Scripta Varia

The State of the World's Biodiversity

Stuart Pimm (Duke University) and Peter Raven (Missouri Botanical Garden)


  • Taxonomists have described about 1.7 million species. Many more remain unknown, with huge uncertainties in the numbers of species of insects and fungi.
  • Current and recent rates of extinction are ~100 extinctions per million species per year.
  • Background rates of extinction — i.e. before human actions inflate them — are probably 0.1 extinctions per million species per year.
  • Unlike many other environmental threats that we can reverse, extinctions are irreversible. We can ask how quickly biodiversity can recover following the massive loss of species. The rates at which species can diversify (and so recover from the current massive loss of species) are on the same order as their extinction rates. Thus, human actions are destroying species 1000 times faster than the process of speciation creates them.
  • Species most likely to face extinction are rare; rare either because they have very small geographic ranges or have a low population density with a larger range.
  • Small-ranged species tend to be concentrated in a few areas that often do not hold the greatest number of species. About 90% of all threatened species are those with small geographical ranges. Some threatened animals have large ranges, but very low densities, because of large body size or feeding habitat (such as predators) or other habitats that bring them into conflict with human activities.
  • Extinctions occur most often when human impacts collide with the places having many rare species.
  • While habitat loss is the leading cause of extinctions, global warming is expected to cause extinctions that are additive to those habitat loss causes.
  • Increasing human population and especially increased human aspirations will increase the future rates of extinction.



In this chapter, we ask several simple questions. How many species there are — including how many and known and how many are not. How fast as species now going extinct? How fast do species go extinct normally — and how fast do they diversify (and so can recover from the current massive loss of species. Finally, where are extinctions concentrated and how can we use this information to prevent extinctions?

How many species are there?

This deceptively simple question has a rich — and even theological — pedigree. (Westwood 1833) speculated “On the probable number of species of insects in the Creation”. In the last few decades many have grappled with the question, reaching widely varying conclusions (Gaston 1991; May & Beverton 1990; Mora et al. 2011; Stork 1993). Clearly, far more species exist than taxonomists have named. Taxonomists have also complicated matters by inadvertently giving multiple names to many known species. A recent, thorough compilation of previous estimates by (Chapman 2009), plus new studies that propose novel methods of estimation, motivated a review of progress (Scheffers et al. 2011).

How many species are known?

Table 1 simplifies Chapman’s compilation of previous estimates of species. To it, we add additional data to illustrate key debates. As have others, we restrict our analyses to metazoans — fungi, plants and animals — because for viruses, bacteria and other microorganisms the definition of “species” is unclear. The column “Currently Catalogued” counts known species within various taxonomic groupings, and represents the work of tens of thousands of taxonomists across hundreds of years. Despite this massive scientific undertaking, simply adding up the current numbers of “known” species, even for well-studied groups like birds, is itself not straightforward. Synonymy is the problem.

Large ranges in the numbers of species arise because taxonomists have described the same species more than once. This is not surprising. Species’ descriptions can come from different taxonomists on different continents in different generations. Fixing this substantial problem requires considerable effort. For flowering plants, for example, the highest estimate of known species is twice that of the lowest; synonymy is suspected to be upwards of ~60-78% for some plant groups (Scotland & Wortley 2003).

For plants, The World Checklist of Selected Plant Families is gradually analysing the numbers, family by family. Kew and many partners intend this process to lead to a Plants of the World Online Portal. It will allow all names to be unambiguously referred to an accepted name according to an expert’s opinion. In parallel, a computer-based, collaborative account of all the world’s plants, the World Flora Online, driven by a network of institutions headquartered at the Missouri Botanical Garden, will provide authoritative evaluations of all plant species, with a deadline for completion by 2020. We hope these two efforts will soon come into register with one another.

How many species are unknown?

The completeness of global inventories varies greatly (see “Estimated” in Table 1). Inventories are ~97% complete for mammals, 80-90% complete for flowering plants, 79% complete for fish, 67% complete for amphibians and ~30% complete for arthropods (Hamilton et al. 2010; Joppa et al. 2010; Mora et al. 2008) (Table 1). Taxonomic effort is near evenly distributed among vertebrates, plants and invertebrates, yet plants have roughly 10 times, and invertebrates 100 times, more known species than vertebrates.

Global inventories (Table 1 “Estimated”) come from a variety of methods, including the expert opinions of taxonomists specialized on the various taxa. Differing methods often result in estimates that vary widely for a given group; for instance, estimates for fungi range nearly twenty-fold.

The hyper-estimates of species numbers

The greatest uncertainties in numbers involve “hyper-estimates”by which we mean individual totals of 5 million species or more. For example, (Grassle & Maciolek 1992)used the relationship between the numbers of invertebrates found in samples of areas of increasing extent to extrapolate the total number of species in the deep sea. They estimated that the world’s deep seafloor could have up to 10 million species — a large total and one several orders of magnitude larger than that found in their geographically restricted sample.

Numbers this large capture the public imagination and invite scientific controversy. In the case of marine invertebrates, such extrapolations from local to global seafloor diversity were unwarranted because of the obvious doubts about scaling up from a small to a much larger geographical scale. Several authors have raised general concerns about the limitations of scaling up from estimates collected at a single spatial scale (ØDegaard 2000) (Gering et al. 2007; Lambshead & Boucher 2003).

For tropical insects, the best known hyper-estimate was Erwin’s (Erwin 1982) astounding conjecture of 30 million species. His approach incorporated data from the number of beetle species associated uniquely with a single species of tropical rainforest tree in Panama. His estimate generated much criticism, primarily from those concerned about the assumptions underlying such a “small to large” extrapolation. The method, however, spawned considerable interest and research. Fundamental to the controversy was the degree of host specificity of herbivorous insects on their food plants, which Erwin’s assumed to be high for his beetles. (Novotny et al. 2007; ØDegaard 2000) and others found considerably lower host specificity than Erwin suggested, perhaps by a factor of four or five. The resulting global estimate of insect species richness has accordingly dropped sharply.

(Hamilton et al. 2010) highlighted the sensitivity of Erwin’s model to its input parameters. As with earlier studies, their estimate requires values for the average effective specialization of herbivorous beetle species across all tree species, a correction factor for beetle species that are not herbivorous, the proportion of canopy arthropod species that are beetles, the proportion of all arthropod species found in the canopy, and the number of tropical tree species. Their approach uniformly and randomly sampled plausible ranges for each of these numbers. Some 90% of these parameter combinations fell between 3.6 and 11.4 million species (Novotny et al. 2007).

Fungi are poorly known. (Hawksworth 1991) started with the 6:1 ratio of fungi to flowering plant species found in Britain, where both groups are well known, and extrapolated this ratio to the global total for flowering plants, yielding an estimate of 1.62 million species of fungi globally. (May 1991) was sharply critical of this estimate because it again involved a small- to large-scale extrapolation. A key concern, he argued, is that the species-rich tropics are unlikely to have the same ratio of fungi to plants as does Britain. If so, then collections of fungi from the tropics should find that over 95% of the species encountered would be new, given that only ~70,000 fungi had been catalogued globally to date. The actual percentages of new species from tropical samples were much smaller. An alternative approach by (Mora et al. 2011) estimates ~611,000 fungal species globally and seemingly supports May’s more conservative estimate of ~500,000 fungal species.

Such low estimates of fungi species have spawned strident criticisms. First, small, quickly obtained samples of species will not be random ones, but dominated by well-known, widespread species. Second, (Hawksworth 1991) emphasized not just fungal and plant associations, but the strong associations of fungi with insects. Each beetle species might have its own unique fungus. Third, Bass and Richards (Bass & Richards 2011) point out that over the past decade, new methods in molecular biology and environmental probing have substantially increased the rate of species’ descriptions.

(Cannon 1997) estimates that there are 9.9 million species of fungi. (O'Brien et al. 2005) estimate 3.5 to 5.1 million species. Very high genetic diversity of fungi in soil samples — 491 distinct fungal genomes in pine-forest soil samples, and 616 in soils from mixed-hardwood forests, respectively — initiate these hyper-estimates. They emerge, as before, from extrapolating ratios from local to global scales, so the concerns about scaling also apply here. At present, there are no comparable genomic surveys in tropical moist forests showing exceptionally high fungal richness there, as would be expected. Moreover, no one has yet shown how communities of fungal genomes change over large geographical areas. In an important potential advance to this ongoing debate, Blackwell [39] lists locations and hosts known to contain rich — and poorly known — fungal communities. These are places where one might test key hypotheses.

Scaling the tree of life

(Mora et al. 2011) used the rates of description to fit asymptotic regression models to taxon-accumulation curves over time for phyla, classes, orders, families, and genera. Using the asymptotic estimates for animals, the ratios of classes per phyla, orders per class, families per order, and genera per family were strikingly similar. On this basis, they posited that the ratio of species per genus would be the same globally and so predicted 8,750,000 terrestrial and 2,210,000 marine species. There is no theoretical reason to make this final supposition, but to the extent that they could compare the best estimates of numbers of species within phyla, there was broad agreement with their predictions.

Rates of species discovery

Early attempts to estimate the asymptotic number of species over time assumed that the rate of description will slow over time (Costello & Wilson 2011; Ricotta et al. 2002; Solow & Smith 2005)]. For birds globally, and for some taxa regionally, the rates of description are slowing over time and asymptotic approaches provide reasonable estimates. (Mora et al. 2011) employ this approach to estimate the numbers of higher taxa as well.

For most taxa, not only are the rates of species description increasing, they are doing so exponentially, so ruling out estimates of asymptotes. The numbers of taxonomists are also increasing exponentially (Joppa et al. 2011b). To account for this, a more truly mechanistic model accounts for the taxonomic effort and taxonomic efficiency required to document previously unknown species. Initially proposed by (Joppa et al. 2011a; Joppa et al. 2010) this defines taxonomic effort as the number of taxonomists involved in describing species and taxonomic efficiency as an increase in the number of species described per taxonomist, adjusted for the continually diminishing pool of as-yet-unknown species.

How well does this model perform? Validating it by expert opinion revealed broad agreement with its predictions (Joppa et al. 2010). In some cases the numbers of species described per taxonomist remains roughly constant even as the pool of missing species inevitably declines. Taxonomists likely describe only so many species in a year — regardless of how many missing species there are — and perhaps work through the backlog methodically, genus by genus.

Where are the missing species?

As we show below, knowing where species live is vital for understanding future rates of species extinction — and setting international priorities for conservation. Incomplete information might leave us unable effectively to prioritize where to allocate conservation efforts. For example, the ‘biodiversity hotspots’ (Myers et al. 2000) combine a measure of habitat destruction (<30% habitat remaining) with the numbers of known endemic flowering plant species (>1,500) (Pimm et al. 2014). Recent studies by (Joppa et al. 2011a) suggest missing plant species will be concentrated in the biodiversity hotspots (Figure 1) — places such as Central America, the northern Andes and South Africa, where, by definition, the threat of habitat loss is greatest.


Herbaria and perhaps by extension, museums, might harbour many of the missing species. For example, (Bebber et al. 2007) found that existing herbaria material typically took decades to describe and perhaps half of all missing plant species were already in herbaria.

Recent advances in DNA barcoding make it easier to discriminate similar species (Hebert et al. 2004) thereby accelerating species descriptions, and generally aiding better taxonomy. Genetic methods used to detect fungi discussed above are rapidly expanding our knowledge of what could be an extremely diverse group, but one poorly sampled by traditional morphological approaches.

Many communities of taxonomists are now addressing the tedious but vital issue of synonymy and placing their lists and taxonomic decisions into the public domain, especially on websites. These include sites for flowering plants (, spiders ( amphibians (, birds (, and mammals (

Global efforts to catalogue all species, such as All-Species (, GBIF (, Species 2000 ( and Tree of Life (, are now readily available online.

Efforts to map where species occur are progressing. Smart phones and software-website applications such as iNaturalist ( that link data directly into the IUCN Red Lists, the Global Biodiversity Information Facility, and other pre-existing databases. Crowd-sourcing of species mapping could greatly expand these databases, which are major contributions to our knowledge of where species live. Such databases are already promoting the discovery of missing species, revealing those that do not fit known descriptions.

How fast are species going extinct?

 “… a mass extinction crisis, with a rate of extinction now 1,000 times higher than the normal background rate”— Al Gore (2006) in the Academy Award-winning documentary “An Inconvenient Truth”. (Quoted as p. 152, (Gore 2006)).

As Gore’s remark testifies, it has become standard to quantify present extinctions as rates and then to compare them to some background that typifies geological history. (Mass extinction events are understood to be exceptions.) Gore’s and similar statements emerged via secondary sources originally derived from (Pimm et al. 1995) who estimated “recent extinction rates are 100 to 1,000 times their pre-human levels”.

Before 1995, the literature quoted statistics on current extinctions in “species per day”. Estimates ranged from a “minimum” of three (Myers 1989) to “a hundred species per day” (Stork 2010). More than uncertainties about the extinctions themselves, the numbers reflected the wide range of estimates for how many eukaryote species there are that we have already discussed.

The uncertainty in the “species per day” estimates also posed problems when dealing with critics of environmental concerns who demanded the scientific names of those recently extinct (Stork 2010). Of course, taxonomists have described only a small fraction of species, while the IUCN’s Red List ( has assessed an even smaller fraction of those — ~53,000 species. To avoid the necessarily complex caveats for extinctions per day estimates, (Pimm et al. 1995) deliberately chose to replace this metric with a proportional rate that they could calculate for a given taxon.

Estimating the current rates of extinctions is a straightforward process: one follows a cohort of species for some specified interval and records what fraction succumbed (Pimm et al. 2006; Pimm et al. 1995) (Pimm et al. 2014). For numerical convenience, we calculate extinctions per million species-years (E/MSY). This method does not count species, such as the dodo, that went extinct before their description. For example, taxonomists described 1230 species of birds since 1900, of which 13 have become extinct (Table 2). This cohort accumulated 98,334 species years — meaning that an average species has been known for 80 years — and so the extinction rate is 13*106/98,334 = 132 E/MSY.

Extinction rates from cohort analyses average about 100 E/MSY (Table 2). Local rates from regions at great risk can be much higher, for example, North American rivers and lakes for fish and gastropods and for cichlid fishes in Africa’s Lake Victoria (Pimm et al. 2014). Given that many species are still undescribed and many species with small ranges are recent discoveries, these numbers are underestimates. Many species will have gone or be going extinct before description. Extinction rates of species described after 1900 are considerably higher than those described before, reflecting the former’s greater rarity (Table 2).

Rates of extinction increase with improved knowledge — since taxonomists describe widespread common species before local and rare ones, and the latter are more vulnerable to human actions. Thus, recent extinction rates based on poorly known taxa (such as insects) may be substantial underestimates since many rare species are undescribed.

How fast should species be going extinct?

(De Vos et al. 2015) explored three lines of evidence towards achieving the more difficult task of estimating this “background rate” of extinction. By this, we mean the geologically recent rates of extinction, before human actions inflated them.

Extinction rates from the fossil record

The fossil record provides essential information, but it is very limited in temporal resolution and taxonomic breadth (Purvis 2008). Moreover, most paleontological studies assess genera, not species (Flessa & Jablonski 1985). The one conclusion one can draw from (Barnosky et al. 2011) are the large uncertainties in the extinction rates fossils provide.

(Alroy 1996) found the mean rate for Cenozoic mammals to be 0.165 extinctions of genera per million genera years (see his figure 6). (Harnik et al. 2012) examined a variety of marine taxa. What they call “extinction rate” is, in fact, a dimensionless extinction fraction, the natural logarithm of the fractional survival of genera measured over an average stage length of 7 million years. Converting these fractions to their corresponding rates yields values for the last few million years of 0.06 genera extinctions per million genera – years for cetaceans, 0.04 for marine carnivores, and for a variety of marine invertebrates between the values of 0.001 (brachiopods) and 0.01 (echinoids). Put another way, only 1% of echinoid genera are lost per million years, were we to make the interpolation.

There are many caveats.

First, fossil estimates suffer the obvious bias that genera may be present somewhere before they are first recorded and after they are last recorded. Thus, unless corrected, longevities are potentially underestimated and the extinction rates are overestimated (Foote & Raup 2010). Fossil data likely most accurately reflect rates during events, such as the five previous mass extinctions, when extinction rates were episodically high.

Second, whether it is reasonable to interpolate fractional survivorship based on stages averaging several million years to shorter intervals of a million years is problematical. For this reason, (Barnosky et al. 2011) show estimates as a function of the interval over which they calculated them. Any interpolation imputes homogenous rates of extinction across geological stages, while evidence suggests extinction rates are pulsed towards their end (Alroy 2008; Foote 2009). Indeed, changes in floras and faunas often define when one stage ends and the other starts. If so, for millions of years, the rates would be even lower than reported values, followed by episodes when they are higher.

In any case, comparing rates of generic extinctions to species extinction is complex (Russell et al. 1998). For mammals, with 4.4 species per genus, were all genera to have four species in them, binomial probabilities show that a species rate of 0.63 E/MSY would give the observed generic rate of 0.165 (Alroy 1996), and for five species, 0.69 E/MSY. There are two problems with this. Most generic extinctions are likely those in monotypic genera. Second, these calculations assume statistical independence. As Russell et al. (1998) show, species extinctions within a genus are highly contingent. Some genera and some places are much more vulnerable than others. Combined, these considerations would lead to the species extinction rate being close to the generic rate, i.e. 0.165 E/MSY.

In short, in comparing the extinction rates of fossils with present biota, we are contrasting genera with species, and, of course, typically very different taxa, and often marine with terrestrial ecosystems.

Species extinction rates from molecular phylogenies

Molecular phylogenies provide an appealing alternative to the fossil record’s shortcomings, covering a large range of taxa, time periods, and environments. The simplest case expects a single lineage to grow to a clade size of N species, E(N), during time, t, according to

E(N) = exp (r * t)                                                                                                    (1)

The net diversification rate, r, is the speciation, λ, minus the extinction, µ, (λ – µ).

(λ – µ) = r = ln(N)/t                                                                                                (2)

Can one separately estimate the speciation and extinction rates, not just their difference? Equation (1) expects the plot of the logarithm of the number of lineages through time (LTT) to be linear, with slope λ – µ but with an important qualification. In the limit of the present day, there are no extinctions of the most recent taxa — they have not yet happened. Thus, near the present, the LTT slope should increase and approach λ, the speciation rate (Nee 2006). This allows the separate calculation of the speciation and extinction rates.

Practice is considerably more complicated than this simple theory (Etienne et al. 2012; Morlon et al. 2011): λ and µ may be time-dependent, be functionally related, both may depend on the number of species already present, and they will likely vary from place-to-place and among different taxa. (McPeek 2008) found that 80% of the studies compiled have LTT graphs that curve downwards on the log-linear scale.

Such studies yield a maximum likelihood estimate of zero extinction, but we can reasonably ask how certain are these estimates. Not all the LTT graphs involve smooth increases in the numbers of species over time. Many show irregularities that increase the uncertainty of the estimates, widening the probable ranges of parameters. That complication means we must employ methods that explore the probability distributions of the parameters we estimate, rather than inferring a most likely point estimate. There are also concerns about how many species might be missing from the clades analysed.

To address these concerns, (De Vos et al. 2015) undertook an extensive set of simulations of known diversifications, with varying fractions of species removed from these modelled clades, and in some cases, different rates of diversification. At best, their simulations demonstrate that the underestimation of extinction due to complex diversification processes may be only slight: they always recovered the correct order of magnitude of absolute extinction across replicate phylogenies, even though individual estimates were associated with large uncertainties. They concluded that phylogenies of extant taxa should at least contain some information on extinction rates (Pyron & Burbrink 2013).

Finally, taxonomists may fall short of recognizing all lineages that will give rise to new species in the future (Phillimore & Price 2008). The entirely arbitrary taxonomic decision of whether to group geographical isolated populations as one species or split them into several recently derived species will affect estimates of extinction rates.

Despite those difficulties, an important conclusion emerges. Of the 140 phylogenies, (De Vos et al. 2015) analysed, all but four had median estimated extinction rates of < 0.4 E/MSY and only two (one arthropod and one mollusc) had rates > 1 and those were < 1.5. These estimates match those of (Weir & Schluter 2007) who estimated bird and mammal extinctions that range from 0.08 E/MSY at the equator — where there are the most species — to ~0.4-0.6 E/MSY at 50° latitude — where they are far fewer. Thus, despite the methodological hurdles and the potentially confounding whims of taxonomists, there is consistent evidence that background extinction rates are below one extinction per million species-years and most likely much less than this.

How fast can species diversify?

In contrast to the methodological complexities of separating speciation and extinction rates, it is relatively easy to calculate their difference — the rates of diversification. Consequently, there are many estimates of diversification. Table 3 shows median diversification rates from ~0.05 to ~0.2 new species per species per million years for a disparate group of animals and plants. Rates > 1.0 are exceptional.

(Valente et al. 2010) explicitly addressed the issue of how fast taxa can diversify. They analysed the genus Dianthus, (carnations, Caryophyllaceae) and found net diversification rates of up to 16 new species per species per million years. This puts them well above 11 other plant groups, to which they compared them, the highest rate of which was Andean Lupinus (lupins, Fabaceae) at ~2 (Koenen et al. 2013)) For birds, the record holder is the group of Southeast Asian Zosterops, (white-eyes, Zosteropidae), at 2.6 new species per species per million years. Others classify some of these “species” as subspecies, which would reduce that rate.

(Valente et al. 2010) also discuss the cichlids of east African lakes that have speciated rapidly, with estimates of stem diversification up to 6 new species per species per million years for Lake Malawi. They notice that rates roughly ten times these for Lake Victoria are possible if the ~500 species now present are all descended from just one ancestor after the lake dried out 14,700 years ago. To achieve such rates, however, one must completely exclude the possibility of several species surviving that desiccation in refugia. An additional example is the rapid divergence of Enallagma damselflies that have added 23 new species from 7 lineages in the last 250,000 years (Turgeon et al. 2005). In contrast are lineages such as Ginkgo biloba that appears to have changed little since the Jurassic (Zhou & Zheng 2003).


We have reviewed three lines of evidence towards obtaining an order of magnitude estimate of the background rate of extinction. We recognize, of course, that this rate will vary over time, space, and taxon. The fossil data are the most direct, but they have many limitations. Separating extinction and speciation rates from phylogenies is methodologically difficult and generates ongoing, vigorous debate. Rates of diversification provide less direct information, but there are many compilations of them across different taxa and ecosystems. Diversification rates are ~0.05 to ~0.2 new species per species per million years, with exceptional rates of > 1. The question is what these tell us about extinction rates.

We notice that the fossil record shows that overall species richness is increasing over time (Rosenzweig 1995). Certainly, some clades are shrinking — (Quental & Marshall 2011) list examples — but these fewer than those increasing. The direct estimates of extinction rates from phylogenies estimated above are also low. The insights from our simulation models show that when averaged across set of phylogenies, the models placed these rates within the right order of magnitude. In sort, what we see in observed phylogenies also precludes high extinction rates.

Simply, there is no widespread evidence for high recent extinction rates from either the fossil record or from molecular phylogenies. Thus, overall, extinction rates cannot exceed diversification rates. Combining the evidence from the fossil record, from the separation of speciation and extinction rates from molecular phylogenies, and overall diversification rates, we conclude that background extinctions rates are approximately 0.1 extinctions per million species per year, whereupon current extinction rates are 1,000 times higher.


How fast will species become extinct in the future?

The best guide to future extinctions, is the IUCN Red List (IUCN 2016). It assigns species as of Least Concern, through Near-Threatened to three progressively escalating categories of Threatened species (Vulnerable, Endangered, Critically Endangered) and Extinct. Other than the last category, these constitute an expert system of the relative likelihood that species will become extinct in the future, given present conditions. The most important criteria in determining risk are how small is a species’ geographic range and whether human actions and shrinking the available habitat. Other factors include whether humans hunt, collect, or kill the species for other reasons. There are two major problems with the Red List: the incompleteness of the data and the inconsistency of the assessments.


By January 2017, IUCN had considered 85,604 of >1.7 million named species. Animals get the most attention. Of the 63,303 total animals assessed, 11,923 were judged to be data deficient — meaning there is not enough information to know their status. This nearly always means they are rare and a large fraction of them may be threatened with extinction, were more information available. Of the remaining, 51,380, 1,285, were extinct or probably so, while 12,630 were threatened, with 2,696 of them deemed critically endangered. These species are mostly terrestrial and freshwater animals. Indeed, birds, mammals, and amphibians constitute ~22,000 of the species assessed.

Efforts are expanding the limited data from oceans for which only 2% of species are assessed compared to 3.6% of all known species (67). (Peters et al. 2013) assessed snails of the genus Conus and (Carpenter & et al. 2008) assessed corals. (Dulvy & al. 2014) assessed 1041 known shark and ray species: 17.4% are threatened, most by overexploitation, and most of them large-bodied, shallow water, coastal species. Only 37.4% of species were deemed of Least Concern, the lowest fraction in any vertebrate group assessed.

For plants, only 22,253 have been assessed, for which 1,780 have insufficient information. Some 11,643 are threatened, 2,506 are critically endangered and 302 are extinct. Almost not fungi have been assessed. Usefully, (Kew 2016) tabulates the various estimates of how many plant species are at risk of extinction. Most of the estimates are in the 20 to 33% range, and it plumps for “1 in 5” as a rough estimate. Their details highlight the complexities. (Kew 2016) argues that the >50% fraction of plants that are threatened is too high because the Red List emphasised taxa at particularly at risk of extinction.

An estimate of 20% is broadly comparable with well-known vertebrate taxa for which one can separately calculate extinction rates directly from following species fates from their year of scientific description (Table 2).

(Kew 2016) tabulations show higher percentages of species at risk when one sensibly adds in the predicted numbers of species as-yet unknown to the total of threatened species. They are likely to be rare, which is often why we have not yet found them. Moreover, they are likely to be where the recent discoveries are — see above — places where habitat loss is proceeding rapidly. The alarming question is whether these as-yet unknown species will survive long enough for us to collect them.


While the IUCN Red List classifies a species risk of extinction, using an open, democratic and rule-based approach, it suffers from a lack of consistency. In particular, (Ocampo-Peñuela et al. 2016) show that important geospatial data do not enter this process explicitly or efficiently. Rapid growth in availability of remotely sensed observations provide fine-scale data on elevation and increasingly sophisticated characterizations of land cover and its changes. These data readily show that species are likely not present within many areas within the overall envelopes of their distributions. Additionally, global databases on protected areas inform how extensively ranges are protected. (Ocampo-Peñuela et al. 2016) selected 586 endemic and threatened forest bird species from six of the world’s most biodiverse and threatened places (Atlantic Forest of Brazil, Central America, Western Andes of Colombia, Madagascar, Sumatra, and Southeast Asia). The Red List deems 18% of these species to be threatened (15 critically endangered, 29 endangered, and 64 vulnerable). Inevitably, after refining ranges by elevation and forest cover, ranges shrink. Do they do so consistently? For example, refined ranges of critically endangered species might reduce by (say) 50%, but so might the ranges of endangered, vulnerable, and non-threatened species. Critically, this is not the case. (Ocampo-Peñuela et al. 2016) found that 43% of species fall below the range threshold where comparable species are deemed threatened. Some 210 bird species belong in a higher threat category than current Red List placement, including 189 species that are currently deemed non-threatened. Incorporating readily available spatial data substantially increases the numbers of species that should be considered at risk. Likely the Red List has also seriously underestimated the fractions of other taxa that are at risk of extinction.

Where at the species that are at risk of extinction?

These concerns motivate the next question of asking where species are at risk of extinction. There are at least seven “laws” to describe the geographical patterns of where species occur. By “law,” we mean a general, widespread pattern, that is, one found across many groups of species and many regions of the world. Recall that (Wallace 1855) described the general patterns of evolution in his famous “Sarawak Law” paper. Wallace reviews the empirical patterns and then concludes:

LAW 1. 'the following law may be deduced from these [preceding] facts: — Every species has come into existence coincident both in space and time with a pre-existing closely allied species. He would uncover natural selection, as the mechanism behind this law, a few years later, independently of Darwin. There are other laws too.

LAW 2. Most species’ ranges are very small; few are very large. (Pimm et al. 2014) show that ranges size of flowering plants, amphibians, mammals, birds, and the marine gastropod genus Conu are highly skewed. There are species with very large ranges — some >10 million km2, for example. However, for example, over half of all amphibian species have ranges smaller than 4,300 km2. The comparable medians for the other taxa range from ~115,602 km2 (mammals) to ~729,770 km2 (plants).

LAW 3. Species with small ranges are locally scarce. There is a well-established relationship across many geographical scales and groups of species that link a species’ range to its local abundance. The largest-scale study is that of (Manne & Pimm 2001) who used data on bird species across South America. A species is “common” if one is nearly guaranteed to see it in a day’s fieldwork, then “fairly common,” “uncommon” down to “rare” — meaning it likely takes several days of fieldwork to find one even in the appropriate habitat. Almost all bird species with ranges greater than 10 million km2 are “common,” while nearly a third of species with ranges of less than 10,000 km2 are “rare” and very few are “common.”

LAW 5. Species with small ranges are geographically concentrated and … LAW 6 … those concentrations are generally not where the greatest numbers of species are fond. The simplest expectation is that where there are more species, there will be more large-ranged, more small-ranged species — and more threatened species. Reality is strikingly different.

Figure 1 shows the patterns for all species, small-ranged species, and threatened species for mammals on land and in the oceans. (By small-ranged, we mean less than the median range size for the taxon in question.) Small ranged species are geographically concentrated, and do not merely mirror the patterns for all species (of which, the constitute exactly half.) Moreover, the concentrations of small-ranged species are, generally, not where the greatest numbers of species are. Finally, the patterns of threatened species very closely resemble those of small-ranged species. Similar terrestrial patterns are found in birds and mammals and at much coarser spatial resolution, they mirror the patterns for plants (Jenkins et al. 2013). 

Several interesting consequences emerge. Most of the species at greatest risk of extinction are concentrated geographically and, broadly, such species in different taxa are concentrated into the same places — the hotspots. This is of huge practical significance for it means that conservation efforts can be concentrated in these special places. Moreover, priorities set for one taxonomic group may be sensible for some others, at least at this geographical scale. These ideas were first developed by Norman Myers (Myers 1988) and expanded with others (Myers et al. 2000) .

Other things being equal extinctions will concentrate where there are many species with small ranges. Other things are not equal of course and the other important driver is human impact. Myers added the second — and vital criterion — that these regions have less than 30% of their natural vegetation remaining. Myers’ idea is a very powerful one. It creates the “number of small ranged species times habitat loss equals extinction” idea with another key and surprising insight. What surprises is that there are few examples of concentrations of small-ranged species that do not also meet the criterion of having lost 70% of more of their natural habitat. The island of New Guinea is an exception, though habitat losses there are quickly depriving it of that distinction. Hotspots have disproportionate human impact measured in other ways besides their habitat loss. (Cincotta et al. 2000) show that hotspots have generally higher than human population densities and that almost all of them have annual population growth rates that are higher (average = 1.6% per annum) than the global average (1.3% per annum).

We considered each of the 25 hotspots using the statistics on endemic bird species, original area, and the present area of remaining natural vegetation (Pimm & Raven 2000). This provides a best-case scenario of what habitat might remain. We predicted that ~1700 species of birds should be lost eventually just from the loss of habitat to date — a number similar the number currently threatened species.

Species can obviously linger in small habitat fragments for decades before they expire (Brooks et al. 1999; Ferraz et al. 2003; Pimm & Brooks 2013). Based on these rates of species loss, perhaps three quarters of these species — 1250 — will likely go extinct this century. If so, (Pimm & Raven 2000) estimated future extinction rates of ~1000 E/MSY from human actions to date — about ten times larger than the ones we currently observe. Put another way, extinction rates should accelerate

Two extrapolations are possible. The worst-case scenario for the hotspots assumes that the only habitats that will remain intact will be the areas currently protected. This increases the prediction of number of extinctions to 2200 (Pimm & Raven 2000) The second adds in species from areas not already extensively deforested. These changes would cause even further acceleration in the rates of extinction.

Unexpected causes of extinction

There are various unexpected causes of extinction and they will add to the totals suggested from habitat destruction. The accidental introduction of the brown tree snake (Boiga irregularis) to Guam eliminated the island's birds in a couple of decades (Savidge 1987). In the oceans, increases in long-line fisheries are a relatively new and very serious threat to three-quarters of the 21 albatross species and other seabirds.

Global change and extinction

Finally, one of the most significant factors in the extinction of species will undoubtedly be climate change, a factor not included in any of the estimates presented above. (Thomas et al. 2004) estimate that climate change threatens 15-37% of species within the next 50 years depending on which climate scenario unfolds. Even more species are at risk if one looks to climate changes beyond 50 years. More detailed, regional modelling exercises in Australia (Williams et al. 2007) and South Africa (Erasmus et al. 2002) have led to predictions of the extinction of many species with narrowly-restricted ranges during this or longer intervals.

The critical question is whether these extinctions, which are predominantly of small-ranged species, are the same as those predicted from habitat destruction or whether they are additional. In many cases, they are certainly the latter (Pimm 2008). 


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