Assessing backyard biodiversity across broad spatial scales: The School of Ants citizen science project

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  Ecologists, educators, and writers collaborate with the publicto assess backyard diversity in The School of Ants Project A NDREA  L UCKY  , 1,2 A MY  M. S AVAGE  , 2,   L AUREN  M. N ICHOLS  , 2 C RISTINA  C ASTRACANI  , 3 L EONORA  S HELL  , 2 D ONATO  A. G RASSO  , 3 A LESSANDRA  M ORI  , 3 AND  R OBERT  R. D UNN 2 1 Department of Entomology and Nematology, University of Florida, 970 Natural Area Drive, Gainesville, Florida 32611-0620 USA 2 Department of Biological Sciences, North Carolina State University, Raleigh, North Carolina 27607-7617 USA 3 Dipartimento di Bioscienze, Universita` degli Studi di Parma, Parco Area delle Scienze, 11/a, 43124 Parma, Italy Citation:  Lucky, A., A. M. Savage, L. M. Nichols, C. Castracani, L. Shell, D. A. Grasso, A. Mori, and R. R. Dunn. 2014.Ecologists, educators, and writers collaborate with the public to assess backyard diversity in The School of Ants Project.Ecosphere 5(7):78. Abstract.  Citizen science can generate data that would not exist otherwise while increasing publicscientific literacy. However, the quality and use of citizen science data have been criticized in the recentecological literature. We need an approach that advances eco-evolutionary understanding, achieveseducation goals and incorporates public participation into as many aspects of the scientific process aspossible. We collaborated with public participants to make new discoveries about the distribution andecology of ants while informing the next studies that participants and scientists might perform together. Weimplemented the School of Ants (SoA) program in which participants sample ants that are identified bytaxonomic experts. Using a comprehensive framework that meets the needs of multiple agents, we alsodeveloped outreach materials about ant biology, collaborated with educators to incorporate SoA intoclassroom science, and launched an international SoA module in Italy. In the first 17 months, SoAvolunteers collected ants at 500 unique sites across the USA-including all 50 states and Washington, D.C.To address concerns about the validity of citizen scientist-derived data, we conducted a ground truthingtrial that confirmed that trained and untrained volunteers were equally effective at collecting ants. Datafrom SoA samples indicate that ant diversity varies across wide geographic scales and that there can behigh levels of native ant diversity where people live. SoA volunteers collected 7 exotic and 107 native antspecies. Although exotic ants were common, ants native to North America occurred in  ; 70 %  of all sites.Many of the ants common in backyards were species that tend to be very poorly studied. For example,citizen scientists documented a range extension of more than 2000 miles for the Asian Needle Ant, Pachycondyla chinensis . Using SoA data as a starting point, we collaborated with a science writer to producea free, interactive iBook about the common ants in North America; the book included distribution mapssuch as that for  P. chinensis  informed by participant collections. Moving forward, we plan to leverage thisexisting framework to address more complex ecological and evolutionary questions in partnership withour public participants. Key words:  ants; citizen science; distribution; diversity; public participation in scientific research; urban ecosystems. Received  13 November 2013; revised 7 March 2014; accepted 10 March 2014; final version received 29 April 2014; published  7 July 2014. Corresponding Editor: C. D’Avanzo. Copyright:    2014 Lucky et al. This is an open-access article distributed under the terms of the Creative CommonsAttribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided thesrcinal author and source are credited.    E-mail: v  1  July 2014  v  Volume 5(7)  v  Article 78  I NTRODUCTION Although historically underappreciated rela-tive to the ecology of protected areas, ecologicaldynamics in cities and other human-dominatedlandscapes are likely to influence populations,communities and ecosystem processes acrossentire landscapes. Humans are integral to thesedynamics, especially those that occur wherepeople live and work. Consequently, we are becoming increasingly aware that engaging non-scientists in the scientific process can not onlyincrease public scientific literacy (Bonney et al.2009, Cronin and Messemer 2013), but alsogenerate scientific data that advance ecologicalknowledge and could exist in no other way (e.g.,Silvertown et al. 2011, Hulcr et al. 2012).Citizen science is broadly defined as anorganized scientific endeavor that includes par-ticipation from professional scientists and thepublic (Dickinson and Bonney 2012). It is deeplyrooted in the historical srcins of science (Miller-Rushing et al. 2012) and has long contributed tothe advancement of ecological theory. For exam-ple, the first analysis of predator-prey cycles byVito Volterra depended on data collected byfishermen (Scudo 1971). More recently, citizenscience has emerged as an increasingly populartool for understanding the structure and dynam-ics of ecological communities over broad spatialranges while educating non-scientists about localecology (Dickinson et al. 2010). Recent techno-logical advances have led to the development of many citizen science programs in ecology,ranging in scope from long-term, broad-scale biodiversity monitoring (e.g., Schmeller et al.2008), to short-term biodiversity surveys of targeted taxonomic groups or ecosystems (e.g.,Hulcr et al. 2012) to the use of applications onmobile telephones to monitor the dynamics of species invasions or plant phenology (Graham etal. 2011).Although citizen science projects often gener-ate large datasets with benefits for professionalscientists and the public (Dickinson and Bonney2012), multiple challenges of the citizen scienceapproach to scientific inquiry have been identi-fied in the recent ecological literature (e.g., Crallet al. 2010, Conrad and Hilchey 2011 andreferences therein). These criticisms fall underthree broad categories. First, organizationalchallenges include lack of public interest incitizen science projects (Conrad and Daoust2008), funding issues (Whitelaw et al. 2003),and limited outreach opportunities which allowprofessional scientists and participants to interact(Milne et al. 2006). Next, data collection issuesare among the most frequently criticized aspectsof citizen scientist projects (Bradshaw 2003,Gouveia et a. 2004, Royle 2004, Conrad 2006,Nerbonne et al. 2008, Fitzpatrick et al. 2009, Crallet al. 2010, 2011, Kremen et al. 2011, Farmer et al.2012). Specifically, controlled studies have dem-onstrated that citizen scientists can have in-creased variability in data collection relative toexperts (Farmer et al. 2012, but see Miller et al.2012), which could lead to an increased likeli-hood of errors. Citizen scientists tend to measureabundances poorly, and abundance estimation isa major source of this among-participant vari-ability (Foster-Smith and Evans 2003). Lack of taxonomic training additionally leads to higherrates of misidentifications, especially at thespecies level, which is often the taxonomic levelof interest (Kremen et al. 2011). Finally, concernshave arisen related to the way that scientists usedata generated by their citizen scientist partners.Data management problems primarily emergewith respect to data accessibility (Crall et al.2010) and a lack of consistent data managementprotocols among researchers (Dickinson et al.2010, Kelling 2012). Furthermore, professionalscientists are often mistrustful of the conclusionsdrawn from citizen scientist-derived data, be-cause researchers have not accounted for the datacollection problems described above (Crall et al.2011). Some of these issues related to data qualityand use have been addressed using data valida-tion (Galloway et al. 2006, Bell 2007, Fitzpatricket al. 2009, Kremen et al. 2011, Bonter and Cooper2012); unfortunately, these error analysis tech-niques are not incorporated into most citizenscience projects (Crall et al. 2010).A final challenge with citizen science relates tothe outcomes for public participants. Benefits forparticipants can vary considerably, even withinthe same project, and no citizen science projectwill perfectly meet the needs of all participants.However, citizen scientist projects should ideallyprovide opportunities for participants to beinvolved in and learn about as many aspects of science as possible. Participants in citizen science LUCKY ET AL. v  2  July 2014  v  Volume 5(7)  v  Article 78  projects are particularly well poised to begin bylearning existing knowledge and then to joinscientists in making new discoveries.With these challenges in mind, we developedand implemented the School of Ants (SoA)citizen science project, in which participantssample ants in their backyards and sidewalks.The motivations for this project were twofold: (1)we wanted to increase scientific knowledgeabout the diversity and distribution of ants acrossa broad spatial range, and (2) we wanted toprovide opportunities for the general public tolearn about and participate in understanding theecology where people live and work. Ants arewidespread and diverse (Dunn et al. 2007),commonly associate with humans and theirstructures (Klotz et al. 1995, Menke et al. 2011),and are an ecologically important group acrossvarious spatial scales and multiple habitat types(Folgarait 1998, Dosta´l et al. 2005), making themideal focal organisms to meet both of these goals.Here, we first detail our methods with aparticular focus on the challenges of data qualityin citizen science projects. Next, we describe theresults to date in terms of (1) the diversity anddistribution of the ants most commonly collected by SoA participants; (2) collaborations withformal educators and international scientistswho used SoA as a vehicle for collaborativelearning; and (3) the development of outreachmaterials, paying particular attention to thecreation of   ‘ Dr. Eleanor ’ s Book of CommonAnts ’ —an accessible and interactive guide forgeneral audiences about the ants most frequentlycollected by SoA participants. M ETHODS Protocol  Data collection .—We provided step-by-stepinstructions on our website. To follow the SoAprotocol, participants placed cookie pieces onindex cards in two different habitat types: (1) agreen space, defined as a vegetated area, such asa lawn, garden or forest; and (2) a nearby pavedspace, defined as an impervious surface, such asasphalt, concrete or cobblestones. Within eachhabitat type, n  ¼  4 stations were placed within ; 30.5 cm of one another. Each bait stationconsisted of one quarter of a Pecan Sandiescookie (Kellogg, Battle Creek, Michigan, USA),placed on a white card ( ; 8  3  13 cm) labeled ‘ green ’  or  ‘ paved ’ . Pecan Sandies have beencommonly used in ant ecology since the early1990s (e.g., Human and Gordon 1996), becausethey contain protein, carbohydrates and lipids,thus providing an attractive food source tomultiple ants. After one hour, participants placedcards, cookies and any ants attracted to the baitsinto individual labeled plastic bags and then putthe bags in a freezer ( sites/default/files/soa-images/dyi_ant_kit.pdf). Data entry .—Participants were guided in datacollection by a table provided on the protocolsheet. Citizen scientists entered data into onlineforms on the SoA website ( to register as an official partic-ipant of the SoA project. Data included (1) thespecific location where baiting occurred; (2)habitat characteristics of green and paved spaces;and (3) abiotic conditions during baiting trials.After data entry was completed, the participantwas assigned a unique confirmation code thatserved as a reference number for the sample. Sample submission .—Participants submittedsamples by mailing completed collections to aregional SoA processing center (currently, there isone at North Carolina State University andanother at the University of Florida, housed inthe labs of project PIs). The associated confirma-tion code linking collection data to the sampleaccompanied each submitted sample. Sample processing .—Teams of trained under-graduate students (see below) and laboratoryassistants received the samples at regionalprocessing centers. Depending on the volume of incoming samples, processing teams included 1lab manager and 1–4 trained undergraduatestudents. The processing teams isolated antsfrom debris and cookie crumbs and sorted antsto morphospecies. Green samples were pooled,as were paved samples; within each habitat xsample combination, one specimen from eachunique morphospecies was point-mounted andlabeled with collection data and a unique barcode. All other ants were stored in 95 % ethanol. Ethanol-preserved samples were storedin the permanent collections of each regionalprocessing center. During the initial phase of theproject (when sample volume was high, July2011–September 2012) this resulted in 40–60person hours per week. Later, fewer samples LUCKY ET AL. v  3  July 2014  v  Volume 5(7)  v  Article 78  resulted in a reduction to 20–30 person hours perweek in the summer and 8–10 hours per week inthe winter.Point-mounted specimens were sent to region-al ant taxonomic experts, who we subcontractedto provide or confirm ant identifications at thespecies level. These taxonomic experts enteredspecies determinations directly into the onlinedatabase. The specimens were then returned toregional processing centers for permanent stor-age alongside ethanol-preserved specimens. Data retrieval by participants .—Once identifica-tions were entered into the database, collectionsites and species names appeared on our onlineinteractive  ‘ Ant Map ’  ( Data management  We build the SoA website on a backbone of aPHP MySQL database in a Drupal environment.The specimen-level database was informed byDarwin Core standards ( index.htm) to ensure the integrity and broadutility of ant distribution data. The taxonomicframework of the project was imported fromAntweb (; August 2011), but maintained the flexibility to note nomencla-tural changes or uncertainties in species identifi-cations. Validating ant collections by citizen scientists It is very common for trained undergraduatesto collect samples that are used in publishedecological papers. For studies of insects-such asants-this training includes basic field and labo-ratory identification skills and field samplingtechniques specific to insects. Our samplingprotocol is simple, and the technical identifica-tion skills are needed after participants mail theirsamples to processing centers. However, partic-ipants still set out cookie baits and collect antsusing only the information provided on ourwebsite. We examined the error associated withusing untrained participants using a groundtruthing trial. The SoA ground truthing trialwas conducted on the campus of North CarolinaState University (Raleigh, NC). Two groupscollected data: (1)  ‘ untrained participants ’  (un-dergraduate students in an Ecology course), whoused only the information provided on the SoAwebsite to collect ants using the SoA protocol;and (2)  ‘ trained participants ’  , undergraduatemembers of the SoA team from Dr. Rob Dunn ’ slaboratory group. Importantly, both groups weresampled from the same population (NCSUundergraduates). Both groups used identicalmethods and collected ants from the same sitesfrom 15 April to 9 May 2013. We compared thenumber of ant species collected by trained anduntrained participants, and used a Spearmancorrelation of rarefied species accumulations foreach group to examine how these results wererelated to trained or untrained status. We usedPrimer-E v.6 to perform rarefied species accumu-lation analyses and SAS v.9.3 to conduct Spear-man correlations. Public outreach We used multiple approaches to provideopportunities for the public to learn about theSoA project. First, we frequently developedoutreach materials for formal public outreachevents (Appendix: Table A1), including: bro-chures describing the SoA project,  ‘ trading cards ’ for common ants, a pictorial dichotomous key forthe most common ants collected by SoA partic-ipants, Dr. Eleanor ’ s Book of Common Ants (Box1, Fig. 1; Spicer Rice 2013) and a short video onthe SoA website showing children using the SoAprotocol to sample ants ( ¼ gMg55LTJ6gQ). We also formedpartnerships with teachers to develop curriculum based upon SoA (Box 2, Figs. 2 and 3). Finally, wecollaborated with scientists in Parma, Italy todevelop an international SoA module (Box 3, Fig.4). R  ESULTS Citizen science participation in the SoA Project  Description of participants .—Between 13 July2011 (when the website was published online)and 2 May 2013, there were 35,994 total visits tothe SoA website (Fig. 5). Most visits were frompeople in the United States (84.9 % ). The mostcommon US region of origin was the SouthAtlantic, with 9,832 (33.1 % ) total visits (Fig. 5a).Additionally, the website has been accessed from132 different countries. There were also 1,170visits from other North American countries (Fig.5b), especially Canada (73.5 %  of NA visitsoutside the USA). Finally, there were  . 5,000 LUCKY ET AL. v  4  July 2014  v  Volume 5(7)  v  Article 78  visits from people outside North America (Fig.5c).From July 2011 to December 2012, we logged814 total kits. Of these, 599 kits (74 % ) from 500unique sites (Fig. 6) were usable and wereincluded in the dataset described below. Duringregistration, we surveyed participants about howthey found out about the SoA project. Approx-imate 55 %  of Project participants answered; of those, most respondents found out about SoAfrom media coverage (including traditional me-dia, social media, and blog posts) of the project,the SoA website, or a school network (e.g., alistserv for parents; Fig. 7). The cities with thegreatest number of samples were Chicago, IL(149 samples), Raleigh, NC (143 samples) andNew York City, NY (34 samples). Data validation: Results from ground truthing  To address concerns in the literature about theaccuracy of untrained vs. trained workers incollecting ants, we conducted ground truthingtrials which showed that the collections of untrained and trained collectors were highlycorrelated (Fig. 8; Spearman correlation:  P  , 0.0001, r 2 ¼ 0.9376).  Assessment of the diversity and distributionof the ants most commonly collected by our citizen science partners  Ant diversity .—We detected a wide range of antspecies across North America using the SoAprotocol. Across 500 sites (Fig. 6), we found 7exotic ant species and 107 native ant species.While we do not appear to be encountering newexotic species (Fig. 9), rarefaction curves indicatethat additional sampling will continue to en-counter more native species, even given the Fig. 1. Cover of the interactive iBook based upon themost commonly collected ants from the SoA project. Box 1Backyard ecology for the masses:Dr. Eleanor ’ s Book of Common Ants How do we get people excited about theecology of species living in their own backyards? One approach is to give thepublic opportunities to collect and observespecies through citizen science projects. Weemployed this approach through the SoAproject. The next step towards achievingthis goal was to provide people withinformation about the natural history of the species that they collected through theSoA project. Therefore, we contracted aprofessional science writer to composevignettes about the ants most commonlycollected for the SoA project-those ants thatpeople were most likely to interact with inthe course of their daily lives.The book is titled Dr. Eleanor ’ s Book of Common Ants (Fig. 1) and is available freeonline as an interactive iBook (https:// ¼ 11). Fea-tures of the iBook include photographs,distribution maps (based upon SoA collec-tions and literature accounts) and naturalhistory stories about each featured species.There are also interactive features, whichinclude a photo gallery, short videos, andlinks to the global SoA map and a glossary.The flexibility of this format allows us toupdate the iBook as more data accumulatethrough the SoA project. For example, newversions are currently being developed thatfocus on the ants of New York City, Chicagoand North Carolina, respectively. This bookwill help (we hope) direct participantstoward particular questions about ants thatthey might study on their own in additionto those questions which we, as scientists,frame. LUCKY ET AL. v  5  July 2014  v  Volume 5(7)  v  Article 78
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