Estimating biomass of mixed and uneven-aged forests using spectral data and a hybrid model combining regression trees and linear models

The Sierra Madre Occidental mountain range (Durango, Mexico) is of great ecological interest because of the high degree of environmental heterogeneity in the area. The objective of the present study was to estimate the biomass of mixed and uneven-aged forests in the Sierra Madre Occidental by using Landsat-5 TM spectral data and forest inventory data. We used the ATCOR3 ® atmospheric and topographic correction module to convert remotely sensed imagery digital signals to surface reflectance values. The usual approach of modeling stand variables by using multiple linear regression was compared with a hybrid model developed in two steps: in the first step a regression tree was used to obtain an initial classification of homogeneous biomass groups, and multiple linear regression models were then fitted to each node of the pruned regression tree. Cross-validation of the hybrid model explained 72.96% of the observed stand biomass variation, with a reduction in the RMSE of 25.47% with respect to the estimates yielded by the linear model fitted to the complete database. The most important variables for the binary classification process in the regression tree were the albedo, the corrected readings of the short-wave infrared band of the satellite (2.08-2.35 µm) and the topographic moisture index. We used the model output to construct a map for estimating biomass in the study area, which yielded values of between 51 and 235 Mg ha-1. The use of regression trees in combination with stepwise regression of corrected satellite imagery proved a reliable method for estimating forest biomass.This research was supported by SEPPROMEP (Project: Seguimiento y Evaluación de Sitios Permanentes de Investigación Forestal y el Impacto Socioeconómico del anejo Forestal en el Norte de México)S

QGIS a constantly growing free and open-source geospatial software contributing to scientific development

QGIS is the most popular free geospatial software in the world. QGIS belongs to the Open-Source Geospatial Foundation (OSGeo). Among the main strengths of this Geographic Information Systems are: the incorporation of tools via plugins, and a community of users and developers in constant growth. Despite the importance on the use of QGIS on the scientific community, to date there are no systematic studies indicating how the acceptance of this software has evolved through time. Therefore, the objective of this research was to characterize the scientific production and extent where QGIS has been used as their main geospatial tool. We conducted a bibliometric analysis of documents published in Scopus from 2005 to 2020 (931 manuscripts). The annual rate of publications increase was 40.3%. We found strong and positive correlations regarding the number of contributing code programmers (r=0.66, p<0.005); and the total income of the QGIS project (r=0.88, p<0.001). Seventy-two percent of the publications were included in six fields of study, being Earth and Planetary Sciences the most representative. Italy was the country with larger scientific production, while the USA was the most influential country (being the first, regarding the number of citations). In terms of the countries, the larger number of papers found were from Portugal, Italy, Brazil, and France. The International Archives of the Photogrammetry Remote Sensing and Spatial Information Sciences - ISPRS Archives stands among journals with the largest number of publications (47). In terms of collaborative networks among countries, we found strong links between authors from Germany, Switzerland, Greece, and Spain. Author network analysis showed three solid networks in different fields of study. We observed a favorable trend in the acceptance of QGIS across the world and a widespread development of collaborative networks. The present paper allowed increase the knowledge of geographic information systems, especially the development of scientific production using QGIS

Avances científicos del búho manchado mexicano (Strix occidentalis lucida Nelson 1903)

Objective: Evaluate quantitatively the research trends of the Mexican Spotted Owl. Design/methodology/approach: Scientific articles published between 2012 and February 2020 for the Mexican spotted owl were analyzed. The content of each article was classified into nine categorical variables: 1) biological description, 2) habitat, 3) distribution and abundance, 4) dispersion and movement, 5) diet and prey, 6) genetics and reproduction, 7) threats, 8) predictive models and 9) others. The published information was classified into similar groups by means of a hierarchical cluster analysis. Subsequently, were calculated and graphed the frequency and proportional representation of each attribute generated by country. Results: Of the 23 scientific articles analyzed, the most studied attribute was habitat. The hierarchical cluster analysis grouped all the published information into five representative topics: a) habitat relationships, b) threats, c) distribution, d) bibliographic review and e) population relationship. The United States was the country with the highest scientific contribution. However, in the last three years of the period studied, publications in Mexico increased. Limitations on study/implications: This study analyzes the research trends of the Mexican spotted owl and provides an overview for future research. Findings/conclusions: There is little published information for this spotted owl subspecies. Although the characteristics of the habitat are widely described; it is necessary to venture into more complex ecological phenomena.Objetivo: Evaluar cuantitativamente las tendencias de la investigación del Búho Manchado Mexicano. Diseño/metodología/aproximación: Se analizaron los artículos científicos publicados entre 2012 y febrero de 2020 para el búho manchado mexicano. El contenido de cada artículo se clasificó en nueve variables categóricas: 1) descripción biológica, 2) hábitat, 3) distribución y abundancia, 4) dispersión y movimiento, 5) dieta y presas, 6) genética y reproducción, 7) amenazas, 8) modelos predictivos y 9) otros. La información publicada, se clasificó en grupos similares mediante un análisis de conglomerado jerárquico. Posteriormente, se calcularon y graficaron la frecuencia y representación proporcional de cada atributo generado por país. Resultados: De los 23 artículos científicos analizados, el atributo más estudiado fue el hábitat. El análisis de conglomerados jerárquicos agrupó toda la información publicada en cinco temas representativos:&nbsp; a) relaciones del hábitat, b) amenazas, c) distribución, d) revisión bibliográfica y e) relación de las poblaciones. Estados Unidos fue el país con mayor contribución científica. Sin embargo, en los últimos tres años del periodo estudiado, las publicaciones en México incrementaron. Limitaciones del estudio/implicaciones: Este estudio analiza las tendencias de investigación del búho manchado mexicano y permite establecer un panorama para investigaciones futuras. Hallazgos/conclusiones: Existe poca información publicada para esa subespecie de búho manchado. Aunque las características del hábitat son ampliamente descritas; es necesario incursionar en fenómenos ecológicos más complejos

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

Co-limitation towards lower latitudes shapes global forest diversity gradients

The latitudinal diversity gradient (LDG) is one of the most recognized global patterns of species richness exhibited across a wide range of taxa. Numerous hypotheses have been proposed in the past two centuries to explain LDG, but rigorous tests of the drivers of LDGs have been limited by a lack of high-quality global species richness data. Here we produce a high-resolution (0.025° × 0.025°) map of local tree species richness using a global forest inventory database with individual tree information and local biophysical characteristics from ~1.3 million sample plots. We then quantify drivers of local tree species richness patterns across latitudes. Generally, annual mean temperature was a dominant predictor of tree species richness, which is most consistent with the metabolic theory of biodiversity (MTB). However, MTB underestimated LDG in the tropics, where high species richness was also moderated by topographic, soil and anthropogenic factors operating at local scales. Given that local landscape variables operate synergistically with bioclimatic factors in shaping the global LDG pattern, we suggest that MTB be extended to account for co-limitation by subordinate drivers

Analysis of Near-Surface Temperature Lapse Rates in Mountain Ecosystems of Northern Mexico Using Landsat-8 Satellite Images and ECOSTRESS

Mountain ecosystems provide environmental goods, which can be threatened by climate change. Near-Surface Temperature Lapse Rate (NSTLR) is an essential factor used for thermal and hydrological analysis in mountain ecosystems. The aims of the present study were to estimate NSTLR and to identify its relationship with aspect, Local solar zenith angle (LSZA) and Evaporative Stress Index (ESI) for two seasons of the year in a mountain ecosystem at the North of Mexico. Normalized Land Surface Temperature (NLST) was estimated using environmental and topographical variables. LSZA was calculated from slope to consider the effect of solar position. NSTLR was estimated through simple linear models. Observed NSTLR was 9.4 °C km−1 for the winter and 14.3 °C km−1 for the summer. Our results showed variation in NSTLR by season. In addition, aspect, LSZA and ESI also influenced NSTLR regulation. In addition, Northwest and West aspects exhibited the highest NSTLR. LSZA angles closest to 90° were related with a decrease in NSTLR for both seasons. Finally, ESI values associated with less evaporative stress were related to lower NSTLR. These results suggest potential of Landsat-8 LST and ECOSTRESS ESI to capture interactions of temperature, topography, and water stress in complex ecosystems

Effect of altitude, slope and geographic exposure on tree fern distribution

Antecedentes y Objetivos: El conocimiento de los rasgos topográficos de un sitio es importante para comprender la diversidad local y monitorear la respuesta de las plantas de alto interés de conservación al cambio climático o al cambio de uso de suelo. El objetivo de este trabajo fue examinar el patrón de distribución de cuatro especies de helechos arborescentes en función de la altitud, la exposición y la pendiente a lo largo de un continuo altitudinal.Métodos: Se estudió el efecto de la altitud, pendiente y exposición geográfica en la distribución de Alsophila firma, Cyathea bicrenata, Cyathea myosuroides y Sphaeropteris horrida, en La Chinantla, al norte de Oaxaca, México. La hipótesis de homogeneidad de proporciones a los factores topográficos se verificó con la prueba de Chi cuadrada y la magnitud de incidencia mediante funciones polinómicas.Resultados clave: Se observaron diferencias significativas entre las proporciones de cada especie en función de cada variable topográfica. En promedio, la pendiente mostró un índice de importancia 43.48 veces más que la orientación geográfica y 2.50 veces más que la altitud. Se observaron similitudes entre el nicho parcial de Cyathea bicrenata y de Alsophila firma, pero disimilitudes entre Alsophila firma y Cyathea myosuroides. Conclusiones: La distribución de proporciones de los helechos arborescentes a nivel local es discontinua y no uniforme, atribuible a la acción de los factores locales predominantes, principalmente a la topografía. Una topografía heterogénea propicia patrones de distribución más aleatorios.Background and Aims: Knowledge of the topographic characteristics of a site is important to understand the local diversity and for proper monitoring of the response of plants with high conservation interest to climate change or land use change. The objective was to examine the distribution pattern of four tree fern species in function of elevation above sea level, exposure, and slope along an altitudinal continuum.Methods: The effect of altitude, slope and geographic exposure on the distribution of Alsophila firma, Cyathea bicrenata, Cyathea myosuroides and Sphaeropteris horrida was studied in La Chinantla, northern Oaxaca, Mexico. The hypothesis of homogeneity of proportions to the change of topographic factors was verified by the Chi square test and the degree of incidence with polynomial functions.Key results: Significant differences between the proportions of each species as a function of each topographic variable were observed. On average, the slope showed an index of significance 43.48 times greater than geographic orientation and 2.50 times greater than elevation above sea level. We observed similarities between the partial niche of Cyathea bicrenata and Alsophila firma, but dissimilarities between Alsophila firma and Cyathea myosuroides.Conclusions: The distribution of tree fern proportions at the local level is discontinuous and non-uniform, attributable to the action of the predominant local factors, mainly topography. Heterogeneous topography leads to highly random distribution patterns of the species studied