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Registro Completo |
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Biblioteca(s): |
Embrapa Gado de Leite. |
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Data corrente: |
16/07/1992 |
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Data da última atualização: |
16/07/1992 |
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Autoria: |
RAMOS, J. A. |
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Título: |
Membracidae de la Republica Dominicana (Homoptera: Auchenorhyncha). |
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Ano de publicação: |
1979 |
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Fonte/Imprenta: |
Rio Piedras, Universidad, 1979. |
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Páginas: |
71p. |
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Série: |
(Porto Rico-Universidade-Colegio de Ciencias Agricolas. Est. Exp. Agric. Boletim, 260). |
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Idioma: |
Espanhol |
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Thesagro: |
Entomologia. |
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Thesaurus Nal: |
entomology. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 00462nam a2200145 a 4500
001 1588022
005 1992-07-16
008 1979 bl uuuu 00u1 u #d
100 1 $aRAMOS, J. A.
245 $aMembracidae de la Republica Dominicana (Homoptera$bAuchenorhyncha).
260 $aRio Piedras, Universidad$c1979
300 $a71p.
490 $a(Porto Rico-Universidade-Colegio de Ciencias Agricolas. Est. Exp. Agric. Boletim, 260).
650 $aentomology
650 $aEntomologia
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Registro original: |
Embrapa Gado de Leite (CNPGL) |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Pantanal. Para informações adicionais entre em contato com cpap.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Pantanal. |
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Data corrente: |
07/12/2021 |
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Data da última atualização: |
07/12/2021 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
PERAZZI, P. R.; PASSAMANI, M.; THIELEN, D.; PADOVANI, C. R.; ALMONACID, M. A. A. |
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Afiliação: |
PAOLO RAMONI PERAZZI, Universidade Federal de Lavras; MARCELO PASSAMANI, Universidade Federal de Lavras; DIRK THIELEN, University of the Andes; CARLOS ROBERTO PADOVANI, CPAP; MARCO AURELIO ARIZAPANA ALMONACID, University of Huanta, Ayacucho, Peru. |
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Título: |
BrazilClim: The overcoming of limitations of pre-existing bioclimate data. |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
International Journal of Climatology, p. 1-15, 2021. |
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Idioma: |
Português |
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Conteúdo: |
Abstract: Species distribution modelling has become instrumental in assessing the influence of environmental conditions on the occurrence or abundance of taxa. The set of environmental layers used for this purpose is a crucial aspect, for which different climate-based (bioclimatic) datasets have been recently developed. These bioclimatic variables result from combinations of precipitation and temperatures surfaces. Here, we explored both the performance and possibility of improving some of the currently available bioclimatic databases, through an evaluation of the precipitation and temperatures surfaces used to generate them. For this purpose, we used a combination of statistic and graphic approaches. We focused on Brazil, not only due to its natural megadiversity, but also due to its continental size and orographic heterogeneity: an excellent ground for refining methods replicable elsewhere. We found a better match between the climatic data measured on-field and Tropical Rainfall Measuring Mission (TRMM 3B43 v7) in the case of precipitation, and the surfaces provided by the National Oceanic and Atmospheric Administration (NOAA) in the case of temperatures, sources uncommonly used for species niche modelling. We gauge-calibrated the best performing surfaces using machine-learning algorithms and generated corrected surfaces that allowed us to create BrazilClim: a database of bioclimatic variables, based on improved primary surfaces, which will result in more assertive predicted distributions and more actual pictures of the species' ecological requirements for megadiverse Brazil, an approach replicable elsewhere. All primary and bioclimatic surfaces generated for this study may be freely downloaded. MenosAbstract: Species distribution modelling has become instrumental in assessing the influence of environmental conditions on the occurrence or abundance of taxa. The set of environmental layers used for this purpose is a crucial aspect, for which different climate-based (bioclimatic) datasets have been recently developed. These bioclimatic variables result from combinations of precipitation and temperatures surfaces. Here, we explored both the performance and possibility of improving some of the currently available bioclimatic databases, through an evaluation of the precipitation and temperatures surfaces used to generate them. For this purpose, we used a combination of statistic and graphic approaches. We focused on Brazil, not only due to its natural megadiversity, but also due to its continental size and orographic heterogeneity: an excellent ground for refining methods replicable elsewhere. We found a better match between the climatic data measured on-field and Tropical Rainfall Measuring Mission (TRMM 3B43 v7) in the case of precipitation, and the surfaces provided by the National Oceanic and Atmospheric Administration (NOAA) in the case of temperatures, sources uncommonly used for species niche modelling. We gauge-calibrated the best performing surfaces using machine-learning algorithms and generated corrected surfaces that allowed us to create BrazilClim: a database of bioclimatic variables, based on improved primary surfaces, which will result in more assertive predict... Mostrar Tudo |
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Thesagro: |
Bioclimatologia; Ecologia. |
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Thesaurus NAL: |
Climatic factors; Ecology. |
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Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
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Marc: |
LEADER 02340naa a2200217 a 4500
001 2137291
005 2021-12-07
008 2021 bl uuuu u00u1 u #d
100 1 $aPERAZZI, P. R.
245 $aBrazilClim$bThe overcoming of limitations of pre-existing bioclimate data.$h[electronic resource]
260 $c2021
520 $aAbstract: Species distribution modelling has become instrumental in assessing the influence of environmental conditions on the occurrence or abundance of taxa. The set of environmental layers used for this purpose is a crucial aspect, for which different climate-based (bioclimatic) datasets have been recently developed. These bioclimatic variables result from combinations of precipitation and temperatures surfaces. Here, we explored both the performance and possibility of improving some of the currently available bioclimatic databases, through an evaluation of the precipitation and temperatures surfaces used to generate them. For this purpose, we used a combination of statistic and graphic approaches. We focused on Brazil, not only due to its natural megadiversity, but also due to its continental size and orographic heterogeneity: an excellent ground for refining methods replicable elsewhere. We found a better match between the climatic data measured on-field and Tropical Rainfall Measuring Mission (TRMM 3B43 v7) in the case of precipitation, and the surfaces provided by the National Oceanic and Atmospheric Administration (NOAA) in the case of temperatures, sources uncommonly used for species niche modelling. We gauge-calibrated the best performing surfaces using machine-learning algorithms and generated corrected surfaces that allowed us to create BrazilClim: a database of bioclimatic variables, based on improved primary surfaces, which will result in more assertive predicted distributions and more actual pictures of the species' ecological requirements for megadiverse Brazil, an approach replicable elsewhere. All primary and bioclimatic surfaces generated for this study may be freely downloaded.
650 $aClimatic factors
650 $aEcology
650 $aBioclimatologia
650 $aEcologia
700 1 $aPASSAMANI, M.
700 1 $aTHIELEN, D.
700 1 $aPADOVANI, C. R.
700 1 $aALMONACID, M. A. A.
773 $tInternational Journal of Climatology, p. 1-15, 2021.
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Embrapa Pantanal (CPAP) |
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