Mapping species richness using opportunistic samples: a case study on ground-floor bryophyte species richness in the Belgian province of Limburg

In species richness studies, citizen-science surveys where participants make individual decisions regarding sampling strategies provide a cost-effective approach to collect a large amount of data. However, it is unclear to what extent the bias inherent to opportunistically collected samples may invalidate our inferences. Here, we compare spatial predictions of forest ground-floor bryophyte species richness in Limburg (Belgium), based on crowd- and expert-sourced data, where the latter are collected by adhering to a rigorous geographical randomisation and data collection protocol. We develop a... Mehr ...

Verfasser: Neyens, Thomas
Diggle, Peter
Faes, Christel
Beenaerts, Natalie
Artois, Tom
Giorgi, Emanuele
Dokumenttyp: other
Erscheinungsdatum: 2019
Schlagwörter: Crowdsourcing / sampling bias
Sprache: unknown
Permalink: https://search.fid-benelux.de/Record/base-26533216
Datenquelle: BASE; Originalkatalog
Powered By: BASE
Link(s) : https://zenodo.org/record/4942713