Spatial distribution of citizen science casuistic observations for different taxonomic groups
MetadataShow full item record
Opportunistic citizen science databases are becoming an important way of gathering information on species distributions. These data are temporally and spatially dispersed and could have limitations regarding biases in the distribution of the observations in space and/or time. In this work, we test the influence of landscape variables in the distribution of citizen science observations for eight taxonomic groups. We use data collected through a Portuguese citizen science database (biodiversity4all.org). We use a zero-inflated negative binomial regression to model the distribution of observations as a function of a set of variables representing the landscape features plausibly influencing the spatial distribution of the records. Results suggest that the density of paths is the most important variable, having a statistically significant positive relationship with number of observations for seven of the eight taxa considered. Wetland coverage was also identified as having a significant, positive relationship, for birds, amphibians and reptiles, and mammals. Our results highlight that the distribution of species observations, in citizen science projects, is spatially biased. Higher frequency of observations is driven largely by accessibility and by the presence of water bodies. We conclude that efforts are required to increase the spatial evenness of sampling effort from volunteers.
Tiago , P , Ceia-Hasse , A , Marques , T A , Capinha , C & Pereira , H M 2017 , ' Spatial distribution of citizen science casuistic observations for different taxonomic groups ' , Scientific Reports , vol. 7 , 12832 . https://doi.org/10.1038/s41598-017-13130-8
© The Author(s) 2017. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
DescriptionPT acknowledges support from the Portuguese Foundation for Science and Technology (FCT/MCTES) (SFRH/BD/89543/2012). ACH acknowledges support from the Portuguese Foundation for Science and Technology (FCT/MCTES) (UID/BIA/50027/2013) and from FEDER through the Operational Programme for Competitiveness Factors – COMPETE (POCI-01-0145-FEDER-006821). TAM thanks partial support by CEAUL (funded by FCT - Fundação para a Ciência e a Tecnologia, Portugal, through the project UID/MAT/00006/2013). CC acknowledges support from the Portuguese Foundation for Science and Technology (FCT) FCT for funds to GHTM - UID/Multi/04413/2013. We thank all volunteers who participate in BioDiversity4All project.
Items in the St Andrews Research Repository are protected by copyright, with all rights reserved, unless otherwise indicated.