FOR ONLINE PUBLICATION ONLY
Citizen Science as a Tool for Overcoming Insufficient Monitoring and Inadequate Stakeholder Buy-in in Adaptive Management: Criteria and Evidence
Erendira Aceves Buenoa, Adeyemi S. Adeleyea, Darcy Bradleya, William Brandta, Patrick Callerya, Marina Ferauda, Kendra Garnera, Rebecca Gentrya, Yuxiong Huanga, Ian McCullougha, Isaac Pearlmana, Sara Sutherlanda, Whitney Wilkinsona, Yi Yanga, Trevor Zinka, Sarah Andersona,b, and Christina Taguea
a Bren School of Environmental Science & Management, University of California, 2400 Bren Hall, Santa Barbara, California 93106, USA
b Corresponding author: ; (805) 893-5886
[1] Authors’ contribution
APPENDIX
Appendix A: Coding Methodology Used for Meta-analysis
The coding of articles for meta-analysis was based on a series of questions addressing key characteristics of the citizen science programs reviewed. For ease of analysis we categorized these questions according to the relevant criteria introduced in our study: basic program data, management objective, monitoring data characteristics, monitoring requirements, stakeholder involvement opportunities, stakeholder engagement pathways, and stakeholder incentives. Summary statistics for each coding question are summarized in Table A1 below.
Questions in the basic program data category were designed to categorize the types of citizen science data collected.
QB1: What was the field of research?
(botany (b), wildlife (w), air/atmosphere (a), energy (e), water (q), and social (s))
QB2: What system was being studied?
(marine (m), freshwater (f), terrestrial (t), atmosphere (a))
QB3: Who was involved in the design of the monitoring?
(scientists (s), community (c), NGO (n), government (g), private entity (p), NA)
QB4. What was the duration of the citizen science research?
(0 - 1 year (includes 1 year), 1 - 5 years (includes 5 years), 5 - 10 years (includes 10 years), greater than 10 years, NA)
QB5. How many citizen scientists were involved in the research?
(1 - 10, 11 - 50, 51 - 100, 101 - 500, 501 - 1000, greater than 1000, NA)
Questions in the management objectives category were designed to test whether citizen science programs were explicitly designed to assist with a management problem and to further test whether the monitoring information obtained by these programs was in fact used to inform management.
QO1: Were the original goals of the study explicitly to inform management?
(Y, N, NA)
QO2: Have the data been used for management?
(Y, N)
QO3: Were the managers directly involved in the design of the study?
(Y, N)
Questions in the monitoring data characteristics category sought to describe the scale, nature and quality checking of the data collected by citizen scientists.
QD1: Are quantitative data (categorical or numeric) collected?
(Y, N)
QD2: Are qualitative data (subjective, descriptive, noncategorical) collected?
(Y, N)
QD3: What spatial scale did the data cover?
(local - includes one location, neighboring communities, or multiple villages (l), regional (r), global - includes more than 1 continent, excludes a single ocean or the European Union (g))
QD4: Are quality assurance and control (QA/QC) metrics for the citizen science collected data discussed?
(Y, N)
QD5: If QA/QC was discussed, were there problems with data accuracy?
(Y, N, NA)
QD6: If there were problems with data accuracy, how substantial were they?
(critical - data were not usable (C), fixable - data were critical but fixable or workable (F), minor - accuracy issues were minimal and did not affect the study (M), NA)
Questions in the monitoring requirements category inquired as to the difficulty or complexity of the citizen science data collection in terms of special skills, training, and equipment.
QM1: Are any special skills required to participate as a citizen scientist? A skill is prior knowledge that is needed for which no training is provided.
(Y, N)
QM2: Was training provided? Training includes live instruction (including videos), not a written set of directions.
(Y, N)
QM3: What level of supplies are the organizers required to provide?
(small supplies such as paper, pencils, lunch, guidebooks, or transect equipment (S), specialized or expensive equipment such as camera, computer, scuba gear, or boat rentals (E), both (B), or nothing (N)). One caveat is that if equipment was required, but the citizen’s had to bring their own, such as scuba gear, then the response was N.
Questions in the stakeholder involvement category were used to identify feedback mechanisms between stakeholders and decision makers.
QSi1: Was there explicit communication/feedback of the results to the public?
(Y, N)
QSi2: Were there explicit opportunities for the public to respond?
(Y, N)
Questions in the stakeholder engagement pathways category focused on the mechanisms that stakeholders used to interact with decision-makers, scientists, and whether citizen scientist retention was discussed.
QSe1: Was a web-tool necessary for the citizen scientists to complete the monitoring?
(Y, N)
QSe2: Were there active measures taken to keep citizen scientists engaged?
(Y, N)
QSe3: How do citizen scientists and scientists interact?
(in person (P), not in person (I), no interactions (N))
QSe4: How do citizen scientists and managers interact?
(in person (P), not in person (I), no interactions (N))
QSe5: What kind of citizen scientists are involved?
(community (C), non-local volunteers (V))
The final category, stakeholder incentives, is made up of only a single, complex question that seeks to describe the nature of the benefits that citizen scientists received as a result of their participation in the study.
QSd1: What benefits do the citizen scientists receive?
(sense of place or social capital (S), tools/technology to enable/empower participants (T), action to improve quality of life (A), knowledge (K), economic benefit (E); Note: more than one could be selected).
Table A1Summary Statistics
Characteristic / Category / Percent
QB1: What was the field of research? / Air/atmosphere / 0.036
Botany / 0.313
Wildlife / 0.699
Water / 0.145
Social / 0.036
QB2: What system was being studied? / Atmosphere / 0.024
Freshwater / 0.084
Terrestrial / 0.675
Marine / 0.277
QB3: Who was involved in the design of the monitoring? / Government / 0.217
NGO / 0.313
Community / 0.169
Scientists / 0.699
Private entity / 0.024
QB4: What was the duration of the citizen science research? / 0 – 1 years / 0.277
1 – 5 years / 0.313
5 – 10 years / 0.133
More than 10 years / 0.229
N/A (not specified) / 0.048
QB5: How many citizen scientists were involved in the research? / 1 – 10 / 0.084
11 – 50 / 0.145
51 – 100 / 0.072
101 – 500 / 0.145
501 – 1000 / 0.205
More than 1000 / 0.145
N/A (not specified) / 0.205
QO1: Were the original goals of the study explicitly to inform management? / No / 0.53
Yes / 0.458
NA / 0.012
QO2: Have the data been used for management? / No / 0.59
Yes / 0.41
QO3: Were the managers directly / No / 0.614
involved in the design of the study? / Yes / 0.386
QD1: Are quantitative data collected? / No / 0.096
Yes / 0.904
QD2: Are qualitative data collected? / No / 0.422
Yes / 0.578
QD3: What spatial scale did the data cover? / Global / 0.024
Local / 0.41
Regional / 0.566
QD4: Are QA/QC metrics discussed? / No / 0.193
Yes / 0.807
QD5: If QA/QC was discussed, were there problems with data accuracy? / No / 0.108
Yes / 0.687
NA / 0.193
QD6: If there were problems with data accuracy, how substantial were they? / Critical, data were not usable / 0.012
Critical but fixable/workable / 0.253
Minor / 0.386
NA / 0.337
QM1: Are any special skills required to participate as a citizen scientist? / No / 0.627
Yes / 0.373
QM2: Was training provided? / No / 0.337
Yes / 0.663
QM3: What level of supplies are the organizers required to provide? / Small and specialized supplies / 0.06
Specialized or expensive equipment / 0.084
No supplies are needed / 0.361
Small supplies / 0.494
QSi1: Was there explicit feedback of the results to the public? / No / 0.614
Yes / 0.386
QSi2: Were there explicit opportunities to respond? / No / 0.735
Yes / 0.265
QSe1: Was a web-tool necessary for monitoring? / No / 0.651
Yes / 0.349
QSe2: Were there measures taken to keep citizen scientists engaged? / No / 0.663
Yes / 0.337
QSe3: How do citizen scientists and scientists interact? / In person / 0.554
Not in person / 0.253
No interactions / 0.229
QSe4: How do citizen scientists and managers interact? / In person / 0.193
Not in person / 0.289
No interaction / 0.687
QSe5: What kind of citizen scientists are involved? / Community / 0.277
Volunteers / 0.723
QSd1: What benefits do the citizen scientists receive? / Sense of place or social capital / 0.494
Tools/technology / 0.253
Action / 0.289
Knowledge / 0.747
Economic benefit / 0.217
STAKE / NA / 0.157
Appendix B: Reviewed Papers
Paper NO. / Paper citation information1 / Brunsdon C, Comber L. 2012. Assessing the changing flowering date of the common lilac in North America: a random coefficient model approach. Geoinformatica 16: 675-690.
2 / Van Rijsoort J, Zhang JF. 2005. Participatory resource monitoring as a means for promoting social change in Yunnan, China. Biodiversity and Conservation 14: 2543-2573.
3 / Hamilton RJ, Giningele M, Aswani S, Ecochard JL. 2012. Fishing in the dark-local knowledge, night spearfishing and spawning aggregations in the Western Solomon Islands. Biological Conservation 145: 246-257.
4 / Pittman SE, Dorcas ME. 2006. Catawba River corridor coverboard program: a citizen science approach to amphibian and reptile inventory. J. NC Acad. Sci 122: 142-151.
5 / Crall AW, Newman GJ, Stohlgren TJ, Holfelder KA, Graham J, Waller DM. 2011. Assessing citizen science data quality: an invasive species case study. Conservation Letters 4: 433-442.
6 / Lye GC, Osborne JL, Park KJ, Goulson D. 2012. Using citizen science to monitor Bombus populations in the UK: nesting ecology and relative abundance in the urban environment. Journal of Insect Conservation 16: 697-707.
7 / Osborne JL, Martin AP, Shortall CR, Todd AD, Goulson D, Knight ME, Hale RJ, Sanderson RA. 2008. Quantifying and comparing bumblebee nest densities in gardens and countryside habitats. Journal of Applied Ecology 45: 784-792.
8 / Davies TK, Stevens G, Meekan MG, Struve J, Rowcliffe JM. 2012. Can citizen science monitor whale-shark aggregations? Investigating bias in mark-recapture modelling using identification photographs sourced from the public. Wildlife Research 39: 696-704.
9 / Oldekop JA, Bebbington AJ, Berdel F, Truelove NK, Wiersberg T, Preziosi RF. 2011. Testing the accuracy of non-experts in biodiversity monitoring exercises using fern species richness in the Ecuadorian Amazon. Biodiversity and Conservation 20: 2615-2626.
10 / Jordan RC, Gray SA, Howe DV, Brooks WR, Ehrenfeld JG. 2011. Knowledge Gain and Behavioral Change in Citizen-Science Programs. Conservation Biology 25: 1148-1154.
11 / Townsend WR, Borman R, Yiyoguaje E, Mendua L. 2005. Cofan Indians' monitoring of freshwater turtles in Zabalo, Ecuador. Biodiversity and Conservation 14: 2743-2755.
12 / Pratihast AK, Herold M, Avitabile V, de Bruin S, Bartholomeus H, Souza CM, Ribbe L. 2013. Mobile Devices for Community-Based REDD+ Monitoring: A Case Study for Central Vietnam. Sensors 13: 21-38.
13 / Downs CT. 2005. Abundance of the endangered Cape parrot, Poicephalus robustus, in South Africa: implications for its survival. African Zoology 40: 15-24.
14 / Sarda-Palomera F, Brotons L, Villero D, Sierdsema H, Newson SE, Jiguet F. 2012. Mapping from heterogeneous biodiversity monitoring data sources. Biodiversity and Conservation 21: 2927-2948.
15 / Hoyer MV, Wellendorf N, Frydenborg R, Bartlett D, Canfield DE. 2012. A comparison between professionally (Florida Department of Environmental Protection) and volunteer (Florida LAKEWATCH) collected trophic state chemistry data in Florida. Lake and Reservoir Management 28: 277-281.
16 / Bonney R, Cooper CB, Dickinson J, Kelling S, Phillips T, Rosenberg KV, Shirk J. 2009. Citizen Science: A Developing Tool for Expanding Science Knowledge and Scientific Literacy. Bioscience 59: 977-984.
17 / Dangles O, Carpio FC, Villares M, Yumisaca F, Liger B, Rebaudo F, Silvain JF. 2010. Community-Based Participatory Research Helps Farmers and Scientists to Manage Invasive Pests in the Ecuadorian Andes. Ambio 39: 325-335.
18 / Metzger ES, Lendvay JM. 2006. Seeking Environmental Justice through Public Participation: A Community-Based Water Quality Assessment in Bayview Hunters Point. Environmental Practice 8: 104-114.
19 / Deguines N, Julliard R, de Flores M, Fontaine C. 2012. The Whereabouts of Flower Visitors: Contrasting Land-Use Preferences Revealed by a Country-Wide Survey Based on Citizen Science. Plos One 7.
20 / Seak S, Schmidt-Vogt D, Thapa GB. 2012. Biodiversity Monitoring at the Tonle Sap Lake of Cambodia: A Comparative Assessment of Local Methods. Environmental Management 50: 707-720.
21 / Tulloch AIT, Szabo JK. 2012. A behavioural ecology approach to understand volunteer surveying for citizen science datasets. Emu 112: 313-325.
22 / Witt MJ, Hardy T, Johnson L, McClellan CM, Pikesley SK, Ranger S, Richardson PB, Solandt JL, Speedie C, Williams R, Godley BJ. 2012. Basking sharks in the northeast Atlantic: spatio-temporal trends from sightings in UK waters. Marine Ecology Progress Series 459: 121-+.
23 / Delaney DG, Sperling CD, Adams CS, Leung B. 2008. Marine invasive species: validation of citizen science and implications for national monitoring networks. Biological Invasions 10: 117-128.
24 / Ottinger G. 2010. Buckets of Resistance: Standards and the Effectiveness of Citizen Science. Science Technology & Human Values 35: 244-270.
25 / Goffredo S, Pensa F, Neri P, Orlandi A, Gagliardi MS, Velardi A, Piccinetti C, Zaccanti F. 2010. Unite research with what citizens do for fun: "recreational monitoring'' of marine biodiversity. Ecological Applications 20: 2170-2187.
26 / 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: 2157-2169.
27 / Oberhauser K, Gebhard I, Cameron C, Oberhauser S. 2007. Parasitism of monarch butterflies (Danaus plexippus) by Lespesia archippivora (Diptera : Tachinidae). American Midland Naturalist 157: 312-328.
28 / Humber F, Godley BJ, Ramahery V, Broderick AC. 2011. Using community members to assess artisanal fisheries: the marine turtle fishery in Madagascar. Animal Conservation 14: 175-185.
29 / Sewell D, Guillera-Arroita G, Griffiths RA, Beebee TJC. 2012. When Is a Species Declining? Optimizing Survey Effort to Detect Population Changes in Reptiles. Plos One 7.