Rigoberto González Cubas’s research while affiliated with Tecnologico Nacional de Mexico and other places

Los inventarios forestales son los métodos de recolección y registro de información para la cuantificación volumétrica y rendimiento de los árboles; sin embargo, esto se dificulta cuando el individuo ha sido cortado y solo permanece el tocón, y esto se logra mediante técnicas de regresión. El objetivo de este trabajo fue ajustar ecuaciones alométricas para la estimación del diámetro normal (dn), altura total (at) y volumen (v) fustal a partir del diámetro del tocón (dt) para Abies religiosa en diferentes regiones de México. Se utilizaron 2.599 datos provenientes de 20 forest management units para analizar las variables con sus respectivas predicciones a través de ocho ecuaciones alométricas; mismas que fueron evaluadas con diferentes criterios estadísticos. El coeficiente de determinación ajustado (R2 adj) explicó el 91 % sobre el diámetro normal, en conjunto con la raíz del error medio cuadrático (REMC) menores a 4,75 cm respecto a la ecuación alométrica (3), también las mejores opciones para estimar la altura total está la de Schumacher exponencial (4) y la alométrica (6) con valores de R2 adj aproximado de 50 %, acompañado de REMC menores a 5,03 m; mientras que, para el volumen fustal, se consideró pertinente la ecuación de Schumacher al tener una REMC que oscilan entre 0,00001 a 0,0026 m3 con R2 adj que explica más del 74 % la variación de los datos observados en cada UMAFOR. Estas regresiones podrán ser de utilidad para la reconstrucción de los árboles después de un evento de derribo no previsto o acontecido, al tener resultados estadísticamente confiable.

Information regarding biomass and wood volume of trees are two important factors that allow for analysis of the sustainability of forests. The objective of this study was to calculate the aerial biomass, amount of carbon and timber volume of dry subtropical temperate forests containing Pinus pseudostrobus Lindl. in northeastern Mexico. Field data corresponding to 57 sampling sites were used, including 28 Permanent Forest Research Sites and 29 conglomerates from the National Forest and Soil Inventory, from which biomass, carbon and volume were calculated using allometric equations. The spectral data (NDVI, Normalized Difference Vegetation Index) were derived from a Landsat 8 image taken in the year 2020. Using the results of the linear relationship between biomass-carbon and NDVI, a positive correlation (P = 0.007) was found using Spectral data from Landsat images for biomass increase and carbon sequestration in coniferous forests in the state of Nuevo León. The research contributes to the understanding of the dynamics of carbon and biomass for the improvement of sustainable development.

Areas with potential to establish Forest Germplasm Production Units (UPGF) with two varieties of P. pseudostrobus were determined. The objectives were (1) to model the current potential distribution of Pinus pseudostrobus var. pseudostrobus and P. pseudostrobus var. apulcensis using MaxEnt algorithms, and (2) to propose areas to locate the best individuals and establish UPGF in Michoacán and Oaxaca, Mexico. For these purposes, 2,451 data of presence obtained from own field records, Forest Biometric System, Global Biodiversity Information Facility and MEXU National Herbarium were used, as well as 19 predictor variables. The 75 % of the records were used for training and 25 % in validation. The adjustment and predictive capacity of ten models was evaluated; eight with 1,000 interactions and two with 500 were evaluated through precision tests of AUC (Area Under the Curve), ROC-standard (Receiver Operating Characteristics) and partial ROC. The models indicated that the two varieties present similar zones of potential distribution in a portion of the Neovolcanic Axis and Sierra Madre del Sur. The environmental variables with the most important contribution to the model for the pseudostrobus variety were those related to temperature; and for the apulcensis variety, temperature and precipitation. The establishment of UPGF can be carried out in areas of optimal growth; in addition, the data generated allow reducing the time and cost for the selection of the best individuals to be included in genetic improvement programs.