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1.
Rev. peru. biol. (Impr.) ; 29(4)oct. 2022.
Artigo em Inglês | LILACS-Express | LILACS | ID: biblio-1424289

RESUMO

The present study analyses the geographical distribution, conservation status, and nomenclature of Peruvian endemic Pedersenia weberbaueri. The species distribution was modelled using MaxEnt based on occurrence data and bioclimatic variables. The conservation status of the species was assessed against the categories and criteria of the IUCN Red List, and nomenclatural and typification issues were resolved. The potential distribution map of P. weberbaueri shows that the species is restricted to the seasonally dry tropical forests of the Marañón valley within a narrow latitudinal, longitudinal, and elevational range. Consequently, we propose to categorise the species as Endangered (EN) and provide the necessary information for its inclusion in the IUCN Red List. Finally, we resolve nomenclatural issues and designate a lectotype. The results contribute to the biological knowledge of P. weberbaueri and support subsequent conservation management plans.


El presente estudio analiza la distribución geográfica, el estado de conservación y la nomenclatura de la endémica peruana Pedersenia weberbaueri. La distribución de especies se modeló usando MaxEnt con base en datos de ocurrencia y variables bioclimáticas. Se evaluó el estado de conservación de la especie frente a las categorías y criterios de la Lista Roja de la UICN y se resolvieron cuestiones de nomenclatura y tipificación. El mapa de distribución potencial de P. weberbaueri muestra que la especie está restringida a los bosques tropicales estacionalmente secos del valle del Marañón dentro de un estrecho rango latitudinal, longitudinal y altitudinal. En consecuencia, proponemos categorizar a la especie como En Peligro (EN) y brindar la información necesaria para su inclusión en la Lista Roja de la UICN. Finalmente, resolvemos cuestiones de nomenclatura y designamos un lectotipo. Los resultados contribuyen al conocimiento biológico de P. weberbaueri y respaldan los planes de manejo de conservación posteriores.

2.
Nat Plants ; 5(11): 1136-1144, 2019 11.
Artigo em Inglês | MEDLINE | ID: mdl-31712754

RESUMO

Taxonomic monographs have the potential to make a unique contribution to the understanding of global biodiversity. However, such studies, now rare, are often considered too daunting to undertake within a realistic time frame, especially as the world's collections have doubled in size in recent times. Here, we report a global-scale monographic study of morning glories (Ipomoea) that integrated DNA barcodes and high-throughput sequencing with the morphological study of herbarium specimens. Our approach overhauled the taxonomy of this megadiverse group, described 63 new species and uncovered significant increases in net diversification rates comparable to the most iconic evolutionary radiations in the plant kingdom. Finally, we show that more than 60 species of Ipomoea, including sweet potato, independently evolved storage roots in pre-human times, indicating that the storage root is not solely a product of human domestication but a trait that predisposed the species for cultivation. This study demonstrates how the world's natural history collections can contribute to global challenges in the Anthropocene.


Assuntos
Ipomoea/classificação , Bancos de Espécimes Biológicos , Código de Barras de DNA Taxonômico , DNA de Plantas , Evolução Molecular , Filogenia , Filogeografia , Análise de Sequência de DNA
3.
Curr Biol ; 25(22): R1066-7, 2015 Nov 16.
Artigo em Inglês | MEDLINE | ID: mdl-26583892

RESUMO

Specimens of plants and animals preserved in museums are the primary source of verifiable data on the geographical and temporal distribution of organisms. Museum datasets are increasingly being uploaded to aggregated regional and global databases (e.g. the Global Biodiversity Information Facility; GBIF) for use in a wide range of analyses. Thus, digitisation of natural history collections is providing unprecedented information to facilitate the study of the natural world on a global scale. The digitisation of this information utilises information provided on specimen labels, and assumes they are correctly identified. Here we evaluate the accuracy of names associated with 4,500 specimens of African gingers from 40 herbaria in 21 countries. Our data show that at least 58% of the specimens had the wrong name prior to a recent taxonomic study. A similar pattern of wrongly named specimens is also shown for Dipterocarps and Ipomoea (morning glory). We also examine the number of available plant specimens worldwide. Our data demonstrate that, while the world's collections have more than doubled since 1970, more than 50% of tropical specimens, on average, are likely to be incorrectly named. This finding has serious implications for the uncritical use of specimen data from natural history collections.


Assuntos
História Natural/métodos , História Natural/normas , Plantas/classificação , Biodiversidade , Bases de Dados Factuais , Geografia , Museus , Reprodutibilidade dos Testes
4.
Healthc Technol Lett ; 2(1): 34-9, 2015 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-26609402

RESUMO

The global trend for increasing life expectancy is resulting in aging populations in a number of countries. This brings to bear a pressure to provide effective care for the older population with increasing constraints on available resources. Providing care for and maintaining the independence of an older person in their own home is one way that this problem can be addressed. The EU Funded Unobtrusive Smart Environments for Independent Living (USEFIL) project is an assistive technology tool being developed to enhance independent living. As part of USEFIL, a wrist wearable unit (WWU) is being developed to monitor the physical activity (PA) of the user and integrate with the USEFIL system. The WWU is a novel application of an existing technology to the assisted living problem domain. It combines existing technologies and new algorithms to extract PA parameters for activity monitoring. The parameters that are extracted include: activity level, step count and worn state. The WWU, the algorithms that have been developed and a preliminary validation are presented. The results show that activity level can be successfully extracted, that worn state can be correctly identified and that step counts in walking data can be estimated within 3% error, using the controlled dataset.

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