SC I ENCE ADVANCES | R E S EARCH ART I C L E

ENV IRONMENTAL STUD I ES

1Royal Veterinary College London UK 2Research Institute for Biological SafetyProblems Gvardeiskiy Kazakhstan 3Department of Zoology University of OxfordOxford UK 4Frankfurt Zoological Society Frankfurt Germany 5Association for theConservation of Biodiversity of Kazakhstan Astana Kazakhstan 6Swedish Universityof Agricultural Sciences Umea Sweden 7School of Biological Sciences QueenrsquosUniversity Belfast Belfast UK 8Food and Agriculture Organization Rome Italy9Universiteacute catholique de Louvain Louvain-la-Neuve BelgiumCorresponding author Email rkockrvcacukdaggerPresent address Cornell University College of Veterinary Medicine Ithaca NY 14853 USA

Kock et al Sci Adv 20184 eaao2314 17 January 2018

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Saigas on the brink Multidisciplinary analysis of thefactors influencing mass mortality eventsRichard A Kock1 Mukhit Orynbayev2 Sarah Robinson3 Steffen Zuther45 Navinder J Singh6

Wendy Beauvais1dagger Eric R Morgan7 Aslan Kerimbayev2 Sergei Khomenko8

Henny M Martineau1 Rashida Rystaeva2 Zamira Omarova2 Sara Wolfs1

Florent Hawotte9 Julien Radoux9 Eleanor J Milner-Gulland3

In 2015 more than 200000 saiga antelopes died in 3 weeks in central Kazakhstan The proximate cause of death isconfirmed as hemorrhagic septicemia caused by the bacterium Pasteurella multocida type B based on multiplestrands of evidence Statistical modeling suggests that there was unusually high relative humidity and temperaturein the days leading up to the mortality event temperature and humidity anomalies were also observed in two pre-vious similar events in the same region Themodeled influenceof environmental covariates is consistentwith knowndrivers of hemorrhagic septicemia Given the saiga populationrsquos vulnerability to mass mortality and the likely exac-erbation of climate-related and environmental stressors in the future management of risks to population viabilitysuch as poaching and viral livestock disease is urgently needed as well as robust ongoing veterinary surveillance Amultidisciplinary approach is needed to research mass mortality events under rapid environmental change

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on O

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agorged from

INTRODUCTIONInMay 2015 researchers witnessed a catastrophic disease event causingthe death of some 200000 saiga antelopes (Saiga tatarica tatarica) incalving aggregations across a landscape stretching for several hundredsof kilometers near the Torgai lowland central Kazakhstan (Fig 1 fig S1and the Supplementary Materials) The syndrome attracted globalmedia attention and considerable speculation as to its cause By Juneadult numbers were reduced to around 15 of the pre-calving numbersof this population representing a loss of around 62 of the global pop-ulation of this critically endangered species (1)

Mass mortality events (MMEs) of animals are demographic catas-trophes that can simultaneously affect all life stages and rapidly removea substantial proportion of a population over a short period of timerelative to the generation time of the organism They are often asso-ciated with multiple stressors including highly transmissible infectionsand exposure to toxins or extreme weather alone or in combination(2) There is considerable speculation as to the increasing influence ofecological perturbations from human activities on MMEs (3 4)Understanding and predicting the response of opportunistic microbesto changing environmental conditions and of hosts to growing num-bers of stressors require a much greater emphasis on investigating theecological context of MMEs than hitherto has been the case (5) Thiscalls for a more multidisciplinary or One Health approach (6)

This paper reports one of the first investigations of a major MMEusing this approach providing a strong empirical example of the crit-ical role played by environmental factors inMMEsWe establish the pri-mary cause of death in theMME inMay 2015 affecting the Betpak-dalasaiga population in central Kazakhstan and investigate potential caus-ative and predisposing factors using contemporaneous and historicaldata analysis and insights from the literature On the basis of our find-

ings wemake recommendations for future management and researchfor this species and MMEs in general

MATERIALS AND METHODSResearch approach at the time of the mortality eventGiven the unexpected nature of the disease event there was no priorexperimental design for the study A research team was in the field fornormal monitoring of calving led by SZ As animals started to die re-searchers SW and SZ took observations and samples using the bestavailable methods An emergency response team including RAK andMO attendedwithin 1 week of the first observations ofmortality Theycarried out field postmortems and sampling according to an outbreakinvestigation protocol that had previously been agreed upon based onFood and Agriculture Organisation of the United Nations best practicefor emergency response to disease outbreaks customized for saigaantelopes (7)

Because mortality and morbidity appeared to be 100 for practi-cal reasons we did not attempt random sampling for epidemiologicalanalysis and no healthy animals remained for comparison Unaffectedanimals and survivors of theMME (approximately 30000 individualsbased on post-MME expeditions and aerial surveys) were either geo-graphically far removed at the time (for example older male groupsoccur to the north at this time of the year) (8) or cryptically locatedaway from aggregations in small herds widely distributed or peripheralto the calving areas Because of the vast landscape neither the preciselocation nor the behavior of these surviving groups could be determined

The selection of carcasses for necropsy was not based on any ran-domization given that the syndrome was so universal and consistentin character It affected a proportion of the aggregations each day witha few initial cases observed but soon affected thousands daily until theend of the die-off which stopped abruptly when all were dead therewas hardly any tailing off of cases Saiga herds during calvingmove upto approximately 2 km each day and the necropsy simply followedthese movements with a number of full postmortem examinations(PMEs) completed on each day It was not possible to catch healthysaigas for comparison of clinical pathology with dead and dyinganimals because the capture technique requires specialized teams

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and no unaffected saigas were within easy range of the teams whichwere situated hundreds of kilometers to the north Unaffected femalesaigas were not observed over the period of mortality

Sampleswere sent to laboratories inKazakhstan and overseas for anal-ysis following normal best practice Once the formal scientific researchcollaboration was established to ensure that the research was carriedout in a systematic and structured manner the characteristics of theoutbreakwere listed by the research teamA set of nonndashmutually exclusivehypotheses for the proximate cause of the outbreak was then developedconsistent with these characteristics These hypotheses were then ex-plored and refined or discarded using a combination of review of theEnglish and Russian language literatures (including texts available onlyin Russia or Kazakhstan) laboratory analyses expert consultation withfield biologists who were present at the time of previous outbreaks con-sultationof archived fieldnotes andmaps follow-up field expeditions andstatistical analysis using a range of data sets of environmental covariates

Clinical and pathological diagnosisAnimals were observed alive from a distance When moribund theywere observed closely and physically examined After death a completepostmortem examination (PME) and sampling were performed onselected cases including adults and calves Before death 26 saigas fromTorgai and 4 fromTengiz (Fig 1)were blood-sampled from the jugularvein using a sterile technique and aliquots of bloodwere stored wholefor parasitological examination and placed in clot tubes for removalof serum For microscopy thin blood smears were prepared freshfixed with 96 ethanol and stained using the Romanovsky-Giemsamethod Given the long distances to the laboratory and the likelihood

Kock et al Sci Adv 20184 eaao2314 17 January 2018

of a delay of more than a week before samples could be processedbiological material was stored in cool boxes or frozen in liquid nitrogenand representative tissues were cut and placed in buffered formal salineSamples from dead saigas included feces gut contents tissues and anyobserved external or internal parasites For bacteriology and virologysamples from liver spleen lungs kidney blood and milk were storedfrozen 26 samples from Torgai and 6 samples from Tengiz were pro-cessed Whole brain and rumen and gut content were taken for plantand toxin studies as were feces and blood for parasite examinationBiological samples were taken to the Research Institute for BiologicalSafety Problems in Gvardeiskiy Kazakhstan for processing Freshtissues underwent polymerase chain reaction (PCR) analysis forthe presence of DNARNA of viral or bacterial pathogens includingmicroscopy of tissue imprint smears stained by Gram and Giemsaisolation of bacterial cultures on nutritional medium microscopy ofcultivated bacteria and identification by biochemical methods andattempted isolation of viruses in cell cultures and identificationthrough electronmicroscopy Full details of the methods used are dis-cussed in the subsequent sections

Polymerase chain reactionRNA was extracted from samples and tested for foot-and-mouth dis-ease virus (FDMV) bluetongue virus and peste des petits ruminantsvirus (PPRV) using the QIAamp Viral RNAMini Kit (Qiagen) DNAwas extracted from samples and tested for viruses (sheep pox Aujeszkyand Visna-Maedi) and protozoa (Theileria Babesia Anaplasma andCoxiella) using theDNeasy blood and tissuemini kit (Qiagen) followingthemanufacturerrsquos protocolsDetection of virusRNADNAof peste des

Fig 1 2015 MME sites showing dates of onset and the location of the two sites studied in detail in the field Inset shows the location of the three saigapopulations within Kazakhstan (x and y units are longitude and latitude respectively)

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petits ruminants (PPR) foot-and-mouth disease (FMD) bluetongueand sheep poxwas carried out usingReal-TimeRT-PCRTarget SpecificReagents (Tetracore) (9ndash12) The PCR was performed following themanufacturerrsquos protocols Amplification and analysis of PCR productswere performed using LightCycler 20 (Roche) Detection of bacterialDNA of Listeria monocytogenes was carried out by PCR using the kitldquoListerrdquo (AmpliSens) again following the manufacturerrsquos protocolsDetection ofDNAor antigens ofPasteurellaMycoplasmaClostridiumtoxinsCoxiella Akabanemalignant catarrhal fever (MCF) andAujeszkyviruses Theileria Babesia and Anaplasma was performed by PCRPCR was completed using the primers and conditions described inthe literature as listed in table S1

Virus isolation and identificationTwo types of cell culture were used for virus isolation primary lambkidney cells (LKCs) and Vero cells (African green monkey kidneycells) A total of 96 tissue samples from saiga (lungs spleen and lymphnodes) were inoculated onto primary LKC and Vero cells The controlflask was inoculated with sterile phosphate-buffered saline only Theinoculated cell cultures were observed twice daily (morning andevening) under an inverted microscope for the appearance of cyto-pathic effects (CPEs) A sample was considered negative for PPRV ifno CPEs were observed within 10 days after inoculation In the case ofcells where there were no CPEs the inoculated cultures were subjectedto freezing and thawing three times to disrupt the intact cells (blindpassages) and 1ml of this suspension was added to a new 25-cm2 flaskof a confluent monolayer of cells A sample was considered negative ifno CPEs were observed after three blind passages The virus isolatesidentified by characteristic CPEs observed on LKC and Vero cellsand the presence or absence of virus were confirmed by testing the cellculture supernatant using PCR and by electron microscopy

Electron microscopySamples of tissues (lungs spleen and lymph nodes) from all the deadsaigaswere examined by electronmicroscopy Preparations for electronmicroscopy were prepared by negative staining with 2 phosphotung-stic acid at pH 68 to 70 Virus was isolated from the tissue material byultracentrifugation at 35000 rpm for 45min from the clarified homog-enate Virus adsorption to mesh procedures used the sputtered carbonsubstrate formvarovoy added to potentially virus-containing fluid(drop) placed on the well of the Teflon plate Adsorption time was10 min After sample adsorption the mesh contrasted with a drop ofphosphotungstic acid for 5 min and after drying the sample wasexamined under a JEM-100 CX II electron microscope (JEOL) at anacceleration voltage of 80 kV and increased by 80000 to 100000

Isolation and identification of bacterial isolatesSmears from inner organs and from broth and agar cultures werestained using Romanovsky-Giemsa Gram and Loeffler methyleneblue (13) Isolation of Pasteurella was undertaken by cultivation ofpathological material samples in meat-peptone broth Hottinger di-gest broth and plain agar (IPA)with 5 sterile horse serum To obtainpure cultures of a single bacterial colony type from blood agar andMacConkey agar only bacterial colonies (with the following charac-teristics rod coccobacilli rough or smooth Gram negative with orwith no growth onMacConkey and presence or absence of hemolysison blood agar) were subjected to subculturing Then each bacterialcolony was characterized and further bacterial identification was carriedout using a series of primary and secondary biochemical tests following

Kock et al Sci Adv 20184 eaao2314 17 January 2018

standard procedures (14) Identification of the isolatedPasteurella culturewas conducted according to biochemical indicators including saccharo-lytic andproteolytic enzyme excretion formation of catalase acetylmeth-ylcarbinol ammonia hydrogen sulfide indole lysis of red blood cells andcattle bile and nitrate reduction (13) Typing of the isolates was con-ducted with the use of PCR analysis applying capsular-specific primersfor determining capsular groups A B D E and F (15)

FTA analysisFlinders Technology Associates (FTA) cards were taken from 12 deador dying saigas at the Tengiz site for rapid dispatch to internationalreference laboratories at the Pirbright Institute (PI) and the Friedrich-Loeffler Institute (FLI) for examination including use of genomic tests[next-generation sequencing (NGS)]

At PI the following procedures were followed Samples of driedblood spots (approximately 2 cm in diameter) were received from12 animals with two spots provided per animal These samples weretaken postmortem to eliminate the possibility of laboratory con-tamination RNA was extracted by taking a 1-cm-diameter disc ofblood spot and incubating in 200 ml of RLT lysis buffer (with 1b-mercaptoethanol) (Qiagen) before incubating at 56degC for 15 minEach sample was processed individually with decontaminationperiods of at least 30 min between the handling of each sample Afterthe incubation the supernatant was then decanted off and tested forthe presence of glyceraldehyde-3-phosphate dehydrogenase (GAPDH)using a previously published qualitative real-time reverse transcription(RT)ndashPCR assay for porcine GAPDH (16) These results provided anindication of the suitability of recoveredextracted nucleic acid withinthe sample for further pathogen testing by real-time RT-PCR andNGS Testing was performed with diagnostic real-time RT-PCR assaysused by both vesicular disease and non-vesicular disease reference lab-oratories at PI (VDRL and NVDRL respectively) Assays used werespecific for FMDV (9) bluetongue virus (10) PPRV (11) capripox(12) and epizootic hemorrhagic disease virus In each case 5 ml ofextracted RNA was tested in duplicate using established protocolswithin both VDRL andNVDRL Assays were run on an ABI 7500 Fast[with the exception of the FMDV assay which was run on anMX3005(Agilent)] All assay runs were validated to standards described withinin-house standard operating procedures (SOPs)

At FLI the following procedures were followed Eleven samples ofdried blood spots on FTA cards were received For whole-genome se-quencing RNA was extracted and was used as a template for double-stranded cDNA synthesis (Roche) The Covaris M220 ultrasonicatorwas used for DNA fragmentation of 05 to 1 mg of double-strandedDNA to an average size of about 500 base pairs (bp) For library prep-aration of the fragmented DNA a GeneRead DNA Library L Core Kitand GeneRead Adapter I Set A 12-plex (both fromQiagen) were usedfollowed by manual size selection using AMPure XP magnetic beads(Beckmann Coulter) The quality of the library was checked on a Bio-analyzer 2100 (Agilent Technologies) using a high-sensitivity DNAchip and corresponding reagents Quantity was determined by quanti-tative PCR with the Ion Library TaqMan Quantitation Kit (Life Tech-nologies) After emulsion PCRwith aOneTouch 2 device and Ion PGMHi-Q OT2 reagents (both from Life Technologies) sequencing wasperformed on an Ion Torrent Personal GenomeMachine (PGM)usingan Ion PGM Hi-Q Seq Kit (Life Technologies) for 400-bp reads Rawsequence data were first analyzed using Reliable Information ExtractedfromMetagenomics Sequential Datasets (RIEMS) (17) and additionallyassembled using the Genome Sequencer software suite (v30 Roche)

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HistopathologyA set of fixed tissues was sent from the Torgai site to the Departmentof Pathobiology at the Royal Veterinary College for histopathologicaldiagnosis the remaining tissues from Tengiz and some from Torgaiwere processed at Research Institute for Biological Safety ProblemsKazakhstan (RIBSP) for histology and some fresh tissuewere processedfor electron microscopy Wax blocks were later sent to the Royal Veteri-naryCollege and further processed including rewaxing slide preparationand histological examination A complete set of histological slides wassent to an experienced wildlife and comparative pathologist at theWakefield School of Medicine Department of PathologyComparativeMedicine Institute in North Carolina for review

FISH analysisA set of fixed tissues from several different saigas was sent to the Uni-versity of Bristol School of Veterinary Science for examination of thedistribution of bacterial populations using fluorescence in situ hydrid-ization (FISH) Paraffin-embedded slide-mounted tissue sampleswere dewaxed in Histoclear for 10 min followed by 3-min hydrationsin 100 90 and 70 ethanol and finally rinsed inwater for 3min Slideswere hybridized with a single probe for either P multocida (non-specific binding all serogroups) or Clostridium (1 ml of probe persample) with a FISH buffer (09 M NaCl 002 M tris-HCl 001 SDSand 25 formamide) in a thermos cycler at 95degC for 10 min and at46degC for an hour Slides were washed dried and mounted under acoverslip with Vectashield (Vector Laboratories) Fluorescing bacteriawere then examined in 10 fields of view in each tissue under times400 totalmagnification

Mineral composition analysisAsubset of saiga fromTengizwas sampled for tissuemineral analysis toevaluate possible micronutrient deficiencies Fresh liver was collectedfrozen and tested at RIBSP for tissue copper molybdenum cobaltzinc and iron using standard methods for an inductively coupledplasma mass spectrometry (ICP-MS) analysis as follows 02 to 03 gof the sample was weighed (Shimadzu AY 220 scale) in a Teflon cu-vette The cuvette with the sample was placed in a Teflon autoclaveand 5 ml of nitric acid and 1 ml of hydrogen peroxide were addedand after termination of the intensive reaction the autoclave was sealedThe autoclaves were placed into the microwave system SpeedWaveFour Technology (Berghof Products) and decomposed using theprogram recommended by the manufacturer for the decompositionof biological samples At the end of the program the autoclaves werecooled to room temperature and depressurized and the resulting solu-tion was transferred to a 500-ml volumetric flask filled up to the markwith water and thoroughly mixed Afterward metals were determinedin the samples through ICP-MS Along with the samples analyzed aldquoblankrdquo solution was prepared without any sample material whichwas treated with all stages of sample preparation and analysis

The samples were analyzed for Fe Co Cu Zn andMo using ICP-MS in the Agilent 7500a mass spectrometer Standard solutions forISP-MS were used to calibrate the mass spectrometer and obtain cal-ibration characteristics The calibration solutions were prepared bysuccessively diluting standard solutions with 25 HNO3

Data acquisition and processing for modelingThe outcome variableThe aim of the statistical analysis was to predict the probability of anMME (cases) versus a normal calving event (controls) Our case sites

Kock et al Sci Adv 20184 eaao2314 17 January 2018

were those corresponding toMMEs in 1988 1981 and 2015 Locationsand dates of onset in 2015were recorded at two sites by RAK and SZInformation for other sites came from rangers and other key infor-mants in the field (fig S1) In the case of the 1988 and 1981 eventsinformation was obtained from literature and maps produced at thetime (1981 Institute of Zoology and Department of Reserves andHunting 1988 Institute of Zoology andBetpak-dala StateHuntingOr-ganisation) Exact calving locations were provided by the Associationfor the Conservation of Biodiversity of Kazakhstan (ACBK) for the pe-riod 2008 to 2016 from field expeditions and telemetry data from col-lared animals Other more approximate calving sites were recordedfrom descriptions available in the annual official saiga aerial andground monitoring reports by the Institute of Zoology and HuntingAgency of Kazakhstan (18) Of the resulting 214 sites the climate dataused in this analysis were available for 135 sites [29 of which includedestimated dates of onset (20 cases 9 controls) and 106 of which lackeddates (4 cases 202 controls)]Predictor variablesOur ldquozero hourrdquo is the start of calving or for MME the day of theindex case and all predictors were aggregated over specified periodsup to these dates MMEs in saigas appear from the literature to bestrongly associated with calving (8) We used the onset of calvingrather than peak calving to focus on environmental conditions beforethe onset of disease rather than when it may already have taken hold

Field observations from 2015 suggest that at an individual levelthe course of the disease from the first visible signs of depression todeath occurred in the course of a few hours In addition the MME ateach calving site occurred over the course of a number of days Thesefactors are strongly suggestive of a relatively recent common riskfactor Evidence from the literature suggests incubation periods forhemorrhagic septicaemia (HS) lasting from 12 hours to several days(19) These factors suggest that external triggers may have been im-portant anytime from several days to approximately 12 hours beforethe onset of clinical signs in the index case Uncertainties in onset datessuggest that it is better to err on the side of longer periods and sopredictor variables were generated for 3 5 and 10 days before onset

Given the large geographic scale of the study range of variables tobe covered long time series coverage and high resolution the dailyEuropean Research Area (ERA)ndashInterim reanalysis data set producedat the European Centre for Medium-Range Weather Forecasts wasselected for this analysis (20) Daily aggregates (means maxima mini-ma or totals)were generated fromraw3or6hourly data for temperaturedew-point temperature soil moisture snow depth maximumwind gustand precipitation Because of uncertainties in precipitation data from thissource interpolated gauge-based products from the Global PrecipitationClimatology Centre (GPCC) which are independent of ERA datawere also used although these were available only from 1988 onward(21) For investigation of long-term anomalies at single sites an addi-tional lower-resolution reanalysis data set from the National Centrefor Environmental Prediction (NCEP) was also used because it coversthe longer time period from 1948 to 2016 (22)

Normalized difference vegetation index (NDVI) anomaly databased on Systeme Probatoire pour lrsquoObservation de la Terre (SPOT)and PROBA-V data going back to 1998 were supplied by FH andJR at the Universiteacute catholique de LouvainndashLifeWatch Wallonia-Brussels (WB) project (23) Snow anomaly datamdashunusual values at thedate of observation compared to mean probability of snow presencemdashwere used to look for unusual variation in winter (for example winterlength severity and sudden cold shocks) and likely to be related to spring

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NDVI patterns derived from filtered MODIS data (24) These data setscover periods from 1998 and 2000 to 2016 respectively and thus in-clude only 2015 MME sites and a set of controls An earlier data setofNDVI anomalies derived fromGlobal InventoryModeling andMap-ping Studies data (25) was provided by the LifeWatch project team forthe period 1982 to 1997 covering the 1988 MME

Data extraction and processingValues of climate metrics at saiga MME and calving sites were extractedfrom the daily rasters using a polygon shapefile for sites available from2008 onward (which represented estimates of the actual size and shapeof the aggregations) For the older sites identified as point data from theliterature means were extracted using buffers of 6 km corresponding tothemedianpolygon size for those siteswhichwere available in that format

From the extracted daily climate data various aggregate metrics(totals maxima minima or means of daily variables depending onthe metric in question) were produced over 3 5 and 10 days beforeonset of MME or calving In the case of precipitation in addition toproductionof sum totals over the days before onset the number of dayswith nonzero precipitation was counted because the duration of wetweather may be more important than the actual total rainfall in milli-metersMetrics of temperature variability in the days to onset includeddaily temperature variation (difference between daily maximum andminimum temperatures) and overall temperature variation (differencebetween minimum daily temperatures) over 3 5 and 10 days beforeonset or calving

The ERA-interim daily snow depth variable was used to calculatethe date of snowmelt by finding the last three consecutive days of snowcover of the season Variables measuring the length of snow cover(total days of snow cover from 1 January to last snow melt) and daysbetween end of last snowmelt and calvingonset were then producedThe extracted 7-day LifeWatch-WB snow and NDVI anomaly datawere interpolated to daily values These were then used to calculateaggregates over various periods before the date of onset or calvingand for fixed periods of the year (for example snow anomaly for thelast week of March and NDVI anomaly in the last week of April)

The process described above depended on knowing dates for onsetof calving and MME However calving dates were missing for manysites In these cases an onset date of 9Maywas used because this is theaverage date of start of calving for those sites for which dates wereavailable For sites having onset dates metrics were aggregated bothbased on actual dates andusing an onset date of 9May for comparison

The resulting database listed 135 siteswith climatemetrics aggregatedin differentways and over differentmultiday periods up to 9May witha second set of these same variables aggregated using actual onset dateswhere these were available In addition the database held informationon calvingMME latitude and longitude for each site

Statistical analysisUnivariate analysisWe first conducted visual plotting (box plots) of all candidate variablesat case and control sites to select those that appeared to show relation-ships with the outcome variable Because of the structure of the datathe results of t tests to compare means would have been unreliableBayesian approaches were therefore used to compare means takinginto account the effect of year using the BRMSpackage for R (26) Lastwe conducted simple t tests for differences in means between MMEand calving sites in 1988 alone the only year for which both types ofsite were available

Kock et al Sci Adv 20184 eaao2314 17 January 2018

Multivariate analysisFrom results of the univariate analysis we selected a subset of eightvariables which both appeared to present differences between casesand controls and represented different types of climatic phenomenaPrincipal components analysis (PCA) was then applied to these varia-bles resulting in the reduction of the data set into twomajor dimensionsThe eight selected climate variables and the PCA dimensions were bothused to build multivariate models again using hierarchical Bayesianapproaches with year as a random variable Latitude was also includedin these models to account for spatial autocorrelation

In the case of models using ldquorawrdquo climate variables all predictorswere standardized using z scores This enabled direct comparisons ofcoefficients and use of a singleweakly informative prior which assumeda normal distribution of coefficients with a mean of 0 and an SD of 3Initially selected variables were included in the model Those with thesmallest coefficients and having confidence intervals crossing zero wereremoved one by one and the model was rerun each time until onlysignificant variables were left At each step the WAIC (Watanabe-Akaike or widely applicable information criterion) was generatedand used to compare the models (27) In the case of models usingPCA results dimensions 1 and 2 capturing the majority of variationand latitude were entered into models and insignificant variables wereremoved The same prior was also used here

Because conditions were known to be different between MMEyears models were run using subsets of the data set (i) removingMME sites from 1981 and (ii) removing MME sites from 1981 and1988 These models had convergence problems or did not producesignificant results Thus in the end only the full data set includingall data for 1981 1988 and 2015 was used Taking this full data setmodels were run using climate variables aggregated over variousperiods to 9 May for all sites as well as for the ldquoreal daterdquo data set inwhich they were aggregated to the actual onset date (where available)or 9 May (if not) In the latter case only those MME sites having es-timated real onset dates were used and thus only at controls weredates set to 9 MayClimate anomalies at single sitesIn addition to the modeling of MME probability at case and controlsites we also explored long-term climatic variation at single die-offsites to understand the extent to which climatic conditions at these siteswere exceptional inMMEyears focusing on those variables that seemedimportant from the modeling This was conducted using ERA dataaggregated over the first and second halves of May and NCEP datafor the month of May

RESULTSDescription of the 2015 MMEIn each of the two sites that were intensively monitored (Tengiz andTorgai 8000 and 62000 animals respectively Fig 1) the die-off lastedapproximately 9 days Morbidity and mortality were estimated at100 although it is possible that a few animals survived The affectedaggregations contained pregnant and recently calved females theircalves and some young males

Carcass distribution in the main areas of mortality showed a re-markably even spread of animals with a spacing of approximately30 to 50 m between individual adults consistent with becoming illwhile grazing and then dying on the spot (fig S2A) Individual animalsrsquobehavior changed from apparent normality (able to run and graze) tosuffering from general depression lethargy and hindlimb weakness

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and ataxia while grazing or standing Sicker animals were recumbentwith some dyspnea and grunting frothy fluid or saliva forming aroundthe mouth and terminal diarrhea frequently with blood and urinestaining of the soil (fig S2B) Most died within a few hours of onsetof clinical signs

Noother wildlife species were seen ill or dead in large numbers norwere there significant excess livestock deaths or human disease in thevicinity over this time period This was confirmed during follow-upexpeditions to villages and farms in the region in summer 2015 andspring 2016 The temporal and spatial distribution of the outbreaksuggested that horizontal transmission of a contagion was unlikelyto have been the cause Calves were observed to suckle until and evenaftermaternal death (fig S2C) and then to dieDelayed death of calveswas consistent with disease transmission from themother rather thanhorizontal transmission of an infectious agent through saiga aggrega-tions which would have affected the calves before or at the same timeas their mothers

A number of saigas were blood-sampledwhilemoribund and a fullPME was performed on 33 animals (24 adult females and 9 calves4 male 5 female) with an even split in necropsies between the twomonitored sites microbiological sampling included 32 saigas (26 fromTorgai and 6 from Tengiz) PMEs were performed as soon after deathas possible The gross pathology was similar in animals from both ge-ographical sites Animals were generally in very good body conditionwith 76 having abundant mesentericomental fat (fig S2D) whichin small ruminants correlates significantly with live weight and bodycondition (28) In the 10 adult animals necropsied immediately afterdeath all organs were diffusely congested and there was bloodstainedfluid in serous cavities (fig S2D) generalized hemorrhages ecchymoses

Kock et al Sci Adv 20184 eaao2314 17 January 2018

and petechiae in the subcutis (fig S2E) hemorrhages onmultiple serosalsurfaces [extensively within the sub-endocardium of the heart (fig S2F)andwithin lungs] lymphnodes (fig S2G) and skeletalmusculature Onoccasion there was severe edema and congestion of the lung (fig S2H)Many cases showed catarrh congestion and intense reddening of theintestinal mucosa with multifocal subserosal hemorrhages and con-gested vasculature (fig S2I)

The preliminary diagnosismade by experienced attending veterinar-ians (RAK andMO) based on the clinical presentation and necropsywas peracute HS as described in the literature (29) This diagnosis wassupported by a pure profuse culture of P multocida serotype B from 32microbiologically sampled saiga which included fresh blood milk andtissues taken from lung liver spleen and kidney tested in the researchlaboratory ofKazakhstanrsquos Research Institute for Biological Safety Prob-lems with similar findings to other in-country reference laboratoriesMicroscopic examination of multiple tissue samples examined at theRoyal Veterinary College found necrosuppurative hepatitis splenitisand lymphadenitis with intralesional and intravascular Gram-negativebacteria (Fig 2 and the SupplementaryMaterials) In lungs there wereperivascular and intra-alveolar hemorrhage and edema These find-ings are consistent with a diagnosis of HS caused by P multocida (29)

Extensive PCR testing of tissue samples from the same 32 individ-uals sampled for microbiology for the presence of viruses in severallaboratories found one positive for sheep pox and no evidence for arange of other viruses (table S1 and the Supplementary Materials) Inthree saigas sampled in Tengiz lung tissues showed evidence of intra-cytoplasmic bronchial epithelial inclusions which were suggestive ofParamyxoviridae however ascribing a specific virus is highly speculativeand to date this finding is inconclusiveMicroscopy of the blood smears

on October 1 2018

iencemagorg

Fig 2 Photomicrographs showing multifocal acute degenerative tissue changes with the light blue staining indicating Gram-negative bacteria consistentwith the pure isolation of P multocida (A) Liver necrosuppurative hepatitis random with intralesional bacteria (arrow) (B) Spleen splenitis necrotizing with bacterialemboli (C) Lung perivascular hemorrhage (arrow) and edema (D) Lymph node lymphadenitis necrosuppurative

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from sick saigas revealed Hemosporidia at various stages of develop-ment this was confirmed by PCR Of 23 tested blood samples DNAof the theileriosis pathogen (Theileria annulata) was identified in 11with negative results for anaplasmosis and babesiosis

FISH for three animals was consistent with a breach of themucosalimmune barrier and systemic invasion of P multocida rather than ageneral invasion of mucosal bacteria into the body which is found indying or recently dead animals (fig S3) The immediacy of the PMEmade this investigation possible and relevant

The proximate cause of death in thisMMEwas therefore amassiveperacute HS However given the extraordinary mortality and extentthis was not considered a sufficient explanation To account for suchrapid concurrent mortality of distant aggregations latent infectionwith P multocida would have to be common across the entire saigapopulation Some prior influence seemed likely priming the majorityof individuals for a breakdown of immunity to opportunistic bacteriaor increasing bacterial growth andor virulence

Exploration of potential underlying cofactorsTo provide a more comprehensive explanation for such an extraordi-nary phenomenon a multidisciplinary approach was used possiblehypotheses for the observed events were developed from the literatureand field observations and were systematically tested (table S4) Thesehypotheses focused on factors that trigger pathogen invasion in theshort term although longer-term influences on P multocida carriageand host susceptibilitymight also be important in the disease dynamicsGiven that causation might be multifactorial competing hypotheseswere not mutually exclusive

The existence of P multocida as a commensal organism in healthysaigas (30) near-simultaneous onset of clinical signs within and be-tween large groups of animals and our understanding of HS fromthe literature (31) all suggest a possible environmental trigger Saigacalving aggregations in this population have beenmonitored regularlysince the 1970s A review of the literature and consultation with saigafield biologists identified two previous large-scale mortality eventswhich could possibly be ascribed to HS in 1981 and 1988 (table S2and the Supplementary Materials) Although pathological evidenceof this syndrome was not reported at the time the clinical signs andmorbidity were similar to those in 2015 especially in 1988 (fig S2J)and P multocida of the same phylogeny and pathogenic potential wasisolated in each case (table S2) In 2015 no disease-free sites were ob-served in 1981 although many animals survived their locations areunknown whereas in 1988 locations of unaffected and affected siteswere documented Using these three cases the impact of environmentalcovariates on the probability of an MME versus a normal calving eventwas explored using statistical modeling

The data set represents a typical case of ldquorare eventsrdquo having smallsample sizes a strong imbalance in the number of case and controlsand autocorrelation issues First MME and non-MME site data werespatially and temporally correlated that is there were many loca-tions from the same year and locations of MME sites were clusteredSecond there was perfect separation between MME and non-MMEsites for certain environmental variables that is MME sites had non-overlapping values of certain variables with non-MME sites Lastthere was pseudo-replication in the data set that is locations werenot independent because many were from the same year but thenumber of levels of year compared to the overall size of the data setprecluded its use as a random variable in standard mixed models Toresolve these issues we used Bayesian generalized linear hierarchical

Kock et al Sci Adv 20184 eaao2314 17 January 2018

models which enabled us to incorporate a random effect structurefor year (32)

On the basis of our hypotheses and evidence concerning triggers ofpasteurellosis from the literature we tested for any differences betweenvarious measures of temperature precipitation wind speed atmo-spheric moisture soil moisture and vegetation greenness (using theNDVI) in 5 to 10 days before die-off and both NDVI and snow coverin the preceding weeks using univariate tests (fig S4 and table S5)A subset of these variableswith good explanatory power was then usedin the regression models both as raw variables and combined asdimensions within a PCA (Fig 3 and fig S5)

In all analyses average maximum daily relative humidity averageminimum daily temperature and average maximum daily dew-pointtemperature showed the strongest positive relationships with theprobability of a die-off in particular die-off sites were unusually hu-mid and in 2015 they were unusually warm Of the Bayesian multi-variate models the strongest associations emerged for the 10-dayaggregates of the days preceding the die-off whether natural climatevariables or PCA dimensions were used (see the SupplementaryMaterials) The final model contained only temperature and humid-ity metrics There was a clear threshold association with humiditywith most die-offs occurring at a mean average maximum daily rel-ative humidity ofmore than 80 (Fig 4A)mean daily relative humid-ity was 846 plusmn 17 at die-off sites and 712 plusmn 17 at control sitesThere was a weak positive association betweenminimum temperatureand die-off events (Fig 4B and the Supplementary Materials)

Long-term climate anomaly data at the Kostanai cluster of sites(affected in all three MME years) support these findings (table S5 andthe Supplementary Materials) At this site atmospheric moisture inMay 2015 not only was extreme but also exhibited the highest recordedvalues of two long-term time series for certainmetrics (covering 1948 to2016 and 1979 to 2016) In 1981 in the second half of May humidity

Fig 3 Kernel density map of the first two components of a PCA of selectedclimatic variables in the 10 days to disease onset (or 9 May for controls forwhich exact date is not available) showing separation of die-off sites fromother sites See fig S5 for indications of the relative contribution of each climatevariable to these two components

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levels were above the 95th percentile precipitation was the highest ofthe 1979 to 2016 time series and minimum temperature was unusuallylow for the time of year Conditions at 1988 MME sites appear less ex-treme than in the other two MME years however in that year theanimals were in very poor condition following a harsh winter and somay have been more vulnerable Average minimum daily temperaturewas significantly higher at the seven case sites than at the four controlsites in 1988 (cases 62degC controls 40degC t = minus432 P = 003) as wasaverage daily maximum humidity (cases 85 controls 82 t =minus3623 P = 0006) In contrast although total precipitation was overallvery high in 1988 it did not differ significantly between control and caselocations

tober 1 2018

DISCUSSIONMMEs in the context of saiga life historyGiven the precedents from other MMEs in the literature particularlyregardingHS events our expectationwas that certain combinations ofclimatic factors might be associated with the 2015 die-off but wouldbe unlikely to fully explain it (table S4) We found strong but notcomplete differentiation between climatic conditions in sites withand without MMEs (Figs 3 and 4) HS caused by P multocida hasbeen linked to humidity and high temperatures in other studies andspecies (33ndash35) but the total numbers of dead animals geographicscale and mortality rate in other recorded outbreaks do not even ap-proach the levels seen in saigas (table S2) Therefore additional factorsmust also be at play

The saiga antelope appears particularly vulnerable toMMEs espe-cially around calving having suffered from several such episodes inthe recorded past (table S2 and the Supplementary Materials) al-though we found no record of MMEs in folklore or pre-Soviet litera-ture Apart from the 2015 event recent years have seen high levels ofdisease-induced mortality in other saiga populations in 2010 aroundtwo-thirds of a calving aggregation of 20000 in the Ural populationdied of a peracute respiratory disease with bloat and this was followed

Kock et al Sci Adv 20184 eaao2314 17 January 2018

in 2011 by a smaller die-off of several hundreds of saiga with similarclinical signs immediately after calving grazing in the exact same lo-cation as the earlier MME suggesting a site-specific cause Pasteurel-losis was implicated based on clinical signs and bacteriology but verylittle pathology was undertaken putting some doubt on the diagnosis(36) The endemic Mongolian saiga subspecies is currently expe-riencing high levels of mortality from PPR (37 38) caused by a mor-billivirus of the Paramyxoviridae family P multocidawas concurrentlyisolated from tissues but in this case P multocida is not implicated inthe primary pathology

This propensity for MMEs may be a result of the speciesrsquo lifehistory strategy of very high investment in reproduction in a harshcontinental climate The species has the largest recorded mass at birthas a proportion of maternal mass of any ungulate (39) producing pre-cocious calves and enabling large-scale seasonal migrations trackinggreenery across thousands of kilometers (40) High mortality as a re-sult of hard winters (dzhuts) where ice forms over snow and thus re-stricting access to pasture and summer droughts is well documentedand the species has a history of rapid recovery from low numbers (8)However high levels of poaching since the 1990s have depleted popu-lations holding out the possibility that anMME could reduce numbersbelow the level at which recovery is possible (41)

Future research needsThemechanisms bywhich climatic factors triggered bacterial invasionin the saigaMMEs remain unknown A trigger factor such as stress orinfectionwith a paramyxovirus is usually invoked inPmultocida out-breaks (42 43) but there is no serological evidence for previous viralinfection other than Akabane in the population that died in 2015based on samples collected opportunistically from 2012 to 2014 andtested for bluetongue virus PPRV and Akabane and Schmallenbergviruses (44) Despite the negative results to date there is still thereforethe possibility of an undiagnosed predisposing infection microbiomeperturbation or environmental change that reduced the resistance of aproportion of the individuals enabling bacterial opportunism In the

Fig 4 Probability of die-off related to selected environmental variables in the 10 day period to onset 1979 to 2015 (A) Fitted values for the probability of adie-off event against mean maximum daily relative humidity in the previous 10 days with the three die-off years in different colors (B) Fitted values for the probabilityof a die-off event against mean minimum daily temperature in the previous 10 days with the three MME years in different colors

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light of the emerging threat fromPPR and the presence ofTheileria inapproximately 40 of the sampled saigas (see the SupplementaryMaterials) interactions between saigas and livestock in a changing so-cial and ecological environment also require further study

The fact that Pasteurella strains of near-homologous genotype arefound in both apparently healthy and sick populations of saigas through-out their range and over decades suggests that latent infection withendemic strains occurs which are all potentially virulent Studies of bac-terial virulence in controlled environments could cast light on the mech-anisms by which these strains become virulent or new strains emerge

Recent history suggests that the saiga must be managed with thehigh probability of future MMEs in mind this requires investmentin preventative measures where possible (for example livestock vac-cination for PPR) strong antipoaching actions so that populations arelarge and resilient enough to withstand large-scale mortality and asustainable landscape-level approach to coexistence between saigaslivestock and people to enable its migratory lifestyle to continue

The fact that P multocida infection in saigas as in bovines (31)appears strongly linked to high humidity and temperature is of con-cern going forward given that a climate changendashinduced increase intemperature is projected for the region over the short tomedium term(45 46) and evidence for recent change is strong (47 48) Predictedprecipitation trends are uncertain and unreliable (46) although somemodels do suggest possible increases over the saiga range particularlyin winter (45 47) Although recent observations do not yet reflect thesepredictions with any certainty (48) there is some evidence to suggestincreased springprecipitation innorthernKazakhstan since 1980 in com-parison with the preceding 30-year period (49) leading to increased airhumidity Predicted increases in extreme rainfall events (45) and abruptvariation in primary productivity (50) also suggest that saigasmight haveto adapt to increased climatic variability in the future affecting resourceacquisition and migration patterns (18) as well as disease risks

on October 1 2018

gorg

CONCLUSIONSThis study illustrates the power of a multidisciplinary collaborativeapproach to investigating MMEs the importance of understandingthe contextual factors as well as the proximate cause and taking a his-torical evidence-based approach to investigations A narrow focus onetiology ofMMEs could fail to elucidate causation where this involvesmultifactorial interactions between pathogens hosts and environ-ment The scale and nature of this event also point to the need forongoing scientific and veterinary monitoring of wildlife populationsand the need to be prepared for rapid and rigorous responses to dis-ease outbreaks when they occur in the absence of a research presenceat the time of disease onset little could have been said about the epi-demiology of the 2015 event

SUPPLEMENTARY MATERIALSSupplementary material for this article is available at httpadvancessciencemagorgcgicontentfull41eaao2314DC1Supplementary Textfig S1 Locations of the three P multocidandashassociated disease events (1981 1988and 2015) in the Betpak-dala population and control sites at which calving proceeded withouta die-off since 1979 used in the climate analysis (x and y units are longitude and latitude)fig S2 Photographs depicting the die-off of saiga and their clinical signs and pathologyfig S3 Fluorescence in situ hydridization (FISH) photomicrographs showing position offluorescing P multocida bacteriafig S4 Box plots for cases (die-off sites) and controls (no die-off) using the full data set with realdates of onset if available or 9 May if not showing the relationship between casescontrolsand selected climate metrics aggregated over 10-day periods before onset

Kock et al Sci Adv 20184 eaao2314 17 January 2018

fig S5 Contributions of variables to components 1 and 2 of the PCA using the full data setwith real dates of onset if available or 9 May if nottable S1 PCR primers used for microorganism detectiontable S2 A summary of the largest MMEs in saiga attributed to Pasteurellaceae-relatedsyndromestable S3 Results of an ICP-MS analysis of livers (ww) of three dead saigas from May 2015(Tengiz group)table S4 Assuming a diagnosis of HS as a primary cause of death this table is a list of possiblestressors which may cause suppressed immunity in the host or increased virulence andinvasion of a commensal parasite such as P multocida subsequent septicemia in infectedhosts andor enhanced transmissiontable S5 Comparison of means for cases and controls using the full data set (all MME years)real dates of onset or 9 May and climate metrics aggregated over the 10 days to onsettable S6 Long-term climate anomaly data at Kostanai sites (ERA data using actual die-off siteNCEP data using pixel covering entire Torgai area)

REFERENCES AND NOTES1 H Nicholls Mysterious die-off sparks race to save Saiga antelope Nature (2015)

doi101038nature2015176752 S B Fey A M Siepielski S Nussleacute K Cervantes-Yoshida J L Hwan E R Huber M J Fey

A Catenazzi S M Carlson Recent shifts in the occurrence cause and magnitude ofanimal mass mortality events Proc Natl Acad Sci USA 112 1083ndash1088 (2015)

3 C D Harvell K Kim J M Burkholder R R Colwell P R Epstein D J GrimesE E Hofmann E K Lipp A D M E Osterhaus R M Overstreet J W Porter G W SmithG R Vasta Emerging marine diseasesmdashClimate links and anthropogenic factorsScience 285 1505ndash1510 (1999)

4 K F Smith D F Sax K D Lafferty Evidence for the role of infectious disease in speciesextinction and endangerment Conserv Biol 20 1349ndash1357 (2006)

5 D M Tompkins S Carver M E Jones M Krkošek L F Skerratt Emerging infectiousdiseases of wildlife A critical perspective Trends Parasitol 31 149ndash159 (2015)

6 D A Travis P Sriramarao C Cardona C J Steer S Kennedy S Sreevatsan M P MurtaughOne medicine one science A framework for exploring challenges at the intersection ofanimals humans and the environment Ann NY Acad Sci 1334 26ndash44 (2014)

7 CMS ldquoStandard Operating Procedures for detecting and reacting to incidents of healthrisks for and die-offs in Saiga antelopes and other wildlife in Kazakhstanrdquo (Conventionon the Conservation of Migratory Species of Wild Animals 2017)

8 A B Bekenov Iu A Grachev E J Milner-Gulland The ecology and management of theSaiga antelope in Kazakhstan Mammal Rev 28 1ndash52 (1998)

9 J D Callahan F Brown F A Osorio J H Sur E Kramer G W Long J Lubroth S J EllisK S Shoulars K L Gaffney D L Rock W M Nelson Use of a portable real-timereverse transcriptase-polymerase chain reaction assay for rapid detection of foot-and-mouthdisease virus J Am Vet Med Assoc 220 1636ndash1642 (2002)

10 M Hofmann C Griot V Chaignat L Perler B Thuumlr Blauzungenkrankheit erreicht dieSchweiz Schweiz Arch Tierheilkd 150 49ndash56 (2008)

11 C A Batten A C Banyard D P King M R Henstock L Edwards A SandersH Buczkowski C C L Oura T Barrett A real time RT-PCR assay for the specific detectionof Peste des petits ruminants virus J Virol Methods 171 401ndash404 (2011)

12 T R Bowden S L Babiuk G R Parkyn J S Copps D B Boyle Capripoxvirus tissuetropism and shedding A quantitative study in experimentally infected sheep and goatsVirology 371 380ndash393 (2008)

13 OIE Hemorrhagic septicemia in Manual of Diagnostic Tests and Vaccines for TerrestrialAnimals 2016 (World Organization for Animal Health 2016) vol 2 chap 2411

14 P J Quinn B K Markey M E Carter W J Donnelly F C Leonard Veterinary Microbiologyand Microbial Disease (Blackwell Science 2002) pp 137ndash143

15 K M Townsend J D Boyce J Y Chung A J Frost B Adler Genetic organization ofPasteurella multocida cap loci and development of a multiplex capsular PCR typingsystem J Clin Microbiol 39 924ndash929 (2001)

16 D P King A Burman S Gold A E Shaw T Jackson N P Ferris Integrin sub-unitexpression in cell cultures used for the diagnosis of foot-and-mouth diseaseVet Immunol Immunopathol 140 259ndash265 (2011)

17 M Scheuch D Houmlper M Beer RIEMS A software pipeline for sensitive andcomprehensive taxonomic classification of reads from metagenomics datasets BMCBioinformatics 16 69 (2015)

18 N J Singh I A Grachev A B Bekenov E J Milner-Gulland Saiga antelope calvingsite selection is increasingly driven by human disturbance Biol Conserv 143 1770ndash1779(2010)

19 S S Bastianello M M Henton Hemorrhagic septicemia in Infectious Diseases of LivestockJ A W Coetzer R C Tustin Eds (Oxford Univ Press 1994) vol 3 chap 164 1690 pp

20 D P Dee S M Uppala A J Simmons P Berrisford P Poli S Kobayashi U AndraeM A Balmaseda G Balsamo P Bauer P Bechtold A C M Beljaars L van de Berg J BidlotN Bormann C Delsol R Dragani M Fuentes A J Geer L Haimberger S B Healy

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H Hersbach E V Hoacutelm L Isaksen P Karingllberg M Koumlhler M Matricardi A P McNallyB M Monge-Sanz J-J Morcrette B-K Park C Peubey P de Rosnay C TavolatoJ-N Theacutepaut F Vitart The ERA-Interim reanalysis Configuration and performance of thedata assimilation system Q J R Meteorol Soc 137 553ndash597 (2011)

21 K Schamm M Ziese A Becker P Finger A Meyer-Christoffer U Schneider M SchroumlderP Stender Global gridded precipitation over land A description of the new GPCC firstguess daily product Earth Syst Sci Data 6 49ndash60 (2014)

22 E Kalnay M Kanamitsu R Kistler W Collins D Deaven L Gandin M Iredell S SahaG White J Woollen Y Zhu A Leetmaa R Reynolds M Chelliah W Ebisuzaki W HigginsJ Janowiak K C Mo C Ropelewski J Wang R Jenne D Joseph The NCEPNCAR40-year reanalysis project Bull Am Meteorol Soc 77 437ndash471 (1996)

23 J Radoux C Rousseau C Lamarche T De Maet P Defourny Seasonal metrics and anomalydetection based on SPOT-VEGETATION archive in Europe paper presented at theInternational Geoscience and Remote Sensing Symposium Milano Italy 26 to 31 July 2015

24 C Rousseau J Radoux C Lamarche T De Maet P Defourny Snow cover anomalies from2000 to 2014 and highlight of two exceptional years over Europe paper presented at theInternational Geoscience and Remote Sensing Symposium Milano Italy 26 to 31 July 2015

25 J E Pinzon C J Tucker A non-stationary 1981ndash2012 AVHRR NDVI3g time series RemoteSens 6 6929ndash6960 (2014)

26 P C Buerkner brms Bayesian Regression Models Using Stan R package version 090(2016) httpsCRANR-projectorgpackage=brms

27 A Gelman J Hwang A Vehtari Understanding predictive information criteria forBayesian models Stat Comput 24 997ndash1016 (2014)

28 T Sezenler M Oumlzder M Yildirir A Ceyhan M A Yuumlksel The relationship betweenbody weight and body condition score in some indigenous sheep breeds in TurkeyJ Anim Plant Sci 21 443ndash447 (2011)

29 J A W Coetzer R C Tustin Infectious Diseases of Livestock (Oxford Univ Press ed 22004)

30 F Sanchez-Monge ldquoCalving status and commensalism of Pasteurella multocida in thesurviving Betpak-dala saiga population in May 2016 after a mass mortality eventin May 2015rdquo thesis Royal Veterinary College University of London (2016)

31 M C L De Alwis Haemorrhagic septicaemiamdashA general review Br Vet J 148 99ndash112(1992)

32 R B Millar M J Anderson Remedies for pseudoreplication Fish Res 70 397ndash407 (2004)33 J Dutta B S Rathore S G Mullick R Singh G C Sharma Epidemiological studies

on occurrence of haemorrhagic septicaemia in India Indian Vet J 67 893ndash899 (1990)34 V G Lunitsyn A S Donchenko S I Ognev N A Frolov Pantovoe Olenevodstvo

i Bolezni Olenei Deer Farming and Disease (Barnaul 2007)35 X Gao J Xiao H Qin Z Cao H Wang Impact of meteorological factors on the

prevalence of porcine pasteurellosis in southcentral of Mainland China Prev Vet Med125 75ndash81 (2016)

36 R Kock ldquoFinal report of mission by Prof Richard Kock RVC to Kazakhstan September 13thto October 1st 2011 and related analysisrdquo (Royal Veterinary College 2011)

37 M Shatar B Khanui D Purevtseren B Khishgee A Loitsch H Unger T B K SettypalliG Cattoli B Damdinjav W G Dundon First genetic characterization of peste despetits ruminants virus from Mongolia Arch Virol 162 3157ndash3160 (2017)

38 Food and Agriculture Organization of the United Nations Crisis Management Centre forAnimal Health Mongolia Investigation of peste des petits ruminants (PPR) among wildanimals and its potential impact on the current PPR situation in livestock Mission Report20th January ndash 1st February 2017 FAO Rome (2017)

39 A Kuumlhl A Mysterud G I Erdnenov A A Lushchekina I A Grachev A B BekenovE J Milner-Gulland The lsquobig spendersrsquo of the steppe Sex-specific maternal allocation andtwinning in the saiga antelope Proc Biol Sci 274 1293ndash1299 (2007)

40 N J Singh I A Grachev A B Bekenov E J Milner-Gulland Tracking greenery acrossa latitudinal gradient in central Asia ndash The migration of the saiga antelope Divers Distrib16 663ndash675 (2010)

41 E J Milner-Gulland M V Kholodova A Bekenov O M Bukreeva I A GrachevL Amgalan A A Lushchekina Dramatic declines in saiga antelope populations Oryx 35340ndash345 (2001)

42 G M Murray R G OrsquoNeill S J More M C McElroy B Earley J P Cassidy Evolving viewson bovine respiratory disease An appraisal of selected key pathogensmdashPart 1Vet J 217 95ndash102 (2016)

43 J D Taylor R W Fulton T W Lehenbauer D L Step A W Confer The epidemiologyof bovine respiratory disease What is the evidence for preventive measuresCan Vet J 51 1351ndash1359 (2010)

44 M B Orynbayev W Beauvais A R Sansyzbay R A Rystaeva K T SultankulovaA A Kerimbaev M N Kospanova R A Kock Seroprevalence of infectious diseases in

Kock et al Sci Adv 20184 eaao2314 17 January 2018

saiga antelope (Saiga tatarica tatarica) in Kazakhstan 2012ndash2014 Prev Vet Med 127100ndash104 (2016)

45 V Kattsov V Govorkova V Meleshko T Pavlova I Shkolnik Climate Change Projectionsand Impacts in Russian Federation and Central Asia States (North Eurasia ClimateCentre 2008) httpneaccmeteoinforuresearch20-research

46 E Lioubimtseva G M Henebry Climate and environmental change in arid Central AsiaImpacts vulnerability and adaptations J Arid Environ 73 963ndash977 (2009)

47 IPCC Climate Change 2014 Impacts Adaptation and Vulnerability Part B Regional AspectsContribution of Working Group II to the Fifth Assessment Report of the IntergovernmentalPanel on Climate Change (Cambridge Univ Press 2014)

48 V Salnikov G Turulina S Polyakova Y Petrova A Skakova Climate change inKazakhstan during the past 70 years Quatern Int 358 77ndash82 (2015)

49 M Turco E Palazzi J von Hardenberg A Provenzale Observed climate change hotspotsGeophys Res Lett 42 3521ndash3528 (2015)

50 R de Jong J Verbesselt M E Schaepman S de Bruin Trend changes in global greeningand browning Contribution of short-term trends to longer-term change Glob ChangBiol 18 642ndash655 (2012)

Acknowledgments This work was undertaken with the approval of the Royal VeterinaryCollege Ethical Review Board (URN 2015 1435) and under the authority of the BiosafetyInstitute of the Ministry of Science and Education and the Ministry of Agriculture Committeefor Forestry and Wildlife Ministry of Agriculture Republic of Kazakhstan This work did notinvolve any experimental use of animals only routine clinical examination and sampling onmoribund animals in extremis during the MME Funding This study was made possiblethrough various funding mechanisms the main one being the National Environment ResearchCouncil of the United Kingdom urgency research grant (NEN0076461) the team alsoreceived substantial support financially or logistically from the following agencies which aregratefully acknowledged the ACBK the Flora and Fauna International the Peoplersquos Trustfor Endangered Species and the Saiga Conservation Alliance the Royal Society for theProtection of Birds and the Frankfurt Zoological Society We thank D King and G Freimanisof the PI S Feroudini and the FLI for the laboratory support on advanced diagnostics Wealso thank the Convention on Migratory Species of the United Nations and the WildlifeConservation Network for their support and assistance We acknowledge cooperation fromI Sytnyk (former Vice Director) and S Tyulegenov (Director) and staff from the NationalReference Veterinary Centre At the University of Bristol we thank B Stuijfzand andW Browne for advice on statistical approaches and E Hector and T Cogan for pathogenvisualization in tissues We also thank A Lushchekina and Y Grachev for provision of keyliterature and insights and A Salemgareyev S Kopeyev E Shalgynbaev and S Inkarbekov fortheir participation in the fieldwork We thank N Kock (Wake Forest School of MedicineWinston-Salem) for review of the histopathology Remote sensing image processing wassupported by the Feacutedeacuteration Wallonie-Bruxelles in the frame of LifeWatch ERIC Authorcontributions RAK led all elements of the study and carried out clinical observations fieldpostmortems and epidemiological assessment MO led the laboratory testing and carriedout field postmortems SR carried out the review of historical evidence and statisticalanalyses SZ led the fieldwork component NJS carried out statistical analyses WB andERM contributed to the evidence review and statistical analyses AK RR and ZO carriedout microbiological analyses SK participated in the fieldwork HMM carried outhistopathological analyses SW carried out field investigations FH and JR produced allNDVI and snow anomaly data EJM-G led the evidence review statistical components andpaper writing RAK MO SR SZ NS WB ERM HMM and EJM-G wrote the paperAll authors contributed to hypothesis development and testing Conflicts of interest Theauthors declare that they have no competing interests Data and materials availability Alldata needed to evaluate the conclusions in the paper are present in the paper andorthe Supplementary Materials Additional data related to this paper may be requested from theauthors and data presented in this paper are archived at NERCrsquos Environmental InformationData Centre (accession number pending)

Submitted 28 June 2017Accepted 14 December 2017Published 17 January 2018101126sciadvaao2314

Citation R A Kock M Orynbayev S Robinson S Zuther N J Singh W BeauvaisE R Morgan A Kerimbayev S Khomenko H M Martineau R Rystaeva Z OmarovaS Wolfs F Hawotte J Radoux E J Milner-Gulland Saigas on the brink Multidisciplinaryanalysis of the factors influencing mass mortality events Sci Adv 4 eaao2314 (2018)

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eventsSaigas on the brink Multidisciplinary analysis of the factors influencing mass mortality

Hawotte Julien Radoux and Eleanor J Milner-GullandAslan Kerimbayev Sergei Khomenko Henny M Martineau Rashida Rystaeva Zamira Omarova Sara Wolfs Florent Richard A Kock Mukhit Orynbayev Sarah Robinson Steffen Zuther Navinder J Singh Wendy Beauvais Eric R Morgan

DOI 101126sciadvaao2314 (1) eaao23144Sci Adv

ARTICLE TOOLS httpadvancessciencemagorgcontent41eaao2314

MATERIALSSUPPLEMENTARY httpadvancessciencemagorgcontentsuppl2018011241eaao2314DC1

REFERENCES

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registered trademark of AAASis aScience Advances Association for the Advancement of Science No claim to original US Government Works The title

York Avenue NW Washington DC 20005 2017 copy The Authors some rights reserved exclusive licensee American (ISSN 2375-2548) is published by the American Association for the Advancement of Science 1200 NewScience Advances

on October 1 2018

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