Validating mammal monitoring methods and assessing theperformance of volunteers in wildlife conservation—‘‘Sed quis

custodiet ipsos custodies ?’’§

Chris Newman*, Christina D. Buesching, David W. Macdonald

Wildlife Conservation Research Unit, Department of Zoology, University of Oxford, South Parks Road, Oxford OX1 3PS, UK

Received 28 August 2002; received in revised form 16 October 2002; accepted 16 October 2002

Abstract

Many conservation organisations rely heavily on volunteers, and the government often relies on them to achieve tasks for whichfunding is insufficient—for example, the monitoring of trends in biodiversity on a national scale. Thus, it is critical to deploy non-professionals effectively. In this study we validated and calibrated the data collected by 155 volunteers, assisting with mammal

monitoring at Wytham Woods, Oxfordshire, between April 2000 and December 2001. Tasks included small mammal trapping andhandling, surveying and censusing for badgers, estimating deer population sizes from dropping counts, and transect surveys formammal field signs. We analysed the effects of age, gender, previous experience, physical fitness and aptitude on volunteer perfor-

mance using quantitative measures and qualitative scores. We found that (1) techniques that could be taught to volunteers withoutlengthy or specialist training were sufficiently accurate to yield reliable data, (2) with approximately half a day of training in eachtask, volunteers could produce reliable data, verified by professionals, and (3) volunteer teams brought considerable time savings tomany tasks, compared with a single professional researcher. Our analyses show that physical fitness was a significant predictor of a

volunteer’s ability to perform tasks well and, in our particular sample, a male-bias in volunteer aptitude was apparent in sometasks. Previous experience as a conservation volunteer did not enhance performance over that of novices nor did age have any effecton volunteers’ ability. The overall veracity of volunteer data compared well with data collected using more specialist methods or

collected by professional researchers using the same method. Volunteers required more time per task and, while they showed atendency to underestimate population sizes, their results were consistent. Additionally, the programme helped to raise the envir-onmental awareness of volunteers and their understanding of woodland ecology.

# 2003 Elsevier Science Ltd. All rights reserved.

Keywords: Earthwatch; Volunteers; Monitoring; Calibration; Validation

1. Introduction

Whether species are imperiled or pestilential, effectivemanagement measures for conservation or control relyupon accurate records of their distributions and trendsin abundance. Monitoring long-term trends in a species’status may also reveal which factors are responsible forthe changes observed (e.g. Bright and Morris, 1990;Barreto et al., 1998; Krebs et al., 1997; Macdonald and

Newman, 2002). In Britain the ecological importance ofmonitoring is reflected in national and internationallegal obligations to do so (e.g. under the Convention onBiological Diversity). However, responsibility forundertaking mammal monitoring has largely fallen onthe voluntary sector, and despite a recent governmentinitiative to provide core-funding for a ‘Mammal Sur-veillance and Monitoring Network’, this seems likely tocontinue (Macdonald and Tattersall, 2002). Many Brit-ish organisations that conserve or study mammals relyheavily upon volunteers (e.g. The Mammal Society,National Federation of Badger Groups, Wildlife Trusts,British Deer Society, Bat Conservation Trust), andvolunteers have contributed to various national cen-suses of British mammals (e.g. badgers Meles meles:

0006-3207/03/$ - see front matter # 2003 Elsevier Science Ltd. All rights reserved.

doi:10.1016/S0006-3207(02)00374-9

Biological Conservation 113 (2003) 189–197

www.elsevier.com/locate/biocon

§ Juvenal’s Satires—loosely translated as ‘but who will monitor the

monitors?’

* Corresponding author. Tel.: +44-1865-881297; fax: +44-1865-

310447.

E-mail address: chris.newman@zoology.ox.ac.uk (C. Newman).

Wilson et al., 1997; dormice Muscardinus avellanarius:Bright et al., 1996, deer: Johnson, 2001; bats: Walsh etal., 2001). Although in Britain and around the worldmany studies rely on some measure of volunteer work, itis unusual for this to be detailed in the ‘Methods’ sec-tions of publications (exceptions would be, e.g. Readinget al. 1994, 1996; Saunders, 2002), and even rarer toread of attempts to calibrate or validate their effective-ness. The issues surrounding the use of volunteers werebrought into sharp focus when, in 1993, an amendmentwas made to prohibit the US National Biological Sur-vey from accepting the services of volunteers. This wassupported by two arguments in the House of Repre-sentatives asserting that volunteers are incompetent andthat they are biased. The British Trust for Ornithology(BTO), the non-governmental organisation (NGO) tohave enjoyed greater success with volunteers than anyother, rebutted this view and concluded ‘‘Trust thevolunteers’’ (Greenwood, 1994). Here, we begin toaddress some of these issues for British mammals.A 1998 report to the British government on mammalmonitoring prioritised the integration of volunteers intothe work of professional scientists to undertake statisti-cally robust surveys (Macdonald et al., 1998), a viewendorsed in Toms et al. (1999) and Macdonald andTattersall (2002). The advantages of using volunteers inwildlife conservation are clear (Toms et al., 1999): mostobviously, they provide an inexpensive and potentiallylarge labour force, the volunteers themselves gain fulfil-ment and knowledge, and local involvement contributesto Government Agenda 21 targets. However, there aredisadvantages as well.The complexity of some scientific methods used byprofessional researchers to monitor mammalian popu-lations (e.g. DNA identification of carnivore scats:Davison et al., 2002; fixed-wing aircraft photographicsurveys for grey seals: Hiby et al., 1988) renders themunsuitable for wide scale volunteer use. Simpler alter-natives may be available, but unless these survey meth-ods can provide meaningful results, of sufficientstatistical power (Gibbs, 1996), volunteers’ efforts willhave been wasted. Long hours of arduous or repetitivework may also be problematic, and given the time andeffort involved in recruiting and training volunteers, itdoes not necessarily follow that their involvement insurveying is cost-effective.It is important, therefore, to identify methods that areboth useful for mammal monitoring and suitable forvolunteers, and to evaluate quantitatively the abilities ofvolunteers compared to professional biologists, and thefactors affecting their competence (see Langbein et al.,1999, National Hare Survey). Macdonald et al. (1998)presented a case study illustrating how volunteer effec-tiveness in surveying for water voles benefited con-siderably from a heavy investment in training, feedbackand professional supervision.

To tackle these issues, and to develop methodologiesfor volunteer data validation, we set up a mammalmonitoring project, assisted by volunteers, at WythamWoods, Oxfordshire, in April 2000. Wytham is the siteof a suite of ongoing long-term studies of residentmammal populations (e.g. badgers: Macdonald andNewman, 2002; small mammals: Flowerdew and Ell-wood, 2001; deer: Morecroft et al., 2001), against whichto validate data collected by volunteers.Here, we report on a series of validation studies fromWytham. We describe the deployment of volunteers tomonitor small mammals, badgers and deer, and com-pare data collected by volunteers with data collected byprofessional research biologists. We then briefly assessthe effectiveness of the volunteers, as perceived by thescientists running the monitoring programme, and howthis was affected by characteristics such as their age,fitness and gender.

2. Methods

2.1. Site

Wytham Woods are located 5 km northwest ofOxford (OS Ref: SP 462, 080). The woods are posi-tioned on two eastern outlying hills of the Cotswoldescarpment, between 60 and 165 m altitude. The wood-land and associated copses constitute 424 ha of mainlymixed-species semi-natural, deciduous woodland, sur-rounded by permanent pasture and mixed arable farm-land (Macdonald and Newman, 2002). The woodlandedge is delimited by a 2 m high deer fence to preventdeer from leaving the woods and causing damage to thesurrounding fields.

2.2. The volunteers

Volunteers were recruited by the Earthwatch InstituteEurope (www.earthwatch.org) (Gilmour and Saunders,1995). All age classes were represented and there was aslight female bias (Fig. 1).

Fig. 1. Age and gender profiles of volunteer sub-sets used in qualita-

tive assessment.

190 C. Newman et al. / Biological Conservation 113 (2003) 189–197

The Earthwatch Institute arranges for its recruits toparticipate in field research, in our case, at a cost of£150 per 5 days (including meals, but excluding accom-modation). Our sample is thus representative of thatsection of the public from inside (n=149) and outside(n=6) Britain attracted to this particular form ofvoluntary conservation work. Although they pay for theopportunity to join a project, Earthwatch recruits areconsidered to be ‘volunteers’ on the project they join.However, one quarter of our volunteers (36 out of 155)joined the project by means of taking up one of thesponsored places provided by Earthwatch. Volunteerscame from various social and educational back-grounds: students, professionals, retired, probationservices and drugs rehabilitation programmes. Somehad considerable background knowledge in biology(e.g. amateur naturalists, veterinarians, biology stu-dents and teachers), while others were on sponsoredplacements or embarking upon a new interest in wild-life conservation.Typically, volunteers were picked up from their over-night accommodation at 9.00 am, brought to the studysite (arrival ca. 9.30 am), and dropped back to theiraccommodation at ca. 10.30 pm, with a 60 min lunch-break and a 90 min dinner-break.Here we report on data from 155 volunteers whoassisted with mammal monitoring tasks at WythamWoods, Oxfordshire, UK: 96 volunteers in 2000 (splitbetween eight teams from April to December), and 59volunteers in 2001 (split between seven teams fromApril to December—during this period restrictions dueto foot and mouth disease affected recruitment). Eachteam spent 5 days assisting in the field.

2.3. Small mammal trapping

Small mammals (wood mice Apodemus sylvaticus,bank voles Clethrionomys glaerolus, and field volesMicrotus agrestis) were censused repeatedly at threedifferent woodland sites by standard capture–mark–recapture methods using Longworth live-trap grids(Gurnell and Flowerdew, 1990). Volunteers wereresponsible for preparing the traps (i.e. assembly,adjustment, provisioning with hay and baiting withseeds and apple pieces), setting the traps at 10 m inter-vals (i.e. laying out the grids and correctly positioningthe traps at suitable sites), checking the traps twicedaily, handling captured animals (i.e. taking rodents outof the traps, sexing, weighing and fur-clip-markingindividuals) and recording the data on pre-designedrecording sheets. For each grid we measured the totallength of time needed by the volunteer teams (12volunteers per team) to lay-out the grid and assembleand position all 100 traps in the field and comparedthese times with the time needed by one professionalresearcher. Practical training and explanation were

given until volunteers were demonstratively proficient atthe task (i.e. correct setting of traps, correct animal-welfare-friendly handling, accurate data collection andrecording). Though the time this took varied, it wasessential to ensure that the welfare of trapped ani-mals was not compromised. During all these activ-ities, experienced researchers continuously supervisedthe volunteers and ensured the accuracy of the datarecorded. During the trap-assembling period weobserved the work of all volunteers and counted thenumber of times we had to show each individualvolunteer how to carry out the task correctly. Datawere then compared between the three different trap-ping grids and were also compared with our long-term data set derived from trapping grids in com-parable habitats/locations (Flowerdew and Ellwood,2001).

2.4. Surveying deer

Deer numbers (fallow Dama dama, roe Capreoluscapreolus, muntjac Muntiacus reevsi) were estimatedfrom standing crop faecal counts in 10�10 m quadrats(Mayle et al., 1999). Volunteers were responsible forlaying out the quadrats and surveying the area fordroppings. They were asked to identify the species pro-ducing the droppings, but in this case their identificationwas always verified by an experienced researcher (fordetailed analysis of identifying skills of volunteers seelater). For each plot we measured the time it took forvolunteer teams (six volunteers per team) to stake outand survey the quadrat for droppings and comparedthese times with the time needed by one professionalresearcher. Data were then compared to estimates from(semi-) professional and certified deer-stalkers from theBritish Deer Society, derived from visual counts, and todropping count data collected by researchers workingfull-time on deer at Wytham.We also performed an experiment to test the surveymethod itself. We asked what proportion of droppingspresent in a quadrat is likely to be found? 10�10 mquadrats were cleared of droppings by the teams andthen naturalistic piles (2–10) of droppings, mimicking anatural distribution and representing a range of deerand lagomorph species, were introduced to the plot bythe researchers, unseen by the volunteers. Volunteers(with no experience) and experienced researchers thensearched the plots for the known number of introduceddroppings. The experimental survey was then repeatedtwice (redistributing the droppings between trials) usingthe same volunteers after they had had, successively,(1) half a day and (2) two half days of surveyingexperience. Deer dropping-identification skills ofvolunteers were analysed on day 2 (half a day fieldtraining) and day 3 (two half days field training) of thisexperiment.

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2.5. Surveying badgers

Badger activity was monitored through bait-markingsurveys (Delahay et al., 2001), sett surveys (Clements etal., 1988) and direct counts of badgers at setts.Volunteers were required to find latrines (bait-mark-ing survey) or setts (sett surveys) while using compassesand maps of the study area (scale: 1:3000) to guide theirown movements and to plot the field signs they found.The volunteers were allocated to groups randomly andtwo training regimes were tested in the latrine survey:one group received only written material about thecharacteristics and positioning of badger latrines, whilethe other group was given a 1 h training session in thefield with practical demonstration. Latrine and settlocations were verified by an experienced researcher andcompared to our bi-annual bait-marking surveys(Johnson et al., 2001).During badger counts, groups of three volunteerswere positioned at different badger setts, and were askedto count the maximum number of badgers seen simul-taneously (thus avoiding multiple counts of the sameindividual) at the sett over the course of one evening. Aprofessional scientist was present to verify the volun-teers’ counts. Data were then compared within thevolunteer groups and to results from our long-termcapture–mark–recapture studies (Macdonald and New-man, 2002).

2.6. Multi-species winter transects

Winter (December) transects were used to assessmammalian species diversity and results were comparedto the established Wytham Woods species list (Macdo-nald and Stafford, 1997). Volunteers received half a daytraining on the identification of mammal field signsduring a guided walk through the woods. They werethen split into three sub-teams of four and were asked towalk along one of three different 1.5 km long transects,marked on a detailed map of the study site (scale1:3000). All field signs of mammals had to be marked onthe map and the species indicated were identified usingstandard field guides (e.g. Strachan, 1995). Each trans-ect was surveyed twice by two different teams.

2.7. Evaluation of volunteers

In 2001, we additionally assessed volunteers at theindividual level on a 0–5 subjective scale of their abilityfor each of the different tasks listed above. Volunteerswere assessed by one male and one female supervisingscientist (CN and CDB) and the resulting scores werethen averaged for each task. On this scale a professionalbiologist working with this method would be consideredto score 5/5. These assessment scores also included theirability to understand the principles of the task, to execute

the task correctly and efficiently, and their ability towork reliably without supervision. Additionally, a sub-jective score was given for attention to information, fit-ness (scored from 0=lacking the physical stamina tocarry out five days of light fieldwork, to 5=comfortablyable), and mental aptitude (defined as enthusiasm forthe work). Though all volunteers were informedbeforehand of the general principles of the assessmentstudy, they were not told any details of the assessmentthat was being made until the conclusion of the teamvisit, and were not aware of the scoring criteria. There-fore, they were not likely to alter their behaviour in anysystematic way. Additional quantitative measures wereincorporated into the scoring where possible, such astheir ability to survey for deer droppings in the artifi-cially stocked quadrats described above. To eliminatethe possibility that the unfamiliar search image ‘‘deerdroppings’’ would lead to an under-representation ofsearch results due to seeing, but not identifying drop-ping piles correctly, we performed the experiment fortwo teams by substituting the droppings with one-penny-coins (UK) (which are of similar size and colour).All ‘per task’ assessment scores were then combinedto create overall mean scores, which indicated theresearchers’ perception of the volunteers’ usefulness. Asecond similar measure, defined as volunteer capacity,was made to include the assessment scores of eachvolunteer’s physical and mental aptitude.To explore which factors affected volunteer perfor-mance for each task, we employed a preliminary analy-sis of co-variance (ANCOVA) including the predictorvariables gender (male/female), age (dichotomised tounder/over 40 years of age), training (novice/instructed)previous experience of conservation work before comingto Wytham (yes/no), a measure of observed physicalaptitude (i.e. fitness) for the tasks (0–5), and mentalaptitude (0–5). To analyse indicative results in moredetail, Mann–Whitney U tests and Kruskal–Wallis testswere used where applicable. All statistical analyses wereperformed using Minitab (Release 11.21).

3. Results

3.1. Small mammal trapping

After basic training (i.e. verbal explanation and 10min of practical demonstration/supervision) volunteerswere able to operate Longworth traps following the stan-dard research method employed by professional biolo-gists. The most difficult part for the volunteers proved tobe the correct assembly of the Longworth traps: 50% ofthe volunteers were able to set the traps correctly after onedemonstration, 81% after two demonstrations, 98% afterthree demonstration, whereas three volunteers needed upto seven repeated demonstrations.

192 C. Newman et al. / Biological Conservation 113 (2003) 189–197

Time-savings due to the deployment of a team ofvolunteers were substantial. Whereas one experiencedresearcher would need ca. 2.5 h to set up one of oursmall mammal trapping grids (meanresearcher 150 min,S.D. 65 min; n=3), volunteer teams finished within 1 h(meanvolunteer team 50 min, S.D. 14 min, n=3) (ANOVA,F1, 5=14.58; P=0.007). To check 100 traps in the field,one experienced researcher needed approx. 1.5 h(meanresearcher 93 min, S.D. 42 min, n=3), whereasvolunteer teams finished within 45 min (meanvolunteerteam 42 min, S.D. 8 min, n=3; ANOVA:F1, 5=9.71;P=0.017). However, inexperienced volunteers tookindividually substantially longer to handle (weigh, sexand clip-mark) captured animals than experiencedresearchers (meanresearcher 65s, s.d. 17s; TWO research-ers, 20 animals); (meanvolunteer 222s, S.D. 76 s; 50volunteers; 120 animals) (ANOVA, F1,7=11.79;P=0.011). While volunteers were closely supervised,this was only to ensure animal welfare standards andnot intended to increase volunteer performance.The volunteers’ results were comparable with smallrodent numbers obtained by our long-term capture-mark-recapture study (Flowerdew and Ellwood, 2001),i.e over 10 sample grids the volunteer average was 13.2(S.D.=6.1) while the average obtained by professionalswas 14.2 (S.D.=7.9) in similar habitats in the sameyear/time period.After the initial training period all volunteers were ableto reliably recognise bank voles, field voles and woodmice (after two animals of each species: 8 out of 10 right,n=120), weight (after one demonstration of weighing: 10out of 10 right, n=120) and sex (after two examples ofmales and females: 7 out of 10 right, n=120).

3.2. Surveying deer

From April to December 2000, 124 quadrats weresurveyed. The time needed to survey one quadratdecreased in proportion to the number of peopleinvolved. Whereas one experienced researcher neededon average 10.3 min, S.D. 2.4 min (n=20), a team offive volunteers finished on average within 2.1 min, S.D.0.3 min (n=79). Confidence in the volunteers’ ability tocorrectly identify deer droppings to species was derivedfrom specific testing of their ability (see later).In 2000, after combining the results from all surveyedquadrats, the population estimates produced by volun-teers using this method (129 fallow, 65 roe, sevenmuntjac) compared well with visual estimates of deerabundance estimated by (semi-) professional stalkersfrom the British Deer Society (100 fallow, 40 roe, munt-jac unknown). Similarly, between April and December2001, 177 quadrats were surveyed. The estimates pro-duced were for 73 fallow, 31 roe and six muntjac. Thesenumbers are consistent with the British Deer Societyestimates for 2001 (75 fallow, 35 roe, muntjac unknown).

For fallow deer the difference between the numbers esti-mated from volunteer dropping counts in 2000 and 2001reflects accurately the absolute numbers of deer shotduring the interceding winter (70 fallow).Volunteers found on average 71% (S.D.=22%) ofthe droppings piles in the artificially stocked plots. Bycomparison, professional scientists performing the sametest found consistently 74% (S.D.=12%) of the drop-pings piles. Volunteer performance declined with timefrom 75% on day 1 (no experience) to 67% by day 3.Volunteer ability to correctly identify deer droppingsto species increased with field training. Whereas afterhalf a day of field experience volunteers mis-identified19.2% (S.D. 29.6, n=72) of the droppings, this numberdropped to 6.9% (S.D. 16.5, n=72) after two half daysof field experience.

3.3. Badger surveys

Over 63 observation evenings between May and Sep-tember in both years at 10 different setts, direct countsby volunteers consistently returned 64.2%(S.D.=14.16) of the number of badgers known to beresident at these setts from long-term trapping records(Macdonald and Newman, 2002; meanAdult=62.6%,S.D.=13.2; meanCub=64.7%, S.D.=15.4). In the caseswhere professional scientists were in attendance at thesetts to verify results (n=28) their counts did not differsignificantly (Wilcoxon matched pairs test, P>0.05).After basic instruction in standard surveying techni-ques, to the level where all volunteers were able to readmaps, navigate by compass and recognise the relevantfield signs reliably, volunteer teams took on averagethree times longer to survey an area for badger setts andoutliers compared with an experienced researcher(ANOVA: F1, 25=102.57, P<0.001, nvolunteer-teams=8,nresearchers=2) based on 25 h of surveying. By surveyingan area systematically (i.e. walking 20 transects across100�100 m quadrats), the teams found 90% of mainbadger setts, known to be there. However, they foundonly 67% of smaller outliers, located by experiencedresearchers.Volunteers who were given only written instructionsabout surveying and identifying badger latrines provedsignificantly less successful than those given demonstrationin the field (ANOVA: F1,7=16.33 P<0.01), so much sothat the experiment had to be terminated prematurely afterthe first day, because lack of success was proving frustrat-ing to the teams given only paper instruction. However,volunteers, who received practical field-training foundonly 56% of the latrines located by research scientists.

3.4. Multi-species winter transects

Fifteenmammal species were known to be present in thewood. Volunteers using this method found a maximum of

C. Newman et al. / Biological Conservation 113 (2003) 189–197 193

11 species (n=8; mean=9.12; S.D.=0.52) (Fig. 2),while under similar conditions, over 12 surveys, profes-sionals found a maximum of 12 species (n=8;mean=10.5; S.D.=0.93). Thus, professionals foundsignificantly more species, from field-signs and sight-ings, than did volunteers (ANOVA: F1,15=5.07;P<0.05). Some species, such as the badger, were detec-ted on all of the six transects performed, while otherspecies (e.g. stoats: Mustela ermina, weasels: Mustelanivalis) were never detected. Mostly, species presencewas inferred from droppings and/or footprints, but ani-mal burrows (e.g. badgers, foxes Vulpes vulpes), feedingremains (grey squirrels Sciurus carolinensis, smallrodents) and mole-hills (Talpa europa) also providedevidence for various species. The only species for whichdirect visual observations were made were fallow deer,grey squirrel and brown hare Lepus europaeus.

3.5. Assessment of volunteers

The preliminary ANCOVA standardising for inter-dependence of the measured individual-specific para-meters, revealed that gender, training, previous experience,and fitness had significant effects on volunteer suitabilityfor several different tasks, whereas age and mental apti-tude had no influence on volunteer performance.More detailed analyses revealed that gender had astrong effect on volunteer ability to find deer droppingsin the experimental quadrats (Mann–Whitney U test:n1=17, n2=27, P<0.001) and attention to information(Mann–Whitney U test: n1=26, n2=31, P<0.001) withmen performing significantly better than women. Thus,the overall median ability scores of men as volunteerson this project were marginally greater than those ofwomen (Mann–Whitney U test: n1=26, n2=31,P<0.05). The variance in the median scores (median-

men=3.2, S.D.=0.7, medianwomen=2.7, S.D.=0.77) was con-sistently higher in women than it was in men (ANOVA:F1,58=4.59, P<0.05), indeed our highest and our lowestscoring volunteers were both female.

Field-training of 1 day (i.e. handling 2–4 mice) sig-nificantly increased volunteer ability to handle smallmammals (Mann–Whitney U test: n1=20, n2=24,P<0.01).Previous experience did not benefit volunteers successrate at finding deer droppings (or one-penny-coins) inthe experimental quadrats compared to novice volun-teers (Mann–Whitney U test: n1=20, n2=24, P<0.05).No difference in relative success rates was found(Mann–Whitney U test: n1=24, n2=24, P>0.05).However, experienced volunteers took significantly lesstime to carry out the survey (Chi-Square test: w22=9.64,n1=20, n2=24, P<0.01). Volunteers with a previousinterest in conservation biology paid significantly moreattention to background information than did novices(Mann–Whitney U test: n1=20, n2=24, P<0.05).Overall, fitness had a significant influence on the meanperceived usefulness (Kruskal–Wallis test: H4, 56:11.82,P<0.02) and capacity (Kruskal–Wallis test: H4,56:14.20, P<0.01) of volunteers, with fitter people beingperceived by the researchers to be better suited to thetasks than less fit people.

4. Discussion

In the particular circumstances of our study, with thevariety of volunteers we tested, volunteers averaged anability score of 2.9 out of 5.0, S.D.=0.8 (=58.8%;max.=84%, min.=23.2%). This variability in perfor-mance between volunteers, moderated by gender, pre-vious experience and fitness, is important. Thedemographics of team compositions will differ, and thustraining and instruction must be adaptable and providesufficient guidance to yield worthwhile results.Volunteer teams allow numerous sites to be surveyedsimultaneously (e.g. the spring red deer census onExmoor: Langbein, 1997); they can cover a large geo-graphical area (e.g. the national hare and badger sur-veys: Hutchings and Harris, 1996; Wilson et al., 1997);they can save time (e.g. deer dropping survey: thisstudy; Toms et al., 1999). Conversely, there are tasksthat are sufficiently technical, arduous or prolonged thatthey may be unsuitable for certain types of volunteers[e.g. procedures licensed under the Animals (ScientificProcedures) Act, 1986]. Additionally, a pragmatic rea-son for using volunteers is that they are increasinglywilling to pay to be involved in environmental science,unlocking new revenue for conservation, a further tan-gential benefit to this project.There are also more intangible benefits to usingvolunteers in monitoring. For example, in contrast tovolunteering on ‘tasks’ such as dry-stone walling orpond-dredging (all of which have their own associatedphysical and vocational training benefits), beinginvolved with mammal monitoring or other research

Fig. 2. Mammals detected by volunteers on ca.1.5 km transects

inspected for field signs: Mean of six transects.

194 C. Newman et al. / Biological Conservation 113 (2003) 189–197

projects enables a wider public to gain an understandingof science. This contributes to the UK government’sbroader concerns over the public’s ability to understandscientific debate, a concern that is reflected by govern-ments internationally.Due to the labour-intensive nature of biological field-work, many scientific studies now rely on the help ofnon-professional volunteers (e.g. water quality survey ofthe US Environmental Protection Agency: www.epa.-gov; the North American amphibian program:www.np2-pwrc.gov; Canada’s wildlife watcher pro-gram: www.on.ec.gc.ca; Texas parks and wildlifevolunteer monitoring program: www.tpwd.state.tx.us/nature; the British Trust for Ornithology’s garden birdwatch survey: www.bto.org/gbw). So far, few studieshave investigated how reliable data collected by ama-teurs are (e.g. Walsh and Harris, 1996). Our study isintended to start bridging this gap in knowledge and tooutline a general approach that would ideally need to becustomised to the requirements and circumstances ofparticular studies.We examined the use of volunteers to monitor threevery different types of mammal: small rodents, badgersand deer. The ecological specifics of the monitoring studyare not the focus of this analysis, rather the finding thatwith appropriate training, volunteers were able to per-form tasks reliably and accurately, is of significance.

4.1. Training

It is important to emphasise that for all monitoringtechniques used in this study, practical field-training anddemonstrations proved to be essential. Without thistraining, volunteers were generally unable to performthe required tasks (even when supplied with writteninstructions). Training had a significant influence onsmall mammal trapping, both in terms of per capitaefficiency and handling ability. A team of 8–12 novicevolunteers given basic instruction (to ensure welfarestandards) can perform this task reliably and provide asignificant time saving over a single researcher. Thisfinding parallels the results reported by Macdonald andStrachan (quoted in Macdonald and Tattersall, 2002),which revealed that intensive instruction was crucial tothe success of volunteers surveying for water vole fieldsigns.In terms of the amount of training needed versusquality of volunteer data, we found that the basictraining we provided (e.g. half a day per focal species,including background theory, practical demonstration andinitial close supervision of volunteers, as described in themethods), produced results which were within the rangerecorded by people using the respective methods pro-fessionally. Although we supervised volunteers closely,this was a cautionary measure to ensure animal welfare(e.g. in the case of small mammal trapping) and volun-

teer safety during field-work, not to enhance volunteerperformance in a way that might distort our evaluation.Importantly, this training regime represents an econ-omy of scale. While training is time-consuming, manyvolunteers can be trained simultaneously, representing atime-, and cost-effective method for ultimately increas-ing the number of people able to continue to collectscientific data for wildlife conservation, especially if thetrained volunteers are able to make a long-term com-mitment to a wildlife conservation project. For example,had our programme required, our results indicate thathalf a day of training would have produced two volun-teer teams of six people competent to survey the entirewoods for deer droppings with acceptable accuracy tentimes faster than one experienced scientist. In this case,however, we are not taking account of time required forrecruitment and support.

4.2. Calibration and validation

There are two principal questions to address in eval-uating volunteer data collection: are the methods thatcan be used by/taught to volunteers themselves reliably(method calibration); and given that the methods per-form satisfactorily, how do novices compare with pro-fessionals (data validation).When counting deer droppings, badgers at setts orsurveying for badger setts, it seems the methods them-selves that appear to be the limiting factors. The evi-dence of this study shows that as experience builds insurveying for droppings, a degree of nonchalance alsodevelops, and survey times, along with survey accuracydecrease. With supervision to ensure that volunteerssurvey thoroughly and systematically, there is no sig-nificant difference between the ability of volunteers andprofessionals to find droppings; but both underestimatethe actual numbers present using this method. Similarly,provided volunteers are instructed to be still andpatient, their ability to count badgers, which are highlyvisible at their setts at dusk, is not significantly differentfrom that of professionals, but an underestimate whencompared with trapping methods. Surveying for badgersetts is a more difficult technique to calibrate. Systema-tic surveying by amateurs or professionals shouldalways reliably find the obvious multi-hole main settspresent, and our results indicate with half-day of train-ing amateurs found 9/10 setts in Wytham. It wouldappear that when setts get missed, it is generally a failureto be able to read maps accurately, and thus cover ‘‘all’’of the ground in the sample area (individuals variedconsiderably in map reading skills and abilities). Bycontrast, latrines are far smaller features and can bemissed much more readily, especially if the surveyors areinexperienced. Although the professional researchersworking in Wytham have a working knowledge of thelocation of many latrines, it was clear during the field-

C. Newman et al. / Biological Conservation 113 (2003) 189–197 195

training phase of this exercise that they were much bet-ter able to find latrines (including previously unknownones) than were our sample of amateurs.Analysing performance in other tasks revealed that itwas the skill brought to a task by professionals thatcompromised, but did not invalidate, the relative per-formance of the volunteers, rather than any limitationof the technique itself.

4.3. Previous experience and team management

Winter transects indicate that amateurs, with lessexperience of finding field-signs (half-day training),produce lower figures for species diversity than didprofessionals. Again, both groups under-represent thetotal number of species present compared to the knownspecies list (established over years of observation andtrapping). However, volunteers still returned on averageonly one less species than professionals.Volunteers with previous experience (i.e. active mem-bers of local conservation groups or worked in relatedfields such as veterinarians, biology teachers, etc.) didnot always score as highly as their novice (i.e. with noprevious experience of practical conservation work,such as the drugs rehabilitation volunteers) counter-parts. The explanation for this counter-intuitive resultprobably lies in the finding that experienced volunteerscarried out the tasks significantly faster than did novi-ces; we judge that their experience brought over-con-fidence, and a lower threshold of boredom.One overarching caveat to our results is that theyapply only to the particular sub-population of potentialvolunteers (though very diverse) from which our samplewas drawn, and to the particular circumstances in whichthey worked with us. Nonetheless, in addition toobvious differences in the perceived usefulness of indi-viduals, we found significant generalisations regardingthe performance of people on our teams. Awareness ofthese generalisations enabled us to make our teams verymuch more effective, as we were able to balance thecomposition of working groups, and adapt our man-agement to their strengths and weaknesses. Similarly,the success of our project rested heavily on having adiversity of tasks and a sufficiency of volunteers, with-out this flexibility the essential balance between securingresults for the researchers and ensuring recreation forthe volunteers would have been unattainable with ourteams. Of course, while the team managers might seekto maximise the team’s performance, the fact that thevolunteers are volunteering, and have their own goals(such as enjoyment) place important constraints onmanagement. In our particular sample of recruits,overall, men made slightly better volunteers thanwomen, a mean difference that could be traced to thesignificantly higher individual variation in our perceivedcapability scores in women than in men. In this context,

the attitudes of the volunteers appeared to be a crucialfactor influencing their performance. Generally, womenin our sample were more hesitant than men, and some-times had to be ‘persuaded’ to perform certain tasks, forexample, handling mice or touching deer droppings.Often, with encouragement and additional tuition thishesitancy abated, but not always, and it generally setthese individuals back relative to their contemporaries,reducing their overall ability to perform the task. Incontrast, people from less privileged backgrounds, asexemplified in our sample by those from the drug reha-bilitation programme, showed no hesitation to under-take these tasks; indeed, they were generally amongstour highest scoring volunteers. Again, these resultsapplied to our assessments of our sample of volunteers,under our particular conditions. We would not neces-sarily expect the same results to apply to other popula-tions of volunteers. On the contrary we would expectdifferences between different populations of volunteersand between different circumstances. The material pointis that differences in aptitude and effectiveness are likelyto exist, and should be taken into account.Our sample contained a broad spectrum of physicalabilities. Not surprisingly, people at the limit of theirphysical fitness did not perform as well as those volun-teers who found the work physically easy. Once con-trolled for fitness, age had no significant influence onvolunteer performance. The flexibility to adapt the pro-gramme to allow for individual fitness, for example,taking some sub-groups to easily accessed badger settsand others to steep/ less accessible setts, to watch, wascrucial to our capacity to make a success of this project.Though no task per se lay outside the ability of volun-teers to perform, simply some coped with the task withless strain.Finally, an important factor is what do volunteers getout of the experience? Are they encouraged to volunteerfurther? From the 155 volunteers passing through theprogramme, seven (=4.5%) have actually changedcareer, re-training in biology (in several cases afteryears in a successful alternative career), while a mini-mum of 30% that we know of, through sustained con-tact, have joined conservation groups such as theBritish Trust for Conservation Volunteers, the Mam-mal Society, etc. Thus, it seems that as well as provid-ing volunteers with the skills necessary to contribute towildlife conservation, it is also possible to foster theirenthusiasm and encourage them to put these skills togood use.

Acknowledgements

This study would not have been possible without theeffort, hard work and goodwill of our volunteer teams

196 C. Newman et al. / Biological Conservation 113 (2003) 189–197

to whom we owe a debt of thanks. A special note shouldbe made of the novice volunteers coming from the LeyCommunity, accompanied by Mr. Steve Hope, whohave made a tremendous contribution to this project.Thanks also to Graeme McLaren, David Slater andStephen Ellwood for assisting with team management.The project relies heavily upon being able to use facil-ities at the Wytham field station, and our thanks toMike Morecroft, Michele Taylor and Phil Smith formaking this possible. We are grateful to the estates stafffor their co-operation. A special note of thanks mustalso be made to the Earthwatch Institute, who recruitedall the volunteers to date, especially to Robert Barring-ton, Pamela Mackney, Nat Spring, Michael Humphries,Jeremy Stokes and Valda Uden. This manuscript hasbenefited considerably from the comments of Fran Tat-tersall and Paul Johnson of WildCRU. Thanks also toJessamy Battersby of the JNCC for her support andadvice under the auspices of the Mammal Surveillanceand Monitoring Network. We are very grateful forfinancial support from English Nature, the Ernest CookTrust and The Mammals Trust UK.

References

Barreto G., Macdonald D.W., Strachan R., 1998. The tightrope

hypothesis: An explanation for plummeting watervole numbers in

the Thames catchment. In: United Kingdom flood plains. Ed. By B.

Sherwood and R. Bailey. Proceedings of the Linnean Society of

London 1.

Bright, P.W., Morris, P.A., 1990. Habitat requirements of dormice

Muscardinus avellanarius in relation to woodland management in

southwest England. Biological Conservation 54, 307–326.

Bright, P.W., Morris, P.A., Mitchell-Jones, A.J., 1996. A new survey

of the dormouse Muscardinus avellanarius in Britain, 1993-4. Mam-

mal Review 26, 189–195.

Clements, E.D., Neal, E.G., Yalden, D.W., 1988. The national badger

sett survey. Mammal Review 18, 1–9.

Davison, A., Birks, J.D.S., Brookes, R.C., Braithwaite, T.C., Messen-

ger, J.E., 2002. On the origin of faeces: morphological versus mole-

cular methods for surveying rare carnivores from their scats.

Journal of Zoology 257, 141–143.

Delahay, R.J., Brown, J., Mallinson, P.J., Spyvee, P.D., Handoll, D.,

Rogers, L.M., Cheeseman, C.L., 2001. The use of marked bait in

studies of the terrestrial organisation of the European badger (Meles

meles). Mammal Review 30, 73–87.

Flowerdew, J.R., Ellwood, S.A., 2001. Impacts of woodland deer on

small mammal ecology. Forestry 74, 278–287.

Gibbs, J., 1996. MONITOR Software for estimating the statistical

power of small scale population monitoring programmes. Unpub-

lished manual.

Gilmour, J., Saunders, D.A., 1995. EARTHWATCH: an international

network in support of research on nature conservation. In: Saun-

ders, D.D. et al. (Eds.), Nature Conservation 4: The Role of Net-

works. Surrey Beatty and Sons, Australia, pp. 627–633.

Gurnell, J., Flowerdew, J.R., 1990. Live Trapping Small Mammals. A

Practical Guide. Occassional publication of the Mammal Society 3.

The Mammal Society, London.

Greenwood, J.J.D., 1994. Trust the wildlife volunteers. Nature 368, 490.

Hiby, A.R., Thompson, D., Ward, A.J., 1988. Census of grey seals

by aerial photography. Photogrammetric Record 12, 589–594.

Hutchings, M.R., Harris, S., 1996. The Current Status of the Brown

Hare (Lepus europeas) in Britain. JNCC, Peterborough.

Johnson, J., 2001. The BDS deer distribution survey 2000. Deer 12,

26–29.

Johnson, D.D.P., Macdonald, D.W., Newman, C., Morecroft, M.D.,

2001. Group size versus territory size in group-living badgers: a

large-sample field test of the Resource Dispersion Hypothesis. Oikos

95, 265–274.

Krebs, J.R., Anderson, A., Clutton-Brock, T., Morrison, I., Young,

D., Donnelly, C., Frost, S., Woodroffe, R., 1997. Bovine tubercu-

losis in cattle and badgers. The Ministry of Agriculture, Fisheries

and Food Publications, London.

Langbein, J., 1997. The Ranging Behaviour, Habitat Use and Impact

of Deer in Oak Woods and Heather Moors of Exmoor and the

Quantock Hills. British Deer Society, Fordingbridge.

Langbein, J., Hutchins, M.R., Harris, S., Stoate, C., Tapper, S.C.,

Wray, S., 1999. Techniques for assessing the abundance of brown

hares. Mammal Review 29, 93–116.

Macdonald, D.W., Newman, C., 2002. Badger (Meles meles) popula-

tion dynamics in Oxfordshire, UK, Numbers, density and cohort

life histories, and a possible role of climate change in population

growth. Journal of Zoology 256, 121–138.

Macdonald, D.W., Stafford, S. (Eds.), 1997. The Wytham Commu-

nicator. The Wildlife Conservation Research Unit, Oxford.

Macdonald, D.W., Mace, G., Rushton, S. (Eds.), 1998. Proposals for

future monitoring of British mammals. HMSO, London.

Macdonald, D.W., Tattersall, F.H., 2002. The State of Britain’s

Mammals 2002. Peoples Trust for Endangered Species/Mammals

Trust UK, London.

Mayle, B.A., Peace, A.J., Gill, R.M.A., 1999. How many deer? A field

guide to estimating deer population size. Forestry Commission

Field Book 18.

Minitab, Release 11.21, 1996. Minitab Inc.

Morecroft, M.D., Taylor, M.E., Ellwood, S.A., Quinn, S.A., 2001.

Impacts of deer herbivory on ground vegetation at Wytham Woods,

central England. Forestry 74, 251–257.

Reading, C.J., Buckland, S.T., McGowan, G.M., Gorzula, S., Jaya-

singhe, G., Staines, B.W., Elston, D.A., Ahmadi, S., 1994. Status of

the adder Vipera berus in Scotland. Scottish Natural Heritage

Research, Survey and Monitoring Report No. 38. Scottish Natural

Heritage, Edinburgh.

Reading, C.J., Buckland, S.T., Jayasinghe, G., McGowan, G.M.,

Gorzula, S., Balharry, D., 1996. The distribution and status of the

adder (Vipera berus L.) in Scotland determined from questionnaire

surveys. Journal of Biogeography 23, 657–667.

Saunders, D.A., 2002. Conservation research leads to a paradigm shift

in farming practice: a case study from the Western Australian

wheatbelt. In: Lunney, D. et al. (Eds.), Community and Research-

based Conservation: A Clash of Paradigms. Royal Zoological

Society of New South Wales, Mosman.

Strachan, R., 1995. Mammal Detective. Whittet Books, Ltd, London.

Toms, M.P., Siriwardena, G.M., Greenwood, J.J.D., 1999. Develop-

ing a mammal monitoring programme for the UK. BTO Research

Report No. 223. BTO, Thetford.

Walsh, A., Harris, S., 1996. Factors determining the abundance of

vespertilionid bats in Britain: geographic, land class and local habi-

tat relationships. Journal of Applied Ecology 33, 519–529.

Walsh, A., Catto, C., Hudson, A., Racey, P., Richardson, P., Lang-

ton, S., 2001. The UK’s National Bat Monitoring Programme.

DEFRA, London.

Wilson, G., Harris, S., McLaren, G., 1997. Changes in the British

badger population, 1988-97. Peoples Trust for Endangered Species,

London.

C. Newman et al. / Biological Conservation 113 (2003) 189–197 197