Insights from a large-scale inventory in the southern Brazilian Atlantic Forest

Detalhes bibliográficos
Autor(a) principal: Vibrans,Alexander Christian
Data de Publicação: 2020
Outros Autores: Gasper,André Luís de, Moser,Paolo, Oliveira,Laio Zimermann, Lingner,Débora Vanessa, Sevegnani,Lucia
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Scientia Agrícola (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162020000101000
Resumo: ABSTRACT: A key issue in large-area inventories is defining a suitable sampling design and the effort required to obtain reliable estimates of species richness and forest attributes, especially in species-diverse forests. To address this issue, data from 418 systematically distributed 0.4 ha plots were collected. Estimators of nonparametric species richness were employed to assess the floristic representativeness of data collected in three forest types in the Brazilian Atlantic Forest. The sampling sufficiency of forest attributes was evaluated as a function of sample size. Altogether, 831 tree/shrub species were recorded. The data acquired through the systematic sampling design were representative of both species richness and basal area. The confidence intervals’ length would not substantially decrease by using more than 70 % of the reference sample (n = 364), thereby reaching a length of ∼5 % of the sample mean. Nevertheless, reliable estimates of species richness for diverse forests demand a thorough sampling approach far more exacting so as to achieve acceptable population estimates of forest attributes. Though the study area is regarded as a biodiversity hotspot, the forest stands showed diminished species richness, basal area, stem volume and biomass when compared to old-growth stands. As regards species richness, the data provided evidence of contrasting great γ-diversity (at the forest type level) and small α-diversity (at the forest stand level). Amongst anthropic impacts, illegal logging and extensive cattle grazing within stands are undoubtedly key factors that threaten forest conservation in the study area.
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spelling Insights from a large-scale inventory in the southern Brazilian Atlantic Forestforest attributes estimationspecies richnessforest monitoringsystematic samplingsecondary forestsABSTRACT: A key issue in large-area inventories is defining a suitable sampling design and the effort required to obtain reliable estimates of species richness and forest attributes, especially in species-diverse forests. To address this issue, data from 418 systematically distributed 0.4 ha plots were collected. Estimators of nonparametric species richness were employed to assess the floristic representativeness of data collected in three forest types in the Brazilian Atlantic Forest. The sampling sufficiency of forest attributes was evaluated as a function of sample size. Altogether, 831 tree/shrub species were recorded. The data acquired through the systematic sampling design were representative of both species richness and basal area. The confidence intervals’ length would not substantially decrease by using more than 70 % of the reference sample (n = 364), thereby reaching a length of ∼5 % of the sample mean. Nevertheless, reliable estimates of species richness for diverse forests demand a thorough sampling approach far more exacting so as to achieve acceptable population estimates of forest attributes. Though the study area is regarded as a biodiversity hotspot, the forest stands showed diminished species richness, basal area, stem volume and biomass when compared to old-growth stands. As regards species richness, the data provided evidence of contrasting great γ-diversity (at the forest type level) and small α-diversity (at the forest stand level). Amongst anthropic impacts, illegal logging and extensive cattle grazing within stands are undoubtedly key factors that threaten forest conservation in the study area.Escola Superior de Agricultura "Luiz de Queiroz"2020-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162020000101000Scientia Agricola v.77 n.1 2020reponame:Scientia Agrícola (Online)instname:Universidade de São Paulo (USP)instacron:USP10.1590/1678-992x-2018-0036info:eu-repo/semantics/openAccessVibrans,Alexander ChristianGasper,André Luís deMoser,PaoloOliveira,Laio ZimermannLingner,Débora VanessaSevegnani,Luciaeng2019-06-28T00:00:00Zoai:scielo:S0103-90162020000101000Revistahttp://revistas.usp.br/sa/indexPUBhttps://old.scielo.br/oai/scielo-oai.phpscientia@usp.br||alleoni@usp.br1678-992X0103-9016opendoar:2019-06-28T00:00Scientia Agrícola (Online) - Universidade de São Paulo (USP)false
dc.title.none.fl_str_mv Insights from a large-scale inventory in the southern Brazilian Atlantic Forest
title Insights from a large-scale inventory in the southern Brazilian Atlantic Forest
spellingShingle Insights from a large-scale inventory in the southern Brazilian Atlantic Forest
Vibrans,Alexander Christian
forest attributes estimation
species richness
forest monitoring
systematic sampling
secondary forests
title_short Insights from a large-scale inventory in the southern Brazilian Atlantic Forest
title_full Insights from a large-scale inventory in the southern Brazilian Atlantic Forest
title_fullStr Insights from a large-scale inventory in the southern Brazilian Atlantic Forest
title_full_unstemmed Insights from a large-scale inventory in the southern Brazilian Atlantic Forest
title_sort Insights from a large-scale inventory in the southern Brazilian Atlantic Forest
author Vibrans,Alexander Christian
author_facet Vibrans,Alexander Christian
Gasper,André Luís de
Moser,Paolo
Oliveira,Laio Zimermann
Lingner,Débora Vanessa
Sevegnani,Lucia
author_role author
author2 Gasper,André Luís de
Moser,Paolo
Oliveira,Laio Zimermann
Lingner,Débora Vanessa
Sevegnani,Lucia
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Vibrans,Alexander Christian
Gasper,André Luís de
Moser,Paolo
Oliveira,Laio Zimermann
Lingner,Débora Vanessa
Sevegnani,Lucia
dc.subject.por.fl_str_mv forest attributes estimation
species richness
forest monitoring
systematic sampling
secondary forests
topic forest attributes estimation
species richness
forest monitoring
systematic sampling
secondary forests
description ABSTRACT: A key issue in large-area inventories is defining a suitable sampling design and the effort required to obtain reliable estimates of species richness and forest attributes, especially in species-diverse forests. To address this issue, data from 418 systematically distributed 0.4 ha plots were collected. Estimators of nonparametric species richness were employed to assess the floristic representativeness of data collected in three forest types in the Brazilian Atlantic Forest. The sampling sufficiency of forest attributes was evaluated as a function of sample size. Altogether, 831 tree/shrub species were recorded. The data acquired through the systematic sampling design were representative of both species richness and basal area. The confidence intervals’ length would not substantially decrease by using more than 70 % of the reference sample (n = 364), thereby reaching a length of ∼5 % of the sample mean. Nevertheless, reliable estimates of species richness for diverse forests demand a thorough sampling approach far more exacting so as to achieve acceptable population estimates of forest attributes. Though the study area is regarded as a biodiversity hotspot, the forest stands showed diminished species richness, basal area, stem volume and biomass when compared to old-growth stands. As regards species richness, the data provided evidence of contrasting great γ-diversity (at the forest type level) and small α-diversity (at the forest stand level). Amongst anthropic impacts, illegal logging and extensive cattle grazing within stands are undoubtedly key factors that threaten forest conservation in the study area.
publishDate 2020
dc.date.none.fl_str_mv 2020-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
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dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162020000101000
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162020000101000
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/1678-992x-2018-0036
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Escola Superior de Agricultura "Luiz de Queiroz"
publisher.none.fl_str_mv Escola Superior de Agricultura "Luiz de Queiroz"
dc.source.none.fl_str_mv Scientia Agricola v.77 n.1 2020
reponame:Scientia Agrícola (Online)
instname:Universidade de São Paulo (USP)
instacron:USP
instname_str Universidade de São Paulo (USP)
instacron_str USP
institution USP
reponame_str Scientia Agrícola (Online)
collection Scientia Agrícola (Online)
repository.name.fl_str_mv Scientia Agrícola (Online) - Universidade de São Paulo (USP)
repository.mail.fl_str_mv scientia@usp.br||alleoni@usp.br
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