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Wildlife Research Wildlife Research Society
Ecology, management and conservation in natural and modified habitats
RESEARCH ARTICLE (Open Access)

Stronger together: different community science platforms all contribute to wildlife research

Lucas Rodriguez Forti A B , Ana Marta P. R. da Silva Passetti B , Talita Oliveira C , Kauane Freitas C , Guilherme de Freitas Costa C , Juan Victor de Lima Maia C , Arthur Queiros C , Maria Alice Dantas Ferreira Lopes C and Judit K. Szabo https://orcid.org/0000-0002-8786-1887 D *
+ Author Affiliations
- Author Affiliations

A Departamento de Biociências, Universidade Federal Rural do Semi-Árido, Avenida Francisco Mota, 572 Bairro Costa e Silva, Mossoró, Rio Grande do Norte 59625-900, Brazil. Email: lucas_forti@yahoo.com.br

B Instituto de Biologia, Universidade Federal da Bahia, Rua Barão de Jeremoabo, 668 Campus de Ondina, Salvador, Bahia CEP: 40170-115, Brazil. Email: ana.mpassetti@outlook.com

C Universidade Federal Rural do Semi-Árido, Avenida Francisco Mota, 572 Bairro Costa e Silva, Mossoró, Rio Grande do Norte 59625-900, Brazil. Email: talitamonielly@gmail.com, kauanemafreitas@gmail.com, guicosta0499@gmail.com, luanarthur00@gmail.com, juanemaze@hotmail.com, alicedflopes.02@gmail.com

D Research Institute for the Environment and Livelihoods, Charles Darwin University, Casuarina, NT 0909, Australia.

* Correspondence to: judit.szabo@cdu.edu.au

Handling Editor: Catarina Campos Ferreira

Wildlife Research 51, WR23160 https://doi.org/10.1071/WR23160
Submitted: 26 December 2023  Accepted: 11 July 2024  Published: 5 August 2024

© 2024 The Author(s) (or their employer(s)). Published by CSIRO Publishing. This is an open access article distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND)

Abstract

Context

Engaging the general public can increase spatio-temporal coverage of wildlife monitoring. Given the potentially substantial costs, we need to evaluate the contribution of known and planned initiatives and confirm whether multiple platforms increase the efficiency of data collection. As observer behaviour affects data quantity and quality, users of specialised and generalist platforms are expected to behave differently, resulting in more connected networks for specialised and higher nestedness for generalist platforms. Specialist observers are expected to contribute a balanced ratio of rare and common species, whereas non-specialist contribution will depend more on species detectability.

Aims

We aim to evaluate whether the combined contribution of observers from different platforms can improve the quality of occurrence and distribution data of 218 endemic Atlantic Forest bird species in Brazil. We also describe and compare observer-bird species interaction networks to illustrate observer behaviour on different platforms.

Methods

On the basis of data from five community science platforms in Brazil, namely, eBird, WikiAves, Biofaces, iNaturalist and Táxeus, we compared the spatial distribution of bird observations, the number of observers, the presence of the same observers on various platforms, bird species coverage, and the proportion of duplicate observations within and among platforms.

Key results

Although species coverage of the joint dataset increased by up to 100%, spatial completeness among the five platforms was low. The network of individual platforms had low values of clustering, and the network of the joint dataset had low connectance and high nestedness.

Conclusions

Each platform had a somewhat unique contribution. Pooling these datasets and integrating them with standardised data can inform our knowledge on bird distributions and trends in this fragile biome. Nevertheless, we encourage observers to provide precise coordinates, dates and other data (and platforms to accommodate such data) and recommend submitting data from all platforms into the Global Biodiversity Information Facility to support wildlife research and conservation.

Implications

If new platforms engage more and different people, new initiatives can cover poorly represented areas and successfully expand monitoring effort for Atlantic Forest endemic bird species.

Keywords: biodiversity, Brazil, citizen science, conservation, mobile nature apps, network analysis, participatory monitoring, public engagement.

References

Aceves-Bueno E, Adeleye AS, Bradley D, Tyler Brandt W, Callery P, Feraud M, Garner KL, Gentry R, Huang Y, McCullough I, Pearlman I, Sutherland SA, Wilkinson W, Yang Y, Zink T, Anderson SE, Tague C (2015) Citizen science as an approach for overcoming insufficient monitoring and inadequate stakeholder buy-in in adaptive management: criteria and evidence. Ecosystems 18, 493-506.
| Crossref | Google Scholar |

Alexandrino ER, da Silva GA, Corbo MC, Demuner BA, Szabo JK (2022) Urban southern house wren (Troglodytes aedon musculus) nesting in apparently unsuitable human-made structures: is it worth it? Ornitología Neotropical 33(1), 44-52.
| Crossref | Google Scholar |

Allen WJ, Bufford JL, Barnes AD, Barratt BIP, Deslippe JR, Dickie IA, Goldson SL, Howlett BG, Hulme PE, Lavorel S, O’Brien SA, Waller LP, Tylianakis JM (2022) A network perspective for sustainable agroecosystems. Trends in Plant Science 27(8), 769-780.
| Crossref | Google Scholar | PubMed |

Allf BC, Cooper CB, Larson LR, Dunn RR, Futch SE, Sharova M, Cavalier D (2022) Citizen science as an ecosystem of engagement: implications for learning and broadening participation. BioScience 72(7), 651-663.
| Crossref | Google Scholar | PubMed |

Atwood JL (2023) Seasonal patterns of least tern distribution along the Atlantic Coasts of North, Central, and South America. Waterbirds 46(1), 85-90.
| Crossref | Google Scholar |

Barrat A, Barthélemy M, Pastor-Satorras R, Vespignani A (2004) The architecture of complex weighted networks. Proceedings of the National Academy of Sciences 101(11), 3747-3752.
| Crossref | Google Scholar | PubMed |

Binley AD, Bennett JR (2023) The data double standard. Methods in Ecology and Evolution 14, 1389-1397.
| Crossref | Google Scholar |

Bonney R (2021) Expanding the impact of citizen science. BioScience 71(5), 448-451.
| Crossref | Google Scholar |

Callaghan CT, Ozeroff I, Hitchcock C, Chandler M (2020) Capitalizing on opportunistic citizen science data to monitor urban biodiversity: a multi-taxa framework. Biological Conservation 251, 108753.
| Crossref | Google Scholar |

Callaghan CT, Poore AGB, Mesaglio T, Moles AT, Nakagawa S, Roberts C, Rowley JJL, Vergés A, Wilshire JH, Cornwell WK (2021) Three frontiers for the future of biodiversity research using citizen science data. BioScience 71(1), 55-63.
| Crossref | Google Scholar |

Csárdi G, Nepusz T (2006) The igraph software package for complex network research. InterJournal, Complex Systems 1695(5), 1-9.
| Google Scholar |

Cunha DGF, Marques JF, Resende JCD, Falco PBD, Souza CMD, Loiselle SA (2017) Citizen science participation in research in the environmental sciences: key factors related to projects’ success and longevity. Anais da Academia Brasileira de Ciências 89, 2229-2245.
| Crossref | Google Scholar | PubMed |

Cunha FCR, Lopes LE, Selezneva A (2022) Revealing migration schedule and potential breeding grounds of Lined Seedeaters using citizen science data. Emu – Austral Ornithology 122(3-4), 167-175.
| Crossref | Google Scholar |

Degroote LW, Hingst-Zaher E, Moreira-Lima L, Whitacre JV, Slyder JB, Wenzel JW (2021) Citizen science data reveals the cryptic migration of the Common Potoo Nyctibius griseus in Brazil. Ibis 163, 380-389.
| Crossref | Google Scholar |

Delmas E, Besson M, Brice M-H, Burkle LA, Dalla Riva GV, Fortin M-J, Gravel D, Guimarães PR, Jr, Hembry DH, Newman EA, Olesen JM, Pires MM, Yeakel JD, Poisot T (2019) Analysing ecological networks of species interactions. Biological Reviews 94(1), 16-36.
| Crossref | Google Scholar | PubMed |

Dennis EB, Morgan BJT, Brereton TM, Roy DB, Fox R (2017) Using citizen science butterfly counts to predict species population trends. Conservation Biology 31(6), 1350-1361.
| Crossref | Google Scholar | PubMed |

Dormann CF, Gruber B, Fründ J (2008) Introducing the bipartite package: analysing ecological networks. R News 8(2), 8-11.
| Google Scholar |

Ellwood ER, Sessa JA, Abraham JK, Budden AE, Douglas N, Guralnick R, Krimmel E, Langen T, Linton D, Phillips M, Soltis PS, Studer M, White LD, Williams J, Monfils AK (2020) Biodiversity science and the twenty-first century workforce. BioScience 70(2), 119-121.
| Crossref | Google Scholar | PubMed |

Farias M, Roper J, Cavarzere V (2022) Bird communities and their conservation priorities are better understood through the integration of traditional and citizen science data: an example from Brazilian Atlantic Forest. Citizen Science: Theory and Practice 7(1), 9.
| Crossref | Google Scholar |

Fletcher RJ, Jr, Hefley TJ, Robertson EP, Zuckerberg B, McCleery RA, Dorazio RM (2019) A practical guide for combining data to model species distributions. Ecology 100(6), e02710.
| Crossref | Google Scholar | PubMed |

Forti L (2023) Dataset of five citizen science platforms with reagards endemic bird species of the Atlantic Forest. Zenodo 2023. [Dataset, posted 20 November 2023] doi:10.5281/zenodo.10177895

Forti LR, Szabo JK (2023) The iNaturalist platform as a source of data to study amphibians in Brazil. Anais da Academia Brasileira de Ciências 95(1), e20220828.
| Crossref | Google Scholar |

Forti LR, Hepp F, de Souza JM, Protazio A, Szabo JK (2022a) Climate drives anuran breeding phenology in a continental perspective as revealed by citizen-collected data. Diversity and Distributions 28, 2094-2109.
| Crossref | Google Scholar |

Forti LR, Pontes MR, Augusto-Alves G, Martins A, Hepp F, Szabo JK (2022b) Data collected by citizen scientists reveal the role of climate and phylogeny on the frequency of shelter types used by frogs across the Americas. Zoology 155, 126052.
| Crossref | Google Scholar | PubMed |

Forti LR, Passetti A, Oliveira T, Lima J, Queiros A, Dantas Ferreira Lopes MA, Szabo JK (2024) Declining representation of imperiled Atlantic Forest birds in community-science datasets. Perspectives in Ecology and Conservation. [In press, corrected proof published 2 July 2024] doi:10.1016/j.pecon.2024.02.001.

Fraisl D, Hager G, Bedessem B, Gold M, Hsing P-Y, Danielsen F, Hitchcock CB, Hulbert JM, Piera J, Spiers H, Thiel M, Haklay M (2022) Citizen science in environmental and ecological sciences. Nature Reviews Methods Primers 2(1), 64.
| Crossref | Google Scholar |

Hertzog LR, Frank C, Klimek S, Röder N, Böhner HGS, Kamp J (2021) Model-based integration of citizen science data from disparate sources increases the precision of bird population trends. Diversity and Distributions 27, 1106-1119.
| Crossref | Google Scholar |

Howard E, Davis AK (2009) The fall migration flyways of monarch butterflies in eastern North America revealed by citizen scientists. Journal of Insect Conservation 13(3), 279-286.
| Crossref | Google Scholar |

Hurlbert AH, Liang Z (2012) Spatiotemporal variation in avian migration phenology: citizen science reveals effects of climate change. PLoS ONE 7(2), e31662.
| Crossref | Google Scholar | PubMed |

Instituto Brasileiro de Geografia e Estatística (2008) Mapa da área de aplicação da Lei nº 11.428 de 2006. (IBGE) Available at https://antigo.mma.gov.br/biomas/mata-atlântica_emdesenvolvimento/mapas-da-mata-atlântica.html [In Portuguese]

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 in Ecology and Evolution 5, 1052-1060.
| Crossref | Google Scholar |

Isaac NJB, Jarzyna MA, Keil P, Dambly LI, Boersch-Supan PH, Browning E, Freeman SN, Golding N, Guillera-Arroita G, Henrys PA, Jarvis S, Lahoz-Monfort J, Pagel J, Pescott OL, Schmucki R, Simmonds EG, O’Hara RB (2020) Data integration for large-scale models of species distributions. Trends in Ecology & Evolution 35, 56-67.
| Crossref | Google Scholar | PubMed |

Jarić I, Correia RA, Brook BW, Buettel JC, Courchamp F, Di Minin E, Firth JA, Gaston KJ, Jepson P, Kalinkat G, Ladle R, Soriano-Redondo A, Souza AT, Roll U (2020) iEcology: harnessing large online resources to generate ecological insights. Trends in Ecology & Evolution 35(7), 630-639.
| Crossref | Google Scholar | PubMed |

Johnston A, Moran N, Musgrove A, Fink D, Baillie SR (2020) Estimating species distributions from spatially biased citizen science data. Ecological Modelling 422, 108927.
| Crossref | Google Scholar |

Lau MK, Borrett SR, Baiser B, Gotelli NJ, Ellison AM (2017) Ecological network metrics: opportunities for synthesis. Ecosphere 8(8), e01900.
| Crossref | Google Scholar |

Mandeville CP, Nilsen EB, Herfindal I, Finstad AG (2023) Participatory monitoring drives biodiversity knowledge in global protected areas. Communications Earth & Environment 4, 240.
| Crossref | Google Scholar |

Mariani MS, Ren Z-M, Bascompte J, Tessone CJ (2019) Nestedness in complex networks: observation, emergence, and implications. Physics Reports 813, 1-90.
| Crossref | Google Scholar |

Mesaglio T, Callaghan CT (2021) An overview of the history, current contributions and future outlook of iNaturalist in Australia. Wildlife Research 48, 289-303.
| Crossref | Google Scholar |

Miller DAW, Pacifici K, Sanderlin JS, Reich BJ (2019) The recent past and promising future for data integration methods to estimate species’ distributions. Methods in Ecology and Evolution 10, 22-37.
| Crossref | Google Scholar |

Newman G, Chandler M, Clyde M, McGreavy B, Haklay M, Ballard H, Gray S, Scarpino R, Hauptfeld R, Mellor D, Gallo J (2017) Leveraging the power of place in citizen science for effective conservation decision making. Biological Conservation 208, 55-64.
| Crossref | Google Scholar |

Parrish JK, Jones T, Burgess HK, He Y, Fortson L, Cavalier D (2019) Hoping for optimality or designing for inclusion: persistence, learning, and the social network of citizen science. Proceedings of the National Academy of Sciences 116(6), 1894-1901.
| Crossref | Google Scholar | PubMed |

Posfai M, Barabasi A-L (2016) ‘Network science.’ (Cambridge University Press: Cambridge, UK)

Robinson OJ, Ruiz-Gutierrez V, Reynolds MD, Golet GH, Strimas-Mackey M, Fink D (2020) Integrating citizen science data with expert surveys increases accuracy and spatial extent of species distribution models. Diversity and Distributions 26, 976-986.
| Crossref | Google Scholar |

Rowley JJL, Callaghan CT, Cutajar T, Portway C, Potter K, Mahony S, Trembath DF, Flemons P, Woods A (2019) FrogID: citizen scientists provide validated biodiversity data on frogs of Australia. Herpetological Conservation and Biology 14(1), 155-170.
| Google Scholar |

Sanderson C, Braby MF, Bond S (2021) Butterflies Australia: a national citizen science database for monitoring changes in the distribution and abundance of Australian butterflies. Austral Entomology 60, 111-127.
| Crossref | Google Scholar |

Schaaf AA, Haag LM, Gonzalez Baffa-Trasci NV, Yapura A, Chocobar N, Caldano SA, Ruggera RA (2024) Comparing different citizen science platforms for collecting urban ecological data from Toco toucan (Ramphastos toco) in Argentina. Austral Ecology 49(2), e13459.
| Crossref | Google Scholar |

Schneider LM, de Oliveira Santos C, Moreira-Lima L, Hingst-Zaher E (2023) Peregrine falcon Falco peregrinus in Brazil: natural history through the lens of citizen science. Ornitología Neotropical 34, 29-39.
| Crossref | Google Scholar |

Schubert SC, Manica LT, Guaraldo ADC (2019) Revealing the potential of a huge citizen-science platform to study bird migration. Emu – Austral Ornithology 119(4), 364-373.
| Crossref | Google Scholar |

Simmonds EG, Jarvis SG, Henrys PA, Isaac NJB, O’Hara RB (2020) Is more data always better? A simulation study of benefits and limitations of integrated distribution models. Ecography 43, 1413-1422.
| Crossref | Google Scholar |

Szabo JK, Vesk PA, Baxter PWJ, Possingham HP (2010) Regional avian species declines estimated from volunteer-collected long-term data using list length analysis. Ecological Applications 20(8), 2157-2169.
| Crossref | Google Scholar | PubMed |

Szabo JK, Fuller RA, Possingham HP (2012) A comparison of estimates of relative abundance from a weakly structured mass-participation bird atlas survey and a robustly designed monitoring scheme. Ibis 154, 468-479.
| Crossref | Google Scholar |

Troudet J, Grandcolas P, Blin A, Vignes-Lebbe R, Legendre F (2017) Taxonomic bias in biodiversity data and societal preferences. Scientific Reports 7, 9132.
| Crossref | Google Scholar | PubMed |

Tubelis DP, Sazima I (2020) Biologia reprodutiva do carão, Aramus guarauna (Gruiformes: Aramidae), no Pantanal brasileiro, com uso de dados da ciência-cidadã. Atualidades Ornitológicas 215, 8-11 [In Portuguese].
| Google Scholar |

Tubelis DP, Sazima I (2021) Nuptial gifts among Brazilian cuckoos: an outline based on citizen science. Ornithology Research 29, 188-192.
| Crossref | Google Scholar |

Tulloch AIT, Szabo JK (2012) A behavioural ecology approach to understand volunteer surveying for citizen science datasets. Emu – Austral Ornithology 112, 313-325.
| Crossref | Google Scholar |

Tulloch AIT, Mustin K, Possingham HP, Szabo JK, Wilson KA (2013a) To boldly go where no volunteer has gone before: predicting volunteer activity to prioritize surveys at the landscape scale. Diversity and Distributions 19, 465-480.
| Crossref | Google Scholar |

Tulloch AIT, Possingham HP, Joseph LN, Szabo J, Martin TG (2013b) Realising the full potential of citizen science monitoring programs. Biological Conservation 165, 128-138.
| Crossref | Google Scholar |

Tylianakis JM, Laliberté E, Nielsen A, Bascompte J (2010) Conservation of species interaction networks. Biological Conservation 143, 2270-2279.
| Crossref | Google Scholar |

Vale MM, Tourinho L, Lorini ML, Rajão H, Figueiredo MSL (2018) Endemic birds of the Atlantic Forest: traits, conservation status, and patterns of biodiversity. Journal of Field Ornithology 89(3), 193-206.
| Crossref | Google Scholar |

Vancine MH, Muylaert RL, Niebuhr BB, Oshima JEdF, Tonetti V, Bernardo R, De Angelo C, Rosa MR, Grohmann CH, Ribeiro MC (2024) The Atlantic Forest of South America: spatiotemporal dynamics of the vegetation and implications for conservation. Biological Conservation 291, 110499.
| Crossref | Google Scholar |

Vohland K, Land-Zandstra A, Ceccaroni L, Lemmens R, Perelló J, Ponti M, Samson R, Wagenknecht K (Eds) (2021) ‘The science of citizen science.’ (Springer)

Wood C, Sullivan B, Iliff M, Fink D, Kelling S (2011) eBird: engaging birders in science and conservation. PLoS Biology 9(12), e1001220.
| Crossref | Google Scholar |

Zhang P, Wang J, Li X, Li M, Di Z, Fan Y (2008) Clustering coefficient and community structure of bipartite networks. Physica – A. Statistical Mechanics and its Applications 387, 6869-6875.
| Crossref | Google Scholar |

Zulian V, Miller DAW, Ferraz G (2021) Integrating citizen-science and planned-survey data improves species distribution estimates. Diversity and Distributions 27, 2498-2509.
| Crossref | Google Scholar |