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 | Acesso ao texto completo restrito à biblioteca da Embrapa Agricultura Digital. Para informações adicionais entre em contato com cnptia.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
08/06/2022 |
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Data da última atualização: |
22/12/2022 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
ZARBÁ, L.; PIQUER-RODRÍGUEZ, M.; BOILLAT, S.; LEVERS, C.; GASPARRI, I.; AIDE, T. M.; ÁLVAREZ-BERRÍOS, N. L.; ANDERSON, L. O; ARAOZ, E.; ARIMA, E.; BATISTELLA, M.; CALDERÓN-LOOR, M.; ECHEVERRÍA, C.; GONZALEZ-ROGLICH, M.; JOBBÁGY, E. G.; MATHEZ-STIEFEL, S. L.; RAMIREZ-REYES, C.; PACHECO, A.; VALLEJOS, M.; YOUNG, K. R.; GRAU, R. |
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Afiliação: |
LUCÍA ZARBÁ, INSTITUTO DE ECOLOGÍA REGIONAL (IER); MARÍA PIQUER-RODRÍGUEZ, IER, FREIE UNIVERSITÄT BERLIN, HUMBOLDT-UNIVERSITÄT ZU BERLIN; SÉBASTIEN BOILLAT, UNIVERSITY OF BERN; CHRISTIAN LEVERS, VRIJE UNIVERSITEIT AMSTERDAM, UNIVERSITY OF BRITISH COLUMBIA; IGNACIO GASPARRI, IER; T. MITCHELL AIDE, UNIVERSITY OF PUERTO RICO - RIO PIEDRAS; NORA L. ÁLVAREZ-BERRÍOS, USDA FOREST SERVICE, INTERNATIONAL INSTITUTE OF TROPICAL FORESTRY, RÍO PIEDRAS, PUERTO RICO; LIANA O. ANDERSON, CEMADEN/MCTI; EZEQUIEL ARAOZ, IER; EUGENIO ARIMA, UNIVERSITY OF TEXAS AT AUSTIN; MATEUS BATISTELLA, CNPTIA; MARCO CALDERÓN-LOOR, DEAKIN UNIVERSITY, UNIVERSIDAD DE LAS AMÉRICAS; CRISTIAN ECHEVERRÍA, UNIVERSIDAD DE CONCEPCIÓN; MILLENNIUM NUCLEUS CENTER FOR THE SOCIOECONOMIC IMPACT OF ENVIRONMENTAL POLICIES, SANTIAGO DE CHILE; MARIANO GONZALEZ-ROGLICH, WILDLIFE CONSERVATION SOCIETY, BUENOS AIRES; ESTEBAN G. JOBBÁGY, GRUPO DE ESTUDIOS AMBIENTALES, IMASL - CONICET AND UNIVERSIDAD NACIONAL DE SAN LUIS; SOUTH AMERICAN INSTITUTE FOR RESILIENCE AND SUSTAINABILITY STUDIES, MALDONADO; SARAH-LAN MATHEZ-STIEFEL, UNIVERSITY OF BERN; CARLOS RAMIREZ-REYES, MISSISSIPPI STATE UNIVERSITY; ANDREA PACHECO, GERMAN CENTRE FOR INTEGRATIVE BIODIVERSITY RESEARCH (IDIV) HALLE-JENA-LEIPZIG; MARÍA VALLEJOS, INIA, UNIVERSIDAD DE BUENOS AIRES; KENNETH R. YOUNG, UNIVERSITY OF TEXAS AT AUSTIN; RICARDO GRAU, IER. |
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Título: |
Mapping and characterizing social-ecological land systems of South America. |
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Ano de publicação: |
2022 |
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Fonte/Imprenta: |
Ecology and Society: a Journal of Integrative Science for Resilience and Sustainability, v. 27, n. 2, 27, 2022. |
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DOI: |
https://doi.org/10.5751/ES-13066-270227 |
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Idioma: |
Inglês |
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Conteúdo: |
ABSTRACT. Humans place !!!!! strong pressure on land and have modified around 75% of Earth?s terrestrial surface. In this context,ecoregions and biomes, merely defined on the basis of their biophysical features, are incomplete characterizations of the territory. Landsystem science requires classification schemes that incorporate both social and biophysical dimensions. In this study, we generatedspatially explicit social-ecological land system (SELS) typologies for South America with a hybrid methodology that combined data-driven spatial analysis with a knowledge-based evaluation by an interdisciplinary group of regional specialists. Our approach embraceda holistic consideration of the social-ecological land systems, gathering a dataset of 26 variables spanning across 7 dimensions: physical,biological, land cover, economic, demographic, political, and cultural. We identified 13 SELS nested in 5 larger social-ecological regions(SER). Each SELS was discussed and described by specific groups of specialists. Although 4 environmental and 1 socioeconomicvariable explained most of the distribution of the coarse SER classification, a diversity of 15 other variables were shown to be essentialfor defining several SELS, highlighting specific features that differentiate them. The SELS spatial classification presented is a systematicand operative characterization of South American social-ecological land systems. We propose its use can contribute as a referenceframework for a wide range of applications such as analyzing observations within larger contexts, designing system-specific solutionsfor sustainable development, and structuring hypothesis testing and comparisons across space. Similar efforts could be done elsewherein the world. MenosABSTRACT. Humans place !!!!! strong pressure on land and have modified around 75% of Earth?s terrestrial surface. In this context,ecoregions and biomes, merely defined on the basis of their biophysical features, are incomplete characterizations of the territory. Landsystem science requires classification schemes that incorporate both social and biophysical dimensions. In this study, we generatedspatially explicit social-ecological land system (SELS) typologies for South America with a hybrid methodology that combined data-driven spatial analysis with a knowledge-based evaluation by an interdisciplinary group of regional specialists. Our approach embraceda holistic consideration of the social-ecological land systems, gathering a dataset of 26 variables spanning across 7 dimensions: physical,biological, land cover, economic, demographic, political, and cultural. We identified 13 SELS nested in 5 larger social-ecological regions(SER). Each SELS was discussed and described by specific groups of specialists. Although 4 environmental and 1 socioeconomicvariable explained most of the distribution of the coarse SER classification, a diversity of 15 other variables were shown to be essentialfor defining several SELS, highlighting specific features that differentiate them. The SELS spatial classification presented is a systematicand operative characterization of South American social-ecological land systems. We propose its use can contribute as a referenceframework for a wide range of... Mostrar Tudo |
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Palavras-Chave: |
Automatização; Automatization; Clusterização hierárquica; Dados multidisciplinares; Hierarchical clustering; Mapeamento; Mapeamento participatório; Mapeamento socioecológico; Multidisciplinary data; Participatory mapping; Sistema socioecológico da América do Sul; Social-ecological mapping. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 03344naa a2200517 a 4500
001 2143841
005 2022-12-22
008 2022 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.5751/ES-13066-270227$2DOI
100 1 $aZARBÁ, L.
245 $aMapping and characterizing social-ecological land systems of South America.$h[electronic resource]
260 $c2022
520 $aABSTRACT. Humans place !!!!! strong pressure on land and have modified around 75% of Earth?s terrestrial surface. In this context,ecoregions and biomes, merely defined on the basis of their biophysical features, are incomplete characterizations of the territory. Landsystem science requires classification schemes that incorporate both social and biophysical dimensions. In this study, we generatedspatially explicit social-ecological land system (SELS) typologies for South America with a hybrid methodology that combined data-driven spatial analysis with a knowledge-based evaluation by an interdisciplinary group of regional specialists. Our approach embraceda holistic consideration of the social-ecological land systems, gathering a dataset of 26 variables spanning across 7 dimensions: physical,biological, land cover, economic, demographic, political, and cultural. We identified 13 SELS nested in 5 larger social-ecological regions(SER). Each SELS was discussed and described by specific groups of specialists. Although 4 environmental and 1 socioeconomicvariable explained most of the distribution of the coarse SER classification, a diversity of 15 other variables were shown to be essentialfor defining several SELS, highlighting specific features that differentiate them. The SELS spatial classification presented is a systematicand operative characterization of South American social-ecological land systems. We propose its use can contribute as a referenceframework for a wide range of applications such as analyzing observations within larger contexts, designing system-specific solutionsfor sustainable development, and structuring hypothesis testing and comparisons across space. Similar efforts could be done elsewherein the world.
653 $aAutomatização
653 $aAutomatization
653 $aClusterização hierárquica
653 $aDados multidisciplinares
653 $aHierarchical clustering
653 $aMapeamento
653 $aMapeamento participatório
653 $aMapeamento socioecológico
653 $aMultidisciplinary data
653 $aParticipatory mapping
653 $aSistema socioecológico da América do Sul
653 $aSocial-ecological mapping
700 1 $aPIQUER-RODRÍGUEZ, M.
700 1 $aBOILLAT, S.
700 1 $aLEVERS, C.
700 1 $aGASPARRI, I.
700 1 $aAIDE, T. M.
700 1 $aÁLVAREZ-BERRÍOS, N. L.
700 1 $aANDERSON, L. O
700 1 $aARAOZ, E.
700 1 $aARIMA, E.
700 1 $aBATISTELLA, M.
700 1 $aCALDERÓN-LOOR, M.
700 1 $aECHEVERRÍA, C.
700 1 $aGONZALEZ-ROGLICH, M.
700 1 $aJOBBÁGY, E. G.
700 1 $aMATHEZ-STIEFEL, S. L.
700 1 $aRAMIREZ-REYES, C.
700 1 $aPACHECO, A.
700 1 $aVALLEJOS, M.
700 1 $aYOUNG, K. R.
700 1 $aGRAU, R.
773 $tEcology and Society: a Journal of Integrative Science for Resilience and Sustainability$gv. 27, n. 2, 27, 2022.
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Registro original: |
Embrapa Agricultura Digital (CNPTIA) |
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Registro Completo
|
Biblioteca(s): |
Embrapa Gado de Leite. |
|
Data corrente: |
10/08/2021 |
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Data da última atualização: |
10/08/2021 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 2 |
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Autoria: |
SILVA, H. T.; LOPES, P. S.; CARVALHEIRA, J.; SILVA, D. A.; SILVA, A. A.; SILVA, F. F.; VERONEZE, R.; THOMPSON, G.; COSTA, C. N. |
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Afiliação: |
HUGO TEIXEIRA SILVA, Universidade Federal de Viçosa; PAULO SÁVIO LOPES, Universidade Federal de Viçosa; JÚLIO CARVALHEIRA, Universidade do Porto; DELVAN ALVES SILVA, Universidade Federal de Viçosa; ALESSANDRA ALVES SILVA, Universidade Federal de Viçosa; FABYANO FONSECA SILVA, Universidade Federal de Viçosa; RENATA VERONEZE, Universidade Federal de Viçosa; GERTRUDE THOMPSON, Universidade do Porto; CLAUDIO NAPOLIS COSTA, CNPGL. |
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Título: |
Autoregressive model for genetic evaluation of longitudinal reproductive traits in Brazilian Holstein cattle. |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
Reproduction in Domestic Animals, v. 56, n. 3, p. 391-399, 2021. |
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Idioma: |
Inglês |
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Conteúdo: |
Reproductive efficiency is major determinant of the dairy herd profitability. Thus, reproductive traits have been widely used as selection objectives in the current dairy cattle breeding programs. We aimed to evaluate strategies to model days open (DO), calving interval (CI) and daughter pregnancy rate (DPR) in Brazilian Holstein cattle. These reproductive traits were analysed by the autoregressive (AR) model and compared with classical repeatability (REP) model using 127,280, 173,092 and 127,280 phenotypic records, respectively. The first three calving orders of cows from 1,469 Holstein herds were used here. The AR model reported lower values for Akaike Information Criteria and Mean Square Errors, as well as larger model probabilities, for all evaluated traits. Similarly, larger additive genetic and lower residual variances were estimated from AR model. Heritability and repeatability estimates were similar for both models. Heritabilities for DO, CI and DPR were 0.04, 0.07 and 0.04; and 0.05, 0.06 and 0.04 for AR and REP models, respectively. Individual EBV reliabilities estimated from AR for DO, CI and DPR were, in average, 0.29, 0.30 and 0.29 units higher than those obtained from REP model. Rank correlation between EBVs obtained from AR and REP models considering the top 10 bulls ranged from 0.72 to 0.76; and increased from 0.98 to 0.99 for the top 100 bulls. The percentage of coincidence between selected bulls from both methods increased over the number of bulls included in the top groups. Overall, the results of model-fitting criteria, genetic parameters estimates and EBV predictions were favourable to the AR model, indicating that it may be applied for genetic evaluation of longitudinal reproductive traits in Brazilian Holstein cattle. MenosReproductive efficiency is major determinant of the dairy herd profitability. Thus, reproductive traits have been widely used as selection objectives in the current dairy cattle breeding programs. We aimed to evaluate strategies to model days open (DO), calving interval (CI) and daughter pregnancy rate (DPR) in Brazilian Holstein cattle. These reproductive traits were analysed by the autoregressive (AR) model and compared with classical repeatability (REP) model using 127,280, 173,092 and 127,280 phenotypic records, respectively. The first three calving orders of cows from 1,469 Holstein herds were used here. The AR model reported lower values for Akaike Information Criteria and Mean Square Errors, as well as larger model probabilities, for all evaluated traits. Similarly, larger additive genetic and lower residual variances were estimated from AR model. Heritability and repeatability estimates were similar for both models. Heritabilities for DO, CI and DPR were 0.04, 0.07 and 0.04; and 0.05, 0.06 and 0.04 for AR and REP models, respectively. Individual EBV reliabilities estimated from AR for DO, CI and DPR were, in average, 0.29, 0.30 and 0.29 units higher than those obtained from REP model. Rank correlation between EBVs obtained from AR and REP models considering the top 10 bulls ranged from 0.72 to 0.76; and increased from 0.98 to 0.99 for the top 100 bulls. The percentage of coincidence between selected bulls from both methods increased over the number of bulls included ... Mostrar Tudo |
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Palavras-Chave: |
Avaliação genética; Cow fertility; Desempenho reprodutivo; Model evaluation. |
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Thesagro: |
Bovino; Fertilidade; Gado Holandês; Reprodução Animal. |
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Thesaurus NAL: |
Autocorrelation; Reproductive performance. |
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Categoria do assunto: |
L Ciência Animal e Produtos de Origem Animal |
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Marc: |
LEADER 02755naa a2200337 a 4500
001 2133402
005 2021-08-10
008 2021 bl uuuu u00u1 u #d
100 1 $aSILVA, H. T.
245 $aAutoregressive model for genetic evaluation of longitudinal reproductive traits in Brazilian Holstein cattle.$h[electronic resource]
260 $c2021
520 $aReproductive efficiency is major determinant of the dairy herd profitability. Thus, reproductive traits have been widely used as selection objectives in the current dairy cattle breeding programs. We aimed to evaluate strategies to model days open (DO), calving interval (CI) and daughter pregnancy rate (DPR) in Brazilian Holstein cattle. These reproductive traits were analysed by the autoregressive (AR) model and compared with classical repeatability (REP) model using 127,280, 173,092 and 127,280 phenotypic records, respectively. The first three calving orders of cows from 1,469 Holstein herds were used here. The AR model reported lower values for Akaike Information Criteria and Mean Square Errors, as well as larger model probabilities, for all evaluated traits. Similarly, larger additive genetic and lower residual variances were estimated from AR model. Heritability and repeatability estimates were similar for both models. Heritabilities for DO, CI and DPR were 0.04, 0.07 and 0.04; and 0.05, 0.06 and 0.04 for AR and REP models, respectively. Individual EBV reliabilities estimated from AR for DO, CI and DPR were, in average, 0.29, 0.30 and 0.29 units higher than those obtained from REP model. Rank correlation between EBVs obtained from AR and REP models considering the top 10 bulls ranged from 0.72 to 0.76; and increased from 0.98 to 0.99 for the top 100 bulls. The percentage of coincidence between selected bulls from both methods increased over the number of bulls included in the top groups. Overall, the results of model-fitting criteria, genetic parameters estimates and EBV predictions were favourable to the AR model, indicating that it may be applied for genetic evaluation of longitudinal reproductive traits in Brazilian Holstein cattle.
650 $aAutocorrelation
650 $aReproductive performance
650 $aBovino
650 $aFertilidade
650 $aGado Holandês
650 $aReprodução Animal
653 $aAvaliação genética
653 $aCow fertility
653 $aDesempenho reprodutivo
653 $aModel evaluation
700 1 $aLOPES, P. S.
700 1 $aCARVALHEIRA, J.
700 1 $aSILVA, D. A.
700 1 $aSILVA, A. A.
700 1 $aSILVA, F. F.
700 1 $aVERONEZE, R.
700 1 $aTHOMPSON, G.
700 1 $aCOSTA, C. N.
773 $tReproduction in Domestic Animals$gv. 56, n. 3, p. 391-399, 2021.
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