Dataset Information

Modelling Highly Biodiverse Areas in Brazil.

ABSTRACT: Traditional conservation techniques for mapping highly biodiverse areas assume there to be satisfactory knowledge about the geographic distribution of biodiversity. There are, however, large gaps in biological sampling and hence knowledge shortfalls. This problem is even more pronounced in the tropics. Indeed, the use of only a few taxonomic groups or environmental surrogates for modelling biodiversity is not viable in mega-diverse countries, such as Brazil. To overcome these limitations, we developed a comprehensive spatial model that includes phylogenetic information and other several biodiversity dimensions aimed at mapping areas with high relevance for biodiversity conservation. Our model applies a genetic algorithm tool for identifying the smallest possible region within a unique biota that contains the most number of species and phylogenetic diversity, as well as the highest endemicity and phylogenetic endemism. The model successfully pinpoints small highly biodiverse areas alongside regions with knowledge shortfalls where further sampling should be conducted. Our results suggest that conservation strategies should consider several taxonomic groups, the multiple dimensions of biodiversity, and associated sampling uncertainties.

SUBMITTER: Oliveira U

PROVIDER: S-EPMC6479156 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Modelling Highly Biodiverse Areas in Brazil.

Oliveira Ubirajara U Soares-Filho Britaldo Silveira BS Santos Adalberto J AJ Paglia Adriano Pereira AP Brescovit Antonio D AD de Carvalho Claudio J B CJB Silva Daniel Paiva DP Rezende Daniella T DT Leite Felipe Sá Fortes FSF Batista João Aguiar Nogueira JAN Barbosa João Paulo Peixoto Pena JPPP Stehmann João Renato JR Ascher John S JS Vasconcelos Marcelo F MF Marco Paulo De P Löwenberg-Neto Peter P Ferro Viviane Gianluppi VG

Scientific reports 20190423 1

Traditional conservation techniques for mapping highly biodiverse areas assume there to be satisfactory knowledge about the geographic distribution of biodiversity. There are, however, large gaps in biological sampling and hence knowledge shortfalls. This problem is even more pronounced in the tropics. Indeed, the use of only a few taxonomic groups or environmental surrogates for modelling biodiversity is not viable in mega-diverse countries, such as Brazil. To overcome these limitations, we dev ...[more]

PMID: 31015555

Similar Datasets

Project description:BACKGROUND:Research on discrimination and health focused on older adults has been scarce, comparatively with younger and middle-aged adults. Considering where people live matters, accurate measures of perceived discrimination might consider how the place of residence interferes on discriminatory experiences. This study aimed to assess the association between perceived discrimination and urban/rural place of residence among a representative sample of older adults in Brazil. METHODS:Data came from the baseline of the Brazilian Longitudinal Study of Aging (ELSI-Brazil), conducted in 2015/2016, with individuals aged 50 years and older. Perceived Discrimination was measured by means of the following question: "In the past 12 months have you felt a victim of any type of discrimination" with five possible answers: (1)"when you sought medical services or health care?", (2)"in social gatherings?", (3)"in the work place?", (4)"within the family?", (5)"due to where you live?". Participants who answered yes for any of the five domains were coded as having reported an experience of discrimination. The main exposure variable was the urban-rural classification of the households, carried out according to the methods employed by the Brazilian Institute of Geography and Statistics during the 2010 Population Census. Other covariates included: age, sex, skin color, household wealth and education. Multiple Poisson regression was used to estimate prevalence ratios and their respective 95% confidence interval for the association between discrimination and independent variables. RESULTS:Prevalence of any perceived discrimination among Brazilian older adults was 16.8%. Regardless the place of residence (either urban or rural), participants reported health care settings as the most common domain where discriminatory experiences occurred and the work place as the least common. According to the adjusted model, perceived discrimination was significantly higher among urban dwellers when compared to their rural counterparts, independent of sociodemographic characteristics, health status and neighborhood social environment. The outcome was significant associated with skin color, education and health status. CONCLUSIONS:Urban environment plays a core role in perceived discrimination and health care settings constitute the most common domain where discriminatory experiences occurred. Our findings may contribute to fulfill the knowledge gap on discrimination among older adults living in developing countries.

Dataset Information

Modelling Highly Biodiverse Areas in Brazil.

Publications

Modelling Highly Biodiverse Areas in Brazil.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets