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The uncontrolled spread of fire can have huge effects on ecosystems. In Ecuador, in 2022, wildfires caused a loss of 6566.66 hectares of vegetation cover. Ibarra is an Andean canton that has also been exposed to wildfires and their effects. The aim of this study was to map wildfire susceptibility in the Ibarra canton. Seven factors that directly affect these fires were examined: precipitation, temperature, water deficit, potential evapotranspiration, slope, proximity to roads, and land cover and land use. The variables were reclassified using Geographic Information Systems and a multicriteria analysis. The results showed that Ibarra has four susceptibility categories: very low, moderate, high, and very high. The more susceptible areas are those considered to have high and very high exposure, occupying 82% of the surface. Consequently, the most susceptible land covers are crops, pastures, shrub vegetation, and forests. [ABSTRACT FROM AUTHOR]

The use of remote sensing and information on social factors specific to each population allows the monitoring of natural resource use. The main objective of this study is to determine the change and future projection of land use and land cover and, at the same time, to understand, from the perspective of the main stakeholders, the driving and underlying factors of these changes in the middle-upper Mira river basin. For this purpose, multispectral, Landsat, and Sentinel images from 1996, 2007, and 2018 have been used and pre-processed and treated. Subsequently, a forecast of land cover and land use changes from 2018-2030 has been made using TerrSet software. The drivers and underlying factors have been identified using the Delphi method. The results show that forests and pastures presented a sustained decrease, while cropland and urban areas increased between 1996-2018 and 2018-2030. These changes are related to urban, agricultural, livestock, mining, and forest industry growth, which are generally driven by population growth, market demand, changing consumption patterns, road expansion, and a lack of environmental policies. [ABSTRACT FROM AUTHOR]

So far, about 770.1 million confirmed cases of COVID-19 have been counted by August 2023, and around 7 million deaths have been reported from these cases to the World Health Organization. In Ecuador, the first confirmed COVID-19 case was registered on 19 February 2020, and the country's mortality rate reached 0.43% with 12986 deaths, suggesting the need to establish a mechanism to show the virus spread in advance. This study aims to build a dynamic model adapted to health and socio-environmental variables as a multivariate model to understand the virus expansion among the population. The model is based on Susceptible-Infected-Recovered (SIR), which is a standard model in which the population is divided into six groups with parameters such as susceptible S(t), transit stage E(t), infected I(t), recovered R(t), deceased Me(t), infected asymptomatic Ia(t), infected symptomatic Is(t) and deceased by other causes M(t) to be considered and adapted. The model was validated by using consistent data from Chile and run by inconsistent data from Ecuador. The forecast error was analyzed based on the mean absolute error between real data and model forecast, showing errors within a range from 6.33% to 8.41% for Chile, with confidence a interval of 6.17%, then 3.87% to 4.70% range for Ecuador with a confidence interval of 2.59% until 23rd December 2020 of the database. The model forecasts exponential variations in biosecurity measures, exposed population, and vaccination. [ABSTRACT FROM AUTHOR]