QUAGGA PROJECT ASSOCIATION (INCORPORATED UNDER SECTION 21) · 2015. 8. 22. · 2 TOTAL!HERD!UPDATE!...

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QUAGGA PROJECT ASSOCIATION (INCORPORATED UNDER SECTION 21)

Co-coordinator’s Report (incorporating Stud Book Manager’s report) February 2015

ASSETS UPDATE & SECT 21 Co:

- 119 animals in 10 locations - Cash in bank as per treasurers report

QUAGGAS BORN: • 15 foals were born in 2014, 6 have been born in 2015 so far

ANIMAL DEATHS: • 1 foal at Wedderwill. • Marylin (born 1993 at Vrolikheid) is missing at Boland Landbou and Monica (born 1993 at Vrolikheid) is

missing at Elandberg. Both are presumed to have died in the veld. (Our next oldest animal is Marriette (born 1994 at Elandsberg). This animal is currently at Wedderwill)

QUAGGA HERD PHOTO UPDATE: • Photographing of foals is going well with all foals, except 3 at Pampoenvlei, have been photographed

and entered into the database/studbook. • Upgrading of photographs of individual animals is continuing where necessary.

ANIMAL CAPTURES & MOVEMENTS: • Animals need to be removed from Bontebok Ridge and Boland Landbou urgently due to population

growth as well as surplus animals from Elandsberg and Pamoenvlei. Most of the surplus animals are not stripy (and can be sold as zebra) but rather second rate Quagga (all exhibit reduced striping).

• There is a possibility to move animals to a second site on the Nuwejaars Wetland SMA but the capture would cost at approximately R7000-‐00 per animal for capture and transport.

• Bernard has detail of which animals need to be moved for each property. • 5 surplus stallions moved off Wedderwil in October by Steve Mitchel and sold – these males had

caused the deaths of 4 young animals with their harassing of the breeding herds – this is a problem we must keep an eye on especially on the smaller properties. We have a similar situation developing at Boland Landbou School.

• The planned capture of a quagga like animal at Remhoogte Stellenbosch did not occur as owner withdrew from the sale, see below.

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TOTAL HERD UPDATE • Below the current herd update as at 28 February 2015

Current Herd as per 28 February 2015Now At SexQuaggaName Studboo Date of Birth Sire Dam

Arc en Ciel FJemyma 84 10/01/2007 Bernard Truida

Mary 159 01/12/2011 Tom Truida

TJ13 189 15/08/2013 Tom Jemyma

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Arc en Ciel MTom 60 15/10/2005 Etienne Marjean

Oliver 98 11/01/2008 Bernard Truida

Craig 167 02/01/2012 Tom Jemyma

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Total 6

Boland Landbou FLucia 92 20/01/2008 Ike Marilyn

Lizette 112 04/04/2009 Douw Strelza

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Boland Landbou MDouw 54 05/11/2003 Etienne Tracy

Willie 111 04/04/2009 Douw Marilyn

Pedro 156 08/10/2011 Douw Sandra

Lance 180 01/10/2012 Douw Lucia

4

Boland Landbou M/FDL11 157 12/10/2011 Douw Lucia

DM12 198 02/02/2012 Douw Marylin

DM13 184 02/02/2013 Douw Marylin

DL13 199 01/12/2013 Douw Lizette

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Total 10

Bontebok Ridge FTracy 18 14/02/2000 Luke Mariette

Margaret 33 22/03/2003 Ike Strelza

Stripes 151 21/01/2011 Tim Margaret

Katja 147 01/05/2011 Eric Nelmarie

Emma 168 05/01/2012 Tim Tracy

TM14 208 01/03/2014 Tim Margaret

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Bontebok Ridge MTim 21 08/01/2003 George Jeanetta

Ben 121 11/06/2009 Tim Tracy

Peter 139 28/12/2010 Tim Tracy

Red 211 01/07/2014 Tim Tracy

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Bontebok Ridge M/FTM12 170 14/02/2012 Tim Margaret

TT13 186 24/06/2013 Tim Tracy

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Now At SexQuaggaName Studboo Date of Birth Sire DamBontebok Ridge M/FTE14 212 01/09/2014 Tim Emma

TS15 218 20/01/2015 Tim Stripes

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Total 14Elandsberg Farm FWhity 25 08/01/2002 Shaun Jeanetta

Joy 28 11/09/2002 Luke MarietteMarlene 38 31/05/2004 Ike Marcelle Anna 73 10/05/2006 George LeslieSandy 85 10/10/2007 George Leslie Cynthia 83 09/12/2007 George Jeanetta Simone 101 28/12/2008 Duncan WhityJulie 127 06/01/2010 Duncan JoyJackie 163 21/12/2011 Duncan JoyCorlie 190 20/09/2013 Troy Monica

10Elandsberg Farm MDuncan 42 24/10/2001 Luke Lulu

Frank 37 05/07/2004 Etienne Tracy Josh 64 12/05/2005 Duncan WhityElan 99 12/01/2008 George JoyTroy 118 10/01/2009 George Jeanetta Garth 173 21/07/2012 George MonicaDJ14 209 01/06/2014 Duncan Joy

7Elandsberg Farm M/FFJ11 162 20/12/2011 Frank Jacqui

JJ11 166 29/12/2011 Josh JeanettaFM12 169 05/01/2012 Frank MarleneDW13 183 01/02/2013 Duncan WhityTE13 204 12/12/2013 Troy MarleneJJ14 210 01/07/2014 Josh Julie

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Total 23Groote Schuur MGabi 47 20/11/2004 Paul Erina

Gordon 69 03/01/2006 Paul Erina Khumba 140 11/01/2010 Eric Ria RitaHermon 158 12/11/2011 Eric Ria RitaEnya 165 28/12/2011 Eric Lydia

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Total 5Kosierskraal FMarjean 19 18/09/2000 Luke Lulu

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Now At SexQuaggaName Studboo Date of Birth Sire DamKosierskraal FSuzi 58 09/01/2005 Etienne Tracy

Michelle 125 01/10/2010 Frank RynaNonnie 179 01/10/2012 Robin MarjeanNoel 205 25/12/2013 Robin Marjean

5Kosierskraal MRobin 44 11/01/2004 Luke Amanda

Gio 145 28/04/2011 Robin ErnaVusi 152 01/08/2011 Robin Marjean

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Total 8Pampoenvlei FElizabeth 22 11/05/2001 Shaun Monica

Rebecca 34 20/07/2003 George LeslieNicola2 68 01/03/2006 Ryan MeintjieRosie 134 14/08/2010 Ryan Rebecca

4Pampoenvlei MRyan 15 05/01/1999 Shaun Monica

Henry 52 20/01/2005 Luke Elizabeth Raulene 82 25/05/2007 Ryan Elizabeth Logan 136 10/10/2010 Henry Nicola2

4Pampoenvlei M/FRE11 153 15/08/2011 Ryan Elizabeth

RE12 175 09/09/2012 Ryan ElizabethRR12 176 15/09/2012 Ryan RebeccaHN12 177 01/10/2012 Henry Nicola2HR13 191 27/09/2013 Henry RosieRE13 192 07/10/2013 Ryan ElizabethRR13 195 07/11/2013 Ryan RebeccaXX 222 01/01/2014XY 223 01/01/2014XZ 224 01/01/2014

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Total 18SMA FSusan 124 08/01/2009 Douw Sandra

Frances 114 29/06/2009 Frank MarleneDerica 135 09/01/2010 Douw SandraFrederica 203 10/12/2013 Freddy Derica

4SMA MFreddy 96 09/04/2008 Etienne Lydia

FF13 194 05/11/2013 Freddy Francis

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Now At SexQuaggaName Studboo Date of Birth Sire Dam

2SMA M/FFF15 216 05/01/2015 Freddy Francis

FD15 220 01/02/2015 Freddy DericaFS15 221 16/02/2015 Freddy Susan

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Total 9Vlakkenhuiwel FLydia 59 10/12/2005 Sebastian Margaret

Ria Rita 77 20/11/2006 Sebastian MargaretDanelle 110 04/03/2009 Ettienne Ria RitaNelmarie 108 01/12/2009 Ettienne MargaretElanor 141 11/05/2010 Eric Lydia

5Vlakkenhuiwel MJack 97 25/09/2008 Tim Tracy

EN12 171 01/05/2012 Eric NelmarieER12 181 01/11/2012 Eric Ria RitaEL13 182 01/01/2013 Eric LydiaJE13 202 06/12/2013 Jack ElanorJN14 207 01/02/2014 Jack NelmarieJD14 213 01/10/2014 Jack Danelle

7Vlakkenhuiwel M/FJL14 206 11/01/2014 Jack Lydia

JE15 217 15/01/2015 Jack ElanorJR15 219 01/02/2015 Jack Ria Rita

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Total 15Wedderwill FMariette 8 20/05/1994 Allan Lulu

Amanda 80 03/04/2001 Alex Melanie Lysie 90 28/12/2007 Nico GrietNina J 120 25/11/2009 Nico MarietteFleur 143 11/01/2011 Mark LlysieBess 172 20/07/2012 Mark MarietteNN14 225 28/04/2014 Niel Nina

7Wedderwill MMark 62 12/02/2005 Luke Mariette

Niel 106 12/12/2008 Nico Ashley

2Wedderwill M/FMM14 215 22/09/2014 Mark Marriette

ML14 214 11/11/2014 Mark Lysie

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Now At SexQuaggaName Studboo Date of Birth Sire Dam

Total 11119Grand Total

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FOAL BIRTHS PHOTOGRAPHIC RECORD • Below is an updated photo schedule of foals born into the project

DJ14 No 209 M Duncan Joy 01/06/2014 Elandsberg

JJ14 No 210 M/F Josh Julie 01/07/2014 Elandsberg

Red No 211 M Tim Tracy 01/07/2014 Bontebok Ridge

TE14 No 212 M/F Tim Emma 01/09/2014 Bontebok Ridge

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TS15 No 218 M/F Tim Stripes 20/01/2015 Bontebok Ridge

JD14 No 213 M Jack Danelle 01/10/2014 Vlakkenhuiwel

JE15 No 217 M/F Jack Elanor 15/01/2015 Vlakkenhuiwel

JR15 No 219 M/F Jack Ria Rita 01/02/2015 Vlakkenhuiwel

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FD15 No 220 M/F Freddy Derica 01/02/2015 SMA 5th generation

FF15 No 216 M/F Freddy Francis 05/01/2015 SMA 5th generation

FS15 No 221 M/F Freddy Susan 16/02/2015 SMA

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DNA SAMPLES:

o Bernard has been in contact with Rasmus Heller of University of Copenhagen who is coming to SA in April. He plans to analyse the Rau Quagga DNA as a genetic variation in Plains Zebra DNA

ZEBRAS SOLD OUT OF THE QPA: o Below is a picture of an animal that Murray Boustred bought from QPA a while ago. It has

turned into an excellent quagga type animal. I attempted to buy it back from Murray and in return offered him 3 (breeding) zebras out of the project as he had lost some of his own. He initially agreed and Hamish Curry obtained the permits move this animal back ito the Project. Sadly Murray had a change of heart and has since opted to not have this animal removed from his premises.

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WEBSITE: The website has recently had a number of articles and useful information added to it including a new studbook link on the opening Home page, and new/updated articles onto the Archives page

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ARTICLES: o Brenda Larrison, University of California, who has had much input over the past years with the

QPA, has been a part of a recent publiction for the Royal Society Open Science, entitled “ How the zebra got its stripes: a problem with too may solutions”

rsos.royalsocietypublishing.org

ResearchCite this article: Larison B, Harrigan RJ,Thomassen HA, Rubenstein DI, Chan-GolstonAM, Li E, Smith TB. 2015 How the zebra got itsstripes: a problem with too many solutions.R. Soc. open sci. 2: 140452.http://dx.doi.org/10.1098/rsos.140452

Received: 17 November 2014Accepted: 15 December 2014

Subject Category:Biology (whole organism)

Subject Areas:ecology/evolution

Keywords:zebra, stripes, patterning, random forest,ecological predictions, species distributionmodelling

Author for correspondence:Brenda Larisone-mail: [email protected]

Electronic supplementary material is availableat http://dx.doi.org/10.1098/rsos.140452 or viahttp://rsos.royalsocietypublishing.org.

How the zebra got itsstripes: a problem with toomany solutionsBrenda Larison1,2, Ryan J. Harrigan1,2, Henri A.Thomassen3, Daniel I. Rubenstein4, Alec M.Chan-Golston5, Elizabeth Li5 and Thomas B. Smith1,21Department of Ecology and Evolutionary Biology, University of California, 610 CharlesE. Young Drive South, Los Angeles, CA 90095, USA2Center for Tropical Research, Institute of the Environment and Sustainability,University of California, 619 Charles E. Young Drive East, Los Angeles, CA 90095, USA3Institute for Evolution and Ecology, University of Tübingen, Building E, Floor 4,Auf der Morgenstelle 28, Tübingen 72076, Germany4Department of Ecology and Evolutionary Biology, Princeton University, 106A GuyotHall, Princeton, NJ 08544, USA5Department of Mathematics, University of California, 520 Portola Plaza, MathSciences Building 6363, Los Angeles, CA 90095, USA

1. SummaryThe adaptive significance of zebra stripes has thus far eludedunderstanding. Many explanations have been suggested,including social cohesion, thermoregulation, predation evasionand avoidance of biting flies. Identifying the associations betweenphenotypic and environmental factors is essential for testing thesehypotheses and substantiating existing experimental evidence.Plains zebra striping pattern varies regionally, from heavy blackand white striping over the entire body in some areas to reducedstripe coverage with thinner and lighter stripes in others. Weexamined how well 29 environmental variables predict thevariation in stripe characteristics of plains zebra across their rangein Africa. In contrast to recent findings, we found no evidencethat striping may have evolved to escape predators or avoidbiting flies. Instead, we found that temperature successfullypredicts a substantial amount of the stripe pattern variationobserved in plains zebra. As this association between striping andtemperature may be indicative of multiple biological processes,we suggest that the selective agents driving zebra striping areprobably multifarious and complex.

2. IntroductionColoration and patterning are important adaptive characteristicsin many taxa [1–3] and species from fruit flies to humans exhibit

2015 The Authors. Published by the Royal Society under the terms of the Creative CommonsAttribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricteduse, provided the original author and source are credited.

on January 14, 2015http://rsos.royalsocietypublishing.org/Downloaded from

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2rsos.royalsocietypublishing.org

R.Soc.opensci.2:140452................................................

environmentally correlated gradients in pigmentation that are strongly suggestive of adaptation to localenvironments [4–6]. Zebra stripes are among the most striking mammalian coat patterns, yet whetherthey are adaptive has not been established nor have the drivers of natural selection been pinpointed.The clinal modification in striping pattern that plains zebra (Equus quagga) exhibit (figure 2; electronicsupplementary material, figure S4) suggests that environmental factors may create selective pressuresthat play a role in determining stripe patterns. Within this single species, individuals run the gamutin terms of striping patterns: some have strong striping over their entire body, while others havefew to no stripes on the legs, and faint shadow stripes interspersed with the primary stripes alongthe torso. Individuals of the extinct quagga subspecies from South Africa had the least amount ofstriping, with stripes limited to the head, neck and torso. The quagga is thought to have divergedquite recently from other plains zebra and may have undergone stripe loss relatively rapidly, possiblyassociated with a more open, drier environment [7]. Variation in striping patterns has also figuredprominently in subspecific classifications [8,9]. Distance and large barriers such as the Zambezi Rivermay play a role in the observed variation [8,10], but the lack of genetic structuring observed amongpopulations that exhibit divergent stripe phenotypes [11] suggests that stripe variation may representadaptive variation rather than simply resulting from drift in isolated populations. That the degreeof striping has a genetic basis is clear from a recent heritability study conducted in captive plainszebra [12].

There are a number of adaptive hypotheses for the existence of striping in zebras [13], includingpredation evasion [14,15], thermoregulation [14], social cohesion [16] and avoidance of biting flies[17]. In this paper we put the predation, thermoregulation and biting fly hypotheses to a spatiallyexplicit empirical test by modelling how variation in plains zebra stripe pattern is associated withvariation in environmental variables. For example, zebra are a common, possibly preferred, prey oflion [18,19]. Computer simulations with human subjects support the notion that strong black andwhite patterns make it difficult for predators to capture their prey [20]. Computer simulations havealso shown that such patterns influence perceived size [21], speed [22] and trajectory (much likethe optical illusions created by the spinning spokes of a wheel or the rotating stripes of a barber’spole) [23]. Each of these ideas depend on a strong pattern in order to produce the correspondingeffect. So if zebra stripes function as an optical illusion that reduces the success of predation efforts,we would expect to see bolder, black and white stripes in areas where encounters with lions aremore likely.

Striping has been shown experimentally to prevent both glossinid (tsetse) and tabanid flies fromlanding on surfaces [17,24,25]. For tabanids this phenomenon has been explained as reduced polarotacticattraction caused by the interspersion of weakly polarizing white stripes between the strongly polarizingand attractive black stripes [24]. However, this explanation does not work for other biting flies, such astsetse flies, which are not polarotactic [26]. More likely, stripes may break up the silhouette of the bodyagainst a strong background [17] or create an optical illusion that confuses flies [23]. Biting flies tendto feed low on the body, especially around legs where the zebra’s skin is the thinnest [24,27,28]. Thus,we expect that stripe characteristics of the legs, or perhaps even the belly, will correlate with tsetse flyprevalence if tsetse flies have played a role in the evolution of zebra stripes.

The hypothesis that stripes help zebra thermoregulate has not been tested empirically. This hypothesisis based on the idea that black and white stripes would heat up differentially, thus causing differentialairflow between black and white stripes and creating eddies of air that would have a cooling effect [14].This mechanism should work most effectively on strong, contrasting stripes, so we would predict goodcoverage with bold black and white striping to occur in areas in which zebra are regularly exposed tohigher temperatures.

In this paper, we make the implicit assumption that striping is adaptive as we attempt to identifypotential drivers of natural selection. We make an assumption typically made in studies of the adaptivesignificance of traits [29], that variation in current striping patterns can be explained by currentenvironmental conditions and that the relationship between stripes and environment has remainedstable over time, although the specifics of the distributions of habitats and, consequently, stripe patternsmay have changed. We conduct spatially explicit modelling of plains zebra striping using a set ofenvironmental layers that allow us to test the hypotheses that stripe characteristics are associated withpredation, biting flies or temperature. In addition to these specific hypotheses about stripe thicknessand stripe saturation as they relate to predicted lion, tsetse fly and temperature distributions, we alsoinvestigate available climatic and remotely sensed variables such as precipitation, surface moistureand vegetation characteristics to investigate whether these environmental predictors help explainstriping patterns.


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R.Soc.opensci.2:140452................................................3. ResultsTo analyse the relationship between stripe phenotype and environment, we quantified stripecharacteristics at 16 sites across the plains zebra range (electronic supplementary material, figure S1).One of the 16 sites is represented by a single photograph of the extinct quagga subspecies, which is theonly quagga specimen with precise locality data such that environmental data could be assigned to it [30].Stripe characteristics were quantified for forelegs, hind legs, torso and belly (electronic supplementarymaterial, figure S2), and included stripe number, thickness, length and colour saturation. As a singlestripe can be described by thickness, length and colour saturation, we multiplied standardized values ofthese traits in order to describe the overall quality of a stripe, which we call stripe definition.

We ran a random forest model [31–35] as implemented in the package randomForest [36,37] in R[38] using a set of 19 predictive variables. Environmental variables successfully explained at least30% and as much as 63% of the variance for 12 of 18 striping characteristics: foreleg stripe number,thickness, saturation and overall definition, hind leg stripe thickness and definition, torso stripe number,length, thickness, saturation and definition, and belly stripe number (table 1). The most consistentlyimportant variables were isothermality (BIO3) and mean temperature of the coldest quarter (BIO11).Maximum annual vegetation as measured by the Normalized Difference Vegetation Index (NDVIMAX)and precipitation of the wettest month (BIO13) were also important for some characteristics. Estimatedtsetse fly and lion distributions, by contrast, consistently failed to predict stripe pattern variation.

A good model has the capacity to predict characteristics for sites that were not included in theoriginal model. We therefore tested our random forest models by quantifying stripe characteristics ateight additional sites (electronic supplementary material, figure S1) using photographs posted on thephoto sharing website Flickr, or sent to us in response to requests placed there and on the Universityof California, Los Angeles’ (UCLA) Center for Tropical Research website. We extracted the valuesof the best environmental predictor variables for the test sites, used these to predict the values forstripe characteristics across those sites, and regressed the predictions onto the observed values of stripecharacteristics. The validity of our model estimates was well supported for stripe length, thickness,saturation and overall definition on the foreleg, thickness and definition on the hind leg, and numberof stripes and definition on the torso. Our models successfully predicted the values of these eight stripecharacteristics across the eight test sites (table 1). Models were also relatively successful at predicting hindleg stripe length and saturation at the test sites (table 1), while other characteristics, particularly those ofthe belly, were not accurately predicted for new sites. The random forest model and correlations betweenobserved and predicted are shown in figure 1 for hind leg stripe thickness and torso stripe definition(as the quagga point is based on a single individual we reran models and predictions without thatpoint included. Results were concordant with our previous models, electronic supplementary material,table S2).

We predicted stripe characteristics across the historical plains zebra range [10] by first extractingthe values of the best predictor variables for 50 000 random points across Africa using ARCGIS(Environmental Systems Research Institute, Redlands, CA). We then used a random forest model topredict values of stripe characteristics for these 50 000 points (interpolated using ordinary kriging andlimited to the plains zebra known range). Figure 2 shows the predicted distribution of stripe variationfor hind leg stripe thickness and torso stripe definition. Both maps show that temperature accuratelypredicts the general pattern of zebra striping. Interestingly, the region of Africa known to have harbouredE. quagga and Equus burchelli [10], the zebra subspecies typically having no stripes on the legs, is welldelineated in the map of hind leg stripe thickness, in spite of the model containing only one data pointin which zebra had no leg stripes. In addition, predictions of torso stripe definition correctly identifyregions at central latitudes in eastern Africa in which zebra have full length and fully saturated butthinner stripes on the torso than zebra farther north. Bivariate plots (electronic supplementary materialfigure S4) show the relationship between the two traits shown in figures 1 and 2 and the environmentalvariables identified as important by our models.

4. DiscussionWe found that environment, particularly temperature, was a significant predictor of zebra stripe patternsacross their entire range in Africa. This was supported by the large amount of variation explained bythe models containing these variables, as well as the successful predictions of striping characteristicsat new sites. The stripe characteristics that were most readily explained by environmental variation


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R.Soc.opensci.2:140452................................................

Table 1. Random forest models, the percentage of variance they explain and their ability to predict stripe characteristics of zebra at newsites. (Models with significant predictive ability are in bold.)

models predictions

body part stripe characteristic model % variance explained r2 p. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

foreleg number BIO3+ BIO13 44 0.01 0.33. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

foreleg length BIO11+ NDVIMAX 20 0.49 0.03. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

foreleg thickness BIO3+ BIO11 42 0.66 0.009. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

foreleg saturation BIO11+ NDVIMAX 37 0.42 0.05. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

foreleg definition BIO3+ BIO11 60 0.66 0.008. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

hind leg number BIO13+ BIO15+MAX 22 −0.10 0.57. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

hind leg length BIO3+ BIO11 13 0.36 0.07. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

hind leg thickness BIO3+ BIO11 51 0.60 0.01. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

hind leg saturation BIO11+ NDVIMAX 20 0.37 0.06. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

hind leg definition BIO3+ BIO11 63 0.60 0.001. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

torso number BIO3+ BIO13 63 0.42 0.04. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

torso length BIO3+ BIO11+ BIO13 51 0.20 0.15. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

torso thickness BIO3+ BIO11+ TREE 37 0.24 0.12. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

torso saturation BIO11+ BIO13 37 −0.01 0.37. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

torso definition BIO3+ BIO11+ BIO13 40 0.45 0.04. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

belly number BIO11+ BIO13+ NDVIMAX 45 0.03 0.31. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

belly thickness NDVIMAX 23 −0.11 0.62. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

belly saturation BIO1+ NDVIMAX 3 −0.02 0.38. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

were stripe thickness and definition on forelegs and hind legs, and the number of stripes and definitionon the torso, suggesting that these traits are the most likely targets of selection. This correlation withtemperature may be explained by more than one causal mechanism, as discussed below, and will requirefurther investigation.

Our finding that the two environmental variables most closely associated with variation in stripingwere both temperature variables lends support to the hypothesis that striping may be related tothermoregulation. One would expect that mechanisms to adapt to temperature would be most relevanton the torso, and the stripe characteristics of the torso are well explained by isothermality (BIO3)and mean temperature of the coldest quarter (BIO11). Given the hypothesis that stripes give rise todifferential air currents that produce a cooling effect [14], intense black stripes would be expected tocreate more of a differential relative to white stripes, and stripe saturation is greatest in the tropicswhere animals experience sustained high temperatures. There have been no published direct tests ofthe thermoregulation hypothesis, however preliminary observations using a non-contact infrared digitalthermometer gun show that zebra maintain a significantly lower surface body temperature (29.2◦C vs32.5◦C) than nearby, similar sized herbivores grazing under the same conditions [39], and observationsof differences in shade seeking behaviour between thin striped Grevy’s zebras and thick striped plainszebras suggest stripe thickness could play a role in thermoregulation (D. I. Rubenstein 1980, personalobservation).

The association between temperature and striping on the legs is not easily explained as a mechanismfor thermoregulation. It may simply be a result of genetic correlation as stripe characteristics on the legsand torso are highly correlated (electronic supplementary material, table S1), or it may be a responseto a different mechanism, such as avoiding fly bites. Tsetse flies and other biting flies can negativelyimpact animals in a number of ways: both directly, through loss of time spent foraging and energeticexpenditures that lead to weight loss [40–42], and indirectly, through the transmission of disease [43].The possibility that biting flies could be a selective agent favouring striping is supported by experimental


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0.020 0.024 0.028

0.010

0.015

0.020

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observed hind leg stripe thickness

pred

icte

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nd le

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QSCATSTDBIO15LIONBIO1QSCATMEANBIO18BIO14BIO8BIO19NDVIGRBRBIO2BIO12TSETSETREECOVERBIO13NDVI_GREENNDVIMAXBIO3BIO11

–10 20

(a) (b)

50

LIONBIO15BIO14QSCATSTDQSCATMEANBIO19BIO1BIO8BIO2BIO18NDVIGRBRBIO12TREECOVERTSETSEBIO13NDVI_GREENNDVIMAXBIO3BIO11

–10 20 50% increase mean square error % increase mean square error

Figure 1. (a) Importance scores for each environmental variable used as input to random forest algorithm models for hind leg stripethickness and torso stripe definition. Variables with higher mean square error (calculated as the average increase in squared residualswhen the variable is permuted) are more important. Variables having an importance score greater than the absolute value of the lowestnegative scoring variable (solid vertical line) are potentially important and informative [30]. Variables shownwith a black circle are thosethat remained important as the model was refined. (b) Correlations between observed and predicted values for hind leg stripe thicknessand torso stripe definition.

evidence that tsetses and tabanids avoid striped surfaces [24]. However, we found no relationshipbetween tsetse flies and variation in striping across populations, which suggests the explanation forstriping in zebra is more complex than simply the avoidance of biting flies. While predicted tsetse flydistributions did not explain stripe variation, it is highly likely that the strongest selective effect of bitingflies is not the bites themselves, but the diseases they may transmit. Tsetse flies, for instance, do notubiquitously carry trypanosomes [44], partly because the ability of trypanosome infections to developin the flies is temperature dependent, with even a small temperature difference of 3◦C significantlyreducing infection rates [45]. Thus, the distribution of the trypanosomes and diseases carried by tsetseflies and other flies may be quite different from the distribution of the flies themselves and could havemore relevance to variation in stripe pattern. We suggest that temperature may influence trypanosomeprevalence in tsetse flies and as a consequence help explain variation in striping.

A recent paper [46] compared the number of stripes on different body parts of the seven extant equidspecies and their subspecies. The authors found significant correlations between either tabanid or tsetseflies and various aspects of striping. However, several points should be considered when interpretingthese results. Estimates of tabanid fly prevalence were not based on species distributions modelled usingtabanid location data, but simply on ranges of temperature and humidity that the authors estimated to


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hind leg stripethickness

thick

thin 0 1000 2000km

weak

N

S

EW

strong

torso stripedefinition

Figure 2. Predicted levels of hind leg stripe thickness (left) and torso stripe definition (right), from a random forest model based on 16populations. Hind leg stripe thickness is best predicted by BIO3 and BIO11. Torso stripe definition is best predicted by BIO3, BIO11 and BIO13.

be favourable for tabanids. This both renders the reliability of the estimated tabanid ranges questionableand begs the question of whether certain ranges of temperature and/or humidity could themselves helpexplain observed striping patterns. The variables used represent a broad overlap between mean valuesof environmental variables and the species or subspecies ranges, and the use of standard statisticaltests with a small number of observations meant that only variables passing individual bivariate testsfor significance were added to their model. Thus, their analysis ignores the substantial variation inenvironmental variables that occurs within each species and subspecies range and does not allow a directtest of multiple hypotheses within the same model. Finally, their work found that the number of bellystripes in a species was positively correlated with predicted probabilities of tsetse flies. However, onlyone species of equid, the plains zebra, actually has both belly stripes and significant range overlap withtsetse flies, suggesting this relationship requires more rigorous analysis.

It is not particularly surprising that probabilities of lion occurrence failed to predict zebra stripepattern, as lion are nearly ubiquitous throughout the range of plains zebra and the predicted probabilityof occurrence does not vary greatly (electronic supplementary material, figure S3). The predictedprobability of lion in the region inhabited by the minimally striped quagga is approximately averagerelative to our other locations. In addition, if striping were a deterrent to lion predation, we might expectlion predation on zebra to be lower in proportion to their abundance than it is on other mammals. Instead,predation on zebra by lion has been found to be in excess of their relative abundance [18,19]. One factorthat could make it difficult to detect a true effect of striping on predation using our dataset is a potentialinteraction between the animal pattern and the background pattern in creating camouflage or predatorconfusion [20,47–49]. Quantification of the backgrounds provided by the habitats inhabited by zebrawould be useful.

One notable aspect of both the training and test datasets is the paucity of sites from southernmostAfrica. This is due to the fact that zebra were extirpated from most of South Africa in the late 1800sresulting in the loss of the quagga and burchelli subspecies, the two with the least striping and withtypically no striping on the legs. The only GIS referenced phenotype we have been able to obtain foreither of these subspecies is one quagga specimen from the Naturhistorisches Museum Basel, which wascollected from a location between Shilow and Whittlesea in South Africa [30]. The ability of this singlepoint to help delineate the region in which zebra with no stripes on the legs used to occur is surprisingand gives even greater credence to the importance of temperature in explaining the adaptive significanceof striping.

Our study has shown a strong correlation between temperature and striping across the plains zebra’srange. The relationship between temperature and stripe pattern is clear and, along with the lack of


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genetic structuring among populations [11], suggests an adaptive explanative for stripe variation. Wefind no clear support for the hypotheses that biting flies or predators have driven stripe evolution,however, the reduction of striping in areas with seasonally low temperatures could be a response toa reduction in the infection rate of tsetse flies with trypanosomes, a reduction in the need for convectivecooling, or both. We expect the function of striping will prove to be complex given the multifarious effectsof striping shown through experimentation to date, and the influence of not only temperature variables,but also the additional, albeit smaller influence, of precipitation and NDVI.

Much additional work is needed to elucidate the true functionality of striping in zebra. Our workshows a correlation with temperature, but the cause of this correlation remains unknown. More realisticexperimental studies are needed to investigate whether stripes function at a distance to help zebra evadedetection, and whether they function at close range to create optical illusions resulting in sufficientconfusion to decrease the likelihood of being bitten or predated. For instance, experimental evidence ismixed as to whether the visual signal of striping may be overcome by the attractiveness of odours suchas CO2 and ammonia [17,50] that tsetse flies use to locate animals, and direct evidence from live animalsin the field is completely lacking. Although zebra blood is not typically found in surveys of tsetse flyblood meals [51,52] and screenings of wild mammals rarely identify zebra with trypanosomes [53], thesame is true for many mammal species that lack stripes. Furthermore, trypanosomiasis has been foundin zebra [54]. Therefore, one cannot reasonably conclude that the lack of parasite data in zebra is relatedto the characteristic of striping. While stripes clearly create confusion in the constrained environment ofa computer screen, this same phenomenon may not occur on a larger scale under normal conditions.Larger scale experiments using live animals or a virtual system are clearly warranted. Experimentsalso need to be conducted to investigate the potential role of temperature. Whether stripes functionin thermoregulation, how environmental factors influence tsetse trypanosome loads and likelihood ofinfection if bitten, all need to be studied. Finally, additional modelling, incorporating genetic data,additional sites, and new variables suggested by experimental data, should be run in order to clarifythe pattern of variation and its causes.

5. Experimental procedures5.1. Phenotype datasetsA minimum of eight zebra per site was measured for the training dataset (with the exception of the singledata point for the quagga), and five or more for the test dataset. Zebra were photographed in profilewith the entire body and legs (to fetlock) visible. The bulk of the photographs were taken by the authorsand a few were donated by trusted individuals (other researchers or professional tour guides). As aconvention, we treated the dark regions of the pelage as stripes. For each zebra, four stripe characteristicswere quantified on each leg (L) and the torso (T), while three were quantified on the belly (B) (electronicsupplementary material, figure S2). We quantified the number of stripes (LTB), length of each stripe(LT only, horizontally across the leg and vertically across the torso), stripe thickness (LTB) and stripesaturation (LTB). Stripe thickness was measured in pixels down the midline of the legs and torso andalong the belly, and standardized by dividing by the pixel length of the body part. Stripe thicknessand body part lengths were measured using IMAGEJ software [55]. For each stripe, however small orfaint, length was estimated categorically as less than or equal to 25, 50, 75 or 100%, and saturation wasestimated in categories from 0 to 7, with 0 being no stripe and 7 being black. All measurements wereperformed by one of three researchers. At least two zebra at each site were measured by a minimumof two researchers in order to estimate repeatability, and two photos at different exposures were takenof a subset of animals to determine the effect of exposure on estimation of colour saturation. Finally, weexamined the possibility that allometry might be a concern using data on skull lengths from [8]. We foundno significant correlations between stripe characteristics and exposure or size. Additional measurementdetails and repeatability results can be found in the electronic supplementary material.

5.2. Environmental variablesVariables input into random forest models included 19 temperature and precipitation variables fromWorldClim [56], (http://www.worldclim.org/), and five remote-sensing variables quantifying theconcentration of green leaf vegetation (MODIS-derived NDVI [57]), which are typically considered ameasure of greenness [58] and productivity [59] (see electronic supplementary material, table S3). We alsoused the MODIS-derived vegetation continuous field (VCF) product as a measure of the percentage of


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tree canopy cover [60]. Monthly composites (mean and standard deviation) of global Quick Scatterometer(QSCAT) [61] are indicative of surface moisture, leaf water content and other seasonal attributes. Weused the Food and Agriculture Organization’s Programme Against African Trypanosomiasis data onpredicted probability of tsetse fly occurrence [62]. The genus Glossina (tsetse flies) is divided into threegroups, which comprise several species each. The Morsitans group is the most common tsetse grouppredicted to co-occur with plains zebra and is often the only one predicted to occur at a site, butthe other two groups, Palpalis and Fuscus, are also predicted to be present in parts of the range. Asmultiple species of tsetse flies are capable of carrying all three species of trypanosomes that infect animals[63,64], we used a composite of the three groups as our predictor variable. We modelled predictedprobabilities for lion presence using MAXENT [65] (electronic supplementary material, figure S3). Lionpresence data for 116 locations was culled from various sources including the American Museum ofNatural History (http://www.amnh.org/our-research/vertebrate-zoology/mammalogy/database), theNational Museum of Natural History (http://vertebrates.si.edu/mammals/mammals_databases.html),the literature [19,66–75] and one personal communication (Kimura D, ranger, Lake Mburo NationalPark, 1980). The tsetse fly and lion data are both predicted probabilities of occurrence based on habitatsuitability; we assume that zebras are more likely to encounter and be impacted by tsetse flies and lionsin those regions where the probability of occurrence of these species are highest. Reduction from 29 to 19variables was accomplished by removing all but one of each set of covarying predictors (correlation ofgreater than 0.9).

Zebra are very mobile and likely to experience a range of conditions within their area of movementthus variables derived from 1 km resolution layers were deemed to be too fine grained. We thereforeaveraged the value of each variable across a 25 km radius around the central point of the protected areawithin which they were photographed.

5.3. Random forest modellingWe ran 20 000 trees within each random forest run, removing the least important variables after each rununtil we identified the ‘best’ model (‘best’ was defined as the model with the highest out of bag, varianceexplained). See the electronic supplementary material for an explanation of random forest analysis.

Ethics statement. This work was conducted under UCLA ARC protocol 2009-090 and the following research permits:Uganda National Council for Science and Technology NS 398, Uganda Wildlife Authority UWA/TDO/33/02, KenyaWildlife Service MOHEST 13/001/21C80V0LII, Namibia Ministry of Environment and Tourism 1406/2009, Kwazulu-Natal OP 3172/2009, Zambia Wildlife Authority 27/September/2012.Data accessibility. Climate and remote sensing data, MAXENT input data, and zebra phenotype data are available athttp://dx.doi.org/10.5061/dryad.s13rt.Acknowledgements. We thank Sunil Basher, John Brancato, Pauline Charruau, Keith Clark, Lisa Fimiani, Anne Griggs,Brooke McWherter, Neville Neveling, Chris Roche, Charl Stafleu and Camille Yabut for providing photographs.Author contributions. B.L. conceived of the project. B.L., T.B.S. and D.I.R. took photographs in the field; B.L., A.C.G. andL.L. collected photographs from additional sources, quantified zebra stripe characteristics and compiled the dataset;A.C.G. ran the repeatability analysis; B.L. and L.L. ran random forest analyses; R.J.H. and H.T. consulted on analysesand provided GIS data; R.J.H. created predictive maps in ARCGIS. B.L. drafted the manuscript. All authors wereinvolved in editing the manuscript.Funding statement. This work was supported by National Geographic grant no. 8941-11 to B.L.Competing interests. There are no competing interests.

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11. Lorenzen ED, Arctander P, Siegismund HR. 2008High variation and very low differentiation in wide


19

o Ralf Krueger of Deutsche Presse-‐Agentur, Germany was a few years ago bureau chief for dpa's

Southern Africa office in Johannesburg and he filed a story on the quagga project then. In May last year he was part of a media tour to the Mountain Zebra NP and the Karoo, and Angela Gaylord from SANParks who told him in a little briefing on the Quagga Project, that SANParks opted out of the project end of 2013. At the same time he was informed that “the fourth generation zebra is (apart from the brown colour) already very much a look-‐alike of what the quaggas looked like according to Mr. Rau's prediction. He was intrigued that the fifth generation will certainly be the interesting part of the project to watch. WE informed him, to his delight that the 5th gernaetion had already been born, and he the wished for us to send out his little story on the status of the project, which we did. The article follows

Wild Things Wild ThingsEXPLORE EXPLORE

Квагга, как живая

Quagga, As Alive

Это фотография, а не фотомонтаж: по финбошу – кустарниковым зарослям в Южной Африке – бежит живая квагга, или почти квагга...

Последняя «полузебра» умерла в Амстердамском зоопарке в 1883 году. Осталось несколько картин с изображением квагги, названной так за ее от-рывистое ржание «куа-ха», всего одна фотография и 23 шкуры в нескольких музеях. Изучая эти остатки зоолог из Южно-Африканского изико-музея Рей-нольд Рау (1932–2006) понял, что можно получить ДНК вымершего животного. И выяснилось, что квагга – это не отдельный вид, а лишь подвид равнинной зебры с очень сходным геномом, появившийся всего 290–120 тысяч лет назад. «Раз так, – решил Рау, то, наверное, можно вывести кваггу, скрещивая кобыл и жеребцов ее близкой родственницы». Тем более, что среди равнинных зебр встречаются не вполне полосатые особи или особи с блеклыми, палевыми, а не черными полосками. Причем, чем южнее – ближе к исконным, более засушли-вым, местам обитания квагги, тем чаще.

По расчетам Рейнольда Рау и его коллег получить кваггу из зебры предпо-лагалось за четыре поколения, для чего отобрали 19 зебр-производителей с неполным развитием полосатости. И вот 28 лет спустя среди нынешнего стада в 89 особей, разделенного на несколько популяций, резвятся отпрыски чет-вертого поколения, внешне неотличимые от квагги. Впрочем, первые из них народились даже раньше. Как отмечают независимые-эксперты генетики из Университета имени Нельсона Манделы, все жеребята вполне себе здоровые, поскольку участникам проекта удалось не превысить долю инбридинга (близко-родственного скрещивания) более, чем на 10 процентов, причем исчезновение полосатости никак не связано с этим явлением. Со временем ученые рассчиты-вают выпустить «воскрешенную» кваггу в дикий финбош. Андрей Журавлев

This is a real photograph, not a photomontage: along the fynbos – bushy vegetation of South Africa – is running a live quagga, or almost quagga…The last half-zebra died in the Amsterdam Zoo in 1883. There were remained only a few paintings depicting quagga (so named for its abrupt call «kwa-ha-ha»), only one photograph, and 23 skins displayed in several museums. By studying these remnants, a zoologist of the Iziko South African Museum, Reinhold Rau (1932-2006) came to the conclusion that it’s possible to obtain DNA of the extinct animal. It turned out that quagga is not a separate species, but it is a subspecies of the plains zebra with a very similar genome, appeared just 290-120 thousand years ago. “Therefore”, decided Rau, “it is possible to breed the quagga by crossing mares and stallions of its close relative”. Moreover, among plaines zebras are met not fully striped individuals or that ones which instead of black have faint, pale stripes. That occurs more often closer to the aboriginal, drier habitats of the quagga. Reinhold Rau and his colleagues calculated that the breeding the quagga from the zebra would take four generations. For this reason, 19 partially striped zebra-breeders were selected. And 28 years later among the present herd of 89 individuals divided in several populations, are frisking the foals of the fourth generation, by appearance identical to quaggas. The first of them were born even earlier. The independent experts on genetics from the Nelson Mandela University noted that all foals are quite healthy, since the members of the project were able not to exceed the proportion of inbreeding more than 10 percent, but the disappearance of striping has nothing to do with this phenomenon. Over some time the scientists hope to release “revived” quaggas in wild fynbos. Andrei Zhuravlev

ARKIMAGES/QUAGGA PROJECT WWW.ARKIMAGES.COM ARKIMAGES/QUAGGA PROJECT WWW.ARKIMAGES.COM

Квагга Рау: же-ребенок 2011 года рождения и его родители зебры в Вед-дервилле, ЮАР.

A quagga-like foal born in 2011 after zebra-like parents. Quagga Project. South Africa..

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o Andrey Zhuravlev of National Geographic Russia wrote the belwo article on the QPA

Frankfurter Rundschau » Leben » Wissen 19. August 2014

Quaggas Ein Zebra mit wenig Streifen Von Ralf E. Krüger

Das Burchell-Zebra jst hinten nur schwach gestreift. Foto: picture alliance / WILDLIFE

Die seit langem ausgestorbenen Quaggas werden seit 27 Jahren rückgezüchtet.

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Sie sehen ein wenig aus wie Zebras, denen im Regen die aufgemalten Streifen abhandengekommen sind: Quaggas zogen noch Ende des 17. Jahrhunderts in großen Herden über die Steppen Südafrikas. Doch für die europäischen Siedler waren sie nur unnütze Konkurrenten um Weideland – gnadenlos wurden die wie eine Mischung aus Pferd und Zebra wirkenden Tiere ausgerottet. Das letzte Quagga starb im August 1883 in einem Amsterdamer Zoo.

Seitdem galt die Zebra-Form als ausgestorben – bis ein aus Deutschland stammender Zoologe herausfand, dass die Quagga-DNA der des Burchell-Zebras zu sehr großen Teilen entspricht. Mit gezielten Kreuzungen von Zebras mit passenden Merkmalen wurden ab dem Jahr 1987 Quagga-ähnliche Tiere gezüchtet. Das Projekt faszinierte viele, rief aber auch erregte Debatten und Widerspruch hervor. Heute ist es still geworden um das Quagga-Projekt – obwohl es gerade auf einen Höhepunkt zusteuert.

„Das Projekt ist auf Kurs, aber wir sind noch nicht am Ziel“, sagt Angela Gaylard von Südafrikas Naturparkbehörde SANParks. „Es ist ein laufender Prozess und daher schwer zu sagen, ob wir schon ein Quagga haben; aber wir haben nach vier Generationen immerhin acht bis zwölf Quagga-ähnliche Tiere, denen allerdings noch ein wenig die dunkelbraune Farbe fehlt.“ Die komme nun aber durch, die anstehende fünfte Generation sei entscheidend für den Erfolg – genau wie es der Initiator des Projektes, Reinhold Rau, einst vorhersagte. Gaylard ist überzeugt: „Rau hatte mit seiner Hypothese in allen Punkten Recht“.

Es gebe den Beweis bereits, lassen Mitarbeiter des Quagga-Projekts durchblicken. „Wir werden nach unserem Jahrestreffen Ende August die Tatsache bekanntgeben, dass wir bereits

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ein Fohlen der fünften Generation haben und dann die weitere Strategie erörtern“, erklärt Projektmanager Bernard Wooding. „Es handelt sich um ein weibliches Tier, das wir Frederica getauft haben.“ Auf ersten Fotos hat das im Nuwejaars-Feuchtgebiet bei Bredasdorp geborene Fohlen in der Tat eine braune Farbe – und Streifen nur noch am Vorderteil. Nach Behörden-Angaben gibt es 27 Jahre nach dem Start des Projektes insgesamt 89 Quagga-ähnliche Zebras an zwölf verschiedenen Orten, darunter auf diversen Wildfarmen und auch in Nationalparks. Dennoch verabschiedet sich SANParks aus dem Projekt und belässt nur einen Vertreter im Projektkomitee. Die Gründe sind neben den schrumpfenden Budgets einer durch die Nashorn-Wilderei strapazierten Behörde auch grundsätzliche Bedenken.

Vor allem im Mountain Zebra Park droht demnach das Risiko der Mischung von Arten. „Wir haben Fotografien von Hybriden aus Bergzebras und Quagga-ähnlichen Tieren, und so etwas können wir nicht riskieren; wir müssen den Gen-Pool der Bergzebras rein halten“, sagt Gaylard. Der Nationalpark sei vor allem geschaffen worden, um die vom Aussterben bedrohten Bergzebras zu retten. „Wir haben daher beschlossen, die Quaggas aus dem Mountain Zebra- und aus dem Karoo-Nationalpark herauszuholen“, sagt die Umweltbeauftragte der Naturpark-Behörde. Sie sollen künftig auf Farmen leben.

Die Wissenschaft hatte schon in der Vergangenheit ebenso fasziniert wie irritiert auf die Zebras geschaut, die ihre Streifen verlieren. „Ich halte das Ganze aus wissenschaftlicher Sicht nicht für unbedingt notwendig“, sagt Professor Dan Parker von der zoologischen Abteilung der südafrikanischen Rhodes-Universität in Grahamstown. Er beobachtet den Fortgang des Projekts mit skeptischer Faszination: „Es gibt da die romantische Vorstellung, dass wir das Quagga wieder zurückbringen sollten auf die Welt, weil wir ja an seiner Auslöschung beteiligt waren – also, dass wir das wieder geraderücken sollten.“

Bei aller Skepsis gibt Parker zu: „Zum jetzigen Stand des Projektes bin ich wirklich gespannt, was bei der fünften Generation herauskommen wird“. Auch wenn diese Tiere vielleicht nur optisch wie Quaggas wirken, sieht er immerhin enormes touristisches Potenzial: „Die Leute würden wahrscheinlich eine Menge Geld dafür zahlen, um so etwas zu sehen“, meint er. Bleibt die Frage, wie diese Tiere genannt werden. Beim Quagga-Projekt fand man dafür eine pragmatische Lösung. Wooding sagt: „Wir nennen die Quagga-ähnlichen Tiere Rau-Quagga“. dpa

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Google Translate of above article: They look a bit like zebras, which the painted stripes have been lost in the rain: quagga attracted even the end of the 17th century in large herds across the steppes of South Africa. However, for the European settlers they were just useless competitors to pasture -‐ mercilessly like a cross between a horse and zebra acting animals were exterminated. The last quagga died in August 1883 in an Amsterdam zoo. Since then, was the zebra-‐form to be extinct -‐ until a native of Germany zoologist found out that the quagga DNA of the Burchell's zebras corresponds to a very large extent. With targeted intersections of zebras with matching characteristics in 1987 quagga-‐like animals have been bred from the year. The project fascinated many, but also provoked excited debates and contradiction. Today it has become quiet around the Quagga Project -‐ although it just heading for a climax. "The project is on track, but we are not there yet," says Angela Gaylard of South Africa's natural park authority SANParks. "It is an ongoing process and therefore difficult to say whether we already have a quagga; but we have four generations at least eight to twelve quagga-‐like animals, which, however, still a little lacking the dark brown color "Then they come through but the upcoming fifth generation is crucial for the success -‐. just as the initiator of the project, Reinhold Rau, once predicted. Gaylard is convinced that "Rau had with his hypothesis on all points." There is already evidence, let employees of the Quagga Project hinted. "We will announce our annual meeting by the end of August, the fact that we already have a foal of the fifth generation and then discuss the further strategy," said project manager Bernard Wooding. "It is a female animal, which we have christened Frederica." At first photos that has born in Nuwejaars Wetlands in Bredasdorp foal in fact a brown color -‐ and stripes only on the front. According to authorities figures, there are 27 years after the start of the project a total of 89 quagga-‐like zebras at twelve different places, including on various game farms and even in national parks. Nevertheless, SANParks adopted from the project, leaving only one representative in the project committee. The reasons, in addition to shrinking budgets strained by a rhino-‐poaching authority also fundamental concerns. Especially in the Mountain Zebra Park therefore threatens the risk of the mixture of species. "We have photographs of hybrids of mountain zebra and quagga-‐like animals, and something we can not risk; We have the gene pool of the Mountain Zebra keep inside, "says Gaylard. The national park was created primarily to save the endangered mountain zebra. "We have decided to get the quagga from the Mountain Zebra and from the Karoo National Park," says the Environmental Commissioner of Natural Parks Authority. They should continue to live on farms. Science had already looked in the past as fascinated as irritated at the zebras lose their stripes. "I think the whole thing from a scientific perspective not absolutely necessary," says Professor Dan Parker of the Zoological Department of the South African Rhodes University in Grahamstown. He watched the progress of the project with skeptical fascination: "There is a romantic notion that we should return the quagga back to the world, because we were involved in its extinction -‐ that is, that we should just move back." For all the skepticism Parker admits: "At this stage of the project I'm really excited to see what will come out in the fifth generation." Although these animals act may only look like quagga, after all, he sees enormous tourism potential: "People would probably pay a lot of money for it, to see such a thing," he says. The question remains how these animals are called. When Quagga project was found for a pragmatic solution. Wooding said: "We call the quagga quagga-‐like animals Rau". dpa

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QUAGGA PROJECT ASSOCIATION (INCORPORATED UNDER SECTION 21) · 2015. 8. 22. · 2 TOTAL!HERD!UPDATE!...

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Transcript of QUAGGA PROJECT ASSOCIATION (INCORPORATED UNDER SECTION 21) · 2015. 8. 22. · 2 TOTAL!HERD!UPDATE!...