Skip to main content
SpringerLink
Log in

Using aerial surveys and citizen science to create species distribution models for an imperiled grouse

Biodiversity and Conservation volume 29, pages 967–986 (2020)Cite this article

Abstract

Estimating species distributions requires species presence data of sufficient quantity from reputable sources that are geographically representative of the species’ space use. Collecting presence data that meets these standards can be costly and is often complicated by limited land access. Citizen science projects are an appealing alternative source of presence data as these data are freely available and collected globally. Websites such as eBird have become increasingly large repositories of citizen science data. The vulnerable lesser prairie-chicken (LPC; Tympanuchus pallidicinctus) is a species well-represented in the eBird database, with presence observations from 140 unique locations from 2012 to 2014. During that same period, a distribution-wide, standardized aerial survey with state and federal support recorded 106 LPC detections. Our objective was to compare species distribution models (SDMs) made with eBird data to models made with aerial survey data to determine the potential for citizen science data to contribute to conservation planning. We used maximum entropy modeling to create SDMs based on eBird data, aerial survey data, and a combination of both data sets using variables of biological significance to LPCs. We obtained comparable model performance using aerial survey data only [standardized test omission rate (STO): 23.4%, test AUC: 0.76] and with eBird data only (STO: 23.8%, AUC: 0.76). The I statistic confirmed a very high degree of similarity between the outputs of the two model sets (I = 0.929). However, a road bias existed within both data sets (positive and negative biases), potentially confounding some environmental correlates. Despite this bias, our combined model predicted an increase of 1,732,500 ha of unique area suitable for the LPC. Our results indicated that eBird data could be used as a low-cost source for species occurrence data to create species distribution models, though biases in these datasets should be assessed to guide interpretability of the predicted outputs.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

39,95 €

Price includes VAT (Netherlands)

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

References

  • Allouche O, Tsoar A, Kadmon R (2006) Assessing the accuracy of species distribution models: prevalence, kappa, and the true skill statistic (TSS). J Appl Ecol 43:1223–1232

    Article  Google Scholar 

  • Anderson RP, Gonzalez I Jr (2011) Species-specific tuning increases robustness to sampling bias in models of species distributions: an implementation with Maxent. Ecol Model 222:2796–2811

    Article  Google Scholar 

  • Bacon L, Hingrat Y, Jiguet F, Monnet A-C, Sarrazin F, Robert A (2017) Habitat suitability and demography, a time-dependent relationship. Ecol Evol 7(7):2214–2222

    Article  PubMed  PubMed Central  Google Scholar 

  • Beck JL (2009) Impacts of oil and natural gas on prairie grouse: current knowledge and research needs. In: 26th conference, proceedings of the 2009 national meeting: American Society of Mining and Reclamation, Vol 1, pp 66–87

    Article  Google Scholar 

  • Boyce MS, Vernier PR, Nielsen SE, Schmiegelow FKA (2002) Evaluating resource selection functions. Ecol Model 157:281–300

    Article  Google Scholar 

  • Brown JL (2014) SDMtoolbox: a python-based GIS toolkit for landscape genetic, biogeographic, and species distribution model analyses. Methods Ecol Evol 5:694–700

    Article  Google Scholar 

  • Carlisle JA, Hornsby FE, Nasman K, McDonald LL, Houts ME, Pavlacky DC Jr (2018) Multi-scale occupancy estimation for the lesser prairie-chicken: 2012–2016. Technical report. Prepared for Oregon State University and Western Association of Fish and Wildlife Agencies. Western EcoSystems Technology, Inc., Laramie, Wyoming, USA

  • Clark JA, May MM (2002) Taxonomic bias in conservation research. Science 297:191–192

    Article  CAS  PubMed  Google Scholar 

  • Clark JA, Hoekstra JM, Boersma PD, Kareiva P (2002) Improving U.S. endangered species act recovery plans: key findings and recommendations of the SCB recovery plan project. Conserv Biol 16:1510–1519

    Article  Google Scholar 

  • Columbia University (2005) Wildlife Conservation Society and Center for International Earth Science Information Network. Last of the Wild Project, Version 2, 2005 (LWP-2): Global Human Footprint Dataset (Geographic). NASA Socioeconomic Data and Applications Center (SEDAC), Palisades. https://doi.org/10.7927/H4M61H5F

  • Copelin FF (1963) The lesser prairie-chicken in Oklahoma. Oklahoma Department of Wildlife Technical Bulletin 6, Oklahoma City, Oklahoma, USA

  • Costa GC, Nogueira C, Machado RB, Colli GR (2010) Sampling bias and the use of ecological niche modeling in conservation planning: a field evaluation in a biodiversity hotspot. Biodivers Conserv 19 (3):883–899

    Article  Google Scholar 

  • Courter JR, Johnson RJ, Stuyck CM, Lang BA, Kaiser EW (2013) Weekend bias in citizen science data reporting: implications for phenology studies. Int J Biometeorol 57:715–720

    Article  PubMed  Google Scholar 

  • Coxen CL, Frey JK, Carleton SA, Collins DP (2017) Species distribution models for a migratory bird based on citizen science and satellite tracking data. Glob Ecol Conserv 11:298–311

    Article  Google Scholar 

  • Davis DM (2009) Nesting ecology and reproductive success of lesser prairie-chickens in shinnery oak-dominated rangelands. Wilson J Ornithol 121:322–327

    Article  Google Scholar 

  • Dickinson JL, Zuckerberg B, Bonter DN (2010) Citizen science as an ecological research tool: challenges and benefits. Annu Rev Ecol Evol S 41:149–172

    Article  Google Scholar 

  • Dormann CF, Elith J, Bacher S, Buchmann C, Carl G, Carré G et al (2013) Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography 36:27–46

    Article  Google Scholar 

  • eBird Basic Dataset. Version EBD_relFeb-2015. Cornell Lab of Ornithology, Ithaca, New York, USA

  • Elith J (2002) Quantitative methods for modeling species habitat: comparative performance and an application to Australian plants. In: Ferson S, Burgman M (eds) Quantitative methods for conservation biology. Springer, New York, pp 39–58

    Google Scholar 

  • Elith J, Phillips SJ, Hastie T, Dudik M, Chee YE, Yates CJ (2011) A statistical explanation of MaxEnt for ecologists. Divers Distrib 17:43–57

    Article  Google Scholar 

  • ESRI (2011) ArcGIS Desktop: Release 10. Environmental Systems Research Institute, Redlands

    Google Scholar 

  • Feeley KJ, Silman MR (2011) Keep collecting: accurate species distribution modelling requires more collections that previously thought. Divers Distrib 17:1132–1140

    Article  Google Scholar 

  • Fielding AH, Bell JF (1997) A review of methods for the assessment of prediction errors in conservation presence/absence models. Environ Conserv 24:38–49

    Article  Google Scholar 

  • Fuhlendorf SD, Woodward AJW, Leslie DM, Shackford JS (2002) Multi-scale effects of habitat loss and fragmentation on lesser prairie-chicken populations of the US Southern Great Plains. Landsc Ecol 17:617–628

    Article  Google Scholar 

  • Geldmann J, Heilmann-Clausen J, Holm TE, Levinsky I, Markussen B, Olsen K, Rahbek C, Tøttrup AP (2016) What determines spatial bias in citizen science? Exploring four recording schemes with different proficiency requirements. Divers Distrib 22:1139–1149

    Article  Google Scholar 

  • Gillette GL, Reese KP, Connelly JW, Colt CJ, Knetter JM (2015) Evaluating the potential of aerial infrared as a lek count method for prairie grouse. J Fish Wildl Manag 6:486–497

    Article  Google Scholar 

  • Guisan A, Thuiller W (2005) Predicting species distribution: offering more than simple habitat models. Ecol Lett 8:993–1009

    Article  PubMed  Google Scholar 

  • Hagen CA (2010) Impacts of energy development on prairie grouse ecology: a research synthesis. Trans N Am Wildl Nat Res 75:96–103

    Google Scholar 

  • Hagen CA, Grisham BA, Boal CW, Haukos DA (2013) A meta-analysis of lesser prairie-chicken nesting and brood rearing habitats: implications for habitat management. Wildl Soc B 37:750–758

    Article  Google Scholar 

  • Hagen CA, Pavlacky DC, Adachi K, Hornsby FE, Rintz TJ, McDonald LL (2016) Multiscale occupancy modeling provides insights into range-wide conservation needs of lesser prairie-chicken (Tympanuchus pallidicinctus). Condor 118:597–612

    Article  Google Scholar 

  • Higa M, Yamaura Y, Koizumi I, Yabuhara Y, Senzaki M, Ono S (2015) Mapping large-scale bird distributions using occupancy models and citizen data with spatially biased sampling effort. Divers Distrib 21:46–54

    Article  Google Scholar 

  • Hirzel AH, Le Lay G, Helfer V, Randin C, Guisan A (2006) Evaluating the ability of habitat suitability models to predict species presences. Ecol Model 199:142–152

    Article  Google Scholar 

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

    Article  PubMed  Google Scholar 

  • Hovick TJ, Elmore RD, Dahlgren DK, Fuhlendorf SD, Engle DM (2014) Evidence of negative effects of anthropogenic structures on wildlife: a review of grouse survival and behavior. J Appl Ecol 51:1680–1689

    Article  Google Scholar 

  • Hovick TJ, Dahlgren DK, Papeş M, Elmore RD, Pitman JC (2015) Predicting greater prairie-chicken lek site suitability to inform conservation actions. PLOS ONE 10:e0137021

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Hunt JL, Best T (2010) Vegetative characteristics of active and abandoned leks of lesser prairie-chicken (Tympanuchus pallidicinctus) in southeastern New Mexico. Southwest Nat 55:477–487

    Article  Google Scholar 

  • Jackson MM, Gergel SE, Martin K (2015) Citizen science and field survey observations provide comparable results for mapping Vancouver Island white-tailed ptarmigan (Lagopus leucura saxatilis) distributions. Biol Conserv 181:162–172

    Article  Google Scholar 

  • Jarnevich CS, Laubhan MK (2011) Balancing energy development and conservation: a method utilizing species distribution models. Environ Manag 47:926–936

    Article  Google Scholar 

  • Jiménez-Valverde A (2012) Insights into the area under the receiver operating characteristic curve (AUC) as a discrimination measure in species distribution modeling. Glob Ecol Biogeogr 21:498–507

    Article  Google Scholar 

  • Kadmon R, Farber O, Danin A (2004) Effect of roadside bias on the accuracy of predictive maps produced by bioclimatic models. Ecol Appl 14(2):401–413

    Article  Google Scholar 

  • Kelling S, Johnston A, Bonn A, Fink D, Ruiz-Gutierrez V, Bonney R, Fernandez M, Hochachka WM, Julliard R, Kraemer R, Guralnick R (2019) Using semistructured surveys to improve citizen science data for monitoring biodiversity. Bioscience 69:170–179

    Article  PubMed  PubMed Central  Google Scholar 

  • Kukal CA (2010) The over-winter ecology of lesser prairie-chickens (Tympanuchus pallidicinctus) in the northeast Texas Panhandle. Thesis. Texas Tech University

  • LANDFIRE (2013) Existing vegetation type layer. U.S.Department of Interior, Geological Survey. http://landfire.cr.usgs.gov

  • Leroy B, Delsol R, Gugueny B, Meynard CN, Barhoumi C, Barbet-Massin M, Bellard C (2018) Without quality presence–absence data, discrimination metrics such as TSS can be misleading measures of model performance. J Biogeogr 45:1994–2002

    Article  Google Scholar 

  • McDonald L, Adachi K, Rintz T, Gardner G, Hornsby F (2014) Range-wide population size of the lesser prairie-chicken: 2012, 2013, and 2014. Report to Western Association of Fish and Wildlife Agencies, WEST Inc., Laramie

    Google Scholar 

  • Miller-Rushing A, Primack R, Bonney R (2012) The history of public participation in ecological research. Front Ecol Environ 10:285–290

    Article  Google Scholar 

  • Naugle DE, Doherty KE, Walker BL, Copeland HE, Holloran MJ, Tack JD (2010) Sage grouse and cumulative impacts of energy development. In: Naugle DE (ed) Energy development and Wildlife Conservation in Western North America. Island Press, Washington, DC, pp 55–70

    Google Scholar 

  • Patten MA, Wolfe DH, Shochat E, Sherrod SK (2005) Effects of microhabitat and microclimate selection on adult survivorship of the lesser prairie-chicken. J Wildl Manag 69:1270–1278

    Article  Google Scholar 

  • Phillips SJ, Dudik M (2008) Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation. Ecography 31:161–175

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Pirius NE, Boal CW, Haukos DA, Wallace MC (2013) Winter habitat use and survival of lesser prairie-chickens in West Texas. Wildl Soc Bull 37(4):759–765

    Article  Google Scholar 

  • Pitman JC, Hagen CA, Robel RJ, Loughin TM, Applegate RD (2005) Location and success of lesser prairie-chicken nests in relation to vegetation and human disturbance. J Wildl Manag 69:1259–1269

    Article  Google Scholar 

  • Pitman JC, Hagen CA, Jamison BE, Robel RJ, Loughin TM, Applegate RD (2006) Nesting ecology of lesser prairie-chickens in sand sagebrush prairie of southwestern Kansas. Wilson J Ornithol 118:23–35

    Article  Google Scholar 

  • Rabe MJ, Rosenstock SS, DeVos JC (2002) Review of big-game survey methods used by wildlife agencies of the western United States. Wildl Soc B 30:46–52

    Google Scholar 

  • Radosavljevic A, Anderson RP (2014) Making better Maxent models of species distributions: complexity, overfitting and evaluation. J Biogeogr 41:629–643

    Article  Google Scholar 

  • Rebelo H, Jones G (2010) Ground validation of presence-only modelling with rare species: a case study on barbastelles Barbastella barbastellus (Chiroptera: Vespertilionidae). J Appl Ecol 47:410–420

    Article  Google Scholar 

  • Richardson DM, Whittaker RJ (2010) Conservation biogeography: foundations, concepts and challenges. Divers Distrib 16:313–320

    Article  Google Scholar 

  • Sahlean TC, Gherghel I, Papeş M, Strugariu A, Zamfirescu ŞR (2014) Refining climate change projections for organisms with low dispersal abilities: a case study of the Caspian whip snake. PLoS ONE 9:e91994

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Silvy NJ (2006) In my opinion: shinnery oak is not a requirement for lesser prairie-chicken habitat. In: Cain III JW, Krausman PR (eds) Proceedings of the symposium on managing wildlife in the Southwest: new challenges for the 21st century, pp 138–142

  • Southern Great Plains Crucial Habitat Assessment Tool. kars.ku.edu/maps/sgpchat/. Accessed Jan 2019

  • Spencer D, Haukos D, Hagen C, Daniels M, Goodin D (2017) Conservation reserve program mitigates grassland loss in the lesser prairie-chicken range of Kansas. Glob Ecol Conserv 9:21–38

    Article  Google Scholar 

  • Stubbs M (2014) Conservation provisions in the 2014 Farm Bill (P.L. 113 – 79). CRS Report R43504

  • Sullins DS, Kraft JD, Haukos DA, Robinson SG, Reitz JH, Plumb RT, Lautenbach JM, Lautenbach JD, Sandercock BK, Hagen CA (2018) Demographic consequences of conservation reserve program grasslands for lesser prairie-chickens. J Wildl Manag 82:1617–1632

    Article  Google Scholar 

  • Sullins DS, Haukos DA, Lautenbach JM, Lautenbach JD, Robinson SG, Rice MB, Sandercock BK, Kraft JD, Plumb RT, Reitz JH, Hutchinson JMS, Hagen CA (2019) Strategic conservation for lesser prairie-chickens among landscapes of varying anthropogenic influence. Biol Conserv 238:108213

    Article  Google Scholar 

  • Sullivan BL, Wood CL, Iliff MJ, Bonney RE, Fink D, Kelling S (2009) eBird: A citizen based bird observation network in the biological sciences. Biol Conserv 142:2282–2292

    Article  Google Scholar 

  • Sullivan BL, Aycrigg JL, Barry JH, Bonney RE, Bruns N, Cooper CB, Damoulas T, Dhondt AA, Dietterich T, Farnsworth A, Fink D (2014) The eBird enterprise: an integrated approach to development and application of citizen science. Biol Conserv 169:31–40

    Article  Google Scholar 

  • Swets JA (1988) Measuring the accuracy of diagnostic systems. Science 240:1285–1293

    Article  CAS  PubMed  Google Scholar 

  • Tanner EP, Fuhlendorf SD (2018) Impact of an agri-environmental scheme on landscape patterns. Ecol Indic 85:956–965

    Article  Google Scholar 

  • Taylor MA, Guthery FS (1980) Status, ecology, and management of the lesser prairie-chicken. US Forest Service General Technical Report RM-77. Rocky Mountain Forest and Range Experiment Station, Fort Collins

    Google Scholar 

  • Theobald EJ, Ettinger AK, Burgess HK, DeBey LB, Schmidt NR, Froehlich HE, Wagner C, HilleRisLambers J, Tewksbury J, Harsch MA, Parrish JK (2015) Global change and local solutions: tapping the unrealized potential of citizen science for biodiversity research. Biol Conserv 181:236–244

    Article  Google Scholar 

  • Timmer JM, Butler MJ, Ballard WB, Boal CW, Whitlaw HA (2014) Spatially explicit modeling of lesser prairie-chicken lek density in Texas. J Wildl Manag 78:142–152

    Article  Google Scholar 

  • US Bureau of Census (1991) 1990 Census of population and housing. US Bureau of Census, Washington, DC, USA

  • Van Pelt WE, Kyle S, Pitman J, Klute D, Beauprez G, Schoeling D, Janus A, Haufler J (2013) The lesser prairie-chicken range-wide conservation plan. Western Association of Fish and Wildlife Agencies. Cheyenne, Wyoming

    Google Scholar 

  • Warren DL, Glor RE, Turelli M (2008) Environmental niche equivalency versus conservatism: quantitative approaches to niche evolution. Evolution 62:2868–2883

    Article  PubMed  Google Scholar 

  • Warren DL, Glor RE, Turelli M (2010) ENMTools (Version 1.4.4): A toolbox for comparative studies of environmental niche models. Ecography 33:607–611

    Article  Google Scholar 

  • Wilson JW, Sexton JO, Job RT, Haddad NM (2013) The relative contribution of terrain, land cover, and vegetation structure indices to species distribution models. Biol Conserv 164:170–176

    Article  Google Scholar 

  • Wisz MS, Hijmans RJ, Li J, Peterson AT, Graham CH, Guisan A, NCEAS Predicting Species Distributions Working Group (2008) Effects of sample size on the performance of species distribution models. Divers Distrib 14:763–773

    Article  Google Scholar 

  • Wolfe DH, Patten MA, Shochat E, Pruett CL, Sherrod SK (2007) Causes and patterns of mortality in lesser prairie-chickens (Tympanuchus pallidicinctus) and implications for management. Wildl Biol 13:95–104

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by funding from the Oklahoma Department of Wildlife Conservation (ODWC) and administered through the Oklahoma Cooperative Fish and Wildlife Research Unit (Oklahoma Department of Wildlife Conservation, Oklahoma State University, US Geological Survey, US Fish and Wildlife Service, and the Wildlife Management Institute cooperating). This material is also based on work supported by the National Science Foundation under Grant No. OIA-1301789 and by the United States Department of Agriculture (USDA) Natural Resource Conservation Service (NRCS) through the Lesser Prairie-Chicken Initiative. Additional support was provided by the Oklahoma Agricultural Experiment Station at Oklahoma State University. We thank A. Janus (ODWC) for providing assistance acquiring aerial survey data.

Author information

Authors and Affiliations

  1. Western EcoSystems Technology, Inc., Albuquerque, NM, 87112, USA

    Ashley M. Tanner

  2. Department of Natural Resource Ecology and Management, Oklahoma State University, Stillwater, OK, 74078, USA

    Ashley M. Tanner, Evan P. Tanner, Samuel D. Fuhlendorf, R. Dwayne Elmore & Craig A. Davis

  3. Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville, TN, 37996, USA

    Monica Papeş

  4. Oklahoma State University, 008C Ag Hall, Stillwater, OK, 74078, USA

    Evan P. Tanner

Authors
  1. Ashley M. Tanner
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Evan P. Tanner
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Monica Papeş
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Samuel D. Fuhlendorf
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. R. Dwayne Elmore
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Craig A. Davis
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Evan P. Tanner.

Additional information

Communicated by Adeline Loyau.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 824.6 kb)

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tanner, A.M., Tanner, E.P., Papeş, M. et al. Using aerial surveys and citizen science to create species distribution models for an imperiled grouse. Biodivers Conserv 29, 967–986 (2020). https://doi.org/10.1007/s10531-019-01921-6

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10531-019-01921-6

Keywords

  • Aerial surveys
  • Citizen science
  • Lesser prairie-chicken
  • Species distribution models
  • Tympanuchus pallidicinctus

Search

Navigation