Skip to main content
SpringerLink
Log in

Quality of citizen science data and its consequences for the conservation of skipper butterflies (Hesperiidae) in Flanders (northern Belgium)

  • ORIGINAL PAPER
  • Published:
Journal of Insect Conservation Aims and scope Submit manuscript

Abstract

Citizen science projects have become important data sources for ecologists. However, opportunistic data are not only characterized by spatial and temporal biases, but probably also contain species identification errors, especially concerning morphologically similar species. Such misidentifications may result in wrongly estimated distribution ranges and trends, and thus in inadequate conservation measures. We illustrate this issue with three skipper butterflies (Hesperiidae) in Flanders (northern Belgium) using photographs uploaded with observations in data portals. Ochlodes sylvanus and Thymelicus lineola records had relatively low identification error rates (1 and 11 %, respectively), but the majority (59 %) of Thymelicus sylvestris records turned out to be misidentified. Using verified records only allowed us to model their distribution more accurately, especially for T. sylvestris whose actual distribution area had hitherto been strongly overestimated. An additional field study on T. sylvestris confirmed the species distribution model output as the species was almost completely restricted to sites with verified records and was largely absent from sites with unverified records. The preference of T. sylvestris for unimproved grasslands was confirmed by the negative correlation between its model-predicted presence and elevated nitrogen and ammonia levels. Thus, quality control of citizen science data is of major importance to improve the knowledge of species distribution ranges, biotope preferences and other limiting factors. This, in turn, will help to better assess species conservation statuses and to suggest more appropriate management and mitigation measures.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  • Araújo MB, New M (2007) Ensemble forecasting of species distributions. Trends Ecol Evol 22:42–47. doi:10.1016/j.tree.2006.09.010

    Article  PubMed  Google Scholar 

  • Asher J, Warren M, Fox R, Harding P, Jeffcoate G, Jeffcoate S (2001) The millennium atlas of butterflies in Britain and Ireland. Oxford University Press, Oxford

    Google Scholar 

  • Beck J, Böller M, Erhardt A, Schwanghart W (2014) Spatial bias in the GBIF database and its effect on modeling species’ geographic distributions. Ecol Inform 19:10–15 doi:10.1016/j.ecoinf.2013.11.002

    Article  Google Scholar 

  • Bink FA (1992) Ecologische atlas van de dagvlinders van Noordwest-Europa. Schuyt & Co Uitgevers en Importeurs bv, Haarlem

    Google Scholar 

  • Bos F, Bosveld M, Groenendijk D, van Swaay CAM, Wynhoff I, De Vlinderstichting (2006) De dagvlinders van Nederland. Verspreiding en bescherming (Lepidoptera: Hesperioidea, Papilionoidea). Nederlandse Fauna 7. Nationaal Natuurhistorisch Museum Naturalis; KNNV Uitgeverij; European Invertebrate Survey, Leiden

    Google Scholar 

  • Breiman L (2001) Random forests. Mach Learn 45:5–32. doi:10.1023/A:1010933404324

    Article  Google Scholar 

  • Brereton TM, Botham MS, Middlebrook I, Randle Z, Roy DB (2015) United Kingdom butterfly monitoring scheme report for 2014. Centre for Ecology & Hydrology/Butterfly Conservation, Wallingford/East Lulworth

    Google Scholar 

  • De Saeger S, Guelinckx R, Van Dam G, Oosterlynck P, Van Hove M, Wils C, Paelinckx D (2014) Biologische Waarderingskaart en Natura 2000 Habitatkaart, uitgave 2014 vol INBO.R.2014.1698392. Rapporten van het Instituut voor Natuur-en Bosonderzoek. Instituut voor Natuur- en Bosonderzoek, Brussel

    Google Scholar 

  • Dennis RLH (2010) A resource-based habitat view for conservation. Butterflies in the British landscape. Wiley-Blackwell, Oxford

    Book  Google Scholar 

  • Desender K, Dekoninck W, Dufrêne M, Maes D (2010) Changes in the distribution of carabid beetles in Belgium revisited: have we halted the diversity loss? Biol Conserv 143:1549–1557. doi:10.1016/j.biocon.2010.03.039

    Article  Google Scholar 

  • Dickinson JL et al (2012) The current state of citizen science as a tool for ecological research and public engagement. Front Ecol Environ 10:291–297. doi:10.1890/110236

    Article  Google Scholar 

  • Dincă V, Lukhtanov VA, Talavera G, Vila R (2011) Unexpected layers of cryptic diversity in wood white Leptidea butterflies. Nat Commun 2:324. doi:10.1038/ncomms1329

    Article  PubMed  Google Scholar 

  • Ebert G, Rennwald E (1993) Die Schmetterlinge Baden-Württembergs, Band 2, Tagfalter II. Verlag Eugen Ulmer, Stuttgart

    Google Scholar 

  • Elith J et al (2006) Novel methods improve prediction of species’ distributions from occurrence data. Ecography 29:129–151. doi:10.1111/j.2006.0906-7590.04596.x

    Article  Google Scholar 

  • Engler JO, Balkenhol N, Filz KJ, Habel JC, Rodder D (2014) Comparative Landscape Genetics of Three Closely Related Sympatric Hesperid Butterflies with Diverging Ecological Traits. Plos One. doi:10.1371/journal.pone.0106526

    Google Scholar 

  • Fox J, Weisberg S (2011) An R companion to applied regression, 2nd edn. Sage, Thousand Oaks

    Google Scholar 

  • Friedman J, Hastie T, Tibshirani R (2000) Additive logistic regression: a statistical view of boosting. Ann Stat 28:337–374. doi:10.1214/aos/1016218223

    Article  Google Scholar 

  • Gilburn AS, Bunnefeld N, Wilson JM, Botham MS, Brereton TM, Fox R, Goulson D (2015) Are neonicotinoid insecticides driving declines of widespread butterflies? PeerJ 3:e1402. doi:10.7717/peerj.1402

    Article  PubMed  PubMed Central  Google Scholar 

  • Guisan A et al (2013) Predicting species distributions for conservation decisions. Ecol Lett 16:1424–1435. doi:10.1111/Ele.12189

    Article  PubMed  PubMed Central  Google Scholar 

  • Hamilton SH, Pollino CA, Jakeman AJ (2015) Habitat suitability modelling of rare species using Bayesian networks: model evaluation under limited data. Ecol Model 299:64–78. doi:10.1016/j.ecolmodel.2014.12.004

    Article  Google Scholar 

  • Hastie T, Tibshirani R (1987) Generalized additive models: some applications. J Am Stat Assoc 82:371–386. doi:10.2307/2289439

    Article  Google Scholar 

  • Hill MO (2012) Local frequency as a key to interpreting species occurrence data when recording effort is not known. Methods Ecol Evol 3:195–205. doi:10.1111/j.2041-210X.2011.00146.x

    Article  Google Scholar 

  • Hochachka WM, Fink D, Hutchinson RA, Sheldon D, Wong WK, Kelling S (2012) Data-intensive science applied to broad-scale citizen science. Trends Ecol Evol 27:130–137. doi:10.1016/j.tree.2011.11.006

    Article  PubMed  Google Scholar 

  • Isaac NJB, Pocock MJ (2015) Bias and information in biological records. Biol J Linn Soc 115:522–531. doi:10.1111/bij.12532

    Article  Google Scholar 

  • Isaac NJB, van Strien AJ, August TA, de Zeeuw MP, Roy DB (2014) Statistics for citizen science: extracting signals of change from noisy ecological data. Methods Ecol Evol 5:1052–1060. doi:10.1111/2041-210X.12254

    Article  Google Scholar 

  • Kelling S, Fink D, La Sorte FA, Johnston A, Bruns NE, Hochachka WM (2015) Taking a ‘Big Data’ approach to data quality in a citizen science project. Ambio 44:S601–S611. doi:10.1007/s13280-015-0710-4

    Article  Google Scholar 

  • Klop E, Omon B, WallisDeVries MF (2015) Impact of nitrogen deposition on larval habitats: the case of the Wall Brown butterfly Lasiommata megera. J Insect Conserv 19:393–402. doi:10.1007/s10841-014-9748-z

    Article  Google Scholar 

  • Kudrna O, Harpke A, Lux K, Pennerstorfer J, Schweiger O, Settele J, Wiemers M (2011) Distribution atlas of butterflies in Europe. Gesellschaft für Schmetterlingsschutz e.V., Halle

    Google Scholar 

  • Lafranchis T (2004) Butterflies of Europe. New field guide and key. Diatheo, Paris

    Google Scholar 

  • Li XH, Wang Y (2013) Applying various algorithms for species distribution modelling. Integr Zool 8:124–135. doi:10.1111/1749-4877.12000

    Article  PubMed  Google Scholar 

  • Louy D, Habel JC, Schmitt T, Assmann T, Meyer M, Muller P (2007) Strongly diverging population genetic patterns of three skipper species: the role of habitat fragmentation and dispersal ability. Conserv Genet 8:671–681. doi:10.1007/s10592-006-9213-y

    Article  Google Scholar 

  • Mace GM (1994) Classifying threatend species: means and ends. Philos Trans R Soc London B 344:91–97. doi:10.1098/rstb.1994.0056

    Article  Google Scholar 

  • Mace GM et al (2008) Quantification of extinction risk: IUCN’s system for classifying threatened species. Conserv Biol 22:1424–1442. doi:10.1111/j.1523-1739.2008.01044.x

    Article  PubMed  Google Scholar 

  • Maes D, Van Dyck H (2001) Butterfly diversity loss in Flanders (north Belgium): Europe’s worst case scenario? Biol Conserv 99:263–276. doi:10.1016/S0006-3207(00)00182-8

    Article  Google Scholar 

  • Maes D, Vanreusel W, Jacobs I, Berwaerts K, Van Dyck H (2012) Applying IUCN Red List criteria at a small regional level: a test case with butterflies in Flanders (north Belgium). Biol Conserv 145:258–266. doi:10.1016/j.biocon.2011.11.021

    Article  Google Scholar 

  • Maes D, Vanreusel W, Van Dyck H (2013) Dagvlinders in Vlaanderen: nieuwe kennis voor betere actie. Uitgeverij Lannoo nv, Tielt

    Google Scholar 

  • Maes D, Isaac NB, Harrower C, Collen B, van Strien A, Roy DB (2015) The use of opportunistic data for IUCN Red List assessments. Biol J Linn Soc 115:690–706. doi:10.1111/bij.12530

    Article  Google Scholar 

  • Maes D et al (2016) A database on the distribution of butterflies (Lepidoptera) in northern Belgium (Flanders and the Brussels Capital Region). ZooKeys 585:143–156. doi:10.3897/zookeys.585.8019

    Article  Google Scholar 

  • McCullagh P, Nelder JA (1989) Generalized linear models, 2nd edition. Chapman & Hall, London

    Book  Google Scholar 

  • OC-GIS Vlaanderen (2001) Bodemkaart van het Vlaams Gewest, schaal 1/20000. Ondersteunend Centrum GIS Vlaanderen, Gent

    Google Scholar 

  • Oenema O, Velthof G, Klimont Z, Winiwarter W (2012) Emissions from agriculture and their control potentials, TSAP Report 3, version 2.1. International Institute for Applied Systems Analysis (IIASA), Laxenburg

    Google Scholar 

  • Phillips SJ, Anderson RP, Schapire RE (2006) Maximum entropy modeling of species geographic distributions. Ecol Model 190:231–259 doi:10.1016/j.ecolmodel.2005.03.026

  • Poelmans L, Van Rompaey A (2009) Detecting and modelling spatial patterns of urban sprawl in highly fragmented areas: a case study in the Flanders-Brussels region. Landscape Urban Plan 93:10–19 doi:10.1016/j.landurbplan.2009.05.018

    Article  Google Scholar 

  • R Core Team (2015) R: a language and environment for statistical computing, 3.1.1 edn. R Foundation for Statistical Computing, Vienna

    Google Scholar 

  • Reis S, Pinder RW, Zhang M, Lijie G, Sutton MA (2009) Reactive nitrogen in atmospheric emission inventories. Atmos Chem Phys 9:7657–7677. doi:10.5194/acp-9-7657-2009

    Article  CAS  Google Scholar 

  • Skjøth CA et al (2011) Spatial and temporal variations in ammonia emissions—a freely accessible model code for Europe. Atmos Chem Phys 11:5221–5236. doi:10.5194/acp-11-5221-2011

    Article  Google Scholar 

  • Stevens CJ et al (2010) Nitrogen deposition threatens species richness of grasslands across Europe. Environ Pollut 158:2940–2945. doi:10.1016/j.envpol.2010.06.006

    Article  CAS  PubMed  Google Scholar 

  • Swets JA (1988) Measuring the accuracy of diagnostic systems. Science 204:1285–1293. doi:10.1126/science.3287615

    Article  Google Scholar 

  • Thuiller W, Georges D, Engler R (2012) Biomod2: Ensemble platform for species distribution modeling. R package version 1.3.7/r529.

  • Titeux N, Maes D, Marmion M, Luoto M, Heikkinen RK (2009) Inclusion of soil data improves the performance of bioclimatic envelope models for insect species distributions in temperate Europe. J Biogeogr 36:1459–1473. doi:10.1111/j.1365-2699.2009.02088.x

    Article  Google Scholar 

  • Tjørnløv RS, Kissling WD, Barnagaud JY, Bøcher PK, Høye TT (2015) Oviposition site selection of an endangered butterfly at local spatial scales. J Insect Conserv 19:377–391. doi:10.1007/s10841-014-9747-0

    Article  Google Scholar 

  • Tulloch AIT et al (2016) Conservation planners tend to ignore improved accuracy of modelled species distributions to focus on multiple threats and ecological processes. Biol Conserv 199:157–171. doi:10.1016/j.biocon.2016.04.023

    Article  Google Scholar 

  • Tweddle JC, Robinson LD, Pocock MJ, Roy HE (2012) Guide to citizen science: developing, implementing and evaluating citizen science to study biodiversity and the environment in the UK. Natural History Museum/NERC Centre for Ecology and Hydrology for UK-Environmental Observation Framework, UK

  • Tye CA, McCleery RA, Fletcher Jr RJ, Greene DU, Butryn RS (2016) Evaluating citizen vs. professional data for modelling distributions of a rare squirrel. J Appl Ecol. doi:10.1111/1365-2664.12682

    Google Scholar 

  • van Swaay CAM (2006) Basisrapport Rode Lijst Dagvlinders. De Vlinderstichting, Wageningen

    Google Scholar 

  • Van Landuyt W, Vanhecke L, Hoste I, Hendrickx F, Bauwens D (2008) Changes in the distribution area of vascular plants in Flanders (northern Belgium): eutrophication as a major driving force. Biodivers Conserv 17:3045–3060. doi:10.1007/s10531-008-9415-3

    Article  Google Scholar 

  • van Swaay CAM, Nowicki P, Settele J, van Strien AJ (2008) Butterfly monitoring in Europe: methods, applications and perspectives. Biodivers Conserv 17:3455–3469. doi:10.1007/s10531-008-9491-4

    Article  Google Scholar 

  • van Swaay CAM et al (2011) Applying IUCN criteria to invertebrates: how red is the Red List of European butterflies? Biol Conserv 144:470–478. doi:10.1016/j.biocon.2010.09.034

    Article  Google Scholar 

  • van Swaay CAM, Termaat T, Kok J, Huskens K, Poot M (2016) Vlinders en libellen geteld. Jaarverslag 2015 vol 2016.001. Rapport VS. De Vlinderstichting, Wageningen

    Google Scholar 

  • Van der Heyden C, Demeyer P, Volcke EIP (2015) Mitigating emissions from pig and poultry housing facilities through air scrubbers and biofilters: state-of-the-art and perspectives. Biosyst Eng 134:74–93. doi:10.1016/j.biosystemseng.2015.04.002

    Article  Google Scholar 

  • VMM (2015) Verzurende en vermestende luchtverontreiniging in Vlaanderen—jaarrapport 2014. Vlaamse Milieumaatschappij, Aalst

    Google Scholar 

  • WallisDeVries MF, Ramaekers I (2001) Does extensive grazing benefit butterflies in coastal dunes? Restor Ecol 9:179–188. doi:10.1046/j.1526-100x.2001.009002179.x

    Article  Google Scholar 

  • WallisDeVries MF, van Swaay CAM (2006) Global warming and excess nitrogen may induce butterfly decline by microclimatic cooling. Global Change Biol 12:1620–1626. doi:10.1111/j.1365-2486.2006.01202.x

    Article  Google Scholar 

  • Wikström L, Milberg P, Bergman KO (2009) Monitoring of butterflies in semi-natural grasslands: diurnal variation and weather effects. J Insect Conserv 13:203–211. doi:10.1007/s10841-008-9144-7

    Article  Google Scholar 

  • Wynhoff I, van Swaay CAM, Veling K, Vliegenthart A (2014) De Nieuwe Veldgids Dagvlinders. KNNV Uitgeverij i.s.m. De Vlinderstichting, Zeist/Wageningen

    Google Scholar 

Download references

Acknowledgments

We thank all volunteers sharing skipper observations on http://www.waarnemingen.be, and are grateful to Natuurpunt Studie (Wouter Vanreusel and Karin Gielen) and Stichting Natuurinformatie for access to this database. We also thank Hans Matheve (TEREC, UGent) for help with GIS. Finally, we thank Butterfly Conservation Europe and De Vlinderstichting for the opportunity to present preliminary results of this study at the Future4Butterflies conference. We also thank two anonymous reviewers and Marc Pollet for commenting on a previous version of the manuscript.

Author information

Authors and Affiliations

  1. Vlinderwerkgroep Natuurpunt, Coxiestraat 11, 2800, Mechelen, Belgium

    Pieter Vantieghem & Thomas Merckx

  2. Terrestrial Ecology Unit, Biology Department, Ghent University, K.L. Ledeganckstraat 35, 9000, Ghent, Belgium

    Pieter Vantieghem

  3. Research Institute for Nature and Forest (INBO), Kliniekstraat 25, 1070, Brussels, Belgium

    Dirk Maes

  4. Behavioural Ecology and Conservation Group, Biodiversity Research Centre, Earth and Life Institute, Université catholique de Louvain (UCL), Louvain-La-Neuve, Belgium

    Aurélien Kaiser & Thomas Merckx

Authors
  1. Pieter Vantieghem
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Dirk Maes
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Aurélien Kaiser
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Thomas Merckx
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Dirk Maes.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Vantieghem, P., Maes, D., Kaiser, A. et al. Quality of citizen science data and its consequences for the conservation of skipper butterflies (Hesperiidae) in Flanders (northern Belgium). J Insect Conserv 21, 451–463 (2017). https://doi.org/10.1007/s10841-016-9924-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10841-016-9924-4

Keywords

Search

Navigation