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Revista Chapingo serie ciencias forestales y del ambiente

versión On-line ISSN 2007-4018versión impresa ISSN 2007-3828

Resumen

SAAVEDRA-ROMERO, Luz de L.; ALVARADO-ROSALES, Dionicio; MARTINEZ-TRINIDAD, Tomás  y  HERNANDEZ-DE LA ROSA, Patricia. Identification of defects and risks in trees of San Juan de Aragon Forest, Mexico City. Rev. Chapingo ser. cienc. for. ambient [online]. 2019, vol.25, n.1, pp.31-47.  Epub 15-Feb-2021. ISSN 2007-4018.  https://doi.org/10.5154/r.rchscfa.2018.06.049.

Introduction:

Urban forests require an assessment of their trees’ structural defects, as well as the risk they represent.

Objective:

To identify the defects and risks of the trees in San Juan de Aragon Forest in Mexico City.

Materials and methods:

Twenty-eight circular plots of 0.1 ha were randomly established. Diameter at breast height, total height and slenderness index were measured in each tree. Structural defects were identified and a risk rating (RR) was obtained at the individual, species and section level using the methods of Matheny and Clark, and Dunster.

Results and discussion:

Of the 760 trees evaluated, Casuarina equisetifolia L., Grevillea robusta A. Cunn. ex R. Br. and Hesperocyparis lusitanica Mill. were the most frequent species with diameter classes from 7.6 to 15.1 cm, heights from 5.1 to 10 m and slenderness index from 26 to 75. Structural damage was identified in 38.7 % of the trees: lean (18.8 %), cankers (15.4 %), epicormic shoots (14.4 %), dead branches (9.9 %), tumors (9.2 %) and cavities (6.2 %). Casuarina equisetifolia and Schinus molle had the highest number of defects. With the Matheny and Clark method, 83.9 % of the trees had a low RR, 14.7 % a medium RR and 1.4 % a high RR; with Dunster's method, 88.1 % had a low RR, 11.3 % a medium RR and 0.68 % a high RR.

Conclusion:

The procedures for evaluating and identifying trees at risk of failure allowed recognizing their main structural defects in a simple way.

Palabras llave : urban forest; structural damage; Matheny and Clark method; Dunster method.

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