The authors have declared that no competing interests exist.
Conceived and designed the experiments: RB JGC. Performed the experiments: RB JGC FP AM RS. Analyzed the data: JGC. Wrote the paper: RB JGC.
Over 1,000 mammal species are red-listed by IUCN, as Critically Endangered, Endangered or Vulnerable. Conservation of many threatened mammal species, even inside protected areas, depends on costly active day-to-day defence against poaching, bushmeat hunting, invasive species and habitat encroachment. Many parks agencies worldwide now rely heavily on tourism for routine operational funding: >50% in some cases. This puts rare mammals at a new risk, from downturns in tourism driven by external socioeconomic factors. Using the survival of individual animals as a metric or currency of successful conservation, we calculate here what proportions of remaining populations of IUCN-redlisted mammal species are currently supported by funds from tourism. This proportion is ≥5% for over half of the species where relevant data exist, ≥15% for one fifth, and up to 66% in a few cases. Many of these species, especially the most endangered, survive only in one single remaining subpopulation. These proportions are not correlated either with global population sizes or recognition as wildlife tourism icons. Most of the more heavily tourism-dependent species, however, are medium sized (>7.5 kg) or larger. Historically, biological concern over the growth of tourism in protected areas has centered on direct disturbance to wildlife. These results show that conservation of threatened mammal species has become reliant on revenue from tourism to a previously unsuspected degree. On the one hand, this provides new opportunities for conservation funding; but on the other, dependence on such an uncertain source of funding is a new, large and growing threat to red-listed species.
Threatened species survive largely in parks; parks need money to remain operational; and some of that money comes from tourism. Therefore, tourism contributes to the conservation of these species in parks. We calculate here what proportions of remaining global populations of IUCN-redlisted mammal species effectively depend on tourism revenue. That is, we use the number of individual living animals, ie the sizes of remaining wild populations, as a basic metric or currency of
Arresting the continuing global decline in biodiversity is a major and broadly agreed international goal
Especially over the past decade, parks budgets in a number of countries have come to rely increasingly on revenues associated with tourism; principally fees and prices charged to visitors by parks agencies for entry, activities, accommodation and purchases
Here we quantify these risks by calculating the numbers and hence the proportions of remaining individuals that rely on tourism revenue for conservation in parks. We acknowledge that the political and financial dynamics of individual protected areas, as well as the population dynamics and conservation measures for individual species, are often highly complex. Sources of parks funding, however, are largely substitutable: parks agencies incur both conservation and recreation management expenditures irrespective of income, and funds are reallocated internally. At global scale, therefore, the simple accounting approach adopted here provides a valid mechanism to measure the reliance of red-listed mammal species on tourism revenue.
CR, Critically Endangered; EN, Endangered; VU, Vulnerable.
Species | IUCN | Global population (G) | Number of protected populations | Numbers protected by tourism (SR) |
Proportion protected (T) |
|
EN | ∼1200 | 2 | 793 | 66.1 |
|
CR | <1000 | 4 | 572 | 57.2 |
|
CR | <250 | 1 | 117 | 46.7 |
|
CR | ∼1000 | 3 | 409 | 40.9 |
|
EN | <1300 | 2 | 476 | 36.7 |
|
VU | 15000–24000 | 2 | 8797 | 36.7 |
|
EN | 1500 | ? | 512 | 34.1 |
|
EN | <1000 | 1 | 318 | 31.8 |
|
EN | <2500 | 1 | 795 | 31.8 |
|
VU | ∼25000 | >140 | 7227 | 28.9 |
|
VU | ∼500000 | ∼110 | 141371 | 28.3 |
|
CR | ∼600 | 3 | 169 | 28.1 |
|
CR | 4880 | 30 | 1067 | 21.9 |
|
EN | 1966–2447 | 7 | 490 | 20.0 |
|
VU | ∼3000 | 17 | 554 | 18.5 |
|
VU | 3500–5100 | 8 | 897 | 17.6 |
|
EN | 1000 | 4 | 164 | 16.4 |
|
EN | <5500 | 14 | 895 | 16.3 |
|
VU | 125000–148001 | 148 | 21015 | 14.2 |
|
VU | <10000 | 9 | 1804 | 14.1 |
|
CR | <5000 | 1 | 655 | 13.1 |
|
EN | 3000–5500 | 53 | 685 | 12.5 |
|
VU | 2575 | 10 | 320 | 12.4 |
|
CR | <250 | 2 | 28 | 11.4 |
|
VU | <10000 | 12 | 1134 | 11.3 |
|
VU | 7000–9000 | 1 | 860 | 9.6 |
|
CR | 2250 | 2 | 213 | 9.5 |
|
CR | 115 | 1 | 11 | 9.4 |
|
CR | 40 | 1 | 4 | 9.4 |
|
EN | <2000 | 1 | 183 | 9.2 |
|
EN | <10000 | 851 | 8.5 | |
|
VU | ∼10000 | 9 | 850 | 8.5 |
|
VU | ∼6000 | 3 | 484 | 8.1 |
|
CR | <500 | 1 | 40 | 8.0 |
|
VU | >25000 | 2 | 1984 | 7.9 |
|
VU | 20000–25000 | 25 | 1917 | 7.7 |
|
VU | 2000 | 2 | 142 | 7.1 |
|
EN | ∼400000 | 9 | 27589 | 6.9 |
|
EN | 1000 | 1 | 64 | 6.4 |
|
EN | 41410–52345 | >33 | 3294 | 6.3 |
|
EN | 500–1000 | 9 | 62 | 6.2 |
|
CR | ∼100 | 1 | 6 | 5.9 |
|
CR | <1000 | ? | 59 | 5.9 |
|
VU | 7000–10000 | 19 | 566 | 5.7 |
|
VU | <10000 | 3 | 567 | 5.7 |
|
EN | 450 | 3 | 24 | 5.2 |
|
CR | <7000 | 8 | 366 | 5.2 |
|
EN | <1000 | 6 | 52 | 5.2 |
|
EN | <2500 | 1 | 125 | 5.0 |
|
EN | <2500 | 1 | 125 | 5.0 |
|
CR | <250 | 1 | 12 | 5.0 |
|
CR | ∼100 | 0 | 5 | 5.0 |
|
EN | <10000 | 1 | 497 | 5.0 |
|
CR | <500 | 2 | 24 | 4.8 |
|
CR | <250 | 1 | 11 | 4.6 |
|
CR | 855 | 4 | 34 | 4.0 |
|
EN | ∼1500 | 2 | 59 | 4.0 |
|
EN | 3000–5000 | >40 | 200 | 3.9 |
|
CR | <10000 | 9 | 391 | 3.9 |
|
CR | 400 | 2 | 14 | 3.6 |
|
EN | 4080–6590 | 27 | 234 | 3.6 |
|
EN | <4000 | 17 | 136 | 3.4 |
|
VU | <20000 | >175 | 672 | 3.4 |
|
VU | 25000 | 8 | 824 | 3.3 |
|
CR | ∼6000 | 3 | 187 | 3.1 |
|
VU | 4000 | 4 | 124 | 3.1 |
|
EN | 2000–2500 | 4 | 73 | 2.9 |
|
EN | <2501 | 3 | 71 | 2.8 |
|
EN | 124000–413000 | 4 | 11179 | 2.7 |
|
EN | 10000–25000 | ? | 661 | 2.6 |
|
EN | 6001–15000 | 2 | 383 | 2.6 |
|
EN | 500–1000 | 6 | 26 | 2.6 |
|
EN | 10000–15400 | 1 | 367 | 2.4 |
|
EN | 8000 | 1 | 189 | 2.4 |
|
EN | 6000–10000 | 1 | 229 | 2.3 |
|
EN | <1500 | 8 | 33 | 2.2 |
|
VU | ∼10000 | 69 | 174 | 1.7 |
|
CR | <150 | 3 | 2 | 1.6 |
|
VU | <2500 | 2 | 34 | 1.4 |
|
EN | ∼24000 | 4 | 320 | 1.3 |
|
VU | <10000 | 6 | 131 | 1.3 |
|
VU | ∼45000 | 2 | 587 | 1.3 |
|
EN | 2478–12120 | 2 | 146 | 1.2 |
|
EN | 2650–3540 | 1 | 41 | 1.2 |
|
CR | <100 | 2 | 1 | 1.0 |
|
EN | 2000 | 1 | 19 | 0.9 |
|
CR | <1500 | 2 | 11 | 0.7 |
|
EN | ∼7265 | 1 | 37 | 0.5 |
|
EN | <5000 | 25 | 0.5 | |
|
CR | <250 | 2 | 1 | 0.2 |
R: Argentina 26.5%, Australia 9.4%, Bolivia 8.1%, Botswana 81.1%, Brazil 7.8%, Canada 13.7%, Chile 37.9%, Colombia 7.6%, Costa Rica 18.2%, Cuba 5.0%, Guatemala 30.8%, Honduras 25.0%, India 8.0%, Kenya 66.1%, Madagascar 5.0%, Mexico 5.9%, Namibia 8.9%, Nepal 35.6%, Nicaragua 8.3%, Panama 13.1%, Philippines 53.0%, South Africa 47.2%, Tanzania 36.7%, Thailand 24.6%, United States 7.4%, Zambia 48.3%. Data from national parks agencies and international compendia (8,9).
For each species
Dotted lines indicate 7.5 kg mean body weight, and 17% protected.
Subpopulation data S (
For many species, data are only available for a subset of known subpopulations. Both the proportions of populations represented, and the reliability of the data concerned, differ considerably between species. For some individual species, reported population data may also change quite rapidly. IUCN Red Lists show common hippopotamus
The scarcity of data reflects the general paucity of information on threatened-species populations and parks-agency operations worldwide. The data presented here, however, are all that are currently available, and are more than adequate to demonstrate general patterns related to tourism revenues. Previous studies
Of the 1131 IUCN-redlisted mammal species worldwide
T≥5% for 58% of species with available data, T≥10% for 28%, and T≥15% for 20% (
There is no correlation between reliance on tourism revenue, and recognition as a wildlife tourism icon, confirming that the data are not biased towards high-T species. Some tourism icon species, such as lion, one-horned rhinoceros and African elephant, have high T (≥10%), but others such as tiger, golden-headed lion tamarin, red panda and a number of lemur species, have low T (<5%) (
Some of these species are already at particular risk since they survive only at a single site in one country. Indeed, this is one factor considered by IUCN in the allocation of CR or EN redlisting status. For the 90 species assessed here, 27% survive in only a single population, and reliance on tourism revenue is proportionately higher for more severely threatened species which occur in fewer remaining subpopulations (
If each individual of each endangered (EN) or critically endangered (CR) mammal species is given equal weight, so that, e.g., one Gilbert’s potoroo is counted the same as one hippopotamus, then in aggregate, tourism protects 4.9% of the 40 EN and 9.6% of the 26 CR mammal species with data available. That is, reliance on tourism revenue is twice as severe for critically endangered as for endangered species.
Our estimates of T are conservative for all species listed, for two main reasons. Firstly, we used maximum published estimates for G. The degree of underestimation from this factor, for different species a, depends on the range of different estimates for Ga. Secondly, we calculated Ta by dividing Σin SiaRia for the n subpopulations where S and R data are available for each species a, by the global totals Ga which also include subpopulations without such data. Thus for the common hippopotamus, as noted earlier, Σin SiaRia is calculated for 4 subpopulations, but Ga is for at least 138. We do not extrapolate from subpopulations with data on S and R to those without, because parks budget structures differ greatly between nations. If parks budgets were available for all African nations, for example, T estimates for African elephant would be increased. The degree of underestimation from this factor depends on the completeness of IUCN subpopulation data for each species, the numbers of subpopulations where it is known to occur, and the countries in which those subpopulations occur.
Arguably, the conservation values of one living individual of different threatened species are not equal, but inversely proportional to total remaining global populations. We could calculate a more complex conservation currency where individuals of different species are weighted according to relative rarity, but this would be less robust than the simpler metric adopted here. Alternatively, we could potentially use a probabilistic rather than an accounting model, calculating how support from tourism increases survival probabilities for each subpopulation, and thus for the species overall. This is not yet feasible, because of uncertainties over raw data
This analysis focuses on public protected areas, because these are the most significant conservation reserves for most IUCN-redlisted mammal species. Conservation on other land tenures, however
With few exceptions
Rather than relying on tourism, a safer and more effective strategy for conservation of threatened mammal species in impoverished nations would be for international donors to fund park ranger salaries and equipment directly. For species with only a few small subpopulations remaining, funding may also be required for captive breeding and translocations. Tourism does contribute to these
From a research perspective, this contribution answers the many recent calls
(DOC)
(DOC)
We thank M Hoffmann and C Hilton-Taylor, IUCN, for updated data on S and G. We thank Les Carlisle, &Beyond, for a field discussion which yielded the idea of using individual animals as a measureable conservation currency.