Literature DB >> 28474803

Using citizen science butterfly counts to predict species population trends.

Emily B Dennis1,2, Byron J T Morgan1, Tom M Brereton2, David B Roy3, Richard Fox2.   

Abstract

Citizen scientists are increasingly engaged in gathering biodiversity information, but trade-offs are often required between public engagement goals and reliable data collection. We compared population estimates for 18 widespread butterfly species derived from the first 4 years (2011-2014) of a short-duration citizen science project (Big Butterfly Count [BBC]) with those from long-running, standardized monitoring data collected by experienced observers (U.K. Butterfly Monitoring Scheme [UKBMS]). BBC data are gathered during an annual 3-week period, whereas UKBMS sampling takes place over 6 months each year. An initial comparison with UKBMS data restricted to the 3-week BBC period revealed that species population changes were significantly correlated between the 2 sources. The short-duration sampling season rendered BBC counts susceptible to bias caused by interannual phenological variation in the timing of species' flight periods. The BBC counts were positively related to butterfly phenology and sampling effort. Annual estimates of species abundance and population trends predicted from models including BBC data and weather covariates as a proxy for phenology correlated significantly with those derived from UKBMS data. Overall, citizen science data obtained using a simple sampling protocol produced comparable estimates of butterfly species abundance to data collected through standardized monitoring methods. Although caution is urged in extrapolating from this U.K. study of a small number of common, conspicuous insects, we found that mass-participation citizen science can simultaneously contribute to public engagement and biodiversity monitoring. Mass-participation citizen science is not an adequate replacement for standardized biodiversity monitoring but may extend and complement it (e.g., through sampling different land-use types), as well as serving to reconnect an increasingly urban human population with nature.
© 2017 The Authors. Conservation Biology published by Wiley Periodicals, Inc. on behalf of Society for Conservation Biology.

Entities:  

Keywords:  Big Butterfly Count; Esquema de Monitoreo de Mariposas del Reino Unido; Gran Conteo de Mariposas; UK Butterfly Monitoring Scheme; abundancia de mariposas; butterfly abundance; fenología; gardens; generalized abundance index; jardines; phenology; species trends; tendencias de las especies; índice de abundancia generalizada

Mesh:

Year:  2017        PMID: 28474803     DOI: 10.1111/cobi.12956

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


  8 in total

1.  Decision-making of citizen scientists when recording species observations.

Authors:  Diana E Bowler; Netra Bhandari; Lydia Repke; Christoph Beuthner; Corey T Callaghan; David Eichenberg; Klaus Henle; Reinhard Klenke; Anett Richter; Florian Jansen; Helge Bruelheide; Aletta Bonn
Journal:  Sci Rep       Date:  2022-06-30       Impact factor: 4.996

2.  Data-derived metrics describing the behaviour of field-based citizen scientists provide insights for project design and modelling bias.

Authors:  Tom August; Richard Fox; David B Roy; Michael J O Pocock
Journal:  Sci Rep       Date:  2020-07-03       Impact factor: 4.379

3.  Improving big citizen science data: Moving beyond haphazard sampling.

Authors:  Corey T Callaghan; Jodi J L Rowley; William K Cornwell; Alistair G B Poore; Richard E Major
Journal:  PLoS Biol       Date:  2019-06-27       Impact factor: 8.029

4.  Predicting resilience of ecosystem functioning from co-varying species' responses to environmental change.

Authors:  Matthew P Greenwell; Tom Brereton; John C Day; David B Roy; Tom H Oliver
Journal:  Ecol Evol       Date:  2019-09-27       Impact factor: 2.912

5.  Counting Cats: The integration of expert and citizen science data for unbiased inference of population abundance.

Authors:  Jenni L McDonald; Dave Hodgson
Journal:  Ecol Evol       Date:  2021-04-02       Impact factor: 2.912

6.  Human influences shape the first spatially explicit national estimate of urban unowned cat abundance.

Authors:  Jennifer L McDonald; Elizabeth Skillings
Journal:  Sci Rep       Date:  2021-10-28       Impact factor: 4.379

7.  Global insect decline is the result of wilful political failure: A battle plan for entomology.

Authors:  Philip Donkersley; Louise Ashton; Greg P A Lamarre; Simon Segar
Journal:  Ecol Evol       Date:  2022-10-12       Impact factor: 3.167

8.  Large-bodied birds are over-represented in unstructured citizen science data.

Authors:  Corey T Callaghan; Alistair G B Poore; Max Hofmann; Christopher J Roberts; Henrique M Pereira
Journal:  Sci Rep       Date:  2021-09-24       Impact factor: 4.379

  8 in total

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