Individual Tree Diameter and Height Growth Models for 30 Tree Species in Mixed-Species and Uneven-Aged Forests of Mexico

Lack of knowledge of individual tree growth in species-rich, mixed forest ecosystems impedes their sustainable management. In this study, species-specific models for predicting individual diameter at breast height (dbh) and total tree height (h) growth were developed for 30 tree species growing in mixed and uneven-aged forest stands in Durango, Mexico. Growth models were also developed for all pine, all oaks, and all other species of the genus Arbutus (strawberry trees). A database of 55,158 trees with remeasurements of dbh and h of a 5-year growth period was used to develop the models. The data were collected from 217 stem-mapped plots located in the Sierra Madre Occidental (Mexico). Weighted regression was used to remove heteroscedasticity from the species-specific dbh and h growth models using a power function of the tree size independent variables. The final models developed in the present study to predict dbh and total tree height growth included size variables, site factors, and competition variables in their formulation. The developed models fitted the data well and explained between 98 and 99% and of the observed variation of dbh, and between 77 and 98% of the observed variation of total tree height for the studied species and groups of species. The developed models can be used for estimating the individual dbh and h growth for the analyzed species and can be integrated in decision support tools for management planning in these mixed forest ecosystemsThis study was supported by the National Forestry Commission (CONAFOR) and the Mexican National Council for Science and Technology (CONACYT)S

Near Real-Time Automated Early Mapping of the Perimeter of Large Forest Fires from the Aggregation of VIIRS and MODIS Active Fires in Mexico

In contrast with current operational products of burned area, which are generally available one month after the fire, active fires are readily available, with potential application for early evaluation of approximate fire perimeters to support fire management decision making in near real time. While previous coarse-scale studies have focused on relating the number of active fires to a burned area, some local-scale studies have proposed the spatial aggregation of active fires to directly obtain early estimate perimeters from active fires. Nevertheless, further analysis of this latter technique, including the definition of aggregation distance and large-scale testing, is still required. There is a need for studies that evaluate the potential of active fire aggregation for rapid initial fire perimeter delineation, particularly taking advantage of the improved spatial resolution of the Visible Infrared Imaging Radiometer (VIIRS) 375 m, over large areas and long periods of study. The current study tested the use of convex hull algorithms for deriving coarse-scale perimeters from Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) active fire detections, compared against the mapped perimeter of the MODIS collection 6 (MCD64A1) burned area. We analyzed the effect of aggregation distance (750, 1000, 1125 and 1500 m) on the relationships of active fire perimeters with MCD64A1, for both individual fire perimeter prediction and total burned area estimation, for the period 2012–2108 in Mexico. The aggregation of active fire detections from MODIS and VIIRS demonstrated a potential to offer coarse-scale early estimates of the perimeters of large fires, which can be available to support fire monitoring and management in near real time. Total burned area predicted from aggregated active fires followed the same temporal behavior as the standard MCD64A1 burned area, with potential to also account for the role of smaller fires detected by the thermal anomalies. The proposed methodology, based on easily available algorithms of point aggregation, is susceptible to be utilized both for near real-time and historical fire perimeter evaluation elsewhere. Future studies might test active fires aggregation between regions or biomes with contrasting fuel characteristics and human activity patterns against medium resolution (e.g., Landsat and Sentinel) fire perimeters. Furthermore, coarse-scale active fire perimeters might be utilized to locate areas where such higher-resolution imagery can be downloaded to improve the evaluation of fire extent and impactFunding for this study was provided by CONAFOR/CONACYT Projects “CO2-2014-3-252620” and “CO-2018-2-A3-S-131553” for the development and enhancement of a Forest Fire Danger Prediction System for Mexico, funded by the Sectorial Fund for forest research, development and technological innovation “Fondo Sectorial para la investigación, el desarrollo y la innovación tecnológica forestal”S

Temporal patterns of active fire density and its relationship with a satellite fuel greenness index by vegetation type and region in Mexico during 2003-2014

Background: Understanding the temporal patterns of fire occurrence and their relationships with fuel dryness is key to sound fire management, especially under increasing global warming. At present, no system for prediction of fire occurrence risk based on fuel dryness conditions is available in Mexico. As part of an ongoing national-scale project, we developed an operational fire risk mapping tool based on satellite and weather information. Results: We demonstrated how differing monthly temporal trends in a fuel greenness index, dead ratio (DR), and fire density (FDI) can be clearly differentiated by vegetation type and region for the whole country, using MODIS satellite observations for the period 2003 to 2014. We tested linear and non-linear models, including temporal autocorrelation terms, for prediction of FDI from DR for a total of 28 combinations of vegetation types and regions. In addition, we developed seasonal autoregressive integrated moving average (ARIMA) models for forecasting DR values based on the last observed values. Most ARIMA models showed values of the adjusted coefficient of determination (R2 adj) above 0.7 to 0.8, suggesting potential to forecast fuel dryness and fire occurrence risk conditions. The best fitted models explained more than 70% of the observed FDI variation in the relation between monthly DR and fire density. Conclusion: These results suggest that there is potential for the DR index to be incorporated in future fire risk operational tools. However, some vegetation types and regions show lower correlations between DR and observed fire density, suggesting that other variables, such as distance and timing of agricultural burn, deserve attention in future studiesAntecedentes: Una adecuada planificación del manejo del fuego requiere de la comprensión de los patrones temporales de humedad del combustible y su influencia en el riesgo de incendio, particularmente bajo un escenario de calentamiento global. En la actualidad en México no existe ningún sistema operacional para la predicción del riesgo de incendio en base al grado de estrés hídrico de los combustibles. Un proyecto de investigación nacional actualmente en funcionamiento, tiene como objetivo el desarrollo de un sistema operacional de riesgo y peligro de incendio en base a información meteorológica y de satélite para México. Este estudio pertenece al citado proyecto Resultados: Se observaron en el país distintas tendencias temporales en un índice de estrés hídrico de los combustibles basado en imágenes MODIS, el índice “dead ratio” (DR), y en las tendencias temporales de un ìndice de densidad de incendios (FDI), en distintos tipos de vegetación y regiones del país. Se evaluaron varios modelos lineales y potenciales, incluyendo términos para la consideración de la autocorrelación temporal, para la predicción de la densidad de incendios a partir del índice DR para un total de 28 tipos de vegetación y regiones. Se desarrollaron además modelos estacionales autoregresivos de media móvil (ARIMA en inglés) para el pronóstico del índice DR a partir de los últimos valores observados. La mayoría de los modelos ARIMA desarrollados mostraron valores del coeficiente de determinación ajustado (R2 adj) por encima de 0.7 to 0.8, sugiriendo potencial para ser empleados para un pronóstico del estrés hídrico de los combustibles y las condiciones de riesgo de ocurrencia de incendio. Con respecto a los modelos que relacionan los valores mensuales de DR con FDI, la mayoría de ellos explicaron más del 70% de la variabilidad observada en FDI. Conclusiones: Los resultados sugirieron potencial del índice DR para ser incluido en futuras herramientas operacionales para determinar el riesgo de incendio. En algunos tipos de vegetación y regiones se obtuvieron correlaciones más reducidas entre el índice DR y los valores observados de densidad de incendios, sugiriendo que el papel de otras variables tales como la distancia y el patrón temporal de quemas agrícolas debería ser explorado en futuros estudiosFunding for this work was provided by CONAFOR-CONACYT Project 252620 “Development of a Fire Danger System for Mexico.” This work was also cofinanced by the Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria and European Social Fund (Dr. E. Jiménez grant)S

Calidad en servicio: El arte de la satisfacción al cliente

México es un país de aproximadamente 90 millones de habitantes, en el que 39.3% de la Población Económicamente Activa (PEA) trabaja en el sector servicios (Encuesta Nacional de empleo 2004); en un país grande y joven con muchas necesidades insatisfechas y, por lo tanto, con mucha oportunidades

Evaluating a New Relative Phenological Correction and the Effect of Sentinel-Based Earth Engine Compositing Approaches to Map Fire Severity and Burned Area

The remote sensing of fire severity and burned area is fundamental in the evaluation of fire impacts. The current study aimed to: (i) compare Sentinel-2 (S2) spectral indices to predict field-observed fire severity in Durango, Mexico; (ii) evaluate the effect of the compositing period (1 or 3 months), techniques (average or minimum), and phenological correction (constant offset, c, against a novel relative phenological correction, rc) on fire severity mapping, and (iii) determine fire perimeter accuracy. The Relative Burn Ratio (RBR), using S2 bands 8a and 12, provided the best correspondence with field-based fire severity (FBS). One-month rc minimum composites showed the highest correspondence with FBS (R2 = 0.83). The decrease in R2 using 3 months rather than 1 month was ≥0.05 (0.05–0.15) for c composites and <0.05 (0.02–0.03) for rc composites. Furthermore, using rc increased the R2 by 0.05–0.09 and 0.10–0.15 for the 3-month RBR and dNBR compared to the corresponding c composites. Rc composites also showed increases of up to 0.16–0.22 and 0.08–0.11 in kappa values and overall accuracy, respectively, in mapping fire perimeters against c composites. These results suggest a promising potential of the novel relative phenological correction to be systematically applied with automated algorithms to improve the accuracy and robustness of fire severity and perimeter evaluations

Fuel-Specific Aggregation of Active Fire Detections for Rapid Mapping of Forest Fire Perimeters in Mexico

Context and Background. Active fires have the potential to provide early estimates of fire perimeters, but there is a lack of information about the best active fire aggregation distances and how they can vary between fuel types, particularly in large areas of study under diverse climatic conditions. Objectives. The current study aimed at analyzing the effect of aggregation distances for mapping fire perimeters from active fires for contrasting fuel types and regions in Mexico. Materials and Methods. Detections of MODIS and VIIRS active fires from the period 2012–2018 were used to obtain perimeters of aggregated active fires (AGAF) at four aggregation distances (750, 1000, 1125, and 1500 m). AGAF perimeters were compared against MODIS MCD64A1 burned area for a total of 24 fuel types and regions covering all the forest area of Mexico. Results/findings. Optimum aggregation distances varied between fuel types and regions, with the longest aggregation distances observed for the most arid regions and fuel types dominated by shrubs and grasslands. Lowest aggregation distances were obtained in the regions and fuel types with the densest forest canopy and more humid climate. Purpose/Novelty. To our best knowledge, this study is the first to analyze the effect of fuel type on the optimum aggregation distance for mapping fire perimeters directly from aggregated active fires. The methodology presented here can be used operationally in Mexico and elsewhere, by accounting for fuel-specific aggregation distances, for improving rapid estimates of fire perimeters. These early fire perimeters could be potentially available in near-real time (at every satellite pass with a 12 h latency) in operational fire monitoring GIS systems to support rapid assessment of fire progression and fire suppression planning

Fuel-Specific Aggregation of Active Fire Detections for Rapid Mapping of Forest Fire Perimeters in Mexico

Context and Background. Active fires have the potential to provide early estimates of fire perimeters, but there is a lack of information about the best active fire aggregation distances and how they can vary between fuel types, particularly in large areas of study under diverse climatic conditions. Objectives. The current study aimed at analyzing the effect of aggregation distances for mapping fire perimeters from active fires for contrasting fuel types and regions in Mexico. Materials and Methods. Detections of MODIS and VIIRS active fires from the period 2012–2018 were used to obtain perimeters of aggregated active fires (AGAF) at four aggregation distances (750, 1000, 1125, and 1500 m). AGAF perimeters were compared against MODIS MCD64A1 burned area for a total of 24 fuel types and regions covering all the forest area of Mexico. Results/findings. Optimum aggregation distances varied between fuel types and regions, with the longest aggregation distances observed for the most arid regions and fuel types dominated by shrubs and grasslands. Lowest aggregation distances were obtained in the regions and fuel types with the densest forest canopy and more humid climate. Purpose/Novelty. To our best knowledge, this study is the first to analyze the effect of fuel type on the optimum aggregation distance for mapping fire perimeters directly from aggregated active fires. The methodology presented here can be used operationally in Mexico and elsewhere, by accounting for fuel-specific aggregation distances, for improving rapid estimates of fire perimeters. These early fire perimeters could be potentially available in near-real time (at every satellite pass with a 12 h latency) in operational fire monitoring GIS systems to support rapid assessment of fire progression and fire suppression planning

Alterations in bacterial communities, SCFA and biomarkers in an elderly HIV-positive and HIV-negative population in western Mexico

Abstract Background The study of stool microbiota has taken great relevance in the last years, given its role in the maintenance of the intestinal metabolic, physiological, and immunological homeostasis, as well as, its effect over HIV biomarkers levels such as CD4/CD8 ratio, high sensitivity C-Reactive Protein (hs-CRP), related to poor outcomes (rapid progression to AIDS). Several efforts have been made to characterize the gut microbiome. In HIV infection, most of the studies report the presence of a dysbiotic pattern; however, few of them have made an approach in elderly HIV-positive subjects despite the fact that nowadays this subgroup is rising. In this study, we compared the composition of faecal microbiota, Short Chain Fatty Acids (SCFAs), and systemic biomarkers between elderly HIV-positive and HIV-negative subjects. Methods A cross-sectional study with 18 HIV-negative controls and 20 HIV-positive patients. The quantification of Bacteroidetes, Firmicutes, Proteobacteria, Actinobacteria, Lactobacillus, Enterobacteriaceae, Bifidobacterium, Escherichia coli, Clostridium leptum, Clostridium coccoides was performed in faecal samples by qPCR. The analysis was performed by calculating the ΔCq of each microorganism using 16S rDNA as a reference gene. Faecal SCFAs were measured by HPLC. The hs-CRP and sCD14 were performed by ELISA. Results An increase in the Firmicutes/Bacteroidetes ratio, coupled with a significant increase in the proteobacteria phylum was detected in HIV-positive subjects. In contrast, a decrease in the Clostridium leptum group was observed. Nevertheless, these elderly HIV-positive patients showed higher levels of total SCFAs mainly by an augmented propionic acid values, compared to HIV-negative subjects. Whereas high levels of hs-CRP were positively correlated with sCD14 in the HIV-positive group. Conclusions Alterations in bacterial communities reveals a dysbiotic state related to an unbalance of faecal SCFAs. Therefore, these intestinal conditions might drive an increase of poor prognostic biomarkers in elderly HIV-positive subjects

Memoria del simposio “Hacia el bicentenario de la Independencia. Antiguo Estado de México”

Contiene 18 trabajos presentados en el simposium “Hacia el bicentenario de la Independencia de México. Antiguo Estado de México”, organizado por la Universidad Autónoma del Estado de México, a través del Centro de Investigación en Ciencias Sociales y Humanidades (CICSyH) y la Facultad de Humanidades de la Universidad Autónoma del Estado de México, y el Centro de Estudios Históricos de El Colegio Mexiquense, A. C