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The assessment of commercial forest plantations (PFC) requires accurate quantitative tools (sampling estimators) to know the timber inventory, to generate reliable information for planning actions and make the best decisions on sustainable forest management of forest resources. In this context the aim of this study was to compare four estimators to propose an efficient sampling strategy that allows calculation of timber stocks of Pinus chiapensis growing in a commercial forest plantation (PFC), in Tlatlauquitepec, Puebla. To quantify the inventory of Pinus chiapensis plantations, we used the mensuration information (D and H) of 44 permanent sampling plots, established in 2014 in an 87 ha-1 surface area and re-measured in 2015. Two classical estimators based on designs: Simple Random Sampling (MSA) and Stratified Sampling (ME), and two based on models: Reason Estimators (ERaz) and Regression Estimators (EReg), the latter employing a population mean that is estimated under ME. The results show that the four estimators are statistically different and that the EReg is the most accurate to estimate the stock in volume when using the basimetric area as an auxiliary variable. EReg allowed to update the inventory of a total of 4 806 m3 for the first year of measurement to 6 496 m3 in the second year. In ERaz (V2/V1) under ME a Reason (R) of volume two (2015) is obtained between volume one (2014) which suggests a percentage increase of 35 % of the volume for 2015.

Estimadores de muestreo para inventario de plantaciones de Pinus chiapensis (Martínez) Andresen