Estimating species richness in hyper-diverse large tree communities
Species richness estimation is one of the most widely used analyses carried out by ecologists, and nonparametric estimators are probably the most used techniques to carry out such estimations. We tested the assumptions and results of nonparametric estimators and those of a logseries approach to spec...
| Autor principal: | ter Steege, H. |
|---|---|
| Outros Autores: | Sabatier, Daniel, Oliveira, Sylvia Mota de, Magnusson, William Ernest, Molino, Jean François, Gomes, Vitor H.F., Pos, Edwin T., Salomão, Rafael Paiva |
| Grau: | Artigo |
| Idioma: | English |
| Publicado em: |
Ecology
2020
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| Assuntos: | |
| Acesso em linha: |
https://repositorio.inpa.gov.br/handle/1/17122 |
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oai:repositorio:1-17122 |
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dspace |
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oai:repositorio:1-17122 Estimating species richness in hyper-diverse large tree communities ter Steege, H. Sabatier, Daniel Oliveira, Sylvia Mota de Magnusson, William Ernest Molino, Jean François Gomes, Vitor H.F. Pos, Edwin T. Salomão, Rafael Paiva Data Set Estimation Method Plant Community Species Richness Tropical Forest Amazonia Biodiversity Ecology Forest Tree Biodiversity Ecology Forests Trees Species richness estimation is one of the most widely used analyses carried out by ecologists, and nonparametric estimators are probably the most used techniques to carry out such estimations. We tested the assumptions and results of nonparametric estimators and those of a logseries approach to species richness estimation for simulated tropical forests and five data sets from the field. We conclude that nonparametric estimators are not suitable to estimate species richness in tropical forests, where sampling intensity is usually low and richness is high, because the assumptions of the methods do not meet the sampling strategy used in most studies. The logseries, while also requiring substantial sampling, is much more effective in estimating species richness than commonly used nonparametric estimators, and its assumptions better match the way field data is being collected. © 2017 by the Ecological Society of America 2020-06-15T21:39:05Z 2020-06-15T21:39:05Z 2017 Artigo https://repositorio.inpa.gov.br/handle/1/17122 10.1002/ecy.1813 en Volume 98, Número 5, Pags. 1444-1454 Restrito Ecology |
| institution |
Instituto Nacional de Pesquisas da Amazônia - Repositório Institucional |
| collection |
INPA-RI |
| language |
English |
| topic |
Data Set Estimation Method Plant Community Species Richness Tropical Forest Amazonia Biodiversity Ecology Forest Tree Biodiversity Ecology Forests Trees |
| spellingShingle |
Data Set Estimation Method Plant Community Species Richness Tropical Forest Amazonia Biodiversity Ecology Forest Tree Biodiversity Ecology Forests Trees ter Steege, H. Estimating species richness in hyper-diverse large tree communities |
| topic_facet |
Data Set Estimation Method Plant Community Species Richness Tropical Forest Amazonia Biodiversity Ecology Forest Tree Biodiversity Ecology Forests Trees |
| description |
Species richness estimation is one of the most widely used analyses carried out by ecologists, and nonparametric estimators are probably the most used techniques to carry out such estimations. We tested the assumptions and results of nonparametric estimators and those of a logseries approach to species richness estimation for simulated tropical forests and five data sets from the field. We conclude that nonparametric estimators are not suitable to estimate species richness in tropical forests, where sampling intensity is usually low and richness is high, because the assumptions of the methods do not meet the sampling strategy used in most studies. The logseries, while also requiring substantial sampling, is much more effective in estimating species richness than commonly used nonparametric estimators, and its assumptions better match the way field data is being collected. © 2017 by the Ecological Society of America |
| format |
Artigo |
| author |
ter Steege, H. |
| author2 |
Sabatier, Daniel Oliveira, Sylvia Mota de Magnusson, William Ernest Molino, Jean François Gomes, Vitor H.F. Pos, Edwin T. Salomão, Rafael Paiva |
| author2Str |
Sabatier, Daniel Oliveira, Sylvia Mota de Magnusson, William Ernest Molino, Jean François Gomes, Vitor H.F. Pos, Edwin T. Salomão, Rafael Paiva |
| title |
Estimating species richness in hyper-diverse large tree communities |
| title_short |
Estimating species richness in hyper-diverse large tree communities |
| title_full |
Estimating species richness in hyper-diverse large tree communities |
| title_fullStr |
Estimating species richness in hyper-diverse large tree communities |
| title_full_unstemmed |
Estimating species richness in hyper-diverse large tree communities |
| title_sort |
estimating species richness in hyper-diverse large tree communities |
| publisher |
Ecology |
| publishDate |
2020 |
| url |
https://repositorio.inpa.gov.br/handle/1/17122 |
| _version_ |
1787142100836417536 |
| score |
11.755432 |