Emu Emu Society
Journal of BirdLife Australia
RESEARCH ARTICLE

A behavioural ecology approach to understand volunteer surveying for citizen science datasets

Ayesha I. T. Tulloch A C and Judit K. Szabo B
+ Author Affiliations
- Author Affiliations

A ARC Centre of Excellence for Environmental Decisions, School of Biological Sciences, Goddard Building 8, The University of Queensland, St Lucia, Qld 4072, Australia.

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

C Corresponding author. Email: a.tulloch@uq.edu.au

Emu 112(4) 313-325 https://doi.org/10.1071/MU12009
Submitted: 9 November 2011  Accepted: 3 September 2012   Published: 8 November 2012

Abstract

Among other outcomes, volunteer surveys are useful for evaluating conservation success and determining priorities for management actions. However, biases that can originate from untargeted and weakly structured surveys can undermine the utility of the data gathered. Identifying and rectifying biases and problems with such data require an understanding of the behaviour of volunteers. We explored the characteristics of volunteer behaviour using bird surveys conducted in south-western Australia, and evaluated how volunteer behaviour affects the quantity and quality of data when volunteers are unconstrained in their selection of survey sites. We related the home-range and site-fidelity of 172 volunteers to the availability of habitat and bird species. Habitat selection by volunteers was assessed using avian species-accumulation curves, which identified 12 habitats for which avian species inventories were <95% complete. Volunteer biases resulted in skewed representation of birds in the resulting dataset. We recommend the minimum sampling effort required for reliable species-richness estimates in each habitat, and suggest ways to achieve spatial representativeness by using different behavioural types. Volunteers with high site-fidelity (often locals) produce high species detection rates, and are useful for long-term monitoring or surveying in less-favoured habitats close to urban areas. Roaming volunteers (often tourists) with large home-ranges are useful for threatened species surveying and can fill gaps far from urban areas, but might require incentives to visit unfavoured habitats, given their high habitat and bird selectivity. By studying volunteer behaviour, we can set realistic goals to achieve a comprehensive dataset useful for research, management and conservation planning.

Additional keywords: generalised linear models, geographical bias, human behaviour, monitoring, New Atlas of Australian Birds.


References

Aebischer, N. J., Robertson, P. A., and Kenward, R. E. (1993). Compositional analysis of habitat use from animal radio-tracking data. Ecology 74, 1313–1325.
Compositional analysis of habitat use from animal radio-tracking data.CrossRef |

Balmford, A., Bennun, L., ten Brink, B., Cooper, D., Cote, I. M., Crane, P., Dobson, A., Dudley, N., Dutton, I., Green, R. E., Gregory, R. D., Harrison, J., Kennedy, E. T., Kremen, C., Leader-Williams, N., Lovejoy, T. E., Mace, G., May, R., Mayaux, P., Morling, P., Phillips, J., Redford, K., Ricketts, T. H., Rodriguez, J. P., Sanjayan, M., Schei, P. J., van Jaarsveld, A. S., and Walther, B. A. (2005a). The convention on biological diversity’s 2010 target. Science 307, 212–213.
The convention on biological diversity’s 2010 target.CrossRef | 1:CAS:528:DC%2BD2MXksFaqsQ%3D%3D&md5=a191583699af60315083f841c354ae3aCAS |

Balmford, A., Crane, P., Dobson, A., Green, R. E., and Mace, G. M. (2005b). The 2010 challenge: data availability, information needs and extraterrestrial insights. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences 360, 221–228.
The 2010 challenge: data availability, information needs and extraterrestrial insights.CrossRef |

Barrett, G. W., Silcocks, A., Barry, S., Cunningham, R., and Poulter, R. (2003). ‘The New Atlas of Australian Birds.’ (Birds Australia: Melbourne.)

Barry, S., and Elith, J. (2006). Error and uncertainty in habitat models. Journal of Applied Ecology 43, 413–423.
Error and uncertainty in habitat models.CrossRef |

Beard, J. S. (1980a). A new phytogeographic map of Western Australia. Research Notes of the Western Australian Herbarium 3, 37–58.

Beard, J. S. (1980b). Vegetation survey of Western Australia. Western Australia 1 : 1 000 000 vegetation series. Swan Sheet 7. University of Western Australia Press and Interim Council for the Australian Biological Resources Study, Nedlands, WA.

Beard, J. S., Chapman, A. R., and Gioia, P. (2000). Species richness and endemism in the Western Australian flora. Journal of Biogeography 27, 1257–1268.
Species richness and endemism in the Western Australian flora.CrossRef |

Blakers, M., Davies, S. J. J. F., and Reilly, P. (1984). ‘The Atlas of Australian Birds.’ (Melbourne University Press: Melbourne.)

Boakes, E. H., McGowan, P. J. K., Fuller, R. A., Chang-qing, D., Clark, N. E., O’Connor, K., and Mace, G. M. (2010). Distorted views of biodiversity: spatial and temporal bias in species occurrence data. PLoS Biology 8, e1000385.
Distorted views of biodiversity: spatial and temporal bias in species occurrence data.CrossRef |

Booth, J. E., Gaston, K. J., Evans, K. L., and Armsworth, P. R. (2011). The value of species rarity in biodiversity recreation: a birdwatching example. Biological Conservation 144, 2728–2732.
The value of species rarity in biodiversity recreation: a birdwatching example.CrossRef |

Burnham, K. P., and Anderson, D. R. (2002). ‘Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach’, 2nd edn. (Springer-Verlag: New York.)

Clayton, S., and Myers, G. (2009). ‘Conservation Psychology: Understanding and Promoting Human Care for Nature.’ (Wiley-Blackwell: Chichester, UK.)

Danielsen, F., Burgess, N. D., Balmford, A., Donald, P. F., Funder, M., Jones, J. P. G., Alviola, P., Balete, D. S., Blomley, T., Brashares, J., Child, B., Enghoff, M., Fjeldsa, J., Holt, S., Hubertz, H., Jensen, A. E., Jensen, P. M., Massao, J., Mendoza, M. M., Ngaga, Y., Poulsen, M. K., Rueda, R., Sam, M., Skielboe, T., Stuart-Hill, G., Topp-Jorgensen, E., and Yonten, D. (2009). Local participation in natural resource monitoring: a characterization of approaches. Conservation Biology 23, 31–42.
Local participation in natural resource monitoring: a characterization of approaches.CrossRef |

Dennis, R. L. H., and Thomas, C. D. (2000). Bias in butterfly distribution maps: the influence of hot spots and recorder’s home range. Journal of Insect Conservation 4, 73–77.
Bias in butterfly distribution maps: the influence of hot spots and recorder’s home range.CrossRef |

Dunn, A. M., and Weston, M. A. (2008). A review of terrestrial bird atlases of the world and their application. Emu 108, 42–67.
A review of terrestrial bird atlases of the world and their application.CrossRef |

ESRI Inc. (2002). ‘ArcView GIS 3.3.’ (Environmental Systems Research Institute Inc.: Redlands, CA.)

ESRI Inc. (2008). ‘ArcGIS 9.3.’ (Environmental Systems Research Institute Inc.: Redlands, CA.)

Field, S. A., Tyre, A. J., and Possingham, H. P. (2002). Estimating bird species richness: how should repeat surveys be organized in time? Austral Ecology 27, 624–629.
Estimating bird species richness: how should repeat surveys be organized in time?CrossRef |

Field, S. A., Tyre, A. J., and Possingham, H. P. (2005). Optimizing allocation of monitoring effort under economic and observational constraints. Journal of Wildlife Management 69, 473–482.
Optimizing allocation of monitoring effort under economic and observational constraints.CrossRef |

Garnett, S., Szabo, J. K., and Dutton, G. (2011). ‘The Action Plan for Australian Birds 2010.’ (CSIRO Publishing: Melbourne.)

Gelman, A., and Hill, J. (2007). ‘Data Analysis Using Regression and Multilevel/Hierarchical Models.’ (Cambridge University Press: Cambridge, UK.)

Greenwood, J. J. D. (2007). Citizens, science and bird conservation. Journal of Ornithology 148, 77–124.
Citizens, science and bird conservation.CrossRef |

Gregory, R. D., and van Strien, A. (2010). Wild bird indicators: using composite population trends of birds as measures of environmental health. Ornithological Science 9, 3–22.
Wild bird indicators: using composite population trends of birds as measures of environmental health.CrossRef |

Gregory, R. D., Noble, D., Field, R., Marchant, J., Raven, M., and Gibbons, D. W. (2003). Using birds as indicators of biodiversity. Ornis Hungarica 12–13, 11–24.

Gu, W. D., and Swihart, R. K. (2004). Absent or undetected? Effects of non-detection of species occurrence on wildlife–habitat models. Biological Conservation 116, 195–203.
Absent or undetected? Effects of non-detection of species occurrence on wildlife–habitat models.CrossRef |

Hall, L. S., and Mannan, R. W. (1999). Multiscaled habitat selection by Elegant Trogons in southeastern Arizona. Journal of Wildlife Management 63, 451–461.
Multiscaled habitat selection by Elegant Trogons in southeastern Arizona.CrossRef |

Higgins, P. J. (Ed.) (1999). ‘Handbook of Australian, New Zealand and Antarctic Birds. Vol. 4: Parrots to Dollarbird.’ (Oxford University Press: Melbourne.)

Higgins, P. J., and Davies, S. J. J. F. (Eds) (1996). ‘Handbook of Australian, New Zealand and Antarctic Birds. Vol. 3: Snipe to Pigeons.’ (Oxford University Press: Melbourne.)

Higgins, P. J., and Peter, J. M. (Eds) (2002). ‘Handbook of Australian, New Zealand and Antarctic Birds. Vol. 6: Pardalotes to Shrike-thrushes.’ (Oxford University Press: Melbourne.)

Higgins, P. J., Peter, J. M., and Steele, W. K. (Eds) (2001). ‘Handbook of Australian, New Zealand and Antarctic Birds. Vol. 5: Tyrant-flycatchers to Chats.’ (Oxford University Press: Melbourne.)

Higgins, P. J., Peter, J. M., and Cowling, S. J. (Eds) (2006). ‘Handbook of Australian, New Zealand and Antarctic Birds. Vol. 7: Boatbill to Starlings.’ (Oxford University Press: Melbourne)

Hooge, P. N., Eichenlaub, W. M., and Solomon, E. K. (1999). Using GIS to analyze animal movements in the marine environment. United States Geological Survey, Anchorage, AK.

Hopper, S. D., and Gioia, P. (2004). The southwest Australian floristic region: evolution and conservation of a global hot spot of biodiversity. Annual Review of Ecology Evolution and Systematics 35, 623–650.
The southwest Australian floristic region: evolution and conservation of a global hot spot of biodiversity.CrossRef |

Mac Nally, R., Ellis, M., and Barrett, G. (2004). Avian biodiversity monitoring in Australian rangelands. Austral Ecology 29, 93–99.
Avian biodiversity monitoring in Australian rangelands.CrossRef |

MacKenzie, D. I., Nichols, J. D., Sutton, N., Kawanishi, K., and Bailey, L. L. (2005). Improving inferences in population studies of rare species that are detected imperfectly. Ecology 86, 1101–1113.
Improving inferences in population studies of rare species that are detected imperfectly.CrossRef |

Marchant, S., and Higgins, P. J. (Eds) (1990). ‘Handbook of Australian, New Zealand and Antarctic Birds. Vol. 1: Ratites to Ducks.’ (Oxford University Press: Melbourne.)

Marchant, S., and Higgins, P. J. (Eds) (1993). ‘Handbook of Australian, New Zealand and Antarctic Birds. Vol. 2: Raptors to Lapwings.’ (Oxford University Press: Melbourne.)

Marchesan, D., and Carthew, S. M. (2008). Use of space by the Yellow-footed Antechinus, Antechinus flavipes, in a fragmented landscape in South Australia. Landscape Ecology 23, 741–752.
Use of space by the Yellow-footed Antechinus, Antechinus flavipes, in a fragmented landscape in South Australia.CrossRef |

Mittermeier, R. A., Robles Gil, P., Hoffmann, M., Pilgrim, J., Brooks, T., Goettsch Mittermeier, C., Lamoreux, J., and Da Fonseca, G. A. B. (Eds) (2004). ‘Hotspots Revisited: Earth’s Biologically Richest and Most Endangered Terrestrial Ecoregions.’ (Cemex: Mexico City.)

Munson, M. A., Caruana, R., Fink, D., Hochachka, W. M., Iliff, M., Rosenberg, K. V., Sheldon, D., Sullivan, B. L., Wood, C., and Kelling, S. (2010). A method for measuring the relative information content of data from different monitoring protocols. Methods in Ecology and Evolution 1, 263–273.

National Land and Water Resources Audit (2001). ‘Australian Native Vegetation Assessment 2001. National Land and Water Resources Audit.’ (Land and Water Australia: Canberra.)

Ottinger, G. (2010). Buckets of resistance: standards and the effectiveness of citizen science. Science, Technology & Human Values 35, 244–270.
Buckets of resistance: standards and the effectiveness of citizen science.CrossRef |

Peterson, A. T., Navarro-Sigüenza, A. G., and Benitez-Diaz, H. (1998). The need for continued scientific collecting; a geographic analysis of Mexican bird specimens. Ibis 140, 288–294.
The need for continued scientific collecting; a geographic analysis of Mexican bird specimens.CrossRef |

R Development Core Team (2010). ‘R: A Language and Environment for Statistical Computing.’ Version 2.11.1. (R Foundation for Statistical Computing: Vienna, Austria.) Available at http://www.r-project.org [Verified 1 October 2012].

Reddy, S., and Dávalos, L. M. (2003). Geographical sampling bias and its implications for conservation priorities in Africa. Journal of Biogeography 30, 1719–1727.
Geographical sampling bias and its implications for conservation priorities in Africa.CrossRef |

Rhodes, J. R., McAlpine, C. A., Lunney, D., and Possingham, H. P. (2005). A spatially explicit habitat selection model incorporating home range behavior. Ecology 86, 1199–1205.
A spatially explicit habitat selection model incorporating home range behavior.CrossRef |

Robertson, M., and Barker, N. (2006). A technique for evaluating species richness maps generated from collections data. South African Journal of Science 102, 78–84.

Robertson, M. P., Cumming, G. S., and Erasmus, B. F. N. (2010). Getting the most out of atlas data. Diversity & Distributions 16, 363–375.
Getting the most out of atlas data.CrossRef |

Romo, H., García-Barros, E., and Lobo, J. M. (2006). Identifying recorder-induced geographic bias in an Iberian butterfly database. Ecography 29, 873–885.
Identifying recorder-induced geographic bias in an Iberian butterfly database.CrossRef |

Rondinini, C., Wilson, K. A., Boitani, L., Grantham, H., and Possingham, H. P. (2006). Tradeoffs of different types of species occurrence data for use in systematic conservation planning. Ecology Letters 9, 1136–1145.
Tradeoffs of different types of species occurrence data for use in systematic conservation planning.CrossRef |

Rosenzweig, M. L. (1981). A theory of habitat selection. Ecology 62, 327–335.
A theory of habitat selection.CrossRef |

Saunders, D. A., Hobbs, R. J., and Margules, C. R. (1991). Biological consequences of ecosystem fragmentation: a review. Conservation Biology 5, 18–32.
Biological consequences of ecosystem fragmentation: a review.CrossRef |

Saunders, D. A., Hobbs, R. J., and Arnold, G. W. (1993). The Kellerberrin project on fragmented landscapes: a review of current information. Biological Conservation 64, 185–192.
The Kellerberrin project on fragmented landscapes: a review of current information.CrossRef |

Schmeller, D. S., Henry, P. Y., Julliard, R., Gruber, B., Clobert, J., Dziock, F., Lengyel, S., Nowicki, P., Deri, E., Budrys, E., Kull, T., Tali, K., Bauch, B., Settele, J., Van Swaay, C., Kobler, A., Babij, V., Papastergiadou, E., and Henle, K. (2009). Advantages of volunteer-based biodiversity monitoring in Europe. Conservation Biology 23, 307–316.
Advantages of volunteer-based biodiversity monitoring in Europe.CrossRef |

Seaman, D. E., and Powell, R. A. (1996). An evaluation of the accuracy of kernel density estimators for home range analysis. Ecology 77, 2075–2085.
An evaluation of the accuracy of kernel density estimators for home range analysis.CrossRef |

Slater, P., Slater, P., and Slater, R. (2009). ‘The Slater Field Guide to Australian Birds.’ (Reed New Holland Pty Ltd: Sydney.)

Soberón, M. J., and Llorente, B. J. (1993). The use of species accumulation functions for the prediction of species richness. Conservation Biology 7, 480–488.
The use of species accumulation functions for the prediction of species richness.CrossRef |

Spencer, S. R., Cameron, G. N., and Swihart, R. K. (1990). Operationally defining home range: temporal dependence exhibited by Hispid Cotton Rats. Ecology 71, 1817–1822.
Operationally defining home range: temporal dependence exhibited by Hispid Cotton Rats.CrossRef |

Sullivan, B. L., Wood, C. L., Iliff, M. J., Bonney, R. E., Fink, D., and Kelling, S. (2009). eBird: a citizen-based bird observation network in the biological sciences. Biological Conservation 142, 2282–2292.
eBird: a citizen-based bird observation network in the biological sciences.CrossRef |

Szabo, J. K., Davy, P. J., Hooper, M. J., and Astheimer, L. B. (2007). Predicting spatio-temporal distribution for eastern Australian birds using Birds Australia’s Atlas data: survey method, habitat and seasonal effects. Emu 107, 89–99.
Predicting spatio-temporal distribution for eastern Australian birds using Birds Australia’s Atlas data: survey method, habitat and seasonal effects.CrossRef |

Szabo, J., Vesk, P., Baxter, P., and Possingham, H. (2010). Regional avian species declines estimated from volunteer-collected long-term data using list length analysis. Ecological Applications 20, 2157–2169.
Regional avian species declines estimated from volunteer-collected long-term data using list length analysis.CrossRef |

Szabo, J. K., Vesk, P. A., Baxter, P. W. J., and Possingham, H. P. (2011). Paying the extinction debt: woodland birds in the Mount Lofty Ranges, South Australia. Emu 111, 59–70.
Paying the extinction debt: woodland birds in the Mount Lofty Ranges, South Australia.CrossRef |

Szabo, J. K., Fuller, R. A., and Possingham, H. P. (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.
A comparison of estimates of relative abundance from a weakly structured mass-participation bird atlas survey and a robustly designed monitoring scheme.CrossRef |

Thomsen, D. C. (2008). Community-based research: facilitating sustainability learning. Australasian Journal of Environmental Management 15, 222–230.
Community-based research: facilitating sustainability learning.CrossRef |

Tulloch, A. I. T., Mustin, K., Possingham, H. P., Szabo, J. K., and Wilson, K. A. (2012). To boldly go where no volunteer has gone before: predicting volunteer activity to prioritise surveys at the landscape scale. Diversity & Distributions , .
To boldly go where no volunteer has gone before: predicting volunteer activity to prioritise surveys at the landscape scale.CrossRef |

Weston, M., Fendley, M., Jewell, R., Satchell, M., and Tzaros, C. (2003). Volunteers in bird conservation: insights from the Australian Threatened Bird Network. Ecological Management & Restoration 4, 205–211.
Volunteers in bird conservation: insights from the Australian Threatened Bird Network.CrossRef |

Weston, M. A., Silcocks, A., Tzaros, C. L., and Ingwersen, D. (2006). A survey of contributors to an Australian bird atlassing project: demography, skills and motivation. Australian Journal on Volunteering 11, 51–58.

Williams, P. H., Prance, G. T., Humphries, C. J., and Edwards, K. S. (1996). Promise and problems in applying quantitative complementary areas for representing the diversity of some Neotropical plants (families Dichapetalaceae, Lecythidaceae, Garyocaraceae, Ghrysobalanaceae and Proteaceae). Biological Journal of the Linnean Society of London 58, 125–157.

Worton, B. J. (1989). Kernel methods for estimating the utilization distribution in home-range studies. Ecology 70, 164–168.
Kernel methods for estimating the utilization distribution in home-range studies.CrossRef |

Yaukey, P. H. (2010). Citizen science and bird-distribution data: an opportunity for geographical research. Geographical Review 100, 263–273.


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