<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Degraded vegetation is the result of a process that affects structural and functional characteristics. Tree species from the <italic>Acacia</italic> genus are very important to the ecosystem in semi-arid lands due to their participation in the recovery of highly degraded areas. One of the most important species among this genus is <italic>A. schaffneri.</italic> The status of a forest stand is determined according to its structure, including height, stratum and density. Remote sensing is a valuable method for estimating volumetric stocks and associated changes in forest populations over established periods of time. The objective of this research was to estimate wood volume of <italic>A. schaffneri</italic> using remote sensing, and to complement that information with the results obtained from an estimation method based on forest measurements. The results obtained showed that the crown area was the dendrometric variable that can be used in a wood volume prediction model. In the exploratory analysis between dendrometric variables and remote sensing showed low and negative associations were observed in the four stations analyzed. There are conservation problems due to anthropogenic activities, among which stands out the intensive grazing that results in a decrease of the natural regeneration capacity of <italic>Acacia schaffneri.</italic></p>
</abstract>

Degraded vegetation is the result of a process that affects structural and functional characteristics. Tree species from the Acacia genus are very important to the ecosystem in semi-arid lands due to their participation in the recovery of highly degraded areas. One of the most important species among this genus is A. schaffneri. The status of a forest stand is determined according to its structure, including height, stratum and density. Remote sensing is a valuable method for estimating volumetric stocks and associated changes in forest populations over established periods of time. The objective of this research was to estimate wood volume of A. schaffneri using remote sensing, and to complement that information with the results obtained from an estimation method based on forest measurements. The results obtained showed that the crown area was the dendrometric variable that can be used in a wood volume prediction model. In the exploratory analysis between dendrometric variables and remote sensing showed low and negative associations were observed in the four stations analyzed. There are conservation problems due to anthropogenic activities, among which stands out the intensive grazing that results in a decrease of the natural regeneration capacity of Acacia schaffneri.

Spatial exploration, dendrometric characteristics and prediction models of wood production in a stand of <italic>Acacia schaffneri</italic> in Durango, Mexico

Laboratorio de Biología y Ecología Forestal, Facultad de Ciencias Biológicas

Universidad Juárez del Estado de Durango

Universidad Autónoma Agraria Antonio Narro

Universidad Autónoma del Estado de Hidalgo

Folia Oecologica

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Spatial exploration, dendrometric characteristics and prediction models of wood production in a stand of  in Durango, Mexico

Degraded vegetation is the result of a process that affects structural and functional characteristics. Tree species from the Acacia genus are very important to...

Spatial exploration, dendrometric characteristics and prediction models of wood production in a stand of Acacia schaffneri in Durango, Mexico

Publicado en línea: 30 dic 2021

Páginas: 70 - 79

Recibido: 16 jul 2021

Aceptado: 13 nov 2021

DOI: https://doi.org/10.2478/foecol-2022-0008

Palabras clave
degradation, forest mensuration, grazing, prediction models

© 2022 Luis Manuel Valenzuela Nuñez et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Spatial exploration, dendrometric characteristics and prediction models of wood production in a stand of Acacia schaffneri in Durango, Mexico

Publicado en línea: 30 dic 2021

Páginas: 70 - 79

Recibido: 16 jul 2021

Aceptado: 13 nov 2021

DOI: https://doi.org/10.2478/foecol-2022-0008

Palabras clavedegradation, forest mensuration, grazing, prediction models

© 2022 Luis Manuel Valenzuela Nuñez et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Palabras clave
degradation, forest mensuration, grazing, prediction models