Show simple item record

Files in this item


Item metadata

dc.contributor.authorJohnston, Alison
dc.contributor.authorMatechou, Eleni
dc.contributor.authorDennis, Emily
dc.identifier.citationJohnston , A , Matechou , E & Dennis , E 2023 , ' Outstanding challenges and future directions for biodiversity monitoring using citizen science data ' , Methods in Ecology and Evolution , vol. 14 , no. 1 , pp. 103-116 .
dc.identifier.otherRIS: urn:3F4017DEDE4BF3B87C7C1B66F09992F0
dc.identifier.otherORCID: /0000-0001-8221-013X/work/110131909
dc.descriptionFunding: AJ was partially funded through the 2017-2018 Belmont Forum and BiodivERsA joint call for research proposals, under the BiodivScen ERA-Net COFUND program, with financial support from the Academy of Finland (AKA, Univ. Turku: 326327, Univ. Helsinki: 326338), the Swedish Research Council (Formas, SLU: 2018-02440, Lund Univ.: 2018-02441), the Research Council of Norway (Forskningsrådet, NINA: 295767) and the U.S. National Science Foundation (NSF, Cornell Univ.: ICER-1927646).en
dc.description.abstract1 There is increasing availability and use of unstructured and semi-structured citizen science data in biodiversity research and conservation. This expansion of a rich source of 'big data' has sparked numerous research directions, driving the development of analytical approaches that account for the complex observation processes in these datasets. 2 We review outstanding challenges in the analysis of citizen science data for biodiversity monitoring. For many of these challenges, the potential impact on ecological inference is unknown. Further research can document these impacts and explore ways to address them. In addition to outlining research directions, describing these challenges may be useful in considering the design of future citizen science projects or additions to existing projects. 3 We outline challenges for biodiversity monitoring using citizen science data in four partially-overlapping categories: challenges that arise as a result of 1) observer behaviour; 2) data structures; 3) statistical models; and 4) communication. Potential solutions for these challenges are combinations of: a) collecting additional data or metadata; b) analytically combining different datasets; c) developing or refining statistical models. 4 Whilst there has been important progress to develop models that tackle most of these challenges, there remain substantial gains in biodiversity monitoring and subsequent conservation actions that we believe will be possible by further research and development in these areas. The degree of challenge and opportunity that each of these presents varies substantially across different datasets, taxa, and ecological questions. In some cases, a route forward to address these challenges is clear, whilst in other cases there is more scope for exploration and creativity.
dc.relation.ispartofMethods in Ecology and Evolutionen
dc.subjectCitizen scienceen
dc.subjectCommunity scienceen
dc.subjectMulti-species modelsen
dc.subjectObservation processen
dc.subjectOccupancy modelsen
dc.subjectStatistical ecologyen
dc.subjectHA Statisticsen
dc.titleOutstanding challenges and future directions for biodiversity monitoring using citizen science dataen
dc.typeJournal articleen
dc.contributor.institutionUniversity of St Andrews. Statisticsen
dc.contributor.institutionUniversity of St Andrews. Centre for Research into Ecological & Environmental Modellingen
dc.description.statusPeer revieweden

This item appears in the following Collection(s)

Show simple item record