Young - 1994 - Natural Die Offs of Large Mammals - Implications for Conservation

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Natural Die-Offs of Large Mammals: Implications for ConservationAuthor(s): Truman P. YoungSource: Conservation Biology, Vol. 8, No. 2 (Jun., 1994), pp. 410-418Published by: Blackwell Publishing for Society for Conservation BiologyStable URL: http://www.jstor.org/stable/2386465Accessed: 13/09/2010 16:10

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Natural ie-Offs f LargeMammals:mplicationsfor ConservationTRUMAN .YOUNGLouis Calder CenterFordhamUniversityBox KArmonk, Y 10504, U.S.A.

Abstract: he viability of populations is a central concernof biological conservation. The occurrence of catastrophicdie-offs may greatly educe the ong-term iability f popu-lations. Theoretical xtinction modelsand viability nalysesrequire nformation n the requency f die-offs nd on thedistribution f die-off everities. review of literature den-tified 6 natural die-offs n large mammal populations,with a die-off eing defined s a peak-to-trough ecline inestimated opulation numbers of at least 25%. If such die-offs re common, opulation viability nalyses that gnorethem may be overly ptimistic. he severities f the naturaldie-offs f large mammals presented here re not uniformlydistributed. here s a relative overabundance of die-offs nthe 70-90% range, and an underabundance of die-offs

greater han 90%. This may indicate the resence of buffersagainst population extinction. The reported auses of largemammal die-offs were ignificantly elated to trophic evel:herbivore ie-offs were more often ttributed o starvation,while carnivore die-offs were more often ttributed o dis-ease.Populations subject to large-scale henomena such asdrought nd severe winters may not be protected rom die-offs y population subdivision. On the other hand, popula-tions subject to catastrophic isease epidemics may be pro-tected by subdivision, and threatened y corridors etweenconservation reas and by translocation fforts.

Introduction nd MethodsA central task of biological conservation s estimatingthe viability f populations, nd how various actors may

Paper submitted eptember , 1992; revised manuscript ccepted

June 1, 1993.410

Conservation iology, ages 410-418Volume 8, No. 2, June 1994

Declinacionesnaturales epentinas pronunciadas nmamiferos randes: mplicaciones ara la conservacionResumen: La viabilidad de las poblaciones es una preocu-pacion central n la biologia de conservacz'n. a ocurrenciade "die-offs" declinaciones repentinas y pronunciadas)catastr6ficos educenen gran medida la viabilidad a largoplazo de las poblaciones. Modelos teoricos de extincion yanalisis de viabilidad requieren de informaci6n obre de lafrecuencia de los "die-off'y sobre la distribucion de la se-riedad de los mismos. Una revision e la literatura dentifico96 "die-offs" naturales en poblaciones de mamiferosgrandes, definiendose l "die-off' omo una declinacion depor lo menos un 25% en el tamafio poblacional. Si tales"die-offs" on comunes, os analisis de viabilidadpoblacio-nal que los ignoran eri'an umamente optimistas. a sever-idad de los "die-offs" aturales de mamiferos randes aquipresentados no estd distribuida uniformemente. xiste unasobreabundancia relativa de "die-offs" n el nivel del 70 al90%, y una superabundancia de "die-offs" mayores que90%. Esto ultimo podria indicar la presencia de "buffers"contra as extinciones oblacionales. Las causas reportadaspara los "die-offs" e grandes mamiferos stuvieron ignifi-cativamente elacionadas con el nivel tr6fico; os "die-offs"de berbivoros e atribuyeron ma'sfrecuentemente la inani-cion, mientras que los "die-offs" e carni'voros e atribuy-eron mas ferecuentemente enfermedades. as poblacionessujetas a fenomenos a una escala espacial grande, tales

como sequfas e inviernos everos no podri'an serprotegidasde los "die-offs" mediante la subdivision poblacional. Porotro ado, laspoblaciones sujetas a epidemias catastr6ficasde enfermedades odrian ser protegidas mediante a subdi-vision ypuestas enpeligropor medio de corredores ntre reasde conservacion por medio de esfuerzos e translocacio6n.

be manipulated o ensure some (high) probability flong-term opulation urvival Soule 1987). Limits nthe viability fpopulations re hypothesized o be set byvarious factors Lande 1988; Simberloff 988), includ-ing inbreeding, oss of genetic variation Lande 1988;

Simberloff 988), demographic tochasticity Richter-



Young Natural ie-Offs f LargeMammals 411

Table 1. Natural ie-offs f arge mammals.

Species % Die-off Primary Cause Reference Biome

Gray Kangaroo 55 starvation drought) Caughley et al. 1985 temperateRed Kangaroo 59 starvation drought) Caughley t al. 1985 temperateRed Kangaroo >50 starvation drought) Newsome 1975 temperateRed Kangaroo 85 starvation drought) Corbet &

Newsome 1987temperate

Warthog >90 starvation drought) Scholes1985 tropical rdWarthog >90? starvation drought) Walker t al. 1987 tropical ridWarthog 38 starvation drought) Walker t al. 1987 tropical ridCollaredPeccary 64 ? Glanz 1982 tropical orestMule Deer 42 starvation winter) Robinette t al. 1952 temperateMoose 50-87 starvation winter) Mech 1966 temperateCaribou 89 starvation winter) Miller t al. 1977 arcticCaribou 60 starvation Davis 1978 arcticCaribou 78 starvation Davis 1978 arcticCaribou 44 starvation Davis1978 arcticCaribou 69 starvation Davis 1978 arcticCaribou 71 starvation winter) Gates et al. 1986 arcticGrant's Gazelle 46 starvation drought) Stewart & Zaphiro 1963 tropical ridThomson'sGazelle 65 predation competition) Borner t al. 1987 tropical rid

Springbok >85 starvation drought) Viljoen & Bothma 1990 tropical ridGemsbok >85 starvation drought) Viljoen & Bothma 1990 tropical ridImpala 75 starvation drought) Scholes1985 tropical ridImpala 72 starvation drought) Walker t al. 1987 tropical ridImpala 36 starvation drought) Walker t al. 1987 tropical ridImpala 87 disease (anthrax) Prins & Weyerhauser 987 tropical ridImpala 90 disease Prins & Douglas-Hamilton 990 tropical ridImpala 49 predation starvation) Hirst 1969 tropical ridWaterbuck 80 starvation drought) Walker t al. 1987 tropical ridWaterbuck 30 starvation drought) Walker t al. 1987 tropical ridWaterbuck 93 disease (brown ear tick) Melton 1987 tropical ridReedbuck 90 starvation multiple) Ferrar Kerr 1971 tropical ridReedbuck 91 disease Prins & Douglas-Hamilton 990 tropical ridKongoni 81 starvation drought) Hillman& Hillman 1977 tropical ridKongoni 69 starvation drought) Stewart Zaphiro 1963 tropical ridWildebeast 88 starvation drought) Scholes1985 tropcial ridWildebeast 90 starvation drought) Walker t al. 1987 tropical ridWildebeast 62 starvation drought) Walker t al. 1987 tropical ridWildebeast 32 starvation drought) Hillman& Hillman 1977 tropical ridWildebeast 46 starvation drought) Stewart Zaphiro 1963 tropical ridWildebeast 31 predation Hirst 1969 tropical ridWildebeast 100 predation drought) Prins & Douglas-Hamilton 990 tropcial ridKudu 50 starvation drought) Walker t al. 1987 tropical ridKudu 40 starvation drought) Walker t al. 1987 tropical ridKudu 51 starvation Hirst 1969 tropical ridEland 50 starvation drought) Stewart Zaphiro 1963 tropical ridGiraffe 27 starvation Hirst 1969 tropical ridBighorn heep 76 disease Anonymous 987 temperateBighorn heep >50 disease (scabies) Langeet al. 1980 temperateBighorn heep 88 starvation disease) Uhazy t al. 1973 temperateBighorn heep >75 ? Stelfox 971 temperateBighorn heep 85 disease starvation) Stelfox 971 temperateBighorn heep 52 ? Stelfox 971 temperateBighorn heep 85 starvation winter) Stelfox 971 temperateDallSheep 70-90 starvation winter) Murie 1944 arcticDallSheep 56 starvation winter) Walters t al. 1981 arcticMuskOxen 86 starvation winter) Miller t at. 1977 arcticBison 43 ? Meagher 1973 temperateBison 63 ?Meagher 1973 temperateBison 74 ?Meagher 1973 temperateAfrican uffalo 87 starvation drought) Walker t al. 1987 tropical ridAfrican uffalo 34 starvation drought) Walker t al. 1987 tropical ridPronghorn 62 starvation winter) Martinka 967 temperateBurchell's ebra 90 starvation drought) Walker t al. 1987 tropical rid

Burchell's ebra 73 starvation drought) Walker t al. 1987 tropical rid

Conservation iologyVolume 8, No. 2, June 1994



412 Natural ie-Offs f LargeMammals Young

Table 1. Continued.

Species % Die-offj Primary Causeb Reference BiomeBurchell's Zebra 80 starvation drought) Scholes 1985 tropical aridBurchell's Zebra 28 starvation drought) Stewart & Zaphiro 1963 tropical aridBurchell's Zebra 50 starvation drought) Hillman & Hillman 1977 tropical aridAfrican Elephant 29 starvation drought) Corfield 1973

tropical aridAfrican Elephant 29 disease (drought) Prins & Douglas-Hamilton 1990 tropical aridVervet Monkey 72 habitat change (predation) Isbell et al. 1990 tropical aridBaboon 95 habitat change Altmann et al. 1985 tropical aridSiamong 67 disease Palombit, personal communication tropical forestTamarin 84 habitat change (?) Glanz 1982 tropical forestCebus Monkey 85 ? Glanz 1982 tropical forestHowler Monkey 48 disease (yellow fever?) Collias & Southwick 1952 tropical forestLangur "massive" disease (viral) Work et al. 1957 tropical forestBonnet Macaque "massive" disease (viral) Work et al. 1957 tropical forestThree-Toed Sloth 76 ? Glanz 1982 tropical forestBottlenose Dolphin 50 disease Harwood & Hall 1990 marineCoyote 50 disease (parvivirus) Pence et al. 1983 temperateCoyote 87 starvation hare cycle) Clark 1972 temperateWild Dog 84 disease (distemper) Borner et al. 1987 tropical arid

Wild Dog 72 disease (competition) Frame et al. 1979 tropical aridWild Dog >63 disease (?) J. Malcolm, personal communication tropical aridAfrican Lion 75 disease (fly outbreak) Fosbrooke 1963 tropical aridNorthern Sea Lion 39 ? Merrick et al. 1987 marineCrabeater Seal 85 disease (crowding, starvation) Laws & Taylor 1957 marineHarbour Seal 85 disease (?) Pitcher 1990 marineHarbour Seal 75 disease (distemper) Bjorge 1991 marineCaspian Seal 80 disease Lauckner 1985 marineFur Seal 62 starvation El Nino) Trillmich & Limberger 1985 marineFur Seal 33 starvation Glynn 1988 marineSea Otter 33 ? Lubina & Levin 1988 marineSea Otter 68 starvation Kenyon 1969 marineSea Otter 68 starvation Kenyon 1969 marineSea Otter 52 starvation Kenyon 1969 marineCoati 59 starvation ?) Kaufmann 1962 tropical foresta Estimates f "percentage die-offt' ere made on samples of various sizes and methodologies. ,"Primary ause" was taken from he originalinvestigators' eports. arenthetical auses are secondary r associated causes.

Dyn & Goel 1972), environmental ariability Leigh1981; Goodman, 1987a, 1987b;Dennis et al. 1991), and"catastrophes." atastrophes an be defined s local ex-tinctions f a metapopulation Ewens et al. 1987) or asrare, evere environmental vents Hanson & Tuckwell1978) such as drought, isease, or habitat hange.Thereis growing nderstanding hat nongenetic actors, ndparticularly atastrophic vents, may be more ikely o

limit the viability f populations than genetic factors(Lande 1988).Catastrophic ie-offs ave the potential for putting

great constraints n minimum iable population size(Hanson & Tuckwell 1978; Mangel & Tier 1993). Buthow common and how severe are such die-offs n na-ture? heoretical models require nformation n the fre-quency of die-offs nd on the distribution f die-off e-verity Mangel& Tier 1993). It s also important hatweidentify he natural actors hat ut populations t occa-sional risk. Populations hat re subject to catastrophicdisease epidemics are likely o be managed differentlythan populations ubject to catastrophic tarvation. t


would therefore e useful o examine the iterature nnatural ie-offs.

Largepopulation luctuations ave been documentedin many opulations f nvertebrates Williamson 1972;Wolda 1982,1992), birds Stout & Cornwell 1976), andsmallmammals Williamson 1972;Hanski1987). I havelimited his urvey o arge mammals or everal reasons.First, ecause of their cological mpact, unting oten-

tial, nd conservation ttention, here re numerous e-peated population estimates of many populations oflarge mammals. econd, arge ong-lived nimals xhibitless severe population fluctuations han do smaller,shorter-lived pecies (Williamson 1972; Pimm 1991)and so serve as conservative amples of population die-offs n nature. Third, ustifiably r not, arge mammalsreceive a disproportionate hare of attention n conser-vation ctivity nd research.

I identified 6 natural ie-offs f arge mammals n asurvey f the literature Table 1). Large mammals redefined ere as those from ll mammalian rders xceptrodents, hrews, ats, and lagomorphs.A die-off s de-




fined s a monotonic drop in population numbers hatoccurs between two or among more than two popula-tion surveys. n long-term ata sets, these die-offs repeak-to-trough opulation hanges. have ncluded nlydie-offs n which there was at least a 25% reduction npopulation ize.

I have not included in the analysis ny die-offs hatwere clearly related to human activities (over-exploitation, abitat destruction), or have I includedintroduced opulations. attempted o differentiate e-tween natural epizootics and diseases introduced byman. For example, have not included die-offs ssoci-ated with rinderpest n African ngulates r Pasteurellain bighorn heep, which are almost certainly ecentlyintroduced iseases, but have included die-offs ssoci-ated with scabies in bighorn heep and distemper nwild dogs, even though he origin f these s not com-pletely lear.

Berger 1990) documented extinctions f isolatedpopulations f bighorn heep, with a greater xtinctionrates among smaller populations. The large number flocal bighorn xtinctions trongly mplies hat he glob-al population was not in equilibrium. ither xtinctionrates have recently ncreased dramatically ompared oearlier imes perhaps through eduction f populationsizes below critical imits), r recolonization ateshavelowered. In either case, die-offs n these populationsmay be related to human activity.

Even though have ncluded ll of the natural ie-offsthat have come to my attention, t is reasonable to as-

sume that he die-offs eported n Table 1represent nlya small fraction f the severe mammalian ie-offs hathave occurred n nature n recent decades.Marinemam-mals are difficult o census unless they come periodi-cally to limited terrestrial reeding and calving sites(Thompson & Harwood 1990). Censusing f forest n-imals s especially difficult Glanz 1982; Milton 1990).Even in open terrestrial abitats, etailed populationcensuses have only recently een carried ut, and onlyfor limited number f species and sites.

Not included here are numerous nonquantitative e-ports of catastrophic ie-offs such as Longhurs t al.

1952; Simmonds 1992). For example, Longhurs t al.(1952) report 180 local die-offs f deer in Californiabetween the ate nineteenth entury nd the mid twen-tieth entury. ver a third f these were attributed odisease and over half ostarvation, sually uring everewinters. nterestingly, hese proportions re similar othose of die-offs ttributed o starvation nd disease forall herbivores n my survey see Table 2). Examples:

"The winter of 1889 killed most of the deer and ante-lope" (Longhurs t al. 1952:14);

"[In 1921] a severe epizootic nearly wiped out a heavypopulation of black-tails long the McCloud River"(Longhurs 1952:21);

Table . Numbersf arge mammalpecies hose ie-offs ereattributedovarious auses or erbivores,arnivores,andprimates.

SuggestedCauseHabitat

Group Starvation Disease Predation Change UnknownHerbivores 22 (48) 5 7) 3 4) 4 (7)Carnivores 4 (7) 7(8) 2 (2)Primates 4 (4) 1(1) 3 3) 1(1)

Numbers n parentheses re the numbers of populations.

"Periodic die-offs f deer on densely populated rangesbecame commonplace-some caused by parasites rdisease,others y outright tarvation, ut all manifes-tations of local over-population" Longhurs et al.1952:22-23).

Results nd DiscussionThese die-offs ere widely diverse etiologically Table2), ecologically Table 3), and taxonomically Table 4).Virtually ll types of large mammals re represented.Ungulates and carnivores account for most of therecords, but primates, marsupials, dentates, nd pro-boscids are also represented. he seven different am-malian orders did not differ ignificantly n the meanseverity of their die-offs F = 1.04, d.f. = 7,p = 0.41).

Die-offs n the five different abitat ypesdid not dif-fer ignificantly n their mean severity F = 0.33, d.f. =

4, p = 0.86). Semiarid savanna) regions are numeri-cally strongly epresented. here are several possiblereasons for his. First, hese regions harbor arge popu-lations f argemammals. econd, these habitats may bemore prone to lethally ry years than are more mesicecosystems. Third, nimals n these open habitats rerelatively asy to count. Tropical forests re sometimesconsidered relatively onstant nvironments. owever,several mammal pecies in tropical orests ave experi-enced documented die-offs.

Die-offs ttributed o different auses did not differsignificantly n their mean severity F = 1.40, d.f. = 4,

p = 0.24). The most commonly reported ources ofmortality ere disease and starvation ue to drought rsevere winter. Although he mean severities f die-offswere independent f guild herbivores, arnivores, ri-

Table . Numbersfpopulations ith eported ie-ofis ordifferent abitatypes.

Habitat FrequencyTropcial rid 46Temperate 15Arctic 9Marine 12Tropical orest 8

ConservationiologyVolume , No. 2, June 994




Table 4. Numbers f populations ith eported ie-offs ordifferent ammalianroups mostly rders).

Group # Species # PopulationsMarsupialia 2 4Ungulata 24 62

Artiodactyla 23 57Perissodactyla 1 5Carnivora 10 17Primates 7 7Proboscidae 1 2Edendata 1 1Cetacea 1 1

mates; F = 0.09, d.f. = 2, p = 0.92), the frequencies ofreported probable causes of die-offs ere significantlydifferent etween herbivores nd carnivores Table 2).Herbivore ie-offs ere more often ttributed o starva-tion, nd carnivore ie-offs ere more often ttributedto disease,when analyzed ither t the species evel X2= 7.36, d.f. = i,p < 0.001) or at the population evel(X2 = 11.54, d.f. = 1,P < 0.001).

There are several possible reasons for his differencein the reported auses of die-offs f predators nd her-bivores. First, most of the carnivores n Table 1 arehighly ocial and live in more ntimate ontact handomost social herbivores, hich may promote the trans-mission f disease. Second, the diets of carnivores mayfacilitate he acquisition and transmission f disease.Third, erbivores s a trophic evel may be more oftenfood-limited han are carnivores. ourth, he food re-sources of carnivores may be less subject to environ-mental luctuations. erbivores food for redators) de-cline more slowly hanfood plants during drought rover a severe winter. inally, hese differences ould bedue to the biases of observers f those studying arni-vores were more likely to attribute ie-offs f mixedetiology o disease.

Although most studies reported only a single ikelycause of the die-off, multiple causes are likely. Over-population may manifest tself oth n starvation nd indiseasesusceptibility Longhurs t al. 1952), and habitatloss can increase food imitation nd predation Isbell et

al. 1990). Although multiple actorsmay be common,only a minority f the studies directly ddressed con-tributing actors see Table 1).

The distribution f die-off ntensities as not random.Die-offs f 70-90% were over-abundant, nd die-offsgreater han 90% were under-abundant Fig. 1; X2 =19.1, d.f. = 6, p < 0.005; among die-offsmore than30%, in 10% intervals). he paucity of natural ie-offsgreater han90% may ndicate demographic bound-ary ffect" hat ends to protect populations rom ocalextinction. f course, these populations re the survi-vors of ong-term, arge-scale rocesses that an be ex-pected to have already liminated opulations uscep-tible to extinction. Human-caused reductions in


12

30 40 50 60 70 80 90 100Percent Die-off

Figure 1. The distribution f 92 reported atural die-offs n large mammal populations (From Table 1).The dotted ine represents uniform istribution.

population ize may have more profound ffects n ex-tinction robabilities han uggested y these data.

The number f die-offs maller han 70% is also lessthan hose 70-90%. If this s real, t may be a thresholdeffect, here populations end to withstand ntermedi-ate levels of enviornmental tress but respond dramati-cally to extreme vents. believed that t more likelyrepresents he relative under-reporting f less severedie-offs.

A similar attern lso occurs among die-offs n cyclicpopulations. Figure 2 shows the distribution f carni-vore die-offs rom the well-known lynx/hare ycle(Keith 1963; Williamson 972). These data come fromtrapping ata and may underestimate minimum num-bers and therefore verestimate opulation reductions.These data show an abundance of die-off ntensities nthe range of 78-92%. Strong density dependence isthought oprotect hesecyclicpopulations rom xtinc-tion. The similarity etween the arge mammal die-offsin Figure 1 and the carnivore rashes n Figure 2 implythat catastrophic ie-offs f large mammals may alsohave a density-dependent omponent. Those die-offsthat were due to density-dependent actors ould be theresults of either overcompensation Grenfell et al.1992) or of changes n carrying apacity ue to externalfactors such as drought or severe winters; Western1975; Caughley& Gunn 1993). Unfortunately, t is dif-

ficult o demonstrate ensity dependence from ime-series data of natural populations Vickery & Nudds1991; Caughley& Gunn 1993).

These data do not allow calculation f the frequencyof die-offs or ndividual opulations. However, severedroughts f the kind associated with the recorded die-offs n eastern nd southern Africa ave occurred sev-eral times his entury. onghurs t al. (1952) reportednumerous die-offs f deer in California uring he late1800s and early 1900s. Harwood and Hall (1990) con-cluded that marine mammal opulations re occasion-ally ubject to events hatmay remove 50% or more ofthe ndividuals. n the case of seals in the United King-dom, such events eem to occur with a periodicity f




L = LynxF = FoxC = CoyoteM = Fisher

C FC F LM M F F L L F

L LMM L C ML MLL LLC CLLLL LL

0% -10% -20% -30% -40% -50% -60% -70% -80% -90% -100%

Figure 2. Distribution of cyclic carnivore opulation crashes rom the ynx-hare ycle.These data comefromtrapping nd may underestimate minimum numbers nd therefore verestimate opulation reductions.

about 50 years." Similarly, hree major die-offs f Alas-kan caribou have occurred n the past hundred years(Miller et al. 1977; Davis 1978). It appears that majordie-offs re not uncommon mong ome large mammalspecies.

The data are even less able to demonstrate hethersuch die-offs ccur regularly r sporadically. urrentmodels of environmental ariation nd catastrophic ie-offs onsider their effects o be temporally andom(Hanson & Tuckwell 1978; Goodman 1987a, 1987b;Mangel & Tier 1993). It is likely hat f die-offs eremore regularly paced, they would represent ess of athreat o population viability ecause they would allowpopulations ime o recover between die-offs. owever,the existence of density ependence as a cause of die-offs oes not guarantee heir regularity f carrying a-pacity tself luctuates andomly nd strongly Caughley& Gunn 1993).

Implications or ConservationThe patterns eported ere have several mplications orbiologicalconservation. irst, evere population rashesin populations of large mammals re apparently wide-spread nd not uncommon n nature. he frequency ndseverity f such die-offs may put severe restrictions nthe viability f populations of large mammals, whichalready require large areas per individual. opulationviability nalyses hould ncorporate he kinds f popu-lation variation ndicated by these die-offs see Mangel& Tier 1993).

Second,there may be limits o the severity f naturaldie-offs mong xtant opulations. he rarity f xtremedie-offs epresents form f density dependence thatmay help buffer opulations against extinction. t ap-pears that hefactor(s) hat ause severe die-offs re noteffective n eliminating ndividuals when populationsizes are greatly educed. Possible explanations ncluderefuges, mmigration, he decreased efficiency f diseasetransmission t low population density, r the recoveryof food resources.

Therefore, heseresultswill affect opulation iabilityanalysis n conflicting ays.Viability nalyses hat ncor-porate occasionalcatastrophic ie-offs ill tend to pre-

dict less long-term iability han analyses that do not.On the other hand, viability nalyses that ncorporatelimits to the severity f die-offs ill tend to predictgreater ong-term iability han analyses hat do not.

More problematic s that hese die-offsmay occur sorarely hat they are statistically npredictable. Otherstochastic ources of variation "demographic," envi-ronmental") an be modelled if the variation occursover time periods that re short relative o the predic-tive range of the viability nalysis. evere and relativelyunpredictable ie-offsmay imit he usefulness f pop-ulation viability nalysis.

While these die-offs may not often hemselves rivenatural populations to extinction, uch demographicbottlenecks may put large populations regularly t riskfrom he factors hat affect mall populations Keith1963; Simberloff 988; Berger 1990), including eneticand demographic ffects; n addition, hey re likely obe negatively ffected y human nterference. s human

influences n nature ncrease, major population rashesare likely o become more threatening o species sur-vival, ven if they re natural n origin.

Third, ifferent ources of massmortality re ikely oaffect ubdivided opulations n different ays. Popula-tion ubdivision metapopulation tructure) nd the ex-istence nd quality f corridors mongpopulations havebecome important onsiderations n the study of re-serve design Simberloff 988). Populations ubject tolarge-scale henomena uch as drought nd severe win-ters may not be protected from ie-offs y populationsubdivision Quinn & Hastings 1987). On the other

hand, populations ubject to catastrophic isease epi-demics may be protected by subdivision SimberloffCox 1987) and threatened y corridors etween con-servation reas and by translocation fforts. t is impor-tant for managers o consider the relative ikelihood ofthese different otential ources of catastrophic ie-offsbefore making ecisions bout habitat r population ma-nipulations.

The list of die-offs n Table 1 is undoubtedly ncom-plete. t is hoped that his preliminary eviewwill serveas a basis for further urvey work on catastrophic ie-offs n nature. Uncommon vents re more ikely o berecorded Weatherhead 1986) and understood Young

Conservation BiologyVolume 8, No. 2, June 1994




& Isbell, 1994) when studies are conducted over thelong term. The patterns evealed n this review are fur-ther vidence for he value of ong-term ield research.

AcknowledgmentsI thank L. Isbell, T. Caro, C. Southwick,M. Mangel,J.Ginsberg, M. Peacock, F. Smith, D. W. Macdonald, R.May, nd D. Ehrenfeld or help with the manuscript ndthe deas therein, nd the Center or opulationBiologyand the Department f Botany f the University f Cal-ifornia t Davisfor ogistical nd intellectual upport.

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