Centro de Investigación para el Territorio y el Hábitat Sostenible
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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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Patterns of timber harvesting and its relationship with sustainable forest management in the western Amazon, Ecuador case

2017 , Bonilla Bedoya, Santiago , Estrella-Bastidas A. , Ordoñez M. , Sánchez A. , Herrera M.A.

The Amazon rainforest lies within the most diverse forest ecosystem in the world. However, a large part of the tropical rainforest is being degraded because of timber harvesting without any sustainability criteria and owing to a limited understanding of the effects of forest exploitation. The Ecuadorian Amazon (EA) is part of the Andes Amazon (AA), an area covered by five countries (Venezuela, Colombia, Ecuador, Peru and Bolivia). This research identified the patterns of legal timber harvesting in the EA and determined current trends with respect to mostly harvested forest species. Two harvesting programs aimed at small farmers prevail in the EA: first, naturally regenerated trees felling program, and simplified timber harvesting programs in native forests. Considering the surface and volume of logging, significant differences were detected between logging procedures and ecosystems in the region. Two hundred and thirty-two genera are registered for harvest and, 51.93% of the total harvesting volume comes from eight genera and ten species. This research shows that in fallows of fragmented forest ecosystems, small farmers are harvesting fast-growing pioneer species. Maintaining a sustainable production in timber harvesting depends, by and large, on the harvesting and felling programs established on small farms. © 2017 Taylor & Francis.

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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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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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The effect of national protest in Ecuador on PM pollution

2021 , Zalakeviciute R. , Alexandrino K. , Mejia D. , Bastidas M.G. , Oleas N.H. , Gabela D. , Chau P.N. , Bonilla Bedoya, Santiago , Diaz V. , Rybarczyk Y.

Particulate matter (PM) accounts for millions of premature deaths in the human population every year. Due to social and economic inequality, growing human dissatisfaction manifests in waves of strikes and protests all over the world, causing paralysis of institutions, services and circulation of transport. In this study, we aim to investigate air quality in Ecuador during the national protest of 2019, by studying the evolution of PM2.5 (PM ≤ 2.5 µm) concentrations in Ecuador and its capital city Quito using ground based and satellite data. Apart from analyzing the PM2.5 evolution over time to trace the pollution changes, we employ machine learning techniques to estimate these changes relative to the business-as-usual pollution scenario. In addition, we present a chemical analysis of plant samples from an urban park housing the strike. Positive impact on regional air quality was detected for Ecuador, and an overall − 10.75 ± 17.74% reduction of particulate pollution in the capital during the protest. However, barricade burning PM peaks may contribute to a release of harmful heavy metals (tire manufacture components such as Co, Cr, Zn, Al, Fe, Pb, Mg, Ba and Cu), which might be of short- and long-term health concerns. © 2021, The Author(s).

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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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Evaluating night-time light sources and correlation with socio-economic development using high-resolution multi-spectral Jilin-1 satellite imagery of Quito, Ecuador

2023 , Watson C.S. , Elliott J.R. , Córdova M. , Menoscal J. , Bonilla Bedoya, Santiago

Artificial light at night (ALAN) has positive and negative effects on social, economic, environmental, and ecological systems, and will increase with urban expansion. In this study, we used a multi-spectral 1.5 m resolution night-time acquisition from a Jilin-1 satellite over the city of Quito, Ecuador, to evaluate spatial lighting patterns in an expanding and topography complex-built environment. We demonstrated a requirement for robust georeferencing and orthorectification due to the complex topography, with errors on the order of 4–6 pixels (5.8–8.4 m CE95). We also quantified differences in observed brightness due to the image acquisition and local geometry. Street light type was distinguishable between high-pressure sodium (HPS) and light emitting diode (LED) sources (F1-score = 0.72–0.83) using a shark random forest decision tree approach. Additionally, street lights could be located within 10 m (F1-score = 0.71) with balanced omissions and commissions. Spatial trends revealed that the road network was the dominant source of illumination, accounting for 45% of illuminated pixels, whereas built-up areas accounted for 23%. Overall, 68% of all illuminated pixels were on or within 10 m of the road. Higher socio-economic development was associated with higher proportions of LED lighting, greater road network lighting and density of street lights, higher overall radiance for built-up areas and the road network, and greater coverage and illumination of designated green spaces. The broad impacts of ALAN mean that addressing the causes and consequences of lighting inequalities is a complex issue. Nonetheless, Jilin-1 night-time imagery offers a low-cost way to map and monitor light sources at high-resolution that will be beneficial to city-planners and progressing Sustainable Development Goals. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

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Urban soil management in the strategies for adaptation to climate change of cities in the Tropical Andes

2022 , Bonilla Bedoya, Santiago , Ángel Herrera, M. , Vaca, A. , Salazar, L. , Zalakeviciute, R. , Mejía, D. , López-Ulloa, M.

The unique characteristics of a city amplify the impacts of climate change; therefore, urban planning in the 21st century is challenged to apply mitigation and adaptation strategies that ensure the collective well-being. Despite advances in monitoring urban environmental change, research on the application of adaptation-oriented criteria remains a challenge in urban planning in the Global South. This study proposes to include urban land management as a criterion and timely strategy for climate change adaptation in the cities of the Tropical Andes. Here, we estimate the distribution of the soil organic carbon stock (OCS) of the city of Quito (2,815 m.a.s.l.; population 2,011,388; 197.09 km2) in the following three methodological moments: i) field/laboratory: city-wide sampling design established to collect 300 soil samples (0–15 cm) and obtain data on organic carbon (OC) concentrations in addition to 30 samples for bulk density (BD); ii) predictors: geographic, spectral and anthropogenic dimensions established from 17 co-variables; and iii) spatial modeling: simple multiple regression (SMRM) and random forest (RFM) models of organic carbon concentrations and density as well as OCS stock estimation. We found that the spatial modeling techniques were complementary; however, SMRM showed a relatively higher fit both (OC: r2 = 20%, BD: r2 = 16%) when compared to RFM (OC: r2 = 8% and BD: r2 = 5%). Thus, soil carbon stock (0–0.15 m) was estimated with a spatial variation that fluctuated between 9.89 and 21.48 kg/m2; whereas, RFM showed fluctuations between 10.38 and 17.67 kg/m2. We found that spatial predictors (topography, relative humidity, precipitation, temperature) and anthropogenic predictors (population density, roads, vehicle traffic, land cover) positively influence the model, while spatial predictors have little influence and show multicollinearity with relative humidity. Our research suggests that urban land management in the 21st century provides key information for adaptation and mitigation strategies aimed at coping with global and local climate variations in the cities of the Tropical Andes. © 2022 Elsevier B.V.

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Urban soils as a spatial indicator of quality for urban socio-ecological systems

2021 , Bonilla Bedoya, Santiago , López-Ulloa M. , Mora-Garcés A. , Macedo-Pezzopane J.E. , Salazar L. , Herrera M.Á.

The development of criteria and indicators to quantify the transition to sustainability of the urban socio-ecological systems quality is determinant for planning policies and the 21st century urban agenda. This study models the spatial variation in the concentration and distribution of some macronutrients, micronutrients, and trace nutrients in the soil of a high-altitude city in the Andes. Meanwhile, machine learning methods were employed to study some interactions between the different dimensions that constitute an urban socio-ecosystem that caused these variations. We proposed a methodology that considered two phases: a) field work to collect data on 300 soil samples; laboratory analysis to measure the concentrations of 24 macronutrients, micronutrients, and trace nutrients; and the design of geophysical, spectral, and urban co-variables; b) statistical and geo-informatics analysis, where multivariate analysis grouped the elements into factors; and, machine learning integrated with co-variables was applied to derive the intensity of each factor across the city. Multivariate statistics described the variation in soil co-concentrations with a moderate percentage (42%). Four factors were determined that grouped some of the analyzed elements, as follows: F1 (Zn, S, Cu, Pb, Ni, and Cr), F2 (Ba, Ag, K, In, and Mg), F3 (B, V, Li, and Sr), and F4 (Si and Mn). The percentage R2 out-of-bag of the spatial model were: F1 = 20%, F2 = 8%, F3 = 14%, and F4 = 10%. Our outputs show that the enrichment and contamination by anthropogenic factors, such as the increase in population density, land use, road network, and traffic generated by fossil fuel vehicles, should be prioritized in urban planning decisions. © 2021

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Distinguishing original and non-original stands at the zhanjiang mangrove national nature reserve (P.r. china): Remote sensing and gis for conservation and ecological research

2021 , Durango-Cordero J. , Satyanarayana B. , Chan J.C.-W. , Bogaert J. , Dahdouh-Guebas F.

The present research developed a novel methodological framework to differentiate natural mangrove stands (i.e., original), from stands which were planted and stands naturally established after interaction between planted and non-planted stands (e.g., through pollination, i.e., non-original). Ground-truth and remote sensing data were collected for Zhanjiang Mangrove National Nature Reserve (ZMNNR) in P.R. China. First, satellite images of Corona (1967) and GeoEye-1 (2009) were overlaid to identify original (1967) and non-original (2009) mangrove stands. Second, in both stands a total of 75 in situ plots (25 m2) were measured for ground-truthing of tree structural parameters including height, density, basal area and Complexity Index (CI). From temporal satellite data, we identify 236.12 ha of original mangrove and 567.88 ha of non-original mangrove in the reserve. Averaged measurements of the original mangrove stands, i.e., stem density (1164 nos. 0.1 ha−1), basal area (90.3 m2 0.1 ha−1) and CI (100.59), indicated that they were in a state of maturity and less disturbed compared to the non-original mangroves (density, 1241 nos. 0.1 ha−1; basal area, 4.92 m2 0.1 ha−1 and CI, 55.65). The Kruskal–Wallis test showed significant differentiation between the original and non-original mangrove tree structural parameters: Kandelia obovata’s density, X2 = 34.78, d.f. = 1, p = 0.001; basal area, X2 = 108.15, d.f. = 1, p = 0.001; Rizhopora stylosa’s density, X2 = 64.03, d.f. = 1, p = 0.001; basal area, X2 = 117.96, d.f. = 1, p = 0.001. The latter is also evident from the clustering plots generated from the Principal Component Analysis (PCA). Vegetation dynamics at the ZMNNR also enabled us to compare the species composition and distribution patterns with other Indo-West Pacific regions. Overall, the present study not only highlights the advantage of >50 years old satellite data but also provide a benchmark for future ecological research, conservation and management of the ZMNNR. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

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