1. bookVolumen 49 (2022): Heft 1 (January 2022)
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Zeitschrift
eISSN
1338-7014
Erstveröffentlichung
16 Apr 2017
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2 Hefte pro Jahr
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Englisch
access type Uneingeschränkter Zugang

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

Online veröffentlicht: 30 Dec 2021
Volumen & Heft: Volumen 49 (2022) - Heft 1 (January 2022)
Seitenbereich: 70 - 79
Eingereicht: 16 Jul 2021
Akzeptiert: 13 Nov 2021
Zeitschriftendaten
License
Format
Zeitschrift
eISSN
1338-7014
Erstveröffentlichung
16 Apr 2017
Erscheinungsweise
2 Hefte pro Jahr
Sprachen
Englisch
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.

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