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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha : |
04/11/2024 |
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Actualizado : |
04/11/2024 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Autor : |
GUIDO, A. C.; ALTESOR, A.; CAYSSIALS, V.; LEZAMA, F.; MELLO, A. L.; PARUELO, J.; BAEZA, S. |
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Afiliación : |
ANA CLARA GUIDO, Facultad de Ciencias, Instituto de Ecología y Ciencias Ambientales, Universidad de la República, Montevideo, Uruguay; ALICE ALTESOR, Facultad de Ciencias, Instituto de Ecología y Ciencias Ambientales, Universidad de la República, Montevideo, Uruguay; VALERIE CAYSSIALS, Facultad de Veterinaria, Unidad de Bioestadística, Universidad de la República, Montevideo, Uruguay; FELIPE LEZAMA, Departamento de Sistemas Ambientales, Facultad de Agronomía, Universidad de la República, Montevideo, Uruguay; ANA LAURA MELLO, Dirección Nacional de Biodiversidad y Servicios Ecosistémicos, Ministerio de Ambiente, Ministerio de Ambiente, Uruguay; JOSÉ PARUELO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; Fac. Ciencias, Instituto de Ecología y Ciencias Ambientales, UdelaR, Montevideo, Uruguay; IFEVA-Fac. Agronomía, Universidad de Buenos Aires & CONICET, Buenos Aires, Argentina; SANTIAGO BAEZA, Departamento de Sistemas Ambientales, Facultad de Agronomía, Universidad de la República, Montevideo, Uruguay. |
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Título : |
Patterns and drivers of alien plant invasion in Uruguayan grasslands. |
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Complemento del título : |
Special Issue: Invasions in plant communities. |
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Fecha de publicación : |
2024 |
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Fuente / Imprenta : |
Journal of Vegetation Science, September/October 2024, Volume 35, Issue 5, e13306. https://doi.org/10.1111/jvs.13306 |
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ISSN : |
1100-9233 |
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DOI : |
10.1111/jvs.13306 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 14 December 2023, Revised 29 June 2024, Accepted 20 August 2024. -- Correspondence: Guido, A.; Instituto de Ecología y Ciencias Ambientales, Facultad de Ciencias, Universidad de la República, Montevideo, Uruguay; email:aguido@fcien.edu.uy --
Co-ordinating Editor: Milan Chytrý. -- Funding: Instituto Nacional de Investigación Agropecuaria; Agencia Nacional de Investigación e Innovación; Comisión Sectorial de Investigación Científica. -- This article is a part of the Special Issue Biological Invasions in Plant Communities, edited by Viktoria Wagner, Marta Carboni, Kwek Yan Chong, Milan Chytrý and Anaclara Guido. -- |
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Contenido : |
ABSTRACT.- Question: Understanding the patterns of alien plant invasions and their underlying drivers is a key step in conserving the remaining native grasslands of Uruguay. We addressed the level of invasion by considering the four invasive alien plants of these ecosystems, Cynodon dactylon, Eragrostis plana, Senecio madagascariensis and Ulex europaeus, throughout the country. Location: Remnant native grasslands of Uruguay, constituting part of the Río de la Plata grasslands. Methods: Extensive fieldwork was carried out over five years of data collection, including hierarchically randomized observations (around 2000) nested in 137 10 × 10-km2 squares covering different geomorphological regions. For each invasive alien species, we constructed distribution maps to show their patterns; for the two most abundant, we fitted models to identify the main explanatory variables at different spatial scales. Results: We found that 77% of the squares were invaded by at least one target species. The level of invasion varied between regions and target plants. The most abundant invasive alien species were Cynodon dactylon and Senecio madagascariensis; while Eragrostis plana and Ulex europaeus were scarce. Cynodon dactylon cover was related to a set of variables at different spatial scales, including climate, topography and several local community descriptors. Senecio madagascariensis cover was positively associated with grassland fragmentation and anthropic disturbance at the landscape, and a few local descriptors. Conclusions: The large sampling effort at the country level, with a randomized design, allowed for a reliable assessment of the level of invasion of Uruguayan grasslands and its possible drivers. This is an important step in the design of policies to conserve Uruguay's remaining native grasslands. We suggest that the prevention should focus on the Basaltic Cuestas region, while control and containment should prioritize the eastern and south-central parts of the country, focusing mainly on Cynodon dactylon management. © 2024 International Association for Vegetation Science. MenosABSTRACT.- Question: Understanding the patterns of alien plant invasions and their underlying drivers is a key step in conserving the remaining native grasslands of Uruguay. We addressed the level of invasion by considering the four invasive alien plants of these ecosystems, Cynodon dactylon, Eragrostis plana, Senecio madagascariensis and Ulex europaeus, throughout the country. Location: Remnant native grasslands of Uruguay, constituting part of the Río de la Plata grasslands. Methods: Extensive fieldwork was carried out over five years of data collection, including hierarchically randomized observations (around 2000) nested in 137 10 × 10-km2 squares covering different geomorphological regions. For each invasive alien species, we constructed distribution maps to show their patterns; for the two most abundant, we fitted models to identify the main explanatory variables at different spatial scales. Results: We found that 77% of the squares were invaded by at least one target species. The level of invasion varied between regions and target plants. The most abundant invasive alien species were Cynodon dactylon and Senecio madagascariensis; while Eragrostis plana and Ulex europaeus were scarce. Cynodon dactylon cover was related to a set of variables at different spatial scales, including climate, topography and several local community descriptors. Senecio madagascariensis cover was positively associated with grassland fragmentation and anthropic disturbance at the landscape, an... Presentar Todo |
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Palabras claves : |
Alien species; Biological invasions; Exotic species; Invasibility; Invasion pattern; Invasive species; Río de la Plata grasslands. |
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Asunto categoría : |
P01 Conservación de la naturaleza y recursos de La tierra |
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Marc : |
LEADER 03682naa a2200313 a 4500
001 1064908
005 2024-11-04
008 2024 bl uuuu u00u1 u #d
022 $a1100-9233
024 7 $a10.1111/jvs.13306$2DOI
100 1 $aGUIDO, A. C.
245 $aPatterns and drivers of alien plant invasion in Uruguayan grasslands.$h[electronic resource]
260 $c2024
500 $aArticle history: Received 14 December 2023, Revised 29 June 2024, Accepted 20 August 2024. -- Correspondence: Guido, A.; Instituto de Ecología y Ciencias Ambientales, Facultad de Ciencias, Universidad de la República, Montevideo, Uruguay; email:aguido@fcien.edu.uy -- Co-ordinating Editor: Milan Chytrý. -- Funding: Instituto Nacional de Investigación Agropecuaria; Agencia Nacional de Investigación e Innovación; Comisión Sectorial de Investigación Científica. -- This article is a part of the Special Issue Biological Invasions in Plant Communities, edited by Viktoria Wagner, Marta Carboni, Kwek Yan Chong, Milan Chytrý and Anaclara Guido. --
520 $aABSTRACT.- Question: Understanding the patterns of alien plant invasions and their underlying drivers is a key step in conserving the remaining native grasslands of Uruguay. We addressed the level of invasion by considering the four invasive alien plants of these ecosystems, Cynodon dactylon, Eragrostis plana, Senecio madagascariensis and Ulex europaeus, throughout the country. Location: Remnant native grasslands of Uruguay, constituting part of the Río de la Plata grasslands. Methods: Extensive fieldwork was carried out over five years of data collection, including hierarchically randomized observations (around 2000) nested in 137 10 × 10-km2 squares covering different geomorphological regions. For each invasive alien species, we constructed distribution maps to show their patterns; for the two most abundant, we fitted models to identify the main explanatory variables at different spatial scales. Results: We found that 77% of the squares were invaded by at least one target species. The level of invasion varied between regions and target plants. The most abundant invasive alien species were Cynodon dactylon and Senecio madagascariensis; while Eragrostis plana and Ulex europaeus were scarce. Cynodon dactylon cover was related to a set of variables at different spatial scales, including climate, topography and several local community descriptors. Senecio madagascariensis cover was positively associated with grassland fragmentation and anthropic disturbance at the landscape, and a few local descriptors. Conclusions: The large sampling effort at the country level, with a randomized design, allowed for a reliable assessment of the level of invasion of Uruguayan grasslands and its possible drivers. This is an important step in the design of policies to conserve Uruguay's remaining native grasslands. We suggest that the prevention should focus on the Basaltic Cuestas region, while control and containment should prioritize the eastern and south-central parts of the country, focusing mainly on Cynodon dactylon management. © 2024 International Association for Vegetation Science.
653 $aAlien species
653 $aBiological invasions
653 $aExotic species
653 $aInvasibility
653 $aInvasion pattern
653 $aInvasive species
653 $aRío de la Plata grasslands
700 1 $aALTESOR, A.
700 1 $aCAYSSIALS, V.
700 1 $aLEZAMA, F.
700 1 $aMELLO, A. L.
700 1 $aPARUELO, J.
700 1 $aBAEZA, S.
773 $tJournal of Vegetation Science, September/October 2024, Volume 35, Issue 5, e13306. https://doi.org/10.1111/jvs.13306
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INIA Las Brujas (LB) |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
28/07/2023 |
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Actualizado : |
28/07/2023 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
Internacional - -- |
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Autor : |
RODRÍGUEZ, J.D.; PERIPOLLI, E.; LONDOÑO-GIL, M.; ESPIGOLAN, R.; LÔBO, R. B.; LÓPEZ-CORREA, R.; AGUILAR, I.; BALDI, F. |
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Afiliación : |
JUAN DIEGO RODRÍGUEZ, Faculdade de Ciências Agrarias e Veterinárias, Departamento de Zootecnia, Universidade Estadual Paulista (Unesp), Jaboticabal, 14884-900, Brazil.; ELISA PERIPOLLI, Faculdade de Ciências Agrarias e Veterinárias, Departamento de Zootecnia, Universidade Estadual Paulista (Unesp), Jaboticabal, 14884-900, Brazil; MARISOL LONDOÑO-GIL, Faculdade de Ciências Agrarias e Veterinárias, Departamento de Zootecnia, Universidade Estadual Paulista (Unesp), Jaboticabal, 14884-900, Brazil; RAFAEL ESPIGOLAN, Faculdade de Zootecnia e Engenharia de Alimentos, Departamento de Medicina Veterinária, Universidade de São Paulo (Usp), Pirassununga, 13535-900, Brazil.; RAYSILDO BARBOSA LÔBO, Associação Nacional de Criadores e Pesquisadores, Ribeirão Preto, Brazil; RODRIGO LÓPEZ-CORREA, Facultad de Veterinaria, Departamento de Genética y Mejoramiento Animal, Universidad de la República, Montevideo, Uruguay; IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; FERNANDO BALDI, Faculdade de Ciências Agrarias e Veterinárias, Departamento de Zootecnia, Universidade Estadual Paulista (Unesp), Jaboticabal, 14884-900, Brazil. |
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Título : |
Effect of minor allele frequency and density of single nucleotide polymorphism marker arrays on imputation performance and prediction ability using the single-step genomic Best Linear Unbiased Prediction in a simulated beef cattle population. |
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Complemento del título : |
Research paper. |
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Fecha de publicación : |
2023 |
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Fuente / Imprenta : |
Animal Production Science. 2023, volume 63, issue 9, p. 844-852. https://doi.org/10.1071/AN21581 |
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ISSN : |
1836-0939; eISSN: 1836-5787. |
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DOI : |
10.1071/AN21581 |
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Idioma : |
Inglés |
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Notas : |
Article history: Submitted 1 December 2021, Accepted 1 March 2023, Published 4 April 2023. -- Correspondence to: Juan Diego Rodríguez,
Universidade Estadual Paulista (Unesp), Faculdade de Ciências Agrarias e Veterinárias, Departamento de Zootecnia, Jaboticabal, 14884-900, Brazil. Email: juan.diego@unesp.br -- Handling Editor: Kim Bunter. -- |
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Contenido : |
Context: In beef cattle populations, there is little evidence regarding the minimum number of genetic markers needed to obtain reliable genomic prediction and imputed genotypes.
Aims: This study aimed to evaluate the impact of single nucleotide polymorphism (SNP) marker density and minor allele frequency (MAF), on genomic predictions and imputation performance for high and low heritability traits using the single-step genomic Best Linear Unbiased Prediction methodology (ssGBLUP) in a simulated beef cattle population.
© 2023 The Author(s) (or their employer(s)). Published by CSIRO Publishing |
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Palabras claves : |
Bias; Bovine; Customised SNP arrays; Genomic selection; Imputation accuracy; Inflation; MAF; Simulation. |
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Asunto categoría : |
L10 Genética y mejoramiento animal |
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Marc : |
LEADER 02068naa a2200337 a 4500
001 1064277
005 2023-07-28
008 2023 bl uuuu u00u1 u #d
022 $a1836-0939; eISSN: 1836-5787.
024 7 $a10.1071/AN21581$2DOI
100 1 $aRODRÍGUEZ, J.D.
245 $aEffect of minor allele frequency and density of single nucleotide polymorphism marker arrays on imputation performance and prediction ability using the single-step genomic Best Linear Unbiased Prediction in a simulated beef cattle population.$h[electronic resource]
260 $c2023
500 $aArticle history: Submitted 1 December 2021, Accepted 1 March 2023, Published 4 April 2023. -- Correspondence to: Juan Diego Rodríguez, Universidade Estadual Paulista (Unesp), Faculdade de Ciências Agrarias e Veterinárias, Departamento de Zootecnia, Jaboticabal, 14884-900, Brazil. Email: juan.diego@unesp.br -- Handling Editor: Kim Bunter. --
520 $aContext: In beef cattle populations, there is little evidence regarding the minimum number of genetic markers needed to obtain reliable genomic prediction and imputed genotypes. Aims: This study aimed to evaluate the impact of single nucleotide polymorphism (SNP) marker density and minor allele frequency (MAF), on genomic predictions and imputation performance for high and low heritability traits using the single-step genomic Best Linear Unbiased Prediction methodology (ssGBLUP) in a simulated beef cattle population. © 2023 The Author(s) (or their employer(s)). Published by CSIRO Publishing
653 $aBias
653 $aBovine
653 $aCustomised SNP arrays
653 $aGenomic selection
653 $aImputation accuracy
653 $aInflation
653 $aMAF
653 $aSimulation
700 1 $aPERIPOLLI, E.
700 1 $aLONDOÑO-GIL, M.
700 1 $aESPIGOLAN, R.
700 1 $aLÔBO, R. B.
700 1 $aLÓPEZ-CORREA, R.
700 1 $aAGUILAR, I.
700 1 $aBALDI, F.
773 $tAnimal Production Science. 2023, volume 63, issue 9, p. 844-852. https://doi.org/10.1071/AN21581
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