Centro de Investigación para el Territorio y el Hábitat Sostenible
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Leveraging Geographic Research, Web Applications and Surveys in the Construction of Educational Strategies in Ecuador

2024 , Santos, Fabián , Fernanda Suárez , Joaquín Gairín

Communicating geographic research and contributing to the construction of regional educational strategies represent little-explored challenges. This paper takes a geographic research study that discusses territorial imbalances in access to higher education in Ecuador as an example. It describes a methodology based on developing a web application software (WAS) named “Brechas Educativas”. This software aims to disseminate research results and encourages users to reflect on their territories and the access to higher education for their student populations. Subsequently, we collected perceptions about the WAS, factors affecting academic performance and the assimilation of experiences post-COVID-19 pandemic through a survey. To achieve this, virtual workshops were conducted with 95 educational institutions (EIs) across Ecuador, complemented by email correspondence with a group of 3284 EIs. Our results enabled us to understand the good practices for developing WAS for scientific dissemination, the achievements and pitfalls in collecting opinions from the EIs and to draft focused strategies for educational decision-making in this area, informed by both app traffic and survey responses.

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Risk assessment of unlined oil pits leaking into groundwater in the Ecuadorian Amazon: A modified GIS-DRASTIC approach

2022 , Durango-Cordero J. , Saqalli M. , Ferrant S. , Bonilla S. , Maurice L. , Arellano P. , Elger A.

This study evaluates the risk of groundwater contamination from unlined oil pits, in the Northern Ecuadorian Amazon (NEA). Applying spatial analysis, several maps were provided for its integration in land use planning, public health improvement and future site-specific investigations. Two main maps were produced: (1) a vulnerability indexed map using a modified DRASTIC model and (2) a hazard map based on the past (1995–1997) and present (2018) contamination using a weighted density equation. The hazard was derived from hydrocarbon contained in oil pits associated with a cost-distance analysis to obtain different maximum distance ranges (MDR), to model the surface of potentially impacted groundwater. The results indicate a total calculated hydrocarbons of 39 052 tons. A MDR from 500–10 000 km was retained to map aquifers at risk, the maximum surface potentially at risk covers 13% of the NEA, while 83% of the area represents low to medium-low vulnerability. This study led to several recommendations, such as the level of suitability of the available information, and what gaps should be filled to improve future research. A surface of 271–766.5 km in the 500-2000-m distance range should be prioritised for finer scale risk assessment. © 2021 Elsevier Ltd

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Assessing Annual and Monthly Precipitation Anomalies in Ecuador Bioregions Using WorldClim CMIP6 GCM Ensemble Projections and Dynamic Time Warping

2025 , Santos, Fabián , José Jara , Nicole Acosta , Raúl Galeas , Bert de Bièvre

ABSTRACT The Coupled Model Inter‐comparison Project phase 6 (CMIP6) provides a suite of general circulation models (GCMs) and Socioeconomic Shared Pathways (SSPs) primarily for continental‐scale climate assessments. However, adapting these models for sub‐national assessments, particularly in countries with varied geography like Ecuador, and for complex variables such as precipitation, introduces challenges, including uncertainties in selecting appropriate GCMs and SSPs. To address these issues, we adopt a biogeographical approach that integrates regional climatic variations. Our analysis explores 26 GCMs, four SSP scenarios and four 20‐year time frames from WorldClim to evaluate discrepancies between the GCM precipitation projections, historical data and national climate projections across five Ecuadorian bioregions. This approach enabled us to sort the GCMs by annual precipitation medians, classify their monthly precipitation using Dynamic Time Warping (DTW) clustering, and develop ensembles highlighting both the largest and average precipitation anomalies within and beyond the bioregions. Among the 26 models examined, 16 projected an increase in annual precipitation in Ecuador, especially during the wet seasons, with the BCC‐CSM2‐MR model showing peak values, notably in the Choco region and eastern Amazon basin. Conversely, 10 models, with CMCC‐ESM2 showing the largest decreases, projected reduced precipitation across almost all Ecuadorian territories, except the Choco region. The largest reductions were in the Amazon basin, raising concerns about reduced precipitation. Discrepancies, primarily in the Andes and Galapagos bioregions, reveal the challenges posed by their complex topography and insular environments. While the GCMs captured spatial patterns of ENSO, our research was constrained to 20‐year averages, making direct comparison with historical records infeasible, highlighting the need for further research with shorter time frames and finer spatial resolutions. The variability in precipitation was linked to geographical factors, GCM configurations and unexpected SSP outcomes. Therefore, selecting GCMs and climatic indices tailored to specific bioregions is recommended for effective climate change impact assessments.

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Sentinel satellite data monitoring of air pollutants with interpolation methods in Guayaquil, Ecuador

2023 , Mejía C. D. , Alvarez H. , Zalakeviciute R. , Macancela D. , Sanchez C. , Bonilla Bedoya, Santiago

In Ecuador, there is a limitation on air quality monitoring due to the cost of monitoring networks. Although air quality monitoring stations are instruments for air measurement, they do not cover an entire city due to their scope. Satellite remote sensing is now an effective tool to study atmospheric pollutants and has been applied to continuously assess a region and overcome the limitations of fixed stations. Despite the application of satellite data for air quality monitoring, there are some limitations, such as measurement frequency, cloud cover and wide spatial resolution, which do not allow the assessment of air pollution in cities. Therefore, downscaling, applying interpolation methods, is essential for continuous air quality monitoring at smaller scales. For this research, Nitrogen Dioxide (NO2) data from the Sentinel-5 satellite percussor was used in the city of Guayaquil for January–December 2020, which is considered before, during and after the COVID-19 quarantine. This mid-size port city does not have a permanent monitoring network, which prevents us from knowing the air quality. Due to the limitation of pixel size, this study used satellite data to apply interpolation techniques and reduce pixels to assess air quality. Two categories of interpolation were selected: deterministic and stochastic. The empirical Bayesian kriging (EBK) interpolation obtained a R2 of 0.9546, which was superior to the other methods applied. Therefore, the EBK method had the best accuracy for tropospheric NO2 concentration. Finally, the method used in this research can help monitor air quality in cities lacking continuous monitoring networks, as the reduction of the pixel size gives us a better pattern of pollutants. © 2023 The Authors

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Gradient boosting machine to assess the public protest impact on urban air quality

2021 , Zalakeviciute R. , Rybarczyk Y. , Alexandrino K. , Bonilla Bedoya, Santiago , Mejia D. , Bastidas M. , Diaz V.

Political and economic protests build-up due to the financial uncertainty and inequality spreading throughout the world. In 2019, Latin America took the main stage in a wave of protests. While the social side of protests is widely explored, the focus of this study is the evolution of gaseous urban air pollutants during and after one of these events. Changes in concentrations of NO2, CO, O3 and SO2 during and after the strike, were studied in Quito, Ecuador using two approaches: (i) inter-period observational analysis; and (ii) machine learning (ML) gradient boosting machine (GBM) developed business-as-usual (BAU) comparison to the observations. During the strike, both methods showed a large reduction in the concentrations of NO2 (31.5–32.36%) and CO (15.55–19.85%) and a slight reduction for O3 and SO2. The GBM approach showed an exclusive potential, especially for a lengthier period of predictions, to estimate strike impact on air quality even after the strike was over. This advocates for the use of machine learning techniques to estimate an extended effect of changes in human activities on urban gaseous pollution. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

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Central parks as air quality oases in the tropical Andean city of Quito

2024 , Zalakeviciute R. , Bonilla Bedoya, Santiago , Mejia Coronel D. , Bastidas M. , Buenano A. , Diaz-Marquez A.

Urban ecosystem is an intricate agglomeration of human, fauna and flora populations coexisting in natural and artificial environments. As a city develops and expands over time; it may become unbalanced, affecting the quality of ecosystem and urban services and leading to environmental and health problems. Fine particulate matter (particulate matter with aerodynamic diameter ≤2.5 μm - PM2.5) is the air pollutant posing the greatest risk to human health. Quito, the capital city of Ecuador, exhibits a high occurrence of exposure to unhealthy levels of PM2.5 due to a combination of natural and social variables. This study focused on three central parks of this high elevation city, investigating the spatial distribution of PM2.5 concentrations. The particle pollution was then modeled using Normalized Difference Vegetation Index (NDVI). Hazardous instantaneous levels of PM2.5 were consistently found on the edges of the parks along busy avenues, which are also the most frequented areas. This raises concerns about both short- and long-term exposures to toxic traffic pollution in recreational areas within urban dwellings in the global south. The NDVI model successfully predicted the spatial concentrations of PM2.5 in a smaller urban park, suggesting its potential application in other cities. However, further research is required to validate its effectiveness. © 2024 The Authors

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Urban–Rural Gradients Predict Educational Gaps: Evidence from a Machine Learning Approach Involving Academic Performance and Impervious Surfaces in Ecuador

2021 , Santos-García F. , Valdivieso K.D. , Rienow A. , Gairín J.

Academic performance (AP) is explained by a multitude of factors, principally by those related to socioeconomic, cultural, and educational environments. However, AP is less understood from a spatial perspective. The aim of this study was to investigate a methodology using a machine learning approach to determine which answers from a questionnaire-based survey were relevant for explaining the high AP of secondary school students across urban–rural gradients in Ecuador. We used high school locations to construct individual datasets and stratify them according to the AP scores. Using the Boruta algorithm and backward elimination, we identified the best predictors, classified them using random forest, and mapped the AP classification probabilities. We summarized these results as frequent answers observed for each natural region in Ecuador and used their probability outputs to formulate hypotheses with respect to the urban–rural gradient derived from annual maps of impervious surfaces. Our approach resulted in a cartographic analysis of AP probabilities with overall accuracies around 0.83–0.84% and Kappa values of 0.65–0.67%. High AP was primarily related to answers regarding the academic environment and cognitive skills. These identified answers varied depending on the region, which allowed for different interpretations of the driving factors of AP in Ecuador. A rural-to-urban transition ranging 8–17 years was found to be the timespan correlated with achievement of high AP. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

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Copper and Temperature Interactions Induce Differential Physiological and Metal Exclusion Responses in the Model Brown Macroalga Ectocarpus

2025 , Santillán Sarmiento, Alex , Paula S. M. Celis-Plá , A. John Moody , Claudio A. Saez , Murray T. Brown

The toxic effects of copper (Cu) excess in brown macroalgae have been well characterized. However, the interactive effects of increased temperatures, associated with climate change, and Cu stress on these macrophytes remain almost unexplored. In this study, we exposed the model brown seaweed Ectocarpus to different Cu concentrations (0, 0.8, 1.6, and 3.2 μM) at two different temperatures (15 and 25 °C). Relative growth rates decreased at 25 °C for the two highest Cu concentrations after 8 days of exposure, but a contrasting pattern was observed in the photosynthetic maximum quantum yield (Fv/Fm) and photosynthetic efficiency (α), where reductions were observed at 15 °C for the same Cu concentrations. Although no differences among treatments were observed for chlorophyll a (Chla) and chlorophyll c (Chlc), a reduction in concentration of the accessory pigment fucoxanthin (Fx) was only observed at 15 °C in all Cu treatments. Interestingly, at 25 °C, 20.1% less total Cu (intracellular + extracellularly bound) accumulated compared to 15 °C upon exposure to 3.2 μM Cu. Likewise, 33.1 and 23.8% less Cu accumulated intracellularly at 25 °C after exposure to 1.6 μM and 3.2 μM Cu, respectively. Additionally, at 25 °C about half of the Cu ions accumulated intracellularly and half extracellularly compared to 15 °C, where Cu accumulated mostly intracellularly at the two highest Cu concentrations. The results presented here provide valuable information to better understand the interactive effects of increased temperature and excess Cu in the stress response of Ectocarpus, suggesting that increased temperature helps to offset the negative impacts of exposure to high Cu concentrations.

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Mapping 50 years of contribution to the development of soil quality biological indicators

2023 , Bonilla Bedoya, Santiago , Valencia K. , Herrera M.Á. , López-Ulloa M. , Donoso D.A. , Macedo Pezzopane J.E.

Biological indicators of soil quality express the capacity of a soil to maintain its ecosystem functions and services between socio-ecosystem inflection thresholds; therefore, they are determinants in management and land use decisions. However, their development until a few decades ago was limited for several reasons: reductionism and early development of other dimensions, such as physical and chemical indicators or their methodological complexity, thus affecting the importance given to biological factors and the integral evaluation of soil quality or health. Thus, this review presents a mapping of the scientific contributions of the last 50 years oriented to the theoretical and methodological development of biological indicators of soil quality, identifying their development and application in these decades. We conducted a bibliometric analysis that allowed us to present an overview of the field with respect to scientific production: temporality, geographical origin, institutional origin, journals that promote the development of the field, articles with greater influence by citation in the field of study, and the co-occurrences of these indicators in research. This analysis was complemented at the second stage by a systematic review of the literature with the greatest impact by citation. We found 2320 scientific papers distributed mainly in the United States (17.8%), China (12.2%), Brazil (8.3%), India (6.3%), and European Mediterranean countries, such as Spain, France, and Italy (14.2%). Our review showed 25 biological indicators with the highest occurrence; for example, microbial biomass (1 1 8), enzymatic activity (90), and organic matter (78); other indicators, such as earthworms, nematodes, or springtails, are also reported. All indicators showed relationships, to a greater or lesser extent, with soil biodiversity and its functions in the landscape. Important advances in soil indicators have developed gradually in the last few decades, with scientific efforts mainly concentrated in developed and emerging countries. In the last decade, the production curve continues with a growth trend., and research questions in the field revolve around the linkage of diversity and function from a molecular point of view. The scope goes beyond productivity, manifesting the real need to conserve and manage the ecosystem services of a limited and non-renewable natural resource. Pioneering research should begin to report on the scope of soil biological monitoring and its influence on policy, management, and land use. Finally, the promotion of research networks with developing countries can foster the development of regional and local soil monitoring policies in these regions. © 2023 The Author(s)

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Vulnerability assessment of natural heritage in the North-Eastern Ecuadorian Amazon using land use cover and nature protection status

2024 , J. Durango-Cordero , M. Saqalli , Bonilla Bedoya, Santiago , A. Elger

This study evaluates the vulnerability of natural heritage in the Northeast Ecuadorian Amazon (NEA), from the perspective of intrinsic vulnerability. Therefore, two proxy indicators of vulnerability were established: (i) the ecological integrity vulnerability index (EIVI), indicating the potential loss of ecological integrity, assessed by protection status (2018); (ii) the biological diversity vulnerability index (BVI), deriving the potential loss of biological diversity, using land cover/land use (2014). Biodiversity values were derived with land cover-related biodiversity data, and (iii) and compared with spatial congruence/correlation between (i) and (ii). The EIVI was directly derived using protection status, which defines vulnerability levels by ranking them according to corresponding levels of anthropic development allowance. A robust relationship between land use classes and species richness was found for both endemic vascular plants in neotropical regions and multi-taxa in tropical forests worldwide, validating the BVI. Furthermore, the moderate spatial correlation between protection status and land cover (r = 0.52) may be partially explained by 3,060 km2 of unprotected primary forest. Overall, 42 % of the NEA have a high degree of congruence between potential biodiversity and protection status. In conclusion, this study provides insights into nature conservation efforts in areas with sparse biodiversity data using readily available geographic information.

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