The global decline of cheetah Acinonyx jubatus and what it means for conservation
Edited by Hugh P. Possingham, University of Queensland, Brisbane, QLD, Australia, and approved November 21, 2016 (received for review July 8, 2016)
Commentary
January 9, 2017
Significance
Here, we compile and present the most comprehensive data available on cheetah distribution and status. Our analysis shows dramatic declines of cheetah across its distributional range. Most cheetah occur outside protected areas, where they are exposed to multiple threats, but there is little information on population status. Simulation modeling shows that, where cheetah population growth rates are suppressed outside protected areas, extinction risk increases markedly. This result can be generalized to other “protection-reliant” species, and a decision tree is provided to improve their extinction risk estimation. Ultimately, the persistence of protection-reliant species depends on their survival outside and inside protected areas and requires a holistic approach to conservation that engages rather than alienates local communities.
Abstract
Establishing and maintaining protected areas (PAs) are key tools for biodiversity conservation. However, this approach is insufficient for many species, particularly those that are wide-ranging and sparse. The cheetah Acinonyx jubatus exemplifies such a species and faces extreme challenges to its survival. Here, we show that the global population is estimated at ∼7,100 individuals and confined to 9% of its historical distributional range. However, the majority of current range (77%) occurs outside of PAs, where the species faces multiple threats. Scenario modeling shows that, where growth rates are suppressed outside PAs, extinction rates increase rapidly as the proportion of population protected declines. Sensitivity analysis shows that growth rates within PAs have to be high if they are to compensate for declines outside. Susceptibility of cheetah to rapid decline is evidenced by recent rapid contraction in range, supporting an uplisting of the International Union for the Conservation of Nature (IUCN) Red List threat assessment to endangered. Our results are applicable to other protection-reliant species, which may be subject to systematic underestimation of threat when there is insufficient information outside PAs. Ultimately, conserving many of these species necessitates a paradigm shift in conservation toward a holistic approach that incentivizes protection and promotes sustainable human–wildlife coexistence across large multiple-use landscapes.
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The spread and dominance of humans across the world during the Anthropocene have precipitated a sixth global biodiversity extinction crisis (1). To maximize biodiversity retention through this period of rapid change, scarce conservation resources need to be targeted toward species and ecosystems that are most threatened. However, in the absence of complete information, reliable assessment of threat is challenging. The International Union for the Conservation of Nature (IUCN) Red List criteria are the primary tools for identifying and categorizing species-based extinction risk, enabling prioritization of species facing the highest threat (2). However, much of the information used for assessment comes from relatively well-monitored populations, usually within protected areas (PAs) (3), although across a species’ distributional range, populations are likely to be exposed to variable threat levels and differing management regimes (4).
Inaccuracies in threat assessment are particularly problematic for large terrestrial mammals, which can be especially vulnerable to anthropogenic impacts, such as habitat loss and fragmentation, human–wildlife conflict, illegal wildlife trade, and overharvesting for bushmeat or traditional use (5–7). These threats are usually higher outside PAs, leading to systematic spatial variation in population status according to levels of protection. However, this spatial variation may go undetected if information on population status and trends is biased toward relatively high-density populations, often found within PAs (3). Such biases are widespread, because wildlife management authorities may be required to monitor wildlife within PAs but not outside them, and monitoring is usually more challenging outside PAs, because wildlife are more elusive and occur there at lower densities (8, 9). This deficit leads to a lack of information on populations outside PAs, where they are generally more threatened, resulting in an overly favorable assessment of status.
Results
Cheetah Status and Threat Assessment.
The cheetah Acinonyx jubatus is a large carnivore that faces particularly acute challenges during the Anthropocene. It is one of the most wide-ranging carnivores, with home ranges documented in excess of 3,000 km2 (10, 11) and movements of translocated animals exceeding 1,000 km (11). However, densities seldom exceed 0.02/km2 and have been recorded as low as 0.0002/km2 (12).
Historically widespread across Africa and southwestern Asia, cheetah are now known to occur in only 9% of their past distributional range (Fig. 1). Not only has there been a worrying contraction in global cheetah range, but current range is extremely fragmented. The global population is tentatively estimated at around 7,100 adult and adolescent cheetah distributed across 33 populations (Table 1). More than one-half of the world’s cheetah occur in a single transboundary population stretching across six countries in southern Africa (Table 1). Only one other population comprises more than 1,000 individuals, and most populations (91%) comprise 200 individuals or fewer. Six populations do not even reach double digits. Ongoing population trends are largely unknown; however, of 18 populations where trends could be assigned, 14 were judged to be in decline, 3 were stable, and only 1 was stable or increasing (Table 1).
Fig. 1.
Table 1.
| Area name | Countries | Resident range (km2) | Population size | Overall increase/stable/decrease* | Resident range in PAs | Range in PAs (%) | Population size in PAs | Population in PAs (%) |
|---|---|---|---|---|---|---|---|---|
| Africa | ||||||||
| Southern Africa six-country polygon | Angola/Botswana/Mozambique/Namibia/South Africa/Zambia | 1,212,179 | 4,021 | ↓ | 283,851 | 23.4 | 1,041 | 25.9 |
| Moxico | Angola | 25,717 | 26 | ? | 0 | 0.0 | 0 | 0.0 |
| Pandmatenga/Hwange/Victoria Falls | Botswana/Zimbabwe | 25,926 | 50 | ↓ | 15,551 | 60.0 | 29 | 58.0 |
| Banhine | Mozambique | 7,266 | 10 | ? | 0 | 0.0 | 0 | 0.0 |
| Malilangwe/Save/Gonarezhou | Mozambique/Zimbabwe | 9,922 | 46 | ↔ | 4,757 | 47.9 | 19 | 41.3 |
| Kafue | Zambia | 26,222 | 65 | ? | 22,185 | 84.6 | 55 | 84.6 |
| Liuwa | Zambia | 3,170 | 20 | ↑ or ↔ | 2,921 | 92.1 | 18 | 90.0 |
| Bubyana, Nuanetsi, and Bubye Conservancies | Zimbabwe | 8,816 | 40 | ↓ | 0 | 0.0 | 0 | 0.0 |
| Zambezi valley | Zimbabwe | 3,612 | 12 | ↓ | 2,102 | 58.2 | 7 | 58.3 |
| Matusadona | Zimbabwe | 1,422 | 3 | ↓ | 1,422 | 100.0 | 3 | 100.0 |
| Midlands Rhino Conservancy | Zimbabwe | 318 | 4 | ↓ | 0 | 0.0 | 0 | 0.0 |
| Subtotal southern Africa | 1,324,570 | 4,297 | 332,789 | 25.1 | 1,172 | 27.3 | ||
| Afar | Ethiopia | 4,480 | 11 | ↓ | 1,092 | 24.4 | 3 | 27.3 |
| Blen-Afar | Ethiopia | 8,170 | 20 | ↓ | 1,856 | 22.7 | 5 | 25.0 |
| Ogaden | Ethiopia | 12,605 | 32 | ↓ | 0 | 0.0 | 0 | 0.0 |
| Yangudi Rassa | Ethiopia | 3,046 | 8 | ↓ | 3,046 | 100.0 | 8 | 100.0 |
| Kenya/Ethiopia/South Sudan | Ethiopia/Kenya/South Sudan | 191,180 | 191 | ? | 37,953 | 19.9 | 38 | 19.9 |
| South Turkana | Kenya | 3,580 | 36 | ? | 1,117 | 31.2 | 11 | 30.6 |
| Kidepo/southern South Sudan/northwest Kenya | Kenya/South Sudan/Uganda | 6,694 | 19 | ? | 1,422 | 21.2 | 4 | 21.1 |
| Serengeti/Mara/Tsavo/Laikipia/Samburu | Kenya/Tanzania | 280,114 | 1,362 | ↓ | 49,705 | 17.7 | 664 | 48.8 |
| Badingilo NP | South Sudan | 8,517 | 85 | ? | 4,741 | 55.7 | 47 | 55.3 |
| Radom NP | South Sudan | 6,821 | 68 | ? | 0 | 0.0 | 0 | 0.0 |
| Southern NP | South Sudan | 14,680 | 147 | ? | 10,863 | 74.0 | 109 | 74.1 |
| Ruaha ecosystem | Tanzania | 30,820 | 200 | ↔ | 25,551 | 82.9 | 166 | 83.0 |
| Maasai Steppe | Tanzania | 20,409 | 51 | ↓ | 3,755 | 18.4 | 9 | 17.6 |
| Katavi-Ugalla | Tanzania | 23,955 | 60 | ? | 10,475 | 43.7 | 26 | 43.3 |
| Subtotal eastern Africa | 615,071 | 2,290 | 151,576 | 24.6 | 1,090 | 47.6 | ||
| Adrar des Ifoghas/Ahaggar/Ajjer and Mali | Algeria/Mali | 762,871 | 191 | ? | 98,867 | 13.0 | 25 | 13.0 |
| WAP | Benin/Burkina Faso/Niger | 25,345 | 25 | ? | 20,923 | 82.6 | 21 | 82.6 |
| CAR/Chad | CAR/Chad | 238,234 | 238 | ? | 44,396 | 18.6 | 44 | 18.6 |
| Termit Massif | Niger | 2,820 | 1 | ? | 2,820 | 100.0 | 1 | 100.0 |
| Air and Ténéré | Niger | 8,052 | 2 | ? | 8,052 | 100.0 | 2 | 100.0 |
| Subtotal western, central, and northern Africa | 1,037,322 | 457 | 175,058 | 16.9 | 93 | 20.3 | ||
| Total Africa | 2,976,963 | 7,044 | 659,423 | 22.2 | 2,355 | 33.4 | ||
| Asia | ||||||||
| Southern landscape | Iran | 107,566 | 20 | ↔ | 41158 | 38.3 | N/A | N/A |
| Northern landscape | Iran | 33,445 | 22 | ↓ | 18077 | 54.04 | N/A | N/A |
| Kavir | Iran | 5,856 | 1 | ↓ | 5,856 | 100.0 | N/A | N/A |
| Total Asia | 146,867 | 43 | 65,091 | 44.3 | N/A | N/A | ||
| Total global | 3,123,830 | 7,087 | 724,514 | 23.2 | 2,355† | 33.4† |
Historical distributional range for cheetah totals 33,056,767 km2, comprising 23,340,522-km2 African range and 9,716,245-km2 Asian range (Fig. 1). CAR, Central African Republic; N/A, not applicable; NP, National Park; WAP, W, Arly and Pendjari protected area complex; ↓, decrease; ↑, increase; ↔, stable.
*
Estimates of trend apply to the entire polygon; thus, for example, populations may increase at specific sites, although there is an overall decrease across the polygon.
†
Does not include Iranian cheetah.
In Asia, the decline of cheetah has been particularly precipitous. Cheetah have been extirpated from 98% of their historical range, and a critically endangered population of Asiatic cheetah Acinonyx jubatus venaticus survives only in Iran (Table 1). This remnant population is tentatively estimated to comprise fewer than 50 individuals distributed across three core areas of range (13). The rest of the world’s cheetah occur in Africa, spread across 30 fragmented populations that are now restricted to only 13% of their historical distributional range (14–16) (Fig. 1 and Table 1).
Across their surviving range, cheetah populations vary in the level of threat that they experience. Most resident range (77%) is on unprotected land, which supports an estimated 67% of the cheetah population (Table 1). Here, cheetah face increased pressures from widespread human–wildlife conflict, prey loss caused by overhunting and bushmeat harvesting, habitat loss and fragmentation, and illegal trade (14–16). The species thus faces spatially heterogeneous threats that are higher outside than inside PAs, whereas much of the data available for threat assessment comes from within PAs, which support the highest reported densities of cheetah (∼0.02/km2) (17, 18). Populations on unprotected lands and in small or poorly managed PAs, where they are exposed to multiple threats, are likely to be in decline. However, because of the considerable survey and monitoring effort required, particularly for a wide-ranging and elusive species like the cheetah, such declines are likely to go undetected.
Protection and Extinction Risk.
Spatial variation in threat across protection gradients in a species’ range is expected to affect overall extinction risk. To assess these impacts for cheetah, we used scenario modeling to (i) explore the relationship between extinction risk and population size while varying both the proportion of land protected and the growth rate on unprotected lands and (ii) predict population trends. We assumed that populations were stable when protected, which is observed in large PAs (19). Our model revealed markedly higher extinction probabilities when the percentage of land under protection was low and when growth rates outside PAs were less than replacement (Fig. 2). When there was no migration or medium migration (5% of the subpopulation per annum) between protected and unprotected land, there was a rapid increase in extinction rate when the proportion of land protected dropped below 40% (Fig. 2 A and B). When the migration rate was high (10% of the subpopulation per annum), extinction rate was high, even when 80% of the population was protected and the reduction in growth rate outside PAs was modest (Fig. 2C). Long-term studies of cheetah suggest that migration rates of between 5 and 10% are likely to be realistic (Materials and Methods).
Fig. 2.
We simulated the global cheetah population by setting the initial population equal to the estimated population of 7,000 individuals, of which 33% occurs in PAs (Table 1). When the population growth rate outside PAs was 10% less than replacement and migration rate was 5% of the subpopulation per annum, simulated populations declined by 53% over 15 y or three cheetah generations (Fig. 3A). When the growth rate outside PAs was 20% less than replacement, then the decline was 70%. Changing the migration rate had little effect on overall population decline (Fig. S1). If the growth rate inside PAs is above replacement, then this slows the rate of decline; however, growth rates need to be high to completely mitigate against declines (Fig. 3B and Fig. S2).
Fig. 3.
Fig. S1.
Fig. S2.
Evidence of recent cheetah population declines is consistent with modeling results. For example, in Zimbabwe, where cheetah distribution is relatively well-known, cheetah were distributed across a contiguous population encompassing 132,931 km2 in 2007, which contracted to a fragmented population occupying only 49,124 km2 by 2015 (16, 20, 21). This 63% range contraction over a short period, equivalent to a loss of 11% of distributional range per year, was largely because of the disappearance of cheetah outside PAs associated with major changes in land tenure (22). The Zimbabwean cheetah population is also estimated to have declined by at least 85% between 1999 and 2015 (20), equivalent to an annual decline of 13%. Similarly, there have been recent large-scale extinctions of cheetah across western and central Africa (23, 24). Ongoing rapid change is likely across the African continent because of changes in land tenure (22), large-scale fencing (25), land grabs (26), and political instability (27). However, cheetah status in areas where they are most threatened is usually uncertain, because those areas lack data. On this basis, in line with the precautionary approach and in the absence of alternative information, our analysis suggests that cheetah should be uplisted to endangered under IUCN Red List criterion A3b (28).
Protection-Reliant Species.
Our model is generic, depending primarily on data on the mean and variance of the growth rate, and shows that extinction risk can be seriously underestimated if differences in population growth rates on protected and unprotected land are not taken into account. We assumed two panmictic subpopulations: one protected and one unprotected. In reality, populations are likely to be much more fragmented, which increases extinction risk, because small isolated populations are more extinction-prone than large connected ones (29). We also assumed that the PA subpopulation was stable and hence, unable to compensate for pressures on unprotected populations. This assumption may hold for many large mammal species. Indeed, given widespread evidence of wildlife declines in many PAs (30), our assumption of stability may even be overly optimistic. If populations are able to grow inside PAs, this increase will help mitigate against declines outside PAs; however, growth rates in excess of 8% per annum inside PAs are needed to counteract a decline of more than 10% per annum outside PAs (Fig. 3B).
There is growing evidence that many populations are subject to source–sink dynamics, whereby protected source populations may supplement declining sink populations (31). Our results show that, when sources are unable to mitigate against declines, then there may be catastrophic consequences on populations. Populations of wide-ranging species are particularly vulnerable to edge effects on PA boundaries, which will damage their capacity to act as sources and compensate for sinks outside (32). Worryingly, there is also increasing evidence for exacerbated sink effects or “ecological traps,” where species are attracted to sinks or “traps” that may be outside PAs, either because they harbor important resources or to avoid competition or predation (33).
Accordingly, our modeling scenarios are not unrealistic, and results may be generalized to those other large mammal species that are assessed to be protection-reliant. Such species may have substantial range outside PAs but are vulnerable to rapid anthropogenic change, which results in populations outside PAs acting as sinks. Our analysis shows that assessment of threat may be underestimated for protection-reliant species, requiring urgent reassessment of extinction risk. We provide a decision tree to assist this assessment process based on our simulation results that takes account of the proportion of distribution or population outside PAs and evidence on threats (Fig. 4). The term protection-reliant differs in important respects from the conservation-dependent subcategory within the lower-risk category used in the IUCN Red List until 2001 (34). Conservation-dependent species are not threatened but might be so if conservation measures are withdrawn. By contrast, protection-reliant species may often be threatened and additionally, face elevated risks of extinction because of increased pressures outside PAs, where a substantial proportion of their population persists.
Fig. 4.
Clearly, an accurate assessment of threat is a key step in identifying those protection-reliant species that are most vulnerable to extinction; however, for some species, the PA system may be insufficient to secure long-term survival. In the case of cheetah, PAs support only an estimated 2,360 individuals, and many PAs are too small to sustain populations that are viable in the long term. For such protection-reliant species, a different approach may be needed to halt declines outside PAs and reduce impacts of edge effects on populations inside PAs to maintain connectivity and secure long-term viability of populations across large multiple-use landscapes. Although some have advocated fencing to reduce edge effects, such interventions are likely to have considerable negative impacts on ecosystems and communities, whereas the massive areas required for wide-ranging species, like cheetah, make the costs prohibitive (25).
Our analysis shows that growth rates within PAs have to be unrealistically high to fully compensate for declining populations outside PAs (Fig. 3B); thus, protection-reliant species are likely to respond better to an approach focused on increasing their growth rates on unprotected lands. Thus, safeguarding protection-reliant species, like cheetah, may require a paradigm shift in conservation away from a primary focus on protection toward a holistic framework that additionally incorporates incentive-based approaches (35). For this shift to occur, new policy, management, and financial tools are needed that promote coexistence between people and wildlife outside and adjacent to PAs (36). This innovation will require concerted action from governments and effective cross-sectoral engagement across the conservation and economic development communities. Securing sustainable solutions for wildlife and people will not be easy, particularly where threatened species may share their range with marginalized and vulnerable communities and where human development challenges are substantial. However, unless this transformation is achieved, the future of wide-ranging and highly threatened species, such as cheetah, is in doubt.
Materials and Methods
Assessing Cheetah Distribution and Status.
Distributional mapping of cheetah in Africa used an expert-based mapping approach established for jaguar and tiger (37, 38) during IUCN/Species Survival Commission conservation strategic planning workshops for cheetah and another similarly sparse and wide-ranging species, African wild dog Lycaon pictus (14–16, 21). Additional map refinements were conducted during National Conservation Action or Management Planning Workshops and from published reports and scientific articles. Mapping in Asia was conducted by a small expert team comprising L.T.B.H., M.S.F., and H.J. using information from ongoing survey work in Iran and the IUCN Red List assessment for the Asian subspecies (13, 39). Resident range was defined as land where the species was known to be still resident as recognized by (i) regular detection of the species in an area over a period of several years and/or (ii) evidence of breeding. Population size for each resident range polygon was estimated either from expert knowledge (based on surveys and monitoring) or using known densities from populations in comparable habitats facing similar levels of threat (14–16, 21, 28). Trends for each polygon were assigned as increasing, decreasing, stable, or unknown based on the expert judgement of those working at sites within polygons.
Simulation Modeling.
Population simulations were conducted in R (40). Mean and SD in the multiplicative growth rate (lambda) in PAs were set at the values observed in the female cheetah population in the Serengeti National Park from 1982 to 2011 (19) (i.e., with a mean of 1.0 and an SD of 0.13). These growth rate parameters implicitly include the impacts of competitors [such as lion (Panthera leo) and spotted hyena (Crocuta crocuta)] on overall growth rate, because both of these predators were present in this PA. Even in well-managed PAs, high cub mortality because of predation may prevent cheetah populations from achieving lambda > 1 (41). Outside PAs, mean lambda was allowed to vary from 1 to 0.8, with the SD set to the same value as within PAs (0.13). For each year, growth rates inside and outside PAs were randomly chosen from a normal distribution.
Migration between subpopulations on protected and unprotected lands was assumed to be proportionate to each subpopulation, with a normal distribution and mean annual rates set at 0.0, 0.05, and 0.1. The SD in migration rate was set at one-half of the mean. The only data available from the long-term study population in the Serengeti National Park (42) record an adult and adolescent immigration rate of 0.07 of the total population per year between 1991 and 2011 with an SD of 0.039 (Table S1).
Table S1.
| Year | Female population size | No. of female immigrants | Immigration females, % | Male population size | No. of male immigrants | Immigration males, % | Total population size | Total no. of immigrants | Immigration total, % |
|---|---|---|---|---|---|---|---|---|---|
| 1991 | 37 | 5 | 13.51 | 17 | 5 | 29.41 | 54 | 10 | 18.52 |
| 1992 | 33 | 1 | 3.03 | 13 | 3 | 23.08 | 46 | 4 | 8.70 |
| 1993 | 34 | 2 | 5.88 | 18 | 4 | 22.22 | 52 | 6 | 11.54 |
| 1994 | 39 | 1 | 2.56 | 11 | 0 | 0.00 | 50 | 1 | 2.00 |
| 1995 | 39 | 1 | 2.56 | 16 | 3 | 18.75 | 55 | 4 | 7.27 |
| 1996 | 36 | 1 | 2.78 | 17 | 2 | 11.76 | 53 | 3 | 5.66 |
| 1997 | 44 | 3 | 6.82 | 23 | 0 | 0.00 | 67 | 3 | 4.48 |
| 1998 | 44 | 0 | 0.00 | 28 | 6 | 21.43 | 72 | 6 | 8.33 |
| 1999 | 46 | 3 | 6.52 | 19 | 0 | 0.00 | 65 | 3 | 4.62 |
| 2000 | 58 | 2 | 3.45 | 23 | 2 | 8.70 | 81 | 4 | 4.94 |
| 2001 | 52 | 3 | 5.77 | 18 | 4 | 22.22 | 70 | 7 | 10.00 |
| 2002 | 45 | 2 | 4.44 | 19 | 2 | 10.53 | 64 | 4 | 6.25 |
| 2003 | 40 | 2 | 5.00 | 20 | 4 | 20.00 | 60 | 6 | 10.00 |
| 2004 | 38 | 0 | 0.00 | 23 | 1 | 4.35 | 61 | 1 | 1.64 |
| 2005 | 42 | 0 | 0.00 | 18 | 2 | 11.11 | 60 | 2 | 3.33 |
| 2006 | 47 | 4 | 8.51 | 22 | 3 | 13.64 | 69 | 7 | 10.14 |
| 2007 | 40 | 0 | 0.00 | 21 | 2 | 9.52 | 61 | 2 | 3.28 |
| 2008 | 32 | 0 | 0.00 | 19 | 3 | 15.79 | 51 | 3 | 5.88 |
| 2009 | 35 | 0 | 0.00 | 28 | 3 | 10.71 | 63 | 3 | 4.76 |
| 2010 | 33 | 2 | 6.06 | 22 | 4 | 18.18 | 55 | 6 | 10.91 |
| 2011 | 31 | 2 | 6.45 | 21 | 1 | 4.76 | 52 | 3 | 5.77 |
| Mean % immigration | 3.97 | 13.15 | 7.05 | ||||||
| SD | 3.51 | 8.44 | 3.93 |
The population is depicted as the number of adult cheetah (>2 y old) and the number of adolescent or adult immigrants that were independent of their mothers.
Additional details on the methods are provided in SI Materials and Methods and the R code for the model is provided in Datasets S1–S3.
SI Materials and Methods
Assessing Cheetah Distribution and Status.
Africa.
Distributional mapping of cheetah in Africa used an expert-based mapping approach established for jaguar and tiger (37, 38) during four regional IUCN/Species Survival Commission conservation strategic planning workshops for cheetah and another similarly sparse and wide-ranging species, African wild dog Lycaon pictus (14–16, 21): regional strategic planning workshop for the conservation of cheetah and African wild dog in eastern Africa (February of 2007, Laikipia, Kenya); regional strategic planning workshop for the conservation of cheetah and African wild dog in southern Africa (November of 2007, Jwaneng, Botswana); regional strategic planning workshop for the conservation of cheetah and African wild dog in western, central, and northern Africa (January of 2012, Parc W, Niger); and regional strategy review workshop for the conservation of cheetah and African wild dog in southern Africa (August of 2015, Johannesburg, South Africa). Participants—some of whom were unable to attend the workshop in person—were contacted in advance of each workshop and asked to provide data from their own geographical area of expertise. Additional map refinements were conducted during 18 National Conservation Action or Management Planning Workshops (Algeria, Angola, Benin, Botswana, Burkina Faso, Chad, Ethiopia, Kenya, Malawi, Mozambique, Namibia, Niger, South Africa, South Sudan, Tanzania, Uganda, Zambia, and Zimbabwe) and from published reports and scientific articles.
Point locations provided the primary data on which distribution maps were based. A point location is a site where cheetah presence has been confirmed. Such records included sightings of live or dead animals; field signs, such as tracks or scats; attacks on livestock; and telemetry locations. Data associated with each point location included the number of animals seen (if any), their age (adult or juvenile), and the reliability of the observation. Workshop participants were asked to map locations from the last 10 y, although older data were also used for areas that had received little recent survey or monitoring effort and to confirm historic range. Point locations were combined with other relevant data (e.g., habitat and PA boundaries) and used to delineate geographic range polygons. All maps used the Albers equal area conic projection.
All land formerly occupied by the species was considered to fall inside the historical range. For some areas, detailed historical data on distribution were available; elsewhere, historical distribution was estimated based on the species’ broad habitat requirements. Resident range was defined as land where the species was known to be still resident. Because cheetah have excellent dispersal abilities, not every point location indicates the presence of a resident population; some may indicate transient dispersing animals. Resident range was recognized by (i) regular detection of the species in an area over a period of several years and/or (ii) evidence of breeding (e.g., young cheetah cubs sighted). Small fenced areas <1,000 km2 harboring cheetah, which are smaller than an average cheetah home range, were not considered to be able to support ecologically functioning cheetah populations and were excluded from resident range estimates.
Draft maps were prepared before each workshop, which were reviewed and modified during the workshop through discussion among participants until a consensus was achieved. Maps were further refined during a series of national conservation action planning workshops in most African cheetah range states and whenever significant new information became available. After the distribution maps were finalized, these outputs were used to evaluate the proportions of each species’ geographic range that fell inside vs. outside PAs according to IUCN PA categories I–IV (43).
Population size for each resident range polygon was estimated either from expert knowledge (based on surveys and monitoring) or using known densities from populations in comparable habitats facing similar levels of threat (14–16, 21, 28). Trends for each polygon were assigned as increasing, decreasing, stable, or unknown based on the expert judgement of those working at sites within polygons.
Asia.
Simulation Modeling.
Population simulations were conducted in R (40). Carrying capacity, in the absence of any data, was set at twice the original starting population to ensure that it had little impact on population trajectories or extinction rates. Mean and SD in the multiplicative growth rate (lambda) in PAs were set at the values observed in the female cheetah population in the Serengeti National Park from 1982 to 2011 (19) (i.e., with a mean of 1.0 and an SD of 0.13). These growth rate parameters implicitly include the impacts of competitors (such as lion Panthera leo and spotted hyena Crocuta crocuta) on overall growth rate, because both of these predators were present in this PA. Even in well-managed PAs, high cub mortality caused by predation may prevent cheetah populations from achieving lambda > 1 (41). Outside PAs, mean lambda was allowed to vary from 1 to 0.8, with the SD set to the same value as within PAs (0.13). For each year, growth rates inside and outside PAs were randomly chosen from a normal distribution.
Migration between subpopulations on protected and unprotected lands was assumed to be proportionate to each subpopulation, with a normal distribution and mean annual rates set at 0.0, 0.05, and 0.1. The SD in migration rate was set at one-half of the mean. The only data available from the long-term study population in the Serengeti National Park (42) suggest that a migration rate of between 0.05 and 0.1 is realistic, because between 1991 and 2011, adult and adolescent immigrants into this population occurred at a rate of 0.07 of the total population per year with an SD of 0.039 (Table S1).
The results depicted in Fig. 3A (with a migration rate of 0.05 and a starting population of 7,000, with 33% occurring in PAs) represent the most likely scenarios for a panmictic global cheetah population over three generations, where mean generation time for cheetah is 5 y (44). Fig. 3B explores the sensitivity of the percentage decline in population size generated by simulations to changes in the growth rate within PAs. We also explored population trajectories under alternative scenarios of low and high migration rates between PAs and unprotected land (Fig. S1) and an increasing growth rate within PAs (Fig. S2). Increasing carrying capacity to 10 times the starting population had no effect on population trajectories or extinction rates.
Data Availability
Data deposition: The data reported in this paper are published on the project website (www.cheetahandwilddog.org) and the International Union for the Conservation of Nature Red List site (www.iucnredlist.org).
Acknowledgments
We thank all of the participants of the strategic planning workshops and national action planning workshops for providing information on cheetah distribution. Karen Minkowski and Lisanne Petracca provided invaluable assistance with the distributional mapping. We also thank the Howard G. Buffett Foundation for supporting this work and Association of Zoos and Aquariums Safeguarding Animals From Extinction (AZA SAFE) for their support of the southern African review workshop in 2015. Additional support was provided by National Geographic's Big Cats Initiative.
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Data Availability
Data deposition: The data reported in this paper are published on the project website (www.cheetahandwilddog.org) and the International Union for the Conservation of Nature Red List site (www.iucnredlist.org).
Submission history
Published online: December 27, 2016
Published in issue: January 17, 2017
Keywords
Acknowledgments
We thank all of the participants of the strategic planning workshops and national action planning workshops for providing information on cheetah distribution. Karen Minkowski and Lisanne Petracca provided invaluable assistance with the distributional mapping. We also thank the Howard G. Buffett Foundation for supporting this work and Association of Zoos and Aquariums Safeguarding Animals From Extinction (AZA SAFE) for their support of the southern African review workshop in 2015. Additional support was provided by National Geographic's Big Cats Initiative.
Notes
This article is a PNAS Direct Submission.
See Commentary on page 430.
Authors
Competing Interests
The authors declare no conflict of interest.
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The global decline of cheetah Acinonyx jubatus and what it means for conservation, Proc. Natl. Acad. Sci. U.S.A.
114 (3) 528-533,
https://doi.org/10.1073/pnas.1611122114
(2017).
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