A Spatial Forestry Productivity Potential Model for Pinus arizonica Engelm, a Key Timber Species from Northwest Mexico

Martin Martínez-Salvador, Ricardo Mata-Gonzalez, Alfredo Pinedo-Alvarez, Carlos R. Morales-Nieto, Jesús A. Prieto-Amparán, Griselda Vázquez-Quintero and Federico Villarreal-Guerrero
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Martin Martínez-Salvador: Facultad de Zootecnia y Ecología, Universidad Autónoma de Chihuahua, Km 1 Perif, R. Almada, Chihuahua 31453, Mexico
Ricardo Mata-Gonzalez: Department of Animal and Rangeland Sciences, Oregon State University, 120 Withycombe Hall, OSU, Corvallis, OR 97331, USA
Alfredo Pinedo-Alvarez: Facultad de Zootecnia y Ecología, Universidad Autónoma de Chihuahua, Km 1 Perif, R. Almada, Chihuahua 31453, Mexico
Carlos R. Morales-Nieto: Facultad de Zootecnia y Ecología, Universidad Autónoma de Chihuahua, Km 1 Perif, R. Almada, Chihuahua 31453, Mexico
Jesús A. Prieto-Amparán: Facultad de Zootecnia y Ecología, Universidad Autónoma de Chihuahua, Km 1 Perif, R. Almada, Chihuahua 31453, Mexico
Griselda Vázquez-Quintero: Facultad de Ciencias Agrotecnológicas, Universidad Autónoma de Chihuahua, Chihuahua 31350, Mexico
Federico Villarreal-Guerrero: Facultad de Zootecnia y Ecología, Universidad Autónoma de Chihuahua, Km 1 Perif, R. Almada, Chihuahua 31453, Mexico

Sustainability, 2019, vol. 11, issue 3, 1-15

Abstract: Pinus arizonica is a widely distributed tree species growing in temperate forests of Northwest Mexico where it is utilized through different regeneration harvest methods. Yet, management models based on estimations of its productive potential are sorely lacking. In this study, a procedure to create a productive map using site index (SI) equations and Geographic Information Systems (GIS) was developed. A SI model for P. arizonica was created for the study area and used to classify a group of randomly sampled plots on three productivity categories (High, Medium, and Low) for management purposes. Climatic, topographic and edaphic variables were determined on the sampled plots. Then, a statistically-based analysis was performed to identify the climatic, topographic and edaphic variables significantly influencing the productivity levels. Based on the values of these significant variables, a map of productive potential was elaborated for the whole study area. Sites with the highest productivity were those with slopes ≤12°, soil depths ≥0.46 m, minimum and maximum mean annual temperatures of 5 °C and 18 °C respectively, and precipitation ≥900 mm. This methodology could be considered for similar species/conditions where productivity models do not exist or to update old models rendered obsolete by climate change.

Keywords: forest productivity; pine tree growth; productive potential map; GIS (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
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