are not applicable in this case, but instead area-interaction models should be considered

Hierarchical spatial modeling of the presence of Chagas disease insect vectors in Argentina. A comparative approach

We modeled the spatial distribution of the most important Chagas disease vectors in Argentina, in order to obtain a predictive mapping method for the probability of presence of the vector species. We analyzed both the binary variable of presence-absence of Chagas disease and the vector species richness in Argentina, in combination with climatic and topographical covariates associated to the region of interest. We used several statistical techniques to produce distribution maps of presence–absence for the different insect species as well as species richness, using a hierarchical Bayesian framework within the context of multivariate geostatistical modeling. Our results show that the inclusion of covariates improves the quality of the fitted models, and that there is spatial interaction between neighboring cells/pixels, so mapping methods used in the past, which assumed spatial independence, are not adequate as they provide unreliable results.We thank J. E. Rabinovich from Centro de Estudios Parasitologicos y de Vectores of Buenos Aires, Argentina for drawing our attention to this particular application problem and for providing access to the Chagas data base used. Work partially funded by grant MTM2013-43917-P from the Spanish Ministry of Science and Education, grant PAPIIT IN114814 of the Direccio ́ n General de Asuntos del Personal Acade ́ mico of the Universidad Nacional Auto ́ noma de Me ́ xico and Grant CONACYT number 241195

Reliability evaluation of the data acquisition potential of a low-cost climatic network for applications in agriculture

Trilles, S., Juan, P., Díaz-Avalos, C., Ribeiro, S., & Painho, M. (2020). Reliability evaluation of the data acquisition potential of a low-cost climatic network for applications in agriculture. Sensors (Switzerland), 20(22), 1-27. [6597]. https://doi.org/10.3390/s20226597Temperature, humidity and precipitation have a strong influence on the generation of diseases in different crops, especially in vine. In recent years, advances in different disciplines have enabled the deployment of sensor nodes on agricultural plots. These sensors are characterised by a low cost and so the reliability of the data obtained from them can be compromised, as they are built from low-confidence components. In this research, two studies were carried out to determine the reliability of the data obtained by different SEnviro nodes installed in vineyards. Two networks of meteorological stations were used to carry out these studies, one official and the other professional. The first study was based on calculating the homogenisation of the data, which was performed using the Climatol tool. The second study proposed a similarity analysis using cross-correlation. The results showed that the low-cost node can be used to monitor climatic conditions in an agricultural area in the central zone of the province of Castelló (Spain) and to obtain reliable observations for use in previously published fungal disease models.publishersversionpublishe

Association between the New COVID-19 Cases and Air Pollution with Meteorological Elements in Nine Counties of New York State

The principal objective of this article is to assess the possible association between the number of COVID-19 infected cases and the concentrations of fine particulate matter (PM2.5) and ozone (O3), atmospheric pollutants related to people’s mobility in urban areas, taking also into account the effect of meteorological conditions. We fit a generalized linear mixed model which includes spatial and temporal terms in order to detect the effect of the meteorological elements and COVID-19 infected cases on the pollutant concentrations. We consider nine counties of the state of New York which registered the highest number of COVID-19 infected cases. We implemented a Bayesian method using integrated nested Laplace approximation (INLA) with a stochastic partial differential equation (SPDE). The results emphasize that all the components used in designing the model contribute to improving the predicted values and can be included in designing similar real-world data (RWD) models. We found only a weak association between PM2.5 and ozone concentrations with COVID-19 infected cases. Records of COVID-19 infected cases and other covariates data from March to May 2020 were collected from electronic health records (EHRs) and standard RWD sources

Modeling Influence of Soil Properties in Different Gradients of Soil Moisture: The Case of the Valencia Anchor Station Validation Site, Spain

The prediction of spatial and temporal variation of soil water content brings numerous benefits in the studies of soil. However, it requires a considerable number of covariates to be included in the study, complicating the analysis. Integrated nested Laplace approximations (INLA) with stochastic partial differential equation (SPDE) methodology is a possible approach that allows the inclusion of covariates in an easy way. The current study has been conducted using INLA-SPDE to study soil moisture in the area of the Valencia Anchor Station (VAS), soil moisture validation site for the European Space Agency SMOS (Soil Moisture and Ocean Salinity). The data used were collected in a typical ecosystem of the semiarid Mediterranean conditions, subdivided into physiohydrological units (SMOS units) which presents a certain degree of internal uniformity with respect to hydrological parameters and capture the spatial and temporal variation of soil moisture at the local fine scale. The paper advances the knowledge of the influence of hydrodynamic properties on VAS soil moisture (texture, porosity/bulk density and soil organic matter and land use). With the goal of understanding the factors that affect the variability of soil moisture in the SMOS pixel (50 km × 50 km), five states of soil moisture are proposed. We observed that the model with all covariates and spatial effect has the lowest DIC value. In addition, the correlation coefficient was close to 1 for the relationship between observed and predicted values. The methodology applied presents the possibility to analyze the significance of different covariates having spatial and temporal effects. This process is substantially faster and more effective than traditional kriging. The findings of this study demonstrate an advancement in that framework, demonstrating that it is faster than previous methodologies, provides significance of individual covariates, is reproducible, and is easy to compare with models

Aplicación de modelos de procesos puntuales para la caracterización espacio-temporal del régimen de incendios en el este de España

Ponència presentada al VI Congreso Forestal Español, celebrat a Vitoria-Gasteiz, els dies 10-14 de juny de 2013Las incidencias de los modelos espacio-temporal de los incendios forestales y sus relaciones con las variables meteorológicas, geográficas y usos del suelo son analizadas en este trabajo. Estas relaciones pueden ser tratadas en un incendio forestal como componentes en los modelos de procesos puntuales es decir como actividades separadas. En este trabajo se muestran algunas técnicas para el análisis de modelos espaciales puntuales que están disponibles gracias a los recientes desarrollos de aplicaciones informáticas en los modelos de procesos puntuales. Estos avances permiten realizar un análisis exploratorio de los datos de forma conveniente, ajuste de los datos a un modelo y evaluación del modelo. La discusión de estas técnicas se realiza conjuntamente dentro del contexto de algunos análisis preliminares de una colección de datos que son de un considerable interés por ellos mismos. Este conjunto de datos consiste en los registros de incendios forestales en la provincia de Castellón (años del 2001 al 2006) y Cataluña (2001 al 2008). Los resultados de estos trabajos apuntan a la posibilidad de zonificar las áreas forestales en zonas de mayor o menor riesgo e intensidad de incendio forestal, con lo que se podría planificar las actuaciones preventivas de una forma mas efectiva y acotada

An Animal Model Using Metallic Ions to Produce Autoimmune Nephritis

Autoimmune nephritis triggered by metallic ions was assessed in a Long-Evans rat model. The parameters evaluated included antinuclear autoantibody production, kidney damage mediated by immune complexes detected by immunofluorescence, and renal function tested by retention of nitrogen waste products and proteinuria. To accomplish our goal, the animals were treated with the following ionic metals: HgCl2, CuSO4, AgNO3, and Pb(NO3)2. A group without ionic metals was used as the control. The results of the present investigation demonstrated that metallic ions triggered antinuclear antibody production in 60% of animals, some of them with anti-DNA specificity. Furthermore, all animals treated with heavy metals developed toxic glomerulonephritis with immune complex deposition along the mesangium and membranes. These phenomena were accompanied by proteinuria and increased concentrations of urea. Based on these results, we conclude that metallic ions may induce experimental autoimmune nephritis

Apoptosis in chronic cutaneous lupus erythematosus, discoid lupus, and lupus profundus

: Introduction: Lupus erythematosus is a multisystemic disease that is characterized by autoantibody production and immune complex deposition in such tissues as the mucosa, joints, the central nervous system, and skin. Cutaneous lupus erythematosus is categorized as acute, subacute, and chronic. Chronic cutaneous lupus erythematosus comprises discoid lupus erythematosus (DLE) and lupus profundus (LP). Aim: To analyze the expression of proapoptotic molecules in patients with lupus erythematosus discoid and lupus profundus. Material and methods: Descriptive study, the study groups comprised 10 cases of LP and 10 cases of DLE, and a control. Skin samples of cases and controls were processed for immunohistochemistry and by TUNEL technique. The database and statistical analysis was performed (statistical test X2) SPSS (Chicago, IL, USA). Results: Apoptotic features were broadly distributed along the skin biopsies in epidermal keratinocytes as well as at dermis. By immunohistochemistry the expression of Fas receptor and Fas-L was higher in the skin of lupus patients compared with controls. We also noted differences in Fas-L, -Fas, and -Bax proteins expression intensity in discoid lupus erythematosus patients in the epidermis, and hair follicles. Conclusions: Fas and Fas-L are expressed similarly in LP and DLE

Soil tillage to reduce surface metal contamination – model development and simulations of zinc and copper concentration profiles in a pig slurry-amended soil

Long-term applications of organic amendments, such as pig slurry (PS), may represent environmental risk of soil and water pollution by trace metals (TM). Our objective was to examine different soil and manure management scenarios that enhance the long-term agricultural use of soils under repetitive PS applications while avoiding environmental risk. Firstly, we developed a new module for simulating the impacts of soil tillage frequencies in Hydrus-1D. Secondly, we used a previously validated modeling approach to predict the surface accumulation and movement of the TM during the next 100-year in the soil under different PS doses (80 and 40m3ha-1cultivation-1) and tillage frequencies (no-tillage and 20, 10, and 5-year tillage). No-tillage simulations revealed consistent TM surface accumulations, reaching the soil threshold value for Cu in the 0-20cm layer after 86 years of PS amendments at high doses, but in layers 0-5, 0-10, and 5-10cm, this concentration was already reached after 17, 38, and 75 years, respectively. While soil tillage reduced TM concentrations over the top 20cm of the soil profile, it increased their transfer to deeper layers. Periodical soil tillage each 5, 10, and 20 years was found to allow PS applications without reaching the Cu threshold value in soil during 100 years. However, soil solution concentrations of Zn reached the threshold values for groundwater. Therefore, the best manure management practice for the long-term PS disposal with respect to Zn and Cu concentrations in soil is the application of moderate PS rates. © 2014 Elsevier B.V