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

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 rand...

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Autores principales:	Efraín Velasco-Bautista, Martin Enrique Romero-Sanchez, David Meza-Juárez, Ramiro Pérez-Miranda
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	two-stage cluster sampling halophytic grassland biomass sample size unbiased estimators Agriculture S
Acceso en línea:	https://doaj.org/article/ffb467fa69194d859e28a60d48111c40
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spelling	oai:doaj.org-article:ffb467fa69194d859e28a60d48111c402021-11-25T18:09:35ZAssessment of the Effect of Six Methods of Analysis and Different Sample Sizes for Biomass Estimation in Grasslands of the State of Puebla, Mexico10.3390/land101111942073-445Xhttps://doaj.org/article/ffb467fa69194d859e28a60d48111c402021-11-01T00:00:00Zhttps://www.mdpi.com/2073-445X/10/11/1194https://doaj.org/toc/2073-445XIn 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.Efraín Velasco-BautistaMartin Enrique Romero-SanchezDavid Meza-JuárezRamiro Pérez-MirandaMDPI AGarticletwo-stage cluster samplinghalophytic grassland biomasssample sizeunbiased estimatorsAgricultureSENLand, Vol 10, Iss 1194, p 1194 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	two-stage cluster sampling halophytic grassland biomass sample size unbiased estimators Agriculture S
spellingShingle	two-stage cluster sampling halophytic grassland biomass sample size unbiased estimators Agriculture S Efraín Velasco-Bautista Martin Enrique Romero-Sanchez David Meza-Juárez Ramiro Pérez-Miranda Assessment of the Effect of Six Methods of Analysis and Different Sample Sizes for Biomass Estimation in Grasslands of the State of Puebla, Mexico
description	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.
format	article
author	Efraín Velasco-Bautista Martin Enrique Romero-Sanchez David Meza-Juárez Ramiro Pérez-Miranda
author_facet	Efraín Velasco-Bautista Martin Enrique Romero-Sanchez David Meza-Juárez Ramiro Pérez-Miranda
author_sort	Efraín Velasco-Bautista
title	Assessment of the Effect of Six Methods of Analysis and Different Sample Sizes for Biomass Estimation in Grasslands of the State of Puebla, Mexico
title_short	Assessment of the Effect of Six Methods of Analysis and Different Sample Sizes for Biomass Estimation in Grasslands of the State of Puebla, Mexico
title_full	Assessment of the Effect of Six Methods of Analysis and Different Sample Sizes for Biomass Estimation in Grasslands of the State of Puebla, Mexico
title_fullStr	Assessment of the Effect of Six Methods of Analysis and Different Sample Sizes for Biomass Estimation in Grasslands of the State of Puebla, Mexico
title_full_unstemmed	Assessment of the Effect of Six Methods of Analysis and Different Sample Sizes for Biomass Estimation in Grasslands of the State of Puebla, Mexico
title_sort	assessment of the effect of six methods of analysis and different sample sizes for biomass estimation in grasslands of the state of puebla, mexico
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/ffb467fa69194d859e28a60d48111c40
work_keys_str_mv	AT efrainvelascobautista assessmentoftheeffectofsixmethodsofanalysisanddifferentsamplesizesforbiomassestimationingrasslandsofthestateofpueblamexico AT martinenriqueromerosanchez assessmentoftheeffectofsixmethodsofanalysisanddifferentsamplesizesforbiomassestimationingrasslandsofthestateofpueblamexico AT davidmezajuarez assessmentoftheeffectofsixmethodsofanalysisanddifferentsamplesizesforbiomassestimationingrasslandsofthestateofpueblamexico AT ramiroperezmiranda assessmentoftheeffectofsixmethodsofanalysisanddifferentsamplesizesforbiomassestimationingrasslandsofthestateofpueblamexico
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Assessment of the Effect of Six Methods of Analysis and Different Sample Sizes for Biomass Estimation in Grasslands of the State of Puebla, Mexico

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