ArticlePDF AvailableLiterature Review

Abstract and Figures

Recent studies clarify where the most vulnerable species live, where and how humanity changes the planet, and how this drives extinctions. We assess key statistics about species, their distribution, and their status. Most are undescribed. Those we know best have large geographical ranges and are often common within them. Most known species have small ranges. The numbers of small-ranged species are increasing quickly, even in well-known taxa. They are geographically concentrated and are disproportionately likely to be threatened or already extinct. Current rates of extinction are about 1000 times the likely background rate of extinction. Future rates depend on many factors and are poised to increase. Although there has been rapid progress in developing protected areas, such efforts are not ecologically representative, nor do they optimally protect biodiversity.
Content may be subject to copyright.
30 MAY 2014 • VOL 344 ISSUE 6187 987SCIENCE
BACKGROUND: A principal function of
the Intergovernmental Science-Policy
Platform on Biodiversity and Ecosystem
Services (IPBES) is to “perform regular
and timely assessments of knowledge on
biodiversity.” In December 2013, its second
plenary session approved a program to be-
gin a global assessment in 2015. The Con-
vention on Biological Diversity (CBD) and
five other biodiversity-related conventions
have adopted IPBES as their science-policy
interface, so these assessments will be im-
portant in evaluating progress towards the
CBD’s Aichi Targets of the Strategic Plan
for Biodiversity 2011–2020. As a contribu-
tion toward such assessment, we review
the biodiversity of eukaryote spe-
cies and their extinction rates,
distributions, and protection. We
document what we know, how
it likely differs from what we do
not, and how these differences
affect biodiversity statistics. In-
terestingly, several targets explic-
itly mention “known species”—a
strong, if implicit, statement of
incomplete knowledge. We start
by asking how many species are
known and how many remain
undescribed. We then consider by
how much human actions inflate
extinction rates. Much depends
on where species are, because
different biomes contain differ-
ent numbers of species of differ-
ent susceptibilities. Biomes also
suffer different levels of damage
and have unequal levels of pro-
tection. How extinction rates
will change depends on how and
where threats expand and whether greater
protection counters them.
ADVANCES: Recent studies have clarified
where the most vulnerable species live, where
and how humanity changes the planet, and
how this drives extinctions. These data are
increasingly accessible, bringing greater
transparency to science and governance.
Taxonomic catalogs of plants, terrestrial ver-
tebrates, freshwater fish, and some marine
taxa are sufficient to assess their status and
the limitations of our knowledge. Most spe-
cies are undescribed, however. The species
we know best have large geographical ranges
and are often common within them. Most
known species have small ranges, however,
and such species are typically newer discov-
eries. The numbers of known species with
very small ranges are increasing quickly, even
in well-known taxa. They are geographically
concentrated and are disproportionately
likely to be threatened or already extinct.
We expect unknown species to share these
characteristics. Current rates of extinction
are about 1000 times the background rate
of extinction. These are
higher than previously
estimated and likely
still underestimated.
Future rates will de-
pend on many factors
and are poised to in-
crease. Finally, although there has been rapid
progress in developing protected areas, such
efforts are not ecologically representative,
nor do they optimally protect biodiversity.
OUTLOOK: Progress on assessing biodiver-
sity will emerge from continued expansion
of the many recently created online data-
bases, combining them with new global data
sources on changing land and ocean use and
with increasingly crowdsourced data on spe-
cies’ distributions. Examples of practical con-
servation that follow from using combined
data in Colombia and Brazil can be found at and
The biodiversity of species and their
rates of extinction, distribution,
and protection
S. L. Pimm,* C. N. Jenkins, R. Abell, T. M. Brooks, J. L. Gittleman, L. N. Joppa,
P. H. Raven, C. M. Roberts, J. O. Sexton
The list of author affiliations is available in the full
article online.
*Corresponding author. E-mail: stuartpimm@
Cite this article as S. L. Pimm et al., Science
344, 1246752 (2014). DOI: 10.1126/
Read the full article
at http://dx.doi
Different visualizations of species biodiversity. (A) The distributions of 9927 bird species. (B) The
4964 species with smaller than the median geographical range size. (C) The 1308 species assessed as
threatened with a high risk of extinction by BirdLife International for the Red List of Threatened Species
of the International Union for Conservation of Nature. (D) The 1080 threatened species with less than the
median range size. (D) provides a strong geographical focus on where local conservation actions can have
the greatest global impact. Additional biodiversity maps are available at
Published by AAAS
The biodiversity of species and their
rates of extinction, distribution,
and protection
S. L. Pimm,
*C. N. Jenkins,
R. Abell,
T. M. Brooks,
J. L. Gittleman,
L. N. Joppa,
P. H. Raven,
C. M. Roberts,
J. O. Sexton
Recent studies clarify where the most vulnerable species live, where and how humanity
changes the planet, and how this drives extinctions. We assess key statistics about
species, their distribution, and their status. Most are undescribed. Those we know best
have large geographical ranges and are often common within them. Most known species
have small ranges. The numbers of small-ranged species are increasing quickly, even in
well-known taxa. They are geographically concentrated and are disproportionately likely
to be threatened or already extinct. Current rates of extinction are about 1000 times
the likely background rate of extinction. Future rates depend on many factors and are
poised to increase. Although there has been rapid progress in developing protected
areas, such efforts are not ecologically representative, nor do they optimally protect
One of the four functions of the Intergov-
ernmental Science-Policy Platform on Bio-
diversity and Ecosystem Services (IPBES)
is to perform regular and timely assess-
ments of knowledge on biodiversity(1).
In December 2013, its second plenary session ap-
proved starting global and regional assessments
in 2015 (1).TheConventiononBiologicalDiversity
(CBD) and five other biodiversity-related conven-
interface, so these assessments will be important
in evaluating progress toward the CBDsAichi
Targets of the Strategic Plan for Biodiversity 2011
2020 (2). They will necessarily follow the defi-
nitions of biodiversity by the CBD introduced by
Norse et al.(3) as spanning genetic, species, and
ecosystem levels of ecological organization. As a
contribution, we review the biodiversity of eu-
karyote species and their extinction rates, dis-
tributions, and protection.
Interestingly, several targets explicitly mention
known species”—a strong, if implicit statement
of incomplete knowledge. So how many eukary-
otespeciesarethere(4)? For land plants, there
are 298,900 accepted speciesnames, 477,601 syn-
onyms, and 263,925 names unresolved (5). Be-
cause the accepted names among those resolved
is 38%, it seems reasonable to predict that the
same proportion of unresolved names will even-
tually be accepted. This yields another ~100,000
species for a total estimate of 400,000 species (5).
Models predict 15% more to be discovered (6), so
the total number of species of land plants should
be >450,000 species, many more than are con-
ventionally assumed to exist.
For animals, recent overviews attest to the ques-
tions difficulty. About 1.9 million species are de-
scribed (7); the great majority are not. Costell o et al.
(8) estimate 5 T3 million species, Mora et al.
(9)8.7T1.3 million, and Chapman (7) 11 million.
Raven and Yeates (10) estimate 5 to 6 million
species of insects alone, whereas Scheffers et al.
(11) think uncertainties in insect and fungi num-
bers make a plausible range impossible. Estimates
for marine species include 2.2 T0.18 million (9), and
Appeltans et al. estimate 0.7 to 1.0 million spe-
cies, with 226,000 described and another 70,000
in collections awaiting description (12).
Concerns about biodiversity arise because
present extinction rates are exceptionally high.
Consequently, we first compare current extinc-
tion rates to those before human actions elevated
centrated, so we next consider the biogeography
of species extinction. Given taxonomic incomplete-
ness, we consider how undescribed species differ
from described species in their geographical range
sizes, distributions, and risks of extinction. To
understand whether species extinction rates will
increase or decrease, we review how and where
threats are expanding and whether greater pro-
tection may counter them. We conclude by re-
viewing prospects for progress in understanding
the key lacunae in current knowledge.
Background Rates of Species Extinction
Given the uncertainties in species numbers and
that only a few percent of species are assessed
for their extinction risk (13), we express extinc-
over timeextinctions per million species-years
(E/MSY) (14)rather than as absolute numbers.
For recent extinctions, we follow cohorts from
the dates of their scientific description (15). This
excludes species, such as the dodo, that went
extinct before description. For example, taxono-
mists described 1230 species of birds after 1900,
and 13 of them are now extinct or possibly ex-
tinct. This cohort accumulated 98,334 species-
yearsmeaning that an average species has been
known for 80 years. The extinction rate is (13/
98,334) × 10
compare such estimates to those in the absence
of human actionsi.e., the background rate of
extinction. Three lines of evidence suggest that
an earlier statement (14)ofabenchmarkrate
of 1 (E/MSY) is too high.
First, the fossil record provides direct evidence
of background rates, but it is coarse in time, space,
and taxonomic level, dealingasitdoesmostlywith
genera (16). Many species are in monotypic genera,
whereas those in polytypic genera often share
the same vulnerabilities to extinction (17), so ex-
tinction rates of species and genera should be
broadly similar. Alroy found Cenozoic mammals
to have 0.165 extinctions of genera per million
genera-years (18). Harnik et al.(19)calculated
the fractions of species going extinct over differ-
ent intervals. Converting these to their corre-
sponding rates yields values for the past few
million years of 0.06 genera extinctions per mil-
lion genera-years for cetaceans, 0.04 for marine
carnivores, and, for a variety of marine inverte-
brates, between the values of 0.001 (brachiopods)
and 0.01 (echinoids).
Second, molecular-based phylogenies cover
many taxa and environments, providing an ap-
pealing alternative to the fossil recordsshort-
comings. A simple model of the observed increase
in the number of species S
in a phylogenetic
clade over time, t,isS
exp[(lmt], where
land mare the speciation and extinction rates.
In practice, land mmay vary in complex ways.
Estimating the average diversification rate, lm,
requires only modest data. Whether one can sep-
arate extinction from speciation rates by using
species numbers over time is controversial (20,21)
and an area of active research that requires care-
fully chosen data to avoid potential biases. With
of lineages [lineages through time (LTT)] should
increase linearly over time, with slope lm,but
with an important qualification. In the limit of
yet had time to become extinct. The LTT curve
Nicholas School of the Environment, Duke University, Box
90328, Durham, NC 27708, USA.
Instituto de Pesquisas
Ecológicas, Rodovia Dom Pedro I, km 47, Caixa Postal 47,
Nazaré Paulista SP, 12960-000, Brazil.
Post Office Box 402
Haverford, PA 19041, USA.
International Union for
Conservation of Nature, IUCN, 28 Rue Mauverney, CH-1196
Gland, Switzerland.
Odum School of Ecology, University of
Georgia, Athens, GA 30602, USA.
Microsoft Research, 21
Station Road, Cambridge, CB1 2FB, UK.
Missouri Botanical
Garden, Post Office Box 299, St. Louis, MO 631660299,
Environment Department, University of York, York,
YO10 5DD, UK.
Global Land Cover Facility, Department of
Geographical Sciences, University of Maryland, College Park,
MD, 20742, USA.
*Corresponding author. E-mail: Authors
after the second are in alphabetical order.
SCIENCE 30 MAY 2014 VOL 344 ISSUE 6187 1246752-1
should be concave, and its slope should approach
l(20,21). This allows separate estimation of
speciation and extinction rates.
Unfortunately, in the many studies McPeek
(22) compiled, 80% of the LLT curves were con-
vex, whence m= 0. If currently recognized sub-
species were to be considered as species, then a
greater fraction of the LTT curves might be con-
cave, making m>0.Thissuggeststhattaxonomic
opinion plays a confounding role and one not
easily resolved, whatever the underlying statisti-
cal models. The critical question is how large an
extinction rate can go undetected by these meth-
ods. Generally, if it were large, then concave curves
would predominate, but that falls short of pro-
viding quantification.
Third, data on net diversification, lm,are
widely available. Plants (23) have median diversi-
fication rates of 0.06 new species per species per
million years, birds 0.15 (24), various chordates
0.2 (22), arthropods 0.17, (22), and mammals 0.07
(22). The rates for individual clades are only ex-
ceptionally >1. Valente et al.(25) specifically
looked for exceptionally high rates, finding them
>1 for the genus Dianthus (carnations, Caryophyl-
laceae), Andean Lupinus (lupins, Fabaceae), Zos-
terops (white-eyes, Zosteropidae), and cichlids in
East African lakes.
There is no evidence for widespread, re-
cent, but prehuman declines in diversity across
most taxa, so extinction rates must be gener-
ally less than diversification rates. This matches
the conclusion from phylogenetic studies that
do not detect high extinction rates relative to
speciation rates, and both lines of evidence are
compatible with the fossil data. This suggests
that 0.1 E/MSY is an order-of-magnitude esti-
mate of the background rate of extinction.
Current Rates of Species Extinction
The International Union for Conservation of Na-
ture (IUCN), in its Red List of Threatened Species,
assesses speciesextinction risk as Least Concern,
Near-Threatened, three progressively escalating
categories of Threatened species (Vulnerable, En-
dangered, and Critically Endangered), and Ex-
tinct (13). By March 2014, IUCN had assessed
71,576 mostly terrestrial and freshwater species:
860 were extinct or extinct in the wild; 21,286
were threatened, with 4286 deemed critically
endangered (13). The percentages of threatened
terrestrial species ran from 13% (birds) to 41%
(amphibians and gymnosperms) (13). For fresh-
water taxa (26), threat levels span 23% (mam-
mals and fishes) to 39% (reptiles).
Efforts are expanding the limited data from
oceans for which only 2% of species are assessed
compared with 3.6% of all known species (27).
Peters et al.(28) assessed the snail genus Conus,
Carpenter et al.(29) corals, and Dulvy et al.(30)
1041 shark and ray species. Overall, some 6041
marine species have sufficient data to assess risk:
16% are threatened and 9% near-threatened, most
by overexploitation, habitat loss, and climate
change (13).
The direct method of estimating extinction
rates tracks changing status over time. Most
changes in IUCN Red List categories result from
improved knowledge, so the calculation of the
Red List Index measures the aggregate extinc-
tion risk of all species in a given group, remov-
ing such nongenuine changes (31). Hoffmann et al.
(32) showed that, on average, 52 of 22,000 spe-
cies of mammals, birds, and amphibians moved
one Red List category closer to extinction each
year. If the probability of change between any
two adjacent Red List categories were identical,
this would yield an extinction rate of 450 E/MSY.
The probability is lower for the transition from
critically endangered to extinct (33), however, per-
haps because the former receive disproportionate
conservation attention.
Extinction rates from cohort analyses av-
erage about 100 E/MSY (Table 1). Local rates
from regions can be much higher: 305 E/MSY
for fish in North American rivers and lakes
(34), 954 E/MSY for the regionsfreshwater
gastropods (35), and likely >1000 E/MSY for
cichlid fishes in AfricasLakeVictoria(36)
Studies of modern extinction rates typically do
not address the rate of generic extinctions, but di-
rect comparisons to fossils are possible. For mam-
mals, the rate is ~100 extinctions of genera per
million genera years (13) and ~60 extinctions
for birds (13,37).
How does incomplete taxonomic knowledge
affect these estimates? Given that many spe-
cies are still undescribed and many species
with small ranges are recent discoveries, these
numbers are surely underestimates. Many spe-
cies will have gone or be going extinct before
description (8,15). Extinction rates of species
described after 1900 are considerably higher than
those described before, reflecting their greater
rarity (Table 1). Moreover, a greater fraction of
recently described species are critically endan-
tions of threatened species thus increase with
improved knowledge. This warns us that esti-
mates of recent extinction rates based on poorly
known taxa (such as insects) may be substantial
underestimates because many rare species are
In sum, present extinction rates of ~100 E/MSY
and the strong suspicion that these rates miss
extinctions even for well-known taxa, and cer-
tainly for poorer known ones, means present
extinction rates are likely a thousand times higher
than the background rate of 0.1 E/MSY.
The Biogeography of Global
Species Extinction
Human actions have eliminated top predators
and other large-bodied species across most con-
tinents (38), and oceans are massively depleted
of predatory fish (39). For example, African savan-
nah ecosystems once covered ~13.5 million km
Only ~1 million km
now have lions, and much
less area has viable populations of them (40).
Recognizing the importance of such regional
extirpations, we concentrate on the irreversible
global species extinctions and now consider
where they will occur.
General patterns—“laws(41)describe spe-
ciesgeographical distributions. First, small geo-
graphical ranges dominate. Gaston (42) suggests
a lognormal distribution, although many taxa
have more small-ranged species than even that
skewed distribution (Fig. 1). In Fig. 1, 25% of most
taxa have ranges <10
and, for amphibians,
These sizes substantially overestimate actual
ranges. Figure 1 assumes that, for plants, the
presence in one of the 369 regions of the World
Checklist of Selected Plant Families (WCSPF)
(43) means the species occurs throughout the en-
tire region. Similar, Fig. 1 assumes that the Conus
species occur throughout the ocean within their
geographical limits. These outer boundaries of the
estimated ranges are too large. Of course, species
are further limited to specific habitats within the
outer boundaries of their ranges (44,45).
A second law is that small-ranged species are
generally locally scarcer than widespread ones
(41). Combined, these two laws have consequences.
First, unsurprisingly, taxonomists generally de-
scribe widespread and locally abundant species
before small-ranged and locally scarce ones (46).
Even for well-known vertebrates, taxonomists de-
scribed over half the species in Brazil with ranges
<20,000 km
after 1975 (47).
Second, since the majority of species are unde-
scribed, one expects that samples from previously
unexplored regions would contain a preponder-
ance of them. Indeed, the fraction of undescribed
species should provide estimates of how many
species there are in total (11,12). In practice, small
Table 1. Extinction rates calculated by cohort analysis and fractions of species that are critically
endangered (CR). Data from (13,37,50,51). Bird species thought to be possibly extinctare counted
as extinctions.
described Species Extinctions Species-years Extinction
rate CR % CR
Before 1900 8922 89 1,812,897 49 123 1.4
1900 to present 1230 13 98,334 132 60 4.9
Before 1900 1437 14 212,348 66 37 2.6
1900 to present 4972 22 206,187 107 483 9.7
Before 1900 2983 36 500,252 72 70 2.3
1900 to present 2523 43 176,858 243 126 5.0
1246752-2 30 MAY 2014 VOL 344 ISSUE 6187 SCIENCE
samples across dispersed locations include
widespread, common species and few rare ones.
For example, in samples across ~6 million km
of Amazonian lowlands, a mere 227 species ac-
counted for half the individual trees, suggest-
ing that the Amazon might be floristically quite
homogeneous. However, the samples contained
4962 known tree species, and many that could
not be identified (48). The Amazon might con-
tain as many as 16,000 species (48). Only accu-
mulating species lists while quantifying sampling
effort can provide compelling estimates of how
diversity varies geographically and thus how
many total species there are.
Uncertainties about where species are may be
more limiting than not knowing how many spe-
cies there are. The IUCN maps 43,000 species
(13). Almost half are amphibians, birds, and mam-
mals. The most commonbut least informative
map for conservationis of species richness.
Widely distributed species dominate these maps,
whereas the majority of species with small ranges
are almost invisible (fig. S1). An essential accom-
paniment maps out small-ranged species, such
as the richness of species with less than the
median range size (49) or, for coarsely defined
regions, those endemic to each region. Figures 2
to 5 provide examples for mammals and am-
phibians (13,50,51), flowering plants (43),
freshwater fish (52), and marine snails of the
genus Conus (28). Supplementary materials
provide details (53). There are similar maps
for 845 reef-building coral species (29), coastal
fis h, various marine predators, and invertebrates
expect the most species of all range sizeslarge
and small alike. Surprisingly, species with small
ranges are geographically concentrated. The high-
est numbers of bird species live in the lowland
Amazon, whereas small-ranged species concen-
trate in the Andes (fig. S1). Although mapped
at a much coarser scale, freshwater fish also
often attain their highest diversities in large
rivers flowing through forests. A striking ex-
ception is the high numbers in East African rift
lakes (Fig. 4). The Philippines have the greatest
number of Conus species; the concentrations of
small-ranged species are elsewhere (Fig. 5). Other
marine taxa are similar (55).
Many past extinctions have been on islands,
but current patterns of threat are geographically
much broader (49,56). Rare specieseither
widespread but scarce (such as top predators
and other large-bodied animals) or with small
geographical ranges and so often locally scarce
(41)dominate the lists. Species with small ranges
ened than those with larger ones (49,57). Inter-
estingly, for a given range size, a smaller fraction
of island species are threatened than for those on
continents, likely because island species are lo-
Concentrations of threatened species more
closely match concentrations of small-ranged spe-
cies than they do total species numbers and so
are more informative about where currently
threatened species live and where species may
become threatened in the future (49,50)(Fig.2
and fig. S1).
Myers et al.(58) made the vital and separate
point that habitat destruction is greatest where
the highest concentrations of small-ranged spe-
cies live. As it were, small-ranged species are born
vulnerable and then have the greater threats
thrust upon them. Myers et al.s hotspot definition
combines a minimum number of small-ranged
plant species and sufficiently high habitat loss.
log 10 (area) km2log 10 (area) km2log 10 (area) km2
log 10 (area) km2log 10 (area) km2
Proportion of species Proportion of species Proportion of species
Terrestrial birds
Terrestrial mammals
Flowering plants
Log means Log means Log means
Log meansLog means
Fig. 1. The sizes of geographical ranges. (Ato E)
In red, the cumulative proportions of species against
log range size in km
for selected groups of species.
In black, the lognormal distributions with the same
corresponding log means and variances. Numbers
are the log means. See details in (53). The photo-
graphs are from S.L.P., except the plantan unde-
scribed species of Corybas orchid (Stephanie Pimm
Lyon) and a newly discovered frog, Andinobates cas-
sidyhornae (Luiz Maziergos). All reproduced with
SCIENCE 30 MAY 2014 VOL 344 ISSUE 6187 1246752-3
Quantitative data from the WCSPF (43)have
clarified these areas (59).
Future Rates of Species Extinction
The overarching driver of species extinction is
human population growth and increasing per
capita consumption. How long these trends
continuewhere and at what ratewill domi-
nate the scenarios of species extinction and chal-
Before the last decade, most applications de-
veloped extinction scenarios from simple assump-
tions of land use change as a primary driver of
biodiversity loss, employing the species-area rela-
tionship (14). For example, Pimm and Raven (60)
projected 18% extinction by 2100 due to defores-
tation to date in tropical forest hotspots and 40%
extinction if these regions retained natural habitat
only in currently protected areas.
Until recently, these scenarios were the only
empirically validated models. The validations
focused on vertebrates, globally (61) or region-
ally: eastern United States (62), South American
Atlantic Forest (63), and insular Southeast Asia
(64). There was excellent correspondence be-
tween the numbers of species predicted to go
extinct and those that did (62) or, for more
recent deforestation, with those threatened
(61,63,64). There are discussions about the un-
derlying theory of such estimates (65). Nonetheless,
when one counts all the extinctions likely to follow
deforestation (66), these estimates are conservative.
Theory predicts that many more extinctions are
possible with severe habitat fragmentation (67),
as observations confirm (68).
Pereira et al.s review of projected future ex-
tinctions (69)classifiedandcomparedvarious
models. Strikingly, the six sets of projections pre-
dicted a hundred-fold range of extinction rates.
This emerged from the different drivers consid-
ered (land use change, climate change, or both),
model approaches, taxonomic coverage, and geo-
graphic scale. Given this range, there is an urgent
need for validation of projections against docu-
mented extinctions to date. Few studies attempt
this. Here, we consider the prospects for such
validation with newly available data that can
reduce the uncertainties.
Climate disruption will cause species extinctions,
but the range of estimates is large. Thomas et al.
(70) estimated that 15 to 37% of various taxa would
be committed to extinction by 2050 for a mid-
range warming scenario. Specific studies for
birds estimated that >400 species of land birds
out of 8750 studied (4.6%) would experience a
range reduction greater than 50% by year 2050
(71). For Western Hemisphere land birds, inter-
mediate extinction estimates based on projected
climate-induced changes in current distributions
ranged from 1.3% (1.1°C warming) to 30% (6.4°C
warming) of the 3349 species studied (72). A
global assessment of expected warming-induced
range contractions estimated that 184 to 327
montane bird species (out of 1009) would lose
>50% of their range and result in range sizes of
<20,000 km
Cheung et al.(74) used a global climate model
to predict range shifts, extinction, and invasion
intensities based on ocean warming up to 2050
for 1066 species of exploited marine fish and
invertebrates. They predicted that poleward range
movements would lead to speciesextinctions
from tropical and subpolar latitudes of 4 and
7% respectively, with mostly range readjustments
in between. They attribute the lower extinction
probabilities than on land (70) to greater free-
dom of movement in the sea. Enclosed seas, like
the Mediterranean, could trap clusters of en-
demic species against insurmountable barriers
(75). Nor did they consider any other potential
extinction drivers, such as ocean acidification
(76), overfishing (30), or the inability of sessile
speciessuch as brooding coralsto move.
On land, the effects of climate disruption re-
main unclear for several reasons. A key uncer-
tainty is whether climate disruption and habitat
destruction harm overlapping sets of species or
broadly different onesand they may act syn-
ergistically. Climate disruption seems to be an
added threat (77). Some studies explicitly com-
bine species-area projections of species loss to
incorporate climate change as a driver, via mod-
els of changing global vegetation (78), and sug-
gest that 12% of species will become extinct.
Other studies estimate that 7 to 24% of plant
species (79) will become extinct. The impacts
Fig. 2. Fine-scale patterns of terrestrial vertebrate diversity. (A) The numbers of threatened mammal species and (B) those with ranges smaller than
the median range size. (C) and (D) show the corresponding maps for amphibians. See details in (53).
1246752-4 30 MAY 2014 VOL 344 ISSUE 6187 SCIENCE
of climate disruption are complex. A meta-
analysis compared 188 predicted with 130
observed climate change responses and sug-
gested that 10 to 14% of species would become
extinct (80). Moreover, the interactions of en-
vironmental drivers with intrinsic biological
traits (e.g., geographic range, body size, and
reproductive rate) indicate that speciesre-
sponses to increased human population den-
sity will become increasingly uncertain (81).
Another uncertainty is that none of Pereira et al.s
(69) models assessed population viability and
habitat suitability. Rather, they take indirect ap-
proaches, such as some fraction of their present
range, as in (70). Approaches incorporating viabil-
ity provide strong empirical foundations for esti-
mating extinction risk (82). Some regional studies
have employed them, however, including a study
of South African Proteaceae (83).
Above all, there are few empirical tests. The
above methods assume species moving pole-
ward, to higher elevations, or to deeper depths
to remain in their climate envelopes. Using for-
tuitous repeats of surveys done decades ago,
diverse studies find substantial lags in upslope
movements for plants (84), insects (85), and
birds (86). These question the fate of species now
living outside past climate envelopes. Further-
more, the few studies that consider predictions
of changing geographical ranges from the past
to the present and then calibrate them against
present ranges do not always find compelling
matches (87).
For freshwater species, direct and indirect
habitat modification, including pollution (88)
and the already extensive and continuing frag-
mentation and flow regulation of rivers (89), are
clearly major drivers of extinction, especially for
species with limited dispersal abilities. Existing
alterations to freshwater systems may already
have compromised speciesviability to the ex-
tent that no level of future protection might
prevent extinction (90).
Introduced species, including diseases, are a
major cause of extinctions and the main cause
of recent bird extinctions (37). Some 10% of plant
species are endemic to islands small enough for
introduced herbivores to be a major threat (59).
We know of no estimates of extinction rates from
introduced species. Such extinctions can unfold
quickly and unpredictably, as the destruction
of Guams endemic avifauna by an introduced
snake (91) and the destruction and possible
extinction, primarily by the Nile perch, of as many
as 200 Lake Victoria haplochromine cichlids
demonstrate (36).
In sum, there are few empirically tested pre-
dictions of future extinctions. Typical scenarios
consider what can be predictedextinctions from
deforestation or climate disruptionbut not po-
tentially important processesdisease, introduced
species, or hydrological changesthat one cannot
easily model.
How Will Protection Slow
Extinction Rates?
Among the many uncertainties in projecting
future extinction rates, a particularly important
one is the effect that conservation actions might
have in reducing them (92). For instance, the
rate at which mammals, birds, and amphibians
have slid toward extinction over the past four
decades would have been 20% higher were it
not for conservation efforts (32).
The destruction of natural habitats is the major
threat to species (13). Thus, protected areas, while
diverse and differing substantially in their pur-
poses and levels of protection (93), are essential
to reducing extinctions. Aichi Target 11 seeks
the protection of >17% ecologically representa-
tiveterrestrial and freshwater ecosystems and
>10% of coastal and marine ecosystems (2),
whereas CBDs Global Strategy for Plant Con-
servation (GSPC) Target 4 seeks >15% of each
ecological region or vegetation type(94).
In 2009, 12.9% of the total land area was un-
der some legal protection, up from <4% in 1985
where there is little human pressure (96). Cover-
age varies between 4% and 25% protection of
14 major terrestrial biomes (96). Of the worlds
821 terrestrial ecoregions, half had <10% of
their area protected (96).
How well these areas capture species within
their boundaries now and in the future is an
essential input to predict future extinction rates
(50,60). Rodrigues et al.(97)analyzedthreat-
ened mammal, bird, amphibian, and turtle
ranges combined with the World Database on
Protected Areas (93). Overall, 27% of threat-
ened amphibians, 20% of threatened birds, 14%
of threatened mammals, and 10% of threatened
turtles live outside protected areas. Subsequent
analyses have set targets for representation scaled
in inverse proportion to range size (98)for ex-
ample, 100% representation for species with
ranges <1000 km
, 10% representation for ranges
>250,000 km
, and a linear interpolation for
species in between. Only ~46% of birds, ~39% of
mammals, and ~19% of amphibians reach or
exceed their targets (98).
These global gap analyses are vulnerable to
commission errorsspecies appearing to occur
when they do notresulting from the overlay of
the coarse-resolution species maps with the
high-resolution protected area boundaries (99).
These can generate a false sense of security:
Fig. 3. Relative numbers of flowering plant species in the different regions used by the World Check-
list of Selected Plant Families (43). (A) All species and (B) endemic species. See details in (53).
SCIENCE 30 MAY 2014 VOL 344 ISSUE 6187 1246752-5
Species thought safely represented may be going
extinct. Alternative approaches that accept
higher omission errors, although less efficient,
are less problematic. Thus, for birds, protected
areas cover only 49% of sites documented to
threatened species (56)andonly51%ofglobally
important sites for birds (100).
Do protected areas work? Certainly, some fail
completely: Even large national parks in West
Africa have lost lions and many of their prey
(40). For freshwater species populations, occur-
rence within reserves is no guarantee of protec-
tion, given external threats like flow modification
and lack of explicit reserve management to
meet freshwater objectives (101). Protected for-
ests generally retain their forest cover (102),
have far fewer anthropogenic fires than unpro-
tected areas (103), and do not attract higher
than expected human population growth to their
perimeters (104). Most studies do not assess
plant and animal populations directly, and re-
maining habitats are often too small, or too
heavily exploited, to retain all of their species
(105). Those that do track species reveal that
protected areas deliver substantial outcomes
for preventing extinctions. Globally, species with
>50% of the sites of particular importance for
them protected are sliding toward extinction only
half as rapidly as those with <50% of their im-
portant sites protected (100).
2013 assessment (106)reported~10,000marine
oceans. Aichi Target 11 admits other effective
area-based conservation measures,so this as-
sessment included large fishery management
zones closed to certain fishing gears, including
some in New England, Florida, and New Zealand.
These were not established for biodiversity con-
servation and, in the New Zealand case, were
proposed by the deep-sea fishing industry, avoid-
ing places important for fishing (106). A more
conservative assessment (107)estimates1.8%
global coverage.
As on land, marine protected area coverage is
uneven. Reserves are often absent where threats
to biodiversity are highest, such as fishing grounds
and oil and gas leases. Beyond the 200 nautical
mile limits of national jurisdiction, 0.17% of open
waters are protected, compared with 8% of con-
tinental shelves (106). Coastal coral reefs are the
best protected, with 18.7% within protected areas
by 2006 (108). Only 2% were in MPAs considered
to be of adequate size, management, level of
protection, and connectivity, however. Moves to
establish large and remote sites as MPAs, such as
the U.K.s British Indian Ocean Territory, have
contributed strongly to recent growth in protec-
tion, suggesting that the Aichi target of 10% cov-
erage may be attainable (109). Marine protected
areas that are no-take, well-enforced, old, large,
proportionately successful in retaining their spe-
cies (110).
Aichi Target 11 seeks protection of 17% of
terrestrial lands (2), whereas the GSPC seeks
to protect 60% of plant species (94). Are both
targets possible simultaneously? The concen-
tration of small-ranged species is such that
were land protected efficiently to capture bio-
diversity, the 17% so selected would encom-
pass part of the ranges of 81% of plant species
and all the ranges of 67% (59). How might the
prediction that 15% more plant species are
currently undescribed change these selections?
Joppa et al.(111) used rates of speciesdescrip-
tion corrected for taxonomic effort and pre-
dicted that undescribed species will be in the
known concentrations of species with small
ranges, leaving current priorities unchanged.
These plant priorities match those for terres-
trial vertebrates. Some 89% of bird species, 80%
of amphibians, and 74% of mammals live within
these plant priority areas (59). Percentages for
88%, 82%, and 73%, respectively (59). With up-
dated data, these results capture Myers et al.s
(58) observation that conserving a large fraction
of species is possible in limited areas if author-
ities choose protected areas cognizant of what
species they contain (112). Areas of high fresh-
water fish diversity match some areas of high
terrestrial diversity, but such congruence cannot
be assumed: Exceptions include the high-diversity
freshwater systems of the Ganges and Mekong
deltas (113) (Fig. 4.) Moreover, protecting fresh-
water species will require managing landscapes
and water use beyond reservesfence lines and
well into larger catchments (101).
What We Know, What We Do Not,
and How to Fix the Gaps
We know enough to see that our ignorance about
speciesnumbers, distributions, and status strong-
ly affects key biodiversity statistics. Two examples
illustrate the consequences. First, ~20% of known
plants are thought threatened (114). Adding the
predicted 15% of undescribed speciesalmost all
will be rare and in places with extensive habitat
loss (36)suggeststhat30%ofplantspeciesare
threatened (6). Climate disruption threatens ad-
ditional species.
Second, only 6.5% of the 632 Conus species are
threatened. Another 14% are Data Deficient”—
there is insufficient information to assess their
status, typically because they are rare and have
small geographical ranges (28). Were better
of where threatened species occur would change
substantially (Fig. 5). Investment in extending
Fig. 4. Relative numbers of freshwater fish species in the different freshwater ecoregions (52).
(A) All species and (B) endemic species. See details in (53).
1246752-6 30 MAY 2014 VOL 344 ISSUE 6187 SCIENCE
the coverage of the IUCN Red List to its target of
160,000 species assessments is a priority (115).
What is the progress toward getting better
knowledge, and what are the prospects for con-
tinued improvements? Aichi Target 19 calls for
data to be widely shared.Recent online efforts
toward this goal include the Global Biodiversity
Information Facility (GBIF) (116), with 420 mil-
lion records and 1.45 million speciesand sub-
speciesnames, and the Ocean Biogeographic
Information System (117), with 38 million records
of 115,000 species. Species 2000 seeks to create
a validated checklist of all species, and the Tree
of Life (118) and TimeTree (119) provide phylo-
genetic relationships.
Communities of taxonomists now address the
tedious but vital issue of synonymy and placing
their lists and taxonomic decisions into the public
domain. Large databases include the World Re-
gister of Marine Species (120), which has checked
95% of 221,000 marine species, and FishBase,
with 32,700 species of fish (121). WCSPF (43)has
currently assessed ~110,000 plant species (5).
New technologies help. Genetic barcoding
(122) offers the potential to identify animal spe-
but unique, DNA sequence. Barcoding for plants
is slightly more difficult. For the great majority
of unknown species in animal taxa with few
taxonomic specialists, this will surely become
the predominant method of discovering new
species. It raises the controversial idea that many
species may become known by a number derived
from barcoding and notor not onlyfrom con-
ventional descriptions (123). The potential to
find new species and untangle clusters of cryp-
tic species (124) is also being realized. Less ap-
preciated is that cost-effective barcoding by
batches of species is now possible. Powerful new
statistical methods (125)estimatehowmanyspe-
cies may be present in an area and how these
overlap with other samples from increasing
sampling efforts. Combined with batch barcod-
what fractions of undescribed species are present
in poorly sampled areasthemostdirectwayof
estimating how many species there are.
Even for species that are mapped, substan-
tial uncertainties remain. The highest apparent
numbers of vertebrate species in South America
(fig. S1) are close to research centers, as are many
GBIF records. The most important consequence
of having a public speciesrange map is that it
challenges observers to confirm or amend it.
Although GBIF (116)istherepositoryfor
information into which other sources feed, the
diversity of those sources merits comment.
They include professional organizations, such
as Tropicos (126), with 4.2 million specimens.
The fastest growth in understanding species
distributions comes from large numbers of ama-
teurs. Birdwatchers are most numerous: eBird
(127) became an international depository in 2010
and already has >100,000 observers and >100 mil-
lion observations. It permits fine-scale mapping
and month-by-month changes in distribution.
Such wealth of data skews broad biodiversity as-
sessments (128), motivating efforts for less pop-
ular taxa.
To be useful, observations require identifica-
tions, and identifying organisms requires train-
ing and skill. Recent advances in photo-sharing
technology and social networking provide new
opportunities. Apps like iNaturalist (129)allow
division of labor between amateur observers up-
loading mystery field observations from smart-
phones and skilled identifiers who later catalog
these observations from the photos provided.
Cooperation between amateurs and experts
now produces high volumes of quality data for
diverse taxa. iNaturalist has already logged over
half a million records and become the pre-
ferred app for incorporating crowd-sourced
data into national biodiversity surveys in
Me xi co and els ewhere. The Reef Life Survey is
generating similar advances for marine bio-
diversity (130).
Crowd-sourced data, especially when including
data on sampling effort, provide substantial
opportunities to monitor a broad range of species
over time and across broad geographical ar ea s
exactly the requirements needed to assess the
various scenarios for future extinction.
Fig. 5. The distribution of species in the marine snai l genus Conus.(A) The numbers of all species; (B) those with ranges smaller than the median
range size; (C) those threatened; and (D) data-deficient species for which there is insufficient data to assess their status. Figure S2 provides a detail of
the Cape Verde islands, where a large number of small-ranged species live. The terrestrial background is shown in approximately true color to show the
distribution of forests (dark green) and drylands (buff) and oceanic bathymetry (darker colors mean deeper water). See details in (53).
SCIENCE 30 MAY 2014 VOL 344 ISSUE 6187 1246752-7
The numbers and kinds of online databases
have increased dramatically in recent years and
will continue to do so. Global estimates of land
cover from remote sensing [e.g., (131)] diver-
sified with the 2009 opening of the U.S. Geol-
ogical Survey Landsat archive and subsequent
efforts to collect and calibrate global reposito-
ries of Landsat images going back to the early
1970s (132,133).
Even more promising is combining data source s.
Studies now permit detailed assessments of the
current status of species by trimming available
range maps using remotely sensed estimates of
elevation and remaining habitats (134) and con-
necting directly to metapopulation models of frag-
mented ranges (45). Figure 6 provides an example
of the extent to which speciesranges have been
lost and fragmented by deforestationand
when this happened. It also shows where forest
remains outside of protected areas, how it has
been lost from within them, and the potential
of crowd-sourced data to monitor species
Combining such sources anticipates an ability
to assess biodiversity continuously and pro-
vide a template onto which crowd-sourced data
could validate predictions of changing species
distributions. Global biodiversity monitoring
can now move to combining databases of in-
creasing scope and certainty at regular intervals.
These coming advances will increasingly enable
scientists and policy-makers to understand the
status, trends, and threats to Earths
biodiversity and to act accordingly
to protect it.
1. Intergovernmental Platform on Biodiversity
and Ecosystem Services (2014); http://
2. Strategic Plan for Biodiversity 20112020
3. E. A. Norse et al., Conserving Biological
Diversity in our National Forests (Wilderness
Society, Washington, 1986).
4. R. M. May, How many species are there on
Earth? Science 241, 14411449 (1988).
doi: 10.1126/science.241.4872.1441;
pmid: 17790039
5. A. J. Paton, From working list to online flora
of all known plants: Looking forward with
hindsight 1. Ann. Mo. Bot. Gard. 99,
206213 (2013). doi: 10.3417/2011115
6. L. N. Joppa, D. L. Roberts, S. L. Pimm, How
many species of flowering plants are there?
Proc. Biol. Sci. 278, 554559 (2011).
doi: 10.1098/rspb.2010.1004;pmid:20610425
7. A. D. Chapman, Numbers of Living Species
in Australia and the World (Biodiversity
Information Services, Toowoomba,
Australia, 2009).
8. M. J. Costello, R. M. May, N. E. Stork, Can
we name Earths species before they go
extinct? Science 339, 413416 (2013). doi:
10.1126/science.1230318; pmid: 23349283
9. C. Mora, D. P. Tittensor, S. Adl, A. G. B.
Simpson, B. Worm, How many species are
there on Earth and in the ocean? PLOS Biol.
9, e1001127 (2011). doi: 10.1371/journal.
pbio.1001127; pmid: 21886479
10. P. H. Raven, D. K. Yeates, Australian
biodiversity: threats for the present,
opportunities for the future. Aust. J.
Entomol. 46, 177187 (2007). doi: 10.1111/
11. B. R. Scheffers, L. N. Joppa, S. L. Pimm,
W. F. Laurance, What we know and dont
know about Earths missing biodiversity.
Trends Ecol. Evol. 27, 501510 (2012).
doi: 10.1016/j.tree.2012.05.008;
pmid: 22784409
12. W. Appeltans et al., The magnitude of global
marine species diversity. Curr. Biol. 22,
21892202 (2012). doi: 10.1016/j.
cub.2012.09.036; pmid: 23159596
13. International Union for the Conservation of
Nature (2014);
14. S. L. Pimm, G. J. Russell, J. L. Gittleman,
T. M. Brooks, The future of biodiversity.
Science 269, 347350 (1995). doi: 10.1126/
science.269.5222.347; pmid: 17841251
15. S.Pimm,P.Raven,A.Peterson.H.Şekercioğlu,
P. R. Ehrlich, Human impacts on the rates of
recent, present, and future bird extinctions.
Proc. Natl. Acad. Sci. U.S.A. 103,1094110946 (2006).
doi: 10.1073/pnas.0604181103; pmid: 16829570
16. A. D. Barnosky et al., Has the Earths sixth mass extinction
already arrived? Nature 471,5157 (2011). doi: 10.1038/
nature09678; pmid: 21368823
17. G. J. Russell, T. M. Brooks, M. M. McKinney, C. G. Anderson,
Present and future taxonomic selectivity in bird and
mammal extinctions. Conserv. Biol. 12, 13651376 (1998).
doi: 10.1046/j.1523-1739.1998.96332.x
18. J. Alroy, Constant extinction, constrained diversification,
and uncoordinated stasis in North American mammals.
Palaeogeogr. Palaeoclimatol. Palaeoecol. 127, 285311
(1996). doi: 10.1016/S0031-0182(96)00100-9
19. P. G. Harnik et al., Extinctions in ancient and modern seas.
Trends Ecol. Evol. 27, 608617 (2012). doi: 10.1016/
j.tree.2012.07.010; pmid: 22889500
20. S. Nee, E. C. Holmes, R. M. May, P. H. Harvey, Extinction
rates can be estimated from molecular phylogenies.
Philos. Trans. R. Soc. London Ser. B 344,7782 (1994).
doi: 10.1098/rstb.1994.0054; pmid: 8878259
Fig. 6. Combining databases to assess the changing status of biodiversity. Maps (A)and(B)showland
cover change in the Yucatan peninsula of Central America. Forest-cover data for 2000 to 2005 available at Although protected areas increased over time, there was extensive deforesta-
tion in lowland Guatemala from 1990 to 2000 (shown in red), some of it in protected areas. Forest loss slowed from
2000 to 2005. (C) Deforestation has reduced and fragmented the ranges of four exemplar species endemic to the
Yuc a ta n. (D) All iNaturalist records from this area. See details in (53).
1246752-8 30 MAY 2014 VOL 344 ISSUE 6187 SCIENCE
21. D. L. Rabosky, Extinction rates should not be estimated from
molecular phylogenies. Evolution 64, 18161824 (2010).
doi: 10.1111/j.1558-5646.2009.00926.x; pmid: 20030708
22. M. A. McPeek, The ecological dynamics of clade
diversification and community assembly. Am. Nat. 172,
E270E284 (2008). doi: 10.1086/593137; pmid: 18851684
23. M. M. Ferrer, S. V. Good, Self-sterility in flowering plants:
preventing self-fertilization increases family diversification
rates. Ann. Bot. 110, 535553 (2012). doi: 10.1093/aob/
mcs124; pmid: 22684683
24. A. B. Phillimore, T. D. Price, Density-dependent cladogenesis
in birds. PLOS Biol. 6, e71 (2008). doi: 10.1371/journal.
pbio.0060071; pmid: 18366256
25. L. M. Valente, V. Savolainen, P. Vargas, Unparalleled rates
of species diversification in Europe. Proc. Biol. Sci. 277,
14891496 (2010). doi: 10.1098/rspb.2009.2163;
pmid: 20106850
26. B. Collen et al., Global patterns of freshwater species
diversity, threat and endemism. Glob. Ecol. Biogeogr. 23,
4051 (2014). doi: 10.1111/geb.12096
27. Global Marine Species Assessment (2014);
28. H. Peters, B. C. OLeary, J. P. Hawkins, K. E. Carpenter,
C. M. Roberts, Conus: First comprehensive conservation
Red List assessment of a marine gastropod mollusc genus.
PLOS ONE 8, e83353 (2013). doi: 10.1371/
journal.pone.0083353; pmid: 24376693
29. K. E. Carpenter et al., One-third of reef-building corals
face elevated extinction risk from climate change and local
impacts. Science 321, 560563 (2008). doi: 10.1126/
science.1159196; pmid: 18653892
30. N. K. Dulvy et al., Extinction risk and conservation of the
worlds sharks and rays. eLife 3, e00590e00590 (2014).
doi: 10.7554/eLife.00590; pmid: 24448405
31. S. H. M. Butchart et al., Measuring global trends in the status
of biodiversity: Red List indices for birds. PLOS Biol. 2, e383
(2004). doi: 10.1371/journal.pbio.0020383; pmid: 15510230
32. M. Hoffmann et al., The impact of conservation on the status
of the worlds vertebrates. Science 330, 15031509 (2010).
doi: 10.1126/science.1194442; pmid: 20978281
33. M. L. Brooke et al., Rates of movement of threatened bird
species between IUCN Red List categories and toward
extinction. Conserv. Biol. 22, 417427 (2008). doi: 10.1111/
j.1523-1739.2008.00905.x; pmid: 18402584
34. N. M. Burkhead, Extinction rates in North American
freshwater fishes, 1900-2010. Bioscience 62, 798808
(2012). doi: 10.1525/bio.2012.62.9.5
35. P. D. Johnson et al., Conservation status of freshwater
gastropods of Canada and the United States. Fisheries
(Bethesda, Md.) 38, 247282 (2013). doi: 10.1080/
36. F. Witte et al., The destruction of an endemic species flock:
Quantitative data on the decline of the haplochromine
cichlids of Lake Victoria. Environ. Biol. Fishes 34,128
(1992). doi: 10.1007/BF00004782
37. Birdlife International (2014);
38. G. Ceballos, P. R. Ehrlich, Mammal population losses and the
extinction crisis. Science 296, 904907 (2002). doi: 10.1126/
science.1069349; pmid: 11988573
39. R. A. Myers, B. Worm, Rapid worldwide depletion of
predatory fish communities. Nature 423, 280283 (2003).
doi: 10.1038/nature01610; pmid: 12748640
40. J. Riggio et al., The size of savannah Africa: A lions(Panthera
leo)view.Biodivers. Conserv. 22,1735 (2013). doi: 10.1007/
41. S. Pimm, C. Jenkins, Extinctions and the practice of
preventing them. Conservation Biology for All 1, 181199
(2010). doi: 10.1093/acprof:oso/9780199554232.003.0011
42. K. J. Gaston, Species-range-size distributions: patterns,
mechanisms and implications. Trends Ecol. Evol. 11,
197201 (1996). doi: 10.1016/0169-5347(96)10027-6;
pmid: 21237808
43. World Checklist of Selected Plant Families (2014). Facilitated by
the Royal Botanic Gardens, K ew;
44. M. Almeida-Gomes, M. L. Lorini, C. F. D. Rocha, M. V. Vieira,
Underestimation of extinction threat to stream-dwelling
amphibians due to lack of consideration of narrow area of
occupancy. Conserv. Biol. 28, 616619 (2014). doi: 10.1111/
cobi.12196; pmid: 24372858
45. J. K. Schnell, G. M. Harris, S. L. Pimm, G. J. Russell,
Quantitative analysis of forest fragmentation in the Atlantic
Forest reveals more threatened bird species than the current
Red List. PLOS ONE 8, e65357 (2013). doi: 10.1371/journal.
pone.0065357; pmid: 23734248
46. B. Collen, A. Purvis, J. Gittleman, Biological correlates of
description date in carnivores and primates. Glob. Ecol.
Biogeogr. 13, 459467 (2004). doi: 10.1111/
47. S. Pimm, C. Jenkins, L. Joppa, D. Roberts, G. Russell, How
many endangered species remain to be discovered in brazil?
Natureza Conservação 8,7177 (2010). doi: 10.4322/
48. H. ter Steege et al., Hyperdominance in the Amazonian tree
flora. Science 342, 1243092 (2013). doi: 10.1126/
science.1243092; pmid: 24136971
49. L. L. Manne, T. M. Brooks, S. L. Pimm, Relative risk of
extinction of passerine birds on continents and islands.
Nature 399, 258261 (1999). doi: 10.1038/20436
50. J. Schipper et al., The status of the worlds land and marine
mammals: Diversity, threat, and knowledge. Science 322,
225230 (2008). doi: 10.1126/science.1165115; pmid:
51. S. N. Stuart et al., Status and trends of amphibian declines
and extinctions worldwide. Science 306, 17831786 (2004).
doi: 10.1126/science.1103538; pmid: 15486254
52. R. Abell et al., Freshwater ecoregions of the world:
A new map of biogeographic units for freshwater
biodiversity conservation. Bioscience 58, 403414 (2008).
doi: 10.1641/B580507
53. Materials and methods are available as supplementary
materials on Science Online.
54. D. P. Tittensor et al., Global patterns and predictors of
marine biodiversity across taxa. Nature 466, 10981101
(2010). doi: 10.1038/nature09329; pmid: 20668450
55. C. M. Roberts et al., Marine biodiversity hotspots and
conservation priorities for tropical reefs. Science 295,
12801284 (2002). doi: 10.1126/science.1067728;
pmid: 11847338
56. T. H. Ricketts et al., Pinpointing and preventing imminent
extinctions. Proc. Natl. Acad. Sci. U.S.A. 102, 1849718501
(2005). doi: 10.1073/pnas.0509060102; pmid: 16344485
57. M. Cardillo et al., The predictability of extinction: Biological
and external correlates of decline in mammals. Proc. Biol. Sci.
275, 14411448 (2008). doi: 10.1098/rspb.2008.0179;
pmid: 18367443
58. N. Myers, R. A. Mi ttermeier, C. G. Mittermeier, G. A . B. da Fonseca,
J. Kent, Biodiversity hotspots for conservation priorities.
Nature 403, 853858 (2000). doi: 10.1038/35002501;
pmid: 10706275
59. L. N. Joppa, P. Visconti, C. N. Jenkins, S. L. Pimm, Achieving
the convention on biological diversitys goals for plant
conservation. Science 341, 11001103 (2013). doi: 10.1126/
science.1241706; pmid: 24009391
60. S. L. Pimm, P. Raven, Biodiversity: Extinction by numbers.
Nature 403, 843845 (2000). doi: 10.1038/35002708;
pmid: 10706267
61. T. M. Brooks et al., Habitat loss and extinction in the hotspots
of biodiversity. Conserv. Biol. 16, 909923 (2002).
doi: 10.1046/j.1523-1739.2002.00530.x
62. S. L. Pimm, R. A. Askins, Forest losses predict bird
extinctions in eastern North America. Proc. Natl. Acad.
Sci. U.S.A. 92, 93439347 (1995). doi: 10.1073/
pnas.92.20.9343; pmid: 11607581
63. T. Brooks, A. Balmford, Atlantic forest extinctions. Nature
380, 115 (1996). doi: 10.1038/380115a0
64. T. M. Brooks, S. L. Pimm, N. J. Collar, Deforestation predicts
the number of threatened birds in insular Southeast Asia.
Conserv. Biol. 11, 382394 (1997). doi: 10.1046/j.1523-
65. S. L. Pimm, T. Brooks, Conservation: Forest fragments,
facts, and fallacies. Curr. Biol. 23, R1098R1101 (2013).
doi: 10.1016/j.cub.2013.10.024; pmid: 24355786
66. T. M. Brooks, Extinctions: Consider all species. Nature 474,
284284 (2011). doi: 10.1038/474284b; pmid: 21677730
67. I. Hanski, G. A. Zurita, M. I. Bellocq, J. Rybicki, Species-
fragmented area relationship. Proc. Natl. Acad. Sci. U.S.A.
110, 1271512720 (2013). doi: 10.1073/pnas.1311491110;
pmid: 23858440
68. L. Gibson et al., Near-complete extinction of native small
mammal fauna 25 years after forest fragmentation. Science
341, 15081510 (2013). doi: 10.1126/science.1240495;
pmid: 24072921
69. H. M. Pereira et al., Scenarios for global biodiversity in the
21st century. Science 330, 14961501 (2010). doi: 10.1126/
science.1196624; pmid: 20978282
70. C. D. Thomas et al., Extinction risk from climate change.
Nature 427,145148 (2004). doi: 10.1038/nature02121;
pmid: 14712274
71. W. Jetz, D. S. Wilcove, A. P. Dobson, Projected impacts of
climate and land-use change on the global diversity of birds.
PLOS Biol. 5, e157 (2007). doi: 10.1371/journal.pbio.0050157;
pmid: 17550306
72. C. H. Sekercioglu, S. H. Schneider, J. P. Fay, S. R. Loarie,
Climate change, elevational range shifts, and bird extinctions.
Conserv. Biol. 22,140150 (2008). doi: 10.1111/
j.1523-1739.2007.00852.x; pmid: 18254859
73. F. A. La Sorte, W. Jetz, Avian distributions under climate
change: Towards improved projections. J. Exp. Biol. 213,
862869 (2010). doi: 10.1242/jeb.038356; pmid: 20190111
74. W. W. Cheung et al., Projecting global marine biodiversity
impacts under climate change scenarios. Fish Fish. 10,
235251 (2009). doi: 10.1111/j.1467-2979.2008.00315.x
75. F. Ben Rais Lasram et al., The Mediterranean Sea as a
culdesacfor endemic fishes facing climate change.
Glob. Change Biol. 16, 32333245 (2010). doi: 10.1111/
76. L. M. Parker et al., Predicting the response of molluscs to the
impact of ocean acidification. Biology 2, 651692 (2013).
doi: 10.3390/biology2020651
77. S. L. Pimm, Biodiversity: Climate change or habitat loss
Which will kill more species? Curr. Biol. 18, R117R119
(2008). doi: 10.1016/j.cub.2007.11.055; pmid: 18269905
78. J. R. Malcolm, C. Liu, R. P. Neilson, L. Hansen, L. Hannah,
Global warming and extinctions of endemic species from
biodiversity hotspots. Conserv. Biol. 20, 538548 (2006).
doi: 10.1111/j.1523-1739.2006.00364.x; pmid: 16903114
79. D. P. van Vuuren, O. E. Sala, H. M. Pereira, The future of
vascular plant diversity under four global scenarios.
Ecol. Soc. 11,2542 (2006).
80. I. M. Maclean, R. J. Wilson, Recent ecological responses to
climate change support predictions of high extinction risk.
Proc. Natl. Acad. Sci. U.S.A. 108, 1233712342 (2011).
doi: 10.1073/pnas.1017352108; pmid: 21746924
81. M. Cardillo, G. M. Mace, J. L. Gittleman, A. Purvis, Latent
extinction risk and the future battlegrounds of mammal
conservation. Proc. Natl. Acad. Sci. U.S.A. 103, 41574161
(2006). doi: 10.1073/pnas.0510541103; pmid: 16537501
82. B. W. Brook et al., Predictive accuracy of population viability
analysis in conservation biology. Nature 404, 385387
(2000). doi: 10.1038/35006050; pmid: 10746724
83. B. Bomhard et al., Potential impacts of future land use and
climate change on the Red List status of the Proteaceae in
the Cape Floristic Region, South Africa. Glob. Change Biol. 11,
14521468 (2005). doi: 10.1111/j.1365-2486.2005.00997.x
84. K. J. Feeley et al., Upslope migration of Andean trees.
J. Biogeogr. 38, 783791 (2011). doi: 10.1111/
85. I.-C. Chen et al., Elevation increases in moth assemblages
over 42 years on a tropical mountain. Proc.Natl.Acad.Sci.U.S.A.
106,14791483 (2009). doi: 10.1073/pnas.0809320106;
pmid: 19164573
86. G. Forero-Medina, J. Terborgh, S. J. Socolar, S. L. Pimm,
Elevational ranges of birds on a tropical montane gradient
lag behind warming temperatures. PLOS ONE 6,
e28535 (2011). doi: 10.1371/journal.pone.0028535;
pmid: 22163309
87. M. B. Araújo, C. Rahbek, Ecology. How does climate
change affect biodiversity? Science 313, 13961397 (2006).
doi: 10.1126/science.1131758; pmid: 16959994
88. I. J. Harrison, M. L. Stiassny, in Extinctions in Near Time.
R. D. E. MacPhee, Ed. (Springer, New York 1999),
pp. 271331.
89. C. Nilsson, C. A. Reidy, M. Dynesius, C. Revenga,
Fragmentation and flow regulation of the worlds large river
systems. Science 308, 405408 (2005). doi: 10.1126/
science.1107887; pmid: 15831757
90. D. L. Strayer, D. Dudgeon, Freshwater biodiversity conservation:
Recent progress and future challenges. J. N. Am. Benthol. Soc.
29,344358 (2010). doi: 10.1899/08-171.1
91. J. A. Savidge, Extinction of an island forest avifauna by
an introduced snake. Ecology 68, 660668 (1987).
doi: 10.2307/1938471
92. A. Waldron et al., Targeting global conservation funding to
limit immediate biodiversity declines. Proc.Natl.Acad.Sci.U.S.A.
110,1214412148 (2013). doi : 10.1073/pnas.1221370110;
pmid: 23818619
93. IUCN and UNEP, The World Database on Protected Areas
(WDPA) (United Nations Environment Programme World
Conservation Monitoring Centre, Cambridge, UK, 2014).
94. Global Strategy for Plant Conservation,
SCIENCE 30 MAY 2014 VOL 344 ISSUE 6187 1246752-9
95. C. N. Jenkins, L. Joppa, Expansion of the global terrestrial
protected area system. Biol. Conserv. 142, 21662174
(2009). doi: 10.1016/j.biocon.2009.04.016
96. L. N. Joppa, A. Pfaff, High and far: Biases in the location of
protected areas. PLOS ONE 4, e8273 (2009). doi: 10.1371/
journal.pone.0008273; pmid: 20011603
97. A. S. L. Rodrigues et al., Effectiveness of the global protected
area network in representing species diversity. Nature 428,
640643 (2004). doi: 10.1038/nature02422; pmid: 15071592
98. L. Cantú-Salazar, C. D. L. Orme, P. C. Rasmussen,
T. M. Blackburn, K. J. Gaston, The performance of the global
protected area system in capturing vertebrate geographic
ranges. Biodivers. Conserv. 22, 10331047 (2013).
doi: 10.1007/s10531-013-0467-7
99. C. Rondinini, K. A. Wilson, L. Boitani, H. Grantham,
H. P. Possingham, Tradeoffs of different types of species
occurrence data for use in systematic conservation planning.
Ecol. Lett. 9, 11361145 (2006). doi: 10.1111/j.1461-
0248.2006.00970.x; pmid: 16972877
100. S. H. M. Butchart et al., Protecting important sites for
biodiversity contributes to meeting global conservation
targets. PLOS ONE 7, e32529 (2012). doi: 10.1371/journal.
pone.0032529; pmid: 22457717
101. B. C. Chessman, Do protected areas benefit freshwater
species? A broad-scale assessment for fish in Australia's
MurrayDarling Basin. J. Appl. Ecol. 50, 969976 (2013).
doi: 10.1111/1365-2664.12104
102. L. N. Joppa, S. R. Loarie, S. L. Pimm, On the protection of
protected areas.Proc. Natl. Acad. Sci. U.S.A. 105,
66736678 (2008). doi: 10.1073/pnas.0802471105;
pmid: 18451028
103. J. M. Adeney, N. L. Christensen, S. L. Pimm, Reserves
protect against deforestation fires in the Amazon. PLOS ONE
4, e5014 (2009). doi: 10.1371/journal.pone.0005014;
pmid: 19352423
104. L. N. Joppa, S. R. Loarie, S. L. Pimm, On population growth
near protected areas. PLOS ONE 4, e4279 (2009).
doi: 10.1371/journal.pone.0004279; pmid: 19169358
105. D. S. Wilkie, E. L. Bennett, C. A. Peres, A. A. Cunningham,
The empty forest revisited. Ann. N. Y. Acad. Sci. 1223,
120128 (2011). doi: 10.1111/j.1749-6632.2010.05908.x;
pmid: 21449969
106. M. Spalding, I. Meliane, A. Milam, C. Fitzgerald, L. Hale,
Protecting marine spaces: Global targets and changing
approaches. Ocean Yearb. 27, 213248 (2013). doi: 10.1163/
107. MPAtlas,
108. C. Mora et al., Coral reefs and the global network of
Marine Protected Areas. Science 312, 17501751 (2006).
doi: 10.1126/science.1125295; pmid: 16794065
109. R. J. Toonen et al., One size does not fit all: The emerging
frontier in large-scale marine conservation. Mar. Pollut. Bull.
77,710 (2013). doi: 10.1016/
j.marpolbul.2013.10.039; pmid: 24246654
110. G. J. Edgar et al., Global conservation outcomes depend on
marine protected areas with five key features. Nature 506,
216220 (2014). doi: 10.1038/nature13022; pmid: 24499817
111. L. N. Joppa, D. L. Roberts, N. Myers, S. L. Pimm,
Biodiversity hotspots house most undiscovered plant
species. Proc. Natl. Acad. Sci. U.S.A. 108, 1317113176 (2011).
doi: 10.1073/pnas.1109389108; pmid: 21730155
112. A. Pino-Del-Carpio, A. H. Ariño, A. Villarroya, J. Puig,
R. Miranda, The biodiversity data knowledge gap: Assessing
information loss in the management of Biosphere Reserves.
Biol. Conserv. (2013). doi: 10.1016/j.biocon.2013.11.020
113. R. Abell et al., Concordance of freshwater and terrestrial
biodiversity. Conserv. Lett. 4, 127136 (2011). doi: 10.1111/
114. N. Brummitt, S. P. Bachman, J. Moat, Applications of the
IUCN Red List: Towards a global barometer for plant
diversity. Endanger. Species Res. 6, 127135 (2008).
doi: 10.3354/esr00135
115. S. N. Stuart, E. O. Wilson, J. A. McNeely, R. A. Mittermeier,
J. P. Rodríguez, The barometer of life. Science 328, 177
(2010). doi: 10.1126/science.1188606; pmid: 20378803
116. Global Biodiversity Information Facility (2014);
117. The Ocean Biogeographic Information System,
Intergovernmental Oceanographic Commission of UNESCO
118. Tree of Life (2014);
119. TimeTree (2014);
120. World Register of Marine Species (2014); http://www.
121. Fishbase (2014);
122. P. D. Hebert, A. Cywinska, S. L. Ball, J. R. deWaard, Biological
identifications through DNA barcodes. Proc. Biol. Sci. 270,
313321 (2003). doi: 10.1098/rspb.2002.2218; pmid:
123. S. Ratnasingham, P. D. Hebert, A DNA-based registry for all
animal species: The barcode index number (BIN) system.
PLOS ONE 8, e66213 (2013). doi: 10.1371/journal.
pone.0066213; pmid: 23861743
124. P. D. N. Hebert, E. H. Penton, J. M. Burns, D. H. Janzen,
W. Hallwachs, Ten species in one: DNA barcoding reveals
cryptic species in the neotropical skipper butterfly Astraptes
fulgerator.Proc. Natl. Acad. Sci. U.S.A. 101, 1481214817
(2004). doi: 10.1073/pnas.0406166101; pmid: 15465915
125. A. Chao, R. L. Chazdon, R. K. Colwell, T. J. Shen, A new
statistical approach for assessing similarity of species
composition with incidence and abundance data. Ecol. Lett.
8,148159 (2005). doi: 10.1111/j.1461-0248.2004.00707.x
126. TROPICOS (2014);
127. eBird (2014);
128. S. Gaiji et al., Content assessment of the primary biodiversity
data published through GBIF network: Status, challenges and
potentials. Biodiversity Informatics 8,94172 (2013).
129. iNaturalist (2014);
130. Reef Life Survey (2014);
131. J. O. Sexton et al., Global, 30-m resolution continuous
fields of tree cover: Landsat-based rescaling of MODIS
vegetation continuous fields with lidar-based estimates of
error. Int. J. Digit. Earth 6, 427448 (2013). doi: 10.1080/
132. J. R. Townshend et al., Global characterization and
monitoring of forest cover using Landsat data: Opportunities
and challenges. Int. J. Digit. Earth 5, 373397 (2012). doi:
133. J. O. Sexton, D. L. Urban, M. J. Donohue, C. Song, Long-term
land cover dynamics by multi-temporal classification
across the Landsat-5 record. Remote Sens. Environ. 128,
246258 (2013). doi: 10.1016/j.rse.2012.10.010
134. G. Harris, S. L. Pimm, Range size and extinction risk in
forest birds. Conserv. Biol. 22, 163171 (2008). doi: 10.1111/
j.1523-1739.2007.00798.x; pmid: 18254861
We thank A. Ariño, J. A. Drake, M. A. Fisher, S. Loarie, E. Norse, and
P. R. Stephens for comments. The original data for this paper
are in public archives from BirdLife International (37), IUCN (13),
WCSPF (43), and the World Conservation Monitoring Centre (94).
We thank those responsible for access to them and especially
the many professionals and amateurs who collected them.
NASAs Making Earth System Data Records for Use in Research
Environments (MEaSUREs) (NNH06ZDA001N) and Land Cover and
Land Use Change (NNH07ZDA001N-LCLUC) programs provided
forest cover data. We thank the World Checklist of Selected
Plant Families. The Brazilian agency CAPES, through the Ciência
Sem Fronteiras program, supports C.N.J. M. Thieme, P. Petry,
and C. Revenga co-led the synthesis of the freshwater fish data.
Additional biodiversity maps are at
Materials and Methods
Figs. S1 and S2
References (135,136)
1246752-10 30 MAY 2014 VOL 344 ISSUE 6187 SCIENCE
... M easuring ongoing and anticipating potential threats is vital for preventing damage to the natural world [1][2][3][4][5][6][7][8] , which entails detailed knowledge about the current state of biodiversity. A central data resource enabling a multitude of overarching analyses in conservation and sustainability science 9 is the International Union for the Conservation of Nature (IUCN)'s Red List of Threatened Species (hereafter: Red List). ...
... Here, numerous DD reef forming corals, sharks, rays, chimaeras, and marine fish species seem to be particularly relevant for a timely and expert-based threat assessment (Supplementary Figs. 3,6). In contrast, including DD species did not change or even lowered the average PE score in large parts of international seas (Fig. 3a). ...
Full-text available
The IUCN Red List of Threatened Species is essential for practical and theoretical efforts to protect biodiversity. However, species classified as “Data Deficient” (DD) regularly mislead practitioners due to their uncertain extinction risk. Here we present machine learning-derived probabilities of being threatened by extinction for 7699 DD species, comprising 17% of the entire IUCN spatial datasets. Our predictions suggest that DD species as a group may in fact be more threatened than data-sufficient species. We found that 85% of DD amphibians are likely to be threatened by extinction, as well as more than half of DD species in many other taxonomic groups, such as mammals and reptiles. Consequently, our predictions indicate that, amongst others, the conservation relevance of biodiversity hotspots in South America may be boosted by up to 20% if DD species were acknowledged. The predicted probabilities for DD species are highly variable across taxa and regions, implying current Red List-derived indices and priorities may be biased.
... Amphibian populations are in decline worldwide, with nearly 40% of known species threatened with extinction (Pimm et al., 2014;Stuart et al., 2004). Drivers of decline vary across species and populations, but can include land use change, climate change, and disease (Grant et al., 2020). ...
Full-text available
Aim Climate change is an increasingly important driver of biodiversity loss. The ectothermic nature of amphibians may make them particularly sensitive to changes in temperature and precipitation regimes, adding to declines from other threats. While active season environmental conditions can influence growth and survival, effects of variation in winter conditions on population dynamics are less well‐studied. Given that extreme winter temperatures can influence amphibian survival and fitness, we expected that increased winter severity—as measured by variability in winter temperatures and snow cover—would be associated with decreased occupancy, and that populations that experience more severe winters would have the largest sensitivities and show the greatest declines. Location Eastern United States. Time period 2001–2015. Major taxa studied Anurans. Methods We used large‐scale citizen science data from the eastern half of the United States, a diverse biogeographic and climatic region, to assess how variation in winter severity influenced occupancy dynamics (i.e. presence or absence of species across sites and years) of 11 spring and summer breeding anuran species. Results Most species had increased occupancy in years with greater than average snow cover and warmer than average mean winter temperatures. Surprisingly, climatic conditions in winter affected occupancy dynamics of species with varying life history characteristics, including both spring and summer breeding species, those that overwinter under the soil, and those that overwinter in ponds and stream beds. For two wide‐ranging species (Lithobates catesbeianus and Lithobates clamitans), colder winter temperatures reduced occupancy more at northern latitudes, while the association between days of snow cover and latitude was equivocal. Main conclusions As the climate continues to change, expected reductions in snowpack may reduce occupancy of already declining anuran populations, while milder winters may improve overwinter survival for some species. The contradictory impacts of temperature and snow cover illustrate the importance of considering multi‐dimensional impacts of climate change on anuran populations.
... Global climate change is a major threat to marine biodiversity (Hillebrand et al., 2012). Ocean warming triggers the redistribution of species and is of especially high risk to ecologically important endemic species with restricted distributions and relatively narrow thermal tolerance ranges (Pimm et al., 2014;Da Silva et al., 2019;Alfonso et al., 2021). Species with small distribution ranges face three possible future scenarios: (1) shifting their distribution to an optimal or sustainable thermal habitat, (2) adapting to the temperature change, or (3) undergoing decline and possibly extinction (Sunday et al., 2015). ...
Full-text available
Ocean warming is a major threat to marine ecosystems, especially to species with a narrow thermal niche width and narrow biogeographic distribution, like some habitat-forming seaweeds. Declines of marine forests have been reported for several canopy-forming species in temperate regions, including the Mediterranean Sea, where they are dominated by species from the order Fucales, but most of the information on their ecology and status comes from the western basin. Here, we studied the thermal vulnerability and metabolic functioning of the endemic Gongolaria rayssiae located in fast-warming waters of the Israeli Mediterranean coast. We followed seasonal changes in phenology and ecology of G. rayssiae and its associated community during 2018-2020. Its highest biomass, density and thallus length were documented in spring-early summer (March-mid June). When seawater temperature exceeded 25°C, it shed its branches until February, when re-growth normally occurred. The thermal performance curve of G. rayssiae was determined by exposing it to 11 temperature levels in the range 15-35°C. The thermal optimum temperature for gross oxygen production, determined from the fitted curve, was 24.5°C. This relatively low thermal optimum suggests marked sensitivity to warming and supports the notion that G. rayssiae is a temperate relict species in the area. Additionally, we conducted seasonal ex-situ incubations during daytime and nighttime and recorded the highest primary productivity in spring, when it is at its peak of growth. In this season, its net inorganic carbon uptake was 42 ± 11 µmol C g dw-1 h-1 ( ± SD), while in its branchless form during late summer, it decreased six-fold. Due to the fast ocean warming conditions of the area, we hypothesize that the growth season of the species will shrink, and the species may eventually disappear. Finally, when exposed to high temperatures in natural and manipulative conditions, G. rayssiae exhibited a dramatic decline in its carbon sequestration rates with important implication for the carbon budget of the reef. This study highlights the importance of establishing a species phenology and environmental sensitivity (and especially that of endemic ones) in rapidly warming ecosystems, to estimate its potential fate due to climate change.
... The Amazonian rainforest is the largest and most diverse tropical rainforest in the world (Jenkins et al. 2013;Pimm et al. 2014). Although generally recognized as a unity, the Amazonian rainforest is included in a mosaic of a broad variety of ecosystems and ecoregions ranging from dense rainforest to savannahs and lowland swamps ( Fig. 2; Olson et al. 2001). ...
Full-text available
Conservation genetics provides wildlife managers powerful tools to assist conservation planning, being recognized as an important biodiversity component. Nevertheless, communication between wildlife conservation actors is still not effective. Furthermore, wildlife conservation funds are often allocated to conservation actions incompatible with thorough long-term genetic research. In the Neotropics, the political organization of the territory, the complex socio-economic context, and the environmental heterogeneity impose additional challenges to the use of genetics for wildlife conservation. Here we present an assessment of the state-of-the-art on the conservation genetics of the giant anteater, as a study case. We use this species to discuss key wildlife threats and challenges along nine major Neotropical biomes. We review the main scientific research on the species, comprising and analyzing genetic data, and focusing on each biome and its region-specific threats. Our genetic meta-analysis reveals low levels of genetic diversity for the species, signs of population differentiation and dissimilar demographic trends per biome. Large-scale investigations are needed to disclose between hypotheses of panmixia, population structure and local adaptation, and to better assess the species demography. The limited information available for a known Vulnerable species perfectly illustrates the need for greater and internationally concerted investment in genetic/genomic research in the Neotropics. Finally, we describe the main wildlife conservation challenges per biome assessed, and present open research questions to which genetics could be of paramount importance.
... Increasingly more species are becoming threatened by extinction worldwide [1]. Scientific research may help develop effective conservation measures by providing accurate knowledge about species' biology and ecology and identifying main threats to biodiversity. ...
Full-text available
There are differences regarding distribution, conservation status and protection accordingto national and European laws and directives between the four dormouse species (Gliridae) native to Central Europe. We question the coherence between scientific knowledge and conservation statusof dormice in Europe and hypothesize that the species included in the Habitats Directive have beenthe subject of considerable research, while those not included have been neglected, despite havingan unfavourable conservation status. We did a review of the research presented at the InternationalConferences on Dormice from 1990–2017 and published in the scientific literature since 1950 to seefor which species the most research was done and whether the Habitats Directive had an impact.The number of presentations increased over time for the Hazel (Muscardinus avellanarius, N = 200)and the Edible dormouse (Glis glis, N = 150), while those on the Garden dormouse (Eliomys quercinus,N = 46) decreased until 2014 with an apparent increase only in 2017; the Forest dormouse (Dryomysnitedula, N = 67) does not show any trends. The number of published articles increased for all speciesexcept for the Garden dormouse. This focus does not adequately address the current threats of thespecies. The results can serve as a guide for the re-evaluation of future research priorities and con-servation strategies as well as the implementation of new monitoring projects and ecological studies.
... Already 80 % of terrestrial land mass is influenced by human activity (Sanderson et al., 2002) and 44 % of plant and animal species have undergone local extinctions (Román-Palacios and Wiens, 2020) including terrestrial vertebrates (Dirzo et al., 2014;Ceballos, Ehrlich and Raven, 2020) and insects (Hallmann et al., 2017). Current rates of extinction are hypothesized to be 1000 times higher than expected background rates (Pimm et al., 2014) leading many researchers to believe we are entering the sixth mass extinction (Barnosky et al., 2011;Ceballos et al., 2015). ...
Humans are changing the Earth. What is unknown is how biotic communities and ecosystems will react to this change on both short and long timescales. The fossil record can provide us with a means of investigating ecosystem responses to long-term climatic fluctuations which can act as baselines for future anthropogenic induced change. How we utilize the fossil record is therefore of critical Importance. The high spatial and temporal resolution of the planktonic foraminifera fossil record provides an ideal system to investigate ecosystem responses to climatic fluctuations at multiple scales and levels. The primary objective of this thesis is to measure and understand the relationship between planktonic foraminifera and their environment, to enable a more biologically informative assessment of the fossil record. I created a diversity record of planktonic foraminifera through the Middle Eocene Climatic Optimum comprising of 22,800 individuals classified to three taxonomic levels and investigated the responses of these assemblages using effective diversity: a novel approach for Palaeogene and deep-time systems (Chapter 2). The results from this study show that analytical size fraction choice is a key determinant of diversity signals in deep-time and furthermore it is small species that maintain ecological function during transient climatic events. I then investigated a key component of these assemblages, Subbotina, using individual morphological and geochemical measurements to link their traits to the environment and assess their persistence through the climatic fluctuations of the Middle Eocene (Chapter 3). I found that longevity of Subbotina is a result of morphological and geochemical trait plasticity resulting in a wide ecological niche which in turn allowed for continued persistence and dominance through the Middle Eocene whilst other groups faltered. Next, I explored the relationship between geochemistry and morphology within a relatively recent system to understand the relationship between geochemistry, size, and genetically identified species (Chapter 4). The results showed that fine resolution geochemical analyses can be used to unpick the drivers of intraindividual variability. However, more work is needed to understand the drivers of geochemistry at the individual level which is possible using the methods I advocate and explore in this thesis. Together, these discoveries expand our understanding of how planktonic foraminifera communities are linked to their environment and demonstrate that by using the appropriate analytical approaches we can investigate this relationship in a more biologically meaningful way. Future studies on planktonic foraminifera will require the application of traitbased approaches through the integration of geochemistry, morphology, and diversity measurements to further our understanding of how past communities responded to climatic perturbations with an aim to inform our understanding of biotic responses to current and future anthropogenic change
Arthropods of kingdom animalia are bountiful on earth and copious of biodiversity is yet to be discovered. Traditional taxonomy identifies the species based on morphological, anatomical, and ecological characters, which is a tedious task with a lot of limitations for describing the species. DNA barcoding has become an alternative and a quick tool to delineate the species and it has been practiced by many researchers across the world. DNA barcoding refers to sequencing of short fragment of mitochondrial cytochrome c oxidase subunit I (COX I) to identify species including the unknown one . Including systematics, it has role in biological control, bio-surveillance, quality control in food industry, conservation of endangered species, and integrated pest management. However, few researchers have criticized this method due to the presence of nuclear mitochondrial DNA (NUMTs) and mitochondrial DNA introgression between closely related species facilitated by Wolbachia which leads to overestimation of the species.
In this work, we update and increase knowledge on the severity and extent of threats affecting 57 populations of 46 amphibian species from Chile and Argentina in southern South America. We analyzed the intrinsic conservation problems that directly impact these populations. We shared a questionnaire among specialists on threats affecting target amphibian populations with information on i) range, ii) historical occurrence and abundance, iii) population trends, iv) local extinctions, v) threats, and vi) ongoing and necessary conservation/research. We assessed association patterns between reported threats and population trends using multiple correspondence analysis. Since 2010, 25 of 57 populations have declined, while 16 experienced local extinctions. These populations were affected by 81% of the threat categories analyzed, with those related to agricultural activities and/or habitat modifications being the most frequently reported. Invasive species, emerging diseases, and activities related to grazing, ranching, or farming were the threats most associated with population declines. Low connectivity was the most frequent intrinsic conservation problem affecting 68% of the target populations, followed by low population numbers, affecting 60%. Ongoing monitoring activity was conducted in 32 (56%) populations and was the most frequent research activity. Threat mitigation was reported in 27 (47%) populations and was the most frequent ongoing management activity. We found that habitat management is ongoing in 5 (9%) populations. At least 44% of the amphibian populations surveyed in Chile and Argentina are declining. More information related to the effect of management actions to restore habitats, recover populations, and eliminate threats such as invasive species is urgently needed to reverse the conservation crisis facing amphibians in this Neotropical region.
Full-text available
The Turkestan lynx (Lynx lynx isabellina Blyth, 1847) is a rare and understudied subspecies of the Eurasian lynx occupying the mountains of Central and South Asia. This elusive felid’s northwestern range includes the Tien Shan and Zhetisu Alatau mountains in the border region of Kazakhstan, China, Kyrgyzstan, and Uzbekistan. As the first step to conserve this vulnerable carnivore, we have conducted the first full-scale research from 2013 until 2022 on its distribution in this region. Using 132 environmental predictors of 359 lynx sightings, we have created species habitat distribution models across the lynx’s northwestern range using machine learning approaches (Maximum Entropy—MaxEnt). Additionally, we created species distribution forecasts based on seven bio-climatic environmental predictors with each three different future global climate model scenarios. To validate these forecasts, we have calculated the changes in the lynx distribution range for the year 2100, making the first species distribution forecast for the Turkestan lynx in the area. Additionally, it provides insight into the possible effects of global climate change on this lynx population. Based on these distribution models, the lynx population in the Northern and Western Tien Shan and Zhetisu Alatau plays a significant role in maintaining the stability of the whole subspecies in its northwestern and global range, while the distribution forecast shows that most lynx distribution ranges will reduce in all future climate scenarios, and we might face the Turkestan lynx’s significant distribution range decline under the ongoing and advancing climate change conditions. For a future (year 2100) warming scenario of 3 deg. C (GCM IPSL), we observe a decrease of 35% in Kazakhstan, 40% in Kyrgyzstan, and 30% in China as the three countries with the highest current predicted distribution range. For a milder temperature increase of 1.5–2 deg. C. (GCM MRI), we observe an increase of 17% Kazakhstan, decrease of 10% in Kyrgyzstan, and 57% in China. For a cooling scenario of approx. 1–1.5 deg. C (GCM MIROC), we observe a decrease of 14% Kazakhstan, increase of 11% in Kyrgyzstan, and a decrease of 13% in China. These modeled declines indicate the necessity to create new and expand the existing protected areas and establish ecological corridors between the countries in Central and South Asia. View Full-Text
Full-text available
The rapid expansion of human activities threatens ocean-wide biodiversity. Numerous marine animal populations have declined, yet it remains unclear whether these trends are symptomatic of a chronic accumulation of global marine extinction risk. We present the first systematic analysis of threat for a globally distributed lineage of 1,041 chondrichthyan fishes-sharks, rays, and chimaeras. We estimate that one-quarter are threatened according to IUCN Red List criteria due to overfishing (targeted and incidental). Large-bodied, shallow-water species are at greatest risk and five out of the seven most threatened families are rays. Overall chondrichthyan extinction risk is substantially higher than for most other vertebrates, and only one-third of species are considered safe. Population depletion has occurred throughout the world's ice-free waters, but is particularly prevalent in the Indo-Pacific Biodiversity Triangle and Mediterranean Sea. Improved management of fisheries and trade is urgently needed to avoid extinctions and promote population recovery.