Spatial Variability and Sampling Structures for Forest Fuel Material Estimation

Mbanze, Aires Afonso; Péllico Netto, Sylvio; Pelissari, Allan Libanio; Fernandes, Anabela Couto; Tetto, Alexandre França

doi:10.1590/2179-8087.002616

Acessibilidade / Reportar erro

Brasil

Español English

sumário « anterior atual seguinte »

Sumário

Original Article • Floresta Ambient. 24 • 2017 • https://doi.org/10.1590/2179-8087.002616 copy

Spatial Variability and Sampling Structures for Forest Fuel Material Estimation

Authorship SCIMAGO INSTITUTIONS RANKINGS

ABSTRACT

The aim of this work was to model the spatial dependence of fuel material deposition on the ground in a pine stand, and to simulate and evaluate sampling procedures for estimating it. Branches with diameters up to 0.7 cm (A) and from 0.71 to 2.5 cm (B) were collected. Subsequently, the structures of systematic sampling and linear clusters were simulated for 50%, 33% and 23% of the total sample size, and the spatial dependence was evaluated through geostatistical modeling. The systematic sampling was suitable, with representative spatial coverage and accurate estimators, whereas linear clusters were inadequate. The reduction of the number of sample units affected the estimators, but their sampling errors did not exceed 10% for the sample sizes of 23% for class A of fuel material and 50% for class B in the systematic structure, resulting in consistent estimates.

Keywords:
intensity of sample size; sampling errors; consistency of the estimators

Fuel material	Geostatistical model	C₀	C	a (m)	R²	SQD
Class A	Spherical	0.060	0.593	3.542	0.991	2.2 × 10^-3
	Exponential	0.086	1.083	4.575	0.968	7.5 × 10^-3
	Gaussian	0.143	0.608	1.797	0.993	1.8 × 10^-3
Class B	Spherical	0.010	0.025	1.120	0.622	2.6 × 10^-5
	Exponential	0.010	0.025	1.500	0.614	2.6 × 10^-5
	Gaussian	0.013	0.025	1.100	0.660	2.3 × 10^-5

Fuel material	$\bar{X}$	n	$\bar{x}$	$r$	$s_{\bar{x}}$	$E_{a}$	$E %$	$C I [\bar{x} - t s_{\bar{x}} \leq \bar{X} \leq \bar{x} + t s_{\bar{x}}] = P$
Fuel material	Mg ha^–1	n	Mg ha^–1	$r$	Mg ha^–1		$E %$
Systematic sampling procedure
Class A	5.66	50%	5.69	-	0.08	0.16	2.7%	5.53 Mg ha^–1 ≤ $\bar{X}$ ≤ 5.85 Mg ha^–1
		33%	5.64	-	0.11	0.23	4.1%	5.41 Mg ha^–1 ≤ $\bar{X}$ ≤ 5.87 Mg ha^–1
		23%	5.68	-	0.18	0.39	6.9%	5.28 Mg ha^–1 ≤ $\bar{X}$ ≤ 6.07 Mg ha^–1
Class B	0.61	50%	0.62	-	0.02	0.05	7.7%	0.57 Mg ha^–1 ≤ $\bar{X}$ ≤ 0.66 Mg ha^–1
		33%	0.62	-	0.04	0.08	12.8%	0.54 Mg ha^–1 ≤ $\bar{X}$ ≤ 0.70 Mg ha^–1
		23%	0.63	-	0.04	0.10	15.2%	0.53 Mg ha^–1 ≤ $\bar{X}$ ≤ 0.72 Mg ha^–1
Sampling procedure in linear clusters
Class A	5.66	50%	5.69	0.65	0.28	0.90	15.9%	4.79 Mg ha^–1 ≤ $\bar{X}$ ≤ 6.59 Mg ha^–1
		33%	5.64	0.48	0.31	1.00	17.6%	4.64 Mg ha^–1 ≤ $\bar{X}$ ≤ 6.63 Mg ha^–1
		23%	5.68	0.60	0.39	1.24	21.8%	4.44 Mg ha^–1 ≤ $\bar{X}$ ≤ 6.92 Mg ha^–1
Class B	0.61	50%	0.62	0.58	0.08	0.17	27.7%	0.45 Mg ha^–1 ≤ $\bar{X}$ ≤ 0.79 Mg ha^–1
		33%	0.62	0.43	0.07	0.23	37.2%	0.39 Mg ha^–1 ≤ $\bar{X}$ ≤ 0.85 Mg ha^–1
		23%	0.63	0.57	0.08	0.25	40.2%	0.37 Mg ha^–1 ≤ $\bar{X}$ ≤ 0.88 Mg ha^–1

Instituto de Florestas da Universidade Federal Rural do Rio de Janeiro Rodovia BR 465 Km 7, CEP 23897-000, Tel.: (21) 2682 0558 | (21) 3787-4033 - Seropédica - RJ - Brazil
E-mail: floram@ufrrj.br

Acompanhe os números deste periódico no seu leitor de RSS

[1] *Allan Libanio Pelissari Departamento de Ciências Florestais, Universidade Federal do Paraná – UFPR, Jardim Botânico, CEP 80210-170, Curitiba, PR, Brasil e-mail: allanpelissari@gmail.com