Literature DB >> 17531062

Limitations of biodiversity databases: case study on seed-plant diversity in Tenerife, Canary Islands.

Joaquín Hortal1, Jorge M Lobo, Alberto Jiménez-Valverde.   

Abstract

Databases on the distribution of species can be used to describe the geographic patterns of biodiversity. Nevertheless, they have limitations. We studied three of these limitations: (1) inadequacy of raw data to describe richness patterns due to sampling bias, (2) lack of survey effort assessment (and lack of exhaustiveness in compiling data about survey effort), and (3) lack of coverage of the geographic and environmental variations that affect the distribution of organisms. We used a biodiversity database (BIOTA-Canarias) to analyze richness data from a well-known group (seed plants) in an intensively surveyed area (Tenerife Island). Observed richness and survey effort were highly correlated. Species accumulation curves could not be used to determine survey effort because data digitalization was not exhaustive, so we identified well-sampled sites based on observed richness to sampling effort ratios. We also developed a predictive model based on the data from well-sampled sites and analyzed the origin of the geographic errors in the obtained extrapolation by means of a geographically constrained cross-validation. The spatial patterns of seed-plant species richness obtained from BIOTA-Canarias data were incomplete and biased. Therefore, some improvements are needed to use this database (and many others) in biodiversity studies. We propose a protocol that includes controls on data quality, improvements on data digitalization and survey design to improve data quality, and some alternative data analysis strategies that will provide a reliable picture of biodiversity patterns.

Entities:  

Mesh:

Year:  2007        PMID: 17531062     DOI: 10.1111/j.1523-1739.2007.00686.x

Source DB:  PubMed          Journal:  Conserv Biol        ISSN: 0888-8892            Impact factor:   6.560


  32 in total

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2.  Displaying bias in sampling effort of data accessed from biodiversity databases using ignorance maps.

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Journal:  Biodivers Data J       Date:  2015-07-28

3.  Remoteness promotes biological invasions on islands worldwide.

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Journal:  Proc Natl Acad Sci U S A       Date:  2018-08-29       Impact factor: 11.205

Review 4.  Orchid conservation and research: An analysis of gaps and priorities for globally Red Listed species.

Authors:  Jenna Wraith; Patrick Norman; Catherine Pickering
Journal:  Ambio       Date:  2020-01-20       Impact factor: 5.129

5.  A novel method to handle the effect of uneven sampling effort in biodiversity databases.

Authors:  Iker Pardo; María P Pata; Daniel Gómez; María B García
Journal:  PLoS One       Date:  2013-01-11       Impact factor: 3.240

6.  Environmental correlates for tree occurrences, species distribution and richness on a high-elevation tropical island.

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Journal:  AoB Plants       Date:  2015-07-10       Impact factor: 3.276

7.  Are we filling the data void? An assessment of the amount and extent of plant collection records and census data available for tropical South America.

Authors:  Kenneth Feeley
Journal:  PLoS One       Date:  2015-04-30       Impact factor: 3.240

8.  Spatial scaling of non-native fish richness across the United States.

Authors:  Qinfeng Guo; Julian D Olden
Journal:  PLoS One       Date:  2014-05-20       Impact factor: 3.240

9.  Legume diversity patterns in West Central Africa: influence of species biology on distribution models.

Authors:  Manuel de la Estrella; Rubén G Mateo; Jan J Wieringa; Barbara Mackinder; Jesús Muñoz
Journal:  PLoS One       Date:  2012-07-23       Impact factor: 3.240

10.  Knowledge gaps hamper understanding the relationship between fragmentation and biodiversity loss: the case of Atlantic Forest fruit-feeding butterflies.

Authors:  Thadeu Sobral-Souza; Juliana Stropp; Jessie Pereira Santos; Victor Mateus Prasniewski; Neucir Szinwelski; Bruno Vilela; André Victor Lucci Freitas; Milton Cezar Ribeiro; Joaquín Hortal
Journal:  PeerJ       Date:  2021-06-25       Impact factor: 2.984

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