How many species are there on Earth and in the... Short title: On the number of species on Earth and... Department of Biology, Dalhousie University, Halifax, NS, Canada

How many species are there on Earth and in the... Short title: On the number of species on Earth and... Department of Biology, Dalhousie University, Halifax, NS, Canada

How many species are there on Earth and in the Ocean?
Short title: On the number of species on Earth and in the ocean
Camilo Mora*, Derek P. Tittensor, Sina Adl, Alastair G.B. Simpson, Boris Worm
Department of Biology, Dalhousie University, Halifax, NS, Canada
*E-mail: [email protected]
ABSTRACT
The diversity of life is one of the most striking aspects of our planet; hence knowing how many
species inhabit Earth is among the most fundamental questions in science. Yet the answer to this
question remains enigmatic because the limited sampling of the world’s biodiversity has precluded
direct quantification, and because indirect estimations rely on assumptions that have proven highly
controversial. Here we quantify the total number of species on Earth using a new described pattern.
We show that the higher taxonomy of species (i.e. assignment of species to kingdom, class, order,
family and genus) follows a consistent pattern from which the total number of species in any
taxonomic group can be extrapolated. The approach was validated with well-known taxa and when
applied to all domains of life it predicts ~8.9 million eukaryotic species globally of which ~2.2
million are marine. In spite of 250 years of taxonomic classification and over 1.2 million species
already cataloged in a central database, our results suggest that some 86% of the species on Earth,
and 91% in the ocean, still await description. With current rates of extinction now reaching 100 to
1000 times natural background rates, our slow advance in the description of species suggest that
many species are likely to become extinct without us ever knowing they existed. Renewed interest
in further exploration and taxonomy is critically required if this significant gap in our knowledge of
life on Earth is to be breached. INTRODUCTION
Robert May [1] recently noted that if aliens visited our planet, one of their first questions would be
"How many distinct life forms-species does your planet have?". He also pointed out that we would
be embarrassed by our answer. This simple narrative illustrates the fundamental nature of knowing
how many species there are on Earth, and our limited progress thus far [1-4]. Unfortunately, the
precarious sampling of the world’s biodiversity has prevented a direct quantification of the number
of species on Earth whereas indirect estimations remain doubtful due to the use of controversial
approaches (see detailed review of available estimations, methods and limitations in Table 1).
Globally, our best approximation to the total number of species is based on the opinion of experts,
whose estimates range widely between 3 and 100 million species [1]; these numbers, however, have
been questioned due to their limited empirical basis [5] and subjectivity [5-6] (Table 1). Several
attempts to improve global estimates have employed macroecological patterns and biodiversity
ratios but the assumptions of these methods have been strongly contested [3vs7, 8vs9, 10vs2, 1112vs13, 14, 15vs5, 16vs17] plus their overall predictions are relevant to only subsets of species,
such as insects [9,18-19], deep sea invertebrates [13], large organisms [6-7,10], animals [7], or
fungi [20]. With the exception of a few extensively studied taxa (e.g. birds [21], fishes [22]), we
are still remarkably uncertain as to how many species there are for most taxonomic groups,
highlighting a significant gap in our basic knowledge of life on Earth. Here we present a novel,
statistically robust method to quantifying the global number of species in all domains of life. We
report that the number of higher taxa, which is much more completely known than the number of
species [23], is strongly correlated to taxonomic rank [24] and that such a pattern allows
extrapolating the global number of species for any kingdom of life (Fig. 1-2).
We note that higher taxonomic data has been used previously to quantify species richness
within specific areas by relating the number of species against the number of genera or families at
well sampled locations, and then, use the resulting regression model to estimate the number of
species at other locations for which higher taxon are better known than species richness (reviewed
by Gaston [23]). This method, however, is inherently developed from and for local and not global
species richness (for it to be suitable for the purpose of quantifying global number of species we
would need data on the richness of replicated planets; obviously, not an option as far as we know).
Here we analyze higher taxonomic data in a different manner by assessing patterns on the entire
taxonomic classification of major taxonomic groups. The existence of predictable patterns in the
classification of species (Fig. 3) could potentially allow predicting the total number of species
within taxonomic groups and we are not aware that this method or idea has been evaluated for the
purpose of estimating global species richness.
RESULTS AND DISCUSSION
We compiled the taxonomic classification of ~1.2 million currently valid species from several
publicly accessible sources (see Materials and Methods). Among eukaryote “kingdoms”,
assessment of time-accumulation curves of taxa (i.e. the cumulative number of described species,
genera, orders, classes and phyla over time) indicated that higher taxonomic ranks are much more
completely described than lower levels (Fig. 1a-f). However, this was not the case for prokaryotes
in which new taxa are steadily described at all taxonomic levels (Fig. S1). For eukaryotes, the rate
of discovery of new phyla (or “divisions” in botanical nomenclature) and classes has slowed
substantially in modern times whereas the number of taxa at the genus or species level continues to
increase steadily in all kingdoms (Fig. 1a-f, Fig. S1). This prevents direct extrapolation of the
number of species from species-accumulation curves [21-22] and highlights our current uncertainty
regarding estimates of total species richness (Fig. 2f). However, the increasing completeness of
higher taxonomic ranks could facilitate the estimation of species richness, if the former predict the
latter. We evaluated this hypothesis at the global scale.
First, we accounted for undiscovered higher taxa by fitting asymptotic regression models to
the time-taxa accumulation curves (Fig. 1a-e) and used a formal multimodel averaging framework
based on Akaike’s Information Criterion [22] to predict the asymptotic number of taxa at each
taxonomic level (Fig. 1a-e; see Material and Methods). Secondly, the predicted number of taxa at
each taxonomic rank down to genus was regressed against the numerical rank, and the fitted model
was used to predict the number of species (Fig. 1g, Material and Methods). We applied this
approach to 18 taxonomic groups for which the total numbers of species are relatively well known
and found that the approach yields accurate predictions for these groups (Fig. 2). When applied to
all eukaryote kingdoms, the approach predicted ~7.9 million species of animals, ~300,000 species
of plants, ~650,000 species of fungi, ~36,000 species of protozoa and ~5,800 species of chromists;
in total 8.9 million species of eukaryotes are estimated to exist on Earth (Table 2). Restricting this
approach to marine taxa resulted in a prediction of 2.2 million eukaryote species in the world’s
oceans (Table 2). We applied the approach to prokaryotes as well; unfortunately, the steady pace of
description of taxa at all taxonomic ranks precluded the calculation of asymptotes for higher taxa
(Fig. S1). Thus, we used raw numbers of higher taxa (rather than asymptotic estimates) for
prokaryotes and as such our estimations represent only a lower boundary of the diversity in this
group. Our approach predicted ~10,000 species of prokaryotes of which ~550 are marine. An
additional reason for the low number of prokaryotes is the existence of horizontal gene transfer
between lineages, which leads to broader criteria for the classification of species in prokaryotes than
in eukaryotes [25]. As a result there are relatively few described species of prokaryotes (only
~10,000 species are currently accepted), which are phenotypically broader and phylogenetically
much older than eukaryotes [25].
We observed that the statistical predictability of the number of species from higher taxa
emerges from a consistent pattern in the frequency distribution of subordinate taxa; that is, at any
taxonomic rank, the diversity of subordinate taxa is concentrated within few groups with a long tail
of low-diversity groups (Fig. 3). The accurate fit of a statistical model to this pattern implies that the
number of taxa at any taxonomic rank can be predicted from the number of subordinate taxa and
vice versa. The existence of these consistent patterns throughout the entire taxonomic hierarchy
implies that knowing the number of taxa at just one taxonomic level could yield, with varying
accuracy, the data necessary to reconstruct the number of taxa in the entire taxonomic hierarchy of a
taxon. The mechanism for this pattern is uncertain, but in the case of taxa classified
phylogenetically, it may involve a consistent pattern of diversification likely characterized by
radiations within few clades and slow evolution (little cladogenesis) in most others [26]. In the case
of taxa classified phenetically, the pattern implies the possibility of congruence with phylogenetic
classifications, which has been demonstrated for some groups [25], although it might also reflect
unseen patterns in the way phenotypic data have been used to classify species.
Two long-standing issues in the classification of species that may influence the
interpretation of our results concern the definition of species and the system of classification.
Different taxonomic communities (e.g. the zoological, botanical and bacteria codes of
nomenclature) use different levels of differentiation to define a species; this implies that estimations
on the number of species according to the different codes are not directly comparable. Although we
estimated the number of species for kingdoms traditionally classified under the same rules, our
global predictions for eukaryotes and prokaryotes should be interpreted with that caution in mind.
With respect to the second issue, changes between cladistic (i.e. classification based on
phylogenetic origins) and taximetric (i.e. classification based on phenetics) systems as well as
improvements within systems due to new technologies and data imply that the higher taxonomy will
likely change in structure. When taxa simply change names or move to other clades while
maintaining their taxonomic level, this will not influence our results since our method relies on the
number of taxa and not their linkages. In contrast, increases or decreases in the number of higher
taxa (e.g. by lumping or splitting or discovering new taxa) will affect our estimations. Nonetheless,
a sensitivity analysis indicated that our predictions are surprisingly robust to moderate changes in
higher taxonomy (Fig. S2).
Knowing the total number of species has been a question of great interest motivated in part
by our collective curiosity about the diversity of life on Earth and in part by the need to provide a
reference point for current and future losses of biodiversity. Unfortunately, incomplete sampling of
the world’s biodiversity combined with a lack of robust extrapolation approaches has yielded highly
uncertain and controversial estimates of how many species there are on Earth. Here we have
introduced a new approach whose validation and explicitly statistical nature adds greater robustness
to its predictions. Our estimates suggest that after 250 years of taxonomic classification only ~14%
of the species on Earth are currently catalogued while only ~9% of those in the ocean have been
indexed in a central database (Table 2). Our slow advance in the description of species in
combination with extinction rates now exceeding natural background rates by a factor of 100 to
1000 [27], suggest that species may become extinct without us ever knowing they existed.
Increasing rates of biodiversity loss provide urgent incentives to increase our knowledge of the
Earth’s remaining species. Though remarkable effort and progress have been made, a further
closing of this knowledge gap will require a renewed interest in exploration and taxonomy by both
researchers and funding agencies, and a continuing effort to catalogue existing biodiversity data in
publicly available databases.
MATERIALS AND METHODS
Databases
Calculations of the number of species on Earth were based on the classification of currently valid
species from the Catalog of Life (www.sp2000.org) whereas the estimations for species in the
Ocean were based on The World’s Registry of Marine Species (www.marinespecies.org). The latter
database is largely contained within the former. These databases were screened for errors in the
higher taxonomy including classification of organisms in multiple clades and homonyms. The
Earth’s prokaryotes were analyzed independently using the most recent classification available in
the List of Prokaryotic Names with Standing in Nomenclature database
(http://www.bacterio.cict.fr). Additional information on the year of description of taxa was obtained
from the Global Names Index database (http://www.globalnames.org). We only used data to 2006
to prevent artificial flattening of accumulation curves due to recent discoveries not yet being entered
into databases.
Statistical analysis
To account for higher taxa yet to be discovered, for each taxonomic rank from phylum to genus we
fitted six asymptotic parametric regression models to the time-taxa-accumulation curve and used
multimodel averaging based on Akaike’s Information Criteria (AIC) to predict the asymptotic
number of taxa (see Fig. 1a-e) [22]. Ideally data should be modelled using only the decelerating
part of the accumulation curve [21-22]. However, there was no obvious breakpoint at which
accumulation curves switched from an increasing to a decelerating rate of discovery (Fig. 1a-e). We
therefore fitted the models starting at all possible years. We considered a specific year cutoff if at
least 10 years of data remained available and if at least five of the six asymptotic models converged
to the subset data. The multimodel asymptotic predictions and standard errors from the different
cutoff years were then used to calculate a weighted consensus asymptotic mean and its standard
error, ensuring that the variability within and among predictions were incorporated [29-30].
To estimate the number of species in a taxonomic group, we related the consensus number of
higher taxa against their numerical rank (Fig. 1g) using least squares regression techniques. Since
data are not strictly independent across hierarchically organized taxa, we also used Generalized
Least Squares models assuming autocorrelated regression errors. Models were run with and without
the inverse of the consensus variance as weights to account for variable uncertainty in the
asymptotic number of higher taxa. We fitted exponential, power and hyperexponential functions to
the data and obtained a prediction of the number of species by multimodel averaging based on AIC.
For the validation analysis (Fig. 2), we could not use the hyperexponential function when less than
three taxonomic ranks were available due to limited degrees of freedom.
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Acknowledgments
We thank David Stang, Ward Appeltans, the Catalog of Life, the World Registry of Marine Species,
and many constituent databases for making their species checklists freely available. We are grateful
to Andrew Solow and Catherine Muir for comments on the manuscript. Funding for this project was
provided by the Sloan Foundation through the Census of Marine Life Program, Future of Marine
Animal Populations project.
Table 1. Current methods for estimating global number of species and their limitations
Case study
Macroecological patterns
Body size frequency distributions. By extrapolation from the
frequency of large to small species, May [7] estimated 10 to 50
million species of animals.
Latitudinal gradients in species. By extrapolation from the better
sampled temperate regions to the tropics, Raven [10] estimated 3 to 5
million species of large organisms.
Species-area relationships. By extrapolation from the number of
species in deep-sea samples, Grassle & Maciolek [13] estimated that
the world’s deep seafloor could contain up 10 million species.
Time-accumulation curves. By extrapolation from the discovery
record it was estimated that there are ~19,800 species of marine
fishes [22] and ~11,997 birds [21].
Diversity ratios
Ratios between taxa. By assuming a global ratio of fungi to vascular
plants of 6:1 and considering that there are ~270.000 species of
vascular plants, Hawksworth [20] estimated 1.6 million species of
fungi.
Host-specificity and spatial ratios. Given the 50.000 known species
of tropical trees and assuming i) a 5:1 ratio of host beetles to trees, ii)
that beetles represent 40% of the canopy arthropods and iii) that the
canopy has twice the species of the ground, Erwin [9] estimated 30
million species of arthropods in the tropics.
Known to unknown ratios. Hodkinson & Casson [18] estimated that
62.5% of the bug species in a sampled location were unknown; by
assuming that 7.5-10% of the global diversity of insects is bugs, they
estimated between 1.84 and 2.57 million species of insects globally.
Expert opinions
Analysis of expert estimations. Estimates of ~5 million species of
insects [15] and ~200,000 marine species [14] were arrived at by
compiling opinion-based estimates from taxonomic experts.
Robustness in the estimations is assumed from the consistency of
responses among different experts.
Limitations
May himself [7] suggested that there was no reason to expect a
simple scaling law from large to small species. Further studies
confirmed different modes of evolution among small species [4] and
inconsistent body frequency distributions among taxa [4].
May [2] questioned the assumption that temperate regions were
better sampled than tropical ones; the approach also assumed
consistent diversity gradients across taxa which is not always true
[4].
Lambshead & Boucher [12] questioned this estimation by showing
that high local diversity in the deep sea does not reflect high global
biodiversity given low species turnover.
This approach is not widely applicable because it requires species
accumulation curves to approach asymptotic levels, which is not
common for most taxa [21-22].
Ratio-like approaches have been heavily critiqued because, given
known patterns of species turnover, locally estimated ratios between
taxa may or may not hold consistent at the global scale [3] and
because at least one group of organisms should be well known at the
global scale, which may not always be true [15]. Bouchet [6]
elegantly demonstrated the shortcomings of ratio-based approaches
by showing how in a well-inventoried area the ratio of fishes to total
multicellular organisms would yield ~0.5 million global marine
species whereas the ratio of Brachyura to total multicellular
organisms in the same sample would yield ~1.5 million species.
Erwin [5] labeled this approach as "non-scientific” due to a lack of
verification. Estimates can vary widely, even those of a single expert
[5,6]. Bouchet [6] argues that expert estimations are often passed on
from one expert to another and therefore a "robust" estimation could
be the same guess copied again and again.
Table 2. Currently cataloged and predicted total number of species on Earth and in the ocean.
Predictions for prokaryotes represent a lower bound because they do not consider undescribed
higher taxa. For protozoa, the ocean database was substantially more complete than the database for
the entire Earth so we only used the former to estimate the total number of species in this taxon. In
some instances our predictions were smaller than the number of catalogued species. This can be due
to the individual or combined effects of the imprecision in the estimations of our approach [note
Standard Errors (SE) around predicted values] and the overestimation in the number of currently
catalogued species due to synonyms, which may be substantial in certain taxa [3,15].
Figure legends
Figure 1. Predicting the global number of species in Animalia from their higher taxonomy.
First, we accounted for undiscovered higher taxa by fitting six asymptotic regression models to the
cumulative number of taxa described over time (solid black lines) at all taxonomic ranks (a-f).
Ideally asymptotic regression models should be fitted only to the decelerating part of such
accumulation curves [21-22]. However, because there was no obvious breakpoint at which
accumulation curves switched from an increasing to a decelerating rate of discovery, we fitted the
models starting at all possible years. We considered a specific year cutoff if at least 10 years of data
remained available and if at least five of the six asymptotic models converged to the subset data.
The graded colors indicate the density of the multimodel fits to all starting years selected. The
predictions from each of the cut-off years were used to calculate a weighted consensus asymptotic
mean (horizontal dashed lines) and its standard error (horizontal grey area), ensuring that the
variability within and among the multimodel average predictions were incorporated. g, Relationship
between the consensus asymptotic number of higher taxa and the numerical hierarchy of each
taxonomic rank. Black circles represent the consensus means, green circles the cataloged number of
taxa, and the box at the species level indicate the 95% prediction interval around the predicted
number of species. The predicted number of species was calculated from weighted averaging of the
predictions of multiple models fitted to the consensus means of higher taxa. The consensus 95%
confidence intervals from all models are presented in red (see Material and Methods).
Figure 2. Validating estimations on the number of species. We compared the number of species
estimated from the higher-taxon approach implement here to the known number of species in
relatively well-studied taxonomic groups as derived from published sources [28]. We also used
estimations from multimodel averaging from species accumulation curves for taxa with nearcomplete inventories. In total, we obtained data for 18 taxonomic groups for which estimates were
available and for which our approach yielded an estimate. Vertical lines indicate the range of
variation in the number of species from different sources. The dotted line indicates the 1:1 ratio.
Figure 3. Frequency distribution of the number of subordinate taxa at different taxonomic
levels. For display purposes we present only the data for Animalia; lines and test statistics are from
a regression model fitted with a power function.
Figure 1
Figure 2
Figure 3
Fig. S1. Completeness of the higher taxonomy of kingdoms of life on Earth. Columns 1 to 6 indicate the temporal
accumulation of the number of taxa at each taxonomic rank (blue lines). The horizontal red lines indicate the consensus
mean on the number of taxa (see Methods). The plots on the far right show the relationship between the number of taxa
and the numerical rank (y-axis is in double log10). Vertical red areas indicate the 95% prediction interval on the number
of species. Blue symbols indicate the currently cataloged number of taxa and red symbols the consensus mean. Where
only blue symbols are shown the catalogued and consensus means overlapped. Note that predictions of the number of
species are based on weighted averages of multiple models (see Methods).
Cont. Fig. S1. Completeness of the higher taxonomy of kingdoms of life in the ocean.
Fig. S2. Sensitivity analysis. One potential caveat in our approach is the degree to which estimations of the number of
species may change if higher taxonomy changes. To test this effect we performed a sensitivity analysis in which the
number of species was calculated after altering the number of higher taxa. We used Animalia as a test case. For each
possible combination of taxonomic levels, we chose a random proportion of taxa from 10 to 100% of the current
number of taxa and recalculated the number of species using the method described in this paper. The approach was
repeated 1000 times and the average and 95% confidence limits of the simulations are shown as points and dark areas,
respectively. Light gray lines and boxes indicate the currently estimated number of species and its 95% prediction
interval, respectively. Our current estimation of the number of species appear remarkably robust to changes in higher
taxonomy. As noted, results were only sensitive to changes in the number of phyla, and only when this number changed
by over 50% relative to the number of currently described phyla. For all other taxonomic levels, expected changes led to
predictions that remain within the confidence intervals of the currently estimated number of species.