Essay

Assessing Threats: Toward a Reevaluation of IUCN Threatened Species Categories

GEORGINA M. MACE Institute of Zoology Zoological Society of London Regent’s Park, London NWl 4RY, U.K. RUSSELL LANDE Department of and Chicago, Illinois 60637, USA.

Abstract: IUCN categories of threat (Endangered Vulnera- Resumen: La categorizacion de la Union Internacional ble, Rare, Indeterminate, and others) are widely used in ‘Red para la Conservacion de la Naturaleza (UICN) de las espe- lists’ of endangered species and have become an important cies amenazadas (en peligro, vulnerables, raras, indetemzi- tool in conservation action at international, national, re- nadas y otras) son ampliamente utilizadas en las Listas Ro- gional, and thematic levels. The existing definitions are jas de especies en peligro y se ban convertido en una her- largely subjective, and as a result, categorizations made by ramienta importante para las acciones de conservacion different authorities diyfer and mynot accurately reflect a1 nivel internacional, nacional, regional y tematico. Las actual extinction risks. Wepresent proposals to redefine cat- definiciones de las categorias existentes son muy subjetivas egories in tams of the probability of extinction within a y, como resultado, las categorizaciones hechas por diyientes specific time perio4 based on the theory of extinction times autores dvieren y quiz& no refrejen con certeza el riesgo real for single populations and on meaningful time scales for de extincion. Presentamospropuestas para re-definir las cat- conservation action. Three categories are proposed (CRITI- egori’as en thninos de la probabilidad de extincion dentro CAL, ENDANGE-, VULNERABLE) with decreasing levels of de un period0 de tiempo especi@o. Las propuestas estan threat over increasing time scales for species estimated to basadas en la teoria del tiempo de extincion para pobla- have at least a 10% probability of extinction within 100 ciones individuales y en escalas de tiempo que tengan sig- years. The process of assigning species to categories may need nificado para las acciones de conservacion. Se proponen tres to vay among different taxonomic groups, but we present categorias (CRITICA, mPELIGR0, VULNmE)con niveles some simple qualitative criteria based on population biol- decrecientes de amenaza sobre escalas de tiempo en au- ogy theory, which we suggest are appropriate at least for mento para especies que se estima tengan cuando menos un most large vertebrates. The process of assessing threat is 10% deprobabilidad de extincion en 100 arios. Elproceso de clearly distinguished from that of setting priorities for con- asignar especies a categorias puede que necesite variar den- servation action, and only the former is discussed here. tro de 10s difwentes grupos taxondmicos per0 nosotros pre- sentamos algunos m’terios cuulitativos simples basados en la teoria de la biologia de las poblaciones, las cuales suger- imos son apropiadas para cuando menos la mayori’a de 10s grandes vertebrados. El proceso de evaluar la amenaza se distingue claramente del de definir las prioridades para las acciones de conservacion, solamente el primer0 se discute lZfUi

Paper submitted February 12, 1990; revised manuscript accepted October 8, 1990.

148

Conservation Volume 5, No. 2, June 1991 Mace & Lande Threatened Species Categories 149

Introduction species under review. Various categorization systems used in the past, and proposed more recently, have confounded Background these two processes (see Fitter & Fitter 1987; Munton The Steering Committee of the Species Survival Com- 1987). To devise a general system for setting priorities is mission (SSC) of the IUCN has initiated a review of the not useful because different concerns predominate within overall functioning of the Red Data Books. The review Merent taxonomic, ecological, geographical, and political will cover three elements: ( 1) the form, format, content, units. The process of setting priorities is therefore best left and publication of Red Data Books; (2) the categories of to specific plans developed by specialist bodies such as the threat used in Red Data Books and the IUCN Red List national and international agencies, the specialist groups, (Extinct, Endangered, Vulnerable, Rare, and Indetermi- and other regional bodies that can devise priority assess- nate); and (3) the system for assigning species to cate- ments in the appropriate regional or taxonomic context. gories. This paper is concerned with the second ele- An objective assessment of extinction risk may also then ment and includes proposals to improve the objectivity contribute to the decisions taken by governments on and scientific basis for the threatened species categories which among a variety of recommendations to implement. currently used in Red Data Books (see IUCN 1988 for The present paper is therefore confined to a discussion of current definitions). assessing threats. There are at least three reasons why a review of the categorization system is now appropriate: ( 1) the exist- ing system is somewhat circular in nature and exces- Aims of the System of Categorization sively subjective. When practiced by a few people who For Whom? are experienced with its use in a variety of contexts it can be a robust and workable system, but increasingly, Holt (1987) identifies three different groups whose different groups with particular regional or taxonomic needs from Red Data Books (and therefore categories of interests are using the Red Data Book format to develop threat) may not be mutually compatible: the lay public, local or specific publications. Although this is generally national and international legislators, and conservation of great benefit, the interpretation and use of the professionals. In each case the purpose is to highlight present threatened species categories are now diverging taxa with a high extinction risk, but there are differ- widely. This leads to disputes and uncertainties over ences in the quality and quantity of information needed particular species that are not easily resolved and that to support the assessment. Scott et al. (1987) make the ultimately may negatively affect species conservation. point that in many cases simple inclusion in a Red Data (2) Increasingly, the categories of threat are being used Book has had as much effect on raising awareness as any in setting priorities for action, for example, through spe- of the supporting data (see also Fitter 1974). Legislators cialist group action plans (e.g., Oates 1986;Eudey 1988; need a simple, but objective and soundly based system East 1988, 1989; Schreiber et al. 1989). If the categories because this is most easily incorporated into legislation are to be used for planning then it is essential that the (Bean 1987). Legislators frequently require some state- system used to establish the level of threat be consistent ment about status for every case they consider, however and clearly understood, which at present it does not weak the available information might be. Inevitably, seem to be. (3) A variety of recent developments in the therefore, there is a conflict between expediency and study of population viability have resulted in techniques the desire for scientific credibility and objectivity. Con- that can be helpful in assessing extinction risks. servationists generally require more precision, particu- larly if they are involved in planning conservation pro- grams that aim to make maximal use of limited Assessing Threats Versus Setting Priorities resources. In the first place it is important to distinguish systems for assessing threats of extinction from systems de- Characteristics of an Ideal System signed to help set priorities for action. The categories of threat should simply provide an assessment of the like- With this multiplicity of purposes in mind it is appro- lihood that if current circumstances prevail the species priate to consider various characteristics of an ideal sys- will go extinct within a given period of time. This tem: should be a scientific assessment, which ideally should ( 1) The system should be essentially simple, provid- be completely objective. In contrast, a system for setting ing easily assimilated data on the risk of extinction. In priorities for action will include the likelihood of ex- terms of assessing risk, there seems to be little virtue in tinction, but will also embrace numerous other factors, developing numerous categories, or in categorizing risk such as the likelihood that restorative action will be on the basis of a range of different parameters (e.g., successful; economic, political, and logistical consider- abundance, nature of threat, likelihood of persistence of ations; and perhaps the taxonomic distinctiveness of the threat, etc.). The categories should be few in number,

Conservation Biology Volume 5, No. 2, June 1991 150 Threatened Species Categories Mace & hde should have a clear relationship to one another (Holt els of population extinction times result in approxi- 1987; Munton 1987), and should be based around a mately exponential distributions, as in Goodman’s probabilistic assessment of extinction risk ( 1987) model of density-dependent population growth (2) The system for categorization has to be flexible in in a fluctuating environment, mean extinction time may terms of data required. The nature and amount of data not accurately reflect the high probability that the spe- available to assess extinction risks varies widely from cies will go extinct within a time period considerably almost none (in the vast majority of species) to highly shorter than the mean (see Fig. 1). More useful are mea- detailed population data (in a very few cases). The cat- sures such as “95% likelihood of persistence for 100 egorization system should make maximum use of what- years.” ever data are available. One beneficial consequence of this process would be to identrfy key population data for field workers to collect that would be useful in assessing Population Viability Analysis and extinction risk. Extinction Factors (3) The categorization system also needs to be flexi- ble in terms of the population unit to which it applies. Various approaches to defining viable populations have Throughout this discussion, it is assumed that the sys- been taken recently (Shafkr 1981, 1990; Gilpin & Soule, tem being developed will apply to any species, subspe- 1986; Soule 1987). These have emphasized that there is cies, or geographically separate population. The catego- no simple solution to the question of what constitutes a rization system therefore needs to be equally applicable viable population. Rather, through an analysis of extinc- to limited lower taxonomic levels and to more limited tion factors and their interactions it is possible to assess geographical scope. Action planning will need to be fo- probabilities and time scales for population persistence cused on particular taxonomic groups or geographical for a particular taxon at a particular time and place. The areas, and can then incorporate an additional system for development of population viability analyses has led to setting priorities that reflect taxonomic distinctiveness the definition of intrinsic and extrinsic factors that de- and extinction risks outside the local area (e.g.,see East termine extinction risks (see Soule 1983; Soule 1987; 1988, 1989; Schreiber et al. 1989). Gilpin & Soule 1986; see also King 1987). Briefly these (4) The terminology used in categorization should be can be summarized as population dynamics (number of appropriate, and the various terms used should have a individuals, life history and age or stage distribution, clear relationship to each other. For example, among geographic structure, growth rate, variation in demo- the current terms both ‘endangered and ‘vulnerable’are graphic parameters), population characteristics (mor- readily comprehended, but ‘rare’ is confusing. It can be phology, physiology, genetic variation, behavior and dis- interpreted as a statement about distribution status, persal patterns), and environmental effects (habitat level of threat, or local population size, and the relation- quality and quantity, patterns and rates of environmen- ships between these factors are complex (Rabinowitz et tal disturbance and change, interactions with other spe- al. 1986). Rare (i.e., low-density) species are not always cies including man). at risk and many species at risk are not numerically rare Preliminary models are available to assess a popula- (King 1987; Munton 1987; Heywood 1988). The rela- tion’s expected persistence under various extinction tionship of ‘rare’ to ‘endangered and ‘vulnerable’ is also pressures, for example, demographic variation (Good- unclear. man 1987% b; Belovsky 1987; CBSG 1989), catastro- (5) If the system is to be objectively based upon phes (ShaJTer 1987), inbreeding and loss of genetic di- sound scientific principles, it should include some as- versity (Lande & Barrowclough 1987; Lacy 1987), sessment of uncertainty. This might be in terms of con- metapopulation structure (Gilpin 1987; Quinn & Hast- fidence levels, sensitivity analyses, or, most simply, on ings 1987; Murphy et al. 1990). In addition, various ap- an ordinal scale reflecting the adequacy of the data and proaches have been made to modeling extinction in models in any particular case. populations threatened by habitat loss (e.g., Gutierrez & (6) The categories should incorporate a time scale. Carey 1985; Maguire et al. 1987; Lande 1988), disease On a geological time scale all species are doomed to (e.g., Anderson & May 1979; Dobson & May 1986; Seal extinction, so terms such as “in danger of extinction” et al. 1989), parasites (e.g., May & Anderson 1979; May are rather meaningless. The concern we are addressing & Robinson 1985; Dobson & May 1986), competitors, here is the high background level of the current rates of poaching (e.g., Caughley 1988), and harvesting or hunt- extinction, and one aim is therefore preservation over ing (e.g., Holt 1987). the upcoming centuries (Soule & Simberloff 1986). So far, the development of these models has been Therefore, the probability of extinction should be ex- rather limited, and in particular they often fail to suc- pressed in terms of a finite time scale, for example, 100 cessfully incorporate several different extinction factors years. Munton ( 1987) suggests using a measure of num- and their interactions (Lande 1988). Nevertheless the ber of years until extinction. However, since most mod- approach has been applied in particular cases even with

Conservation Biology Volume 5, No. 2, June 1991 Mace & Lande Threatened Species Categories 151 existing models (e.g., grizzly bear: Shaffer 1983; spotted events more than about 100 years in the future are hard owl: Gutierrez & Carey 1985; Florida panther: CBSG to foresee, and this may be the longest duration that 1989), and there is much potential for further develop- legislative systems are capable of dealing with effec- ment. tively. Although different extinction factors may be critical It seems desirable to establish a CRITICAL category to for different species, other, noncritical factors cannot be emphasize that some species or populations have a very ignored. For example, it seems likely that for many spe- high risk of extinction in the immediate future. We pro- cies, habitat loss constitutes the most immediate threat. pose that this category include species or populations However, simply preserving habitats may not be suffi- with a 50% chance of extinction within 5 years or two cient to permit long term persistence if surviving pop- generations, and which are clearly at very high risk. ulations are small and subdivided and therefore have a An intermediate category, ENDANGERED, seems de- high probability of extinction from demographic or ge- sirable to focus attention on species or populations that netic causes. Extinction factors may also have cumula- are in substantial danger of extinction within our life- tive or synergistic effects; for example, the hunting of a times. A 20%chance of extinction within 20 years or 10 species may not have been a problem before the popu- generations seems to be appropriate in this context. lation was fragmented by habitat loss. In every case, For increasing levels of risk represented by the cate- therefore, all the various extinction factors and their gories VULNERABLE, ENDANGERED, and CRITICAL, it interactions need to be considered. To this end more is necessary to increase the probability of extinction or attention needs to be directed toward development of to decrease the time scale, or both. We have chosen to models that reflect the random influences that are sig- do both for the following reasons. First, as already men- nificant to most populations, that incorporate the effects tioned, decreasing the time scale emphasizes the imme- of many different factors, and that relate to the many diacy of the situation. Ideally, the time scale should be plant, invertebrate, and lower vertebrate species whose expressed in natural biological units of generation time population biology has only rarely been considered so of the species or population (Leslie 1966), but there is far by these methods. also a natural time scale for human activities such as Viability analysis should suggest the appropriate kind conservation efforts, so we have given time scales in of data for assigning extinction risks to species, though years and in generations for the CRITICAL and ENDAN- much additional effort will be needed to develop appro- GERED categories. priate models and collect appropriate field data. Second, the uncertainty of estimates of extinction probabilities decreases with increasing risk levels. In population models incorporating fluctuating environ- Proposal ments and catastrophes, the probability distribution of extinction times is approximately exponential (Nobile Three Categories and Their Justification et al. 1985; Goodman 1987). In a fluctuating environ- We propose the recognition of three categories of threat ment where a population can become extinct only (plus EXTINCT), defined as follows: through a series of unfavorable events, there is an initial, CRITICAL: 50% probability of extinction relatively brief period in which the chance of extinction within 5 years or 2 generations, is near zero, as in the inverse Gaussian distribution of whichever is longer. extinction times for density-independent fluctuations ENDANGERED: 20% probability of extinction (Ginzburg et al. 1982; Lande & Orzack 1988). If catas- within 20 years or 10 genera- trophes that can extinguish the population occur with tions, whichever is longer. probabilityp per unit time, and are much more impor- VULNERABLE: 10% probability of extinction tant than normal environmental fluctuations, the prob- within 100 years. ability distribution of extinction times is approximately These definitions are based on a consideration of the exponential, pePPt, and the cumulative probability of theory of extinction times for single populations as well extinction up to time t is approximately 1 - e-pt. Thus, as on meaningful time scales for conservation action. If typical probability distributions of extinction times look biological diversity is to be maintained for the foresee- like the curves in Figures 1A and lB, and the cumulative able future at anywhere near recent levels occurring in probabilities of extinction up to any given time look like natural ecosystems, fairly stringent criteria must be the curves in Figures 1C and 1D. Dashed curves repre- adopted for the lowest level of extinction risk, which we sent different distributions of extinction times and cu- call VULNERABLE. A 10% probability of extinction mulative extinction probabilities obtained by changing within 100 years has been suggested as the highest level the model parameters in a formal population viability of risk that is biologically acceptable (Shder 198 1 ) and analysis (e.g., different amounts of environmental varia- seems appropriate for this category. Furthermore, tion in demographic parameters). The uncertainty in an

Conservation Biology Volume 5, No. 2, June 1991 152 Threatened Species Categoifes Mace & hde estimate of cumulative extinction probability up to a that the categorization of many species should be based certain time can be measured by its coefficient of vari- on more qualitative criteria derived from the same body ation, that is, the standard deviation among different of theory as the definitions above, which will broaden estimates of the cumulative extinction probability with the scope and applicability of the categorization system. respect to reasonable variation in model parameters, di- In these more qualitative criteria we use measures of vided by the best estimate. It is apparent from Figures effective population size (N,) and give approximate 1C and 1D that at least for small variations in the pa- equivalents in actual population size (N). It is important rameters (if the parameters are reasonably well known), to recognize that the relationship between N, and N the uncertainty of estimates of cumulative extinction depends upon a variety of interacting factors. Estimating probability at particular times decreases as the level of N, for a particular population will require quite exten- risk increases. Thus at times, t,, t,, and tj when the best sive information on breeding structure and life history estimates of the cumulative extinction probabilities are characteristics of the population and may then produce lo%, 20%, and 50% respectively, the corresponding only an approximate figure (Lande & Barrowclough ranges of extinction probabilities in Figure 1C are 1987). In addition, different methods of estimating N, 6.5%-14.8%. 13.2%-28.6%, and 35.1%-65.0%,and in will give variable results (Harris & Allendorf 1989). NJ Figure ID are 6.8%-13.1%, 13.9%-25.7%, and N ratios vary widely across species, but are typically in 37.2%-60.2%.Taking half the range as a rough approx- the range 0.2 to 0.5. In the criteria below we give a imation of the standard deviation in this simple illustra- value for N, as well as an approximate value of N as- tion gives uncertainty measures of 0.41, 0.38, and 0.30 suming that the NJN ratio is 0.2. in Figure lC, and 0.31, 0.29, and 0.23 in Figure lD, We suggest the following criteria for the three cate- corresponding to the three levels of risk. Given that for gories: practical reasons we have chosen to shorten the time scales for the more threatened categories, these results CRITICAL: 50% probability of extinction within suggest that to maintain low levels of uncertainty, we 5 years or 2 generations, whichever is should also increase the probabilities of extinction in longer, or the definition of the ENDANGERED and CRITICAL cat- (1) Any two of the following criteria: egories. (a) Total population N, < 50 (corre- These definitions are based on general principles of sponding to actual N < 250). population biology with broad applicability, and we be- (b) Population fragmented: S2 sub- lieve them to be appropriate across a wide range of life populations with N, > 25 (N > forms. Although we expect the process of assigning spe- 125) with immigration rates < 1 cies to categories (see below) to be an evolving (though per generation. closely controlled and monitored) process, and one that (c) Census data of >20% annual de- might vary across broad taxonomic groups, we recom- cline in numbers over the past 2 mend that the definitions be constant both across tax- years, or >50% decline in the onomic groups and over time. last generation, or equivalent projected declines based on de- mographic projections after al- Assigning Species or Populations to Categories lowing for known cycles. (d) Population subject to cata- We recognize that in most cases, there are insufficient strophic crashes ( > 50% reduc- data and imperfect models on which to base a formal tion) per 5 to 10 years, or 2 to 4 probabilistic analysis. Even when considerable informa- generations, with subpopula- tion does exist there may be substantial uncertainties in tions highly correlated in their the extinction risks obtained from population models fluctuations. containing many parameters that are difficult to esti- or (2) Observed, inferred, or projected hab- mate accurately. Parameters such as environmental sto- itat alteration (is., degradation, loss, chasticity (temporal fluctuations in demographic pa- or fragmentation) resulting in charac- rameters such as age- or developmental stage-specific teristics of (1). mortality and fertility rates), rare catastrophic events, as or (3) Observed, inferred, or projected com- well as inbreeding depression and genetic variability in mercial exploitation or ecological in- particular characters required for adaptation are all dif- teractions with introduced species ficult to estimate accurately. Therefore it may not be (predators, competitors, pathogens, possible to do an accurate probabilistic viability analysis or parasites) resulting in characteris- even for some very well studied species. We suggest tics of (1).

Conservation Biology Volume 5, No. 2, June 1991 Threatened Species Categories 153

Fluctuatina Environment Catastrophes

I I

I

Time Time Figure 1. Probability distributions of time to extinction in a fluctuating environment, inverse Gaussian distri- butions (A), or with catastrophes, exponential distributions (B). Corresponding cumulative extinction proba- bilities of extinction up to any given time are shown below (C and 0).Solid curves represent the best estimates from available data and dashed curves represent different estimates based upon the likely range of variation in the parameters. t,, fa and t3 are times at which the best estimates of cumulative extinction probabilities are lo%, 20%, and 50%. t is the expected time to extinction in the solid curves.

ENDANGERED: 100 (N > 500) with immigration 20% probability of extinction within rates <1 per generation, or 20 years or 10 generations, which- (ii) S2 subpopulations with Ne ever is longer, or > 250 (N > 1,250) with immi- (1) Any two of the following or any one gration rates < 1 per generation. criterion under (c) Census data of >5% annual de- CRITICAL cline in numbers over past 5 (a) Total population N, < 500 (cor- years, or >lo%decline per gen- responding to actual N < 2,500). eration over past 2 generations, (b) Population fragmented: or equivalent projected declines (i) <5 subpopulationswith N, > based on demographic data after

Conservation Biology Volume 5, No. 2, June 1991 154 Threatened Species Categories Mace & Lande

allowing for known cycles. teractions with introduced species (d) Population subject to catastroph- (predators, competitors, pathogens, ic crashes: an average of >20% or parasites) resulting in characteris- reduction per 5 to 10 years or 2 tics of ( 1). to 4 generations, or >50% re- Prior to any general acceptance, we recommend that duction per 10 to 20 years or 5 these criteria be assessed by comparison of the catego- to 10 generations, with subpop- rizations they lead to in particular cases with the results ulations strongly correlated in of formal viability analyses, and categorizations based on their fluctuations. existing methods. This process should help to resolve or (2) Observed, inferred, or projected hab- uncertainties about both the practice of, and results itat alteration (i.e., degradation, loss, from, our proposals. We expect a system such as this to or fragmentation)resulting in charac- be relatively robust and of widespread applicability, at teristics of (1). the very least for most higher vertebrates. For some or (3) Observed, inferred, or projected com- invertebrate and plant taxa, different kinds of criteria mercial exploitation or ecological in- will need to be developed within the framework of the teractions with introduced species definitions above. For example, many of these species (predators, competitors, pathogens, have very high rates of population growth, short gener- or parasites) resulting in characteris- ation times, marked or episodic fluctuations in popula- tics of (1). tion size, and high habitat specificity. Under these cir- VULNERABLE: cumstances, it will be more important to incorporate 10% probability of extinction within metapopulation characteristics such as subpopulation 100 years, or persistence times, colonization rates, and the distribu- (1) Any two of the following criteria or tion and persistence of suitable habitats into the analy- any criterion under ENDAN- one sis, which are less significant for most large vertebrate GERED. populations (Murphy et al. 1990; Menges 1990). (a) Total population N, < 2,000 (corresponding to actual N < Change of Status 10,000). The status of a population or species with respect to risk (b) Population fragmented: of extinction should be up-listed (from unlisted to VUL- (i) S 5 subpopulations with Ne > NERABLE, from VULNERABLE to ENDANGERED, or 500 (N > 2,500) with immigra- from ENDANGERED to CRITICAL) as soon as current tion rates 1,000 (N > 5,000)with immi- tion should be down-listed (from CRITICAL to ENDAN- gration rates < 1 per generation. GERED, from ENDANGERED to VULNERABLE, or from (c) Census data of > 1% annual de- VULNERABLE to unlisted) only when the criteria of the cline in numbers over past 10 lower risk category have been satisfied for a time period years, or equivalent projected equal to that spent in the original category, or if it is declines based on demographic shown that past data were inaccurate. data after allowing for known cy- For example, if an isolated population is discovered cles. consisting of 500 individuals and no other information is (d) Population subject to catastroph- available on its demography, ecology, or the history of ic crashes: an average of >lo% the population or its habitat, this population would ini- reduction per 5 to 10 years, tially be classified as ENDANGERED. If management ef- >20% reduction per 10 to 20 forts, natural events, or both caused the population to years, or >50% reduction per 50 increase so that 10 years later it satisfied the criteria of years, with subpopulations the VULNERABLE category, the population would not strongly correlated in their fluc- be removed from the ENDANGERED category for a fur- tuations. ther period of 10 years. This time lag in down-listing or (2) Observed, inferred, or projected hab- prevents frequent up-listing and down-listing of a pop- itat alteration (i.e., degradation, loss, ulation or species. or fragmentation) resulting in charac- teristics of ( 1). Uncertain or Conflicting Results or (3) Observed, inferred, or projected com- Because of uncertainties in parameter estimates, espe- mercial exploitation or ecological in- cially those dealing with and environmental

Conservation Biology Volume 5, No. 2, June 1991 Mace & Lande Threatened Species Categories 155 variability and catastrophes, substantial differences may DANGERED, and VULNERABLE, with decreasing arise in the results from analyses of equal validity per- probabilities of extinction risk over increasing time formed by different parties. In such cases, we recom- periods. mend that the criteria for categorizing a species or pop- 6. For most cases, we recommend development of ulation should revert to the more qualitative ones more qualitative criteria for allocation to categories outlined above. based on basic principles of population biology. We present some criteria that we believe to be appro- Reporting Categories of Threat priate for many taxa, but are appropriate at least for higher vertebrates. To objectively compare categorizations made by differ- ent investigators and at different times, we recommend that any published categorization also cite the method Acknowledgments used, the source of the data, a date when the data were We would like to acknowledge the support and encour- accurate, and the name of the investigator who made agement of Simon Stuart, Steven Edwards, and Ulysses the categorization. If the method was by a formal via- Seal in the preparation of this paper. We are also very bility model, then the name and version of the model grateful to the many members of the SSC network for used should also be included. the time they put into commenting upon earlier drafts of this paper, and only regret that they are too numerous Conclusion to mention individually.

Any system of categorizing degrees of threat of extinc- Literature Cited tion inevitably contains arbitrary elements. No single Anderson, R. M., and R. M. May. 1979. Population biology of system can adequately cover every possibility for all infectious diseases. Part I. Nature 280561-367. species. The system we describe here has the advantage of being based on general principles from population Bean, M. J. 1987. Legal experience and implications. Pages 3% biology and can be used to categorize species for which 43 in R. Fitter and M. Fitter, editors. The road to extinction. either very little or a great deal of information is avail- IUCN, Gland, Switzerland. able. Although this system may be improved in the fu- Belovsky, G. E. 1987. Extinction models and mammalian per- ture, we feel that its use will help to promote a more sistence. Pages 35-57 in M. E. Soule, editor. Viable populations uniform recognition of species and populations at risk of for conservation. Cambridge University Press, Cambridge, En- premature extinction, and should thereby aid in setting gland. priorities for conservation efforts. Caughley, G. 1988. A projection of ivory production and its implications for the conservation of African elephants. CSIRO consultancy report to CITES. CSIRO Division of Wildlife and summary Ecology.

1. Threatened species categories should highlight spe- CBSG. 1989. Florida panther: population viability analysis. cies vulnerable to extinction and focus appropriate IUCN/SSC/CBSG: Apple Valley, Minneapolis, Minnesota. reaction. They should therefore aim to provide ob- jective, scientifically based assessments of extinc- Cumming, D. H. M., R. F. du Toit, and S. N. Stuart. 1989. African tion risks. elephants and rhinos: status, survey and conservation action plan. IUCN, Gland, Switzerland. 2. The audience for Red Data Books is diverse. Positive steps to raise public awareness and implement na- Dobson, A. P., and R. M. May. 1986. Disease and conservation. tional and international legislation benefit from sim- Pages 345-365 in M. Soule, editor. Conservation biology-the ple but soundly based categorization systems. More science of scarcity and diversity. Sinauer Associates, Sunder- precise information is needed for planning by con- land. Massachusetts. servation bodies. Dobson, A. P., and D. Miller. 1989. Infectious diseases and en- 3. An ideal system needs to be simple but flexible in dangered species management. Endangered Species Update terms of data required. The category definitions q9):1-5. should be based on a probabilistic assessment of extinction risk over a specified time interval, includ- East, R. 1988. Antelopes: global survey and regional action ing an estimate of error. plans. Part 1. east and north east Africa. IUCN, Gland, Switzer- 4. Definitions of categories are appropriately based on land. extinction probabilities such as those arising from East, R. 1989. Antelopes: global survey and regional action population viability analysis methods. plans. Part 2. southern and south central Africa. IUCN, Gland, 5. We recommend three categories, CRITICAL, EN- Switzerland.

Conservation Biology Volume 5, No. 2, June 1991 156 Threatened Species Categories Mace & hde

Eudey, A. 1988. Action plan for Asian primate conservation, Lande, R., and G. F. Barrowclough. 1987. Effective population IUCN/SSC, Gland, Switzerland. size, genetic variation and their use in population manage- ment. Pages 87-123 in M. E. Soule, editor. Viable populations Fitter, R. F. 1974. 25 years on: a look at endangered species. for conservation, Cambridge University Press, Cambridge, En- Ory~12~341-346. gland.

Fitter, R., and M. Fitter, editors. 1987. The road to extinction. Lande, R., and S. H. Orzack. 1988. Extinction dynamics of age- IUCN, Gland, Switzerland. structured populations in a fluctuating environment. PNAS 85:74 18-742 1. Fuller, W. A. 1987. Synthesis and recommendations. Pages 47- 55 in R. Fitter and M. Fitter, editors. The road to extinction. Leslie, P. H. 1966. Journal of Animal Ecology 25:291. IUCN, Gland, Switzerland. Maguire, L.A., U. S. Seal, and P. F. Brussard. 1987. Managing Gilpin, M.E. 1987. Spatial structure and population vulnerabil- critically endangered species: the Sumatran rhino as an exam- ity. Pages 125-139 in M. E. Soule, editor. Viable populations ple. Pages 141-158 in M. E. Soule, editor. Viable populations for conservation. Cambridge University Press, Cambridge, En- for conservation. Cambridge University Press, Cambridge, En- gland. gland.

Gilpin, M. E., and M. E. Soule. 1986. Minimum viable popula- May, R. M., and R. M. Anderson. 1979. Population biology of tions: processes of species . Pages 19-34 in M. E. infectious diseases. Part 11. Nature 280:455-461. Soule, editor. Consekation biology-the science of scarcity and diversity. Sinauer Associates, Sunderland, Massachusetts. May, R. M., and S. K. Robinson. 1985. Population dynamics of avian brood parasitism. American Naturalist 126~475494. Ginzburg, L. R., L. B. Slobodkin, K. Johnson, and A. G. Bindman. 1982. Quasiextinction probabilities as measure of impact on a Menges, E. S. 1990. Population viability analysis for an endan- population growth. Risk Analysis 2:171-181. gered plant. Conservation Biology 452-62. Goodman, D. 1987~.The demography of chance extinction. Pages 11-34 in M. E. Soule, editor. Viable populations for con- Munton, P. 1987. Concepts of threat to the survival of species servation. Cambridge University Press, Cambridge, England. used in Red Data books and similar compilations. Pages 72-95 in R. Fitter and M. Fitter, editors. The road to extinction. IUCN, Gland, Switzerland. Goodman, D. 19876. How do any species persist? Lessons for conservation biology. Conservation Biology 159-62. Murphy, D. D., K. E. Freas, and S. B. Weiss. 1990. An environ- Gutierrez, R. J., and A. B. Carey, editors. 1985. Ecology and ment-metapopulation approach to population viability analysis management of the Spotted Owl in the Pacific Northwest. for a threatened invertebrate. Conservation Biology 4:41-5 1. General Technical Report PNW-185, USDA Forest Service, Pa- cific Northwest Station, Portland, Oregon. Nobile, A. G., L. M. Ricciardi, and L. Sacerdote. 1985. Exponen- tial trends of first passage-time densities for a class of diffusion Harris, R. B., and F. W. Allendorf. 1989. Genetically effective processes with steady-state distribution. J. Appl. Probab. population size of large mammals: an assessment of estimators. 22:611-618. Conservation Biology 5181-1 91. Oates, J. F. 1986. Action plan for African primate conservation: Heywood, V. H. 1988. Rarity: a privilege and a threat. Pages 19861990, IUCN/SSC, Gland, Switzerland. 277-290 in W. Greuter and B. Zimmer, editors. Proceedings of the XN International Botanical Congress Koeltz, Konigsteinl Quinn, J. F., and A. Hastings. 1987. Extinction in subdivided Taunus. habitats. Conservation Biology 1:198-208.

Holt, S. J. 1987. Categorization of threats to and status of wild Rabinowitz, D., S. Cairns, and T. Dillon. 1986. Seven forms of populations. Pages 19-30 in R. Fitter and M. Fitter, editors. rarity and their frequency in the flora of the British Isles. Pages The road to extinction. IUCN, Gland, Switzerland. 182-204 in M. E. Soule, editor. Conservation biology-the sci- ence of scarcity and diversity. Sinauer Associates, Sunderland, IUCN. 1988. 1988 IUCN red list of threatened animals IUCN, Massachusetts. Gland. Switzerland. Schreiber, A,, R. Wirth, M. Wel, and H. von Rompaey. 1989. King, F. W. 1987. Thirteen milestones on the road to extinc- Weasels, civets, mongooses and their relations: an action plan tion. Pages 7-18 in R. Fitter and M. Fitter, editors. The road to for the conservation of mustelids and viverrids. IUCN, Gland, extinction. IUCN, Gland, Switzerland. Switzerland.

Lacy, R. C. 1987. Loss of genetic diversity from managed pop- Scott, P., J. A. Burton, and R. Fitter. 1987. Red Data Books: the ulations: interacting effects of drift, mutation, immigration, se- historical background. Pages 1-5 in R. Fitter and M. Fitter, lection and population subdivision. Conservation Biology editors. The road to extinction. IUCN, Gland, Switzerland. 1:143-157. Seal, U. S., E. T. Thorne, M. A. Bogan, and S. H. Anderson. 1989. Lande, R. 1988. Genetics and demography in biological con- Conservation biology and the black-footed ferret. Yale Univer- servation. Science 241:1455-1460. sity Press, New Haven, Connecticut.

Conservation Biology Volume 5, No. 2, June 1991 Mace & hde Threatened Species Categories 157

Shaffer, M. L. 1981. Minimum population sizes for species con- Soule, M. E. 1983. What do we really know about extinction? servation. Bioscience 31:131-134. Pages 111-124 in C. Schonewald-Cox, S. Chambers, B. Mac- Bryde, and L. Thomas. Genetics and conservation. Benjamin/ Shaffer, M. L. 1983. Determining minimum viable population Cummings, Menlo Park, California. sizes for the grizzly bear. Int. Conf. Bear Res. Manag. 5:133- 139. Shaffer, M. L. 1987. Minimum viable populations; coping with Soule, M. E., editor. 1987. Viable populations for conservation. uncertainty. Pages 6-6 in M. E. Soule, editor. Viable popu- Cambridge University Press, Cambridge, England. lations for Conservation. Cambridge University Press, Cam- bridge, England. Soule, M. E., and D. Simberloff. 1986. What do ecology and Shaffer, M. L. 1990. Population viability analysis. Conservation genetics tell us about the design of nature reserves? Biolo@cA Biology 4:39-40. Conservation 35: 19-40.

Conservation Biology Volume 5, No. 2, June 1991