Assessment of the Effect of Six Methods of Analysis and Different Sample Sizes for Biomass Estimation in Grasslands of the State of Puebla, Mexico

Efraín Velasco-Bautista, Martin Enrique Romero-Sanchez, David Meza-Juárez and Ramiro Pérez-Miranda
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Efraín Velasco-Bautista: Sustainable Forest Management, National Institute of Forestry, Agriculture and Livestock Research, Mexico City 04010, Mexico
Martin Enrique Romero-Sanchez: Sustainable Forest Management, National Institute of Forestry, Agriculture and Livestock Research, Mexico City 04010, Mexico
David Meza-Juárez: Senior Environmental Consultant, Private Business, Texcoco 56226, Mexico
Ramiro Pérez-Miranda: Sustainable Forest Management, National Institute of Forestry, Agriculture and Livestock Research, Mexico City 04010, Mexico

Land, 2021, vol. 10, issue 11, 1-18

Abstract: In the assessment of natural resources, such as forests or grasslands, it is common to apply a two-stage cluster sampling design, the application of which in the field determines the following situations: (a) difficulty in locating secondary sampling units (SSUs) precisely as planned, so that a random pattern of SSUs can be identified; and (b) the possibility that some primary sampling units (PSUs) have fewer SSUs than planned, leading to PSUs of different sizes. In addition, when considering the estimated variance of the various potential estimators for two-stage cluster sampling, the part corresponding to the variation between SSUs tends to be small for large populations, so the estimator’s variance may depend only on the divergence between PSUs. Research on these aspects is incipient in grassland assessment, so this study generated an artificial population of 759 PSUs and examined the effect of six estimation methods, using 15 PSU sample sizes, on unbiased and relative sampling errors when estimating aboveground, belowground, and total biomass of halophytic grassland. The results indicated that methods 1, 2, 4, and 5 achieved unbiased biomass estimates regardless of sample size, while methods 3 and 6 led to slightly biased estimates. Methods 4 and 5 had relative sampling errors of less than 5% with a sample size of 140 when estimating total biomass.

Keywords: two-stage cluster sampling; halophytic grassland biomass; sample size; unbiased estimators (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jlands:v:10:y:2021:i:11:p:1194-:d:672901

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