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Spider species richness and sampling effort at Cracraft´S Belém Area of Endemism

Overview of attention for article published in Anais da Academia Brasileira de Ciências, September 2017
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Title
Spider species richness and sampling effort at Cracraft´S Belém Area of Endemism
Published in
Anais da Academia Brasileira de Ciências, September 2017
DOI 10.1590/0001-3765201720150378
Pubmed ID
Authors

Bruno V B Rodrigues, Manoel B Aguiar-Neto, Ubirajara DE Oliveira, Adalberto J Santos, Antonio D Brescovit, Marlúcia B Martíns, Alexandre B Bonaldo

Abstract

A list of spider species is presented for the Belém Area of Endemism, the most threatened region in the Amazon Basin, comprising portions of eastern State of Pará and western State of Maranhão, Brazil. The data are based both on records from the taxonomic and biodiversity survey literature and on scientific collection databases. A total of 319 identified species were recorded, with 318 occurring in Pará and only 22 in Maranhão. About 80% of species are recorded at the vicinities of the city of Belém, indicating that sampling effort have been strongly biased. To identify potentially high-diversity areas, discounting the effect of variations in sampling effort, the residues of a linear regression between the number of records and number of species mapped in each 0.25°grid cells were analyzed. One grid, representing the Alto Turiaçu Indigenous land, had the highest deviation from the expected from the linear regression, indicating high expected species richness. Several other grid cells showed intermediate values of the regression residuals, indicating species richness moderately above to the expected from the model.

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Geographical breakdown

Country Count As %
Unknown 26 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 15%
Student > Bachelor 3 12%
Student > Doctoral Student 2 8%
Professor 2 8%
Researcher 2 8%
Other 2 8%
Unknown 11 42%
Readers by discipline Count As %
Agricultural and Biological Sciences 6 23%
Environmental Science 5 19%
Computer Science 2 8%
Arts and Humanities 1 4%
Unknown 12 46%